From 9d52347dc67d3dc28a7bd23084911113287482d5 Mon Sep 17 00:00:00 2001 From: Toon Hasenack Date: Thu, 4 Apr 2024 15:01:42 +0200 Subject: [PATCH 01/98] PHENIX implementation, eta still needs to be done --- .../PHENIX_1JET_200GEV_ALL/data.yaml | 9 ++ .../PHENIX_1JET_200GEV_ALL/filter.py | 87 +++++++++++++++++ .../PHENIX_1JET_200GEV_ALL/kinematics.yaml | 97 +++++++++++++++++++ .../PHENIX_1JET_200GEV_ALL/metadata.yaml | 52 ++++++++++ .../rawdata/Table_18.yaml | 48 +++++++++ .../PHENIX_1JET_200GEV_ALL/uncertainties.yaml | 14 +++ 6 files changed, 307 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/rawdata/Table_18.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/data.yaml new file mode 100644 index 0000000000..a91ae42005 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/data.yaml @@ -0,0 +1,9 @@ +data_central: + - -0.0007 + - 0.0039 + - -0.0014 + - -0.0005 + - 0.0058 + - 0.0034 + - 0.0077 + - -0.0181 diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py new file mode 100644 index 0000000000..995c716ab9 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py @@ -0,0 +1,87 @@ +import glob + +import pandas as pd +import yaml + + +def read_data(fnames): + df = pd.DataFrame() + for fname in fnames: + with open(fname, "r") as file: + data = yaml.safe_load(file) + + pTbsub = data["independent_variables"][0]["values"] + pTsub = data["dependent_variables"][0]["values"] + ALLsub = data["dependent_variables"][1]["values"] + + for i in range(len(ALLsub)): + df = pd.concat( + [ + df, + pd.DataFrame( + { + "pT": [pTsub[i]["value"]], + "pTmin": [pTbsub[i]["low"]], + "pTmax": [pTbsub[i]["high"]], + "eta": [0.0], + "sqrts": [200], + "ALL": [ALLsub[i]["value"]], + "stat": [ALLsub[i]["errors"][0]["symerror"]], + } + ), + ], + ignore_index=True, + ) + + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["ALL"])): + data_central.append(float(df.loc[i, "ALL"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["ALL"])): + kin_value = { + "pT": {"min": float(df.loc[i, "pTmin"]), "mid": float(df.loc[i, "pT"]), "max": float(df.loc[i, "pTmax"])}, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": {"min": None, "mid": float(df.loc[i, "eta"]), "max": None}, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for idx, i in enumerate(range(len(df))): + e = { + "stat": float(df.loc[i, "stat"]), + } + error.append(e) + + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # TODO: Need to generate `observable` cards and corresponding + # pineappl grids and FK tables as the orders have changed!!!! + fnames = glob.glob("rawdata/*.yaml") + nnames = sorted([i for i in fnames]) + df = read_data(nnames) + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/kinematics.yaml new file mode 100644 index 0000000000..45e1315eb4 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/kinematics.yaml @@ -0,0 +1,97 @@ +bins: +- pT: + min: 2.0 + mid: 2.4 + max: 3.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null +- pT: + min: 3.0 + mid: 3.4 + max: 4.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null +- pT: + min: 4.0 + mid: 4.4 + max: 5.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null +- pT: + min: 5.0 + mid: 5.4 + max: 6.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null +- pT: + min: 6.0 + mid: 6.4 + max: 7.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null +- pT: + min: 7.0 + mid: 7.4 + max: 8.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null +- pT: + min: 8.0 + mid: 8.8 + max: 10.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null +- pT: + min: 10.0 + mid: 10.8 + max: 12.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: null + mid: 0.0 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml new file mode 100644 index 0000000000..bace4835dc --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml @@ -0,0 +1,52 @@ +setname: "PHENIX_1JET_200GEV_ALL" + +nnpdf_metadata: + experiment: "PHENIX" + nnpdf31_process: "JET_POL" + +iNSPIRE: + url: "https://inspirehep.net/literature/870912" +hepdata: + url: "https://www.hepdata.net/record/ins870912" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL w.r.t. pT", + label: '$\frac{d^2\sigma}{dq^{2}d\langle pT \rangle}$', + units: "$pb/GeV^3$", + } + observable_name: ALL + process_type: JET_POL + ndata: 8 + tables: [18] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { description: "COM energy", label: '$\sqrt{s}$', units: "$GeV$" } + eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, eta] + plotting: + kinematics_override: identity + dataset_label: "$A_{LL}$" + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - PHENIX_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/rawdata/Table_18.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/rawdata/Table_18.yaml new file mode 100644 index 0000000000..5dcc2a6066 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/rawdata/Table_18.yaml @@ -0,0 +1,48 @@ +independent_variables: +- header: {name: '$p^{reco}_T$ Bins (GeV/$c$)'} + values: + - {low: 2, high: 3} + - {low: 3, high: 4} + - {low: 4, high: 5} + - {low: 5, high: 6} + - {low: 6, high: 7} + - {low: 7, high: 8} + - {low: 8, high: 10} + - {low: 10, high: 12} +dependent_variables: +- header: {name: '$$ (GeV/$c$)'} + values: + - value: 2.4 + - value: 3.4 + - value: 4.4 + - value: 5.4 + - value: 6.4 + - value: 7.4 + - value: 8.8 + - value: 10.8 +- header: {name: 'Jet $A_{LL}$'} + values: + - value: -0.0007 + errors: + - {symerror: 7.7e-5, label: 'stat.'} + - value: 0.0039 + errors: + - {symerror: 8.2e-4, label: 'stat.'} + - value: -0.0014 + errors: + - {symerror: 5.2e-4, label: 'stat.'} + - value: -0.0005 + errors: + - {symerror: 3.0e-4, label: 'stat.'} + - value: 0.0058 + errors: + - {symerror: 5.2e-3, label: 'stat.'} + - value: 0.0034 + errors: + - {symerror: 4.5e-3, label: 'stat.'} + - value: 0.0077 + errors: + - {symerror: 1.2e-2, label: 'stat.'} + - value: -0.0181 + errors: + - {symerror: 5.1e-2, label: 'stat.'} diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/uncertainties.yaml new file mode 100644 index 0000000000..6b799cce3d --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/uncertainties.yaml @@ -0,0 +1,14 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR +bins: +- stat: 7.7e-05 +- stat: 0.00082 +- stat: 0.00052 +- stat: 0.0003 +- stat: 0.0052 +- stat: 0.0045 +- stat: 0.012 +- stat: 0.051 From 90f5342950cffd66d2fec14425e3691df5b5436d Mon Sep 17 00:00:00 2001 From: Toon Hasenack Date: Thu, 4 Apr 2024 17:02:12 +0200 Subject: [PATCH 02/98] pre-commit change --- .../new_commondata/PHENIX_1JET_200GEV_ALL/filter.py | 12 +++++++----- 1 file changed, 7 insertions(+), 5 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py index 995c716ab9..38a37d0e0a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py @@ -49,7 +49,11 @@ def write_data(df): kin = [] for i in range(len(df["ALL"])): kin_value = { - "pT": {"min": float(df.loc[i, "pTmin"]), "mid": float(df.loc[i, "pT"]), "max": float(df.loc[i, "pTmax"])}, + "pT": { + "min": float(df.loc[i, "pTmin"]), + "mid": float(df.loc[i, "pT"]), + "max": float(df.loc[i, "pTmax"]), + }, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, "eta": {"min": None, "mid": float(df.loc[i, "eta"]), "max": None}, } @@ -63,13 +67,11 @@ def write_data(df): # Write unc file error = [] for idx, i in enumerate(range(len(df))): - e = { - "stat": float(df.loc[i, "stat"]), - } + e = {"stat": float(df.loc[i, "stat"])} error.append(e) error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"} } uncertainties_yaml = {"definitions": error_definition, "bins": error} From 577512c0c392b682d420fe70c575c26827503e8e Mon Sep 17 00:00:00 2001 From: Toon Hasenack Date: Fri, 12 Apr 2024 20:32:15 +0200 Subject: [PATCH 03/98] implemented changes for PHENIX --- .../data.yaml | 0 .../filter.py | 10 ++++++++-- .../kinematics.yaml | 0 .../metadata.yaml | 17 ++++++++--------- .../rawdata/Table_18.yaml | 0 .../uncertainties.yaml | 0 6 files changed, 16 insertions(+), 11 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/{PHENIX_1JET_200GEV_ALL => PHENIX_1JET_200GEV}/data.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{PHENIX_1JET_200GEV_ALL => PHENIX_1JET_200GEV}/filter.py (89%) rename nnpdf_data/nnpdf_data/new_commondata/{PHENIX_1JET_200GEV_ALL => PHENIX_1JET_200GEV}/kinematics.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{PHENIX_1JET_200GEV_ALL => PHENIX_1JET_200GEV}/metadata.yaml (76%) rename nnpdf_data/nnpdf_data/new_commondata/{PHENIX_1JET_200GEV_ALL => PHENIX_1JET_200GEV}/rawdata/Table_18.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{PHENIX_1JET_200GEV_ALL => PHENIX_1JET_200GEV}/uncertainties.yaml (100%) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py similarity index 89% rename from nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py rename to nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py index 38a37d0e0a..4542947712 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py @@ -24,6 +24,8 @@ def read_data(fnames): "pTmin": [pTbsub[i]["low"]], "pTmax": [pTbsub[i]["high"]], "eta": [0.0], + "eta_min": [-0.35], + "eta_max": [0.35], "sqrts": [200], "ALL": [ALLsub[i]["value"]], "stat": [ALLsub[i]["errors"][0]["symerror"]], @@ -55,7 +57,11 @@ def write_data(df): "max": float(df.loc[i, "pTmax"]), }, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, - "eta": {"min": None, "mid": float(df.loc[i, "eta"]), "max": None}, + "eta": { + "min": float(df.loc[i, "eta_min"]), + "mid": float(df.loc[i, "eta"]), + "max": float(df.loc[i, "eta_max"]), + }, } kin.append(kin_value) @@ -66,7 +72,7 @@ def write_data(df): # Write unc file error = [] - for idx, i in enumerate(range(len(df))): + for i in range(len(df)): e = {"stat": float(df.loc[i, "stat"])} error.append(e) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml similarity index 76% rename from nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml rename to nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml index bace4835dc..d608a07978 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml @@ -1,8 +1,8 @@ -setname: "PHENIX_1JET_200GEV_ALL" +setname: "PHENIX_1JET_200GEV" nnpdf_metadata: experiment: "PHENIX" - nnpdf31_process: "JET_POL" + nnpdf31_process: "JETS" iNSPIRE: url: "https://inspirehep.net/literature/870912" @@ -14,12 +14,7 @@ version: 1 version_comment: "Initial implementation" implemented_observables: - - observable: - { - description: "ALL w.r.t. pT", - label: '$\frac{d^2\sigma}{dq^{2}d\langle pT \rangle}$', - units: "$pb/GeV^3$", - } + - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } observable_name: ALL process_type: JET_POL ndata: 8 @@ -33,7 +28,11 @@ implemented_observables: units: "$GeV$", } sqrts: - { description: "COM energy", label: '$\sqrt{s}$', units: "$GeV$" } + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } eta: { description: "pseudorapidity", label: '$\eta$', units: "" } file: kinematics.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/rawdata/Table_18.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table_18.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/rawdata/Table_18.yaml rename to nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table_18.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml From 49a3755e50ff5f866a30f6451a14d29ff0d3729d Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Mon, 15 Apr 2024 15:12:43 +0200 Subject: [PATCH 04/98] STAR2012 and STAR2015 addition --- .../STAR2012_1JET_200GEV/data.yaml | 20 + .../STAR2012_1JET_200GEV/filter.py | 115 ++++ .../STAR2012_1JET_200GEV/kinematics.yaml | 229 +++++++ .../STAR2012_1JET_200GEV/metadata.yaml | 52 ++ .../rawdata/Table_14.yaml | 69 ++ .../rawdata/Table_15.yaml | 63 ++ .../STAR2012_1JET_200GEV/uncertainties.yaml | 48 ++ .../STAR2015_1JET_200GEV/data.yaml | 23 + .../STAR2015_1JET_200GEV/filter.py | 123 ++++ .../STAR2015_1JET_200GEV/kinematics.yaml | 265 ++++++++ .../STAR2015_1JET_200GEV/metadata.yaml | 52 ++ .../rawdata/Table_3_ALL.csv | 12 + .../rawdata/Table_3_pT.csv | 12 + .../rawdata/Table_4_ALL.csv | 12 + .../rawdata/Table_4_pT.csv | 12 + .../STAR2015_1JET_200GEV/rawdata/Table_5.csv | 602 ++++++++++++++++++ .../STAR2015_1JET_200GEV/uncertainties.yaml | 54 ++ 17 files changed, 1763 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_14.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_15.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_ALL.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_pT.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_ALL.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_pT.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_5.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/data.yaml new file mode 100644 index 0000000000..7120f27208 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/data.yaml @@ -0,0 +1,20 @@ +data_central: +- 0.0053 +- -0.0027999999999999995 +- 0.0021999999999999997 +- 0.015 +- -0.0058000000000000005 +- 0.0036000000000000003 +- -0.013800000000000002 +- -0.0522 +- 0.0569 +- 0.148 +- 0.0033 +- 0.00365 +- 0.01025 +- 0.00135 +- 0.00925 +- 0.02595 +- 0.026850000000000002 +- 0.02375 +- 0.0139 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/filter.py new file mode 100644 index 0000000000..5b7182fb80 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/filter.py @@ -0,0 +1,115 @@ +import glob +import sys + +import pandas as pd +import yaml + +sys.path.append('../') +from ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors + + +def read_data(fnames): + df = pd.DataFrame() + for fname in fnames: + with open(fname, "r") as file: + data = yaml.safe_load(file) + if "14" in fname: + eta_min = 0.2 + eta_max = 0.8 + + elif "15" in fname: + eta_min = -0.7 + eta_max = 0.9 + + else: + print("ERROR: Unknown table number detected! Check input files.") + + pTsub = data["independent_variables"][0]["values"] + ALLsub = data["dependent_variables"][0]["values"] + + for i in range(len(ALLsub)): + df = pd.concat( + [ + df, + pd.DataFrame( + { + "pT": [pTsub[i]["value"]], + "pTmin": [pTsub[i]["low"]], + "pTmax": [pTsub[i]["high"]], + "eta": [(eta_min + eta_max) / 2], + "eta_min": [eta_min], + "eta_max": [eta_max], + "sqrts": [200], + "ALL": [ALLsub[i]["value"] * 1e-3], + "stat": [ALLsub[i]["errors"]["symerror"]["value"] * 1e-3], + "sys_min": [ALLsub[i]["errors"]["asymerror"]["minus"] * 1e-3], + "sys_max": [ALLsub[i]["errors"]["asymerror"]["plus"] * 1e-3], + } + ), + ], + ignore_index=True, + ) + for i in range(len(df)): + shift, unc = symmetrize_errors(df.loc[i, "sys_max"], df.loc[i, "sys_min"]) + df.loc[i, "sys"] = unc + df.loc[i, "ALL"] += shift + + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["ALL"])): + data_central.append(float(df.loc[i, "ALL"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["ALL"])): + kin_value = { + "pT": { + "min": float(df.loc[i, "pTmin"]), + "mid": float(df.loc[i, "pT"]), + "max": float(df.loc[i, "pTmax"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": { + "min": float(df.loc[i, "eta_min"]), + "mid": float(df.loc[i, "eta"]), + "max": float(df.loc[i, "eta_max"]), + }, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for i in range(len(df)): + e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + error.append(e) + + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # TODO: Need to generate `observable` cards and corresponding + # pineappl grids and FK tables as the orders have changed!!!! + fnames = glob.glob("rawdata/*.yaml") + nnames = sorted([i for i in fnames]) + df = read_data(nnames) + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/kinematics.yaml new file mode 100644 index 0000000000..f183806bd3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/kinematics.yaml @@ -0,0 +1,229 @@ +bins: +- pT: + min: 4.9 + mid: 5.3 + max: 5.7 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 5.9 + mid: 6.3 + max: 6.8 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 6.7 + mid: 7.1 + max: 7.7 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 8.1 + mid: 8.7 + max: 9.4 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 10.0 + mid: 10.7 + max: 11.5 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 12.3 + mid: 13.1 + max: 14.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 15.2 + mid: 16.0 + max: 17.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 18.4 + mid: 19.4 + max: 20.7 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 22.4 + mid: 23.6 + max: 25.1 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 26.7 + mid: 28.1 + max: 29.9 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 7.8 + mid: 8.5 + max: 9.3 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 9.5 + mid: 10.3 + max: 11.1 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 11.3 + mid: 12.2 + max: 13.1 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 13.4 + mid: 14.4 + max: 15.4 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 16.1 + mid: 17.2 + max: 18.3 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 19.2 + mid: 20.5 + max: 21.8 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 22.9 + mid: 24.4 + max: 25.9 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 27.6 + mid: 29.4 + max: 31.2 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 +- pT: + min: 32.0 + mid: 34.7 + max: 37.3 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.7 + mid: 0.10000000000000003 + max: 0.9 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/metadata.yaml new file mode 100644 index 0000000000..4664eca4ef --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/metadata.yaml @@ -0,0 +1,52 @@ +setname: "STAR_1JET_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1114529" +hepdata: + url: "https://www.hepdata.net/record/ins1114529" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: JET_POL + ndata: 19 + tables: [14, 15] + npoints: [10, 9] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, eta] + plotting: + kinematics_override: identity + dataset_label: "$A_{LL}$" + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_14.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_14.yaml new file mode 100644 index 0000000000..e654ea3dc8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_14.yaml @@ -0,0 +1,69 @@ +dependent_variables: + - header: { name: '$A_{LL}\times 10^{-3}$' } + qualifiers: + - { name: "Source", value: "2005 STAR Data" } + + values: + - value: 5.3 + errors: + symerror: { "value": 5.9, label: "stat" } + asymerror: { minus: -2.4, plus: 2.4 } + + - value: -2.7 + errors: + symerror: { "value": 5.4, label: "stat" } + asymerror: { minus: -1.9, plus: 1.8 } + + - value: 2.4 + errors: + symerror: { "value": 5.7, label: "stat" } + asymerror: { minus: -1.9, plus: 1.7 } + + - value: 14.3 + errors: + symerror: { "value": 6.7, label: "stat" } + asymerror: { minus: -2.2, plus: 2.9 } + + - value: -6.7 + errors: + symerror: { "value": 8.7, label: "stat" } + asymerror: { minus: -1.7, plus: 2.6 } + + - value: 2.6 + errors: + symerror: { "value": 12.7, label: "stat" } + asymerror: { minus: -1.7, plus: 2.7 } + + - value: -14.6 + errors: + symerror: { "value": 20.3, label: "stat" } + asymerror: { minus: -2.2, plus: 3.0 } + + - value: -52.2 + errors: + symerror: { "value": 35.0, label: "stat" } + asymerror: { minus: -2.9, plus: 2.9 } + + - value: 56.9 + errors: + symerror: { "value": 67.1, label: "stat" } + asymerror: { minus: -4.1, plus: 4.1 } + + - value: 146 + errors: + symerror: { "value": 138, label: "stat" } + asymerror: { minus: -3.7, plus: 5.7 } + +independent_variables: + - header: { name: "$p_{T}$", units: GeV/c } + values: + - { value: 5.3, low: 4.9, high: 5.7 } + - { value: 6.3, low: 5.9, high: 6.8 } + - { value: 7.1, low: 6.7, high: 7.7 } + - { value: 8.7, low: 8.1, high: 9.4 } + - { value: 10.7, low: 10.0, high: 11.5 } + - { value: 13.1, low: 12.3, high: 14.0 } + - { value: 16.0, low: 15.2, high: 17.0 } + - { value: 19.4, low: 18.4, high: 20.7 } + - { value: 23.6, low: 22.4, high: 25.1 } + - { value: 28.1, low: 26.7, high: 29.9 } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_15.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_15.yaml new file mode 100644 index 0000000000..a8ac09d945 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_15.yaml @@ -0,0 +1,63 @@ +dependent_variables: + - header: { name: '$A_{LL}\times 10^{-3}$' } + qualifiers: + - { name: "Source", value: '2006 STAR Data, -0.7 < $\eta$ < 0.9' } + + values: + - value: 2.7 + errors: + symerror: { value: 5.3, label: "stat" } + asymerror: { minus: -2.6, plus: 3.8 } + + - value: 3.3 + errors: + symerror: { value: 4.3, label: "stat" } + asymerror: { minus: -1.6, plus: 2.3 } + + - value: 9.9 + errors: + symerror: { value: 4.1, label: "stat" } + asymerror: { minus: -1.6, plus: 2.3 } + + - value: 1.2 + errors: + symerror: { value: 4.5, label: "stat" } + asymerror: { minus: -1.2, plus: 1.5 } + + - value: 9.2 + errors: + symerror: { value: 5.8, label: "stat" } + asymerror: { minus: -1.1, plus: 1.2 } + + - value: 25.7 + errors: + symerror: { value: 8.8, label: "stat" } + asymerror: { minus: -1.3, plus: 1.8 } + + - value: 25.6 + errors: + symerror: { value: 15.4, label: "stat" } + asymerror: { minus: -1.6, plus: 4.1 } + + - value: 22.0 + errors: + symerror: { value: 31.0, label: "stat" } + asymerror: { minus: -2.1, plus: 5.6 } + + - value: 12.0 + errors: + symerror: { value: 70.6, label: "stat" } + asymerror: { minus: -3.3, plus: 7.1 } + +independent_variables: + - header: { name: "$p_{T}$", units: GeV/c } + values: + - { value: 8.5, low: 7.8, high: 9.3 } + - { value: 10.3, low: 9.5, high: 11.1 } + - { value: 12.2, low: 11.3, high: 13.1 } + - { value: 14.4, low: 13.4, high: 15.4 } + - { value: 17.2, low: 16.1, high: 18.3 } + - { value: 20.5, low: 19.2, high: 21.8 } + - { value: 24.4, low: 22.9, high: 25.9 } + - { value: 29.4, low: 27.6, high: 31.2 } + - { value: 34.7, low: 32.0, high: 37.3 } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..deef3a4deb --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/uncertainties.yaml @@ -0,0 +1,48 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + sys: + description: systematic uncertainty + treatment: ADD + type: UNCORR +bins: +- stat: 0.005900000000000001 + sys: 0.0024 +- stat: 0.0054 + sys: 0.0018513508581573619 +- stat: 0.0057 + sys: 0.0018055470085267787 +- stat: 0.0067 + sys: 0.002597595041572108 +- stat: 0.0087 + sys: 0.0022422087324778664 +- stat: 0.0127 + sys: 0.002310844001658269 +- stat: 0.020300000000000002 + sys: 0.002660826939130014 +- stat: 0.035 + sys: 0.0029 +- stat: 0.06709999999999999 + sys: 0.0040999999999999995 +- stat: 0.138 + sys: 0.004908156476723211 +- stat: 0.0053 + sys: 0.00331058907144937 +- stat: 0.0043 + sys: 0.002011839953873071 +- stat: 0.0040999999999999995 + sys: 0.002011839953873071 +- stat: 0.0045000000000000005 + sys: 0.001366565036871645 +- stat: 0.0058 + sys: 0.0011521718621802911 +- stat: 0.0088 + sys: 0.0015898113095584648 +- stat: 0.0154 + sys: 0.0033537292675468 +- stat: 0.031 + sys: 0.004576843890717707 +- stat: 0.0706 + sys: 0.005853204250664759 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/data.yaml new file mode 100644 index 0000000000..56efa8beb3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/data.yaml @@ -0,0 +1,23 @@ +data_central: +- 0.002 +- 0.0056 +- 0.0013 +- 0.005 +- 0.0054 +- 0.0114 +- 0.0115 +- 0.0132 +- 0.0207 +- 0.0326 +- 0.0332 +- 0.0018 +- 0.004 +- 0.0059 +- 0.0027 +- 0.0069 +- 0.0087 +- 0.015 +- 0.0195 +- 0.0333 +- 0.0437 +- 0.0055 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/filter.py new file mode 100644 index 0000000000..647d059b1d --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/filter.py @@ -0,0 +1,123 @@ +import glob +import sys + +import pandas as pd +import yaml + +sys.path.append('../') +from ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors + + +def read_data(fnames): + df3 = pd.DataFrame() + df4 = pd.DataFrame() + for fname in fnames: + if "3" in fname: + dfi = pd.read_csv(fname) + if "pT" in fname: + correlation = False + df3["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] + + elif "ALL" in fname: + df3["ALL"] = dfi["$A_{LL}$"] + df3["stat_min"] = dfi["stat +"] + df3["stat_max"] = dfi["stat -"] + df3["sys_min"] = dfi["sys +"] + df3["sys_max"] = dfi["sys -"] + + df3["eta_min"] = -0.5 + df3["eta_max"] = 0.5 + df3["eta"] = 0.0 + df3["sqrts"] = 200 + + elif "4" in fname: + dfi = pd.read_csv(fname) + if "pT" in fname: + correlation = False + df4["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] + + if "ALL" in fname: + df4["ALL"] = dfi["$A_{LL}$"] + df4["stat_min"] = dfi["stat +"] + df4["stat_max"] = dfi["stat -"] + df4["sys_min"] = dfi["sys +"] + df4["sys_max"] = dfi["sys -"] + + df4["eta_min"] = -1.0 + df4["eta_max"] = 1.0 + df4["eta"] = 0.0 + df4["sqrts"] = 200 + + elif "5" in fname: + correlation = True + # Write correlation code here Giacomo + + else: + print("ERROR: Unknown table number detected! Check input files.") + + df = pd.concat([df3, df4], ignore_index=True) + + for i in range(len(df)): + shift, unc = symmetrize_errors(df.loc[i, "stat_max"], df.loc[i, "stat_min"]) + df.loc[i, "stat"] = unc + df.loc[i, "ALL"] += shift + + shift, unc = symmetrize_errors(df.loc[i, "sys_max"], df.loc[i, "sys_min"]) + df.loc[i, "sys"] = unc + df.loc[i, "ALL"] += shift + + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["ALL"])): + data_central.append(float(df.loc[i, "ALL"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["ALL"])): + kin_value = { + "pT": {"min": None, "mid": float(df.loc[i, "pT"]), "max": None}, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": { + "min": float(df.loc[i, "eta_min"]), + "mid": float(df.loc[i, "eta"]), + "max": float(df.loc[i, "eta_max"]), + }, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for i in range(len(df)): + e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + error.append(e) + + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # TODO: Need to generate `observable` cards and corresponding + # pineappl grids and FK tables as the orders have changed!!!! + fnames = glob.glob("rawdata/*.csv") + nnames = sorted([i for i in fnames]) + df = read_data(nnames) + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/kinematics.yaml new file mode 100644 index 0000000000..36d1079c95 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/kinematics.yaml @@ -0,0 +1,265 @@ +bins: +- pT: + min: null + mid: 5.5 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 6.49 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 8.25 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 10.08 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 12.26 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 14.78 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 17.23 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 20.56 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 23.61 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 27.78 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 32.46 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -0.5 + mid: 0.0 + max: 0.5 +- pT: + min: null + mid: 5.61 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 6.62 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 8.48 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 10.17 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 12.2 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 14.57 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 16.99 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 20.16 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 23.35 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 27.13 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 +- pT: + min: null + mid: 31.08 + max: null + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: -1.0 + mid: 0.0 + max: 1.0 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/metadata.yaml new file mode 100644 index 0000000000..1e193d1448 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/metadata.yaml @@ -0,0 +1,52 @@ +setname: "STAR2015_1JET_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://www.hepdata.net/record/ins1297229" +hepdata: + url: "https://inspirehep.net/literature/1297229" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: JET_POL + ndata: 21 + tables: [3, 4] + npoints: [11, 10] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, eta] + plotting: + kinematics_override: identity + dataset_label: "$A_{LL}$" + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR2015_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_ALL.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_ALL.csv new file mode 100644 index 0000000000..782f8abb98 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_ALL.csv @@ -0,0 +1,12 @@ +Bin,$A_{LL}$,stat +,stat -,sys +,sys - +1.0,0.002,0.0015,-0.0015,0.0003,-0.0003 +2.0,0.0056,0.0016,-0.0016,0.0004,-0.0004 +3.0,0.0013,0.0014,-0.0014,0.0004,-0.0004 +4.0,0.005,0.0016,-0.0016,0.0004,-0.0004 +5.0,0.0054,0.002,-0.002,0.0005,-0.0005 +6.0,0.0114,0.0026,-0.0026,0.0006,-0.0006 +7.0,0.0115,0.0037,-0.0037,0.0015,-0.0015 +8.0,0.0132,0.0055,-0.0055,0.0016,-0.0016 +9.0,0.0207,0.0092,-0.0092,0.0022,-0.0022 +10.0,0.0326,0.016,-0.016,0.0039,-0.0039 +11.0,0.0332,0.0297,-0.0297,0.0048,-0.0048 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_pT.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_pT.csv new file mode 100644 index 0000000000..26c494a751 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_pT.csv @@ -0,0 +1,12 @@ +Bin,Parton Jet $p_T$ [GeV/c],stat +,stat -,sys +,sys - +1.0,5.5,0.0,-0.0,0.79,-0.79 +2.0,6.49,0.0,-0.0,0.8,-0.8 +3.0,8.25,0.0,-0.0,0.7,-0.7 +4.0,10.08,0.0,-0.0,0.67,-0.67 +5.0,12.26,0.0,-0.0,0.67,-0.67 +6.0,14.78,0.0,-0.0,0.71,-0.71 +7.0,17.23,0.0,-0.0,0.77,-0.77 +8.0,20.56,0.0,-0.0,0.88,-0.88 +9.0,23.61,0.0,-0.0,0.94,-0.94 +10.0,27.78,0.0,-0.0,0.98,-0.98 +11.0,32.46,0.0,-0.0,1.11,-1.11 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_ALL.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_ALL.csv new file mode 100644 index 0000000000..50abb7106e --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_ALL.csv @@ -0,0 +1,12 @@ +Bin,$A_{LL}$,stat +,stat -,sys +,sys - +12.0,0.0018,0.0016,-0.0016,0.0004,-0.0004 +13.0,0.004,0.0018,-0.0018,0.0004,-0.0004 +14.0,0.0059,0.0016,-0.0016,0.0004,-0.0004 +15.0,0.0027,0.0019,-0.0019,0.0004,-0.0004 +16.0,0.0069,0.0024,-0.0024,0.0005,-0.0005 +17.0,0.0087,0.0032,-0.0032,0.0006,-0.0006 +18.0,0.015,0.0046,-0.0046,0.0011,-0.0011 +19.0,0.0195,0.0071,-0.0071,0.0015,-0.0015 +20.0,0.0333,0.0122,-0.0122,0.0025,-0.0025 +21.0,0.0437,0.0221,-0.0221,0.0038,-0.0038 +22.0,0.0055,0.0434,-0.0434,0.006,-0.006 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_pT.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_pT.csv new file mode 100644 index 0000000000..40a537e8a5 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_pT.csv @@ -0,0 +1,12 @@ +Bin,Parton Jet $p_T$ [GeV/c],stat +,stat -,sys +,sys - +12.0,5.61,0.0,-0.0,0.81,-0.81 +13.0,6.62,0.0,-0.0,0.81,-0.81 +14.0,8.48,0.0,-0.0,0.69,-0.69 +15.0,10.17,0.0,-0.0,0.65,-0.65 +16.0,12.2,0.0,-0.0,0.64,-0.64 +17.0,14.57,0.0,-0.0,0.61,-0.61 +18.0,16.99,0.0,-0.0,0.69,-0.69 +19.0,20.16,0.0,-0.0,0.9,-0.9 +20.0,23.35,0.0,-0.0,0.93,-0.93 +21.0,27.13,0.0,-0.0,1.09,-1.09 +22.0,31.08,0.0,-0.0,1.08,-1.08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_5.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_5.csv new file mode 100644 index 0000000000..3e15ef3e34 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_5.csv @@ -0,0 +1,602 @@ +#: table_doi: 10.17182/hepdata.73432.v1/t5 +#: name: Table 5 +#: description: The uncertainties on the parton jet pT values are strongly correlated across the bins. The point-to-point statistical and systematic uncertainties on the measured A_LL values given above are only weakly correlated among the bins. The correlation matrix for the quadrature sum of the point-to-point statistical and systematic uncertainties is given below. In that matrix, the order of the rows and columns matches the bin numbering above. In addition to the point-to-point statistical and systematic uncertainties, there are two systematic uncertainties that are common to all the measured A_LL values (and not included in the systematic uncertainty numbers quoted above): (a) +/-0.0005 vertical shift uncertainty from relative luminosity and (b) +/-6.5% vertical scale uncertainty from polarization. + +#: data_file: Table5.yaml +#: keyword reactions: P P --> JET X +#: keyword observables: +#: keyword phrases: Inclusive | Proton-Proton Scattering | Jet Production +#: keyword cmenergies: 200.0 +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,1.0 +1.0,1.0 +2.0,0.013 +3.0,0.008 +4.0,0.007 +5.0,0.008 +6.0,0.008 +7.0,0.006 +8.0,0.005 +9.0,0.003 +10.0,0.002 +11.0,0.002 +12.0,0.043 +13.0,0.011 +14.0,0.011 +15.0,0.005 +16.0,0.005 +17.0,0.003 +18.0,0.005 +19.0,0.002 +20.0,0.001 +21.0,0.002 +22.0,0.001 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,2.0 +1.0,0.013 +2.0,1.0 +3.0,0.013 +4.0,0.011 +5.0,0.015 +6.0,0.015 +7.0,0.01 +8.0,0.009 +9.0,0.005 +10.0,0.004 +11.0,0.003 +12.0,0.011 +13.0,0.047 +14.0,0.018 +15.0,0.009 +16.0,0.008 +17.0,0.006 +18.0,0.009 +19.0,0.004 +20.0,0.003 +21.0,0.004 +22.0,0.002 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,3.0 +1.0,0.008 +2.0,0.013 +3.0,1.0 +4.0,0.012 +5.0,0.014 +6.0,0.013 +7.0,0.009 +8.0,0.007 +9.0,0.004 +10.0,0.003 +11.0,0.002 +12.0,0.007 +13.0,0.011 +14.0,0.051 +15.0,0.009 +16.0,0.008 +17.0,0.007 +18.0,0.008 +19.0,0.004 +20.0,0.002 +21.0,0.002 +22.0,0.001 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,4.0 +1.0,0.007 +2.0,0.011 +3.0,0.012 +4.0,1.0 +5.0,0.017 +6.0,0.017 +7.0,0.013 +8.0,0.009 +9.0,0.005 +10.0,0.003 +11.0,0.002 +12.0,0.006 +13.0,0.01 +14.0,0.013 +15.0,0.039 +16.0,0.012 +17.0,0.01 +18.0,0.01 +19.0,0.005 +20.0,0.003 +21.0,0.003 +22.0,0.001 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,5.0 +1.0,0.008 +2.0,0.015 +3.0,0.014 +4.0,0.017 +5.0,1.0 +6.0,0.028 +7.0,0.022 +8.0,0.017 +9.0,0.01 +10.0,0.006 +11.0,0.003 +12.0,0.008 +13.0,0.013 +14.0,0.017 +15.0,0.014 +16.0,0.034 +17.0,0.016 +18.0,0.017 +19.0,0.011 +20.0,0.007 +21.0,0.005 +22.0,0.002 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,6.0 +1.0,0.008 +2.0,0.015 +3.0,0.013 +4.0,0.017 +5.0,0.028 +6.0,1.0 +7.0,0.031 +8.0,0.026 +9.0,0.016 +10.0,0.009 +11.0,0.004 +12.0,0.008 +13.0,0.014 +14.0,0.018 +15.0,0.014 +16.0,0.018 +17.0,0.033 +18.0,0.026 +19.0,0.018 +20.0,0.011 +21.0,0.008 +22.0,0.003 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,7.0 +1.0,0.006 +2.0,0.01 +3.0,0.009 +4.0,0.013 +5.0,0.022 +6.0,0.031 +7.0,1.0 +8.0,0.033 +9.0,0.024 +10.0,0.013 +11.0,0.006 +12.0,0.005 +13.0,0.009 +14.0,0.012 +15.0,0.01 +16.0,0.014 +17.0,0.019 +18.0,0.04 +19.0,0.024 +20.0,0.016 +21.0,0.011 +22.0,0.005 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,8.0 +1.0,0.005 +2.0,0.009 +3.0,0.007 +4.0,0.009 +5.0,0.017 +6.0,0.026 +7.0,0.033 +8.0,1.0 +9.0,0.039 +10.0,0.026 +11.0,0.013 +12.0,0.004 +13.0,0.007 +14.0,0.01 +15.0,0.007 +16.0,0.01 +17.0,0.015 +18.0,0.026 +19.0,0.05 +20.0,0.026 +21.0,0.02 +22.0,0.009 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,9.0 +1.0,0.003 +2.0,0.005 +3.0,0.004 +4.0,0.005 +5.0,0.01 +6.0,0.016 +7.0,0.024 +8.0,0.039 +9.0,1.0 +10.0,0.046 +11.0,0.028 +12.0,0.003 +13.0,0.005 +14.0,0.006 +15.0,0.004 +16.0,0.005 +17.0,0.009 +18.0,0.017 +19.0,0.026 +20.0,0.046 +21.0,0.032 +22.0,0.018 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,10.0 +1.0,0.002 +2.0,0.004 +3.0,0.003 +4.0,0.003 +5.0,0.006 +6.0,0.009 +7.0,0.013 +8.0,0.026 +9.0,0.046 +10.0,1.0 +11.0,0.052 +12.0,0.002 +13.0,0.003 +14.0,0.004 +15.0,0.002 +16.0,0.003 +17.0,0.004 +18.0,0.008 +19.0,0.016 +20.0,0.026 +21.0,0.048 +22.0,0.032 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,11.0 +1.0,0.002 +2.0,0.003 +3.0,0.002 +4.0,0.002 +5.0,0.003 +6.0,0.004 +7.0,0.006 +8.0,0.013 +9.0,0.028 +10.0,0.052 +11.0,1.0 +12.0,0.001 +13.0,0.003 +14.0,0.003 +15.0,0.001 +16.0,0.002 +17.0,0.002 +18.0,0.004 +19.0,0.006 +20.0,0.013 +21.0,0.028 +22.0,0.04 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,12.0 +1.0,0.043 +2.0,0.011 +3.0,0.007 +4.0,0.006 +5.0,0.008 +6.0,0.008 +7.0,0.005 +8.0,0.004 +9.0,0.003 +10.0,0.002 +11.0,0.001 +12.0,1.0 +13.0,0.009 +14.0,0.009 +15.0,0.005 +16.0,0.003 +17.0,0.003 +18.0,0.004 +19.0,0.002 +20.0,0.001 +21.0,0.002 +22.0,0.001 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,13.0 +1.0,0.011 +2.0,0.047 +3.0,0.011 +4.0,0.01 +5.0,0.013 +6.0,0.014 +7.0,0.009 +8.0,0.007 +9.0,0.005 +10.0,0.003 +11.0,0.003 +12.0,0.009 +13.0,1.0 +14.0,0.016 +15.0,0.008 +16.0,0.006 +17.0,0.004 +18.0,0.008 +19.0,0.003 +20.0,0.002 +21.0,0.003 +22.0,0.001 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,14.0 +1.0,0.011 +2.0,0.018 +3.0,0.051 +4.0,0.013 +5.0,0.017 +6.0,0.018 +7.0,0.012 +8.0,0.01 +9.0,0.006 +10.0,0.004 +11.0,0.003 +12.0,0.009 +13.0,0.016 +14.0,1.0 +15.0,0.011 +16.0,0.009 +17.0,0.007 +18.0,0.01 +19.0,0.005 +20.0,0.004 +21.0,0.004 +22.0,0.002 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,15.0 +1.0,0.005 +2.0,0.009 +3.0,0.009 +4.0,0.039 +5.0,0.014 +6.0,0.014 +7.0,0.01 +8.0,0.007 +9.0,0.004 +10.0,0.002 +11.0,0.001 +12.0,0.005 +13.0,0.008 +14.0,0.011 +15.0,1.0 +16.0,0.009 +17.0,0.008 +18.0,0.008 +19.0,0.004 +20.0,0.002 +21.0,0.003 +22.0,0.001 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,16.0 +1.0,0.005 +2.0,0.008 +3.0,0.008 +4.0,0.012 +5.0,0.034 +6.0,0.018 +7.0,0.014 +8.0,0.01 +9.0,0.005 +10.0,0.003 +11.0,0.002 +12.0,0.003 +13.0,0.006 +14.0,0.009 +15.0,0.009 +16.0,1.0 +17.0,0.012 +18.0,0.011 +19.0,0.007 +20.0,0.004 +21.0,0.002 +22.0,0.002 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,17.0 +1.0,0.003 +2.0,0.006 +3.0,0.007 +4.0,0.01 +5.0,0.016 +6.0,0.033 +7.0,0.019 +8.0,0.015 +9.0,0.009 +10.0,0.004 +11.0,0.002 +12.0,0.003 +13.0,0.004 +14.0,0.007 +15.0,0.008 +16.0,0.012 +17.0,1.0 +18.0,0.015 +19.0,0.01 +20.0,0.006 +21.0,0.004 +22.0,0.001 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,18.0 +1.0,0.005 +2.0,0.009 +3.0,0.008 +4.0,0.01 +5.0,0.017 +6.0,0.026 +7.0,0.04 +8.0,0.026 +9.0,0.017 +10.0,0.008 +11.0,0.004 +12.0,0.004 +13.0,0.008 +14.0,0.01 +15.0,0.008 +16.0,0.011 +17.0,0.015 +18.0,1.0 +19.0,0.017 +20.0,0.01 +21.0,0.007 +22.0,0.003 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,19.0 +1.0,0.002 +2.0,0.004 +3.0,0.004 +4.0,0.005 +5.0,0.011 +6.0,0.018 +7.0,0.024 +8.0,0.05 +9.0,0.026 +10.0,0.016 +11.0,0.006 +12.0,0.002 +13.0,0.003 +14.0,0.005 +15.0,0.004 +16.0,0.007 +17.0,0.01 +18.0,0.017 +19.0,1.0 +20.0,0.015 +21.0,0.011 +22.0,0.005 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,20.0 +1.0,0.001 +2.0,0.003 +3.0,0.002 +4.0,0.003 +5.0,0.007 +6.0,0.011 +7.0,0.016 +8.0,0.026 +9.0,0.046 +10.0,0.026 +11.0,0.013 +12.0,0.001 +13.0,0.002 +14.0,0.004 +15.0,0.002 +16.0,0.004 +17.0,0.006 +18.0,0.01 +19.0,0.015 +20.0,1.0 +21.0,0.017 +22.0,0.008 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,21.0 +1.0,0.002 +2.0,0.004 +3.0,0.002 +4.0,0.003 +5.0,0.005 +6.0,0.008 +7.0,0.011 +8.0,0.02 +9.0,0.032 +10.0,0.048 +11.0,0.028 +12.0,0.002 +13.0,0.003 +14.0,0.004 +15.0,0.003 +16.0,0.002 +17.0,0.004 +18.0,0.007 +19.0,0.011 +20.0,0.017 +21.0,1.0 +22.0,0.014 + +#: RE,P P --> JET X +#: SQRT(S) [GeV],200.0 +See description,See description +-,22.0 +1.0,0.001 +2.0,0.002 +3.0,0.001 +4.0,0.001 +5.0,0.002 +6.0,0.003 +7.0,0.005 +8.0,0.009 +9.0,0.018 +10.0,0.032 +11.0,0.04 +12.0,0.001 +13.0,0.001 +14.0,0.002 +15.0,0.001 +16.0,0.002 +17.0,0.001 +18.0,0.003 +19.0,0.005 +20.0,0.008 +21.0,0.014 +22.0,1.0 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..a48e36cbe1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/uncertainties.yaml @@ -0,0 +1,54 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + sys: + description: systematic uncertainty + treatment: ADD + type: UNCORR +bins: +- stat: 0.0015 + sys: 0.0003 +- stat: 0.0016 + sys: 0.0004 +- stat: 0.0014 + sys: 0.0004 +- stat: 0.0016 + sys: 0.0004 +- stat: 0.002 + sys: 0.0005 +- stat: 0.0026 + sys: 0.0006 +- stat: 0.0037 + sys: 0.0015 +- stat: 0.0055 + sys: 0.0016 +- stat: 0.0092 + sys: 0.0022 +- stat: 0.016 + sys: 0.0039 +- stat: 0.0297 + sys: 0.0048 +- stat: 0.0016 + sys: 0.0004 +- stat: 0.0018 + sys: 0.0004 +- stat: 0.0016 + sys: 0.0004 +- stat: 0.0019 + sys: 0.0004 +- stat: 0.0024 + sys: 0.0005 +- stat: 0.0032 + sys: 0.0006 +- stat: 0.0046 + sys: 0.0011 +- stat: 0.0071 + sys: 0.0015 +- stat: 0.0122 + sys: 0.0025 +- stat: 0.0221 + sys: 0.0038 +- stat: 0.0434 + sys: 0.006 From aace47cf7bd849f81666f23806fcb744345ca22b Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Wed, 17 Apr 2024 09:05:00 +0200 Subject: [PATCH 05/98] Name change of STARyear to STAR_year convention --- .../{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/data.yaml | 0 .../{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/filter.py | 0 .../kinematics.yaml | 0 .../{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/metadata.yaml | 0 .../rawdata/Table_14.yaml | 0 .../rawdata/Table_15.yaml | 0 .../uncertainties.yaml | 0 .../{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/data.yaml | 0 .../{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/filter.py | 0 .../kinematics.yaml | 0 .../{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/metadata.yaml | 0 .../rawdata/Table_3_ALL.csv | 0 .../rawdata/Table_3_pT.csv | 0 .../rawdata/Table_4_ALL.csv | 0 .../rawdata/Table_4_pT.csv | 0 .../rawdata/Table_5.csv | 0 .../uncertainties.yaml | 0 17 files changed, 0 insertions(+), 0 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/data.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/filter.py (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/kinematics.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/metadata.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/rawdata/Table_14.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/rawdata/Table_15.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2012_1JET_200GEV => STAR_2012_1JET_200GEV}/uncertainties.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/data.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/filter.py (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/kinematics.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/metadata.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/rawdata/Table_3_ALL.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/rawdata/Table_3_pT.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/rawdata/Table_4_ALL.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/rawdata/Table_4_pT.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/rawdata/Table_5.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR2015_1JET_200GEV => STAR_2015_1JET_200GEV}/uncertainties.yaml (100%) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/data.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/filter.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/kinematics.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/kinematics.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/metadata.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_14.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_14.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_14.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_14.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_15.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_15.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/rawdata/Table_15.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_15.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/uncertainties.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2012_1JET_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/filter.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/metadata.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_ALL.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_ALL.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_ALL.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_ALL.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_pT.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_pT.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_3_pT.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_pT.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_ALL.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_ALL.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_ALL.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_ALL.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_pT.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_pT.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_4_pT.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_pT.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_5.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/rawdata/Table_5.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR2015_1JET_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml From 994638ad5869642d2eb7d863684b62d44c31a3da Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Wed, 17 Apr 2024 09:07:30 +0200 Subject: [PATCH 06/98] propagate previous namechange --- .../new_commondata/STAR_2012_1JET_200GEV/metadata.yaml | 4 ++-- .../new_commondata/STAR_2015_1JET_200GEV/metadata.yaml | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml index 4664eca4ef..ca0b772dbe 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml @@ -1,4 +1,4 @@ -setname: "STAR_1JET_200GEV" +setname: "STAR_2012_1JET_200GEV" nnpdf_metadata: experiment: "STAR" @@ -49,4 +49,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_1JET_200GEV_ALL + - - STAR_2012_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml index 1e193d1448..28ac029853 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml @@ -1,4 +1,4 @@ -setname: "STAR2015_1JET_200GEV" +setname: "STAR_2015_1JET_200GEV" nnpdf_metadata: experiment: "STAR" @@ -49,4 +49,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR2015_1JET_200GEV_ALL + - - STAR_2015_1JET_200GEV_ALL From 12d2ac96437b56afa2b69d1a91674489ab268788 Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Wed, 17 Apr 2024 10:23:58 +0200 Subject: [PATCH 07/98] implemented correlations for STAR_2015 --- .../STAR_2015_1JET_200GEV/filter.py | 47 +- .../STAR_2015_1JET_200GEV/rawdata/Table_5.csv | 97 +-- .../STAR_2015_1JET_200GEV/uncertainties.yaml | 572 ++++++++++++++++++ 3 files changed, 613 insertions(+), 103 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index 647d059b1d..86cec57ed2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -6,6 +6,7 @@ sys.path.append('../') from ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors +from HERMES_NC_7GEV_EP.filter import compute_covmat def read_data(fnames): @@ -50,7 +51,18 @@ def read_data(fnames): elif "5" in fname: correlation = True - # Write correlation code here Giacomo + dfc_col = pd.read_csv(fname) + + dfc = pd.DataFrame() + biny = 1 + for i in range(len(dfc_col)): + if dfc_col.loc[i, "binx"] == "-": + biny = float(dfc_col.loc[i, "val"]) + else: + binx = float(dfc_col.loc[i, "binx"]) + dfc.loc[binx, biny] = dfc_col.loc[i, "val"] + + dfc = dfc.astype("float") else: print("ERROR: Unknown table number detected! Check input files.") @@ -66,10 +78,10 @@ def read_data(fnames): df.loc[i, "sys"] = unc df.loc[i, "ALL"] += shift - return df + return df, dfc -def write_data(df): +def write_data(df, dfc): data_central = [] for i in range(len(df["ALL"])): data_central.append(float(df.loc[i, "ALL"])) @@ -78,6 +90,10 @@ def write_data(df): with open("data.yaml", "w") as file: yaml.dump(data_central_yaml, file, sort_keys=False) + # Compute the covariance matrix + corrmat = dfc.values.reshape((len(df), len(df))) + art_sys = compute_covmat(corrmat, df, len(df)) + # Write kin file kin = [] for i in range(len(df["ALL"])): @@ -101,13 +117,30 @@ def write_data(df): error = [] for i in range(len(df)): e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + for j in range(len(df)): + e[f"sys_{j}"] = art_sys[i][j] error.append(e) error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + f"sys_{i}": { + "description": f"{i} artificial correlated statistical uncertainty", + "treatment": "ADD", + "type": "CORR", + } + for i in range(len(df)) } + error_definition.update( + { + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + ) + uncertainties_yaml = {"definitions": error_definition, "bins": error} with open("uncertainties.yaml", "w") as file: @@ -119,5 +152,5 @@ def write_data(df): # pineappl grids and FK tables as the orders have changed!!!! fnames = glob.glob("rawdata/*.csv") nnames = sorted([i for i in fnames]) - df = read_data(nnames) - write_data(df) + df, dfc = read_data(nnames) + write_data(df, dfc) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv index 3e15ef3e34..3dbe5a424d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv @@ -1,15 +1,4 @@ -#: table_doi: 10.17182/hepdata.73432.v1/t5 -#: name: Table 5 -#: description: The uncertainties on the parton jet pT values are strongly correlated across the bins. The point-to-point statistical and systematic uncertainties on the measured A_LL values given above are only weakly correlated among the bins. The correlation matrix for the quadrature sum of the point-to-point statistical and systematic uncertainties is given below. In that matrix, the order of the rows and columns matches the bin numbering above. In addition to the point-to-point statistical and systematic uncertainties, there are two systematic uncertainties that are common to all the measured A_LL values (and not included in the systematic uncertainty numbers quoted above): (a) +/-0.0005 vertical shift uncertainty from relative luminosity and (b) +/-6.5% vertical scale uncertainty from polarization. - -#: data_file: Table5.yaml -#: keyword reactions: P P --> JET X -#: keyword observables: -#: keyword phrases: Inclusive | Proton-Proton Scattering | Jet Production -#: keyword cmenergies: 200.0 -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description +binx,val -,1.0 1.0,1.0 2.0,0.013 @@ -33,10 +22,6 @@ See description,See description 20.0,0.001 21.0,0.002 22.0,0.001 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,2.0 1.0,0.013 2.0,1.0 @@ -60,10 +45,6 @@ See description,See description 20.0,0.003 21.0,0.004 22.0,0.002 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,3.0 1.0,0.008 2.0,0.013 @@ -87,10 +68,6 @@ See description,See description 20.0,0.002 21.0,0.002 22.0,0.001 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,4.0 1.0,0.007 2.0,0.011 @@ -114,10 +91,6 @@ See description,See description 20.0,0.003 21.0,0.003 22.0,0.001 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,5.0 1.0,0.008 2.0,0.015 @@ -141,10 +114,6 @@ See description,See description 20.0,0.007 21.0,0.005 22.0,0.002 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,6.0 1.0,0.008 2.0,0.015 @@ -168,10 +137,6 @@ See description,See description 20.0,0.011 21.0,0.008 22.0,0.003 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,7.0 1.0,0.006 2.0,0.01 @@ -195,10 +160,6 @@ See description,See description 20.0,0.016 21.0,0.011 22.0,0.005 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,8.0 1.0,0.005 2.0,0.009 @@ -222,10 +183,6 @@ See description,See description 20.0,0.026 21.0,0.02 22.0,0.009 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,9.0 1.0,0.003 2.0,0.005 @@ -249,10 +206,6 @@ See description,See description 20.0,0.046 21.0,0.032 22.0,0.018 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,10.0 1.0,0.002 2.0,0.004 @@ -276,10 +229,6 @@ See description,See description 20.0,0.026 21.0,0.048 22.0,0.032 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,11.0 1.0,0.002 2.0,0.003 @@ -303,10 +252,6 @@ See description,See description 20.0,0.013 21.0,0.028 22.0,0.04 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,12.0 1.0,0.043 2.0,0.011 @@ -330,10 +275,6 @@ See description,See description 20.0,0.001 21.0,0.002 22.0,0.001 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,13.0 1.0,0.011 2.0,0.047 @@ -357,10 +298,6 @@ See description,See description 20.0,0.002 21.0,0.003 22.0,0.001 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,14.0 1.0,0.011 2.0,0.018 @@ -384,10 +321,6 @@ See description,See description 20.0,0.004 21.0,0.004 22.0,0.002 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,15.0 1.0,0.005 2.0,0.009 @@ -411,10 +344,6 @@ See description,See description 20.0,0.002 21.0,0.003 22.0,0.001 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,16.0 1.0,0.005 2.0,0.008 @@ -438,10 +367,6 @@ See description,See description 20.0,0.004 21.0,0.002 22.0,0.002 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,17.0 1.0,0.003 2.0,0.006 @@ -465,10 +390,6 @@ See description,See description 20.0,0.006 21.0,0.004 22.0,0.001 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,18.0 1.0,0.005 2.0,0.009 @@ -492,10 +413,6 @@ See description,See description 20.0,0.01 21.0,0.007 22.0,0.003 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,19.0 1.0,0.002 2.0,0.004 @@ -519,10 +436,6 @@ See description,See description 20.0,0.015 21.0,0.011 22.0,0.005 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,20.0 1.0,0.001 2.0,0.003 @@ -546,10 +459,6 @@ See description,See description 20.0,1.0 21.0,0.017 22.0,0.008 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,21.0 1.0,0.002 2.0,0.004 @@ -573,10 +482,6 @@ See description,See description 20.0,0.017 21.0,1.0 22.0,0.014 - -#: RE,P P --> JET X -#: SQRT(S) [GeV],200.0 -See description,See description -,22.0 1.0,0.001 2.0,0.002 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml index a48e36cbe1..6ff8d3bc4d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -1,4 +1,92 @@ definitions: + sys_0: + description: 0 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_1: + description: 1 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_2: + description: 2 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_3: + description: 3 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_4: + description: 4 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_5: + description: 5 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_6: + description: 6 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_7: + description: 7 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_8: + description: 8 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_9: + description: 9 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_10: + description: 10 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_11: + description: 11 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_12: + description: 12 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_13: + description: 13 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_14: + description: 14 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_15: + description: 15 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_16: + description: 16 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_17: + description: 17 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_18: + description: 18 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_19: + description: 19 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_20: + description: 20 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_21: + description: 21 artificial correlated statistical uncertainty + treatment: ADD + type: CORR stat: description: statistical uncertainty treatment: ADD @@ -10,45 +98,529 @@ definitions: bins: - stat: 0.0015 sys: 0.0003 + sys_0: -1.6448417112301333e-06 + sys_1: 3.0767956744795033e-06 + sys_2: 2.985686421137934e-06 + sys_3: 2.6739400670555545e-06 + sys_4: 1.5799135431026458e-06 + sys_5: 4.469439476545788e-06 + sys_6: 3.5031982026635955e-06 + sys_7: -8.192103049239285e-06 + sys_8: 8.519902585570326e-06 + sys_9: 1.0162143079716163e-05 + sys_10: 5.851109783478681e-06 + sys_11: 1.9163436414823837e-05 + sys_12: 1.1503154098901525e-05 + sys_13: 3.266469386476217e-05 + sys_14: 2.303922686539146e-05 + sys_15: 6.747820260959229e-05 + sys_16: 3.817964657258357e-05 + sys_17: 0.0014256774940655404 + sys_18: 0.00035118617038519697 + sys_19: -0.0002906207220419269 + sys_20: -3.13699619655819e-05 + sys_21: -1.4797025494046162e-05 - stat: 0.0016 sys: 0.0004 + sys_0: -3.4518076796518805e-06 + sys_1: 4.96397343778174e-06 + sys_2: 6.477702387074787e-06 + sys_3: 5.831872404589162e-06 + sys_4: 4.903983464637898e-06 + sys_5: 7.724039432497479e-06 + sys_6: 7.409090510462631e-06 + sys_7: -1.5725599983883505e-05 + sys_8: 1.648520346596191e-05 + sys_9: 1.8430421088323036e-05 + sys_10: 1.2989102745154597e-05 + sys_11: 4.030678459253012e-05 + sys_12: 2.102206802324885e-05 + sys_13: 7.865712901534335e-05 + sys_14: 5.836027217666717e-05 + sys_15: 0.0003342791734870414 + sys_16: 3.573059862965882e-05 + sys_17: -7.565683816981277e-05 + sys_18: 0.0006274657183167754 + sys_19: 0.0002189113700384152 + sys_20: 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Mon, 22 Apr 2024 18:50:41 +0200 Subject: [PATCH 08/98] init 510 correlated data --- .../nnpdf_data/filter_utils/correlations.py | 78 +++++ .../filter_utils/star_2013_510gev.py | 268 ++++++++++++++++++ .../STAR_2013_1JET_510GEV/data.yaml | 15 + .../STAR_2013_1JET_510GEV/kinematics.yaml | 169 +++++++++++ .../STAR_2013_1JET_510GEV/metadata.yaml | 50 ++++ ...jettopologyA-DijettopologyAcorrelation.csv | 86 ++++++ ...jettopologyA-DijettopologyBcorrelation.csv | 164 +++++++++++ ...jettopologyA-DijettopologyCcorrelation.csv | 152 ++++++++++ ...jettopologyA-DijettopologyDcorrelation.csv | 152 ++++++++++ ...jettopologyB-DijettopologyBcorrelation.csv | 99 +++++++ ...jettopologyB-DijettopologyCcorrelation.csv | 164 +++++++++++ ...jettopologyB-DijettopologyDcorrelation.csv | 164 +++++++++++ ...jettopologyC-DijettopologyCcorrelation.csv | 86 ++++++ ...jettopologyC-DijettopologyDcorrelation.csv | 152 ++++++++++ ...jettopologyD-DijettopologyDcorrelation.csv | 86 ++++++ .../STAR_2013_1JET_510GEV/rawdata/Figure3.csv | 54 ++++ .../rawdata/Figure5topologyA.csv | 34 +++ .../rawdata/Figure5topologyB.csv | 36 +++ .../rawdata/Figure5topologyC.csv | 34 +++ .../rawdata/Figure5topologyD.csv | 34 +++ ...Inclusivejet-DijettopologyAcorrelation.csv | 176 ++++++++++++ ...Inclusivejet-DijettopologyBcorrelation.csv | 190 +++++++++++++ ...Inclusivejet-DijettopologyCcorrelation.csv | 176 ++++++++++++ ...Inclusivejet-DijettopologyDcorrelation.csv | 176 ++++++++++++ .../Inclusivejet-Inclusivejetcorrelation.csv | 113 ++++++++ .../STAR_2013_1JET_510GEV/uncertainties.yaml | 268 ++++++++++++++++++ .../STAR_2013_2JET_A_510GEV/data.yaml | 13 + .../STAR_2013_2JET_A_510GEV/kinematics.yaml | 97 +++++++ .../STAR_2013_2JET_A_510GEV/metadata.yaml | 39 +++ .../uncertainties.yaml | 210 ++++++++++++++ .../STAR_2013_2JET_B_510GEV/data.yaml | 14 + .../STAR_2013_2JET_B_510GEV/kinematics.yaml | 105 +++++++ .../STAR_2013_2JET_B_510GEV/metadata.yaml | 39 +++ .../uncertainties.yaml | 240 ++++++++++++++++ .../STAR_2013_2JET_C_510GEV/data.yaml | 13 + .../STAR_2013_2JET_C_510GEV/kinematics.yaml | 97 +++++++ .../STAR_2013_2JET_C_510GEV/metadata.yaml | 39 +++ .../uncertainties.yaml | 210 ++++++++++++++ .../STAR_2013_2JET_D_510GEV/data.yaml | 13 + .../STAR_2013_2JET_D_510GEV/kinematics.yaml | 97 +++++++ .../STAR_2013_2JET_D_510GEV/metadata.yaml | 39 +++ .../uncertainties.yaml | 210 ++++++++++++++ 42 files changed, 4651 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/filter_utils/correlations.py create mode 100644 nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyAcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyBcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyCcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyDcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyBcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyCcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyDcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyCcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyDcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyD-DijettopologyDcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure3.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyA.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyB.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyC.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyD.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyAcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyBcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyCcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyDcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-Inclusivejetcorrelation.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/correlations.py b/nnpdf_data/nnpdf_data/filter_utils/correlations.py new file mode 100644 index 0000000000..8589fd1c6c --- /dev/null +++ b/nnpdf_data/nnpdf_data/filter_utils/correlations.py @@ -0,0 +1,78 @@ +import numpy as np +from numpy.linalg import eig + + +def compute_covmat(corrmat: np.ndarray, unc: np.ndarray, ndata: int) -> list: + """Compute the covariance matrix with the artificial stat uncertainties.""" + # multiply by stat err + cov_mat = np.einsum("i,ij,j->ij", unc, corrmat, unc) + return covmat_to_artunc(ndata, cov_mat.flatten().tolist()) + + +def covmat_to_artunc(ndata, covmat_list, no_of_norm_mat=0): + r"""Convert the covariance matrix to a matrix of + artificial uncertainties. + + NOTE: This function has been taken from validphys.newcommondata_utils. + If those utils get merged in the future, we can replace this. + + Parameters + ---------- + ndata : integer + Number of data points + covmat_list : list + A one dimensional list which contains the elements of + the covariance matrix row by row. Since experimental + datasets provide these matrices in a list form, this + simplifies the implementation for the user. + no_of_norm_mat : int + Normalized covariance matrices may have an eigenvalue + of 0 due to the last data point not being linearly + independent. To allow for this, the user should input + the number of normalized matrices that are being treated + in an instance. For example, if a single covariance matrix + of a normalized distribution is being processed, the input + would be 1. If a covariance matrix contains pertains to + 3 normalized datasets (i.e. cross covmat for 3 + distributions), the input would be 3. The default value is + 0 for when the covariance matrix pertains to an absolute + distribution. + + Returns + ------- + artunc : list + A two dimensional matrix (given as a list of lists) + which contains artificial uncertainties to be added + to the commondata. i^th row (or list) contains the + artificial uncertainties of the i^th data point. + + """ + epsilon = -0.0000000001 + neg_eval_count = 0 + psd_check = True + covmat = np.zeros((ndata, ndata)) + artunc = np.zeros((ndata, ndata)) + for i in range(len(covmat_list)): + a = i // ndata + b = i % ndata + covmat[a][b] = covmat_list[i] + eigval, eigvec = eig(covmat) + for j in range(len(eigval)): + if eigval[j] < epsilon: + psd_check = False + elif eigval[j] > epsilon and eigval[j] <= 0: + neg_eval_count = neg_eval_count + 1 + if neg_eval_count == (no_of_norm_mat + 1): + psd_check = False + elif eigval[j] > 0: + continue + if psd_check == False: + raise ValueError("The covariance matrix is not positive-semidefinite") + else: + for i in range(ndata): + for j in range(ndata): + if eigval[j] < 0: + continue + else: + artunc[i][j] = eigvec[i][j] * np.sqrt(eigval[j]) + return artunc.tolist() diff --git a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py new file mode 100644 index 0000000000..f545e7e45f --- /dev/null +++ b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py @@ -0,0 +1,268 @@ +"""This script provides the common filer to the jet and dijet STAR 2013 datasets. +Files need to be parsed all together as there are correlations provided. +""" +import pandas as pd +import numpy as np +import pathlib +import yaml + +from correlations import compute_covmat + +# values from the paper https://arxiv.org/pdf/2110.11020.pdf +SQRTS = 510 +ETA_ABS = 0.9 +TOPOPLOGY_LIST = ["1JET", "A", "B", "C", "D"] + +HERE = pathlib.Path(__file__).parents[1] +RAWDATA_PATH = HERE / "new_commondata/STAR_2013_1JET_510GEV/rawdata/" + + +def read_1jet_data(): + data_table = pathlib.Path(RAWDATA_PATH / "Figure3.csv") + + with open(data_table, "r", encoding="utf-8") as file: + parton_jet_data = pd.read_csv( + file, delimiter=",", skiprows=lambda x: (x <= 21 or x >= 38) + ) + with open(data_table, "r", encoding="utf-8") as file: + all_data = pd.read_csv(file, delimiter=",", skiprows=37) + + df = pd.DataFrame() + df["pT"] = parton_jet_data[r"Parton Jet $p_{T}$ (GeV/$c$)"] + df["pT_min"] = ( + parton_jet_data[r"Parton Jet $p_{T}$ (GeV/$c$)"] + parton_jet_data["syst -"] + ) + df["pT_max"] = ( + parton_jet_data[r"Parton Jet $p_{T}$ (GeV/$c$)"] + parton_jet_data["syst +"] + ) + df["eta"] = 0.0 + df["eta_min"] = -ETA_ABS + df["eta_max"] = +ETA_ABS + df["sqrts"] = SQRTS + df["ALL"] = all_data[r"Inclusive Jet $A_{LL}$"] + df["stat"] = all_data[r"stat +"] + df["syst"] = all_data[r"syst +"] + + print("1JET data loaded. Npoint: ", len(df)) + return df + + +def read_2jet_data(topology): + data_table = RAWDATA_PATH / f"Figure5topology{topology}.csv" + with open(data_table, "r", encoding="utf-8") as file: + mjj_data = pd.read_csv( + file, delimiter=",", skiprows=lambda x: (x <= 5 or x >= 20) + ) + with open(data_table, "r", encoding="utf-8") as file: + all_data = pd.read_csv(file, delimiter=",", skiprows=20) + + df = pd.DataFrame() + df["mjj"] = mjj_data[r"Parton Dijet $M_{inv}$ (GeV/$c^{2}$)"] + df["mjj_min"] = ( + mjj_data[r"Parton Dijet $M_{inv}$ (GeV/$c^{2}$)"] + mjj_data["syst -"] + ) + df["mjj_max"] = ( + mjj_data[r"Parton Dijet $M_{inv}$ (GeV/$c^{2}$)"] + mjj_data["syst +"] + ) + df["sqrts"] = SQRTS + df["ALL"] = all_data[r"Dijet $A_{LL}$, topology " + topology] + df["stat"] = all_data[r"stat +"] + df["syst"] = all_data[r"syst +"] + + print(f"2JET {topology} data loaded. Npoint: ", len(df)) + return df + + +def get_correlation_label(a): + if a == "1JET": + return "Inclusivejet" + return f"Dijettopology{a}" + + +def upper_triangular_to_symmetric(ut, dim): + """Build a symmetric matrix from the upper diagonal""" + corr = np.zeros((dim, dim)) + last = dim + first = 0 + for i in range(dim): + corr[i, i:] = ut[first:last] + last += dim - i - 1 + first += dim - i + return corr + corr.T - np.eye(dim) + + +def read_correlations(ndata_dict): + """Read the correlation files and build a big matix""" + corr_rows = [] + # loop on block rows + for a, ndata_a in ndata_dict.items(): + label_a = get_correlation_label(a) + la = [a for _ in range(ndata_a)] + corr_row = pd.DataFrame() + # loop on block columns + for b, ndata_b in ndata_dict.items(): + label_b = get_correlation_label(b) + lb = [b for _ in range(ndata_b)] + + # build the block + try: + with open( + RAWDATA_PATH / f"{label_a}-{label_b}correlation.csv", + encoding="utf-8", + ) as file: + corr_df = pd.read_csv(file, delimiter=",", skiprows=6) + if a == b: + corr = upper_triangular_to_symmetric(corr_df.values[:, 2], ndata_a) + else: + corr = corr_df.values[:, 2].reshape((ndata_a, ndata_b)) + except FileNotFoundError: + corr = pd.DataFrame(np.zeros((ndata_a, ndata_b)), index=la, columns=lb) + + corr = pd.DataFrame(corr, index=la, columns=lb) + corr_row = pd.concat([corr_row, corr], axis=1) + corr_rows.append(corr_row) + + tot_corr = pd.concat(corr_rows) + return tot_corr + tot_corr.T - np.eye(np.sum((*ndata_dict.values(),))) + + +def write_1jet_data(df, art_sys, ndata): + STORE_PATH = HERE / "new_commondata/STAR_2013_1JET_510GEV/" + + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + kin_value = { + "pT": { + "min": float(df.loc[i, "pT_min"]), + "mid": float(df.loc[i, "pT"]), + "max": float(df.loc[i, "pT_max"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": { + "min": float(df.loc[i, "eta_min"]), + "mid": float(df.loc[i, "eta"]), + "max": float(df.loc[i, "eta_max"]), + }, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + for i in range(ndata): + e = {} + # add the art sys + for j in range(ndata): + e[f"sys_{j}"] = art_sys[i][j] + e[ + "stat" + ] = 0 # This is set to 0 as the stat unc is correlated and reported in sys_0 + error.append(e) + + error_definition = { + f"sys_{i}": { + "description": f"{i} artificial correlated statistical + systematics uncertainty", + "treatment": "ADD", + "type": "CORR", + } + for i in range(ndata) + } + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +def write_2jet_data(df, topology, art_sys, ndata): + STORE_PATH = HERE / f"new_commondata/STAR_2013_2JET_{topology}_510GEV/" + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + kin_value = { + "mjj": { + "min": float(df.loc[i, "mjj_min"]), + "mid": float(df.loc[i, "mjj"]), + "max": float(df.loc[i, "mjj_max"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + for i in range(ndata): + e = {} + # add the art sys + for j in range(ndata): + e[f"sys_{j}"] = art_sys[i][j] + e["stat"] = float(df.loc[i, "stat"]) + error.append(e) + + error_definition = { + f"sys_{i}": { + "description": f"{i} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": "CORR", + } + for i in range(ndata) + } + error_definition.update( + { + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + } + } + ) + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # load all the data + dfs = {"1JET": read_1jet_data()} + for topo in TOPOPLOGY_LIST[1:]: + dfs[topo] = read_2jet_data(topo) + + # load correlations + ndata_dict = {a: len(b) for a, b in dfs.items()} + correlation_df = read_correlations(ndata_dict) + # from the paper we understand that stat dijet is not correlated + # I-I (stat + sys) | I-D (stat + sys) + # D-I (stat + sys) | D-D (sys) + correlated_unc = np.sqrt( + dfs["1JET"]["syst"] ** 2 + dfs["1JET"]["stat"] ** 2 + ).values.tolist() + for a in TOPOPLOGY_LIST[1:]: + correlated_unc.extend(dfs[a]["syst"].values) + ndata_points = np.sum((*ndata_dict.values(),)) + # decompose uncertainties + art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) + + # write data + cnt = 0 + for topo, df in dfs.items(): + ndata = ndata_dict[topo] + syst = art_sys[cnt:cnt+ndata, cnt:cnt+ndata].tolist() + if topo == "1JET": + write_1jet_data(df, syst, ndata) + else: + write_2jet_data(df, topo, syst, ndata) + cnt += ndata diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/data.yaml new file mode 100644 index 0000000000..1f9f10754d --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/data.yaml @@ -0,0 +1,15 @@ +data_central: +- 0.00626 +- 0.00258 +- 0.00277 +- -0.00075 +- -0.00085 +- 0.00444 +- 0.00308 +- 0.00572 +- 0.01008 +- 0.01033 +- 0.01249 +- 0.01824 +- 0.02205 +- 0.04527 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/kinematics.yaml new file mode 100644 index 0000000000..dd7cb965e2 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/kinematics.yaml @@ -0,0 +1,169 @@ +bins: +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 8.65 + mid: 7.79 + min: 6.93 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 10.209999999999999 + mid: 9.62 + min: 9.03 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 12.14 + mid: 11.67 + min: 11.2 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 14.1 + mid: 13.59 + min: 13.08 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 16.3 + mid: 15.76 + min: 15.219999999999999 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 20.62 + mid: 19.89 + min: 19.16 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 23.49 + mid: 22.68 + min: 21.87 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 26.830000000000002 + mid: 25.94 + min: 25.05 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 30.75 + mid: 29.75 + min: 28.75 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 35.5 + mid: 34.29 + min: 33.08 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 40.99 + mid: 39.59 + min: 38.190000000000005 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 47.28 + mid: 45.76 + min: 44.239999999999995 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 54.9 + mid: 53.17 + min: 51.440000000000005 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 63.32 + mid: 61.37 + min: 59.419999999999995 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml new file mode 100644 index 0000000000..72b51bfebf --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml @@ -0,0 +1,50 @@ +setname: "STAR_2013_1JET_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "$A_{LL}$ as function of $p_T$", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: JET_POL + ndata: 14 + tables: [3] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, eta] + plotting: + dataset_label: "STAR 510 TeV (2013) 1-JET $A_{LL}$" + kinematics_override: identity + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_1JET_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyAcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyAcorrelation.csv new file mode 100644 index 0000000000..2f4590b1e3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyAcorrelation.csv @@ -0,0 +1,86 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t11 +#: name: Dijet topology A correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) for forward-forward dijet measurements (topology A). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijA.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology A - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology A - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetA +15.74,15.74,1.0 +15.74,18.5,0.016 +15.74,21.96,0.019 +15.74,26.17,0.021 +15.74,31.63,0.019 +15.74,37.8,0.015 +15.74,44.75,0.014 +15.74,53.31,0.01 +15.74,63.64,0.007 +15.74,75.32,0.005 +15.74,89.66,0.003 +15.74,105.63,0.002 +18.5,18.5,1.0 +18.5,21.96,0.073 +18.5,26.17,0.079 +18.5,31.63,0.073 +18.5,37.8,0.058 +18.5,44.75,0.052 +18.5,53.31,0.039 +18.5,63.64,0.028 +18.5,75.32,0.017 +18.5,89.66,0.011 +18.5,105.63,0.006 +21.96,21.96,1.0 +21.96,26.17,0.042 +21.96,31.63,0.039 +21.96,37.8,0.031 +21.96,44.75,0.028 +21.96,53.31,0.021 +21.96,63.64,0.015 +21.96,75.32,0.009 +21.96,89.66,0.006 +21.96,105.63,0.003 +26.17,26.17,1.0 +26.17,31.63,0.052 +26.17,37.8,0.041 +26.17,44.75,0.037 +26.17,53.31,0.027 +26.17,63.64,0.02 +26.17,75.32,0.012 +26.17,89.66,0.008 +26.17,105.63,0.004 +31.63,31.63,1.0 +31.63,37.8,0.039 +31.63,44.75,0.035 +31.63,53.31,0.026 +31.63,63.64,0.019 +31.63,75.32,0.012 +31.63,89.66,0.008 +31.63,105.63,0.004 +37.8,37.8,1.0 +37.8,44.75,0.029 +37.8,53.31,0.022 +37.8,63.64,0.015 +37.8,75.32,0.01 +37.8,89.66,0.006 +37.8,105.63,0.004 +44.75,44.75,1.0 +44.75,53.31,0.021 +44.75,63.64,0.015 +44.75,75.32,0.009 +44.75,89.66,0.006 +44.75,105.63,0.003 +53.31,53.31,1.0 +53.31,63.64,0.013 +53.31,75.32,0.008 +53.31,89.66,0.005 +53.31,105.63,0.003 +63.64,63.64,1.0 +63.64,75.32,0.01 +63.64,89.66,0.006 +63.64,105.63,0.003 +75.32,75.32,1.0 +75.32,89.66,0.007 +75.32,105.63,0.004 +89.66,89.66,1.0 +89.66,105.63,0.004 +105.63,105.63,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyBcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyBcorrelation.csv new file mode 100644 index 0000000000..2a74b4f314 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyBcorrelation.csv @@ -0,0 +1,164 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t12 +#: name: Dijet topology A - Dijet topology B correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) coupling forward-forward dijet measurements (topology A) with forward-central dijet measurements (topology B). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijA-B.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology A - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology B - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetA-DijetB +15.74,15.49,0.008 +15.74,18.48,0.018 +15.74,22.33,0.022 +15.74,26.67,0.024 +15.74,32.16,0.022 +15.74,38.59,0.018 +15.74,45.66,0.016 +15.74,54.49,0.012 +15.74,65.02,0.009 +15.74,77.16,0.006 +15.74,91.33,0.004 +15.74,109.2,0.002 +15.74,129.75,0.001 +18.5,15.49,0.024 +18.5,18.48,0.055 +18.5,22.33,0.065 +18.5,26.67,0.072 +18.5,32.16,0.068 +18.5,38.59,0.054 +18.5,45.66,0.049 +18.5,54.49,0.037 +18.5,65.02,0.027 +18.5,77.16,0.017 +18.5,91.33,0.011 +18.5,109.2,0.006 +18.5,129.75,0.003 +21.96,15.49,0.02 +21.96,18.48,0.044 +21.96,22.33,0.053 +21.96,26.67,0.059 +21.96,32.16,0.055 +21.96,38.59,0.044 +21.96,45.66,0.04 +21.96,54.49,0.03 +21.96,65.02,0.022 +21.96,77.16,0.014 +21.96,91.33,0.009 +21.96,109.2,0.005 +21.96,129.75,0.003 +26.17,15.49,0.024 +26.17,18.48,0.055 +26.17,22.33,0.066 +26.17,26.67,0.073 +26.17,32.16,0.068 +26.17,38.59,0.055 +26.17,45.66,0.049 +26.17,54.49,0.037 +26.17,65.02,0.027 +26.17,77.16,0.017 +26.17,91.33,0.011 +26.17,109.2,0.006 +26.17,129.75,0.003 +31.63,15.49,0.024 +31.63,18.48,0.054 +31.63,22.33,0.065 +31.63,26.67,0.072 +31.63,32.16,0.067 +31.63,38.59,0.054 +31.63,45.66,0.049 +31.63,54.49,0.036 +31.63,65.02,0.026 +31.63,77.16,0.017 +31.63,91.33,0.011 +31.63,109.2,0.006 +31.63,129.75,0.003 +37.8,15.49,0.02 +37.8,18.48,0.046 +37.8,22.33,0.055 +37.8,26.67,0.061 +37.8,32.16,0.057 +37.8,38.59,0.046 +37.8,45.66,0.041 +37.8,54.49,0.031 +37.8,65.02,0.023 +37.8,77.16,0.014 +37.8,91.33,0.009 +37.8,109.2,0.005 +37.8,129.75,0.003 +44.75,15.49,0.02 +44.75,18.48,0.045 +44.75,22.33,0.054 +44.75,26.67,0.06 +44.75,32.16,0.056 +44.75,38.59,0.045 +44.75,45.66,0.041 +44.75,54.49,0.03 +44.75,65.02,0.022 +44.75,77.16,0.014 +44.75,91.33,0.009 +44.75,109.2,0.005 +44.75,129.75,0.003 +53.31,15.49,0.019 +53.31,18.48,0.042 +53.31,22.33,0.051 +53.31,26.67,0.056 +53.31,32.16,0.052 +53.31,38.59,0.042 +53.31,45.66,0.038 +53.31,54.49,0.028 +53.31,65.02,0.021 +53.31,77.16,0.013 +53.31,91.33,0.009 +53.31,109.2,0.005 +53.31,129.75,0.003 +63.64,15.49,0.02 +63.64,18.48,0.045 +63.64,22.33,0.055 +63.64,26.67,0.06 +63.64,32.16,0.056 +63.64,38.59,0.045 +63.64,45.66,0.041 +63.64,54.49,0.031 +63.64,65.02,0.022 +63.64,77.16,0.014 +63.64,91.33,0.009 +63.64,109.2,0.005 +63.64,129.75,0.003 +75.32,15.49,0.023 +75.32,18.48,0.051 +75.32,22.33,0.062 +75.32,26.67,0.068 +75.32,32.16,0.064 +75.32,38.59,0.051 +75.32,45.66,0.046 +75.32,54.49,0.035 +75.32,65.02,0.025 +75.32,77.16,0.016 +75.32,91.33,0.01 +75.32,109.2,0.006 +75.32,129.75,0.003 +89.66,15.49,0.022 +89.66,18.48,0.049 +89.66,22.33,0.058 +89.66,26.67,0.064 +89.66,32.16,0.06 +89.66,38.59,0.048 +89.66,45.66,0.043 +89.66,54.49,0.033 +89.66,65.02,0.024 +89.66,77.16,0.015 +89.66,91.33,0.01 +89.66,109.2,0.006 +89.66,129.75,0.003 +105.63,15.49,0.019 +105.63,18.48,0.043 +105.63,22.33,0.052 +105.63,26.67,0.057 +105.63,32.16,0.053 +105.63,38.59,0.043 +105.63,45.66,0.039 +105.63,54.49,0.029 +105.63,65.02,0.021 +105.63,77.16,0.013 +105.63,91.33,0.009 +105.63,109.2,0.005 +105.63,129.75,0.003 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyCcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyCcorrelation.csv new file mode 100644 index 0000000000..1e6f4a26a6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyCcorrelation.csv @@ -0,0 +1,152 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t13 +#: name: Dijet topology A - Dijet topology C correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) coupling forward-forward dijet measurements (topology A) with forward-central dijet measurements (topology C). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijA-C.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology A - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology C - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetA-DijetC +15.74,15.72,0.009 +15.74,18.9,0.018 +15.74,22.24,0.022 +15.74,27.14,0.023 +15.74,33.03,0.022 +15.74,39.35,0.017 +15.74,46.62,0.015 +15.74,55.74,0.012 +15.74,66.39,0.008 +15.74,78.97,0.005 +15.74,94.22,0.003 +15.74,111.48,0.002 +18.5,15.72,0.047 +18.5,18.9,0.096 +18.5,22.24,0.116 +18.5,27.14,0.125 +18.5,33.03,0.115 +18.5,39.35,0.092 +18.5,46.62,0.082 +18.5,55.74,0.061 +18.5,66.39,0.044 +18.5,78.97,0.028 +18.5,94.22,0.018 +18.5,111.48,0.011 +21.96,15.72,0.013 +21.96,18.9,0.027 +21.96,22.24,0.032 +21.96,27.14,0.035 +21.96,33.03,0.032 +21.96,39.35,0.025 +21.96,46.62,0.023 +21.96,55.74,0.017 +21.96,66.39,0.012 +21.96,78.97,0.008 +21.96,94.22,0.005 +21.96,111.48,0.003 +26.17,15.72,0.022 +26.17,18.9,0.046 +26.17,22.24,0.055 +26.17,27.14,0.059 +26.17,33.03,0.055 +26.17,39.35,0.044 +26.17,46.62,0.039 +26.17,55.74,0.029 +26.17,66.39,0.021 +26.17,78.97,0.013 +26.17,94.22,0.009 +26.17,111.48,0.005 +31.63,15.72,0.02 +31.63,18.9,0.041 +31.63,22.24,0.049 +31.63,27.14,0.053 +31.63,33.03,0.049 +31.63,39.35,0.039 +31.63,46.62,0.035 +31.63,55.74,0.026 +31.63,66.39,0.019 +31.63,78.97,0.012 +31.63,94.22,0.008 +31.63,111.48,0.004 +37.8,15.72,0.016 +37.8,18.9,0.033 +37.8,22.24,0.039 +37.8,27.14,0.042 +37.8,33.03,0.039 +37.8,39.35,0.031 +37.8,46.62,0.028 +37.8,55.74,0.021 +37.8,66.39,0.015 +37.8,78.97,0.01 +37.8,94.22,0.006 +37.8,111.48,0.004 +44.75,15.72,0.015 +44.75,18.9,0.031 +44.75,22.24,0.038 +44.75,27.14,0.041 +44.75,33.03,0.038 +44.75,39.35,0.03 +44.75,46.62,0.027 +44.75,55.74,0.02 +44.75,66.39,0.014 +44.75,78.97,0.009 +44.75,94.22,0.006 +44.75,111.48,0.003 +53.31,15.72,0.014 +53.31,18.9,0.029 +53.31,22.24,0.035 +53.31,27.14,0.038 +53.31,33.03,0.035 +53.31,39.35,0.028 +53.31,46.62,0.025 +53.31,55.74,0.019 +53.31,66.39,0.013 +53.31,78.97,0.009 +53.31,94.22,0.006 +53.31,111.48,0.003 +63.64,15.72,0.016 +63.64,18.9,0.034 +63.64,22.24,0.04 +63.64,27.14,0.044 +63.64,33.03,0.04 +63.64,39.35,0.032 +63.64,46.62,0.029 +63.64,55.74,0.021 +63.64,66.39,0.015 +63.64,78.97,0.01 +63.64,94.22,0.006 +63.64,111.48,0.004 +75.32,15.72,0.021 +75.32,18.9,0.043 +75.32,22.24,0.052 +75.32,27.14,0.056 +75.32,33.03,0.051 +75.32,39.35,0.041 +75.32,46.62,0.037 +75.32,55.74,0.027 +75.32,66.39,0.02 +75.32,78.97,0.013 +75.32,94.22,0.008 +75.32,111.48,0.005 +89.66,15.72,0.02 +89.66,18.9,0.04 +89.66,22.24,0.049 +89.66,27.14,0.052 +89.66,33.03,0.048 +89.66,39.35,0.039 +89.66,46.62,0.035 +89.66,55.74,0.026 +89.66,66.39,0.019 +89.66,78.97,0.012 +89.66,94.22,0.008 +89.66,111.48,0.004 +105.63,15.72,0.021 +105.63,18.9,0.044 +105.63,22.24,0.053 +105.63,27.14,0.057 +105.63,33.03,0.052 +105.63,39.35,0.042 +105.63,46.62,0.037 +105.63,55.74,0.028 +105.63,66.39,0.02 +105.63,78.97,0.013 +105.63,94.22,0.008 +105.63,111.48,0.005 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyDcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyDcorrelation.csv new file mode 100644 index 0000000000..ba66cb31db --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyA-DijettopologyDcorrelation.csv @@ -0,0 +1,152 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t14 +#: name: Dijet topology A - Dijet topology D correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) coupling forward-forward dijet measurements (topology A) with forward-central dijet measurements (topology D). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijA-D.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology A - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology C - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetA-DijetD +15.74,18.2,0.029 +15.74,21.67,0.039 +15.74,26.12,0.044 +15.74,31.42,0.043 +15.74,37.33,0.036 +15.74,44.6,0.033 +15.74,53.61,0.025 +15.74,63.38,0.019 +15.74,75.52,0.012 +15.74,89.6,0.008 +15.74,106.63,0.005 +15.74,127.17,0.003 +18.5,18.2,0.062 +18.5,21.67,0.084 +18.5,26.12,0.096 +18.5,31.42,0.094 +18.5,37.33,0.078 +18.5,44.6,0.071 +18.5,53.61,0.054 +18.5,63.38,0.04 +18.5,75.52,0.026 +18.5,89.6,0.017 +18.5,106.63,0.01 +18.5,127.17,0.005 +21.96,18.2,0.026 +21.96,21.67,0.035 +21.96,26.12,0.041 +21.96,31.42,0.04 +21.96,37.33,0.033 +21.96,44.6,0.03 +21.96,53.61,0.023 +21.96,63.38,0.017 +21.96,75.52,0.011 +21.96,89.6,0.007 +21.96,106.63,0.004 +21.96,127.17,0.002 +26.17,18.2,0.067 +26.17,21.67,0.092 +26.17,26.12,0.105 +26.17,31.42,0.103 +26.17,37.33,0.084 +26.17,44.6,0.077 +26.17,53.61,0.059 +26.17,63.38,0.044 +26.17,75.52,0.029 +26.17,89.6,0.019 +26.17,106.63,0.011 +26.17,127.17,0.006 +31.63,18.2,0.058 +31.63,21.67,0.078 +31.63,26.12,0.09 +31.63,31.42,0.088 +31.63,37.33,0.072 +31.63,44.6,0.066 +31.63,53.61,0.051 +31.63,63.38,0.038 +31.63,75.52,0.025 +31.63,89.6,0.016 +31.63,106.63,0.01 +31.63,127.17,0.005 +37.8,18.2,0.043 +37.8,21.67,0.058 +37.8,26.12,0.067 +37.8,31.42,0.065 +37.8,37.33,0.054 +37.8,44.6,0.049 +37.8,53.61,0.038 +37.8,63.38,0.028 +37.8,75.52,0.018 +37.8,89.6,0.012 +37.8,106.63,0.007 +37.8,127.17,0.004 +44.75,18.2,0.038 +44.75,21.67,0.052 +44.75,26.12,0.059 +44.75,31.42,0.058 +44.75,37.33,0.048 +44.75,44.6,0.044 +44.75,53.61,0.034 +44.75,63.38,0.025 +44.75,75.52,0.016 +44.75,89.6,0.011 +44.75,106.63,0.006 +44.75,127.17,0.003 +53.31,18.2,0.032 +53.31,21.67,0.044 +53.31,26.12,0.05 +53.31,31.42,0.049 +53.31,37.33,0.041 +53.31,44.6,0.037 +53.31,53.61,0.028 +53.31,63.38,0.021 +53.31,75.52,0.014 +53.31,89.6,0.009 +53.31,106.63,0.005 +53.31,127.17,0.003 +63.64,18.2,0.031 +63.64,21.67,0.042 +63.64,26.12,0.048 +63.64,31.42,0.047 +63.64,37.33,0.038 +63.64,44.6,0.035 +63.64,53.61,0.027 +63.64,63.38,0.02 +63.64,75.52,0.013 +63.64,89.6,0.009 +63.64,106.63,0.005 +63.64,127.17,0.003 +75.32,18.2,0.032 +75.32,21.67,0.043 +75.32,26.12,0.049 +75.32,31.42,0.048 +75.32,37.33,0.04 +75.32,44.6,0.036 +75.32,53.61,0.028 +75.32,63.38,0.021 +75.32,75.52,0.014 +75.32,89.6,0.009 +75.32,106.63,0.005 +75.32,127.17,0.003 +89.66,18.2,0.03 +89.66,21.67,0.041 +89.66,26.12,0.047 +89.66,31.42,0.046 +89.66,37.33,0.038 +89.66,44.6,0.034 +89.66,53.61,0.026 +89.66,63.38,0.02 +89.66,75.52,0.013 +89.66,89.6,0.008 +89.66,106.63,0.005 +89.66,127.17,0.003 +105.63,18.2,0.028 +105.63,21.67,0.038 +105.63,26.12,0.044 +105.63,31.42,0.043 +105.63,37.33,0.035 +105.63,44.6,0.032 +105.63,53.61,0.025 +105.63,63.38,0.018 +105.63,75.52,0.012 +105.63,89.6,0.008 +105.63,106.63,0.005 +105.63,127.17,0.002 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyBcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyBcorrelation.csv new file mode 100644 index 0000000000..b01d7a8276 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyBcorrelation.csv @@ -0,0 +1,99 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t15 +#: name: Dijet topology B correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) for forward-forward dijet measurements (topology B). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijB.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology B - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology B - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetB +15.49,15.49,1.0 +15.49,18.48,0.02 +15.49,22.33,0.024 +15.49,26.67,0.027 +15.49,32.16,0.025 +15.49,38.59,0.021 +15.49,45.66,0.019 +15.49,54.49,0.014 +15.49,65.02,0.01 +15.49,77.16,0.007 +15.49,91.33,0.004 +15.49,109.2,0.003 +15.49,129.75,0.001 +18.48,18.48,1.0 +18.48,22.33,0.059 +18.48,26.67,0.066 +18.48,32.16,0.062 +18.48,38.59,0.051 +18.48,45.66,0.046 +18.48,54.49,0.035 +18.48,65.02,0.026 +18.48,77.16,0.017 +18.48,91.33,0.011 +18.48,109.2,0.007 +18.48,129.75,0.004 +22.33,22.33,1.0 +22.33,26.67,0.08 +22.33,32.16,0.076 +22.33,38.59,0.061 +22.33,45.66,0.056 +22.33,54.49,0.042 +22.33,65.02,0.031 +22.33,77.16,0.02 +22.33,91.33,0.013 +22.33,109.2,0.008 +22.33,129.75,0.004 +26.67,26.67,1.0 +26.67,32.16,0.089 +26.67,38.59,0.072 +26.67,45.66,0.065 +26.67,54.49,0.05 +26.67,65.02,0.036 +26.67,77.16,0.024 +26.67,91.33,0.016 +26.67,109.2,0.009 +26.67,129.75,0.005 +32.16,32.16,1.0 +32.16,38.59,0.074 +32.16,45.66,0.067 +32.16,54.49,0.051 +32.16,65.02,0.037 +32.16,77.16,0.024 +32.16,91.33,0.016 +32.16,109.2,0.01 +32.16,129.75,0.005 +38.59,38.59,1.0 +38.59,45.66,0.058 +38.59,54.49,0.044 +38.59,65.02,0.033 +38.59,77.16,0.021 +38.59,91.33,0.014 +38.59,109.2,0.008 +38.59,129.75,0.004 +45.66,45.66,1.0 +45.66,54.49,0.043 +45.66,65.02,0.032 +45.66,77.16,0.021 +45.66,91.33,0.014 +45.66,109.2,0.008 +45.66,129.75,0.004 +54.49,54.49,1.0 +54.49,65.02,0.03 +54.49,77.16,0.019 +54.49,91.33,0.013 +54.49,109.2,0.008 +54.49,129.75,0.004 +65.02,65.02,1.0 +65.02,77.16,0.021 +65.02,91.33,0.014 +65.02,109.2,0.008 +65.02,129.75,0.004 +77.16,77.16,1.0 +77.16,91.33,0.014 +77.16,109.2,0.009 +77.16,129.75,0.005 +91.33,91.33,1.0 +91.33,109.2,0.008 +91.33,129.75,0.004 +109.2,109.2,1.0 +109.2,129.75,0.003 +129.75,129.75,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyCcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyCcorrelation.csv new file mode 100644 index 0000000000..3002182748 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyCcorrelation.csv @@ -0,0 +1,164 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t16 +#: name: Dijet topology B - Dijet topology C correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) coupling forward-forward dijet measurements (topology B) with forward-central dijet measurements (topology C). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijB-C.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology B - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology C - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetB-DijetC +15.49,15.72,0.009 +15.49,18.9,0.02 +15.49,22.24,0.024 +15.49,27.14,0.027 +15.49,33.03,0.025 +15.49,39.35,0.02 +15.49,46.62,0.018 +15.49,55.74,0.014 +15.49,66.39,0.01 +15.49,78.97,0.006 +15.49,94.22,0.004 +15.49,111.48,0.003 +18.48,15.72,0.039 +18.48,18.9,0.086 +18.48,22.24,0.105 +18.48,27.14,0.115 +18.48,33.03,0.107 +18.48,39.35,0.086 +18.48,46.62,0.078 +18.48,55.74,0.059 +18.48,66.39,0.043 +18.48,78.97,0.028 +18.48,94.22,0.018 +18.48,111.48,0.011 +22.33,15.72,0.016 +22.33,18.9,0.036 +22.33,22.24,0.044 +22.33,27.14,0.048 +22.33,33.03,0.045 +22.33,39.35,0.036 +22.33,46.62,0.032 +22.33,55.74,0.024 +22.33,66.39,0.018 +22.33,78.97,0.011 +22.33,94.22,0.008 +22.33,111.48,0.004 +26.67,15.72,0.026 +26.67,18.9,0.057 +26.67,22.24,0.07 +26.67,27.14,0.077 +26.67,33.03,0.072 +26.67,39.35,0.058 +26.67,46.62,0.052 +26.67,55.74,0.039 +26.67,66.39,0.029 +26.67,78.97,0.018 +26.67,94.22,0.012 +26.67,111.48,0.007 +32.16,15.72,0.024 +32.16,18.9,0.053 +32.16,22.24,0.065 +32.16,27.14,0.071 +32.16,33.03,0.066 +32.16,39.35,0.053 +32.16,46.62,0.048 +32.16,55.74,0.036 +32.16,66.39,0.026 +32.16,78.97,0.017 +32.16,94.22,0.011 +32.16,111.48,0.007 +38.59,15.72,0.02 +38.59,18.9,0.044 +38.59,22.24,0.053 +38.59,27.14,0.058 +38.59,33.03,0.055 +38.59,39.35,0.044 +38.59,46.62,0.039 +38.59,55.74,0.03 +38.59,66.39,0.022 +38.59,78.97,0.014 +38.59,94.22,0.009 +38.59,111.48,0.005 +45.66,15.72,0.019 +45.66,18.9,0.043 +45.66,22.24,0.053 +45.66,27.14,0.058 +45.66,33.03,0.054 +45.66,39.35,0.044 +45.66,46.62,0.039 +45.66,55.74,0.029 +45.66,66.39,0.022 +45.66,78.97,0.014 +45.66,94.22,0.009 +45.66,111.48,0.005 +54.49,15.72,0.018 +54.49,18.9,0.041 +54.49,22.24,0.049 +54.49,27.14,0.054 +54.49,33.03,0.051 +54.49,39.35,0.041 +54.49,46.62,0.037 +54.49,55.74,0.028 +54.49,66.39,0.02 +54.49,78.97,0.013 +54.49,94.22,0.009 +54.49,111.48,0.005 +65.02,15.72,0.02 +65.02,18.9,0.045 +65.02,22.24,0.055 +65.02,27.14,0.06 +65.02,33.03,0.057 +65.02,39.35,0.045 +65.02,46.62,0.041 +65.02,55.74,0.031 +65.02,66.39,0.022 +65.02,78.97,0.015 +65.02,94.22,0.01 +65.02,111.48,0.006 +77.16,15.72,0.024 +77.16,18.9,0.053 +77.16,22.24,0.065 +77.16,27.14,0.071 +77.16,33.03,0.067 +77.16,39.35,0.054 +77.16,46.62,0.048 +77.16,55.74,0.036 +77.16,66.39,0.027 +77.16,78.97,0.017 +77.16,94.22,0.011 +77.16,111.48,0.007 +91.33,15.72,0.021 +91.33,18.9,0.046 +91.33,22.24,0.057 +91.33,27.14,0.062 +91.33,33.03,0.058 +91.33,39.35,0.047 +91.33,46.62,0.042 +91.33,55.74,0.032 +91.33,66.39,0.023 +91.33,78.97,0.015 +91.33,94.22,0.01 +91.33,111.48,0.006 +109.2,15.72,0.019 +109.2,18.9,0.042 +109.2,22.24,0.051 +109.2,27.14,0.056 +109.2,33.03,0.053 +109.2,39.35,0.042 +109.2,46.62,0.038 +109.2,55.74,0.029 +109.2,66.39,0.021 +109.2,78.97,0.014 +109.2,94.22,0.009 +109.2,111.48,0.005 +129.75,15.72,0.057 +129.75,18.9,0.126 +129.75,22.24,0.154 +129.75,27.14,0.169 +129.75,33.03,0.158 +129.75,39.35,0.127 +129.75,46.62,0.114 +129.75,55.74,0.086 +129.75,66.39,0.063 +129.75,78.97,0.041 +129.75,94.22,0.027 +129.75,111.48,0.016 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyDcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyDcorrelation.csv new file mode 100644 index 0000000000..9312d55d2b --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyB-DijettopologyDcorrelation.csv @@ -0,0 +1,164 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t17 +#: name: Dijet topology B - Dijet topology D correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) coupling forward-forward dijet measurements (topology B) with forward-central dijet measurements (topology D). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijB-D.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology B - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology D - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetB-DijetD +15.49,18.2,0.031 +15.49,21.67,0.043 +15.49,26.12,0.05 +15.49,31.42,0.05 +15.49,37.33,0.041 +15.49,44.6,0.038 +15.49,53.61,0.03 +15.49,63.38,0.022 +15.49,75.52,0.015 +15.49,89.6,0.01 +15.49,106.63,0.006 +15.49,127.17,0.003 +18.48,18.2,0.055 +18.48,21.67,0.076 +18.48,26.12,0.088 +18.48,31.42,0.087 +18.48,37.33,0.072 +18.48,44.6,0.066 +18.48,53.61,0.052 +18.48,63.38,0.039 +18.48,75.52,0.026 +18.48,89.6,0.017 +18.48,106.63,0.01 +18.48,127.17,0.006 +22.33,18.2,0.035 +22.33,21.67,0.048 +22.33,26.12,0.055 +22.33,31.42,0.055 +22.33,37.33,0.046 +22.33,44.6,0.042 +22.33,53.61,0.033 +22.33,63.38,0.025 +22.33,75.52,0.016 +22.33,89.6,0.011 +22.33,106.63,0.007 +22.33,127.17,0.004 +26.67,18.2,0.084 +26.67,21.67,0.116 +26.67,26.12,0.134 +26.67,31.42,0.133 +26.67,37.33,0.111 +26.67,44.6,0.102 +26.67,53.61,0.079 +26.67,63.38,0.06 +26.67,75.52,0.039 +26.67,89.6,0.027 +26.67,106.63,0.016 +26.67,127.17,0.009 +32.16,18.2,0.075 +32.16,21.67,0.103 +32.16,26.12,0.119 +32.16,31.42,0.118 +32.16,37.33,0.098 +32.16,44.6,0.09 +32.16,53.61,0.07 +32.16,63.38,0.053 +32.16,75.52,0.035 +32.16,89.6,0.024 +32.16,106.63,0.014 +32.16,127.17,0.008 +38.59,18.2,0.057 +38.59,21.67,0.079 +38.59,26.12,0.091 +38.59,31.42,0.09 +38.59,37.33,0.075 +38.59,44.6,0.069 +38.59,53.61,0.054 +38.59,63.38,0.04 +38.59,75.52,0.027 +38.59,89.6,0.018 +38.59,106.63,0.011 +38.59,127.17,0.006 +45.66,18.2,0.052 +45.66,21.67,0.072 +45.66,26.12,0.083 +45.66,31.42,0.083 +45.66,37.33,0.069 +45.66,44.6,0.063 +45.66,53.61,0.049 +45.66,63.38,0.037 +45.66,75.52,0.024 +45.66,89.6,0.016 +45.66,106.63,0.01 +45.66,127.17,0.005 +54.49,18.2,0.044 +54.49,21.67,0.062 +54.49,26.12,0.071 +54.49,31.42,0.07 +54.49,37.33,0.058 +54.49,44.6,0.054 +54.49,53.61,0.042 +54.49,63.38,0.032 +54.49,75.52,0.021 +54.49,89.6,0.014 +54.49,106.63,0.008 +54.49,127.17,0.005 +65.02,18.2,0.041 +65.02,21.67,0.057 +65.02,26.12,0.065 +65.02,31.42,0.065 +65.02,37.33,0.054 +65.02,44.6,0.05 +65.02,53.61,0.039 +65.02,63.38,0.029 +65.02,75.52,0.019 +65.02,89.6,0.013 +65.02,106.63,0.008 +65.02,127.17,0.004 +77.16,18.2,0.039 +77.16,21.67,0.055 +77.16,26.12,0.063 +77.16,31.42,0.062 +77.16,37.33,0.052 +77.16,44.6,0.048 +77.16,53.61,0.037 +77.16,63.38,0.028 +77.16,75.52,0.018 +77.16,89.6,0.012 +77.16,106.63,0.007 +77.16,127.17,0.004 +91.33,18.2,0.034 +91.33,21.67,0.048 +91.33,26.12,0.055 +91.33,31.42,0.055 +91.33,37.33,0.045 +91.33,44.6,0.042 +91.33,53.61,0.032 +91.33,63.38,0.024 +91.33,75.52,0.016 +91.33,89.6,0.011 +91.33,106.63,0.007 +91.33,127.17,0.004 +109.2,18.2,0.027 +109.2,21.67,0.037 +109.2,26.12,0.043 +109.2,31.42,0.043 +109.2,37.33,0.035 +109.2,44.6,0.033 +109.2,53.61,0.025 +109.2,63.38,0.019 +109.2,75.52,0.013 +109.2,89.6,0.008 +109.2,106.63,0.005 +109.2,127.17,0.003 +129.75,18.2,0.063 +129.75,21.67,0.087 +129.75,26.12,0.1 +129.75,31.42,0.099 +129.75,37.33,0.082 +129.75,44.6,0.076 +129.75,53.61,0.059 +129.75,63.38,0.044 +129.75,75.52,0.029 +129.75,89.6,0.02 +129.75,106.63,0.012 +129.75,127.17,0.007 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyCcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyCcorrelation.csv new file mode 100644 index 0000000000..91b0628ba6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyCcorrelation.csv @@ -0,0 +1,86 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t18 +#: name: Dijet topology C correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) for forward-forward dijet measurements (topology C). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijC.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology C - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology C - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetC +15.72,15.72,1.0 +15.72,18.9,0.02 +15.72,22.24,0.025 +15.72,27.14,0.026 +15.72,33.03,0.024 +15.72,39.35,0.019 +15.72,46.62,0.017 +15.72,55.74,0.013 +15.72,66.39,0.009 +15.72,78.97,0.006 +15.72,94.22,0.004 +15.72,111.48,0.002 +18.9,18.9,1.0 +18.9,22.24,0.183 +18.9,27.14,0.196 +18.9,33.03,0.181 +18.9,39.35,0.145 +18.9,46.62,0.13 +18.9,55.74,0.097 +18.9,66.39,0.07 +18.9,78.97,0.045 +18.9,94.22,0.03 +18.9,111.48,0.018 +22.24,22.24,1.0 +22.24,27.14,0.028 +22.24,33.03,0.026 +22.24,39.35,0.021 +22.24,46.62,0.019 +22.24,55.74,0.014 +22.24,66.39,0.01 +22.24,78.97,0.006 +22.24,94.22,0.004 +22.24,111.48,0.003 +27.14,27.14,1.0 +27.14,33.03,0.058 +27.14,39.35,0.046 +27.14,46.62,0.041 +27.14,55.74,0.031 +27.14,66.39,0.022 +27.14,78.97,0.014 +27.14,94.22,0.009 +27.14,111.48,0.006 +33.03,33.03,1.0 +33.03,39.35,0.038 +33.03,46.62,0.034 +33.03,55.74,0.025 +33.03,66.39,0.018 +33.03,78.97,0.012 +33.03,94.22,0.008 +33.03,111.48,0.005 +39.35,39.35,1.0 +39.35,46.62,0.027 +39.35,55.74,0.02 +39.35,66.39,0.014 +39.35,78.97,0.009 +39.35,94.22,0.006 +39.35,111.48,0.004 +46.62,46.62,1.0 +46.62,55.74,0.019 +46.62,66.39,0.014 +46.62,78.97,0.009 +46.62,94.22,0.006 +46.62,111.48,0.004 +55.74,55.74,1.0 +55.74,66.39,0.013 +55.74,78.97,0.008 +55.74,94.22,0.006 +55.74,111.48,0.003 +66.39,66.39,1.0 +66.39,78.97,0.01 +66.39,94.22,0.007 +66.39,111.48,0.004 +78.97,78.97,1.0 +78.97,94.22,0.009 +78.97,111.48,0.005 +94.22,94.22,1.0 +94.22,111.48,0.005 +111.48,111.48,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyDcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyDcorrelation.csv new file mode 100644 index 0000000000..2ae48ee0d0 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyC-DijettopologyDcorrelation.csv @@ -0,0 +1,152 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t19 +#: name: Dijet topology C - Dijet topology D correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) coupling forward-forward dijet measurements (topology C) with forward-central dijet measurements (topology D). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijC-D.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology C - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology D - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetC-DijetD +15.72,18.2,0.032 +15.72,21.67,0.044 +15.72,26.12,0.05 +15.72,31.42,0.049 +15.72,37.33,0.04 +15.72,44.6,0.037 +15.72,53.61,0.028 +15.72,63.38,0.021 +15.72,75.52,0.014 +15.72,89.6,0.009 +15.72,106.63,0.006 +15.72,127.17,0.003 +18.9,18.2,0.097 +18.9,21.67,0.134 +18.9,26.12,0.152 +18.9,31.42,0.15 +18.9,37.33,0.123 +18.9,44.6,0.113 +18.9,53.61,0.087 +18.9,63.38,0.065 +18.9,75.52,0.043 +18.9,89.6,0.029 +18.9,106.63,0.017 +18.9,127.17,0.01 +22.24,18.2,0.021 +22.24,21.67,0.029 +22.24,26.12,0.033 +22.24,31.42,0.032 +22.24,37.33,0.027 +22.24,44.6,0.024 +22.24,53.61,0.019 +22.24,63.38,0.014 +22.24,75.52,0.009 +22.24,89.6,0.006 +22.24,106.63,0.004 +22.24,127.17,0.002 +27.14,18.2,0.07 +27.14,21.67,0.097 +27.14,26.12,0.11 +27.14,31.42,0.108 +27.14,37.33,0.089 +27.14,44.6,0.082 +27.14,53.61,0.063 +27.14,63.38,0.047 +27.14,75.52,0.031 +27.14,89.6,0.021 +27.14,106.63,0.012 +27.14,127.17,0.007 +33.03,18.2,0.056 +33.03,21.67,0.078 +33.03,26.12,0.088 +33.03,31.42,0.087 +33.03,37.33,0.071 +33.03,44.6,0.065 +33.03,53.61,0.05 +33.03,63.38,0.037 +33.03,75.52,0.025 +33.03,89.6,0.017 +33.03,106.63,0.01 +33.03,127.17,0.006 +39.35,18.2,0.04 +39.35,21.67,0.056 +39.35,26.12,0.063 +39.35,31.42,0.062 +39.35,37.33,0.051 +39.35,44.6,0.047 +39.35,53.61,0.036 +39.35,63.38,0.027 +39.35,75.52,0.018 +39.35,89.6,0.012 +39.35,106.63,0.007 +39.35,127.17,0.004 +46.62,18.2,0.036 +46.62,21.67,0.05 +46.62,26.12,0.057 +46.62,31.42,0.056 +46.62,37.33,0.046 +46.62,44.6,0.042 +46.62,53.61,0.032 +46.62,63.38,0.024 +46.62,75.52,0.016 +46.62,89.6,0.011 +46.62,106.63,0.006 +46.62,127.17,0.004 +55.74,18.2,0.031 +55.74,21.67,0.043 +55.74,26.12,0.049 +55.74,31.42,0.048 +55.74,37.33,0.039 +55.74,44.6,0.036 +55.74,53.61,0.028 +55.74,63.38,0.021 +55.74,75.52,0.014 +55.74,89.6,0.009 +55.74,106.63,0.006 +55.74,127.17,0.003 +66.39,18.2,0.03 +66.39,21.67,0.042 +66.39,26.12,0.048 +66.39,31.42,0.047 +66.39,37.33,0.039 +66.39,44.6,0.035 +66.39,53.61,0.027 +66.39,63.38,0.02 +66.39,75.52,0.013 +66.39,89.6,0.009 +66.39,106.63,0.005 +66.39,127.17,0.003 +78.97,18.2,0.033 +78.97,21.67,0.046 +78.97,26.12,0.052 +78.97,31.42,0.051 +78.97,37.33,0.042 +78.97,44.6,0.038 +78.97,53.61,0.029 +78.97,63.38,0.022 +78.97,75.52,0.014 +78.97,89.6,0.01 +78.97,106.63,0.006 +78.97,127.17,0.003 +94.22,18.2,0.029 +94.22,21.67,0.04 +94.22,26.12,0.045 +94.22,31.42,0.044 +94.22,37.33,0.036 +94.22,44.6,0.033 +94.22,53.61,0.026 +94.22,63.38,0.019 +94.22,75.52,0.013 +94.22,89.6,0.008 +94.22,106.63,0.005 +94.22,127.17,0.003 +111.48,18.2,0.027 +111.48,21.67,0.038 +111.48,26.12,0.043 +111.48,31.42,0.042 +111.48,37.33,0.035 +111.48,44.6,0.032 +111.48,53.61,0.024 +111.48,63.38,0.018 +111.48,75.52,0.012 +111.48,89.6,0.008 +111.48,106.63,0.005 +111.48,127.17,0.003 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyD-DijettopologyDcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyD-DijettopologyDcorrelation.csv new file mode 100644 index 0000000000..aca0dc39f5 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/DijettopologyD-DijettopologyDcorrelation.csv @@ -0,0 +1,86 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t20 +#: name: Dijet topology D correlation +#: description: The correlation matrix for the point-to-point uncertainties (systematics only) for forward-forward dijet measurements (topology D). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: DijD.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +Topology D - Parton Dijet $M_{inv}$ (GeV/$c^2$),Topology D - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation DijetD +18.2,18.2,1.0 +18.2,21.67,0.097 +18.2,26.12,0.115 +18.2,31.42,0.12 +18.2,37.33,0.103 +18.2,44.6,0.096 +18.2,53.61,0.077 +18.2,63.38,0.059 +18.2,75.52,0.04 +18.2,89.6,0.027 +18.2,106.63,0.017 +18.2,127.17,0.009 +21.67,21.67,1.0 +21.67,26.12,0.038 +21.67,31.42,0.04 +21.67,37.33,0.034 +21.67,44.6,0.032 +21.67,53.61,0.025 +21.67,63.38,0.019 +21.67,75.52,0.013 +21.67,89.6,0.009 +21.67,106.63,0.005 +21.67,127.17,0.003 +26.12,26.12,1.0 +26.12,31.42,0.197 +26.12,37.33,0.168 +26.12,44.6,0.158 +26.12,53.61,0.125 +26.12,63.38,0.097 +26.12,75.52,0.065 +26.12,89.6,0.045 +26.12,106.63,0.027 +26.12,127.17,0.015 +31.42,31.42,1.0 +31.42,37.33,0.13 +31.42,44.6,0.122 +31.42,53.61,0.097 +31.42,63.38,0.075 +31.42,75.52,0.05 +31.42,89.6,0.034 +31.42,106.63,0.021 +31.42,127.17,0.012 +37.33,37.33,1.0 +37.33,44.6,0.082 +37.33,53.61,0.065 +37.33,63.38,0.05 +37.33,75.52,0.034 +37.33,89.6,0.023 +37.33,106.63,0.014 +37.33,127.17,0.008 +44.6,44.6,1.0 +44.6,53.61,0.054 +44.6,63.38,0.042 +44.6,75.52,0.028 +44.6,89.6,0.019 +44.6,106.63,0.012 +44.6,127.17,0.007 +53.61,53.61,1.0 +53.61,63.38,0.032 +53.61,75.52,0.022 +53.61,89.6,0.015 +53.61,106.63,0.009 +53.61,127.17,0.005 +63.38,63.38,1.0 +63.38,75.52,0.018 +63.38,89.6,0.012 +63.38,106.63,0.007 +63.38,127.17,0.004 +75.52,75.52,1.0 +75.52,89.6,0.011 +75.52,106.63,0.007 +75.52,127.17,0.004 +89.6,89.6,1.0 +89.6,106.63,0.006 +89.6,127.17,0.003 +106.63,106.63,1.0 +106.63,127.17,0.003 +127.17,127.17,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure3.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure3.csv new file mode 100644 index 0000000000..a2811b10a3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure3.csv @@ -0,0 +1,54 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t1 +#: name: Figure 3 +#: description: Parton jet $p_T$ vs $A_{LL}$ values with associated uncertainties. +#: data_file: InclusiveJet.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET X +Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range,Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range LOW,Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range HIGH,Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$,syst +,syst - +0.03055,0.02719,0.03391,0.03055,0.00336,-0.00336 +0.037725,0.03542,0.04003,0.03773,0.0023,-0.0023 +0.045759999999999995,0.04391,0.04761,0.04576,0.00185,-0.00185 +0.053290000000000004,0.05129,0.05529,0.05329,0.002,-0.002 +0.061805,0.05969,0.06392,0.0618,0.00211,-0.00211 +0.078,0.07516,0.08084,0.078,0.00284,-0.00284 +0.088945,0.08577,0.09212,0.08894,0.00318,-0.00318 +0.10172500000000001,0.09822,0.10523,0.10173,0.0035,-0.0035 +0.11667,0.11273,0.12061,0.11667,0.00394,-0.00394 +0.13446999999999998,0.12971,0.13923,0.13447,0.00476,-0.00476 +0.155255,0.14978,0.16073,0.15525,0.00548,-0.00548 +0.179455,0.17348,0.18543,0.17945,0.00597,-0.00597 +0.20851,0.20173,0.21529,0.20851,0.00678,-0.00678 +0.24066500000000002,0.23302,0.24831,0.24067,0.00765,-0.00765 + +Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range,Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range LOW,Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range HIGH,Parton Jet $p_{T}$ (GeV/$c$),syst +,syst - +0.03055,0.02719,0.03391,7.79,0.86,-0.86 +0.037725,0.03542,0.04003,9.62,0.59,-0.59 +0.045759999999999995,0.04391,0.04761,11.67,0.47,-0.47 +0.053290000000000004,0.05129,0.05529,13.59,0.51,-0.51 +0.061805,0.05969,0.06392,15.76,0.54,-0.54 +0.078,0.07516,0.08084,19.89,0.73,-0.73 +0.088945,0.08577,0.09212,22.68,0.81,-0.81 +0.10172500000000001,0.09822,0.10523,25.94,0.89,-0.89 +0.11667,0.11273,0.12061,29.75,1.0,-1.0 +0.13446999999999998,0.12971,0.13923,34.29,1.21,-1.21 +0.155255,0.14978,0.16073,39.59,1.4,-1.4 +0.179455,0.17348,0.18543,45.76,1.52,-1.52 +0.20851,0.20173,0.21529,53.17,1.73,-1.73 +0.24066500000000002,0.23302,0.24831,61.37,1.95,-1.95 + +Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range,Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range LOW,Parton Jet $x_{T} (=2p_{T}/\sqrt{s})$ range HIGH,Inclusive Jet $A_{LL}$,stat +,stat -,syst +,syst - +0.03055,0.02719,0.03391,0.00626,0.00241,-0.00241,0.0006,-0.0006 +0.037725,0.03542,0.04003,0.00258,0.00249,-0.00249,0.00056,-0.00056 +0.045759999999999995,0.04391,0.04761,0.00277,0.00176,-0.00176,0.00054,-0.00054 +0.053290000000000004,0.05129,0.05529,-0.00075,0.00187,-0.00187,0.00054,-0.00054 +0.061805,0.05969,0.06392,-0.00085,0.00216,-0.00216,0.00051,-0.00051 +0.078,0.07516,0.08084,0.00444,0.00112,-0.00112,0.0005,-0.0005 +0.088945,0.08577,0.09212,0.00308,0.00114,-0.00114,0.0005,-0.0005 +0.10172500000000001,0.09822,0.10523,0.00572,0.00128,-0.00128,0.00051,-0.00051 +0.11667,0.11273,0.12061,0.01008,0.00161,-0.00161,0.00054,-0.00054 +0.13446999999999998,0.12971,0.13923,0.01033,0.00217,-0.00217,0.00059,-0.00059 +0.155255,0.14978,0.16073,0.01249,0.00312,-0.00312,0.00064,-0.00064 +0.179455,0.17348,0.18543,0.01824,0.00478,-0.00478,0.00068,-0.00068 +0.20851,0.20173,0.21529,0.02205,0.00788,-0.00788,0.00092,-0.00092 +0.24066500000000002,0.23302,0.24831,0.04527,0.01388,-0.01388,0.00212,-0.00212 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyA.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyA.csv new file mode 100644 index 0000000000..7efc331aa9 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyA.csv @@ -0,0 +1,34 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t2 +#: name: Figure 5 topology A +#: description: Parton dijet $M_{inv}$ vs $A_{LL}$ values with associated uncertainties, for topology A. +#: data_file: DijetA.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET JET X +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,Parton Dijet $M_{inv}$ (GeV/$c^{2}$),syst +,syst - +15.74,14.32,17.16,15.74,1.42,-1.42 +18.5,17.36,19.64,18.5,1.14,-1.14 +21.96,21.01,22.91,21.96,0.95,-0.95 +26.17,25.23,27.11,26.17,0.94,-0.94 +31.630000000000003,30.59,32.67,31.63,1.04,-1.04 +37.8,36.44,39.16,37.8,1.36,-1.36 +44.75,43.4,46.1,44.75,1.35,-1.35 +53.31,51.81,54.81,53.31,1.5,-1.5 +63.64,61.91,65.37,63.64,1.73,-1.73 +75.32,73.26,77.38,75.32,2.06,-2.06 +89.66,87.15,92.17,89.66,2.51,-2.51 +105.63,102.73,108.53,105.63,2.9,-2.9 + +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,"Dijet $A_{LL}$, topology A",stat +,stat -,syst +,syst - +15.74,14.32,17.16,-0.00548,0.00619,-0.00619,0.00055,-0.00055 +18.5,17.36,19.64,-0.00011,0.00289,-0.00289,0.00074,-0.00074 +21.96,21.01,22.91,0.00165,0.00248,-0.00248,0.0005,-0.0005 +26.17,25.23,27.11,0.00129,0.00226,-0.00226,0.00055,-0.00055 +31.630000000000003,30.59,32.67,0.00248,0.00246,-0.00246,0.00056,-0.00056 +37.8,36.44,39.16,0.00581,0.00311,-0.00311,0.00057,-0.00057 +44.75,43.4,46.1,0.00666,0.00349,-0.00349,0.00059,-0.00059 +53.31,51.81,54.81,0.0114,0.00472,-0.00472,0.00066,-0.00066 +63.64,61.91,65.37,0.01826,0.00659,-0.00659,0.00082,-0.00082 +75.32,73.26,77.38,0.02431,0.01045,-0.01045,0.00114,-0.00114 +89.66,87.15,92.17,0.03638,0.01633,-0.01633,0.00144,-0.00144 +105.63,102.73,108.53,-0.00789,0.02919,-0.02919,0.00198,-0.00198 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyB.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyB.csv new file mode 100644 index 0000000000..98b3cb8c59 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyB.csv @@ -0,0 +1,36 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t3 +#: name: Figure 5 topology B +#: description: Parton dijet $M_{inv}$ vs $A_{LL}$ values with associated uncertainties, for topology B. +#: data_file: DijetB.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET JET X +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,Parton Dijet $M_{inv}$ (GeV/$c^{2}$),syst +,syst - +15.49,14.02,16.96,15.49,1.47,-1.47 +18.479999999999997,17.65,19.31,18.48,0.83,-0.83 +22.33,21.58,23.08,22.33,0.75,-0.75 +26.67,25.76,27.58,26.67,0.91,-0.91 +32.16,31.17,33.15,32.16,0.99,-0.99 +38.59,37.42,39.76,38.59,1.17,-1.17 +45.66,44.25,47.07,45.66,1.41,-1.41 +54.489999999999995,52.98,56.0,54.49,1.51,-1.51 +65.02,63.27,66.77,65.02,1.75,-1.75 +77.16,75.09,79.23,77.16,2.07,-2.07 +91.33000000000001,88.76,93.9,91.33,2.57,-2.57 +109.2,106.15,112.25,109.2,3.05,-3.05 +129.75,126.3,133.2,129.75,3.45,-3.45 + +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,"Dijet $A_{LL}$, topology B",stat +,stat -,syst +,syst - +15.49,14.02,16.96,0.00381,0.00533,-0.00533,0.00048,-0.00048 +18.479999999999997,17.65,19.31,0.00299,0.00213,-0.00213,0.00048,-0.00048 +22.33,21.58,23.08,-0.00116,0.00173,-0.00173,0.00048,-0.00048 +26.67,25.76,27.58,0.00336,0.00152,-0.00152,0.00049,-0.00049 +32.16,31.17,33.15,-0.0006,0.00161,-0.00161,0.00051,-0.00051 +38.59,37.42,39.76,0.00154,0.00202,-0.00202,0.00053,-0.00053 +45.66,44.25,47.07,0.0062,0.00224,-0.00224,0.00056,-0.00056 +54.489999999999995,52.98,56.0,0.00865,0.00297,-0.00297,0.00062,-0.00062 +65.02,63.27,66.77,0.00806,0.00406,-0.00406,0.00074,-0.00074 +77.16,75.09,79.23,0.02428,0.00629,-0.00629,0.00094,-0.00094 +91.33000000000001,88.76,93.9,0.01063,0.00953,-0.00953,0.00108,-0.00108 +109.2,106.15,112.25,0.01248,0.01613,-0.01613,0.00121,-0.00121 +129.75,126.3,133.2,0.05037,0.02978,-0.02978,0.0028,-0.0028 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyC.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyC.csv new file mode 100644 index 0000000000..abc0f66560 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyC.csv @@ -0,0 +1,34 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t4 +#: name: Figure 5 topology C +#: description: Parton dijet $M_{inv}$ vs $A_{LL}$ values with associated uncertainties, for topology C. +#: data_file: DijetC.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET JET X +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,Parton Dijet $M_{inv}$ (GeV/$c^{2}$),syst +,syst - +15.72,14.18,17.26,15.72,1.54,-1.54 +18.9,17.91,19.89,18.9,0.99,-0.99 +22.240000000000002,21.22,23.26,22.24,1.02,-1.02 +27.14,26.16,28.12,27.14,0.98,-0.98 +33.03,31.94,34.12,33.03,1.09,-1.09 +39.35,37.92,40.78,39.35,1.43,-1.43 +46.62,45.08,48.16,46.62,1.54,-1.54 +55.74,54.03,57.45,55.74,1.71,-1.71 +66.38999999999999,64.46,68.32,66.39,1.93,-1.93 +78.97,76.71,81.23,78.97,2.26,-2.26 +94.22,91.37,97.07,94.22,2.85,-2.85 +111.48,108.26,114.7,111.48,3.22,-3.22 + +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,"Dijet $A_{LL}$, topology C",stat +,stat -,syst +,syst - +15.72,14.18,17.26,-0.01155,0.00785,-0.00785,0.00079,-0.00079 +18.9,17.91,19.89,0.00075,0.00367,-0.00367,0.00153,-0.00153 +22.240000000000002,21.22,23.26,-0.00293,0.00317,-0.00317,0.00052,-0.00052 +27.14,26.16,28.12,0.00018,0.00291,-0.00291,0.00075,-0.00075 +33.03,31.94,34.12,0.00655,0.00317,-0.00317,0.00071,-0.00071 +39.35,37.92,40.78,0.00969,0.004,-0.004,0.0007,-0.0007 +46.62,45.08,48.16,0.00817,0.00448,-0.00448,0.00073,-0.00073 +55.74,54.03,57.45,0.01317,0.00603,-0.00603,0.00082,-0.00082 +66.38999999999999,64.46,68.32,0.01866,0.00833,-0.00833,0.00105,-0.00105 +78.97,76.71,81.23,0.01712,0.01292,-0.01292,0.00151,-0.00151 +94.22,91.37,97.07,0.01357,0.01964,-0.01964,0.00173,-0.00173 +111.48,108.26,114.7,-0.00575,0.03322,-0.03322,0.00236,-0.00236 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyD.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyD.csv new file mode 100644 index 0000000000..a24a5f4ff1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Figure5topologyD.csv @@ -0,0 +1,34 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t5 +#: name: Figure 5 topology D +#: description: Parton dijet $M_{inv}$ vs $A_{LL}$ values with associated uncertainties, for topology D. +#: data_file: DijetD.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET JET X +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,Parton Dijet $M_{inv}$ (GeV/$c^{2}$),syst +,syst - +18.200000000000003,17.05,19.35,18.2,1.15,-1.15 +21.67,20.63,22.71,21.67,1.04,-1.04 +26.119999999999997,25.08,27.16,26.12,1.04,-1.04 +31.419999999999998,30.4,32.44,31.42,1.02,-1.02 +37.33,36.08,38.58,37.33,1.25,-1.25 +44.6,43.09,46.11,44.6,1.51,-1.51 +53.61,51.92,55.3,53.61,1.69,-1.69 +63.38,61.45,65.31,63.38,1.93,-1.93 +75.52000000000001,73.25,77.79,75.52,2.27,-2.27 +89.6,86.9,92.3,89.6,2.7,-2.7 +106.63,103.43,109.83,106.63,3.2,-3.2 +127.17,123.35,130.99,127.17,3.82,-3.82 + +Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range LOW,Parton Dijet $M_{inv}$ (GeV/$c^{2}$) range HIGH,"Dijet $A_{LL}$, topology D",stat +,stat -,syst +,syst - +18.200000000000003,17.05,19.35,0.01048,0.00466,-0.00466,0.0012,-0.0012 +21.67,20.63,22.71,0.00296,0.00302,-0.00302,0.00055,-0.00055 +26.119999999999997,25.08,27.16,0.00307,0.00235,-0.00235,0.00113,-0.00113 +31.419999999999998,30.4,32.44,-0.00072,0.00229,-0.00229,0.00097,-0.00097 +37.33,36.08,38.58,0.00169,0.00278,-0.00278,0.00086,-0.00086 +44.6,43.09,46.11,0.00501,0.003,-0.003,0.00081,-0.00081 +53.61,51.92,55.3,0.00443,0.00382,-0.00382,0.0008,-0.0008 +63.38,61.45,65.31,0.00887,0.005,-0.005,0.00082,-0.00082 +75.52000000000001,73.25,77.79,0.00985,0.00747,-0.00747,0.00094,-0.00094 +89.6,86.9,92.3,0.00351,0.01095,-0.01095,0.00106,-0.00106 +106.63,103.43,109.83,0.03141,0.01797,-0.01797,0.00123,-0.00123 +127.17,123.35,130.99,0.01114,0.03187,-0.03187,0.00224,-0.00224 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyAcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyAcorrelation.csv new file mode 100644 index 0000000000..7b7b2f6b4a --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyAcorrelation.csv @@ -0,0 +1,176 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t7 +#: name: Inclusive jet - Dijet topology A correlation +#: description: The correlation matrix for the point-to-point uncertainties (statistical and systematics) for the inclusive jet measurements coupling with the forward-forward dijet measurements (topology A). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: IncDijA.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +Parton Jet $p_{T}$ (GeV/$c$),Topology A - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation Inclusive-DijetA +7.79,15.74,0.021 +7.79,18.5,0.012 +7.79,21.96,0.005 +7.79,26.17,0.002 +7.79,31.63,0.0 +7.79,37.8,0.0 +7.79,44.75,0.0 +7.79,53.31,0.0 +7.79,63.64,0.0 +7.79,75.32,0.0 +7.79,89.66,0.0 +7.79,105.63,0.0 +9.62,15.74,0.008 +9.62,18.5,0.017 +9.62,21.96,0.009 +9.62,26.17,0.005 +9.62,31.63,0.002 +9.62,37.8,0.0 +9.62,44.75,0.0 +9.62,53.31,0.0 +9.62,63.64,0.0 +9.62,75.32,0.0 +9.62,89.66,0.0 +9.62,105.63,0.0 +11.67,15.74,0.001 +11.67,18.5,0.022 +11.67,21.96,0.019 +11.67,26.17,0.014 +11.67,31.63,0.007 +11.67,37.8,0.002 +11.67,44.75,0.0 +11.67,53.31,0.0 +11.67,63.64,0.0 +11.67,75.32,0.0 +11.67,89.66,0.0 +11.67,105.63,0.0 +13.59,15.74,0.0 +13.59,18.5,0.01 +13.59,21.96,0.021 +13.59,26.17,0.02 +13.59,31.63,0.015 +13.59,37.8,0.006 +13.59,44.75,0.002 +13.59,53.31,0.0 +13.59,63.64,0.0 +13.59,75.32,0.0 +13.59,89.66,0.0 +13.59,105.63,0.0 +15.76,15.74,0.0 +15.76,18.5,0.001 +15.76,21.96,0.016 +15.76,26.17,0.02 +15.76,31.63,0.02 +15.76,37.8,0.014 +15.76,44.75,0.006 +15.76,53.31,0.001 +15.76,63.64,0.0 +15.76,75.32,0.0 +15.76,89.66,0.0 +15.76,105.63,0.0 +19.89,15.74,0.0 +19.89,18.5,0.0 +19.89,21.96,0.013 +19.89,26.17,0.033 +19.89,31.63,0.047 +19.89,37.8,0.049 +19.89,44.75,0.041 +19.89,53.31,0.017 +19.89,63.64,0.004 +19.89,75.32,0.0 +19.89,89.66,0.0 +19.89,105.63,0.0 +22.68,15.74,0.0 +22.68,18.5,0.0 +22.68,21.96,0.002 +22.68,26.17,0.023 +22.68,31.63,0.041 +22.68,37.8,0.055 +22.68,44.75,0.066 +22.68,53.31,0.045 +22.68,63.64,0.015 +22.68,75.32,0.002 +22.68,89.66,0.0 +22.68,105.63,0.0 +25.94,15.74,0.0 +25.94,18.5,0.0 +25.94,21.96,0.0 +25.94,26.17,0.01 +25.94,31.63,0.027 +25.94,37.8,0.043 +25.94,44.75,0.071 +25.94,53.31,0.077 +25.94,63.64,0.047 +25.94,75.32,0.012 +25.94,89.66,0.001 +25.94,105.63,0.0 +29.75,15.74,0.0 +29.75,18.5,0.0 +29.75,21.96,0.0 +29.75,26.17,0.002 +29.75,31.63,0.014 +29.75,37.8,0.025 +29.75,44.75,0.051 +29.75,53.31,0.081 +29.75,63.64,0.088 +29.75,75.32,0.043 +29.75,89.66,0.009 +29.75,105.63,0.001 +34.29,15.74,0.0 +34.29,18.5,0.0 +34.29,21.96,0.0 +34.29,26.17,0.0 +34.29,31.63,0.004 +34.29,37.8,0.011 +34.29,44.75,0.026 +34.29,53.31,0.055 +34.29,63.64,0.094 +34.29,75.32,0.09 +34.29,89.66,0.039 +34.29,105.63,0.006 +39.59,15.74,0.0 +39.59,18.5,0.0 +39.59,21.96,0.0 +39.59,26.17,0.0 +39.59,31.63,0.0 +39.59,37.8,0.003 +39.59,44.75,0.011 +39.59,53.31,0.027 +39.59,63.64,0.062 +39.59,75.32,0.101 +39.59,89.66,0.094 +39.59,105.63,0.03 +45.76,15.74,0.0 +45.76,18.5,0.0 +45.76,21.96,0.0 +45.76,26.17,0.0 +45.76,31.63,0.0 +45.76,37.8,0.0 +45.76,44.75,0.003 +45.76,53.31,0.01 +45.76,63.64,0.029 +45.76,75.32,0.066 +45.76,89.66,0.114 +45.76,105.63,0.091 +53.17,15.74,0.0 +53.17,18.5,0.0 +53.17,21.96,0.0 +53.17,26.17,0.0 +53.17,31.63,0.0 +53.17,37.8,0.0 +53.17,44.75,0.0 +53.17,53.31,0.002 +53.17,63.64,0.01 +53.17,75.32,0.028 +53.17,89.66,0.071 +53.17,105.63,0.116 +61.37,15.74,0.0 +61.37,18.5,0.0 +61.37,21.96,0.0 +61.37,26.17,0.0 +61.37,31.63,0.0 +61.37,37.8,0.0 +61.37,44.75,0.0 +61.37,53.31,0.0 +61.37,63.64,0.002 +61.37,75.32,0.009 +61.37,89.66,0.028 +61.37,105.63,0.076 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyBcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyBcorrelation.csv new file mode 100644 index 0000000000..6f991bec44 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyBcorrelation.csv @@ -0,0 +1,190 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t8 +#: name: Inclusive jet - Dijet topology B correlation +#: description: The correlation matrix for the point-to-point uncertainties (statistical and systematics) for the inclusive jet measurements coupling with the forward-forward dijet measurements (topology B). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: IncDijB.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +Parton Jet $p_{T}$ (GeV/$c$),Topology B - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation Inclusive-DijetB +7.79,15.49,0.026 +7.79,18.48,0.022 +7.79,22.33,0.009 +7.79,26.67,0.004 +7.79,32.16,0.001 +7.79,38.59,0.0 +7.79,45.66,0.0 +7.79,54.49,0.0 +7.79,65.02,0.0 +7.79,77.16,0.0 +7.79,91.33,0.0 +7.79,109.2,0.0 +7.79,129.75,0.0 +9.62,15.49,0.007 +9.62,18.48,0.025 +9.62,22.33,0.015 +9.62,26.67,0.008 +9.62,32.16,0.003 +9.62,38.59,0.001 +9.62,45.66,0.0 +9.62,54.49,0.0 +9.62,65.02,0.0 +9.62,77.16,0.0 +9.62,91.33,0.0 +9.62,109.2,0.0 +9.62,129.75,0.0 +11.67,15.49,0.001 +11.67,18.48,0.025 +11.67,22.33,0.029 +11.67,26.67,0.022 +11.67,32.16,0.013 +11.67,38.59,0.005 +11.67,45.66,0.001 +11.67,54.49,0.0 +11.67,65.02,0.0 +11.67,77.16,0.0 +11.67,91.33,0.0 +11.67,109.2,0.0 +11.67,129.75,0.0 +13.59,15.49,0.0 +13.59,18.48,0.009 +13.59,22.33,0.029 +13.59,26.67,0.029 +13.59,32.16,0.023 +13.59,38.59,0.012 +13.59,45.66,0.004 +13.59,54.49,0.001 +13.59,65.02,0.0 +13.59,77.16,0.0 +13.59,91.33,0.0 +13.59,109.2,0.0 +13.59,129.75,0.0 +15.76,15.49,0.0 +15.76,18.48,0.001 +15.76,22.33,0.017 +15.76,26.67,0.027 +15.76,32.16,0.029 +15.76,38.59,0.022 +15.76,45.66,0.012 +15.76,54.49,0.003 +15.76,65.02,0.0 +15.76,77.16,0.0 +15.76,91.33,0.0 +15.76,109.2,0.0 +15.76,129.75,0.0 +19.89,15.49,0.0 +19.89,18.48,0.0 +19.89,22.33,0.01 +19.89,26.67,0.041 +19.89,32.16,0.061 +19.89,38.59,0.068 +19.89,45.66,0.065 +19.89,54.49,0.033 +19.89,65.02,0.009 +19.89,77.16,0.001 +19.89,91.33,0.0 +19.89,109.2,0.0 +19.89,129.75,0.0 +22.68,15.49,0.0 +22.68,18.48,0.0 +22.68,22.33,0.001 +22.68,26.67,0.025 +22.68,32.16,0.052 +22.68,38.59,0.073 +22.68,45.66,0.095 +22.68,54.49,0.075 +22.68,65.02,0.033 +22.68,77.16,0.007 +22.68,91.33,0.001 +22.68,109.2,0.0 +22.68,129.75,0.0 +25.94,15.49,0.0 +25.94,18.48,0.0 +25.94,22.33,0.0 +25.94,26.67,0.008 +25.94,32.16,0.033 +25.94,38.59,0.055 +25.94,45.66,0.093 +25.94,54.49,0.112 +25.94,65.02,0.082 +25.94,77.16,0.028 +25.94,91.33,0.005 +25.94,109.2,0.0 +25.94,129.75,0.0 +29.75,15.49,0.0 +29.75,18.48,0.0 +29.75,22.33,0.0 +29.75,26.67,0.001 +29.75,32.16,0.015 +29.75,38.59,0.031 +29.75,45.66,0.063 +29.75,54.49,0.105 +29.75,65.02,0.129 +29.75,77.16,0.08 +29.75,91.33,0.025 +29.75,109.2,0.003 +29.75,129.75,0.0 +34.29,15.49,0.0 +34.29,18.48,0.0 +34.29,22.33,0.0 +34.29,26.67,0.0 +34.29,32.16,0.003 +34.29,38.59,0.013 +34.29,45.66,0.033 +34.29,54.49,0.069 +34.29,65.02,0.124 +34.29,77.16,0.136 +34.29,91.33,0.079 +34.29,109.2,0.018 +34.29,129.75,0.001 +39.59,15.49,0.0 +39.59,18.48,0.0 +39.59,22.33,0.0 +39.59,26.67,0.0 +39.59,32.16,0.0 +39.59,38.59,0.003 +39.59,45.66,0.013 +39.59,54.49,0.033 +39.59,65.02,0.079 +39.59,77.16,0.136 +39.59,91.33,0.149 +39.59,109.2,0.069 +39.59,129.75,0.011 +45.76,15.49,0.0 +45.76,18.48,0.0 +45.76,22.33,0.0 +45.76,26.67,0.0 +45.76,32.16,0.0 +45.76,38.59,0.0 +45.76,45.66,0.003 +45.76,54.49,0.012 +45.76,65.02,0.037 +45.76,77.16,0.085 +45.76,91.33,0.156 +45.76,109.2,0.152 +45.76,129.75,0.053 +53.17,15.49,0.0 +53.17,18.48,0.0 +53.17,22.33,0.0 +53.17,26.67,0.0 +53.17,32.16,0.0 +53.17,38.59,0.0 +53.17,45.66,0.0 +53.17,54.49,0.002 +53.17,65.02,0.012 +53.17,77.16,0.038 +53.17,91.33,0.096 +53.17,109.2,0.173 +53.17,129.75,0.144 +61.37,15.49,0.0 +61.37,18.48,0.0 +61.37,22.33,0.0 +61.37,26.67,0.0 +61.37,32.16,0.0 +61.37,38.59,0.0 +61.37,45.66,0.0 +61.37,54.49,0.0 +61.37,65.02,0.002 +61.37,77.16,0.012 +61.37,91.33,0.04 +61.37,109.2,0.11 +61.37,129.75,0.182 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyCcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyCcorrelation.csv new file mode 100644 index 0000000000..8483014b7e --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyCcorrelation.csv @@ -0,0 +1,176 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t9 +#: name: Inclusive jet - Dijet topology C correlation +#: description: The correlation matrix for the point-to-point uncertainties (statistical and systematics) for the inclusive jet measurements coupling with the forward-forward dijet measurements (topology C). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: IncDijC.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +Parton Jet $p_{T}$ (GeV/$c$),Topology C - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation Inclusive-DijetC +7.79,15.72,0.015 +7.79,18.9,0.009 +7.79,22.24,0.004 +7.79,27.14,0.002 +7.79,33.03,0.0 +7.79,39.35,0.0 +7.79,46.62,0.0 +7.79,55.74,0.0 +7.79,66.39,0.0 +7.79,78.97,0.0 +7.79,94.22,0.0 +7.79,111.48,0.0 +9.62,15.72,0.006 +9.62,18.9,0.012 +9.62,22.24,0.007 +9.62,27.14,0.004 +9.62,33.03,0.001 +9.62,39.35,0.0 +9.62,46.62,0.0 +9.62,55.74,0.0 +9.62,66.39,0.0 +9.62,78.97,0.0 +9.62,94.22,0.0 +9.62,111.48,0.0 +11.67,15.72,0.001 +11.67,18.9,0.015 +11.67,22.24,0.014 +11.67,27.14,0.011 +11.67,33.03,0.006 +11.67,39.35,0.002 +11.67,46.62,0.0 +11.67,55.74,0.0 +11.67,66.39,0.0 +11.67,78.97,0.0 +11.67,94.22,0.0 +11.67,111.48,0.0 +13.59,15.72,0.0 +13.59,18.9,0.007 +13.59,22.24,0.016 +13.59,27.14,0.015 +13.59,33.03,0.012 +13.59,39.35,0.005 +13.59,46.62,0.002 +13.59,55.74,0.0 +13.59,66.39,0.0 +13.59,78.97,0.0 +13.59,94.22,0.0 +13.59,111.48,0.0 +15.76,15.72,0.0 +15.76,18.9,0.001 +15.76,22.24,0.011 +15.76,27.14,0.015 +15.76,33.03,0.016 +15.76,39.35,0.011 +15.76,46.62,0.005 +15.76,55.74,0.001 +15.76,66.39,0.0 +15.76,78.97,0.0 +15.76,94.22,0.0 +15.76,111.48,0.0 +19.89,15.72,0.0 +19.89,18.9,0.0 +19.89,22.24,0.008 +19.89,27.14,0.023 +19.89,33.03,0.033 +19.89,39.35,0.035 +19.89,46.62,0.03 +19.89,55.74,0.013 +19.89,66.39,0.003 +19.89,78.97,0.0 +19.89,94.22,0.0 +19.89,111.48,0.0 +22.68,15.72,0.0 +22.68,18.9,0.0 +22.68,22.24,0.001 +22.68,27.14,0.016 +22.68,33.03,0.03 +22.68,39.35,0.041 +22.68,46.62,0.051 +22.68,55.74,0.034 +22.68,66.39,0.013 +22.68,78.97,0.002 +22.68,94.22,0.0 +22.68,111.48,0.0 +25.94,15.72,0.0 +25.94,18.9,0.0 +25.94,22.24,0.0 +25.94,27.14,0.007 +25.94,33.03,0.02 +25.94,39.35,0.033 +25.94,46.62,0.054 +25.94,55.74,0.059 +25.94,66.39,0.036 +25.94,78.97,0.011 +25.94,94.22,0.002 +25.94,111.48,0.0 +29.75,15.72,0.0 +29.75,18.9,0.0 +29.75,22.24,0.0 +29.75,27.14,0.001 +29.75,33.03,0.009 +29.75,39.35,0.018 +29.75,46.62,0.038 +29.75,55.74,0.061 +29.75,66.39,0.067 +29.75,78.97,0.034 +29.75,94.22,0.009 +29.75,111.48,0.001 +34.29,15.72,0.0 +34.29,18.9,0.0 +34.29,22.24,0.0 +34.29,27.14,0.0 +34.29,33.03,0.003 +34.29,39.35,0.008 +34.29,46.62,0.02 +34.29,55.74,0.042 +34.29,66.39,0.072 +34.29,78.97,0.07 +34.29,94.22,0.033 +34.29,111.48,0.006 +39.59,15.72,0.0 +39.59,18.9,0.0 +39.59,22.24,0.0 +39.59,27.14,0.0 +39.59,33.03,0.0 +39.59,39.35,0.002 +39.59,46.62,0.008 +39.59,55.74,0.021 +39.59,66.39,0.049 +39.59,78.97,0.079 +39.59,94.22,0.075 +39.59,111.48,0.027 +45.76,15.72,0.0 +45.76,18.9,0.0 +45.76,22.24,0.0 +45.76,27.14,0.0 +45.76,33.03,0.0 +45.76,39.35,0.0 +45.76,46.62,0.002 +45.76,55.74,0.008 +45.76,66.39,0.024 +45.76,78.97,0.054 +45.76,94.22,0.09 +45.76,111.48,0.074 +53.17,15.72,0.0 +53.17,18.9,0.0 +53.17,22.24,0.0 +53.17,27.14,0.0 +53.17,33.03,0.0 +53.17,39.35,0.0 +53.17,46.62,0.0 +53.17,55.74,0.002 +53.17,66.39,0.009 +53.17,78.97,0.025 +53.17,94.22,0.062 +53.17,111.48,0.097 +61.37,15.72,0.0 +61.37,18.9,0.0 +61.37,22.24,0.0 +61.37,27.14,0.0 +61.37,33.03,0.0 +61.37,39.35,0.0 +61.37,46.62,0.0 +61.37,55.74,0.0 +61.37,66.39,0.002 +61.37,78.97,0.008 +61.37,94.22,0.028 +61.37,111.48,0.073 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyDcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyDcorrelation.csv new file mode 100644 index 0000000000..32ff709efc --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-DijettopologyDcorrelation.csv @@ -0,0 +1,176 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t10 +#: name: Inclusive jet - Dijet topology D correlation +#: description: The correlation matrix for the point-to-point uncertainties (statistical and systematics) for the inclusive jet measurements coupling with the forward-forward dijet measurements (topology D). The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: IncDijD.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +Parton Jet $p_{T}$ (GeV/$c$),Topology D - Parton Dijet $M_{inv}$ (GeV/$c^2$),Correlation Inclusive-DijetD +7.79,18.2,0.019 +7.79,21.67,0.01 +7.79,26.12,0.004 +7.79,31.42,0.002 +7.79,37.33,0.0 +7.79,44.6,0.0 +7.79,53.61,0.0 +7.79,63.38,0.0 +7.79,75.52,0.0 +7.79,89.6,0.0 +7.79,106.63,0.0 +7.79,127.17,0.0 +9.62,18.2,0.013 +9.62,21.67,0.014 +9.62,26.12,0.008 +9.62,31.42,0.004 +9.62,37.33,0.001 +9.62,44.6,0.0 +9.62,53.61,0.0 +9.62,63.38,0.0 +9.62,75.52,0.0 +9.62,89.6,0.0 +9.62,106.63,0.0 +9.62,127.17,0.0 +11.67,18.2,0.006 +11.67,21.67,0.021 +11.67,26.12,0.017 +11.67,31.42,0.012 +11.67,37.33,0.006 +11.67,44.6,0.002 +11.67,53.61,0.0 +11.67,63.38,0.0 +11.67,75.52,0.0 +11.67,89.6,0.0 +11.67,106.63,0.0 +11.67,127.17,0.0 +13.59,18.2,0.001 +13.59,21.67,0.013 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+53.17,37.33,0.0 +53.17,44.6,0.0 +53.17,53.61,0.0 +53.17,63.38,0.004 +53.17,75.52,0.013 +53.17,89.6,0.038 +53.17,106.63,0.088 +53.17,127.17,0.114 +61.37,18.2,0.0 +61.37,21.67,0.0 +61.37,26.12,0.0 +61.37,31.42,0.0 +61.37,37.33,0.0 +61.37,44.6,0.0 +61.37,53.61,0.0 +61.37,63.38,0.0 +61.37,75.52,0.003 +61.37,89.6,0.013 +61.37,106.63,0.04 +61.37,127.17,0.096 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-Inclusivejetcorrelation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-Inclusivejetcorrelation.csv new file mode 100644 index 0000000000..d86b9d37d2 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/rawdata/Inclusivejet-Inclusivejetcorrelation.csv @@ -0,0 +1,113 @@ +#: table_doi: 10.17182/hepdata.114778.v1/t6 +#: name: Inclusive jet - Inclusive jet correlation +#: description: The correlation matrix for the point-to-point uncertainties (statistical and systematics) for the inclusive jet measurements.The relative luminosity and beam polarization uncertainties are not included because they are the same for all points. +#: data_file: IncInc.yaml +#: keyword reactions: P P --> JET X +#: keyword observables: CORR +Parton Jet $p_{T}$ (GeV/$c$),Parton Jet $p_{T}$ (GeV/$c$),Correlation Inclusive-Inclusive jet +7.79,7.79,1.0 +7.79,9.62,0.007 +7.79,11.67,0.004 +7.79,13.59,0.004 +7.79,15.76,0.003 +7.79,19.89,0.001 +7.79,22.68,0.001 +7.79,25.94,0.0 +7.79,29.75,0.0 +7.79,34.29,0.0 +7.79,39.59,0.0 +7.79,45.76,0.0 +7.79,53.17,0.0 +7.79,61.37,0.0 +9.62,9.62,1.0 +9.62,11.67,0.005 +9.62,13.59,0.005 +9.62,15.76,0.005 +9.62,19.89,0.002 +9.62,22.68,0.001 +9.62,25.94,0.001 +9.62,29.75,0.0 +9.62,34.29,0.0 +9.62,39.59,0.0 +9.62,45.76,0.0 +9.62,53.17,0.0 +9.62,61.37,0.0 +11.67,11.67,1.0 +11.67,13.59,0.008 +11.67,15.76,0.009 +11.67,19.89,0.004 +11.67,22.68,0.002 +11.67,25.94,0.002 +11.67,29.75,0.001 +11.67,34.29,0.001 +11.67,39.59,0.0 +11.67,45.76,0.0 +11.67,53.17,0.0 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systematics uncertainty + treatment: ADD + type: CORR + sys_4: + description: 4 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_5: + description: 5 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_6: + description: 6 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_7: + description: 7 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_8: + description: 8 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_9: + description: 9 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_10: + description: 10 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_11: + description: 11 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_12: + description: 12 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR + sys_13: + description: 13 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: CORR +bins: +- sys_0: -1.0951625464162565e-09 + sys_1: 1.1516691091869679e-08 + sys_2: -7.854773848580345e-08 + sys_3: 6.866154309094594e-07 + sys_4: 2.164283413432904e-05 + sys_5: -0.000620696156135884 + sys_6: 0.0024031769111292163 + sys_7: 1.5218755279690372e-05 + sys_8: -1.7780887091095855e-05 + sys_9: -6.419814679578488e-05 + sys_10: -2.0149056225408066e-06 + sys_11: 2.086134837183203e-05 + sys_12: -3.067777040199403e-05 + sys_13: -2.2721684612739994e-05 + stat: 0 +- sys_0: -1.7477653367624728e-09 + sys_1: 1.681965030873789e-08 + sys_2: -1.134653307823307e-07 + sys_3: 1.0671058187857347e-06 + sys_4: 3.362733369615975e-05 + sys_5: -0.002476570972603001 + sys_6: -0.0006066860957810047 + sys_7: 1.2628824308356746e-05 + sys_8: -2.1444694110942473e-05 + sys_9: 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml @@ -0,0 +1,39 @@ +setname: "STAR_2013_2JET_A_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JJET_A_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..abaa88e526 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml @@ -0,0 +1,210 @@ +definitions: + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_5: + description: 5 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--- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml @@ -0,0 +1,39 @@ +setname: "STAR_2013_2JET_B_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 13 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JJET_B_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..51030020ba --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml @@ -0,0 +1,240 @@ +definitions: + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + 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null +- mjj: + max: 48.16 + mid: 46.62 + min: 45.08 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 57.45 + mid: 55.74 + min: 54.03 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 68.32000000000001 + mid: 66.39 + min: 64.46 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 81.23 + mid: 78.97 + min: 76.71 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 97.07 + mid: 94.22 + min: 91.37 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 114.7 + mid: 111.48 + min: 108.26 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml new file mode 100644 index 0000000000..1e828f32ab --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml @@ -0,0 +1,39 @@ +setname: "STAR_2013_2JET_C_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JJET_C_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..7a887c47a3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml @@ -0,0 +1,210 @@ +definitions: + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR +bins: +- sys_0: 3.9309507861888136e-05 + sys_1: 0.00036333998397519696 + sys_2: 2.3186570417783925e-05 + sys_3: 5.556881029025214e-06 + sys_4: 2.311859688314046e-05 + sys_5: 6.918856751372635e-06 + sys_6: -3.475850160770912e-06 + sys_7: -8.161015217013543e-07 + sys_8: 1.4810303438451368e-06 + sys_9: -1.1917087394724004e-05 + sys_10: 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4.20372228212075e-07 + sys_10: -1.2109789544176688e-06 + sys_11: 1.4199038245942606e-06 + stat: 0.01964 +- sys_0: -6.4021605860023e-07 + sys_1: -3.4929060031472936e-07 + sys_2: -2.1175490331606037e-06 + sys_3: 1.0199189629631558e-06 + sys_4: 1.562290856564072e-06 + sys_5: 2.740729621384654e-07 + sys_6: -2.907160471761827e-07 + sys_7: -7.005381187136291e-07 + sys_8: 2.075654509591278e-06 + sys_9: -1.0707394560948261e-06 + sys_10: -7.196059070035401e-07 + sys_11: 6.599902358889499e-07 + stat: 0.03322 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/data.yaml new file mode 100644 index 0000000000..6c7101a8a8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/data.yaml @@ -0,0 +1,13 @@ +data_central: +- 0.01048 +- 0.00296 +- 0.00307 +- -0.00072 +- 0.00169 +- 0.00501 +- 0.00443 +- 0.00887 +- 0.00985 +- 0.00351 +- 0.03141 +- 0.01114 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml new file mode 100644 index 0000000000..b9a9c8476d --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml @@ -0,0 +1,97 @@ +bins: +- mjj: + max: 19.349999999999998 + mid: 18.2 + min: 17.05 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 22.71 + mid: 21.67 + min: 20.630000000000003 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 27.16 + mid: 26.12 + min: 25.080000000000002 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 32.440000000000005 + mid: 31.42 + min: 30.400000000000002 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 38.58 + mid: 37.33 + min: 36.08 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 46.11 + mid: 44.6 + min: 43.09 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 55.3 + mid: 53.61 + min: 51.92 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 65.31 + mid: 63.38 + min: 61.45 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 77.78999999999999 + mid: 75.52 + min: 73.25 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 92.3 + mid: 89.6 + min: 86.89999999999999 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 109.83 + mid: 106.63 + min: 103.42999999999999 + sqrts: + max: null + mid: 510.0 + min: null +- mjj: + max: 130.99 + mid: 127.17 + min: 123.35000000000001 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml new file mode 100644 index 0000000000..0ac491a3e6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml @@ -0,0 +1,39 @@ +setname: "STAR_2013_2JET_D_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JJET_D_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..ed1963c210 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml @@ -0,0 +1,210 @@ +definitions: + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: CORR + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR +bins: +- sys_0: -8.43519900277388e-07 + sys_1: -2.8903062169093345e-06 + sys_2: -1.5652343086514804e-06 + sys_3: -2.8882672445145354e-06 + sys_4: -1.9444777669882674e-06 + sys_5: 2.5290382619603253e-06 + sys_6: 7.1122527893593345e-06 + sys_7: -3.460310965307252e-06 + sys_8: 9.384861853760815e-06 + sys_9: 7.214192887288997e-06 + sys_10: 3.5834180743311576e-05 + sys_11: 2.256673391931869e-05 + stat: 0.00466 +- 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0.003 +- sys_0: 4.516798871302951e-06 + sys_1: 6.730369762680619e-07 + sys_2: 4.900961389730739e-07 + sys_3: 1.108955642708728e-05 + sys_4: -2.417955636714097e-06 + sys_5: 1.8351726000717505e-05 + sys_6: -5.972188946707324e-06 + sys_7: -9.21203710311868e-06 + sys_8: 3.4078503655638985e-06 + sys_9: -1.324697919385448e-05 + sys_10: -2.7190391494755554e-06 + sys_11: 3.82328544943926e-06 + stat: 0.00382 +- sys_0: 4.283774404043299e-06 + sys_1: -6.400228369462858e-07 + sys_2: -8.336356401886303e-07 + sys_3: 1.1274719235506756e-05 + sys_4: -2.6958094260136256e-06 + sys_5: 2.010921770794475e-05 + sys_6: -8.587121271521463e-06 + sys_7: -8.142133301379008e-06 + sys_8: 3.3807214841581733e-06 + sys_9: -1.3440850793070515e-05 + sys_10: -2.9591535141716864e-07 + sys_11: 4.232223740746207e-06 + stat: 0.005 +- sys_0: 2.040796442748057e-06 + sys_1: -1.1521173792384669e-06 + sys_2: -7.123496712193556e-07 + sys_3: 7.084144009488653e-06 + sys_4: -1.4586385929798076e-06 + sys_5: 1.3543085214218745e-05 + sys_6: -7.24828462105499e-06 + sys_7: -4.0673667087698235e-06 + sys_8: 2.2927473173135823e-06 + sys_9: -9.035461187397544e-06 + sys_10: 9.464135023813589e-07 + sys_11: 2.745686104005418e-06 + stat: 0.00747 +- sys_0: 9.173853618403658e-07 + sys_1: -1.2452827116574767e-06 + sys_2: -7.242112663499281e-07 + sys_3: 4.6794989744842264e-06 + sys_4: -5.551965659656485e-07 + sys_5: 8.839233308945949e-06 + sys_6: -5.9873961067219504e-06 + sys_7: -1.7943051368968727e-06 + sys_8: 9.732764612765583e-07 + sys_9: -5.727337539772073e-06 + sys_10: 1.4802554909674975e-06 + sys_11: 1.6739227300186697e-06 + stat: 0.01095 +- sys_0: 1.0719748599030783e-07 + sys_1: -1.267609718425314e-06 + sys_2: -3.604984702218042e-07 + sys_3: 2.3373367638764382e-06 + sys_4: 9.602105083277494e-08 + sys_5: 4.423870404583834e-06 + sys_6: -3.6607331785779715e-06 + sys_7: -5.776787994918907e-07 + sys_8: 2.4684217126532586e-07 + sys_9: -2.6376233368334807e-06 + sys_10: 1.0036304622431668e-06 + sys_11: 4.692690203894524e-07 + stat: 0.01797 +- sys_0: -1.3430015023569493e-07 + sys_1: -6.201118847936362e-07 + sys_2: -1.4876584314772848e-07 + sys_3: 6.587521288100003e-07 + sys_4: 1.2696667856314305e-07 + sys_5: 9.079687107449232e-07 + sys_6: -8.653149770338326e-07 + sys_7: -6.9656619477665965e-09 + sys_8: -4.274278312132293e-08 + sys_9: -5.857686756491707e-07 + sys_10: 4.5906629936432784e-07 + sys_11: 1.7755985099104273e-07 + stat: 0.03187 From 9c7654893e263e3d77f1e69fad5426259c5365a2 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 22 Apr 2024 19:02:16 +0200 Subject: [PATCH 09/98] move symm error to utils --- .../filter_utils/star_2013_510gev.py | 1 + .../nnpdf_data/filter_utils/uncertainties.py | 27 + .../ATLAS_1JET_13TEV_DIF/filter.py | 2 +- .../ATLAS_2JET_13TEV_DIF/filter.py | 2 +- .../ATLAS_TTBAR_13TEV_HADR_DIF/utils.py | 26 - .../ATLAS_TTBAR_13TEV_LJ_DIF/filter.py | 2 +- .../ATLAS_TTBAR_8TEV_LJ_DIF/filter.py | 2 +- .../CMS_TTBAR_8TEV_2L_DIF/filter.py | 2 +- .../H1_1JET_319GEV_290PB-1_DIF/filter.py | 2 +- .../H1_2JET_319GEV_290PB-1_DIF/filter.py | 2 +- .../HERMES_NC_7GEV_ED/filter.py | 7 +- .../HERMES_NC_7GEV_EP/filter.py | 84 +- .../STAR_2012_1JET_200GEV/filter.py | 4 +- .../STAR_2015_1JET_200GEV/filter.py | 8 +- .../STAR_2015_1JET_200GEV/uncertainties.yaml | 962 +++++++++--------- .../ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py | 2 +- .../ZEUS_1JET_319GEV_82PB-1_DIF/filter.py | 2 +- .../ZEUS_2JET_319GEV_374PB-1_DIF/filter.py | 2 +- 18 files changed, 527 insertions(+), 612 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/filter_utils/uncertainties.py diff --git a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py index f545e7e45f..6136b00de4 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py @@ -254,6 +254,7 @@ def write_2jet_data(df, topology, art_sys, ndata): correlated_unc.extend(dfs[a]["syst"].values) ndata_points = np.sum((*ndata_dict.values(),)) # decompose uncertainties + # TODO: how come this is not yet block diagonal?? art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) # write data diff --git a/nnpdf_data/nnpdf_data/filter_utils/uncertainties.py b/nnpdf_data/nnpdf_data/filter_utils/uncertainties.py new file mode 100644 index 0000000000..8d2a923dd8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/filter_utils/uncertainties.py @@ -0,0 +1,27 @@ + +import numpy as np + +def symmetrize_errors(delta_plus, delta_minus): + r"""Compute the symmetrized uncertainty and the shift in data point. + + Parameters + ---------- + delta_plus : float + The top/plus uncertainty with sign + delta_minus : float + The bottom/minus uncertainty with sign + + Returns + ------- + se_delta : float + The value to be added to the data point + se_sigma : float + The symmetrized uncertainty to be used in commondata + + """ + semi_diff = (delta_plus + delta_minus) / 2 + average = (delta_plus - delta_minus) / 2 + se_delta = semi_diff + se_sigma = np.sqrt(average * average + 2 * semi_diff * semi_diff) + return se_delta, se_sigma + diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py index ff222f5fea..b3442e89bd 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py index 0655765b51..47dee7baba 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py index dac59de537..756b13f18c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py @@ -19,32 +19,6 @@ import numpy as np from numpy.linalg import eig - -def symmetrize_errors(delta_plus, delta_minus): - r"""Compute the symmterized uncertainty and the shift in data point. - - Parameters - ---------- - delta_plus : float - The top/plus uncertainty with sign - delta_minus : float - The bottom/minus uncertainty with sign - - Returns - ------- - se_delta : float - The value to be added to the data point - se_sigma : float - The symmetrized uncertainty to be used in commondata - - """ - semi_diff = (delta_plus + delta_minus) / 2 - average = (delta_plus - delta_minus) / 2 - se_delta = semi_diff - se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff) - return se_delta, se_sigma - - def percentage_to_absolute(percentage, value): r"""Compute the absolute value of uncertainty from percentage. diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py index 37b78e0988..6798d7ae1b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py @@ -2,7 +2,7 @@ from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py index b114623b64..85063e274e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py @@ -5,7 +5,7 @@ import yaml from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py index 0cd577753c..5e8c5db0bb 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py @@ -4,7 +4,7 @@ from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import trimat_to_fullmat as ttf +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py index 7f19469816..19325631d1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py @@ -4,7 +4,7 @@ import yaml from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py index ecf4dff877..a3923e6b9f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py @@ -4,7 +4,7 @@ import yaml from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_ED/filter.py b/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_ED/filter.py index 38e3209d55..8ffa9f2f16 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_ED/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_ED/filter.py @@ -9,8 +9,7 @@ HERE = pathlib.Path(__file__).parent sys.path = [str(HERE.parent / "HERMES_NC_7GEV_EP")] + sys.path -from filter import compute_covmat - +from nnpdf_data.filter_utils.correlations import compute_covmat def read_data(fnames): df = pd.DataFrame() @@ -81,11 +80,9 @@ def write_data(df): # Extract the correlation matrix and compute artificial systematics ndata_points = len(data_central) corrmatrix = read_corrmatrix(nb_datapoints=ndata_points) - # Compute the covariance matrix - compute_covmat(corrmatrix, df, ndata_points) # Compute the covariance matrix - art_sys = compute_covmat(corrmatrix, df, ndata_points) + art_sys = compute_covmat(corrmatrix, df['stat'], ndata_points) error = [] for i in range(ndata_points): diff --git a/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_EP/filter.py b/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_EP/filter.py index 7b4613de30..055db9276e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_EP/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/HERMES_NC_7GEV_EP/filter.py @@ -2,10 +2,10 @@ import pathlib import numpy as np -from numpy.linalg import eig import pandas as pd import yaml +from nnpdf_data.filter_utils.correlations import compute_covmat def read_data(fnames): df = pd.DataFrame() @@ -49,84 +49,6 @@ def read_corrmatrix(nb_datapoints: int = 15) -> np.ndarray: return df_corrs.value.values.reshape((nb_datapoints, nb_datapoints)) - -def covmat_to_artunc(ndata, covmat_list, no_of_norm_mat=0): - r"""Convert the covariance matrix to a matrix of - artificial uncertainties. - - NOTE: This function has been taken from validphys.newcommondata_utils. - If those utils get merged in the future, we can replace this. - - Parameters - ---------- - ndata : integer - Number of data points - covmat_list : list - A one dimensional list which contains the elements of - the covariance matrix row by row. Since experimental - datasets provide these matrices in a list form, this - simplifies the implementation for the user. - no_of_norm_mat : int - Normalized covariance matrices may have an eigenvalue - of 0 due to the last data point not being linearly - independent. To allow for this, the user should input - the number of normalized matrices that are being treated - in an instance. For example, if a single covariance matrix - of a normalized distribution is being processed, the input - would be 1. If a covariance matrix contains pertains to - 3 normalized datasets (i.e. cross covmat for 3 - distributions), the input would be 3. The default value is - 0 for when the covariance matrix pertains to an absolute - distribution. - - Returns - ------- - artunc : list - A two dimensional matrix (given as a list of lists) - which contains artificial uncertainties to be added - to the commondata. i^th row (or list) contains the - artificial uncertainties of the i^th data point. - - """ - epsilon = -0.0000000001 - neg_eval_count = 0 - psd_check = True - covmat = np.zeros((ndata, ndata)) - artunc = np.zeros((ndata, ndata)) - for i in range(len(covmat_list)): - a = i // ndata - b = i % ndata - covmat[a][b] = covmat_list[i] - eigval, eigvec = eig(covmat) - for j in range(len(eigval)): - if eigval[j] < epsilon: - psd_check = False - elif eigval[j] > epsilon and eigval[j] <= 0: - neg_eval_count = neg_eval_count + 1 - if neg_eval_count == (no_of_norm_mat + 1): - psd_check = False - elif eigval[j] > 0: - continue - if psd_check == False: - raise ValueError('The covariance matrix is not positive-semidefinite') - else: - for i in range(ndata): - for j in range(ndata): - if eigval[j] < 0: - continue - else: - artunc[i][j] = eigvec[i][j] * np.sqrt(eigval[j]) - return artunc.tolist() - - -def compute_covmat(corrmat: np.ndarray, df: pd.DataFrame, ndata: int) -> list: - """Compute the covariance matrix with the artificial stat uncertanties.""" - # multiply by stat err - stat = df["stat"] - cov_mat = np.einsum("i,ij,j->ij", stat, corrmat, stat) - return covmat_to_artunc(ndata, cov_mat.flatten().tolist()) - - def write_data(df): data_central = [] for i in range(len(df["G"])): @@ -153,11 +75,9 @@ def write_data(df): # Extract the correlation matrix and compute artificial systematics ndata_points = len(data_central) corrmatrix = read_corrmatrix(nb_datapoints=ndata_points) - # Compute the covariance matrix - compute_covmat(corrmatrix, df, ndata_points) # Compute the covariance matrix - art_sys = compute_covmat(corrmatrix, df, ndata_points) + art_sys = compute_covmat(corrmatrix, df['stat'], ndata_points) error = [] for i in range(ndata_points): diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py index 5b7182fb80..a4fe2af75e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py @@ -1,11 +1,9 @@ import glob -import sys import pandas as pd import yaml -sys.path.append('../') -from ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def read_data(fnames): diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index 86cec57ed2..3801674e29 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -1,12 +1,10 @@ import glob -import sys import pandas as pd import yaml -sys.path.append('../') -from ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors -from HERMES_NC_7GEV_EP.filter import compute_covmat +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors +from nnpdf_data.filter_utils.correlations import compute_covmat def read_data(fnames): @@ -92,7 +90,7 @@ def write_data(df, dfc): # Compute the covariance matrix corrmat = dfc.values.reshape((len(df), len(df))) - art_sys = compute_covmat(corrmat, df, len(df)) + art_sys = compute_covmat(corrmat, df["stat"], len(df)) # Write kin file kin = [] diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml index 6ff8d3bc4d..4149557d46 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -98,529 +98,529 @@ definitions: bins: - stat: 0.0015 sys: 0.0003 - sys_0: -1.6448417112301333e-06 - sys_1: 3.0767956744795033e-06 - sys_2: 2.985686421137934e-06 - sys_3: 2.6739400670555545e-06 - sys_4: 1.5799135431026458e-06 - sys_5: 4.469439476545788e-06 - sys_6: 3.5031982026635955e-06 - sys_7: -8.192103049239285e-06 - sys_8: 8.519902585570326e-06 - sys_9: 1.0162143079716163e-05 - sys_10: 5.851109783478681e-06 - sys_11: 1.9163436414823837e-05 - sys_12: 1.1503154098901525e-05 - sys_13: 3.266469386476217e-05 - sys_14: 2.303922686539146e-05 - sys_15: 6.747820260959229e-05 - sys_16: 3.817964657258357e-05 - sys_17: 0.0014256774940655404 - sys_18: 0.00035118617038519697 - sys_19: -0.0002906207220419269 - sys_20: -3.13699619655819e-05 - sys_21: -1.4797025494046162e-05 + sys_0: -1.6448417112333418e-06 + sys_1: 3.0767956744796355e-06 + sys_2: 2.985686421142568e-06 + sys_3: 2.673940067049602e-06 + sys_4: 1.5799135431010748e-06 + sys_5: 4.469439476538994e-06 + sys_6: 3.5031982026613432e-06 + sys_7: -8.1921030492366e-06 + sys_8: 8.519902585571064e-06 + sys_9: 1.0162143079714145e-05 + sys_10: 5.851109783476301e-06 + sys_11: 1.9163436414824488e-05 + sys_12: 1.1503154098899344e-05 + sys_13: 3.2664693864755716e-05 + sys_14: 2.3039226865385585e-05 + sys_15: 6.747820260957826e-05 + sys_16: 3.8179646572563185e-05 + sys_17: 0.0014256774940655367 + sys_18: 0.0003511861703851319 + sys_19: -0.0002906207220420177 + sys_20: -3.136996196577313e-05 + sys_21: -1.4797025494576926e-05 - stat: 0.0016 sys: 0.0004 - sys_0: -3.4518076796518805e-06 - 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stat: 0.0221 sys: 0.0038 - sys_0: -0.0004551543900004909 - sys_1: 0.0013883598392172814 - sys_2: 0.022022046125861193 - sys_3: -0.0011249872659298908 - sys_4: -0.00014963689330641577 - sys_5: -0.00012520007960570422 - sys_6: -2.322229407153053e-05 - sys_7: 2.2819133423036335e-05 - sys_8: -4.799887931168836e-06 - sys_9: -4.967968716288533e-06 - sys_10: -1.2407767922627104e-06 - sys_11: -1.7390290174771895e-06 - sys_12: -1.7394982131031865e-07 - sys_13: -6.700078986174951e-07 - sys_14: -3.6062737144925745e-07 - sys_15: -3.6847028187476367e-07 - sys_16: 3.0091366414723814e-08 - sys_17: -5.7292660770133625e-08 - sys_18: -4.6986463922386556e-07 - sys_19: -1.1387630609523068e-07 - sys_20: -7.767009761208889e-08 - sys_21: -1.2127736386574572e-08 + sys_0: -0.0004551543900004952 + sys_1: 0.001388359839217281 + sys_2: 0.022022046125861203 + sys_3: -0.001124987265929876 + sys_4: -0.000149636893306413 + sys_5: -0.000125200079605701 + sys_6: -2.32222940715299e-05 + sys_7: 2.2819133423035843e-05 + sys_8: -4.799887931168238e-06 + sys_9: -4.967968716288324e-06 + sys_10: -1.2407767922626161e-06 + sys_11: -1.739029017477025e-06 + sys_12: -1.7394982131026158e-07 + sys_13: -6.700078986176279e-07 + sys_14: -3.6062737144925385e-07 + sys_15: -3.6847028187470067e-07 + sys_16: 3.009136641463142e-08 + sys_17: -5.729266077014168e-08 + sys_18: -4.6986463922381326e-07 + sys_19: -1.1387630609504136e-07 + sys_20: -7.767009761187372e-08 + sys_21: -1.2127736386358772e-08 - stat: 0.0434 sys: 0.006 - sys_0: -0.04337071162054244 + sys_0: -0.043370711620542436 sys_1: -0.0015695501970985082 - sys_2: -0.0001978892564880431 - sys_3: -0.00019320951003664913 - sys_4: -2.3153132718638234e-05 - sys_5: -2.8657491227276497e-05 - sys_6: -4.184112512098821e-06 - sys_7: 4.347708483568332e-06 - sys_8: -8.641965407956742e-07 - sys_9: -1.002647578381799e-06 - sys_10: -5.838572886197024e-08 - sys_11: -2.9010364045999787e-07 - sys_12: -1.8551346809229957e-07 - sys_13: -1.028974645147263e-07 - sys_14: -4.9288823452424046e-08 - sys_15: -5.58494115494554e-08 - sys_16: 8.24429327471205e-09 - sys_17: -1.3979433472408974e-08 - sys_18: -1.14012183583828e-07 - sys_19: -2.0642063350458738e-08 - sys_20: -2.4056520791451592e-08 - sys_21: -2.6129264562384213e-08 + sys_2: -0.00019788925648804294 + sys_3: -0.00019320951003665 + sys_4: -2.3153132718638176e-05 + sys_5: -2.8657491227276663e-05 + sys_6: -4.184112512098797e-06 + sys_7: 4.3477084835685e-06 + sys_8: -8.641965407956168e-07 + sys_9: -1.0026475783818943e-06 + sys_10: -5.8385728861666226e-08 + sys_11: -2.901036404600478e-07 + sys_12: -1.8551346809212596e-07 + sys_13: -1.0289746451456385e-07 + sys_14: -4.928882345241368e-08 + sys_15: -5.5849411549514293e-08 + sys_16: 8.244293274545548e-09 + sys_17: -1.397943347217152e-08 + sys_18: -1.1401218358386539e-07 + sys_19: -2.064206335065571e-08 + sys_20: -2.4056520791443638e-08 + sys_21: -2.612926456242647e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py index e6c5b3fa0b..b86614b230 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py index 1804a8e969..f992b7a8e6 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py index ce56dd4dab..dd930278b2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def processData(): From a5888e120c4809e62dfc1ca5132b487fa4c4d2c3 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 22 Apr 2024 20:14:59 +0200 Subject: [PATCH 10/98] correct label --- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 28 +++++++++---------- .../uncertainties.yaml | 24 ++++++++-------- .../uncertainties.yaml | 26 ++++++++--------- .../uncertainties.yaml | 24 ++++++++-------- .../uncertainties.yaml | 24 ++++++++-------- 5 files changed, 63 insertions(+), 63 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml index d85950b6fb..0584f1292d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml @@ -2,59 +2,59 @@ definitions: sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_1: description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_2: description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_3: description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_4: description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_5: description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_6: description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_7: description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_8: description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_9: description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_10: description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_11: description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_12: description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_13: description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 bins: - sys_0: -1.0951625464162565e-09 sys_1: 1.1516691091869679e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml index abaa88e526..6391c635c0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml @@ -2,51 +2,51 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 stat: description: statistical uncertainty treatment: ADD diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml index 51030020ba..c412bc89c7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml @@ -2,55 +2,55 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 stat: description: statistical uncertainty treatment: ADD diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml index 7a887c47a3..dece180828 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml @@ -2,51 +2,51 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 stat: description: statistical uncertainty treatment: ADD diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml index ed1963c210..f0e185e052 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml @@ -2,51 +2,51 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: CORR + type: STAR2015 stat: description: statistical uncertainty treatment: ADD From 34e2c8bcbc67e5b54dc3f09f45e3a275c242c1ce Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 22 Apr 2024 20:15:08 +0200 Subject: [PATCH 11/98] correct label --- nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py index 6136b00de4..cab335895e 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py @@ -171,7 +171,7 @@ def write_1jet_data(df, art_sys, ndata): f"sys_{i}": { "description": f"{i} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", - "type": "CORR", + "type": "STAR2015", } for i in range(ndata) } @@ -217,7 +217,7 @@ def write_2jet_data(df, topology, art_sys, ndata): f"sys_{i}": { "description": f"{i} artificial correlated systematics uncertainty", "treatment": "ADD", - "type": "CORR", + "type": "STAR2015", } for i in range(ndata) } From 79bb21faf1470d8954d243a717826077abaabbf5 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 22 Apr 2024 22:34:43 +0200 Subject: [PATCH 12/98] fix art systematics --- .../filter_utils/star_2013_510gev.py | 86 +- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 896 ++++++++++++- .../uncertainties.yaml | 1110 +++++++++++++-- .../uncertainties.yaml | 1194 ++++++++++++++--- .../uncertainties.yaml | 1110 +++++++++++++-- .../uncertainties.yaml | 1110 +++++++++++++-- 6 files changed, 4839 insertions(+), 667 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py index cab335895e..2d02b583fe 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py @@ -1,12 +1,12 @@ """This script provides the common filer to the jet and dijet STAR 2013 datasets. Files need to be parsed all together as there are correlations provided. """ -import pandas as pd -import numpy as np import pathlib -import yaml from correlations import compute_covmat +import numpy as np +import pandas as pd +import yaml # values from the paper https://arxiv.org/pdf/2110.11020.pdf SQRTS = 510 @@ -157,24 +157,27 @@ def write_1jet_data(df, art_sys, ndata): # Write unc file error = [] - for i in range(ndata): + error_definition = {} + # loop on data points + for i, sys_i in enumerate(art_sys): e = {} - # add the art sys - for j in range(ndata): - e[f"sys_{j}"] = art_sys[i][j] - e[ - "stat" - ] = 0 # This is set to 0 as the stat unc is correlated and reported in sys_0 + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated statistical + systematics uncertainty", + "treatment": "ADD", + "type": "STAR2015", + } + for j in range(len(sys_i)) + } + ) error.append(e) - error_definition = { - f"sys_{i}": { - "description": f"{i} artificial correlated statistical + systematics uncertainty", - "treatment": "ADD", - "type": "STAR2015", - } - for i in range(ndata) - } uncertainties_yaml = {"definitions": error_definition, "bins": error} with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) @@ -205,31 +208,34 @@ def write_2jet_data(df, topology, art_sys, ndata): # Write unc file error = [] - for i in range(ndata): - e = {} - # add the art sys - for j in range(ndata): - e[f"sys_{j}"] = art_sys[i][j] - e["stat"] = float(df.loc[i, "stat"]) - error.append(e) - error_definition = { - f"sys_{i}": { - "description": f"{i} artificial correlated systematics uncertainty", + "stat": { + "description": "statistical uncertainty", "treatment": "ADD", - "type": "STAR2015", + "type": "UNCORR", } - for i in range(ndata) } - error_definition.update( - { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - } - } - ) + # loop on data points + for i, sys_i in enumerate(art_sys): + e = {} + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + e["stat"] = float(df.loc[i, "stat"]) + error.append(e) + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": "STAR2015", + } + for j in range(len(sys_i)) + } + ) + uncertainties_yaml = {"definitions": error_definition, "bins": error} with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) @@ -261,7 +267,7 @@ def write_2jet_data(df, topology, art_sys, ndata): cnt = 0 for topo, df in dfs.items(): ndata = ndata_dict[topo] - syst = art_sys[cnt:cnt+ndata, cnt:cnt+ndata].tolist() + syst = art_sys[cnt : cnt + ndata, :].tolist() if topo == "1JET": write_1jet_data(df, syst, ndata) else: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml index 0584f1292d..1ef751385c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml @@ -55,6 +55,202 @@ definitions: description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015 + sys_14: + description: 14 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_15: + description: 15 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_16: + description: 16 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_17: + description: 17 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_18: + description: 18 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_19: + description: 19 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_20: + description: 20 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_21: + description: 21 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_22: + description: 22 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_23: + description: 23 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_24: + description: 24 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_25: + description: 25 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_26: + description: 26 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_27: + description: 27 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_28: + description: 28 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_29: + description: 29 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_30: + description: 30 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_31: + description: 31 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_32: + description: 32 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_33: + description: 33 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_34: + description: 34 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_35: + description: 35 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_36: + description: 36 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_37: + description: 37 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_38: + description: 38 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_39: + description: 39 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_40: + description: 40 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_41: + description: 41 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_42: + description: 42 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_43: + description: 43 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_44: + description: 44 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_45: + description: 45 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_46: + description: 46 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_47: + description: 47 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_48: + description: 48 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_49: + description: 49 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_50: + description: 50 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_51: + description: 51 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_52: + description: 52 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_53: + description: 53 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_54: + description: 54 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_55: + description: 55 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_56: + description: 56 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_57: + description: 57 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_58: + description: 58 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_59: + description: 59 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_60: + description: 60 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_61: + description: 61 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 + sys_62: + description: 62 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015 bins: - sys_0: -1.0951625464162565e-09 sys_1: 1.1516691091869679e-08 @@ -70,7 +266,55 @@ bins: sys_11: 2.086134837183203e-05 sys_12: -3.067777040199403e-05 sys_13: -2.2721684612739994e-05 - stat: 0 + sys_14: -1.4463054685169093e-05 + sys_15: 3.5999936568569414e-08 + sys_16: 1.2815920167376136e-05 + sys_17: -3.7997341768995305e-06 + sys_18: 1.2795345455424942e-06 + sys_19: 3.0805921064734674e-06 + sys_20: 4.352543394974936e-06 + sys_21: 3.38643695082662e-07 + sys_22: -7.417477536355032e-07 + sys_23: 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treatment: ADD type: STAR2015 - stat: - description: statistical uncertainty + sys_12: + description: 12 artificial correlated systematics uncertainty treatment: ADD - type: UNCORR + type: STAR2015 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_54: + description: 54 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_55: + description: 55 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_56: + description: 56 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_57: + description: 57 artificial 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artificial correlated systematics uncertainty treatment: ADD type: STAR2015 - stat: - description: statistical uncertainty + sys_13: + description: 13 artificial correlated systematics uncertainty treatment: ADD - type: UNCORR + type: STAR2015 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_54: + description: 54 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_55: + description: 55 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_56: + description: 56 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_57: + description: 57 artificial correlated systematics uncertainty + treatment: ADD + type: 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uncertainty + sys_12: + description: 12 artificial correlated systematics uncertainty treatment: ADD - type: UNCORR + type: STAR2015 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_30: + description: 30 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correlated systematics uncertainty treatment: ADD type: STAR2015 - stat: - description: statistical uncertainty + sys_12: + description: 12 artificial correlated systematics uncertainty treatment: ADD - type: UNCORR + type: STAR2015 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_54: + description: 54 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_55: + description: 55 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_56: + description: 56 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015 + sys_57: + 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+ sys_23: 3.3801035196969704e-08 + sys_24: 3.3106475772528136e-05 + sys_25: -1.1477797795327538e-05 + sys_26: -4.4943171861651475e-06 + sys_27: 9.358906346218257e-06 + sys_28: -7.2411978843001205e-06 + sys_29: -2.451932270873732e-05 + sys_30: 2.8117668161532793e-06 + sys_31: -1.1471049141673807e-05 + sys_32: -1.549758013170435e-06 + sys_33: 1.957676455562059e-06 + sys_34: -1.8251236952983769e-06 + sys_35: 1.993794008786609e-06 + sys_36: 4.92093055058544e-07 + sys_37: 4.3922186763893265e-06 + sys_38: 9.290722736841817e-07 + sys_39: -1.0088518259228287e-06 + sys_40: 8.064896103782205e-07 + sys_41: -4.2439392979265107e-07 + sys_42: -8.33699331095173e-07 + sys_43: -7.695702706920173e-07 + sys_44: -8.800245450276794e-07 + sys_45: 1.284496870858482e-07 + sys_46: -1.0619129169777661e-06 + sys_47: 3.050016352434509e-06 + sys_48: -2.8038487616665674e-06 + sys_49: 1.8463951429481834e-07 + sys_50: 1.1634477428938096e-06 + sys_51: -1.3430015023569493e-07 + sys_52: -6.201118847936362e-07 + sys_53: -1.4876584314772848e-07 + sys_54: 6.587521288100003e-07 + sys_55: 1.2696667856314305e-07 + sys_56: 9.079687107449232e-07 + sys_57: -8.653149770338326e-07 + sys_58: -6.9656619477665965e-09 + sys_59: -4.274278312132293e-08 + sys_60: -5.857686756491707e-07 + sys_61: 4.5906629936432784e-07 + sys_62: 1.7755985099104273e-07 stat: 0.03187 From 250ea794ba33621cd34375c8b500165f5c8457e6 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 22 Apr 2024 22:40:48 +0200 Subject: [PATCH 13/98] fix metadata --- .../new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml | 2 +- .../new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml | 2 +- .../new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml | 2 +- .../new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml | 2 +- 4 files changed, 4 insertions(+), 4 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml index c7dba4a313..eb1b12396c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml @@ -22,7 +22,7 @@ implemented_observables: kinematics: variables: m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} file: kinematics.yaml kinematic_coverage: [m_jj, sqrts] data_central: data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml index 20d54714e0..88517aec19 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml @@ -22,7 +22,7 @@ implemented_observables: kinematics: variables: m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} file: kinematics.yaml kinematic_coverage: [m_jj, sqrts] data_central: data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml index 1e828f32ab..9cba81df37 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml @@ -22,7 +22,7 @@ implemented_observables: kinematics: variables: m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} file: kinematics.yaml kinematic_coverage: [m_jj, sqrts] data_central: data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml index 0ac491a3e6..be1e3c53c8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml @@ -22,7 +22,7 @@ implemented_observables: kinematics: variables: m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {"center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} file: kinematics.yaml kinematic_coverage: [m_jj, sqrts] data_central: data.yaml From fb54e162169560fda860b49218fba2a4651b5d3e Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 22 Apr 2024 23:34:12 +0200 Subject: [PATCH 14/98] make test passing --- .../filter_utils/star_2013_510gev.py | 14 +- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 126 +++++++++--------- .../STAR_2013_2JET_A_510GEV/kinematics.yaml | 24 ++-- .../uncertainties.yaml | 126 +++++++++--------- .../STAR_2013_2JET_B_510GEV/kinematics.yaml | 26 ++-- .../uncertainties.yaml | 126 +++++++++--------- .../STAR_2013_2JET_C_510GEV/kinematics.yaml | 24 ++-- .../uncertainties.yaml | 126 +++++++++--------- .../STAR_2013_2JET_D_510GEV/kinematics.yaml | 24 ++-- .../uncertainties.yaml | 126 +++++++++--------- .../STAR_2015_1JET_200GEV/metadata.yaml | 2 +- validphys2/src/validphys/commondataparser.py | 4 + validphys2/src/validphys/filters.py | 2 + validphys2/src/validphys/process_options.py | 20 ++- 14 files changed, 396 insertions(+), 374 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py index 2d02b583fe..8b68deba25 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py @@ -126,7 +126,7 @@ def read_correlations(ndata_dict): return tot_corr + tot_corr.T - np.eye(np.sum((*ndata_dict.values(),))) -def write_1jet_data(df, art_sys, ndata): +def write_1jet_data(df, art_sys): STORE_PATH = HERE / "new_commondata/STAR_2013_1JET_510GEV/" # Write central data @@ -171,7 +171,7 @@ def write_1jet_data(df, art_sys, ndata): f"sys_{j}": { "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", - "type": "STAR2015", + "type": f"STAR2013JETunc{j}", } for j in range(len(sys_i)) } @@ -183,7 +183,7 @@ def write_1jet_data(df, art_sys, ndata): yaml.dump(uncertainties_yaml, file, sort_keys=False) -def write_2jet_data(df, topology, art_sys, ndata): +def write_2jet_data(df, topology, art_sys): STORE_PATH = HERE / f"new_commondata/STAR_2013_2JET_{topology}_510GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} @@ -194,7 +194,7 @@ def write_2jet_data(df, topology, art_sys, ndata): kin = [] for i in range(len(df)): kin_value = { - "mjj": { + "m_jj": { "min": float(df.loc[i, "mjj_min"]), "mid": float(df.loc[i, "mjj"]), "max": float(df.loc[i, "mjj_max"]), @@ -230,7 +230,7 @@ def write_2jet_data(df, topology, art_sys, ndata): f"sys_{j}": { "description": f"{j} artificial correlated systematics uncertainty", "treatment": "ADD", - "type": "STAR2015", + "type": f"STAR2013JETunc{j}", } for j in range(len(sys_i)) } @@ -269,7 +269,7 @@ def write_2jet_data(df, topology, art_sys, ndata): ndata = ndata_dict[topo] syst = art_sys[cnt : cnt + ndata, :].tolist() if topo == "1JET": - write_1jet_data(df, syst, ndata) + write_1jet_data(df, syst) else: - write_2jet_data(df, topo, syst, ndata) + write_2jet_data(df, topo, syst) cnt += ndata diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml index 1ef751385c..8df1790037 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml @@ -2,255 +2,255 @@ definitions: sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc0 sys_1: description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc1 sys_2: description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc2 sys_3: description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc3 sys_4: description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc4 sys_5: description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc5 sys_6: description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc6 sys_7: description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc7 sys_8: description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc8 sys_9: description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc9 sys_10: description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc10 sys_11: description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc11 sys_12: description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc12 sys_13: description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc13 sys_14: description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc14 sys_15: description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc15 sys_16: description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc16 sys_17: description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc17 sys_18: description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc18 sys_19: description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc19 sys_20: description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc20 sys_21: description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc21 sys_22: description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc22 sys_23: description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc23 sys_24: description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc24 sys_25: description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc25 sys_26: description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc26 sys_27: description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc27 sys_28: description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc28 sys_29: description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc29 sys_30: description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc30 sys_31: description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc31 sys_32: description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc32 sys_33: description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc33 sys_34: description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc34 sys_35: description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc35 sys_36: description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc36 sys_37: description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc37 sys_38: description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc38 sys_39: description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc39 sys_40: description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc40 sys_41: description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc41 sys_42: description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc42 sys_43: description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc43 sys_44: description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc44 sys_45: description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc45 sys_46: description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc46 sys_47: description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc47 sys_48: description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc48 sys_49: description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc49 sys_50: description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc50 sys_51: description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc51 sys_52: description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc52 sys_53: description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc53 sys_54: description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc54 sys_55: description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc55 sys_56: description: 56 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc56 sys_57: description: 57 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc57 sys_58: description: 58 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc58 sys_59: description: 59 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc59 sys_60: description: 60 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc60 sys_61: description: 61 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc61 sys_62: description: 62 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc62 bins: - sys_0: -1.0951625464162565e-09 sys_1: 1.1516691091869679e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/kinematics.yaml index 183c61e511..20be3d2291 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/kinematics.yaml @@ -1,5 +1,5 @@ bins: -- mjj: +- m_jj: max: 17.16 mid: 15.74 min: 14.32 @@ -7,7 +7,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 19.64 mid: 18.5 min: 17.36 @@ -15,7 +15,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 22.91 mid: 21.96 min: 21.01 @@ -23,7 +23,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 27.110000000000003 mid: 26.17 min: 25.23 @@ -31,7 +31,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 32.67 mid: 31.63 min: 30.59 @@ -39,7 +39,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 39.16 mid: 37.8 min: 36.44 @@ -47,7 +47,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 46.1 mid: 44.75 min: 43.4 @@ -55,7 +55,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 54.81 mid: 53.31 min: 51.81 @@ -63,7 +63,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 65.37 mid: 63.64 min: 61.910000000000004 @@ -71,7 +71,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 77.38 mid: 75.32 min: 73.25999999999999 @@ -79,7 +79,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 92.17 mid: 89.66 min: 87.14999999999999 @@ -87,7 +87,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 108.53 mid: 105.63 min: 102.72999999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml index f5ddf3aa62..e383897cbe 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml @@ -6,255 +6,255 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc55 sys_56: description: 56 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc56 sys_57: description: 57 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc57 sys_58: description: 58 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc58 sys_59: description: 59 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc59 sys_60: description: 60 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc60 sys_61: description: 61 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc61 sys_62: description: 62 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc62 bins: - sys_0: -2.15815708458702e-08 sys_1: 1.0594463351038498e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/kinematics.yaml index 5a8d75d9c2..50a3d5933a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/kinematics.yaml @@ -1,5 +1,5 @@ bins: -- mjj: +- m_jj: max: 16.96 mid: 15.49 min: 14.02 @@ -7,7 +7,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 19.31 mid: 18.48 min: 17.650000000000002 @@ -15,7 +15,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 23.08 mid: 22.33 min: 21.58 @@ -23,7 +23,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 27.580000000000002 mid: 26.67 min: 25.76 @@ -31,7 +31,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 33.15 mid: 32.16 min: 31.169999999999998 @@ -39,7 +39,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 39.760000000000005 mid: 38.59 min: 37.42 @@ -47,7 +47,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 47.06999999999999 mid: 45.66 min: 44.25 @@ -55,7 +55,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 56.0 mid: 54.49 min: 52.980000000000004 @@ -63,7 +63,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 66.77 mid: 65.02 min: 63.269999999999996 @@ -71,7 +71,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 79.22999999999999 mid: 77.16 min: 75.09 @@ -79,7 +79,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 93.89999999999999 mid: 91.33 min: 88.76 @@ -87,7 +87,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 112.25 mid: 109.2 min: 106.15 @@ -95,7 +95,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 133.2 mid: 129.75 min: 126.3 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml index f5cdd760f9..1e29298891 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml @@ -6,255 +6,255 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc55 sys_56: description: 56 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc56 sys_57: description: 57 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc57 sys_58: description: 58 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc58 sys_59: description: 59 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc59 sys_60: description: 60 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc60 sys_61: description: 61 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc61 sys_62: description: 62 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc62 bins: - sys_0: -4.1525469266539024e-08 sys_1: 2.0171864231284964e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/kinematics.yaml index 1c121f1a75..c11cf4363b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/kinematics.yaml @@ -1,5 +1,5 @@ bins: -- mjj: +- m_jj: max: 17.26 mid: 15.72 min: 14.18 @@ -7,7 +7,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 19.889999999999997 mid: 18.9 min: 17.91 @@ -15,7 +15,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 23.259999999999998 mid: 22.24 min: 21.22 @@ -23,7 +23,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 28.12 mid: 27.14 min: 26.16 @@ -31,7 +31,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 34.120000000000005 mid: 33.03 min: 31.94 @@ -39,7 +39,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 40.78 mid: 39.35 min: 37.92 @@ -47,7 +47,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 48.16 mid: 46.62 min: 45.08 @@ -55,7 +55,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 57.45 mid: 55.74 min: 54.03 @@ -63,7 +63,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 68.32000000000001 mid: 66.39 min: 64.46 @@ -71,7 +71,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 81.23 mid: 78.97 min: 76.71 @@ -79,7 +79,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 97.07 mid: 94.22 min: 91.37 @@ -87,7 +87,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 114.7 mid: 111.48 min: 108.26 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml index cfa04db442..1aab75fd81 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml @@ -6,255 +6,255 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc55 sys_56: description: 56 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc56 sys_57: description: 57 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc57 sys_58: description: 58 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc58 sys_59: description: 59 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc59 sys_60: description: 60 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc60 sys_61: description: 61 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc61 sys_62: description: 62 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc62 bins: - sys_0: -4.218515531944061e-07 sys_1: 1.2027789348309312e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml index b9a9c8476d..1fd76f3d0e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml @@ -1,5 +1,5 @@ bins: -- mjj: +- m_jj: max: 19.349999999999998 mid: 18.2 min: 17.05 @@ -7,7 +7,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 22.71 mid: 21.67 min: 20.630000000000003 @@ -15,7 +15,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 27.16 mid: 26.12 min: 25.080000000000002 @@ -23,7 +23,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 32.440000000000005 mid: 31.42 min: 30.400000000000002 @@ -31,7 +31,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 38.58 mid: 37.33 min: 36.08 @@ -39,7 +39,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 46.11 mid: 44.6 min: 43.09 @@ -47,7 +47,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 55.3 mid: 53.61 min: 51.92 @@ -55,7 +55,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 65.31 mid: 63.38 min: 61.45 @@ -63,7 +63,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 77.78999999999999 mid: 75.52 min: 73.25 @@ -71,7 +71,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 92.3 mid: 89.6 min: 86.89999999999999 @@ -79,7 +79,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 109.83 mid: 106.63 min: 103.42999999999999 @@ -87,7 +87,7 @@ bins: max: null mid: 510.0 min: null -- mjj: +- m_jj: max: 130.99 mid: 127.17 min: 123.35000000000001 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml index 049db3afe6..78493a2223 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml @@ -6,255 +6,255 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc55 sys_56: description: 56 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc56 sys_57: description: 57 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc57 sys_58: description: 58 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc58 sys_59: description: 59 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc59 sys_60: description: 60 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc60 sys_61: description: 61 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc61 sys_62: description: 62 artificial correlated systematics uncertainty treatment: ADD - type: STAR2015 + type: STAR2013JETunc62 bins: - sys_0: -8.802670691481952e-07 sys_1: 2.9027374291159905e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml index 28ac029853..8fe7c9a23f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml @@ -17,7 +17,7 @@ implemented_observables: - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } observable_name: ALL process_type: JET_POL - ndata: 21 + ndata: 22 tables: [3, 4] npoints: [11, 10] kinematics: diff --git a/validphys2/src/validphys/commondataparser.py b/validphys2/src/validphys/commondataparser.py index dc2df55599..d9e8c7c5f6 100644 --- a/validphys2/src/validphys/commondataparser.py +++ b/validphys2/src/validphys/commondataparser.py @@ -109,6 +109,8 @@ def _quick_yaml_load(filepath): "JET": ("$\\eta$", "$p_T^2 (GeV^2)$", "$\\sqrt{s} (GeV)$"), "PHT": ("$\\eta_\\gamma$", "$E_{T,\\gamma}^2 (GeV^2)$", "$\\sqrt{s} (GeV)$"), "SIA": ("$z$", "$Q^2 (GeV^2)$", "$y$"), + "JET_POL": ("$\\eta$", "$p_T^2 (GeV^2)$", "$\\sqrt{s} (GeV)$"), + "DIJET_POL": ("\\eta", "$\\m_{1,2} (GeV)", "$\\sqrt{s} (GeV)"), } PROCESS_DESCRIPTION_LABEL = { @@ -133,6 +135,8 @@ def _quick_yaml_load(filepath): "EWK_MLL": "Drell-Yan Mass Distribution", "DIJET": "Dijets Invariant Mass and Rapidity Distribution", "DYP": "Fixed-Target Drell-Yan", + "JET_POL": "Longitudinal double-spin asymmetry", + "DIJET_POL": "Longitudinal double-spin asymmetry", } diff --git a/validphys2/src/validphys/filters.py b/validphys2/src/validphys/filters.py index cded762eab..5201f12a8d 100644 --- a/validphys2/src/validphys/filters.py +++ b/validphys2/src/validphys/filters.py @@ -43,6 +43,8 @@ "HQP_PTQ": ("p_TQ", "mu2", "sqrts"), "HIG_RAP": ("y", "M_H2", "sqrts"), "SIA": ("z", "Q2", "y"), + "JET_POL": ("eta", "pT2", "sqrts"), + "DIJET_POL": ("eta", "m_12", "sqrts"), } diff --git a/validphys2/src/validphys/process_options.py b/validphys2/src/validphys/process_options.py index 73435ea92e..6c93a66cc0 100644 --- a/validphys2/src/validphys/process_options.py +++ b/validphys2/src/validphys/process_options.py @@ -233,11 +233,25 @@ def _dywboson_xq2map(kin_dict): DIJET = _Process( "DIJET", - "DiJets Production", + "DiJets production", accepted_variables=(_Vars.ystar, _Vars.m_jj, _Vars.sqrts, _Vars.ydiff), xq2map_function=_dijets_xq2map, ) +JET_POL = _Process( + "JET_POL", + "Longitudinal double-spin asymmetry in inclusive jet production", + accepted_variables=(_Vars.eta, _Vars.pT, _Vars.sqrts), + xq2map_function=_jets_xq2map, +) + +DIJET_POL = _Process( + "DIJET_POL", + "Longitudinal double-spin asymmetry in dijets production", + accepted_variables=(_Vars.m_jj, _Vars.sqrts), + xq2map_function=_dijets_xq2map, +) + HQP_YQ = _Process( "HQP_YQ", "Normalized differential cross section w.r.t. absolute rapidity of t", @@ -287,7 +301,9 @@ def _dywboson_xq2map(kin_dict): "HQP_PTQ": HQP_PTQ, "HERAJET": HERAJET, "HERADIJET": dataclasses.replace(HERAJET, name="HERADIJET", description="DIS + jj production"), - "DY_W_ETA": DY_W_ETA + "DY_W_ETA": DY_W_ETA, + "JET_POL": JET_POL, + "DIJET_POL": DIJET_POL, } From 9d3f3f457684467472dfec2631336420a941f496 Mon Sep 17 00:00:00 2001 From: Toon Hasenack Date: Tue, 23 Apr 2024 14:06:02 +0200 Subject: [PATCH 15/98] Giacomo's suggestions with 1 to go --- .../STAR_2005_1JET_200GEV/data.yaml | 11 + .../filter.py | 6 +- .../STAR_2005_1JET_200GEV/kinematics.yaml | 121 ++++ .../metadata.yaml | 10 +- .../rawdata/Table_14.yaml | 0 .../uncertainties.yaml | 18 - .../STAR_2006_1JET_200GEV/data.yaml | 10 + .../STAR_2006_1JET_200GEV/filter.py | 115 ++++ .../kinematics.yaml | 120 ---- .../STAR_2006_1JET_200GEV/metadata.yaml | 52 ++ .../rawdata/Table_15.yaml | 0 .../STAR_2006_1JET_200GEV/uncertainties.yaml | 28 + .../data.yaml | 0 .../filter.py | 46 +- .../kinematics.yaml | 132 ++-- .../metadata.yaml | 8 +- .../rawdata/Table_3_ALL.csv | 0 .../rawdata/Table_3_pT.csv | 0 .../rawdata/Table_4_ALL.csv | 0 .../rawdata/Table_4_pT.csv | 0 .../rawdata/Table_5.csv | 0 .../STAR_2009_1JET_200GEV/uncertainties.yaml | 574 ++++++++++++++++ .../STAR_2012_1JET_200GEV/data.yaml | 20 - .../STAR_2015_1JET_200GEV/uncertainties.yaml | 626 ------------------ 24 files changed, 1004 insertions(+), 893 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/data.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_1JET_200GEV => STAR_2005_1JET_200GEV}/filter.py (95%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/kinematics.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_1JET_200GEV => STAR_2005_1JET_200GEV}/metadata.yaml (90%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_1JET_200GEV => STAR_2005_1JET_200GEV}/rawdata/Table_14.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_1JET_200GEV => STAR_2005_1JET_200GEV}/uncertainties.yaml (60%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_1JET_200GEV => STAR_2006_1JET_200GEV}/kinematics.yaml (50%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_1JET_200GEV => STAR_2006_1JET_200GEV}/rawdata/Table_15.yaml (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/data.yaml (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/filter.py (74%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/kinematics.yaml (74%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/metadata.yaml (94%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/rawdata/Table_3_ALL.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/rawdata/Table_3_pT.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/rawdata/Table_4_ALL.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/rawdata/Table_4_pT.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_1JET_200GEV => STAR_2009_1JET_200GEV}/rawdata/Table_5.csv (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/data.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/data.yaml new file mode 100644 index 0000000000..b5bc5e2f36 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/data.yaml @@ -0,0 +1,11 @@ +data_central: +- 0.0053 +- -0.00275 +- 0.0023 +- 0.01465 +- -0.00625 +- 0.0031000000000000003 +- -0.0142 +- -0.0522 +- 0.0569 +- 0.147 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py similarity index 95% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py index a4fe2af75e..b31a0748fc 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py @@ -2,8 +2,10 @@ import pandas as pd import yaml +import sys -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +sys.path.append('../../') +from filter_utils.uncertainties import symmetrize_errors as se def read_data(fnames): @@ -48,7 +50,7 @@ def read_data(fnames): ignore_index=True, ) for i in range(len(df)): - shift, unc = symmetrize_errors(df.loc[i, "sys_max"], df.loc[i, "sys_min"]) + shift, unc = se(df.loc[i, "sys_max"], df.loc[i, "sys_min"]) df.loc[i, "sys"] = unc df.loc[i, "ALL"] += shift diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/kinematics.yaml new file mode 100644 index 0000000000..c0c8b17dfd --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/kinematics.yaml @@ -0,0 +1,121 @@ +bins: +- pT: + min: 4.9 + mid: 5.3 + max: 5.7 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 5.9 + mid: 6.3 + max: 6.8 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 6.7 + mid: 7.1 + max: 7.7 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 8.1 + mid: 8.7 + max: 9.4 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 10.0 + mid: 10.7 + max: 11.5 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 12.3 + mid: 13.1 + max: 14.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 15.2 + mid: 16.0 + max: 17.0 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 18.4 + mid: 19.4 + max: 20.7 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 22.4 + mid: 23.6 + max: 25.1 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 26.7 + mid: 28.1 + max: 29.9 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml similarity index 90% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml index ca0b772dbe..aa7892ff86 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml @@ -1,4 +1,4 @@ -setname: "STAR_2012_1JET_200GEV" +setname: "STAR_2005_1JET_200GEV" nnpdf_metadata: experiment: "STAR" @@ -17,9 +17,9 @@ implemented_observables: - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } observable_name: ALL process_type: JET_POL - ndata: 19 - tables: [14, 15] - npoints: [10, 9] + ndata: 10 + tables: [14] + npoints: [10] kinematics: variables: pT: @@ -49,4 +49,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_1JET_200GEV_ALL + - - STAR_2005_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_14.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/rawdata/Table_14.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_14.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/rawdata/Table_14.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/uncertainties.yaml similarity index 60% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/uncertainties.yaml index deef3a4deb..8c448e3378 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/uncertainties.yaml @@ -28,21 +28,3 @@ bins: sys: 0.0040999999999999995 - stat: 0.138 sys: 0.004908156476723211 -- stat: 0.0053 - sys: 0.00331058907144937 -- stat: 0.0043 - sys: 0.002011839953873071 -- stat: 0.0040999999999999995 - sys: 0.002011839953873071 -- stat: 0.0045000000000000005 - sys: 0.001366565036871645 -- stat: 0.0058 - sys: 0.0011521718621802911 -- stat: 0.0088 - sys: 0.0015898113095584648 -- stat: 0.0154 - sys: 0.0033537292675468 -- stat: 0.031 - sys: 0.004576843890717707 -- stat: 0.0706 - sys: 0.005853204250664759 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/data.yaml new file mode 100644 index 0000000000..9a5cd41d27 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/data.yaml @@ -0,0 +1,10 @@ +data_central: +- 0.0033 +- 0.00365 +- 0.01025 +- 0.00135 +- 0.00925 +- 0.02595 +- 0.026850000000000002 +- 0.02375 +- 0.0139 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py new file mode 100644 index 0000000000..b31a0748fc --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py @@ -0,0 +1,115 @@ +import glob + +import pandas as pd +import yaml +import sys + +sys.path.append('../../') +from filter_utils.uncertainties import symmetrize_errors as se + + +def read_data(fnames): + df = pd.DataFrame() + for fname in fnames: + with open(fname, "r") as file: + data = yaml.safe_load(file) + if "14" in fname: + eta_min = 0.2 + eta_max = 0.8 + + elif "15" in fname: + eta_min = -0.7 + eta_max = 0.9 + + else: + print("ERROR: Unknown table number detected! Check input files.") + + pTsub = data["independent_variables"][0]["values"] + ALLsub = data["dependent_variables"][0]["values"] + + for i in range(len(ALLsub)): + df = pd.concat( + [ + df, + pd.DataFrame( + { + "pT": [pTsub[i]["value"]], + "pTmin": [pTsub[i]["low"]], + "pTmax": [pTsub[i]["high"]], + "eta": [(eta_min + eta_max) / 2], + "eta_min": [eta_min], + "eta_max": [eta_max], + "sqrts": [200], + "ALL": [ALLsub[i]["value"] * 1e-3], + "stat": [ALLsub[i]["errors"]["symerror"]["value"] * 1e-3], + "sys_min": [ALLsub[i]["errors"]["asymerror"]["minus"] * 1e-3], + "sys_max": [ALLsub[i]["errors"]["asymerror"]["plus"] * 1e-3], + } + ), + ], + ignore_index=True, + ) + for i in range(len(df)): + shift, unc = se(df.loc[i, "sys_max"], df.loc[i, "sys_min"]) + df.loc[i, "sys"] = unc + df.loc[i, "ALL"] += shift + + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["ALL"])): + data_central.append(float(df.loc[i, "ALL"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["ALL"])): + kin_value = { + "pT": { + "min": float(df.loc[i, "pTmin"]), + "mid": float(df.loc[i, "pT"]), + "max": float(df.loc[i, "pTmax"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": { + "min": float(df.loc[i, "eta_min"]), + "mid": float(df.loc[i, "eta"]), + "max": float(df.loc[i, "eta_max"]), + }, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for i in range(len(df)): + e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + error.append(e) + + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # TODO: Need to generate `observable` cards and corresponding + # pineappl grids and FK tables as the orders have changed!!!! + fnames = glob.glob("rawdata/*.yaml") + nnames = sorted([i for i in fnames]) + df = read_data(nnames) + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/kinematics.yaml similarity index 50% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/kinematics.yaml index f183806bd3..b9f422549d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/kinematics.yaml @@ -1,124 +1,4 @@ bins: -- pT: - min: 4.9 - mid: 5.3 - max: 5.7 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 5.9 - mid: 6.3 - max: 6.8 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 6.7 - mid: 7.1 - max: 7.7 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 8.1 - mid: 8.7 - max: 9.4 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 10.0 - mid: 10.7 - max: 11.5 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 12.3 - mid: 13.1 - max: 14.0 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 15.2 - mid: 16.0 - max: 17.0 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 18.4 - mid: 19.4 - max: 20.7 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 22.4 - mid: 23.6 - max: 25.1 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 -- pT: - min: 26.7 - mid: 28.1 - max: 29.9 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: 0.2 - mid: 0.5 - max: 0.8 - pT: min: 7.8 mid: 8.5 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml new file mode 100644 index 0000000000..b8dfe98236 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml @@ -0,0 +1,52 @@ +setname: "STAR_2006_1JET_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1114529" +hepdata: + url: "https://www.hepdata.net/record/ins1114529" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: JET_POL + ndata: 9 + tables: [15] + npoints: [9] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, eta] + plotting: + kinematics_override: identity + dataset_label: "$A_{LL}$" + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2006_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_15.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/rawdata/Table_15.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_200GEV/rawdata/Table_15.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/rawdata/Table_15.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..ad0bdfe9d1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml @@ -0,0 +1,28 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + sys: + description: systematic uncertainty + treatment: ADD + type: UNCORR +bins: +- stat: 0.0053 + sys: 0.00331058907144937 +- stat: 0.0043 + sys: 0.002011839953873071 +- stat: 0.0040999999999999995 + sys: 0.002011839953873071 +- stat: 0.0045000000000000005 + sys: 0.001366565036871645 +- stat: 0.0058 + sys: 0.0011521718621802911 +- stat: 0.0088 + sys: 0.0015898113095584648 +- stat: 0.0154 + sys: 0.0033537292675468 +- stat: 0.031 + sys: 0.004576843890717707 +- stat: 0.0706 + sys: 0.005853204250664759 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py similarity index 74% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index 3801674e29..98c4fc95ff 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -2,9 +2,10 @@ import pandas as pd import yaml +import sys -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors -from nnpdf_data.filter_utils.correlations import compute_covmat +sys.path.append('../../') +from filter_utils.correlations import compute_covmat def read_data(fnames): @@ -24,9 +25,8 @@ def read_data(fnames): df3["sys_min"] = dfi["sys +"] df3["sys_max"] = dfi["sys -"] - df3["eta_min"] = -0.5 - df3["eta_max"] = 0.5 - df3["eta"] = 0.0 + df3["abs_eta_min"] = 0.0 + df3["abs_eta_max"] = 0.5 df3["sqrts"] = 200 elif "4" in fname: @@ -42,9 +42,8 @@ def read_data(fnames): df4["sys_min"] = dfi["sys +"] df4["sys_max"] = dfi["sys -"] - df4["eta_min"] = -1.0 - df4["eta_max"] = 1.0 - df4["eta"] = 0.0 + df4["abs_eta_min"] = 0.5 + df4["abs_eta_max"] = 1.0 df4["sqrts"] = 200 elif "5" in fname: @@ -68,14 +67,8 @@ def read_data(fnames): df = pd.concat([df3, df4], ignore_index=True) for i in range(len(df)): - shift, unc = symmetrize_errors(df.loc[i, "stat_max"], df.loc[i, "stat_min"]) - df.loc[i, "stat"] = unc - df.loc[i, "ALL"] += shift - - shift, unc = symmetrize_errors(df.loc[i, "sys_max"], df.loc[i, "sys_min"]) - df.loc[i, "sys"] = unc - df.loc[i, "ALL"] += shift - + df.loc[i, "stat"] = df.loc[i, "stat_max"] + df.loc[i, "sys"] = df.loc[i, "sys_max"] return df, dfc @@ -98,10 +91,10 @@ def write_data(df, dfc): kin_value = { "pT": {"min": None, "mid": float(df.loc[i, "pT"]), "max": None}, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, - "eta": { - "min": float(df.loc[i, "eta_min"]), - "mid": float(df.loc[i, "eta"]), - "max": float(df.loc[i, "eta_max"]), + "abs_eta": { + "min": float(df.loc[i, "abs_eta_min"]), + "mid": None, + "max": float(df.loc[i, "abs_eta_max"]), }, } kin.append(kin_value) @@ -114,7 +107,7 @@ def write_data(df, dfc): # Write unc file error = [] for i in range(len(df)): - e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + e = {} for j in range(len(df)): e[f"sys_{j}"] = art_sys[i][j] error.append(e) @@ -128,17 +121,6 @@ def write_data(df, dfc): for i in range(len(df)) } - error_definition.update( - { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - }, - "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, - } - ) - uncertainties_yaml = {"definitions": error_definition, "bins": error} with open("uncertainties.yaml", "w") as file: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml similarity index 74% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml index 36d1079c95..6cf872824d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml @@ -7,9 +7,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -19,9 +19,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -31,9 +31,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -43,9 +43,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -55,9 +55,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -67,9 +67,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -79,9 +79,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -91,9 +91,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -103,9 +103,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -115,9 +115,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -127,9 +127,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -0.5 - mid: 0.0 + abs_eta: + min: 0.0 + mid: null max: 0.5 - pT: min: null @@ -139,9 +139,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -151,9 +151,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -163,9 +163,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -175,9 +175,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -187,9 +187,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -199,9 +199,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -211,9 +211,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -223,9 +223,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -235,9 +235,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -247,9 +247,9 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 - pT: min: null @@ -259,7 +259,7 @@ bins: min: null mid: 200.0 max: null - eta: - min: -1.0 - mid: 0.0 + abs_eta: + min: 0.5 + mid: null max: 1.0 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml similarity index 94% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml index 8fe7c9a23f..48ee1f0637 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml @@ -1,13 +1,13 @@ -setname: "STAR_2015_1JET_200GEV" +setname: "STAR_2009_1JET_200GEV" nnpdf_metadata: experiment: "STAR" nnpdf31_process: "JETS" iNSPIRE: - url: "https://www.hepdata.net/record/ins1297229" -hepdata: url: "https://inspirehep.net/literature/1297229" +hepdata: + url: "https://www.hepdata.net/record/ins1297229" version: 1 version: 1 @@ -49,4 +49,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_1JET_200GEV_ALL + - - STAR_2009_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_ALL.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_ALL.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_ALL.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_ALL.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_pT.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_pT.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_3_pT.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_pT.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_ALL.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_ALL.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_ALL.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_ALL.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_pT.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_pT.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_4_pT.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_pT.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_5.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table_5.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_5.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..74bd2bd5f8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml @@ -0,0 +1,574 @@ +definitions: + sys_0: + description: 0 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_1: + description: 1 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_2: + description: 2 artificial correlated statistical uncertainty + 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statistical uncertainty + treatment: ADD + type: CORR + sys_13: + description: 13 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_14: + description: 14 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_15: + description: 15 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_16: + description: 16 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_17: + description: 17 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_18: + description: 18 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_19: + description: 19 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_20: + description: 20 artificial correlated statistical uncertainty + treatment: ADD + type: CORR + sys_21: + description: 21 artificial correlated statistical uncertainty + treatment: ADD + type: CORR +bins: +- 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2 +- .../STAR_2013_2JET_A_510GEV/metadata.yaml | 2 +- .../STAR_2013_2JET_B_510GEV/metadata.yaml | 2 +- .../STAR_2013_2JET_C_510GEV/metadata.yaml | 2 +- .../STAR_2013_2JET_D_510GEV/metadata.yaml | 2 +- 9 files changed, 347 insertions(+), 20 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/filter_utils/manipulate.py rename nnpdf_data/nnpdf_data/filter_utils/{star_2013_510gev.py => star/jet_dijet_2013_510gev.py} (95%) create mode 100644 nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py diff --git a/nnpdf_data/nnpdf_data/filter_utils/correlations.py b/nnpdf_data/nnpdf_data/filter_utils/correlations.py index 8589fd1c6c..6f01f09bc1 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/correlations.py +++ b/nnpdf_data/nnpdf_data/filter_utils/correlations.py @@ -2,6 +2,18 @@ from numpy.linalg import eig +def upper_triangular_to_symmetric(ut, dim): + """Build a symmetric matrix from the upper diagonal""" + corr = np.zeros((dim, dim)) + last = dim + first = 0 + for i in range(dim): + corr[i, i:] = ut[first:last] + last += dim - i - 1 + first += dim - i + return corr + corr.T - np.eye(dim) + + def compute_covmat(corrmat: np.ndarray, unc: np.ndarray, ndata: int) -> list: """Compute the covariance matrix with the artificial stat uncertainties.""" # multiply by stat err diff --git a/nnpdf_data/nnpdf_data/filter_utils/manipulate.py b/nnpdf_data/nnpdf_data/filter_utils/manipulate.py new file mode 100644 index 0000000000..4fd31eae71 --- /dev/null +++ b/nnpdf_data/nnpdf_data/filter_utils/manipulate.py @@ -0,0 +1,21 @@ + +def concatenate_dicts(multidict: list[dict]) -> dict: + """Given a list of dictionaries combined the values. + + Parameters + ---------- + multidict: list[dict] + list of dictionaries with the same keys + + Returns + ------- + dict: + dictionary whose keys are combined + """ + new_dict = {} + for key in multidict[0].keys(): + new_dict[key] = [] + for element in multidict: + new_dict[key] += element[key] + + return new_dict \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py similarity index 95% rename from nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py rename to nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 8b68deba25..92c8b15efb 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -3,17 +3,18 @@ """ import pathlib -from correlations import compute_covmat import numpy as np import pandas as pd import yaml +from nnpdf_data.filter_utils.correlations import compute_covmat, upper_triangular_to_symmetric + # values from the paper https://arxiv.org/pdf/2110.11020.pdf SQRTS = 510 ETA_ABS = 0.9 TOPOPLOGY_LIST = ["1JET", "A", "B", "C", "D"] -HERE = pathlib.Path(__file__).parents[1] +HERE = pathlib.Path(__file__).parents[2] RAWDATA_PATH = HERE / "new_commondata/STAR_2013_1JET_510GEV/rawdata/" @@ -79,18 +80,6 @@ def get_correlation_label(a): return f"Dijettopology{a}" -def upper_triangular_to_symmetric(ut, dim): - """Build a symmetric matrix from the upper diagonal""" - corr = np.zeros((dim, dim)) - last = dim - first = 0 - for i in range(dim): - corr[i, i:] = ut[first:last] - last += dim - i - 1 - first += dim - i - return corr + corr.T - np.eye(dim) - - def read_correlations(ndata_dict): """Read the correlation files and build a big matix""" corr_rows = [] @@ -260,7 +249,6 @@ def write_2jet_data(df, topology, art_sys): correlated_unc.extend(dfs[a]["syst"].values) ndata_points = np.sum((*ndata_dict.values(),)) # decompose uncertainties - # TODO: how come this is not yet block diagonal?? art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) # write data diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py new file mode 100644 index 0000000000..2beb5911d1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -0,0 +1,306 @@ +"""This script provides the common filer to the jet and dijet STAR 2015 datasets. +Files need to be parsed all together as there are correlations provided. +""" +import pathlib + +import numpy as np +import pandas as pd +import yaml + +from nnpdf_data.filter_utils.correlations import compute_covmat, upper_triangular_to_symmetric + +# values from the paper +SQRTS = 200 +YEAR = 2015 +# mapping between topologies, tables and abs_eta values +TOPOPLOGY_LIST = { + "CC": ("bottom", 0, 0.5), + "CF": ("top", 0.5, 1.0), + "OS": "bottom", + "SS": "top", +} + +# mapping between correlations blocks and tables +MAP_CORR_TABLE = { + ("CC", "CC"): 2, + ("CC", "CF"): 4, + ("CC", "OS"): 8, + ("CC", "SS"): 7, + ("CF", "CF"): 1, + ("CF", "OS"): 6, + ("CF", "SS"): 5, + ("OS", "OS"): 12, + ("OS", "SS"): 13, + ("SS", "SS"): 11, +} + +HERE = pathlib.Path(__file__).parents[2] +RAWDATA_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/rawdata/" + + +def read_1jet_data(topology): + table_label = TOPOPLOGY_LIST[topology][0] + max_eta = TOPOPLOGY_LIST[topology][2] + min_eta = TOPOPLOGY_LIST[topology][1] + data_table = pathlib.Path(RAWDATA_PATH / f"Table1{table_label}.csv") + + with open(data_table, "r", encoding="utf-8") as file: + parton_jet_data = pd.read_csv( + file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 20) + ) + with open(data_table, "r", encoding="utf-8") as file: + all_data = pd.read_csv(file, delimiter=",", skiprows=21) + + df = pd.DataFrame() + df["pT"] = parton_jet_data[ + r"Inclusive jet transverse momentum $p_T$ at the parton level [GeV/$c$]" + ] + df["pT_min"] = df["pT"] + parton_jet_data["Syst -"] + df["pT_max"] = df["pT"] + parton_jet_data["Syst +"] + df["abs_eta"] = (max_eta + min_eta) / 2 + df["abs_eta_min"] = min_eta + df["abs_eta_max"] = max_eta + df["sqrts"] = SQRTS + df["ALL"] = all_data[r"Double spin asymmetry $A_{LL}$"] + df["stat"] = all_data["Stat +"] + df["syst"] = all_data["Syst +"] + df["lumi"] = all_data["Lumi +"] + df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] + + print(f"1JET {topology} data loaded. Npoint: ", len(df)) + return df + + +def read_2jet_data(topology): + table_label = TOPOPLOGY_LIST[topology] + data_table = RAWDATA_PATH / f"Table2{table_label}.csv" + with open(data_table, "r", encoding="utf-8") as file: + mjj_data = pd.read_csv( + file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 16) + ) + with open(data_table, "r", encoding="utf-8") as file: + all_data = pd.read_csv(file, delimiter=",", skiprows=27) + + df = pd.DataFrame() + df["mjj"] = mjj_data['Dijet invariant mass $M_{inv}$ at the parton level [GeV/$c$]'] + df["mjj_min"] = df["mjj"] + mjj_data["Syst -"] + df["mjj_max"] = df["mjj"] + mjj_data["Syst +"] + df["sqrts"] = SQRTS + df["ALL"] = all_data[r"Double spin asymmetry $A_{LL}$"] + df["stat"] = all_data["Stat +"] + df["syst"] = all_data["Syst +"] + df["lumi"] = all_data["Lumi +"] + df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] + + print(f"2JET {topology} data loaded. Npoint: ", len(df)) + return df + + +def read_correlations(ndata_dict): + """Read the correlation files and build a big matix""" + corr_rows = [] + + # loop on block rows + for a, ndata_a in ndata_dict.items(): + la = [a for _ in range(ndata_a)] + corr_row = pd.DataFrame() + + # loop on block columns + for b, ndata_b in ndata_dict.items(): + lb = [b for _ in range(ndata_b)] + + # build the block + try: + idx = MAP_CORR_TABLE[(a, b)] + with open( + RAWDATA_PATH / f"Table{idx}SupplementalMaterial.csv", + encoding="utf-8", + ) as file: + corr_df = pd.read_csv(file, delimiter=",", skiprows=7) + + if a == b: + corr = upper_triangular_to_symmetric(corr_df.values[:, 2], ndata_a) + else: + corr = corr_df.values[:, 2].reshape((ndata_a, ndata_b)) + except (FileNotFoundError, KeyError) as _: + corr = pd.DataFrame(np.zeros((ndata_a, ndata_b)), index=la, columns=lb) + + corr = pd.DataFrame(corr, index=la, columns=lb) + corr_row = pd.concat([corr_row, corr], axis=1) + corr_rows.append(corr_row) + + tot_corr = pd.concat(corr_rows) + return tot_corr + tot_corr.T - np.eye(np.sum((*ndata_dict.values(),))) + + +def write_1jet_data(df, art_sys): + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/" + + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + kin_value = { + "pT": { + "min": float(df.loc[i, "pT_min"]), + "mid": float(df.loc[i, "pT"]), + "max": float(df.loc[i, "pT_max"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "abs_eta": { + "min": float(df.loc[i, "abs_eta_min"]), + "mid": float(df.loc[i, "abs_eta"]), + "max": float(df.loc[i, "abs_eta_max"]), + }, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + error_definition = { + "lumi": { + "description": "luminosity uncertainty", + "treatment": "ADD", + "type": "UNCORR", + } + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = {} + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated statistical + systematics uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}JETunc{j}", + } + for j in range(len(sys_i)) + } + ) + e["lumi"] = float(df.loc[i, "lumi"]) + error.append(e) + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +def write_2jet_data(df, topology, art_sys): + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{topology}_{SQRTS}GEV/" + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + kin_value = { + "m_jj": { + "min": float(df.loc[i, "mjj_min"]), + "mid": float(df.loc[i, "mjj"]), + "max": float(df.loc[i, "mjj_max"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + error_definition = { + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "lumi": { + "description": "luminosity uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = {} + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + e["stat"] = float(df.loc[i, "stat"]) + e["lumi"] = float(df.loc[i, "lumi"]) + error.append(e) + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}JETunc{j}", + } + for j in range(len(sys_i)) + } + ) + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # load all the data + dfs = {} + for topo in TOPOPLOGY_LIST: + fcn = read_1jet_data if "C" in topo else read_2jet_data + dfs[topo] = fcn(topo) + + # load correlations + ndata_dict = {a: len(b) for a, b in dfs.items()} + correlation_df = read_correlations(ndata_dict) + + # merge the 1JET topologies + new_dfs = { + "1JET": pd.concat([dfs['CC'], dfs['CF']], ignore_index=True), + "OS": dfs["OS"], + "SS": dfs["SS"] + } + + # from the paper we understand that stat dijet is not correlated + # I-I (stat + sys) | I-D (stat + sys) + # D-I (stat + sys) | D-D (sys) + correlated_unc = np.sqrt( + new_dfs["1JET"]["syst"] ** 2 + new_dfs["1JET"]["stat"] ** 2 + ).values.tolist() + for a in (*TOPOPLOGY_LIST,)[2:]: + correlated_unc.extend(new_dfs[a]["syst"].values) + + import pdb; pdb.set_trace() + # decompose uncertainties + ndata_dict = {a: len(b) for a, b in new_dfs.items()} + ndata_points = np.sum((*ndata_dict.values(),)) + art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) + + # write data + cnt = 0 + for topo, df in new_dfs.items(): + ndata = ndata_dict[topo] + syst = art_sys[cnt : cnt + ndata, :].tolist() + if topo == "1JET": + write_1jet_data(df, syst) + else: + write_2jet_data(df, topo, syst) + cnt += ndata diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml index 72b51bfebf..0713622d3e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml @@ -40,7 +40,7 @@ implemented_observables: - uncertainties.yaml kinematic_coverage: [pT, sqrts, eta] plotting: - dataset_label: "STAR 510 TeV (2013) 1-JET $A_{LL}$" + dataset_label: "STAR 510 GeV (2013) 1-JET $A_{LL}$" kinematics_override: identity plot_x: pT x_scale: log diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml index eb1b12396c..add2f35e89 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml @@ -29,7 +29,7 @@ implemented_observables: data_uncertainties: - uncertainties.yaml plotting: - dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology A" kinematics_override: identity plot_x: m_jj x_scale: log diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml index 88517aec19..01e3001a36 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml @@ -29,7 +29,7 @@ implemented_observables: data_uncertainties: - uncertainties.yaml plotting: - dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology B" kinematics_override: identity plot_x: m_jj x_scale: log diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml index 9cba81df37..6f04416535 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml @@ -29,7 +29,7 @@ implemented_observables: data_uncertainties: - uncertainties.yaml plotting: - dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology C" kinematics_override: identity plot_x: m_jj x_scale: log diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml index be1e3c53c8..143c30b1f3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml @@ -29,7 +29,7 @@ implemented_observables: data_uncertainties: - uncertainties.yaml plotting: - dataset_label: "STAR 510 TeV (2013) DIJET $A_{LL}$" + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology D" kinematics_override: identity plot_x: m_jj x_scale: log From 106d475f170cef02b93aefc487cfc7cdeb078ed9 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 23 Apr 2024 22:21:50 +0200 Subject: [PATCH 17/98] implement 2015 dijet and jet and fix tests --- .../nnpdf_data/filter_utils/correlations.py | 2 +- .../star/jet_dijet_2013_510gev.py | 2 + .../star/jet_dijet_2015_200gev.py | 19 +- .../STAR_2009_1JET_200GEV/metadata.yaml | 4 +- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 1764 ++++++++--------- .../uncertainties.yaml | 1512 +++++++------- .../uncertainties.yaml | 1638 +++++++-------- .../uncertainties.yaml | 1512 +++++++------- .../uncertainties.yaml | 1512 +++++++------- .../STAR_2015_1JET_200GEV/data.yaml | 23 + .../STAR_2015_1JET_200GEV/kinematics.yaml | 265 +++ .../STAR_2015_1JET_200GEV/metadata.yaml | 50 + .../rawdata/Table11SupplementalMaterial.csv | 37 + .../rawdata/Table12SupplementalMaterial.csv | 37 + .../rawdata/Table13SupplementalMaterial.csv | 58 + .../rawdata/Table1SupplementalMaterial.csv | 75 + .../rawdata/Table1bottom.csv | 34 + .../rawdata/Table1top.csv | 34 + .../rawdata/Table2SupplementalMaterial.csv | 75 + .../rawdata/Table2bottom.csv | 36 + .../rawdata/Table2top.csv | 36 + .../rawdata/Table4SupplementalMaterial.csv | 130 ++ .../rawdata/Table5SupplementalMaterial.csv | 86 + .../rawdata/Table6SupplementalMaterial.csv | 86 + .../rawdata/Table7SupplementalMaterial.csv | 86 + .../rawdata/Table8SupplementalMaterial.csv | 86 + .../STAR_2015_1JET_200GEV/uncertainties.yaml | 990 +++++++++ .../STAR_2015_2JET_OS_200GEV/data.yaml | 8 + .../STAR_2015_2JET_OS_200GEV/kinematics.yaml | 57 + .../STAR_2015_2JET_OS_200GEV/metadata.yaml | 39 + .../uncertainties.yaml | 431 ++++ .../STAR_2015_2JET_SS_200GEV/data.yaml | 8 + .../STAR_2015_2JET_SS_200GEV/kinematics.yaml | 57 + .../STAR_2015_2JET_SS_200GEV/metadata.yaml | 39 + .../uncertainties.yaml | 431 ++++ validphys2/src/validphys/process_options.py | 3 +- 36 files changed, 7286 insertions(+), 3976 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table11SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table12SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table13SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1bottom.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1top.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2bottom.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2top.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table4SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table5SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table6SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table7SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table8SupplementalMaterial.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/correlations.py b/nnpdf_data/nnpdf_data/filter_utils/correlations.py index 6f01f09bc1..c9c1cdc07b 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/correlations.py +++ b/nnpdf_data/nnpdf_data/filter_utils/correlations.py @@ -11,7 +11,7 @@ def upper_triangular_to_symmetric(ut, dim): corr[i, i:] = ut[first:last] last += dim - i - 1 first += dim - i - return corr + corr.T - np.eye(dim) + return corr def compute_covmat(corrmat: np.ndarray, unc: np.ndarray, ndata: int) -> list: diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 92c8b15efb..77d947d13c 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -112,6 +112,8 @@ def read_correlations(ndata_dict): corr_rows.append(corr_row) tot_corr = pd.concat(corr_rows) + if not np.allclose(tot_corr, np.triu(tot_corr)): + raise ValueError("Correlation matrix not read correctly") return tot_corr + tot_corr.T - np.eye(np.sum((*ndata_dict.values(),))) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py index 2beb5911d1..ec479eb8fe 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -130,6 +130,8 @@ def read_correlations(ndata_dict): corr_rows.append(corr_row) tot_corr = pd.concat(corr_rows) + if not np.allclose(tot_corr, np.triu(tot_corr)): + raise ValueError("Correlation matrix not read correctly") return tot_corr + tot_corr.T - np.eye(np.sum((*ndata_dict.values(),))) @@ -168,7 +170,12 @@ def write_1jet_data(df, art_sys): "lumi": { "description": "luminosity uncertainty", "treatment": "ADD", - "type": "UNCORR", + "type": "STAR2015LUMI", + }, + "pol": { + "description": "polarization uncertainty", + "treatment": "MULT", + "type": "STAR2015POL", } } # loop on data points @@ -190,6 +197,7 @@ def write_1jet_data(df, art_sys): } ) e["lumi"] = float(df.loc[i, "lumi"]) + e["pol"] = float(df.loc[i, "pol"]) error.append(e) uncertainties_yaml = {"definitions": error_definition, "bins": error} @@ -231,8 +239,13 @@ def write_2jet_data(df, topology, art_sys): "lumi": { "description": "luminosity uncertainty", "treatment": "ADD", - "type": "UNCORR", + "type": "STAR2015LUMI", }, + "pol": { + "description": "polarization uncertainty", + "treatment": "MULT", + "type": "STAR2015POL", + } } # loop on data points for i, sys_i in enumerate(art_sys): @@ -242,6 +255,7 @@ def write_2jet_data(df, topology, art_sys): e[f"sys_{j}"] = val e["stat"] = float(df.loc[i, "stat"]) e["lumi"] = float(df.loc[i, "lumi"]) + e["pol"] = float(df.loc[i, "pol"]) error.append(e) if i == 0: @@ -288,7 +302,6 @@ def write_2jet_data(df, topology, art_sys): for a in (*TOPOPLOGY_LIST,)[2:]: correlated_unc.extend(new_dfs[a]["syst"].values) - import pdb; pdb.set_trace() # decompose uncertainties ndata_dict = {a: len(b) for a, b in new_dfs.items()} ndata_points = np.sum((*ndata_dict.values(),)) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml index 48ee1f0637..637a7143bf 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml @@ -34,13 +34,13 @@ implemented_observables: label: '$\sqrt{s}$', units: "$GeV$", } - eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + abs_eta: { description: "pseudorapidity", label: '$\eta$', units: "" } file: kinematics.yaml data_central: data.yaml data_uncertainties: - uncertainties.yaml - kinematic_coverage: [pT, sqrts, eta] + kinematic_coverage: [pT, sqrts, abs_eta] plotting: kinematics_override: identity dataset_label: "$A_{LL}$" diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml new file mode 100644 index 0000000000..a4781fd3fd --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml @@ -0,0 +1,265 @@ +bins: +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 6.2 + mid: 6.0 + min: 5.8 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 7.529999999999999 + mid: 7.31 + min: 7.09 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 9.72 + mid: 9.47 + min: 9.22 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 11.64 + mid: 11.33 + min: 11.02 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 13.7 + mid: 13.36 + min: 13.02 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 16.09 + mid: 15.74 + min: 15.39 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 18.81 + mid: 18.43 + min: 18.05 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 21.93 + mid: 21.49 + min: 21.049999999999997 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 25.610000000000003 + mid: 25.1 + min: 24.59 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 29.73 + mid: 29.17 + min: 28.610000000000003 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 34.43 + mid: 33.81 + min: 33.190000000000005 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 6.340000000000001 + mid: 6.15 + min: 5.96 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 7.54 + mid: 7.34 + min: 7.14 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 9.78 + mid: 9.5 + min: 9.22 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 11.62 + mid: 11.34 + min: 11.06 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 13.56 + mid: 13.25 + min: 12.94 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 15.83 + mid: 15.47 + min: 15.110000000000001 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 18.44 + mid: 18.07 + min: 17.7 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 21.57 + mid: 21.16 + min: 20.75 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 25.16 + mid: 24.68 + min: 24.2 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 29.09 + mid: 28.56 + min: 28.029999999999998 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 33.5 + mid: 32.9 + min: 32.3 + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml new file mode 100644 index 0000000000..ec3fc04699 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml @@ -0,0 +1,50 @@ +setname: "STAR_2015_1JET_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1850855" +hepdata: + url: "https://www.hepdata.net/record/ins1850855" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "$A_{LL}$ as function of $p_T$", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: JET_POL + ndata: 22 + tables: [1] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + abs_eta: {description: "absolute pseudorapidity", label: '$|\eta|$', units: "" } + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, abs_eta] + plotting: + dataset_label: "STAR 200 GeV (2015) 1-JET $A_{LL}$" + kinematics_override: identity + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2015_1JET_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table11SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table11SupplementalMaterial.csv new file mode 100644 index 0000000000..22e588f648 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table11SupplementalMaterial.csv @@ -0,0 +1,37 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t19 +#: name: Table 11 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties for dijet measurements with the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_11_supplemental_material.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$) [GeV/$c^2$],Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$) [GeV/$c^2$],Correlation +20.29,20.29,1.0 +20.29,23.5,0.044 +20.29,28.28,0.033 +20.29,34.15,0.02 +20.29,40.96,0.013 +20.29,50.75,0.012 +20.29,69.11,0.006 +23.5,23.5,1.0 +23.5,28.28,0.038 +23.5,34.15,0.023 +23.5,40.96,0.016 +23.5,50.75,0.015 +23.5,69.11,0.008 +28.28,28.28,1.0 +28.28,34.15,0.019 +28.28,40.96,0.013 +28.28,50.75,0.014 +28.28,69.11,0.008 +34.15,34.15,1.0 +34.15,40.96,0.009 +34.15,50.75,0.009 +34.15,69.11,0.005 +40.96,40.96,1.0 +40.96,50.75,0.007 +40.96,69.11,0.004 +50.75,50.75,1.0 +50.75,69.11,0.006 +69.11,69.11,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table12SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table12SupplementalMaterial.csv new file mode 100644 index 0000000000..430b2a39c6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table12SupplementalMaterial.csv @@ -0,0 +1,37 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t20 +#: name: Table 12 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties for dijet measurements with the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_12_supplemental_material.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$) [GeV/$c^2$],Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$) [GeV/$c^2$],Correlation +20.48,20.48,1.0 +20.48,23.65,0.011 +20.48,28.5,0.012 +20.48,34.38,0.008 +20.48,41.38,0.006 +20.48,51.25,0.008 +20.48,69.96,0.004 +23.65,23.65,1.0 +23.65,28.5,0.016 +23.65,34.38,0.01 +23.65,41.38,0.008 +23.65,51.25,0.01 +23.65,69.96,0.005 +28.5,28.5,1.0 +28.5,34.38,0.011 +28.5,41.38,0.009 +28.5,51.25,0.011 +28.5,69.96,0.006 +34.38,34.38,1.0 +34.38,41.38,0.006 +34.38,51.25,0.008 +34.38,69.96,0.004 +41.38,41.38,1.0 +41.38,51.25,0.006 +41.38,69.96,0.003 +51.25,51.25,1.0 +51.25,69.96,0.004 +69.96,69.96,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table13SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table13SupplementalMaterial.csv new file mode 100644 index 0000000000..2bf53ee3e8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table13SupplementalMaterial.csv @@ -0,0 +1,58 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t21 +#: name: Table 13 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties coupling dijet measurements with the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology and the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_13_supplemental_material.yaml +#: keyword reactions: P P --> JET JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$) [GeV/$c^2$],Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$) [GeV/$c^2$],Correlation +20.48,20.29,0.008 +20.48,23.5,0.01 +20.48,28.28,0.01 +20.48,34.15,0.007 +20.48,40.96,0.006 +20.48,50.75,0.008 +20.48,69.11,0.005 +23.65,20.29,0.01 +23.65,23.5,0.013 +23.65,28.28,0.013 +23.65,34.15,0.009 +23.65,40.96,0.008 +23.65,50.75,0.01 +23.65,69.11,0.007 +28.5,20.29,0.011 +28.5,23.5,0.014 +28.5,28.28,0.015 +28.5,34.15,0.01 +28.5,40.96,0.008 +28.5,50.75,0.011 +28.5,69.11,0.007 +34.38,20.29,0.007 +34.38,23.5,0.009 +34.38,28.28,0.01 +34.38,34.15,0.007 +34.38,40.96,0.006 +34.38,50.75,0.007 +34.38,69.11,0.005 +41.38,20.29,0.006 +41.38,23.5,0.008 +41.38,28.28,0.008 +41.38,34.15,0.006 +41.38,40.96,0.005 +41.38,50.75,0.006 +41.38,69.11,0.004 +51.25,20.29,0.008 +51.25,23.5,0.01 +51.25,28.28,0.011 +51.25,34.15,0.007 +51.25,40.96,0.006 +51.25,50.75,0.008 +51.25,69.11,0.006 +69.96,20.29,0.004 +69.96,23.5,0.005 +69.96,28.28,0.005 +69.96,34.15,0.004 +69.96,40.96,0.003 +69.96,50.75,0.004 +69.96,69.11,0.003 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1SupplementalMaterial.csv new file mode 100644 index 0000000000..9c7741b8f6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1SupplementalMaterial.csv @@ -0,0 +1,75 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t9 +#: name: Table 1 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties for inclusive jet measurements with jets in the $0.5<|\eta|<1$ region. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_1_supplemental_material.yaml +#: keyword reactions: P P --> JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Inclusive jet transverse momentum $p_T$ at the parton level ($0.5<|\eta|<1$) [GeV/$c$],Inclusive jet transverse momentum $p_T$ at the parton level ($0.5<|\eta|<1$) [GeV/$c$],Correlation +6.15,6.15,1.0 +6.15,7.34,0.043 +6.15,9.5,0.062 +6.15,11.34,0.051 +6.15,13.25,0.037 +6.15,15.47,0.026 +6.15,18.07,0.019 +6.15,21.16,0.012 +6.15,24.68,0.011 +6.15,28.56,0.007 +6.15,32.9,0.003 +7.34,7.34,1.0 +7.34,9.5,0.051 +7.34,11.34,0.045 +7.34,13.25,0.033 +7.34,15.47,0.023 +7.34,18.07,0.018 +7.34,21.16,0.012 +7.34,24.68,0.011 +7.34,28.56,0.007 +7.34,32.9,0.003 +9.5,9.5,1.0 +9.5,11.34,0.069 +9.5,13.25,0.051 +9.5,15.47,0.037 +9.5,18.07,0.029 +9.5,21.16,0.019 +9.5,24.68,0.017 +9.5,28.56,0.011 +9.5,32.9,0.005 +11.34,11.34,1.0 +11.34,13.25,0.051 +11.34,15.47,0.039 +11.34,18.07,0.032 +11.34,21.16,0.02 +11.34,24.68,0.019 +11.34,28.56,0.013 +11.34,32.9,0.006 +13.25,13.25,1.0 +13.25,15.47,0.034 +13.25,18.07,0.028 +13.25,21.16,0.019 +13.25,24.68,0.017 +13.25,28.56,0.01 +13.25,32.9,0.005 +15.47,15.47,1.0 +15.47,18.07,0.027 +15.47,21.16,0.019 +15.47,24.68,0.016 +15.47,28.56,0.01 +15.47,32.9,0.004 +18.07,18.07,1.0 +18.07,21.16,0.023 +18.07,24.68,0.019 +18.07,28.56,0.011 +18.07,32.9,0.005 +21.16,21.16,1.0 +21.16,24.68,0.022 +21.16,28.56,0.014 +21.16,32.9,0.006 +24.68,24.68,1.0 +24.68,28.56,0.02 +24.68,32.9,0.011 +28.56,28.56,1.0 +28.56,32.9,0.016 +32.9,32.9,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1bottom.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1bottom.csv new file mode 100644 index 0000000000..48f86b8a87 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1bottom.csv @@ -0,0 +1,34 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t5 +#: name: Table 1 bottom +#: description: Parton inclusive-jet $p_T$ and $A_{LL}$ values with associated uncertainties for jet-$\eta$ region $|\eta|<0.5$. +#: data_file: table_1_bottom.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET X +#: SQRT(S) [GeV],200 +bin,Inclusive jet transverse momentum $p_T$ at the parton level [GeV/$c$],Syst +,Syst - +1.0,6.0,0.2,-0.2 +2.0,7.31,0.22,-0.22 +3.0,9.47,0.25,-0.25 +4.0,11.33,0.31,-0.31 +5.0,13.36,0.34,-0.34 +6.0,15.74,0.35,-0.35 +7.0,18.43,0.38,-0.38 +8.0,21.49,0.44,-0.44 +9.0,25.1,0.51,-0.51 +10.0,29.17,0.56,-0.56 +11.0,33.81,0.62,-0.62 + +#: SQRT(S) [GeV],200 +bin,Double spin asymmetry $A_{LL}$,Stat +,Stat -,Syst +,Syst -,Lumi +,Lumi -,Pol +,Pol - +1.0,0.0002,0.0014,-0.0014,0.0015,-0.0015,0.0007,-0.0007,6.1%,-6.1% +2.0,0.0006,0.0017,-0.0017,0.0012,-0.0012,0.0007,-0.0007,6.1%,-6.1% +3.0,0.0034,0.001,-0.001,0.0011,-0.0011,0.0007,-0.0007,6.1%,-6.1% +4.0,0.0041,0.0011,-0.0011,0.0009,-0.0009,0.0007,-0.0007,6.1%,-6.1% +5.0,0.007,0.0014,-0.0014,0.0008,-0.0008,0.0007,-0.0007,6.1%,-6.1% +6.0,0.0045,0.0019,-0.0019,0.0007,-0.0007,0.0007,-0.0007,6.1%,-6.1% +7.0,0.0182,0.0028,-0.0028,0.0008,-0.0008,0.0007,-0.0007,6.1%,-6.1% +8.0,0.022,0.0043,-0.0043,0.0009,-0.0009,0.0007,-0.0007,6.1%,-6.1% +9.0,0.0196,0.0072,-0.0072,0.0011,-0.0011,0.0007,-0.0007,6.1%,-6.1% +10.0,0.0348,0.0127,-0.0127,0.0014,-0.0014,0.0007,-0.0007,6.1%,-6.1% +11.0,0.0515,0.0239,-0.0239,0.0015,-0.0015,0.0007,-0.0007,6.1%,-6.1% + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1top.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1top.csv new file mode 100644 index 0000000000..96ed05bb37 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table1top.csv @@ -0,0 +1,34 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t4 +#: name: Table 1 top +#: description: Parton inclusive-jet $p_T$ and $A_{LL}$ values with associated uncertainties for jet-$\eta$ region $0.5<|\eta|<1$. +#: data_file: table_1_top.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET X +#: SQRT(S) [GeV],200 +bin,Inclusive jet transverse momentum $p_T$ at the parton level [GeV/$c$],Syst +,Syst - +1.0,6.15,0.19,-0.19 +2.0,7.34,0.2,-0.2 +3.0,9.5,0.28,-0.28 +4.0,11.34,0.28,-0.28 +5.0,13.25,0.31,-0.31 +6.0,15.47,0.36,-0.36 +7.0,18.07,0.37,-0.37 +8.0,21.16,0.41,-0.41 +9.0,24.68,0.48,-0.48 +10.0,28.56,0.53,-0.53 +11.0,32.9,0.6,-0.6 + +#: SQRT(S) [GeV],200 +bin,Double spin asymmetry $A_{LL}$,Stat +,Stat -,Syst +,Syst -,Lumi +,Lumi -,Pol +,Pol - +1.0,-0.00021,0.0017,-0.0017,0.0004,-0.0004,0.0007,-0.0007,6.1%,-6.1% +2.0,0.00091,0.0019,-0.0019,0.0004,-0.0004,0.0007,-0.0007,6.1%,-6.1% +3.0,0.00084,0.0012,-0.0012,0.0004,-0.0004,0.0007,-0.0007,6.1%,-6.1% +4.0,0.00333,0.0014,-0.0014,0.0004,-0.0004,0.0007,-0.0007,6.1%,-6.1% +5.0,0.00238,0.0018,-0.0018,0.0004,-0.0004,0.0007,-0.0007,6.1%,-6.1% +6.0,0.00214,0.0025,-0.0025,0.0004,-0.0004,0.0007,-0.0007,6.1%,-6.1% +7.0,0.01141,0.0037,-0.0037,0.0005,-0.0005,0.0007,-0.0007,6.1%,-6.1% +8.0,0.01228,0.0058,-0.0058,0.0006,-0.0006,0.0007,-0.0007,6.1%,-6.1% +9.0,0.02057,0.0099,-0.0099,0.001,-0.001,0.0007,-0.0007,6.1%,-6.1% +10.0,0.05314,0.018,-0.018,0.0013,-0.0013,0.0007,-0.0007,6.1%,-6.1% +11.0,0.02316,0.0357,-0.0357,0.0016,-0.0016,0.0007,-0.0007,6.1%,-6.1% + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2SupplementalMaterial.csv new file mode 100644 index 0000000000..dd0f806245 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2SupplementalMaterial.csv @@ -0,0 +1,75 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t10 +#: name: Table 2 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties for inclusive jet measurements with jets in the $|\eta|<0.5$ region. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_2_supplemental_material.yaml +#: keyword reactions: P P --> JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Inclusive jet transverse momentum $p_T$ at the parton level ($|\eta|<0.5$) [GeV/$c$],Inclusive jet transverse momentum $p_T$ at the parton level ($|\eta|<0.5$) [GeV/$c$],Correlation +6.0,6.0,1.0 +6.0,7.31,0.448 +6.0,9.47,0.549 +6.0,11.33,0.463 +6.0,13.36,0.353 +6.0,15.74,0.244 +6.0,18.43,0.163 +6.0,21.49,0.102 +6.0,25.1,0.064 +6.0,29.17,0.035 +6.0,33.81,0.018 +7.31,7.31,1.0 +7.31,9.47,0.45 +7.31,11.33,0.379 +7.31,13.36,0.287 +7.31,15.74,0.198 +7.31,18.43,0.13 +7.31,21.49,0.08 +7.31,25.1,0.049 +7.31,29.17,0.027 +7.31,33.81,0.014 +9.47,9.47,1.0 +9.47,11.33,0.47 +9.47,13.36,0.361 +9.47,15.74,0.251 +9.47,18.43,0.171 +9.47,21.49,0.109 +9.47,25.1,0.069 +9.47,29.17,0.038 +9.47,33.81,0.02 +11.33,11.33,1.0 +11.33,13.36,0.309 +11.33,15.74,0.217 +11.33,18.43,0.149 +11.33,21.49,0.095 +11.33,25.1,0.06 +11.33,29.17,0.033 +11.33,33.81,0.017 +13.36,13.36,1.0 +13.36,15.74,0.177 +13.36,18.43,0.129 +13.36,21.49,0.085 +13.36,25.1,0.056 +13.36,29.17,0.031 +13.36,33.81,0.016 +15.74,15.74,1.0 +15.74,18.43,0.104 +15.74,21.49,0.072 +15.74,25.1,0.049 +15.74,29.17,0.027 +15.74,33.81,0.014 +18.43,18.43,1.0 +18.43,21.49,0.075 +18.43,25.1,0.056 +18.43,29.17,0.032 +18.43,33.81,0.017 +21.49,21.49,1.0 +21.49,25.1,0.062 +21.49,29.17,0.04 +21.49,33.81,0.021 +25.1,25.1,1.0 +25.1,29.17,0.056 +25.1,33.81,0.033 +29.17,29.17,1.0 +29.17,33.81,0.053 +33.81,33.81,1.0 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2bottom.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2bottom.csv new file mode 100644 index 0000000000..353441b4fe --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2bottom.csv @@ -0,0 +1,36 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t7 +#: name: Table 2 bottom +#: description: Parton dijet invariant mass $M_{inv}$ and $A_{LL}$ values with associated uncertainties for the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. +#: data_file: table_2_bottom.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET JET X +#: SQRT(S) [GeV],200 +bin,Dijet invariant mass $M_{inv}$ at the parton level [GeV/$c$],Syst +,Syst - +1.0,20.48,0.62,-0.62 +2.0,23.65,0.59,-0.59 +3.0,28.5,0.69,-0.69 +4.0,34.38,0.79,-0.79 +5.0,41.38,0.92,-0.92 +6.0,51.25,1.08,-1.08 +7.0,69.96,1.31,-1.31 + +#: SQRT(S) [GeV],200 +bin,Dijet $M_{inv}/\sqrt{s}$ at the parton level,Syst +,Syst - +1.0,0.1024,0.0031,-0.0031 +2.0,0.1183,0.003,-0.003 +3.0,0.1425,0.0035,-0.0035 +4.0,0.1719,0.004,-0.004 +5.0,0.2069,0.0046,-0.0046 +6.0,0.2563,0.0054,-0.0054 +7.0,0.3498,0.0066,-0.0066 + +#: SQRT(S) [GeV],200 +bin,Double spin asymmetry $A_{LL}$,Stat +,Stat -,Syst +,Syst -,Lumi +,Lumi -,Pol +,Pol - +1.0,0.0067,0.004,-0.004,0.0005,-0.0005,0.0007,-0.0007,6.1%,-6.1% +2.0,0.0024,0.0027,-0.0027,0.0005,-0.0005,0.0007,-0.0007,6.1%,-6.1% +3.0,0.0052,0.0032,-0.0032,0.0006,-0.0006,0.0007,-0.0007,6.1%,-6.1% +4.0,0.011,0.0044,-0.0044,0.0007,-0.0007,0.0007,-0.0007,6.1%,-6.1% +5.0,0.0201,0.0068,-0.0068,0.0009,-0.0009,0.0007,-0.0007,6.1%,-6.1% +6.0,0.024,0.0097,-0.0097,0.0012,-0.0012,0.0007,-0.0007,6.1%,-6.1% +7.0,0.0934,0.0304,-0.0304,0.002,-0.002,0.0007,-0.0007,6.1%,-6.1% + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2top.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2top.csv new file mode 100644 index 0000000000..cb61d55282 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table2top.csv @@ -0,0 +1,36 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t6 +#: name: Table 2 top +#: description: Parton dijet invariant mass $M_{inv}$ and $A_{LL}$ values with associated uncertainties for the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. +#: data_file: table_2_top.yaml +#: keyword observables: ASYM +#: keyword reactions: P P --> JET JET X +#: SQRT(S) [GeV],200 +bin,Dijet invariant mass $M_{inv}$ at the parton level [GeV/$c$],Syst +,Syst - +1.0,20.29,0.53,-0.53 +2.0,23.5,0.61,-0.61 +3.0,28.28,0.66,-0.66 +4.0,34.15,0.78,-0.78 +5.0,40.96,0.89,-0.89 +6.0,50.75,1.03,-1.03 +7.0,69.11,1.31,-1.31 + +#: SQRT(S) [GeV],200 +bin,Dijet $M_{inv}/\sqrt{s}$ at the parton level,Syst +,Syst - +1.0,0.1015,0.0027,-0.0027 +2.0,0.1175,0.0031,-0.0031 +3.0,0.1414,0.0033,-0.0033 +4.0,0.1708,0.0039,-0.0039 +5.0,0.2048,0.0045,-0.0045 +6.0,0.2538,0.0052,-0.0052 +7.0,0.3456,0.0066,-0.0066 + +#: SQRT(S) [GeV],200 +bin,Double spin asymmetry $A_{LL}$,Stat +,Stat -,Syst +,Syst -,Lumi +,Lumi -,Pol +,Pol - +1.0,0.0071,0.0036,-0.0036,0.0009,-0.0009,0.0007,-0.0007,6.1%,-6.1% +2.0,0.0049,0.0028,-0.0028,0.0007,-0.0007,0.0007,-0.0007,6.1%,-6.1% +3.0,0.0017,0.0035,-0.0035,0.0008,-0.0008,0.0007,-0.0007,6.1%,-6.1% +4.0,0.0137,0.0051,-0.0051,0.0009,-0.0009,0.0007,-0.0007,6.1%,-6.1% +5.0,0.0316,0.0081,-0.0081,0.0011,-0.0011,0.0007,-0.0007,6.1%,-6.1% +6.0,0.0232,0.0121,-0.0121,0.0015,-0.0015,0.0007,-0.0007,6.1%,-6.1% +7.0,0.0228,0.0418,-0.0418,0.0033,-0.0033,0.0007,-0.0007,6.1%,-6.1% + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table4SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table4SupplementalMaterial.csv new file mode 100644 index 0000000000..4851f501b0 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table4SupplementalMaterial.csv @@ -0,0 +1,130 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t12 +#: name: Table 4 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<0.5$ region and jets in the $0.5<|\eta|<1$ region. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_4_supplemental_material.yaml +#: keyword reactions: P P --> JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Inclusive jet transverse momentum $p_T$ at the parton level ($|\eta|<0.5$) [GeV/$c$],Inclusive jet transverse momentum $p_T$ at the parton level ($0.5<|\eta|<1$) [GeV/$c$],Correlation +6.0,6.15,0.019 +6.0,7.34,0.021 +6.0,9.5,0.029 +6.0,11.34,0.033 +6.0,13.25,0.026 +6.0,15.47,0.02 +6.0,18.07,0.018 +6.0,21.16,0.012 +6.0,24.68,0.013 +6.0,28.56,0.009 +6.0,32.9,0.005 +7.31,6.15,0.013 +7.31,7.34,0.015 +7.31,9.5,0.019 +7.31,11.34,0.021 +7.31,13.25,0.017 +7.31,15.47,0.013 +7.31,18.07,0.012 +7.31,21.16,0.008 +7.31,24.68,0.008 +7.31,28.56,0.006 +7.31,32.9,0.003 +9.47,6.15,0.021 +9.47,7.34,0.024 +9.47,9.5,0.037 +9.47,11.34,0.042 +9.47,13.25,0.034 +9.47,15.47,0.027 +9.47,18.07,0.024 +9.47,21.16,0.016 +9.47,24.68,0.017 +9.47,28.56,0.011 +9.47,32.9,0.005 +11.33,6.15,0.019 +11.33,7.34,0.021 +11.33,9.5,0.034 +11.33,11.34,0.039 +11.33,13.25,0.033 +11.33,15.47,0.027 +11.33,18.07,0.024 +11.33,21.16,0.016 +11.33,24.68,0.016 +11.33,28.56,0.01 +11.33,32.9,0.005 +13.36,6.15,0.02 +13.36,7.34,0.022 +13.36,9.5,0.037 +13.36,11.34,0.044 +13.36,13.25,0.038 +13.36,15.47,0.034 +13.36,18.07,0.03 +13.36,21.16,0.021 +13.36,24.68,0.019 +13.36,28.56,0.012 +13.36,32.9,0.006 +15.74,6.15,0.016 +15.74,7.34,0.018 +15.74,9.5,0.03 +15.74,11.34,0.037 +15.74,13.25,0.035 +15.74,15.47,0.033 +15.74,18.07,0.033 +15.74,21.16,0.025 +15.74,24.68,0.021 +15.74,28.56,0.013 +15.74,32.9,0.006 +18.43,6.15,0.019 +18.43,7.34,0.021 +18.43,9.5,0.034 +18.43,11.34,0.041 +18.43,13.25,0.038 +18.43,15.47,0.038 +18.43,18.07,0.041 +18.43,21.16,0.035 +18.43,24.68,0.03 +18.43,28.56,0.019 +18.43,32.9,0.009 +21.49,6.15,0.015 +21.49,7.34,0.017 +21.49,9.5,0.027 +21.49,11.34,0.033 +21.49,13.25,0.03 +21.49,15.47,0.031 +21.49,18.07,0.037 +21.49,21.16,0.038 +21.49,24.68,0.038 +21.49,28.56,0.026 +21.49,32.9,0.013 +25.1,6.15,0.014 +25.1,7.34,0.015 +25.1,9.5,0.024 +25.1,11.34,0.028 +25.1,13.25,0.024 +25.1,15.47,0.024 +25.1,18.07,0.029 +25.1,21.16,0.035 +25.1,24.68,0.042 +25.1,28.56,0.037 +25.1,32.9,0.023 +29.17,6.15,0.009 +29.17,7.34,0.009 +29.17,9.5,0.015 +29.17,11.34,0.017 +29.17,13.25,0.014 +29.17,15.47,0.014 +29.17,18.07,0.017 +29.17,21.16,0.022 +29.17,24.68,0.032 +29.17,28.56,0.04 +29.17,32.9,0.03 +33.81,6.15,0.005 +33.81,7.34,0.005 +33.81,9.5,0.008 +33.81,11.34,0.009 +33.81,13.25,0.008 +33.81,15.47,0.007 +33.81,18.07,0.008 +33.81,21.16,0.01 +33.81,24.68,0.019 +33.81,28.56,0.029 +33.81,32.9,0.035 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table5SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table5SupplementalMaterial.csv new file mode 100644 index 0000000000..af3ef60677 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table5SupplementalMaterial.csv @@ -0,0 +1,86 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t13 +#: name: Table 5 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $0.5<|\eta|<1$ region with dijet measurements with the the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_5_supplemental_material.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Inclusive jet transverse momentum $p_T$ at the parton level ($0.5<|\eta|<1$) [GeV/$c$],Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$) [GeV/$c^2$],Correlation +6.15,20.29,0.013 +6.15,23.5,0.013 +6.15,28.28,0.012 +6.15,34.15,0.008 +6.15,40.96,0.007 +6.15,50.75,0.009 +6.15,69.11,0.006 +7.34,20.29,0.021 +7.34,23.5,0.018 +7.34,28.28,0.014 +7.34,34.15,0.009 +7.34,40.96,0.008 +7.34,50.75,0.01 +7.34,69.11,0.007 +9.5,20.29,0.06 +9.5,23.5,0.056 +9.5,28.28,0.032 +9.5,34.15,0.015 +9.5,40.96,0.012 +9.5,50.75,0.016 +9.5,69.11,0.01 +11.34,20.29,0.063 +11.34,23.5,0.081 +11.34,28.28,0.06 +11.34,34.15,0.024 +11.34,40.96,0.014 +11.34,50.75,0.018 +11.34,69.11,0.012 +13.25,20.29,0.03 +13.25,23.5,0.074 +13.25,28.28,0.083 +13.25,34.15,0.045 +13.25,40.96,0.016 +13.25,50.75,0.014 +13.25,69.11,0.009 +15.47,20.29,0.011 +15.47,23.5,0.043 +15.47,28.28,0.076 +15.47,34.15,0.08 +15.47,40.96,0.036 +15.47,50.75,0.014 +15.47,69.11,0.007 +18.07,20.29,0.01 +18.07,23.5,0.02 +18.07,28.28,0.046 +18.07,34.15,0.078 +18.07,40.96,0.081 +18.07,50.75,0.03 +18.07,69.11,0.007 +21.16,20.29,0.006 +21.16,23.5,0.009 +21.16,28.28,0.02 +21.16,34.15,0.041 +21.16,40.96,0.085 +21.16,50.75,0.08 +21.16,69.11,0.005 +24.68,20.29,0.007 +24.68,23.5,0.009 +24.68,28.28,0.012 +24.68,34.15,0.017 +24.68,40.96,0.042 +24.68,50.75,0.114 +24.68,69.11,0.017 +28.56,20.29,0.005 +28.56,23.5,0.007 +28.56,28.28,0.007 +28.56,34.15,0.007 +28.56,40.96,0.015 +28.56,50.75,0.081 +28.56,69.11,0.068 +32.9,20.29,0.002 +32.9,23.5,0.003 +32.9,28.28,0.003 +32.9,34.15,0.003 +32.9,40.96,0.004 +32.9,50.75,0.027 +32.9,69.11,0.108 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table6SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table6SupplementalMaterial.csv new file mode 100644 index 0000000000..cc47c69a26 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table6SupplementalMaterial.csv @@ -0,0 +1,86 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t14 +#: name: Table 6 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $0.5<|\eta|<1$ region with dijet measurements with the the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_6_supplemental_material.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Inclusive jet transverse momentum $p_T$ at the parton level ($0.5<|\eta|<1$) [GeV/$c$],Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$) [GeV/$c^2$],Correlation +6.15,20.48,0.016 +6.15,23.65,0.015 +6.15,28.5,0.013 +6.15,34.38,0.008 +6.15,41.38,0.007 +6.15,51.25,0.009 +6.15,69.96,0.005 +7.34,20.48,0.02 +7.34,23.65,0.022 +7.34,28.5,0.016 +7.34,34.38,0.009 +7.34,41.38,0.008 +7.34,51.25,0.01 +7.34,69.96,0.005 +9.5,20.48,0.056 +9.5,23.65,0.064 +9.5,28.5,0.042 +9.5,34.38,0.019 +9.5,41.38,0.012 +9.5,51.25,0.016 +9.5,69.96,0.008 +11.34,20.48,0.035 +11.34,23.65,0.076 +11.34,28.5,0.071 +11.34,34.38,0.035 +11.34,41.38,0.016 +11.34,51.25,0.018 +11.34,69.96,0.009 +13.25,20.48,0.015 +13.25,23.65,0.052 +13.25,28.5,0.079 +13.25,34.38,0.063 +13.25,41.38,0.027 +13.25,51.25,0.015 +13.25,69.96,0.007 +15.47,20.48,0.011 +15.47,23.65,0.024 +15.47,28.5,0.06 +15.47,34.38,0.08 +15.47,41.38,0.061 +15.47,51.25,0.023 +15.47,69.96,0.005 +18.07,20.48,0.01 +18.07,23.65,0.013 +18.07,28.5,0.033 +18.07,34.38,0.059 +18.07,41.38,0.088 +18.07,51.25,0.06 +18.07,69.96,0.006 +21.16,20.48,0.006 +21.16,23.65,0.008 +21.16,28.5,0.014 +21.16,34.38,0.027 +21.16,41.38,0.063 +21.16,51.25,0.112 +21.16,69.96,0.011 +24.68,20.48,0.007 +24.68,23.65,0.009 +24.68,28.5,0.01 +24.68,34.38,0.013 +24.68,41.38,0.026 +24.68,51.25,0.114 +24.68,69.96,0.056 +28.56,20.48,0.005 +28.56,23.65,0.006 +28.56,28.5,0.007 +28.56,34.38,0.006 +28.56,41.38,0.009 +28.56,51.25,0.057 +28.56,69.96,0.13 +32.9,20.48,0.002 +32.9,23.65,0.003 +32.9,28.5,0.003 +32.9,34.38,0.002 +32.9,41.38,0.003 +32.9,51.25,0.018 +32.9,69.96,0.122 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table7SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table7SupplementalMaterial.csv new file mode 100644 index 0000000000..e7aa7cc143 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table7SupplementalMaterial.csv @@ -0,0 +1,86 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t15 +#: name: Table 7 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<0.5$ region with dijet measurements with the the $\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_7_supplemental_material.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Inclusive jet transverse momentum $p_T$ at the parton level ($|\eta|<0.5$) [GeV/$c$],Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) = \textrm{sign}(\eta_2)$) [GeV/$c^2$],Correlation +6.0,20.29,0.019 +6.0,23.5,0.02 +6.0,28.28,0.02 +6.0,34.15,0.013 +6.0,40.96,0.011 +6.0,50.75,0.015 +6.0,69.11,0.01 +7.31,20.29,0.024 +7.31,23.5,0.019 +7.31,28.28,0.013 +7.31,34.15,0.008 +7.31,40.96,0.007 +7.31,50.75,0.009 +7.31,69.11,0.006 +9.47,20.29,0.066 +9.47,23.5,0.062 +9.47,28.28,0.036 +9.47,34.15,0.017 +9.47,40.96,0.014 +9.47,50.75,0.018 +9.47,69.11,0.012 +11.33,20.29,0.077 +11.33,23.5,0.098 +11.33,28.28,0.07 +11.33,34.15,0.025 +11.33,40.96,0.013 +11.33,50.75,0.015 +11.33,69.11,0.01 +13.36,20.29,0.042 +13.36,23.5,0.106 +13.36,28.28,0.122 +13.36,34.15,0.068 +13.36,40.96,0.021 +13.36,50.75,0.017 +13.36,69.11,0.011 +15.74,20.29,0.014 +15.74,23.5,0.066 +15.74,28.28,0.12 +15.74,34.15,0.135 +15.74,40.96,0.061 +15.74,50.75,0.019 +15.74,69.11,0.009 +18.43,20.29,0.016 +18.43,23.5,0.033 +18.43,28.28,0.078 +18.43,34.15,0.138 +18.43,40.96,0.149 +18.43,50.75,0.055 +18.43,69.11,0.011 +21.49,20.29,0.013 +21.49,23.5,0.018 +21.49,28.28,0.038 +21.49,34.15,0.075 +21.49,40.96,0.16 +21.49,50.75,0.161 +21.49,69.11,0.011 +25.1,20.29,0.012 +25.1,23.5,0.015 +25.1,28.28,0.02 +25.1,34.15,0.03 +25.1,40.96,0.078 +25.1,50.75,0.236 +25.1,69.11,0.038 +29.17,20.29,0.007 +29.17,23.5,0.009 +29.17,28.28,0.01 +29.17,34.15,0.011 +29.17,40.96,0.024 +29.17,50.75,0.164 +29.17,69.11,0.168 +33.81,20.29,0.004 +33.81,23.5,0.005 +33.81,28.28,0.006 +33.81,34.15,0.005 +33.81,40.96,0.007 +33.81,50.75,0.057 +33.81,69.11,0.259 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table8SupplementalMaterial.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table8SupplementalMaterial.csv new file mode 100644 index 0000000000..73fb408e65 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/rawdata/Table8SupplementalMaterial.csv @@ -0,0 +1,86 @@ +#: table_doi: 10.17182/hepdata.104836.v1/t16 +#: name: Table 8 Supplemental Material +#: description: The correlation matrix for the point-to-point uncertainties coupling inclusive jet measurements with jets in the $|\eta|<0.5$ region with dijet measurements with the the $\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$ topology. The $A_{LL}$ uncertainty contribution of $0.0007$ from uncertainty in the relative luminosity measurement and $6.1\%$ from the beam polarization uncertainty, which are common to all the data points, are separated from the listed values. +#: data_file: table_8_supplemental_material.yaml +#: keyword reactions: P P --> JET X | P P --> JET JET X +#: keyword observables: CORR +#: SQRT(S) [GeV],200 +Inclusive jet transverse momentum $p_T$ at the parton level ($|\eta|<0.5$) [GeV/$c$],Dijet invariant mass $M_{inv}$ at the parton level ($\textrm{sign}(\eta_1) \neq \textrm{sign}(\eta_2)$) [GeV/$c^2$],Correlation +6.0,20.48,0.022 +6.0,23.65,0.021 +6.0,28.5,0.02 +6.0,34.38,0.013 +6.0,41.38,0.011 +6.0,51.25,0.015 +6.0,69.96,0.007 +7.31,20.48,0.027 +7.31,23.65,0.022 +7.31,28.5,0.014 +7.31,34.38,0.008 +7.31,41.38,0.007 +7.31,51.25,0.009 +7.31,69.96,0.004 +9.47,20.48,0.075 +9.47,23.65,0.07 +9.47,28.5,0.042 +9.47,34.38,0.019 +9.47,41.38,0.013 +9.47,51.25,0.018 +9.47,69.96,0.009 +11.33,20.48,0.07 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+33.81,51.25,0.046 +33.81,69.96,0.248 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..1f69454720 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -0,0 +1,990 @@ +definitions: + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2015LUMI + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2015POL + sys_0: + description: 0 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc0 + sys_1: + description: 1 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc1 + sys_2: + description: 2 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc2 + sys_3: + description: 3 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc3 + sys_4: + description: 4 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc4 + sys_5: + description: 5 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc5 + sys_6: + description: 6 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc6 + sys_7: + description: 7 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc7 + sys_8: + description: 8 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc8 + sys_9: + description: 9 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc9 + sys_10: + description: 10 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc10 + sys_11: + description: 11 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc11 + sys_12: + description: 12 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc12 + sys_13: + description: 13 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc13 + sys_14: + description: 14 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc14 + sys_15: + description: 15 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc15 + sys_16: + description: 16 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc16 + sys_17: + description: 17 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc17 + sys_18: + description: 18 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc18 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a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/data.yaml new file mode 100644 index 0000000000..7fcb4963f4 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/data.yaml @@ -0,0 +1,8 @@ +data_central: +- 0.0067 +- 0.0024 +- 0.0052 +- 0.011 +- 0.0201 +- 0.024 +- 0.0934 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/kinematics.yaml new file mode 100644 index 0000000000..de1e3b24f5 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/kinematics.yaml @@ -0,0 +1,57 @@ +bins: +- m_jj: + max: 21.1 + mid: 20.48 + min: 19.86 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 24.24 + mid: 23.65 + min: 23.06 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 29.19 + mid: 28.5 + min: 27.81 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 35.17 + mid: 34.38 + min: 33.59 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 42.300000000000004 + mid: 41.38 + min: 40.46 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 52.33 + mid: 51.25 + min: 50.17 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 71.27 + mid: 69.96 + min: 68.64999999999999 + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml new file mode 100644 index 0000000000..c93fd4edc9 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml @@ -0,0 +1,39 @@ +setname: "STAR_2015_2JET_OS_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1850855" +hepdata: + url: "https://www.hepdata.net/record/ins1850855" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, opposite sign $\eta$ topology", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 7 + tables: [2] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, opposite sign $\eta$ topology" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2015_2JJET_OS_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..5906e64bab --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml @@ -0,0 +1,431 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2015LUMI + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2015POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: 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19.759999999999998 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 24.11 + mid: 23.5 + min: 22.89 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 28.94 + mid: 28.28 + min: 27.62 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 34.93 + mid: 34.15 + min: 33.37 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 41.85 + mid: 40.96 + min: 40.07 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 51.78 + mid: 50.75 + min: 49.72 + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: 70.42 + mid: 69.11 + min: 67.8 + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml new file mode 100644 index 0000000000..2f79c16f39 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml @@ -0,0 +1,39 @@ +setname: "STAR_2015_2JET_SS_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1850855" +hepdata: + url: "https://www.hepdata.net/record/ins1850855" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 7 + tables: [2] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, same sign $\eta$ topology" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2015_2JJET_SS_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..211c4e9394 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml @@ -0,0 +1,431 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2015LUMI + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2015POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2015JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty 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-8.699164389319231e-07 + sys_24: 2.4204943149963057e-05 + sys_25: -3.7156615201748225e-06 + sys_26: 1.749179619738508e-05 + sys_27: 3.534730483972865e-07 + sys_28: 1.349183196534521e-07 + sys_29: -7.779631996597293e-08 + sys_30: 6.633292161656245e-07 + sys_31: 1.054976034309479e-06 + sys_32: -3.378806930895894e-07 + sys_33: 2.2001974670195147e-06 + sys_34: -7.33634436311964e-07 + sys_35: -5.440401898597821e-06 + stat: 0.0418 + lumi: 0.0007 + pol: 0.13908 diff --git a/validphys2/src/validphys/process_options.py b/validphys2/src/validphys/process_options.py index 6c93a66cc0..686e17b392 100644 --- a/validphys2/src/validphys/process_options.py +++ b/validphys2/src/validphys/process_options.py @@ -32,6 +32,7 @@ class _Vars: m_ttBar = "m_ttBar" eta = "eta" m_W2 = "m_W2" + abs_eta = "abs_eta" class _KinematicsInformation: @@ -241,7 +242,7 @@ def _dywboson_xq2map(kin_dict): JET_POL = _Process( "JET_POL", "Longitudinal double-spin asymmetry in inclusive jet production", - accepted_variables=(_Vars.eta, _Vars.pT, _Vars.sqrts), + accepted_variables=(_Vars.eta, _Vars.pT, _Vars.sqrts, _Vars.abs_eta), xq2map_function=_jets_xq2map, ) From 42d413529365a0ef8f58891bce255d785b468e57 Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Wed, 24 Apr 2024 11:45:35 +0200 Subject: [PATCH 18/98] STAR_2009_2JET implementation with only correlations to go --- .../STAR_2009_2JET_A_200GEV/data.yaml | 6 ++ .../STAR_2009_2JET_A_200GEV/filter.py | 85 +++++++++++++++++++ .../STAR_2009_2JET_A_200GEV/kinematics.yaml | 41 +++++++++ .../STAR_2009_2JET_A_200GEV/metadata.yaml | 49 +++++++++++ .../rawdata/Figure9_Bottom.yaml | 34 ++++++++ .../uncertainties.yaml | 20 +++++ .../STAR_2009_2JET_B_200GEV/data.yaml | 8 ++ .../STAR_2009_2JET_B_200GEV/filter.py | 85 +++++++++++++++++++ .../STAR_2009_2JET_B_200GEV/kinematics.yaml | 57 +++++++++++++ .../STAR_2009_2JET_B_200GEV/metadata.yaml | 49 +++++++++++ .../rawdata/Figure9_Top.yaml | 44 ++++++++++ .../uncertainties.yaml | 24 ++++++ .../STAR_2009_2JET_C_200GEV/data.yaml | 8 ++ .../STAR_2009_2JET_C_200GEV/filter.py | 85 +++++++++++++++++++ .../STAR_2009_2JET_C_200GEV/kinematics.yaml | 57 +++++++++++++ .../STAR_2009_2JET_C_200GEV/metadata.yaml | 49 +++++++++++ .../rawdata/Figure9_Mid.yaml | 44 ++++++++++ .../uncertainties.yaml | 24 ++++++ 18 files changed, 769 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Figure9_Bottom.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Figure9_Mid.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/data.yaml new file mode 100644 index 0000000000..e0a271f93e --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/data.yaml @@ -0,0 +1,6 @@ +data_central: +- 0.0019 +- -0.0069 +- 0.0212 +- 0.043 +- 0.078 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py new file mode 100644 index 0000000000..101ba76767 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py @@ -0,0 +1,85 @@ +import glob + +import pandas as pd +import yaml + + +def read_data(fnames): + df = pd.DataFrame() + for fname in fnames: + with open(fname, "r") as file: + data = yaml.safe_load(file) + + Msub = data["independent_variables"][0]["values"] + Gsub = data["dependent_variables"][0]["values"] + + for i in range(len(Msub)): + + df = pd.concat( + [ + df, + pd.DataFrame( + { + "m_low": [Msub[i]["low"]], + "m_high": [Msub[i]["high"]], + "G": [Gsub[i]["value"]], + "stat": [Gsub[i]["errors"][0]["symerror"]], + "sys": [Gsub[i]["errors"][1]["symerror"]], + } + ), + ], + ignore_index=True, + ) + + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["G"])): + data_central.append(float(df.loc[i, "G"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["G"])): + kin_value = { + "m_jj": { + "min": float(df.loc[i, "m_low"]), + "mid": None, + "max": float(df.loc[i, "m_high"]), + }, + "sqrts": {"min": None, "mid": 200, "max": None}, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for idx, i in enumerate(range(len(df))): + e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + error.append(e) + + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + fnames = glob.glob("rawdata/*.yaml") + nnames = sorted([i for i in fnames]) + df = read_data(nnames) + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml new file mode 100644 index 0000000000..5d726a28bc --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml @@ -0,0 +1,41 @@ +bins: +- m_jj: + min: 17.62 + mid: null + max: 19.38 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 20.5 + mid: null + max: 22.9 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 25.03 + mid: null + max: 27.59 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 30.0 + mid: null + max: 33.48 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 37.37 + mid: null + max: 40.39 + sqrts: + min: null + mid: 200 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml new file mode 100644 index 0000000000..58d18669e4 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml @@ -0,0 +1,49 @@ +setname: "STAR_2009_2JET_A_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL as function of $M_{inv}$, topology A", + label: "$A_{LL}$", + units: "", + } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology A" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_A_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Figure9_Bottom.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Figure9_Bottom.yaml new file mode 100644 index 0000000000..ef946d92e2 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Figure9_Bottom.yaml @@ -0,0 +1,34 @@ +dependent_variables: +- header: {name: 'Dijet $A_{LL}$'} + qualifiers: + - {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$', value: Endcap + Endcap} + values: + - errors: + - {label: stat, symerror: 0.007} + - {label: sys, symerror: 0.002} + value: 0.0019 + - errors: + - {label: stat, symerror: 0.007} + - {label: sys, symerror: 0.0024} + value: -0.0069 + - errors: + - {label: stat, symerror: 0.01} + - {label: sys, symerror: 0.0016} + value: 0.0212 + - errors: + - {label: stat, symerror: 0.019} + - {label: sys, symerror: 0.005} + value: 0.043 + - errors: + - {label: stat, symerror: 0.05} + - {label: sys, symerror: 0.007} + value: 0.078 +independent_variables: +- header: {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$'} + values: + - {high: 19.38, low: 17.62} + - {high: 22.9, low: 20.5} + - {high: 27.59, low: 25.03} + - {high: 33.48, low: 30.0} + - {high: 40.39, low: 37.37} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..60987a1e31 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml @@ -0,0 +1,20 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + sys: + description: systematic uncertainty + treatment: ADD + type: UNCORR +bins: +- stat: 0.007 + sys: 0.002 +- stat: 0.007 + sys: 0.0024 +- stat: 0.01 + sys: 0.0016 +- stat: 0.019 + sys: 0.005 +- stat: 0.05 + sys: 0.007 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/data.yaml new file mode 100644 index 0000000000..ee5207be44 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/data.yaml @@ -0,0 +1,8 @@ +data_central: +- -0.0178 +- 0.0058 +- 0.0048 +- 0.0017 +- -0.0078 +- 0.0099 +- 0.012 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py new file mode 100644 index 0000000000..101ba76767 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py @@ -0,0 +1,85 @@ +import glob + +import pandas as pd +import yaml + + +def read_data(fnames): + df = pd.DataFrame() + for fname in fnames: + with open(fname, "r") as file: + data = yaml.safe_load(file) + + Msub = data["independent_variables"][0]["values"] + Gsub = data["dependent_variables"][0]["values"] + + for i in range(len(Msub)): + + df = pd.concat( + [ + df, + pd.DataFrame( + { + "m_low": [Msub[i]["low"]], + "m_high": [Msub[i]["high"]], + "G": [Gsub[i]["value"]], + "stat": [Gsub[i]["errors"][0]["symerror"]], + "sys": [Gsub[i]["errors"][1]["symerror"]], + } + ), + ], + ignore_index=True, + ) + + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["G"])): + data_central.append(float(df.loc[i, "G"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["G"])): + kin_value = { + "m_jj": { + "min": float(df.loc[i, "m_low"]), + "mid": None, + "max": float(df.loc[i, "m_high"]), + }, + "sqrts": {"min": None, "mid": 200, "max": None}, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for idx, i in enumerate(range(len(df))): + e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + error.append(e) + + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + fnames = glob.glob("rawdata/*.yaml") + nnames = sorted([i for i in fnames]) + df = read_data(nnames) + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml new file mode 100644 index 0000000000..17497d6cc1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml @@ -0,0 +1,57 @@ +bins: +- m_jj: + min: 17.06 + mid: null + max: 19.82 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 21.12 + mid: null + max: 23.1 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 25.41 + mid: null + max: 27.73 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 30.66 + mid: null + max: 33.76 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 36.95 + mid: null + max: 39.75 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 46.36 + mid: null + max: 49.66 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 63.58 + mid: null + max: 67.88 + sqrts: + min: null + mid: 200 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml new file mode 100644 index 0000000000..461ccf9857 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml @@ -0,0 +1,49 @@ +setname: "STAR_2009_2JET_B_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL as function of $M_{inv}$, topology B", + label: "$A_{LL}$", + units: "", + } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology B" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_B_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml new file mode 100644 index 0000000000..f3823ff792 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml @@ -0,0 +1,44 @@ +dependent_variables: +- header: {name: 'Dijet $A_{LL}$'} + qualifiers: + - {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$', value: East-Barrel + Endcap} + values: + - errors: + - {label: stat, symerror: 0.011} + - {label: sys, symerror: 0.001} + value: -0.0178 + - errors: + - {label: stat, symerror: 0.005} + - {label: sys, symerror: 0.0015} + value: 0.0058 + - errors: + - {label: stat, symerror: 0.004} + - {label: sys, symerror: 0.0016} + value: 0.0048 + - errors: + - {label: stat, symerror: 0.004} + - {label: sys, symerror: 0.0013} + value: 0.0017 + - errors: + - {label: stat, symerror: 0.006} + - {label: sys, symerror: 0.0017} + value: -0.0078 + - errors: + - {label: stat, symerror: 0.008} + - {label: sys, symerror: 0.0027} + value: 0.0099 + - errors: + - {label: stat, symerror: 0.03} + - {label: sys, symerror: 0.007} + value: 0.012 +independent_variables: +- header: {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$'} + values: + - {high: 19.82, low: 17.06} + - {high: 23.1, low: 21.12} + - {high: 27.73, low: 25.41} + - {high: 33.76, low: 30.66} + - {high: 39.75, low: 36.95} + - {high: 49.66, low: 46.36} + - {high: 67.88, low: 63.58} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..ef5c867b0c --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml @@ -0,0 +1,24 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + sys: + description: systematic uncertainty + treatment: ADD + type: UNCORR +bins: +- stat: 0.011 + sys: 0.001 +- stat: 0.005 + sys: 0.0015 +- stat: 0.004 + sys: 0.0016 +- stat: 0.004 + sys: 0.0013 +- stat: 0.006 + sys: 0.0017 +- stat: 0.008 + sys: 0.0027 +- stat: 0.03 + sys: 0.007 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/data.yaml new file mode 100644 index 0000000000..ca01f4b281 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/data.yaml @@ -0,0 +1,8 @@ +data_central: +- -0.0034 +- 0.0131 +- 0.0027 +- 0.0066 +- 0.0209 +- 0.011 +- 0.031 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py new file mode 100644 index 0000000000..101ba76767 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py @@ -0,0 +1,85 @@ +import glob + +import pandas as pd +import yaml + + +def read_data(fnames): + df = pd.DataFrame() + for fname in fnames: + with open(fname, "r") as file: + data = yaml.safe_load(file) + + Msub = data["independent_variables"][0]["values"] + Gsub = data["dependent_variables"][0]["values"] + + for i in range(len(Msub)): + + df = pd.concat( + [ + df, + pd.DataFrame( + { + "m_low": [Msub[i]["low"]], + "m_high": [Msub[i]["high"]], + "G": [Gsub[i]["value"]], + "stat": [Gsub[i]["errors"][0]["symerror"]], + "sys": [Gsub[i]["errors"][1]["symerror"]], + } + ), + ], + ignore_index=True, + ) + + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["G"])): + data_central.append(float(df.loc[i, "G"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["G"])): + kin_value = { + "m_jj": { + "min": float(df.loc[i, "m_low"]), + "mid": None, + "max": float(df.loc[i, "m_high"]), + }, + "sqrts": {"min": None, "mid": 200, "max": None}, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for idx, i in enumerate(range(len(df))): + e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + error.append(e) + + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + fnames = glob.glob("rawdata/*.yaml") + nnames = sorted([i for i in fnames]) + df = read_data(nnames) + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml new file mode 100644 index 0000000000..2122d767e6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml @@ -0,0 +1,57 @@ +bins: +- m_jj: + min: 17.31 + mid: null + max: 19.71 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 20.62 + mid: null + max: 22.94 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 24.83 + mid: null + max: 27.21 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 29.42 + mid: null + max: 32.16 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 36.62 + mid: null + max: 39.28 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 44.88 + mid: null + max: 47.98 + sqrts: + min: null + mid: 200 + max: null +- m_jj: + min: 59.6 + mid: null + max: 66.04 + sqrts: + min: null + mid: 200 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml new file mode 100644 index 0000000000..6e966a7071 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml @@ -0,0 +1,49 @@ +setname: "STAR_2009_2JET_C_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL as function of $M_{inv}$, topology C", + label: "$A_{LL}$", + units: "", + } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology C" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_C_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Figure9_Mid.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Figure9_Mid.yaml new file mode 100644 index 0000000000..5c094c43a8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Figure9_Mid.yaml @@ -0,0 +1,44 @@ +dependent_variables: +- header: {name: 'Dijet $A_{LL}$'} + qualifiers: + - {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$', value: West-Barrel + Endcap} + values: + - errors: + - {label: stat, symerror: 0.005} + - {label: sys, symerror: 0.0012} + value: -0.0034 + - errors: + - {label: stat, symerror: 0.004} + - {label: sys, symerror: 0.0015} + value: 0.0131 + - errors: + - {label: stat, symerror: 0.004} + - {label: sys, symerror: 0.0007} + value: 0.0027 + - errors: + - {label: stat, symerror: 0.006} + - {label: sys, symerror: 0.0015} + value: 0.0066 + - errors: + - {label: stat, symerror: 0.01} + - {label: sys, symerror: 0.0019} + value: 0.0209 + - errors: + - {label: stat, symerror: 0.016} + - {label: sys, symerror: 0.004} + value: 0.011 + - errors: + - {label: stat, symerror: 0.09} + - {label: sys, symerror: 0.006} + value: 0.031 +independent_variables: +- header: {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$'} + values: + - {high: 19.71, low: 17.31} + - {high: 22.94, low: 20.62} + - {high: 27.21, low: 24.83} + - {high: 32.16, low: 29.42} + - {high: 39.28, low: 36.62} + - {high: 47.98, low: 44.88} + - {high: 66.04, low: 59.6} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..43934dead9 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml @@ -0,0 +1,24 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + sys: + description: systematic uncertainty + treatment: ADD + type: UNCORR +bins: +- stat: 0.005 + sys: 0.0012 +- stat: 0.004 + sys: 0.0015 +- stat: 0.004 + sys: 0.0007 +- stat: 0.006 + sys: 0.0015 +- stat: 0.01 + sys: 0.0019 +- stat: 0.016 + sys: 0.004 +- stat: 0.09 + sys: 0.006 From 73d93f7bc2ead978ddf30e7a7e9c4947bc56b5e1 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 24 Apr 2024 13:56:49 +0200 Subject: [PATCH 19/98] fix 2009 dijet and implement 2012 --- .../star/jet_dijet_2012_510gev.py | 290 +++++ .../star/jet_dijet_2013_510gev.py | 5 +- .../star/jet_dijet_2015_200gev.py | 25 +- .../STAR_2009_2JET_A_200GEV/metadata.yaml | 4 +- .../STAR_2009_2JET_B_200GEV/metadata.yaml | 4 +- .../STAR_2009_2JET_C_200GEV/metadata.yaml | 4 +- .../STAR_2012_1JET_510GEV/data.yaml | 15 + .../STAR_2012_1JET_510GEV/kinematics.yaml | 169 +++ .../STAR_2012_1JET_510GEV/metadata.yaml | 52 + .../rawdata/Figure12(Run12).csv | 22 + .../rawdata/Figure14(b,A,data).csv | 18 + .../rawdata/Figure14(b,B,data).csv | 19 + .../rawdata/Figure14(b,C,data).csv | 18 + .../rawdata/Figure14(b,D,data).csv | 19 + .../rawdata/corrAVsA.tex | 18 + .../rawdata/corrAVsB.tex | 18 + .../rawdata/corrAVsC.tex | 18 + .../rawdata/corrAVsD.tex | 18 + .../rawdata/corrBVsB.tex | 19 + .../rawdata/corrBVsC.tex | 19 + .../rawdata/corrBVsD.tex | 19 + .../rawdata/corrCVsC.tex | 18 + .../rawdata/corrCVsD.tex | 18 + .../rawdata/corrDVsD.tex | 19 + .../rawdata/corrIVsA.tex | 22 + .../rawdata/corrIVsB.tex | 22 + .../rawdata/corrIVsC.tex | 22 + .../rawdata/corrIVsD.tex | 22 + .../rawdata/corrIVsI.tex | 22 + .../STAR_2012_1JET_510GEV/uncertainties.yaml | 1046 +++++++++++++++++ .../STAR_2012_2JET_A_510GEV/data.yaml | 11 + .../STAR_2012_2JET_A_510GEV/kinematics.yaml | 81 ++ .../STAR_2012_2JET_A_510GEV/metadata.yaml | 41 + .../uncertainties.yaml | 828 +++++++++++++ .../STAR_2012_2JET_B_510GEV/data.yaml | 12 + .../STAR_2012_2JET_B_510GEV/kinematics.yaml | 89 ++ .../STAR_2012_2JET_B_510GEV/metadata.yaml | 41 + .../uncertainties.yaml | 887 ++++++++++++++ .../STAR_2012_2JET_C_510GEV/data.yaml | 11 + .../STAR_2012_2JET_C_510GEV/kinematics.yaml | 81 ++ .../STAR_2012_2JET_C_510GEV/metadata.yaml | 41 + .../uncertainties.yaml | 828 +++++++++++++ .../STAR_2012_2JET_D_510GEV/data.yaml | 12 + .../STAR_2012_2JET_D_510GEV/kinematics.yaml | 89 ++ .../STAR_2012_2JET_D_510GEV/metadata.yaml | 41 + .../uncertainties.yaml | 887 ++++++++++++++ 46 files changed, 5966 insertions(+), 18 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure12(Run12).csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,A,data).csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,B,data).csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,C,data).csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,D,data).csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsA.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsB.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsC.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsD.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsB.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsC.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsD.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsC.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsD.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrDVsD.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsA.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsB.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsC.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsD.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsI.tex create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py new file mode 100644 index 0000000000..c932252b5b --- /dev/null +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py @@ -0,0 +1,290 @@ +"""This script provides the common filer to the jet and dijet STAR 2012 datasets. +Files need to be parsed all together as there are correlations provided. +""" +import pathlib +import math + +import numpy as np +import pandas as pd +import yaml + +from nnpdf_data.filter_utils.correlations import ( + compute_covmat, + upper_triangular_to_symmetric, +) + +# values from the paper https://arxiv.org/abs/1906.02740 +SQRTS = 510 +YEAR = 2012 +ETA_ABS = 0.9 +POL_UNC = 0.066 +TOPOPLOGY_LIST = ["I", "A", "B", "C", "D"] + +HERE = pathlib.Path(__file__).parents[2] +RAWDATA_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/rawdata/" + + +def read_1jet_data(): + data_table = pathlib.Path(RAWDATA_PATH / "Figure12(Run12).csv") + + with open(data_table, "r", encoding="utf-8") as file: + all_data = pd.read_csv(file, delimiter=",", skiprows=6) + + df = pd.DataFrame() + df["pT"] = all_data["Parton Jet $p_{T}$ [GeV/c]"] + df["pT_min"] = all_data["Parton Jet $p_{T}$ [GeV/c] LOW"] + df["pT_max"] = all_data["Parton Jet $p_{T}$ [GeV/c] HIGH"] + df["eta"] = 0.0 + df["eta_min"] = -ETA_ABS + df["eta_max"] = +ETA_ABS + df["sqrts"] = SQRTS + df["ALL"] = all_data["Inclusive Jet $A_{LL}$"] + df["stat"] = all_data["stat +"] + df["syst"] = all_data["sys +"] + df["pol"] = POL_UNC * df["ALL"] + df["lumi_ue"] = all_data["UE/RL sys +"] + + print("1JET data loaded. Npoint: ", len(df)) + return df + + +def read_2jet_data(topology): + data_table = RAWDATA_PATH / f"Figure14(b,{topology},data).csv" + + with open(data_table, "r", encoding="utf-8") as file: + all_data = pd.read_csv(file, delimiter=",", skiprows=6) + + df = pd.DataFrame() + df["mjj"] = all_data["Parton DiJet $M_{inv}$ [$GeV/c^{2}$]"] + df["mjj_min"] = all_data["Parton DiJet $M_{inv}$ [$GeV/c^{2}$] LOW"] + df["mjj_max"] = all_data["Parton DiJet $M_{inv}$ [$GeV/c^{2}$] HIGH"] + df["sqrts"] = SQRTS + df["ALL"] = all_data[r"DiJet $A_{LL}$"] + df["stat"] = all_data[r"stat +"] + df["syst"] = all_data[r"sys +"] + df["pol"] = POL_UNC * df["ALL"] + df["lumi_ue"] = all_data["UE/RL sys +"] + print(f"2JET {topology} data loaded. Npoint: ", len(df)) + return df + + +def read_correlations(ndata_dict): + """Read the correlation files and build a big matix""" + corr_rows = [] + # loop on block rows + for a, ndata_a in ndata_dict.items(): + la = [a for _ in range(ndata_a)] + corr_row = pd.DataFrame() + # loop on block columns + for b, ndata_b in ndata_dict.items(): + lb = [b for _ in range(ndata_b)] + # build the block + try: + with open(RAWDATA_PATH / f"corr{a}Vs{b}.tex", encoding="utf-8") as file: + corr_df = pd.read_csv( + file, sep="&", skiprows=3, skipfooter=3, engine="python" + ) + + # add some parsing + corr_vals = [] + for val in corr_df.values.flatten(): + if val is None: + continue + if isinstance(val, str): + val = val.replace("\\", "") + try: + val = float(val) + except ValueError: + continue + if not math.isnan(val): + corr_vals.append(val) + + if a == b: + corr = upper_triangular_to_symmetric(corr_vals, ndata_a) + else: + corr = np.array(corr_vals).reshape((ndata_a, ndata_b)) + except FileNotFoundError: + corr = pd.DataFrame(np.zeros((ndata_a, ndata_b)), index=la, columns=lb) + + corr = pd.DataFrame(corr, index=la, columns=lb) + corr_row = pd.concat([corr_row, corr], axis=1) + corr_rows.append(corr_row) + + tot_corr = pd.concat(corr_rows) + if not np.allclose(tot_corr, np.triu(tot_corr)): + raise ValueError("Correlation matrix not read correctly") + return tot_corr + tot_corr.T - np.eye(np.sum((*ndata_dict.values(),))) + + +def write_1jet_data(df, art_sys): + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/" + + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + kin_value = { + "pT": { + "min": float(df.loc[i, "pT_min"]), + "mid": float(df.loc[i, "pT"]), + "max": float(df.loc[i, "pT_max"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": { + "min": float(df.loc[i, "eta_min"]), + "mid": float(df.loc[i, "eta"]), + "max": float(df.loc[i, "eta_max"]), + }, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + error_definition = { + "lumi_ue": { + "description": "underlying event and relative luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}LUMIUE", + }, + "pol": { + "description": "polarization uncertainty", + "treatment": "MULT", + "type": f"STAR{YEAR}POL", + }, + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = { + "lumi_ue": float(df.loc[i, "lumi_ue"]), + "pol": float(df.loc[i, "pol"]), + } + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + error.append(e) + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated statistical + systematics uncertainty", + "treatment": "ADD", + "type": f"STAR2013JETunc{j}", + } + for j in range(len(sys_i)) + } + ) + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +def write_2jet_data(df, topology, art_sys): + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{topology}_{SQRTS}GEV/" + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + kin_value = { + "m_jj": { + "min": float(df.loc[i, "mjj_min"]), + "mid": float(df.loc[i, "mjj"]), + "max": float(df.loc[i, "mjj_max"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + error_definition = { + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "lumi_ue": { + "description": "underlying event and relative luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}LUMIUE", + }, + "pol": { + "description": "polarization uncertainty", + "treatment": "MULT", + "type": f"STAR{YEAR}POL", + }, + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = { + "stat": float(df.loc[i, "stat"]), + "lumi_ue": float(df.loc[i, "lumi_ue"]), + "pol": float(df.loc[i, "pol"]), + } + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + error.append(e) + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": f"STAR2013JETunc{j}", + } + for j in range(len(sys_i)) + } + ) + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # load all the data + dfs = {"I": read_1jet_data()} + for topo in TOPOPLOGY_LIST[1:]: + dfs[topo] = read_2jet_data(topo) + + # load correlations + ndata_dict = {a: len(b) for a, b in dfs.items()} + correlation_df = read_correlations(ndata_dict) + # from the paper we understand that stat dijet is not correlated + # I-I (stat + sys) | I-D (stat + sys) + # D-I (stat + sys) | D-D (sys) + correlated_unc = np.sqrt( + dfs["I"]["syst"] ** 2 + dfs["I"]["stat"] ** 2 + ).values.tolist() + for a in TOPOPLOGY_LIST[1:]: + correlated_unc.extend(dfs[a]["syst"].values) + ndata_points = np.sum((*ndata_dict.values(),)) + # decompose uncertainties + art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) + + # write data + cnt = 0 + for topo, df in dfs.items(): + ndata = ndata_dict[topo] + syst = art_sys[cnt : cnt + ndata, :].tolist() + if topo == "I": + write_1jet_data(df, syst) + else: + write_2jet_data(df, topo, syst) + cnt += ndata diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 77d947d13c..638bcfe7e3 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -7,7 +7,10 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.correlations import compute_covmat, upper_triangular_to_symmetric +from nnpdf_data.filter_utils.correlations import ( + compute_covmat, + upper_triangular_to_symmetric, +) # values from the paper https://arxiv.org/pdf/2110.11020.pdf SQRTS = 510 diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py index ec479eb8fe..24bd837143 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -7,7 +7,10 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.correlations import compute_covmat, upper_triangular_to_symmetric +from nnpdf_data.filter_utils.correlations import ( + compute_covmat, + upper_triangular_to_symmetric, +) # values from the paper SQRTS = 200 @@ -82,7 +85,7 @@ def read_2jet_data(topology): all_data = pd.read_csv(file, delimiter=",", skiprows=27) df = pd.DataFrame() - df["mjj"] = mjj_data['Dijet invariant mass $M_{inv}$ at the parton level [GeV/$c$]'] + df["mjj"] = mjj_data["Dijet invariant mass $M_{inv}$ at the parton level [GeV/$c$]"] df["mjj_min"] = df["mjj"] + mjj_data["Syst -"] df["mjj_max"] = df["mjj"] + mjj_data["Syst +"] df["sqrts"] = SQRTS @@ -170,13 +173,13 @@ def write_1jet_data(df, art_sys): "lumi": { "description": "luminosity uncertainty", "treatment": "ADD", - "type": "STAR2015LUMI", + "type": f"STAR{YEAR}LUMI", }, "pol": { "description": "polarization uncertainty", "treatment": "MULT", - "type": "STAR2015POL", - } + "type": f"STAR{YEAR}POL", + }, } # loop on data points for i, sys_i in enumerate(art_sys): @@ -239,13 +242,13 @@ def write_2jet_data(df, topology, art_sys): "lumi": { "description": "luminosity uncertainty", "treatment": "ADD", - "type": "STAR2015LUMI", + "type": f"STAR{YEAR}LUMI", }, "pol": { "description": "polarization uncertainty", "treatment": "MULT", - "type": "STAR2015POL", - } + "type": f"STAR{YEAR}POL", + }, } # loop on data points for i, sys_i in enumerate(art_sys): @@ -288,9 +291,9 @@ def write_2jet_data(df, topology, art_sys): # merge the 1JET topologies new_dfs = { - "1JET": pd.concat([dfs['CC'], dfs['CF']], ignore_index=True), - "OS": dfs["OS"], - "SS": dfs["SS"] + "1JET": pd.concat([dfs["CC"], dfs["CF"]], ignore_index=True), + "OS": dfs["OS"], + "SS": dfs["SS"], } # from the paper we understand that stat dijet is not correlated diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml index 58d18669e4..75ab1997b3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml @@ -22,8 +22,8 @@ implemented_observables: } observable_name: ALL process_type: DIJET_POL - ndata: 12 - tables: [5] + ndata: 5 + tables: [9] kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml index 461ccf9857..93d593d014 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml @@ -22,8 +22,8 @@ implemented_observables: } observable_name: ALL process_type: DIJET_POL - ndata: 12 - tables: [5] + ndata: 7 + tables: [9] kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml index 6e966a7071..675cf5256d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml @@ -22,8 +22,8 @@ implemented_observables: } observable_name: ALL process_type: DIJET_POL - ndata: 12 - tables: [5] + ndata: 7 + tables: [9] kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/data.yaml new file mode 100644 index 0000000000..7922dfd3e0 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/data.yaml @@ -0,0 +1,15 @@ +data_central: +- 1.71e-05 +- -0.00215 +- 0.00162 +- 0.0005 +- 0.00148 +- 0.00293 +- 0.00158 +- 0.00445 +- 0.00496 +- 0.0036 +- 0.0169 +- -0.00492 +- 0.0122 +- 0.00177 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/kinematics.yaml new file mode 100644 index 0000000000..680a8a3950 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/kinematics.yaml @@ -0,0 +1,169 @@ +bins: +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 7.282 + mid: 7.02 + min: 6.758 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 8.267 + mid: 7.97 + min: 7.673 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 10.26 + mid: 9.9 + min: 9.54 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 12.002 + mid: 11.6 + min: 11.198 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 13.865 + mid: 13.4 + min: 12.935 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 16.1 + mid: 15.6 + min: 15.1 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 19.599 + mid: 19.0 + min: 18.401 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 22.829 + mid: 22.200000000000003 + min: 21.571 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 26.441 + mid: 25.7 + min: 24.959 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 30.533 + mid: 29.700000000000003 + min: 28.867 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 35.349 + mid: 34.4 + min: 33.451 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 40.78 + mid: 39.7 + min: 38.62 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 47.54 + mid: 46.3 + min: 45.06 + sqrts: + max: null + mid: 510.0 + min: null +- eta: + max: 0.9 + mid: 0.0 + min: -0.9 + pT: + max: 55.29 + mid: 53.8 + min: 52.31 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml new file mode 100644 index 0000000000..b082cf20bd --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml @@ -0,0 +1,52 @@ +setname: "STAR_2012_1JET_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1738738" +hepdata: + url: "https://www.hepdata.net/record/ins1738738" + version: 1 +arXiv: + url: https://arxiv.org/abs/1906.02740 + +version: 1 +version_comment: "Initial implementation, correlations from arXiv" + +implemented_observables: + - observable: { description: "$A_{LL}$ as function of $p_T$", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: JET_POL + ndata: 14 + tables: [12] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, eta] + plotting: + dataset_label: "STAR 510 GeV (2012) 1-JET $A_{LL}$" + kinematics_override: identity + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_1JET_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure12(Run12).csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure12(Run12).csv new file mode 100644 index 0000000000..3eabe1e964 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure12(Run12).csv @@ -0,0 +1,22 @@ +#: table_doi: 10.17182/hepdata.105278.v1/t29 +#: name: Figure 12 (Run12) +#: description: the inclusive jet asymmetries and systematic uncertainties,as function of pT compared to the theoretical predictions (Run12) +#: data_file: fig12_run12_input_yaml.yaml +#: keyword cmenergies: 510.0 +#: Parton Jet $p_{T}$ [GeV/c],,,Inclusive Jet $A_{LL}$, 510GeV, Run12, R=0.5,$\vert \eta \vert$ < 0.9 +Parton Jet $p_{T}$ [GeV/c],Parton Jet $p_{T}$ [GeV/c] LOW,Parton Jet $p_{T}$ [GeV/c] HIGH,Inclusive Jet $A_{LL}$,stat +,stat -,sys +,sys -,UE/RL sys +,UE/RL sys - +7.02,6.758,7.282,1.71e-05,0.00132,-0.00132,0.000132,-0.000132,0.000364,-0.000364 +7.97,7.673,8.267,-0.00215,0.0014,-0.0014,0.000485,-0.000485,0.000326,-0.000326 +9.899999999999999,9.54,10.26,0.00162,0.00101,-0.00101,0.000109,-0.000109,0.000311,-0.000311 +11.600000000000001,11.198,12.002,0.0005,0.00112,-0.00112,8.01e-05,-8.01e-05,0.000284,-0.000284 +13.4,12.935,13.865,0.00148,0.00129,-0.00129,0.000106,-0.000106,0.000272,-0.000272 +15.600000000000001,15.1,16.1,0.00293,0.00159,-0.00159,0.000159,-0.000159,0.000256,-0.000256 +19.0,18.401,19.599,0.00158,0.00158,-0.00158,0.000139,-0.000139,0.000251,-0.000251 +22.200000000000003,21.571,22.829,0.00445,0.00181,-0.00181,0.000228,-0.000228,0.000246,-0.000246 +25.7,24.959,26.441,0.00496,0.00214,-0.00214,0.000177,-0.000177,0.000239,-0.000239 +29.700000000000003,28.867,30.533,0.0036,0.00273,-0.00273,0.000251,-0.000251,0.000234,-0.000234 +34.4,33.451,35.349,0.0169,0.00372,-0.00372,0.000376,-0.000376,0.000231,-0.000231 +39.7,38.62,40.78,-0.00492,0.00537,-0.00537,0.000336,-0.000336,0.000229,-0.000229 +46.3,45.06,47.54,0.0122,0.00836,-0.00836,0.000687,-0.000687,0.000227,-0.000227 +53.8,52.31,55.29,0.00177,0.0137,-0.0137,0.000813,-0.000813,0.000226,-0.000226 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,A,data).csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,A,data).csv new file mode 100644 index 0000000000..7774167103 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,A,data).csv @@ -0,0 +1,18 @@ +#: table_doi: 10.17182/hepdata.105278.v1/t53 +#: name: Figure 14 (b,A,data) +#: description: Dijet asymmetries for the same topological bins in 510 GeV pp collisions (b,A,data) +#: data_file: fig14_b_data_A_input_yaml.yaml +#: keyword cmenergies: 510.0 +#: Parton DiJet $M_{inv}$ [$GeV/c^{2}$],,,DiJet $A_{LL}$,b, A, data +Parton DiJet $M_{inv}$ [$GeV/c^{2}$],Parton DiJet $M_{inv}$ [$GeV/c^{2}$] LOW,Parton DiJet $M_{inv}$ [$GeV/c^{2}$] HIGH,DiJet $A_{LL}$,stat +,stat -,sys +,sys -,UE/RL sys +,UE/RL sys - +19.04,18.22,19.86,-0.0128,0.0066,-0.0066,0.0002,-0.0002,0.00025,-0.00025 +21.619999999999997,20.66,22.58,0.009,0.0052,-0.0052,0.0002,-0.0002,0.00058,-0.00058 +26.380000000000003,25.3,27.46,0.0079,0.005,-0.005,0.0004,-0.0004,0.00062,-0.00062 +32.3,31.14,33.46,-0.0012,0.0052,-0.0052,0.0004,-0.0004,0.00056,-0.00056 +38.42,37.22,39.62,0.0101,0.0061,-0.0061,0.0004,-0.0004,0.00051,-0.00051 +45.18,43.7,46.66,-0.0013,0.0064,-0.0064,0.0006,-0.0006,0.00046,-0.00046 +53.42,51.87,54.97,0.0048,0.0081,-0.0081,0.0009,-0.0009,0.00044,-0.00044 +63.519999999999996,61.72,65.32,0.0052,0.0108,-0.0108,0.001,-0.001,0.00037,-0.00037 +75.55000000000001,73.34,77.76,0.0363,0.0167,-0.0167,0.002,-0.002,0.00037,-0.00037 +89.12,86.74,91.5,-0.0218,0.0264,-0.0264,0.0048,-0.0048,0.00031,-0.00031 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,B,data).csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,B,data).csv new file mode 100644 index 0000000000..5acdc8e0c6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,B,data).csv @@ -0,0 +1,19 @@ +#: table_doi: 10.17182/hepdata.105278.v1/t54 +#: name: Figure 14 (b,B,data) +#: description: Dijet asymmetries for the same topological bins in 510 GeV pp collisions (b,B,data) +#: data_file: fig14_b_data_B_input_yaml.yaml +#: keyword cmenergies: 510.0 +#: Parton DiJet $M_{inv}$ [$GeV/c^{2}$],,,DiJet $A_{LL}$,b, B, data +Parton DiJet $M_{inv}$ [$GeV/c^{2}$],Parton DiJet $M_{inv}$ [$GeV/c^{2}$] LOW,Parton DiJet $M_{inv}$ [$GeV/c^{2}$] HIGH,DiJet $A_{LL}$,stat +,stat -,sys +,sys -,UE/RL sys +,UE/RL sys - +18.799999999999997,17.99,19.61,-0.0023,0.0053,-0.0053,0.0002,-0.0002,0.0004,-0.0004 +21.799999999999997,20.86,22.74,0.0041,0.0036,-0.0036,0.0003,-0.0003,0.00063,-0.00063 +26.37,25.28,27.46,0.0016,0.0033,-0.0033,0.0003,-0.0003,0.00041,-0.00041 +32.24,31.17,33.31,0.0029,0.0034,-0.0034,0.0004,-0.0004,0.00043,-0.00043 +38.42,37.11,39.73,-0.0063,0.004,-0.004,0.0005,-0.0005,0.00035,-0.00035 +45.83,44.42,47.24,0.002,0.0041,-0.0041,0.0007,-0.0007,0.00036,-0.00036 +54.14,52.45,55.83,0.0128,0.005,-0.005,0.0008,-0.0008,0.0003,-0.0003 +64.17,62.34,66,-0.0022,0.0065,-0.0065,0.0011,-0.0011,0.00031,-0.00031 +76.06,73.93,78.19,-0.001,0.0096,-0.0096,0.0014,-0.0014,0.00028,-0.00028 +89.81,87.33,92.29,-0.016,0.0143,-0.0143,0.002,-0.002,0.00026,-0.00026 +107.92,105.03,110.81,-0.0205,0.0242,-0.0242,0.0027,-0.0027,0.00026,-0.00026 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,C,data).csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,C,data).csv new file mode 100644 index 0000000000..7ebe2ca958 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,C,data).csv @@ -0,0 +1,18 @@ +#: table_doi: 10.17182/hepdata.105278.v1/t55 +#: name: Figure 14 (b,C,data) +#: description: Dijet asymmetries for the same topological bins in 510 GeV pp collisions (b,C,data) +#: data_file: fig14_b_data_C_input_yaml.yaml +#: keyword cmenergies: 510.0 +#: Parton DiJet $M_{inv}$ [$GeV/c^{2}$],,,DiJet $A_{LL}$,b, C, data +Parton DiJet $M_{inv}$ [$GeV/c^{2}$],Parton DiJet $M_{inv}$ [$GeV/c^{2}$] LOW,Parton DiJet $M_{inv}$ [$GeV/c^{2}$] HIGH,DiJet $A_{LL}$,stat +,stat -,sys +,sys -,UE/RL sys +,UE/RL sys - +19.810000000000002,19,20.62,0.0058,0.0085,-0.0085,0.0002,-0.0002,0.00026,-0.00026 +22.009999999999998,20.89,23.13,-0.0006,0.0066,-0.0066,0.0006,-0.0006,0.00063,-0.00063 +26.159999999999997,25.08,27.24,-0.0043,0.0062,-0.0062,0.0004,-0.0004,0.00074,-0.00074 +32.7,31.51,33.89,0.0049,0.0065,-0.0065,0.0006,-0.0006,0.00078,-0.00078 +38.709999999999994,37.37,40.05,0.0046,0.0077,-0.0077,0.0007,-0.0007,0.00081,-0.00081 +46.01,44.65,47.37,0.0155,0.0079,-0.0079,0.0006,-0.0006,0.00052,-0.00052 +53.89,52.11,55.67,-0.0045,0.0098,-0.0098,0.0012,-0.0012,0.00053,-0.00053 +64.75,63.01,66.49,0.0104,0.0127,-0.0127,0.0014,-0.0014,0.00041,-0.00041 +77.15,74.88,79.42,0.0346,0.0192,-0.0192,0.0019,-0.0019,0.00041,-0.00041 +91.14,88.56,93.72,0.0593,0.0294,-0.0294,0.0073,-0.0073,0.00041,-0.00041 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,D,data).csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,D,data).csv new file mode 100644 index 0000000000..e83c815db6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/Figure14(b,D,data).csv @@ -0,0 +1,19 @@ +#: table_doi: 10.17182/hepdata.105278.v1/t56 +#: name: Figure 14 (b,D,data) +#: description: Dijet asymmetries for the same topological bins in 510 GeV pp collisions (b,D,data) +#: data_file: fig14_b_data_D_input_yaml.yaml +#: keyword cmenergies: 510.0 +#: Parton DiJet $M_{inv}$ [$GeV/c^{2}$],,,DiJet $A_{LL}$,b, D, data +Parton DiJet $M_{inv}$ [$GeV/c^{2}$],Parton DiJet $M_{inv}$ [$GeV/c^{2}$] LOW,Parton DiJet $M_{inv}$ [$GeV/c^{2}$] HIGH,DiJet $A_{LL}$,stat +,stat -,sys +,sys -,UE/RL sys +,UE/RL sys - +20.54,18.4,22.68,0.0054,0.0161,-0.0161,0.0002,-0.0002,0.00131,-0.00131 +22.09,21.14,23.04,0.0042,0.0051,-0.0051,0.0002,-0.0002,0.00022,-0.00022 +26.31,25.33,27.29,0.0051,0.005,-0.005,0.0003,-0.0003,0.00072,-0.00072 +31.72,30.5,32.94,-0.0031,0.0059,-0.0059,0.0003,-0.0003,0.00052,-0.00052 +38.480000000000004,37.17,39.79,-0.0018,0.006,-0.006,0.0004,-0.0004,0.00054,-0.00054 +45.209999999999994,43.66,46.76,-0.004,0.007,-0.007,0.0005,-0.0005,0.00044,-0.00044 +54.150000000000006,52.46,55.84,0.0034,0.0087,-0.0087,0.0008,-0.0008,0.00044,-0.00044 +64.3,62.38,66.22,0.005,0.0123,-0.0123,0.0011,-0.0011,0.00036,-0.00036 +76.66,74.51,78.81,0.0058,0.0178,-0.0178,0.0024,-0.0024,0.00036,-0.00036 +89.57,86.95,92.19,0.0291,0.0296,-0.0296,0.0014,-0.0014,0.00036,-0.00036 +106.86,103.89,109.83,-0.0055,0.0461,-0.0461,0.0028,-0.0028,0.00029,-0.00029 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsA.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsA.tex new file mode 100644 index 0000000000..efcf99dcb1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsA.tex @@ -0,0 +1,18 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & A1 & A2 & A3 & A4 & A5 & A6 & A7 & A8 & A9 & A10 \\ +\hline +A1 & 1 & 0.003 & 0.004 & 0.004 & 0.004 & 0.004 & 0.004 & 0.003 & 0.004 & 0.006 \\ +A2 & & 1 & 0.015 & 0.013 & 0.011 & 0.011 & 0.010 & 0.007 & 0.007 & 0.009 \\ +A3 & & & 1 & 0.016 & 0.014 & 0.014 & 0.013 & 0.010 & 0.011 & 0.014 \\ +A4 & & & & 1 & 0.012 & 0.013 & 0.012 & 0.009 & 0.010 & 0.013 \\ +A5 & & & & & 1 & 0.011 & 0.011 & 0.009 & 0.010 & 0.013 \\ +A6 & & & & & & 1 & 0.013 & 0.010 & 0.012 & 0.017 \\ +A7 & & & & & & & 1 & 0.012 & 0.014 & 0.020 \\ +A8 & & & & & & & & 1 & 0.012 & 0.017 \\ +A9 & & & & & & & & & 1 & 0.021 \\ +A10 & & & & & & & & & & 1 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsB.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsB.tex new file mode 100644 index 0000000000..84ff964010 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsB.tex @@ -0,0 +1,18 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & B1 & B2 & B3 & B4 & B5 & B6 & B7 & B8 & B9 & B10 & B11 \\ +\hline +A1 & 0.001 & 0.002 & 0.003 & 0.004 & 0.004 & 0.005 & 0.005 & 0.005 & 0.004 & 0.004 & 0.004 \\ +A2 & 0.002 & 0.003 & 0.004 & 0.005 & 0.005 & 0.007 & 0.007 & 0.007 & 0.006 & 0.006 & 0.005 \\ +A3 & 0.003 & 0.006 & 0.007 & 0.009 & 0.008 & 0.011 & 0.011 & 0.012 & 0.010 & 0.010 & 0.008 \\ +A4 & 0.003 & 0.005 & 0.007 & 0.009 & 0.008 & 0.011 & 0.011 & 0.012 & 0.010 & 0.010 & 0.008 \\ +A5 & 0.003 & 0.005 & 0.007 & 0.009 & 0.008 & 0.011 & 0.011 & 0.012 & 0.010 & 0.010 & 0.008 \\ +A6 & 0.004 & 0.007 & 0.009 & 0.011 & 0.010 & 0.015 & 0.014 & 0.016 & 0.013 & 0.013 & 0.010 \\ +A7 & 0.004 & 0.008 & 0.011 & 0.013 & 0.012 & 0.017 & 0.017 & 0.018 & 0.015 & 0.015 & 0.012 \\ +A8 & 0.004 & 0.007 & 0.009 & 0.011 & 0.010 & 0.015 & 0.014 & 0.016 & 0.013 & 0.013 & 0.010 \\ +A9 & 0.004 & 0.009 & 0.012 & 0.014 & 0.013 & 0.019 & 0.018 & 0.020 & 0.017 & 0.016 & 0.013 \\ +A10 & 0.007 & 0.014 & 0.018 & 0.022 & 0.020 & 0.028 & 0.027 & 0.030 & 0.025 & 0.025 & 0.020 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsC.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsC.tex new file mode 100644 index 0000000000..69651a090c --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsC.tex @@ -0,0 +1,18 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & C1 & C2 & C3 & C4 & C5 & C6 & C7 & C8 & C9 & C10 \\ +\hline +A1 & 0.001 & 0.003 & 0.002 & 0.003 & 0.003 & 0.002 & 0.004 & 0.004 & 0.003 & 0.008 \\ +A2 & 0.001 & 0.004 & 0.003 & 0.004 & 0.004 & 0.003 & 0.005 & 0.005 & 0.004 & 0.011 \\ +A3 & 0.002 & 0.007 & 0.005 & 0.006 & 0.007 & 0.005 & 0.009 & 0.008 & 0.007 & 0.018 \\ +A4 & 0.002 & 0.007 & 0.005 & 0.006 & 0.006 & 0.005 & 0.008 & 0.008 & 0.007 & 0.017 \\ +A5 & 0.002 & 0.007 & 0.005 & 0.006 & 0.006 & 0.005 & 0.008 & 0.008 & 0.007 & 0.017 \\ +A6 & 0.002 & 0.009 & 0.006 & 0.008 & 0.008 & 0.007 & 0.011 & 0.010 & 0.009 & 0.023 \\ +A7 & 0.002 & 0.010 & 0.007 & 0.009 & 0.010 & 0.008 & 0.013 & 0.012 & 0.010 & 0.026 \\ +A8 & 0.002 & 0.009 & 0.006 & 0.008 & 0.008 & 0.007 & 0.011 & 0.011 & 0.009 & 0.023 \\ +A9 & 0.003 & 0.011 & 0.008 & 0.010 & 0.011 & 0.009 & 0.014 & 0.013 & 0.011 & 0.029 \\ +A10 & 0.004 & 0.017 & 0.012 & 0.015 & 0.016 & 0.013 & 0.021 & 0.020 & 0.017 & 0.043 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsD.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsD.tex new file mode 100644 index 0000000000..2ed9cb914e --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrAVsD.tex @@ -0,0 +1,18 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & D1 & D2 & D3 & D4 & D5 & D6 & D7 & D8 & D9 & D10 & D11 \\ +\hline +A1 & 0.000 & 0.001 & 0.002 & 0.002 & 0.002 & 0.002 & 0.003 & 0.003 & 0.004 & 0.002 & 0.002 \\ +A2 & 0.001 & 0.002 & 0.003 & 0.002 & 0.003 & 0.003 & 0.004 & 0.004 & 0.006 & 0.002 & 0.003 \\ +A3 & 0.001 & 0.003 & 0.004 & 0.004 & 0.005 & 0.006 & 0.006 & 0.007 & 0.010 & 0.004 & 0.004 \\ +A4 & 0.001 & 0.003 & 0.004 & 0.004 & 0.005 & 0.005 & 0.006 & 0.006 & 0.009 & 0.003 & 0.004 \\ +A5 & 0.001 & 0.003 & 0.004 & 0.004 & 0.005 & 0.005 & 0.006 & 0.007 & 0.010 & 0.003 & 0.004 \\ +A6 & 0.001 & 0.004 & 0.005 & 0.005 & 0.006 & 0.007 & 0.008 & 0.008 & 0.012 & 0.004 & 0.006 \\ +A7 & 0.001 & 0.005 & 0.006 & 0.006 & 0.007 & 0.008 & 0.010 & 0.010 & 0.014 & 0.005 & 0.007 \\ +A8 & 0.001 & 0.004 & 0.005 & 0.005 & 0.006 & 0.007 & 0.008 & 0.009 & 0.012 & 0.005 & 0.006 \\ +A9 & 0.002 & 0.006 & 0.007 & 0.006 & 0.008 & 0.009 & 0.010 & 0.011 & 0.016 & 0.006 & 0.007 \\ +A10 & 0.002 & 0.008 & 0.010 & 0.010 & 0.012 & 0.013 & 0.016 & 0.016 & 0.024 & 0.009 & 0.011 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsB.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsB.tex new file mode 100644 index 0000000000..8465e239f8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsB.tex @@ -0,0 +1,19 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & B1 & B2 & B3 & B4 & B5 & B6 & B7 & B8 & B9 & B10 & B11 \\ +\hline +B1 & 1 & 0.013 & 0.010 & 0.011 & 0.008 & 0.010 & 0.008 & 0.008 & 0.006 & 0.006 & 0.005 \\ +B2 & & 1 & 0.024 & 0.027 & 0.019 & 0.023 & 0.018 & 0.018 & 0.014 & 0.012 & 0.009 \\ +B3 & & & 1 & 0.023 & 0.018 & 0.023 & 0.019 & 0.020 & 0.016 & 0.015 & 0.012 \\ +B4 & & & & 1 & 0.021 & 0.026 & 0.023 & 0.024 & 0.019 & 0.018 & 0.014 \\ +B5 & & & & & 1 & 0.022 & 0.020 & 0.021 & 0.017 & 0.016 & 0.013 \\ +B6 & & & & & & 1 & 0.027 & 0.029 & 0.023 & 0.022 & 0.018 \\ +B7 & & & & & & & 1 & 0.027 & 0.022 & 0.022 & 0.017 \\ +B8 & & & & & & & & 1 & 0.024 & 0.024 & 0.019 \\ +B9 & & & & & & & & & 1 & 0.020 & 0.016 \\ +B10 & & & & & & & & & & 1 & 0.015 \\ +B11 & & & & & & & & & & & 1 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsC.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsC.tex new file mode 100644 index 0000000000..569ff26fb8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsC.tex @@ -0,0 +1,19 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & C1 & C2 & C3 & C4 & C5 & C6 & C7 & C8 & C9 & C10 \\ +\hline +B1 & 0.001 & 0.004 & 0.002 & 0.003 & 0.003 & 0.003 & 0.004 & 0.004 & 0.004 & 0.009 \\ +B2 & 0.002 & 0.007 & 0.005 & 0.007 & 0.007 & 0.006 & 0.009 & 0.009 & 0.007 & 0.018 \\ +B3 & 0.002 & 0.009 & 0.006 & 0.009 & 0.009 & 0.007 & 0.012 & 0.011 & 0.009 & 0.024 \\ +B4 & 0.003 & 0.012 & 0.008 & 0.011 & 0.011 & 0.009 & 0.014 & 0.014 & 0.012 & 0.029 \\ +B5 & 0.002 & 0.011 & 0.007 & 0.010 & 0.010 & 0.008 & 0.013 & 0.012 & 0.011 & 0.027 \\ +B6 & 0.003 & 0.015 & 0.010 & 0.014 & 0.014 & 0.011 & 0.018 & 0.017 & 0.015 & 0.038 \\ +B7 & 0.003 & 0.015 & 0.010 & 0.013 & 0.014 & 0.011 & 0.018 & 0.017 & 0.015 & 0.037 \\ +B8 & 0.004 & 0.016 & 0.011 & 0.015 & 0.015 & 0.012 & 0.020 & 0.019 & 0.016 & 0.041 \\ +B9 & 0.003 & 0.013 & 0.009 & 0.012 & 0.013 & 0.010 & 0.017 & 0.016 & 0.014 & 0.034 \\ +B10 & 0.003 & 0.013 & 0.009 & 0.012 & 0.012 & 0.010 & 0.016 & 0.015 & 0.013 & 0.033 \\ +B11 & 0.002 & 0.010 & 0.007 & 0.010 & 0.010 & 0.008 & 0.013 & 0.012 & 0.011 & 0.027 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsD.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsD.tex new file mode 100644 index 0000000000..7c29a0c7ab --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrBVsD.tex @@ -0,0 +1,19 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & D1 & D2 & D3 & D4 & D5 & D6 & D7 & D8 & D9 & D10 & D11 \\ +\hline +B1 & 0.001 & 0.002 & 0.002 & 0.002 & 0.003 & 0.003 & 0.003 & 0.003 & 0.005 & 0.002 & 0.002 \\ +B2 & 0.001 & 0.004 & 0.004 & 0.004 & 0.005 & 0.006 & 0.007 & 0.007 & 0.010 & 0.004 & 0.005 \\ +B3 & 0.001 & 0.005 & 0.006 & 0.005 & 0.007 & 0.007 & 0.009 & 0.009 & 0.013 & 0.005 & 0.006 \\ +B4 & 0.002 & 0.006 & 0.007 & 0.007 & 0.008 & 0.009 & 0.011 & 0.011 & 0.016 & 0.006 & 0.007 \\ +B5 & 0.002 & 0.005 & 0.006 & 0.006 & 0.008 & 0.008 & 0.010 & 0.010 & 0.015 & 0.005 & 0.007 \\ +B6 & 0.002 & 0.007 & 0.009 & 0.008 & 0.011 & 0.012 & 0.014 & 0.014 & 0.021 & 0.007 & 0.010 \\ +B7 & 0.002 & 0.007 & 0.009 & 0.008 & 0.010 & 0.012 & 0.014 & 0.014 & 0.020 & 0.007 & 0.009 \\ +B8 & 0.002 & 0.008 & 0.010 & 0.009 & 0.011 & 0.013 & 0.015 & 0.015 & 0.022 & 0.008 & 0.010 \\ +B9 & 0.002 & 0.007 & 0.008 & 0.008 & 0.010 & 0.011 & 0.012 & 0.013 & 0.019 & 0.007 & 0.009 \\ +B10 & 0.002 & 0.006 & 0.008 & 0.007 & 0.009 & 0.010 & 0.012 & 0.012 & 0.018 & 0.007 & 0.008 \\ +B11 & 0.002 & 0.005 & 0.006 & 0.006 & 0.008 & 0.008 & 0.010 & 0.010 & 0.015 & 0.005 & 0.007 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsC.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsC.tex new file mode 100644 index 0000000000..cd24942170 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsC.tex @@ -0,0 +1,18 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & C1 & C2 & C3 & C4 & C5 & C6 & C7 & C8 & C9 & C10 \\ +\hline +C1 & 1 & 0.004 & 0.003 & 0.004 & 0.004 & 0.003 & 0.003 & 0.003 & 0.002 & 0.006 \\ +C2 & & 1 & 0.016 & 0.018 & 0.017 & 0.012 & 0.016 & 0.013 & 0.011 & 0.024 \\ +C3 & & & 1 & 0.019 & 0.017 & 0.012 & 0.013 & 0.010 & 0.008 & 0.017 \\ +C4 & & & & 1 & 0.019 & 0.013 & 0.016 & 0.013 & 0.010 & 0.022 \\ +C5 & & & & & 1 & 0.012 & 0.015 & 0.013 & 0.010 & 0.023 \\ +C6 & & & & & & 1 & 0.012 & 0.010 & 0.008 & 0.018 \\ +C7 & & & & & & & 1 & 0.015 & 0.012 & 0.029 \\ +C8 & & & & & & & & 1 & 0.011 & 0.027 \\ +C9 & & & & & & & & & 1 & 0.023 \\ +C10 & & & & & & & & & & 1 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsD.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsD.tex new file mode 100644 index 0000000000..a6931b51d8 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrCVsD.tex @@ -0,0 +1,18 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & D1 & D2 & D3 & D4 & D5 & D6 & D7 & D8 & D9 & D10 & D11 \\ +\hline +C1 & 0.000 & 0.001 & 0.001 & 0.001 & 0.002 & 0.002 & 0.002 & 0.002 & 0.003 & 0.001 & 0.001 \\ +C2 & 0.001 & 0.004 & 0.005 & 0.005 & 0.006 & 0.007 & 0.008 & 0.009 & 0.013 & 0.005 & 0.006 \\ +C3 & 0.001 & 0.003 & 0.004 & 0.004 & 0.004 & 0.005 & 0.006 & 0.006 & 0.009 & 0.003 & 0.004 \\ +C4 & 0.001 & 0.004 & 0.005 & 0.005 & 0.006 & 0.007 & 0.008 & 0.008 & 0.011 & 0.004 & 0.005 \\ +C5 & 0.001 & 0.004 & 0.005 & 0.005 & 0.006 & 0.007 & 0.008 & 0.008 & 0.012 & 0.004 & 0.005 \\ +C6 & 0.001 & 0.003 & 0.004 & 0.004 & 0.005 & 0.006 & 0.006 & 0.007 & 0.010 & 0.004 & 0.004 \\ +C7 & 0.002 & 0.006 & 0.007 & 0.006 & 0.008 & 0.009 & 0.010 & 0.011 & 0.016 & 0.006 & 0.007 \\ +C8 & 0.002 & 0.005 & 0.006 & 0.006 & 0.008 & 0.008 & 0.010 & 0.010 & 0.015 & 0.005 & 0.007 \\ +C9 & 0.001 & 0.005 & 0.006 & 0.005 & 0.007 & 0.007 & 0.008 & 0.009 & 0.013 & 0.005 & 0.006 \\ +C10 & 0.003 & 0.011 & 0.014 & 0.013 & 0.016 & 0.018 & 0.021 & 0.022 & 0.032 & 0.012 & 0.015 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrDVsD.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrDVsD.tex new file mode 100644 index 0000000000..239b258913 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrDVsD.tex @@ -0,0 +1,19 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & D1 & D2 & D3 & D4 & D5 & D6 & D7 & D8 & D9 & D10 & D11 \\ +\hline +D1 & 1 & 0.004 & 0.012 & 0.007 & 0.007 & 0.005 & 0.005 & 0.003 & 0.003 & 0.001 & 0.001 \\ +D2 & & 1 & 0.009 & 0.006 & 0.007 & 0.006 & 0.006 & 0.005 & 0.007 & 0.003 & 0.003 \\ +D3 & & & 1 & 0.014 & 0.015 & 0.012 & 0.011 & 0.008 & 0.010 & 0.004 & 0.004 \\ +D4 & & & & 1 & 0.010 & 0.008 & 0.008 & 0.007 & 0.008 & 0.003 & 0.004 \\ +D5 & & & & & 1 & 0.010 & 0.010 & 0.008 & 0.010 & 0.004 & 0.004 \\ +D6 & & & & & & 1 & 0.009 & 0.008 & 0.011 & 0.004 & 0.005 \\ +D7 & & & & & & & 1 & 0.009 & 0.012 & 0.005 & 0.006 \\ +D8 & & & & & & & & 1 & 0.012 & 0.005 & 0.006 \\ +D9 & & & & & & & & & 1 & 0.007 & 0.008 \\ +D10 & & & & & & & & & & 1 & 0.003 \\ +D11 & & & & & & & & & & & 1 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsA.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsA.tex new file mode 100644 index 0000000000..05ea6a40f9 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsA.tex @@ -0,0 +1,22 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & A1 & A2 & A3 & A4 & A5 & A6 & A7 & A8 & A9 & A10 \\ +\hline +I1 & 0.020 & 0.011 & 0.009 & 0.007 & 0.007 & 0.009 & 0.010 & 0.009 & 0.011 & 0.017 \\ +I2 & 0.027 & 0.025 & 0.023 & 0.018 & 0.018 & 0.023 & 0.027 & 0.023 & 0.029 & 0.044 \\ +I3 & 0.066 & 0.054 & 0.029 & 0.013 & 0.006 & 0.006 & 0.007 & 0.006 & 0.008 & 0.012 \\ +I4 & 0.033 & 0.062 & 0.056 & 0.025 & 0.009 & 0.006 & 0.006 & 0.006 & 0.007 & 0.010 \\ +I5 & 0.006 & 0.053 & 0.064 & 0.053 & 0.020 & 0.010 & 0.007 & 0.006 & 0.007 & 0.011 \\ +I6 & 0.002 & 0.023 & 0.058 & 0.064 & 0.042 & 0.018 & 0.008 & 0.005 & 0.007 & 0.010 \\ +I7 & 0.002 & 0.005 & 0.047 & 0.072 & 0.078 & 0.059 & 0.024 & 0.009 & 0.008 & 0.012 \\ +I8 & 0.003 & 0.005 & 0.026 & 0.059 & 0.073 & 0.096 & 0.059 & 0.023 & 0.014 & 0.019 \\ +I9 & 0.002 & 0.003 & 0.008 & 0.034 & 0.052 & 0.081 & 0.103 & 0.052 & 0.018 & 0.012 \\ +I10 & 0.002 & 0.003 & 0.005 & 0.016 & 0.031 & 0.056 & 0.086 & 0.116 & 0.048 & 0.021 \\ +I11 & 0.002 & 0.003 & 0.005 & 0.007 & 0.015 & 0.031 & 0.057 & 0.093 & 0.124 & 0.047 \\ +I12 & 0.001 & 0.002 & 0.003 & 0.003 & 0.005 & 0.012 & 0.026 & 0.057 & 0.096 & 0.131 \\ +I13 & 0.002 & 0.003 & 0.005 & 0.004 & 0.005 & 0.008 & 0.014 & 0.029 & 0.063 & 0.116 \\ +I14 & 0.001 & 0.002 & 0.003 & 0.003 & 0.003 & 0.004 & 0.006 & 0.011 & 0.026 & 0.064 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsB.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsB.tex new file mode 100644 index 0000000000..73afd6f419 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsB.tex @@ -0,0 +1,22 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & B1 & B2 & B3 & B4 & B5 & B6 & B7 & B8 & B9 & B10 & B11 \\ +\hline +I1 & 0.028 & 0.020 & 0.013 & 0.012 & 0.011 & 0.015 & 0.015 & 0.016 & 0.013 & 0.013 & 0.010 \\ +I2 & 0.033 & 0.043 & 0.035 & 0.032 & 0.028 & 0.038 & 0.038 & 0.041 & 0.034 & 0.034 & 0.027 \\ +I3 & 0.086 & 0.085 & 0.051 & 0.024 & 0.011 & 0.011 & 0.010 & 0.011 & 0.009 & 0.009 & 0.007 \\ +I4 & 0.032 & 0.090 & 0.087 & 0.046 & 0.018 & 0.012 & 0.009 & 0.010 & 0.008 & 0.008 & 0.006 \\ +I5 & 0.005 & 0.063 & 0.094 & 0.089 & 0.037 & 0.019 & 0.011 & 0.011 & 0.009 & 0.009 & 0.007 \\ +I6 & 0.002 & 0.022 & 0.082 & 0.094 & 0.078 & 0.035 & 0.014 & 0.010 & 0.008 & 0.008 & 0.006 \\ +I7 & 0.003 & 0.006 & 0.055 & 0.101 & 0.109 & 0.103 & 0.043 & 0.019 & 0.010 & 0.010 & 0.008 \\ +I8 & 0.004 & 0.008 & 0.027 & 0.080 & 0.103 & 0.138 & 0.105 & 0.047 & 0.020 & 0.015 & 0.012 \\ +I9 & 0.002 & 0.005 & 0.008 & 0.043 & 0.071 & 0.114 & 0.147 & 0.101 & 0.033 & 0.012 & 0.007 \\ +I10 & 0.003 & 0.006 & 0.007 & 0.020 & 0.041 & 0.078 & 0.119 & 0.171 & 0.094 & 0.031 & 0.010 \\ +I11 & 0.003 & 0.005 & 0.007 & 0.010 & 0.020 & 0.043 & 0.077 & 0.131 & 0.185 & 0.089 & 0.023 \\ +I12 & 0.001 & 0.003 & 0.003 & 0.004 & 0.006 & 0.017 & 0.035 & 0.076 & 0.134 & 0.200 & 0.072 \\ +I13 & 0.002 & 0.005 & 0.006 & 0.008 & 0.007 & 0.012 & 0.019 & 0.040 & 0.081 & 0.156 & 0.208 \\ +I14 & 0.002 & 0.003 & 0.004 & 0.005 & 0.005 & 0.006 & 0.008 & 0.016 & 0.035 & 0.086 & 0.179 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsC.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsC.tex new file mode 100644 index 0000000000..743124a965 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsC.tex @@ -0,0 +1,22 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & C1 & C2 & C3 & C4 & C5 & C6 & C7 & C8 & C9 & C10 \\ +\hline +I1 & 0.016 & 0.014 & 0.008 & 0.008 & 0.008 & 0.007 & 0.011 & 0.011 & 0.009 & 0.023 \\ +I2 & 0.021 & 0.034 & 0.020 & 0.022 & 0.022 & 0.018 & 0.029 & 0.027 & 0.023 & 0.059 \\ +I3 & 0.051 & 0.045 & 0.024 & 0.012 & 0.007 & 0.005 & 0.008 & 0.007 & 0.006 & 0.016 \\ +I4 & 0.026 & 0.052 & 0.044 & 0.022 & 0.009 & 0.005 & 0.007 & 0.007 & 0.006 & 0.014 \\ +I5 & 0.004 & 0.046 & 0.052 & 0.045 & 0.018 & 0.008 & 0.008 & 0.007 & 0.006 & 0.015 \\ +I6 & 0.001 & 0.021 & 0.047 & 0.055 & 0.038 & 0.015 & 0.008 & 0.006 & 0.005 & 0.013 \\ +I7 & 0.002 & 0.008 & 0.036 & 0.057 & 0.062 & 0.046 & 0.021 & 0.010 & 0.007 & 0.017 \\ +I8 & 0.002 & 0.010 & 0.020 & 0.048 & 0.060 & 0.077 & 0.051 & 0.023 & 0.012 & 0.025 \\ +I9 & 0.001 & 0.006 & 0.006 & 0.028 & 0.044 & 0.065 & 0.086 & 0.045 & 0.015 & 0.016 \\ +I10 & 0.002 & 0.007 & 0.005 & 0.015 & 0.027 & 0.046 & 0.073 & 0.096 & 0.041 & 0.025 \\ +I11 & 0.002 & 0.006 & 0.004 & 0.007 & 0.015 & 0.025 & 0.049 & 0.080 & 0.102 & 0.047 \\ +I12 & 0.001 & 0.003 & 0.002 & 0.003 & 0.005 & 0.010 & 0.024 & 0.051 & 0.083 & 0.112 \\ +I13 & 0.001 & 0.006 & 0.004 & 0.005 & 0.006 & 0.006 & 0.014 & 0.027 & 0.055 & 0.108 \\ +I14 & 0.001 & 0.004 & 0.003 & 0.004 & 0.004 & 0.003 & 0.006 & 0.012 & 0.024 & 0.064 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsD.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsD.tex new file mode 100644 index 0000000000..963dc3f77f --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsD.tex @@ -0,0 +1,22 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & D1 & D2 & D3 & D4 & D5 & D6 & D7 & D8 & D9 & D10 & D11 \\ +\hline +I1 & 0.011 & 0.018 & 0.011 & 0.006 & 0.007 & 0.007 & 0.008 & 0.009 & 0.012 & 0.005 & 0.006 \\ +I2 & 0.011 & 0.029 & 0.026 & 0.017 & 0.017 & 0.019 & 0.022 & 0.022 & 0.032 & 0.012 & 0.015 \\ +I3 & 0.030 & 0.060 & 0.047 & 0.023 & 0.010 & 0.006 & 0.006 & 0.006 & 0.009 & 0.003 & 0.004 \\ +I4 & 0.004 & 0.042 & 0.061 & 0.043 & 0.019 & 0.009 & 0.006 & 0.005 & 0.008 & 0.003 & 0.004 \\ +I5 & 0.001 & 0.016 & 0.056 & 0.061 & 0.038 & 0.018 & 0.008 & 0.006 & 0.008 & 0.003 & 0.004 \\ +I6 & 0.001 & 0.004 & 0.034 & 0.057 & 0.057 & 0.037 & 0.014 & 0.006 & 0.007 & 0.003 & 0.003 \\ +I7 & 0.001 & 0.003 & 0.015 & 0.054 & 0.065 & 0.076 & 0.045 & 0.018 & 0.011 & 0.004 & 0.004 \\ +I8 & 0.001 & 0.005 & 0.008 & 0.034 & 0.056 & 0.078 & 0.085 & 0.047 & 0.023 & 0.006 & 0.007 \\ +I9 & 0.001 & 0.003 & 0.004 & 0.013 & 0.035 & 0.059 & 0.080 & 0.089 & 0.042 & 0.011 & 0.005 \\ +I10 & 0.001 & 0.003 & 0.004 & 0.005 & 0.018 & 0.036 & 0.060 & 0.091 & 0.096 & 0.036 & 0.010 \\ +I11 & 0.001 & 0.003 & 0.004 & 0.004 & 0.008 & 0.019 & 0.035 & 0.064 & 0.101 & 0.098 & 0.030 \\ +I12 & 0.000 & 0.002 & 0.002 & 0.002 & 0.003 & 0.006 & 0.015 & 0.032 & 0.064 & 0.109 & 0.094 \\ +I13 & 0.001 & 0.003 & 0.004 & 0.003 & 0.004 & 0.005 & 0.009 & 0.016 & 0.036 & 0.068 & 0.127 \\ +I14 & 0.001 & 0.002 & 0.002 & 0.002 & 0.003 & 0.003 & 0.004 & 0.006 & 0.016 & 0.033 & 0.076 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsI.tex b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsI.tex new file mode 100644 index 0000000000..99e5900359 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/rawdata/corrIVsI.tex @@ -0,0 +1,22 @@ +\begin{tabular}{c@{~~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c@{~~}c} +\hline + \hline +Bin & I1 & I2 & I3 & I4 & I5 & I6 & I7 & I8 & I9 & I10 & I11 & I12 & I13 & I14 \\ +\hline +I1 & 1 & 0.065 & 0.057 & 0.044 & 0.036 & 0.026 & 0.024 & 0.024 & 0.016 & 0.013 & 0.011 & 0.006 & 0.007 & 0.005 \\ +I2 & & 1 & 0.056 & 0.045 & 0.039 & 0.030 & 0.031 & 0.036 & 0.023 & 0.023 & 0.020 & 0.010 & 0.016 & 0.011 \\ +I3 & & & 1 & 0.046 & 0.039 & 0.030 & 0.027 & 0.024 & 0.016 & 0.013 & 0.009 & 0.005 & 0.006 & 0.004 \\ +I4 & & & & 1 & 0.035 & 0.028 & 0.025 & 0.022 & 0.014 & 0.011 & 0.008 & 0.005 & 0.005 & 0.003 \\ +I5 & & & & & 1 & 0.029 & 0.026 & 0.023 & 0.015 & 0.012 & 0.009 & 0.005 & 0.005 & 0.003 \\ +I6 & & & & & & 1 & 0.025 & 0.023 & 0.016 & 0.012 & 0.009 & 0.005 & 0.005 & 0.003 \\ +I7 & & & & & & & 1 & 0.028 & 0.022 & 0.019 & 0.014 & 0.008 & 0.008 & 0.005 \\ +I8 & & & & & & & & 1 & 0.029 & 0.027 & 0.022 & 0.014 & 0.012 & 0.008 \\ +I9 & & & & & & & & & 1 & 0.030 & 0.026 & 0.018 & 0.014 & 0.008 \\ +I10 & & & & & & & & & & 1 & 0.035 & 0.028 & 0.022 & 0.013 \\ +I11 & & & & & & & & & & & 1 & 0.037 & 0.031 & 0.020 \\ +I12 & & & & & & & & & & & & 1 & 0.041 & 0.030 \\ +I13 & & & & & & & & & & & & & 1 & 0.044 \\ +I14 & & & & & & & & & & & & & & 1 \\ +\hline + \hline +\end{tabular} \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..c882bbfc92 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml @@ -0,0 +1,1046 @@ +definitions: + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2012LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2012POL + sys_0: + description: 0 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc0 + sys_1: + description: 1 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc1 + sys_2: + description: 2 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc2 + sys_3: + description: 3 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc3 + sys_4: + description: 4 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc4 + sys_5: + description: 5 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc5 + sys_6: + description: 6 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc6 + sys_7: + description: 7 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc7 + sys_8: + description: 8 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc8 + sys_9: + description: 9 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc9 + sys_10: + description: 10 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc10 + sys_11: + description: 11 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc11 + sys_12: + description: 12 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc12 + sys_13: + description: 13 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc13 + sys_14: + description: 14 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc14 + sys_15: + description: 15 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc15 + sys_16: + description: 16 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc16 + sys_17: + description: 17 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc17 + sys_18: + description: 18 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc18 + sys_19: + description: 19 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc19 + sys_20: + description: 20 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc20 + sys_21: + description: 21 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc21 + sys_22: + description: 22 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc22 + sys_23: + description: 23 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc23 + sys_24: + description: 24 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc24 + sys_25: + description: 25 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc25 + sys_26: + description: 26 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc26 + sys_27: + description: 27 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc27 + sys_28: + description: 28 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc28 + sys_29: + description: 29 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc29 + sys_30: + description: 30 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc30 + sys_31: + description: 31 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc31 + sys_32: + description: 32 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc32 + sys_33: + description: 33 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc33 + sys_34: + description: 34 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc34 + sys_35: + description: 35 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc35 + sys_36: + description: 36 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc36 + sys_37: + description: 37 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc37 + sys_38: + description: 38 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc38 + sys_39: + description: 39 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc39 + sys_40: + description: 40 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc40 + sys_41: + description: 41 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc41 + sys_42: + description: 42 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc42 + sys_43: + description: 43 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc43 + sys_44: + description: 44 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc44 + sys_45: + description: 45 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2013JETunc45 + sys_46: + description: 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sys_34: -3.8530515659520536e-08 + sys_35: 1.0728441568670239e-07 + sys_36: 6.214679324429229e-09 + sys_37: -6.986221501753868e-08 + sys_38: 9.861791738248979e-10 + sys_39: -7.280487478451985e-08 + sys_40: -8.024537666939139e-08 + sys_41: -8.933921828313462e-09 + sys_42: -1.0330244421961704e-08 + sys_43: 3.861452855463656e-09 + sys_44: -3.6083948296348184e-09 + sys_45: 2.463817977126938e-09 + sys_46: 4.674049774422517e-10 + sys_47: -3.723128004171262e-08 + sys_48: -1.0158152894581887e-08 + sys_49: 1.5376116888983531e-09 + sys_50: -6.752114402721217e-09 + sys_51: 1.282874579934122e-09 + sys_52: 3.873154541500846e-10 + sys_53: 1.1239378569623433e-09 + sys_54: 1.3794245316759332e-09 + sys_55: 1.2540320616809989e-09 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/data.yaml new file mode 100644 index 0000000000..96f7365a39 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/data.yaml @@ -0,0 +1,11 @@ +data_central: +- -0.0128 +- 0.009 +- 0.0079 +- -0.0012 +- 0.0101 +- -0.0013 +- 0.0048 +- 0.0052 +- 0.0363 +- -0.0218 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/kinematics.yaml new file mode 100644 index 0000000000..aa74b03509 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/kinematics.yaml @@ -0,0 +1,81 @@ +bins: +- m_jj: + max: 19.86 + mid: 19.04 + min: 18.22 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 22.58 + mid: 21.62 + min: 20.66 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 27.46 + mid: 26.380000000000003 + min: 25.3 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 33.46 + mid: 32.3 + min: 31.14 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 39.62 + mid: 38.42 + min: 37.22 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 46.66 + mid: 45.18 + min: 43.7 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 54.97 + mid: 53.42 + min: 51.87 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 65.32 + mid: 63.52 + min: 61.72 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 77.76 + mid: 75.55000000000001 + min: 73.34 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 91.5 + mid: 89.12 + min: 86.74 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml new file mode 100644 index 0000000000..636cc9c53b --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml @@ -0,0 +1,41 @@ +setname: "STAR_2012_2JET_A_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1738738" +hepdata: + url: "https://www.hepdata.net/record/ins1738738" + version: 1 +arXiv: + url: https://arxiv.org/abs/1906.02740 + +version: 1 +version_comment: "Initial implementation, correlations from arXiv" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 10 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology A" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JJET_A_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..f64d5a79c9 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml @@ -0,0 +1,828 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2012LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2012POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc47 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc48 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc49 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc50 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc51 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc52 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc53 + sys_54: + description: 54 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc54 + 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null + mid: 510.0 + min: null +- m_jj: + max: 22.74 + mid: 21.8 + min: 20.86 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 27.46 + mid: 26.37 + min: 25.28 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 33.31 + mid: 32.24 + min: 31.17 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 39.73 + mid: 38.42 + min: 37.11 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 47.24 + mid: 45.83 + min: 44.42 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 55.83 + mid: 54.14 + min: 52.45 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 66.0 + mid: 64.17 + min: 62.34 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 78.19 + mid: 76.06 + min: 73.93 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 92.29 + mid: 89.81 + min: 87.33 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 110.81 + mid: 107.92 + min: 105.03 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml new file mode 100644 index 0000000000..6e31c91b59 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml @@ -0,0 +1,41 @@ +setname: "STAR_2012_2JET_B_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1738738" +hepdata: + url: "https://www.hepdata.net/record/ins1738738" + version: 1 +arXiv: + url: https://arxiv.org/abs/1906.02740 + +version: 1 +version_comment: "Initial implementation, correlations from arXiv" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 11 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology B" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JJET_B_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..a33894ad64 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml @@ -0,0 +1,887 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2012LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2012POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc47 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc48 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc49 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc50 + 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1.262359229870813e-07 + sys_43: -6.081353258315695e-08 + sys_44: 1.0560829220358257e-07 + sys_45: -2.450655837451025e-08 + sys_46: 2.487057404799191e-08 + sys_47: 4.941399429648063e-07 + sys_48: 1.0336475711600947e-07 + sys_49: -2.7651578798549535e-08 + sys_50: 1.0636285008630778e-07 + sys_51: -1.1285352348201996e-08 + sys_52: 1.494306642883637e-08 + sys_53: -2.967856390762434e-09 + sys_54: -1.6641019042708856e-08 + sys_55: -3.3283838979182453e-09 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/data.yaml new file mode 100644 index 0000000000..9fe7a0dfa4 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/data.yaml @@ -0,0 +1,11 @@ +data_central: +- 0.0058 +- -0.0006 +- -0.0043 +- 0.0049 +- 0.0046 +- 0.0155 +- -0.0045 +- 0.0104 +- 0.0346 +- 0.0593 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/kinematics.yaml new file mode 100644 index 0000000000..3249f1848e --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/kinematics.yaml @@ -0,0 +1,81 @@ +bins: +- m_jj: + max: 20.62 + mid: 19.81 + min: 19.0 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 23.13 + mid: 22.01 + min: 20.89 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 27.24 + mid: 26.16 + min: 25.08 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 33.89 + mid: 32.7 + min: 31.51 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 40.05 + mid: 38.71 + min: 37.37 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 47.37 + mid: 46.01 + min: 44.65 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 55.67 + mid: 53.89 + min: 52.11 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 66.49 + mid: 64.75 + min: 63.01 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 79.42 + mid: 77.15 + min: 74.88 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 93.72 + mid: 91.14 + min: 88.56 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml new file mode 100644 index 0000000000..5a33d1227c --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml @@ -0,0 +1,41 @@ +setname: "STAR_2012_2JET_C_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1738738" +hepdata: + url: "https://www.hepdata.net/record/ins1738738" + version: 1 +arXiv: + url: https://arxiv.org/abs/1906.02740 + +version: 1 +version_comment: "Initial implementation, correlations from arXiv" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 10 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology C" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JJET_C_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..16fe89f45b --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml @@ -0,0 +1,828 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2012LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2012POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc47 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc48 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc49 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc50 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc51 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc52 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc53 + sys_54: + description: 54 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc54 + sys_55: + description: 55 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc55 +bins: +- stat: 0.0085 + lumi_ue: 0.00026 + pol: 0.0003828 + sys_0: -2.5482830979737217e-07 + sys_1: -5.769850292115005e-07 + sys_2: -1.1005432363669914e-06 + sys_3: -2.1294360101953275e-07 + sys_4: -7.07382830391889e-07 + sys_5: 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/data.yaml @@ -0,0 +1,12 @@ +data_central: +- 0.0054 +- 0.0042 +- 0.0051 +- -0.0031 +- -0.0018 +- -0.004 +- 0.0034 +- 0.005 +- 0.0058 +- 0.0291 +- -0.0055 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/kinematics.yaml new file mode 100644 index 0000000000..abb28d91f6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/kinematics.yaml @@ -0,0 +1,89 @@ +bins: +- m_jj: + max: 22.68 + mid: 20.54 + min: 18.4 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 23.04 + mid: 22.09 + min: 21.14 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 27.29 + mid: 26.31 + min: 25.33 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 32.94 + mid: 31.72 + min: 30.5 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 39.79 + mid: 38.48 + min: 37.17 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 46.76 + mid: 45.21 + min: 43.66 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 55.84 + mid: 54.150000000000006 + min: 52.46 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 66.22 + mid: 64.3 + min: 62.38 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 78.81 + mid: 76.66 + min: 74.51 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 92.19 + mid: 89.57 + min: 86.95 + sqrts: + max: null + mid: 510.0 + min: null +- m_jj: + max: 109.83 + mid: 106.86 + min: 103.89 + sqrts: + max: null + mid: 510.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml new file mode 100644 index 0000000000..2234430df2 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml @@ -0,0 +1,41 @@ +setname: "STAR_2012_2JET_D_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +iNSPIRE: + url: "https://inspirehep.net/literature/1738738" +hepdata: + url: "https://www.hepdata.net/record/ins1738738" + version: 1 +arXiv: + url: https://arxiv.org/abs/1906.02740 + +version: 1 +version_comment: "Initial implementation, correlations from arXiv" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 11 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology D" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JJET_D_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml new file mode 100644 index 0000000000..38e92da673 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml @@ -0,0 +1,887 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2012LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2012POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2013JETunc36 + sys_37: + description: 37 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sys_53: -4.714010101544476e-09 + sys_54: -9.521018682603238e-09 + sys_55: -7.908290426262239e-09 From 875eede6899e0ab2eb0ec6d2d9a6d4fa5e3c976e Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Wed, 24 Apr 2024 16:30:32 +0200 Subject: [PATCH 20/98] small correction in metadata --- .../new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml | 4 ++-- .../new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml | 4 ++-- .../new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml | 4 ++-- 3 files changed, 6 insertions(+), 6 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml index 58d18669e4..75ab1997b3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml @@ -22,8 +22,8 @@ implemented_observables: } observable_name: ALL process_type: DIJET_POL - ndata: 12 - tables: [5] + ndata: 5 + tables: [9] kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml index 461ccf9857..93d593d014 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml @@ -22,8 +22,8 @@ implemented_observables: } observable_name: ALL process_type: DIJET_POL - ndata: 12 - tables: [5] + ndata: 7 + tables: [9] kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml index 6e966a7071..675cf5256d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml @@ -22,8 +22,8 @@ implemented_observables: } observable_name: ALL process_type: DIJET_POL - ndata: 12 - tables: [5] + ndata: 7 + tables: [9] kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } From dfa92ba5234a6ab3bb34ce6c24cdd6cc29af3c69 Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Mon, 29 Apr 2024 10:41:01 +0200 Subject: [PATCH 21/98] full implementation of STAR_2009 including correlations --- .../star/jet_dijet_2009_200gev.py | 319 +++ .../STAR_2009_1JET_200GEV/filter.py | 136 -- .../STAR_2009_1JET_200GEV/kinematics.yaml | 354 +-- .../rawdata/correlation.csv | 56 + .../STAR_2009_1JET_200GEV/uncertainties.yaml | 1966 ++++++++++++----- .../STAR_2009_2JET_A_200GEV/filter.py | 85 - .../STAR_2009_2JET_A_200GEV/kinematics.yaml | 40 +- .../STAR_2009_2JET_A_200GEV/metadata.yaml | 4 +- .../{Figure9_Bottom.yaml => Table.yaml} | 0 .../uncertainties.yaml | 520 ++++- .../STAR_2009_2JET_B_200GEV/filter.py | 85 - .../STAR_2009_2JET_B_200GEV/kinematics.yaml | 56 +- .../STAR_2009_2JET_B_200GEV/metadata.yaml | 4 +- .../rawdata/Figure9_Top.yaml | 44 - .../rawdata/Table.yaml | 47 + .../uncertainties.yaml | 636 +++++- .../STAR_2009_2JET_C_200GEV/filter.py | 85 - .../STAR_2009_2JET_C_200GEV/kinematics.yaml | 56 +- .../STAR_2009_2JET_C_200GEV/metadata.yaml | 4 +- .../rawdata/{Figure9_Mid.yaml => Table.yaml} | 0 .../uncertainties.yaml | 636 +++++- .../STAR_2009_2JET_OS_200GEV/data.yaml | 8 + .../STAR_2009_2JET_OS_200GEV/kinematics.yaml | 57 + .../STAR_2009_2JET_OS_200GEV/metadata.yaml | 49 + .../rawdata/Table.yaml | 81 + .../uncertainties.yaml | 640 ++++++ .../STAR_2009_2JET_SS_200GEV/data.yaml | 8 + .../STAR_2009_2JET_SS_200GEV/kinematics.yaml | 57 + .../STAR_2009_2JET_SS_200GEV/metadata.yaml | 49 + .../rawdata/Table.yaml | 81 + .../uncertainties.yaml | 640 ++++++ .../STAR_2012_1JET_510GEV/metadata.yaml | 11 +- 32 files changed, 5561 insertions(+), 1253 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/correlation.csv delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py rename nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/{Figure9_Bottom.yaml => Table.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Table.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py rename nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/{Figure9_Mid.yaml => Table.yaml} (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/rawdata/Table.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/rawdata/Table.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py new file mode 100644 index 0000000000..8b98c15ca7 --- /dev/null +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -0,0 +1,319 @@ +"""This script provides the common filer to the jet and dijet STAR 2012 datasets. +Files need to be parsed all together as there are correlations provided. +""" + +import pathlib + +import numpy as np +import pandas as pd +import yaml + +from nnpdf_data.filter_utils.correlations import compute_covmat + +TOPOPLOGY_LIST = ["I", "SS", "OS", "A", "B", "C"] +POL_UNC = 0.065 +LUMI_UNC = 0.0005 +HERE = pathlib.Path(__file__).parents[2] + + +def read_1jet_data(): + df3 = pd.DataFrame() + df4 = pd.DataFrame() + + fnames = [ + "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_ALL.csv", + "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_pT.csv", + "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_ALL.csv", + "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_pT.csv", + "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_5.csv", + ] + + for fname in fnames: + if "3" in fname: + dfi = pd.read_csv(fname) + if "pT" in fname: + df3["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] + + elif "ALL" in fname: + df3["ALL"] = dfi["$A_{LL}$"] + df3["stat_min"] = dfi["stat +"] + df3["stat_max"] = dfi["stat -"] + df3["sys_min"] = dfi["sys +"] + df3["sys_max"] = dfi["sys -"] + + df3["abs_eta_min"] = 0.0 + df3["abs_eta_max"] = 0.5 + df3["abs_eta"] = (df3["abs_eta_min"] + df3["abs_eta_max"]) / 2 + df3["sqrts"] = 200 + + elif "4" in fname: + dfi = pd.read_csv(fname) + if "pT" in fname: + df4["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] + + if "ALL" in fname: + df4["ALL"] = dfi["$A_{LL}$"] + df4["stat_min"] = dfi["stat +"] + df4["stat_max"] = dfi["stat -"] + df4["sys_min"] = dfi["sys +"] + df4["sys_max"] = dfi["sys -"] + + df4["abs_eta_min"] = 0.5 + df4["abs_eta_max"] = 1.0 + df4["sqrts"] = 200 + + elif "5" in fname: + dfc_col = pd.read_csv(fname) + + dfc = pd.DataFrame() + biny = 1 + for i in range(len(dfc_col)): + if dfc_col.loc[i, "binx"] == "-": + biny = float(dfc_col.loc[i, "val"]) + else: + binx = float(dfc_col.loc[i, "binx"]) + dfc.loc[binx, biny] = dfc_col.loc[i, "val"] + + dfc = dfc.astype("float") + + else: + print("ERROR: Unknown table number detected! Check input files.") + + df = pd.concat([df3, df4], ignore_index=True) + df["pol"] = POL_UNC * df["ALL"] + df["lumi_ue"] = LUMI_UNC + + for i in range(len(df)): + df.loc[i, "stat"] = df.loc[i, "stat_max"] + df.loc[i, "sys"] = df.loc[i, "sys_max"] + return df, dfc + + +def read_2jet_data(topology): + fname = f"../../new_commondata/STAR_2009_2JET_{topology}_200GEV/rawdata/Table.yaml" + df = pd.DataFrame() + with open(fname, "r") as file: + data = yaml.safe_load(file) + + if topology in ["A", "B", "C"]: + Msub = data["independent_variables"][0]["values"] + Gsub = data["dependent_variables"][0]["values"] + + for i in range(len(Msub)): + + df = pd.concat( + [ + df, + pd.DataFrame( + { + "m_low": [Msub[i]["low"]], + "m_high": [Msub[i]["high"]], + "ALL": [Gsub[i]["value"]], + "stat": [Gsub[i]["errors"][0]["symerror"]], + "sys": [Gsub[i]["errors"][1]["symerror"]], + "pol": [POL_UNC * Gsub[i]["value"]], + "lumi_ue": [LUMI_UNC], + } + ), + ], + ignore_index=True, + ) + + df["m"] = (df["m_low"] + df["m_high"]) / 2 + df["sqrts"] = 200 + + else: + Msub = data["dependent_variables"][0]["values"] + Gsub = data["dependent_variables"][1]["values"] + + for i in range(len(Msub)): + + df = pd.concat( + [ + df, + pd.DataFrame( + { + "m": [Msub[i]["value"]], + "ALL": [Gsub[i]["value"]], + "stat": [Gsub[i]["errors"][0]["symerror"]], + "sys": [Gsub[i]["errors"][1]["symerror"]], + "pol": [POL_UNC * Gsub[i]["value"]], + "lumi_ue": [LUMI_UNC], + } + ), + ], + ignore_index=True, + ) + df["sqrts"] = 200 + + return df + + +def write_1jet_data(df, art_sys): + STORE_PATH = "../../new_commondata/STAR_2009_1JET_200GEV/" + + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH + "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + kin_value = { + "pT": {"min": None, "mid": float(df.loc[i, "pT"]), "max": None}, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": { + "min": float(df.loc[i, "abs_eta_min"]), + "mid": float(df.loc[i, "abs_eta"]), + "max": float(df.loc[i, "abs_eta_max"]), + }, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH + "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + error_definition = { + "lumi_ue": { + "description": "underlying event and relative luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR2009LUMI", + }, + "pol": { + "description": "polarization uncertainty", + "treatment": "MULT", + "type": f"STAR2009POL", + }, + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = {"lumi_ue": float(df.loc[i, "lumi_ue"]), "pol": float(df.loc[i, "pol"])} + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + error.append(e) + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated statistical + systematics uncertainty", + "treatment": "ADD", + "type": f"STAR2009JETunc{j}", + } + for j in range(len(sys_i)) + } + ) + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH + "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +def write_2jet_data(df, topology, art_sys): + STORE_PATH = f"../../new_commondata/STAR_2009_2JET_{topology}_200GEV/" + # Write central data + data_central_yaml = {"data_central": list(df["ALL"])} + with open(STORE_PATH + "data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file) + + # Write kin file + kin = [] + for i in range(len(df)): + try: + kin_value = { + "m_jj": { + "min": float(df.loc[i, "m_low"]), + "mid": float(df.loc[i, "m"]), + "max": float(df.loc[i, "m_high"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + } + except: + kin_value = { + "m_jj": {"min": None, "mid": float(df.loc[i, "m"]), "max": None}, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + } + kin.append(kin_value) + kinematics_yaml = {"bins": kin} + with open(STORE_PATH + "kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file) + + # Write unc file + error = [] + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "lumi_ue": { + "description": "underlying event and relative luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR2009LUMIUE", + }, + "pol": { + "description": "polarization uncertainty", + "treatment": "MULT", + "type": f"STAR2009POL", + }, + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = { + "stat": float(df.loc[i, "stat"]), + "lumi_ue": float(df.loc[i, "lumi_ue"]), + "pol": float(df.loc[i, "pol"]), + } + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + error.append(e) + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": f"STAR2009JETunc{j}", + } + for j in range(len(sys_i)) + } + ) + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + with open(STORE_PATH + "uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + # load all the data + df, dfc = read_1jet_data() + dfs = {"I": df} + for topo in TOPOPLOGY_LIST[1:]: + dfs[topo] = read_2jet_data(topo) + + # load correlations + ndata_dict = {a: len(b) for a, b in dfs.items()} + correlation_df = pd.read_csv( + "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/correlation.csv", index_col=0 + ) + # from the paper we understand that stat dijet is not correlated + # I-I (stat + sys) | I-D (stat + sys) + # D-I (stat + sys) | D-D (sys) + correlated_unc = np.sqrt(dfs["I"]["sys"] ** 2 + dfs["I"]["stat"] ** 2).values.tolist() + for a in TOPOPLOGY_LIST[1:]: + correlated_unc.extend(dfs[a]["sys"].values) + ndata_points = np.sum((*ndata_dict.values(),)) + # decompose uncertainties + art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) + + # write data + cnt = 0 + for topo, df in dfs.items(): + ndata = ndata_dict[topo] + syst = art_sys[cnt : cnt + ndata, :].tolist() + if topo == "I": + write_1jet_data(df, syst) + else: + write_2jet_data(df, topo, syst) + cnt += ndata diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py deleted file mode 100644 index 98c4fc95ff..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py +++ /dev/null @@ -1,136 +0,0 @@ -import glob - -import pandas as pd -import yaml -import sys - -sys.path.append('../../') -from filter_utils.correlations import compute_covmat - - -def read_data(fnames): - df3 = pd.DataFrame() - df4 = pd.DataFrame() - for fname in fnames: - if "3" in fname: - dfi = pd.read_csv(fname) - if "pT" in fname: - correlation = False - df3["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] - - elif "ALL" in fname: - df3["ALL"] = dfi["$A_{LL}$"] - df3["stat_min"] = dfi["stat +"] - df3["stat_max"] = dfi["stat -"] - df3["sys_min"] = dfi["sys +"] - df3["sys_max"] = dfi["sys -"] - - df3["abs_eta_min"] = 0.0 - df3["abs_eta_max"] = 0.5 - df3["sqrts"] = 200 - - elif "4" in fname: - dfi = pd.read_csv(fname) - if "pT" in fname: - correlation = False - df4["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] - - if "ALL" in fname: - df4["ALL"] = dfi["$A_{LL}$"] - df4["stat_min"] = dfi["stat +"] - df4["stat_max"] = dfi["stat -"] - df4["sys_min"] = dfi["sys +"] - df4["sys_max"] = dfi["sys -"] - - df4["abs_eta_min"] = 0.5 - df4["abs_eta_max"] = 1.0 - df4["sqrts"] = 200 - - elif "5" in fname: - correlation = True - dfc_col = pd.read_csv(fname) - - dfc = pd.DataFrame() - biny = 1 - for i in range(len(dfc_col)): - if dfc_col.loc[i, "binx"] == "-": - biny = float(dfc_col.loc[i, "val"]) - else: - binx = float(dfc_col.loc[i, "binx"]) - dfc.loc[binx, biny] = dfc_col.loc[i, "val"] - - dfc = dfc.astype("float") - - else: - print("ERROR: Unknown table number detected! Check input files.") - - df = pd.concat([df3, df4], ignore_index=True) - - for i in range(len(df)): - df.loc[i, "stat"] = df.loc[i, "stat_max"] - df.loc[i, "sys"] = df.loc[i, "sys_max"] - return df, dfc - - -def write_data(df, dfc): - data_central = [] - for i in range(len(df["ALL"])): - data_central.append(float(df.loc[i, "ALL"])) - - data_central_yaml = {"data_central": data_central} - with open("data.yaml", "w") as file: - yaml.dump(data_central_yaml, file, sort_keys=False) - - # Compute the covariance matrix - corrmat = dfc.values.reshape((len(df), len(df))) - art_sys = compute_covmat(corrmat, df["stat"], len(df)) - - # Write kin file - kin = [] - for i in range(len(df["ALL"])): - kin_value = { - "pT": {"min": None, "mid": float(df.loc[i, "pT"]), "max": None}, - "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, - "abs_eta": { - "min": float(df.loc[i, "abs_eta_min"]), - "mid": None, - "max": float(df.loc[i, "abs_eta_max"]), - }, - } - kin.append(kin_value) - - kinematics_yaml = {"bins": kin} - - with open("kinematics.yaml", "w") as file: - yaml.dump(kinematics_yaml, file, sort_keys=False) - - # Write unc file - error = [] - for i in range(len(df)): - e = {} - for j in range(len(df)): - e[f"sys_{j}"] = art_sys[i][j] - error.append(e) - - error_definition = { - f"sys_{i}": { - "description": f"{i} artificial correlated statistical uncertainty", - "treatment": "ADD", - "type": "CORR", - } - for i in range(len(df)) - } - - uncertainties_yaml = {"definitions": error_definition, "bins": error} - - with open("uncertainties.yaml", "w") as file: - yaml.dump(uncertainties_yaml, file, sort_keys=False) - - -if __name__ == "__main__": - # TODO: Need to generate `observable` cards and corresponding - # pineappl grids and FK tables as the orders have changed!!!! - fnames = glob.glob("rawdata/*.csv") - nnames = sorted([i for i in fnames]) - df, dfc = read_data(nnames) - write_data(df, dfc) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml index 6cf872824d..547551a6b9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml @@ -1,265 +1,265 @@ bins: -- pT: - min: null - mid: 5.5 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 5.5 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 6.49 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 6.49 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 8.25 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 8.25 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 10.08 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 10.08 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 12.26 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 12.26 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 14.78 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 14.78 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 17.23 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 17.23 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 20.56 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 20.56 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 23.61 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 23.61 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 27.78 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 27.78 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 32.46 +- eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: max: null - sqrts: + mid: 32.46 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.0 - mid: null - max: 0.5 -- pT: + mid: 200.0 min: null - mid: 5.61 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 5.61 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 6.62 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 6.62 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 8.48 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 8.48 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 10.17 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 10.17 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 12.2 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 12.2 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 14.57 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 14.57 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 16.99 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 16.99 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 20.16 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 20.16 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 23.35 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 23.35 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 27.13 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 27.13 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 -- pT: + mid: 200.0 min: null - mid: 31.08 +- eta: + max: 1.0 + mid: .nan + min: 0.5 + pT: max: null - sqrts: + mid: 31.08 min: null - mid: 200.0 + sqrts: max: null - abs_eta: - min: 0.5 - mid: null - max: 1.0 + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/correlation.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/correlation.csv new file mode 100644 index 0000000000..79a3996ebd --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/rawdata/correlation.csv @@ -0,0 +1,56 @@ +,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46,47,48,49,50,51,52,53,54,55 +1,1.0,0.013,0.008,0.007,0.008,0.008,0.006,0.005,0.003,0.002,0.002,0.043,0.011,0.011,0.005,0.005,0.003,0.005,0.002,0.001,0.002,0.001,0.014,0.003,0.0,0.0,0.0,0.0,0.0,0.019,0.004,0.001,0.0,0.0,0.0,0.0,0.005,0.005,0.001,0.0,0.0,0.0,0.0,0.004,0.002,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml index 74bd2bd5f8..1b7e453a80 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml @@ -1,574 +1,1484 @@ definitions: + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2009LUMI + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2009POL sys_0: - description: 0 artificial correlated statistical uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc0 sys_1: - description: 1 artificial correlated statistical uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc1 sys_2: - description: 2 artificial correlated statistical uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc2 sys_3: - description: 3 artificial correlated statistical uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc3 sys_4: - description: 4 artificial correlated statistical uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc4 sys_5: - description: 5 artificial correlated statistical uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc5 sys_6: - description: 6 artificial correlated statistical uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc6 sys_7: - description: 7 artificial correlated statistical uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc7 sys_8: - description: 8 artificial correlated statistical uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc8 sys_9: - description: 9 artificial correlated statistical uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc9 sys_10: - description: 10 artificial correlated statistical uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc10 sys_11: - description: 11 artificial correlated statistical uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc11 sys_12: - description: 12 artificial correlated statistical uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc12 sys_13: - description: 13 artificial correlated statistical uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc13 sys_14: - description: 14 artificial correlated statistical uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc14 sys_15: - description: 15 artificial correlated statistical uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc15 sys_16: - description: 16 artificial correlated statistical uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc16 sys_17: - description: 17 artificial correlated statistical uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc17 sys_18: - description: 18 artificial correlated statistical uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc18 sys_19: - description: 19 artificial correlated statistical uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc19 sys_20: - description: 20 artificial correlated statistical uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD - type: CORR + type: STAR2009JETunc20 sys_21: - description: 21 artificial correlated statistical uncertainty + description: 21 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc21 + sys_22: + description: 22 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc22 + sys_23: + description: 23 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc23 + sys_24: + description: 24 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc24 + sys_25: + description: 25 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc25 + sys_26: + description: 26 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc26 + sys_27: + description: 27 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc27 + sys_28: + description: 28 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc28 + sys_29: + description: 29 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc29 + sys_30: + description: 30 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc30 + sys_31: + description: 31 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc31 + sys_32: + description: 32 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc32 + sys_33: + description: 33 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc33 + sys_34: + description: 34 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc34 + sys_35: + description: 35 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc35 + sys_36: + description: 36 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc36 + sys_37: + description: 37 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc37 + sys_38: + description: 38 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc38 + sys_39: + description: 39 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc39 + sys_40: + description: 40 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc40 + sys_41: + description: 41 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc41 + sys_42: + description: 42 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc42 + sys_43: + description: 43 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc43 + sys_44: + description: 44 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc44 + sys_45: + description: 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1.6292256152871623e-08 + sys_31: -1.2390334942278296e-08 + sys_32: -1.4885948676438113e-08 + sys_33: 2.2528106917481325e-08 + sys_34: -2.7030581613058837e-08 + sys_35: 2.3742513511423296e-07 + sys_36: -2.1597010198170506e-07 + sys_37: 1.1931390121573002e-07 + sys_38: 4.4533807346141286e-08 + sys_39: 6.407695867467303e-07 + sys_40: -2.0139996183325178e-07 + sys_41: 2.100533102184625e-07 + sys_42: -3.171882294283553e-07 + sys_43: 9.105097274462783e-08 + sys_44: -1.824010064563299e-08 + sys_45: 1.1094546401956935e-07 + sys_46: 2.832006453676485e-08 + sys_47: 6.794129331636266e-07 + sys_48: 9.293649613076237e-08 + sys_49: -6.192954821576939e-08 + sys_50: 5.974620545393152e-07 + sys_51: 1.7108877834351418e-06 + sys_52: -1.6791417730060202e-06 + sys_53: -1.3564390794808346e-06 + sys_54: -2.141353274086469e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py deleted file mode 100644 index 101ba76767..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/filter.py +++ /dev/null @@ -1,85 +0,0 @@ -import glob - -import pandas as pd -import yaml - - -def read_data(fnames): - df = pd.DataFrame() - for fname in fnames: - with open(fname, "r") as file: - data = yaml.safe_load(file) - - Msub = data["independent_variables"][0]["values"] - Gsub = data["dependent_variables"][0]["values"] - - for i in range(len(Msub)): - - df = pd.concat( - [ - df, - pd.DataFrame( - { - "m_low": [Msub[i]["low"]], - "m_high": [Msub[i]["high"]], - "G": [Gsub[i]["value"]], - "stat": [Gsub[i]["errors"][0]["symerror"]], - "sys": [Gsub[i]["errors"][1]["symerror"]], - } - ), - ], - ignore_index=True, - ) - - return df - - -def write_data(df): - data_central = [] - for i in range(len(df["G"])): - data_central.append(float(df.loc[i, "G"])) - - data_central_yaml = {"data_central": data_central} - with open("data.yaml", "w") as file: - yaml.dump(data_central_yaml, file, sort_keys=False) - - # Write kin file - kin = [] - for i in range(len(df["G"])): - kin_value = { - "m_jj": { - "min": float(df.loc[i, "m_low"]), - "mid": None, - "max": float(df.loc[i, "m_high"]), - }, - "sqrts": {"min": None, "mid": 200, "max": None}, - } - kin.append(kin_value) - - kinematics_yaml = {"bins": kin} - - with open("kinematics.yaml", "w") as file: - yaml.dump(kinematics_yaml, file, sort_keys=False) - - # Write unc file - error = [] - for idx, i in enumerate(range(len(df))): - e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} - error.append(e) - - error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, - } - - uncertainties_yaml = {"definitions": error_definition, "bins": error} - - with open("uncertainties.yaml", "w") as file: - yaml.dump(uncertainties_yaml, file, sort_keys=False) - - -if __name__ == "__main__": - fnames = glob.glob("rawdata/*.yaml") - nnames = sorted([i for i in fnames]) - df = read_data(nnames) - write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml index 5d726a28bc..23089be979 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml @@ -1,41 +1,41 @@ bins: - m_jj: - min: 17.62 - mid: null max: 19.38 + mid: 18.5 + min: 17.62 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 20.5 - mid: null max: 22.9 + mid: 21.7 + min: 20.5 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 25.03 - mid: null max: 27.59 + mid: 26.310000000000002 + min: 25.03 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 30.0 - mid: null max: 33.48 + mid: 31.74 + min: 30.0 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 37.37 - mid: null max: 40.39 + mid: 38.879999999999995 + min: 37.37 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml index 75ab1997b3..469110bc80 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml @@ -5,9 +5,9 @@ nnpdf_metadata: nnpdf31_process: "DIJET" iNSPIRE: - url: "https://inspirehep.net/literature/1949588" + url: "https://inspirehep.net/literature/1674714" hepdata: - url: "https://www.hepdata.net/record/ins1949588" + url: "https://www.hepdata.net/record/ins1674714" version: 1 version: 1 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Figure9_Bottom.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Table.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Figure9_Bottom.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Table.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml index 60987a1e31..d614af1a44 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml @@ -3,18 +3,522 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - sys: - description: systematic uncertainty + lumi_ue: + description: underlying event and relative luminosity uncertainty treatment: ADD - type: UNCORR + type: STAR2009LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2009POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc47 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc48 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc49 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc50 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc51 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc52 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc53 + sys_54: + description: 54 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc54 bins: - stat: 0.007 - sys: 0.002 + lumi_ue: 0.0005 + pol: 0.0001235 + sys_0: -2.9341441875924853e-09 + sys_1: 5.662769814057847e-09 + sys_2: 3.947516339994088e-08 + sys_3: 3.474259906408537e-08 + sys_4: -4.1987083112144685e-07 + sys_5: 4.6980584967303393e-07 + sys_6: 1.6895587313557183e-05 + sys_7: 2.2729048660249382e-05 + sys_8: 6.306184493591873e-06 + sys_9: 1.2710948031307327e-05 + sys_10: -2.5789963843588195e-06 + sys_11: -2.1708424299713873e-05 + sys_12: 5.276451607974827e-06 + sys_13: 1.9633555980514045e-05 + sys_14: 8.248512495989165e-06 + sys_15: -6.108320795175292e-07 + 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1.8296228631547162e-05 + sys_47: -1.0545480744846846e-05 + sys_48: 6.924840530443168e-06 + sys_49: -6.415829585144976e-06 + sys_50: -3.390306554994056e-05 + sys_51: 2.6078959892613234e-05 + sys_52: -1.0756716695095525e-05 + sys_53: -1.338375509238332e-05 + sys_54: -1.8477958927331985e-06 - stat: 0.007 - sys: 0.0024 + lumi_ue: 0.0005 + pol: -0.0004485 + sys_0: -5.89864323557035e-09 + sys_1: 1.1973393934428427e-08 + sys_2: 7.77965450612318e-08 + sys_3: 7.416871876269945e-08 + sys_4: -7.985574948962801e-07 + sys_5: 9.350155690481822e-07 + sys_6: 3.1855141517541805e-05 + sys_7: 4.391081130552541e-05 + sys_8: 9.864730425254366e-06 + sys_9: 2.7112519417976648e-05 + sys_10: -4.2249542471596606e-06 + sys_11: -4.474742097944607e-05 + sys_12: 6.987177471243068e-06 + sys_13: 4.2628704935199975e-05 + sys_14: 1.9538926909859026e-05 + sys_15: -1.7506689751714958e-06 + sys_16: 3.850469490876804e-06 + sys_17: 2.5134194494492035e-05 + sys_18: -0.00011999000608407455 + sys_19: -0.00013174627021246313 + 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-4.0495428931684195e-05 + sys_51: 2.971385717258841e-05 + sys_52: -1.0565804858797907e-05 + sys_53: -1.9343984302625813e-05 + sys_54: 3.5154212080782464e-07 - stat: 0.01 - sys: 0.0016 + lumi_ue: 0.0005 + pol: 0.001378 + sys_0: -6.415581388921306e-09 + sys_1: 1.409642897031362e-08 + sys_2: 7.746596134549398e-08 + sys_3: 9.33034487652313e-08 + sys_4: -7.235587446500231e-07 + sys_5: 1.0158306104352489e-06 + sys_6: 2.7904732797661167e-05 + sys_7: 3.254099647236957e-05 + sys_8: 6.52357787045941e-06 + sys_9: 1.961341752112639e-05 + sys_10: -2.8030025648975518e-06 + sys_11: -3.52139197246018e-05 + sys_12: -4.298086439902791e-06 + sys_13: 2.3033625298799316e-05 + sys_14: 1.650708022641387e-05 + sys_15: -2.571619408737067e-06 + sys_16: 3.5264127033578895e-06 + sys_17: 3.517019381160326e-05 + sys_18: -5.867542307177835e-05 + sys_19: 2.5032695836614977e-06 + sys_20: -9.16903500741288e-05 + sys_21: -9.062621376864844e-06 + sys_22: -1.1055176164584399e-06 + sys_23: -0.00017459427443785696 + sys_24: 6.197017917920655e-05 + sys_25: 2.352324617959438e-05 + sys_26: -0.00015740595874289703 + sys_27: 1.722699953472693e-06 + sys_28: 1.9964560911026174e-07 + sys_29: -3.863878699104774e-06 + sys_30: 3.910199249854049e-06 + sys_31: -2.3827251325497906e-06 + sys_32: -2.993310426790834e-06 + sys_33: -2.846855830380958e-06 + sys_34: 4.925307867909738e-06 + sys_35: -2.4601182028748656e-05 + sys_36: 2.448783262938782e-05 + sys_37: 2.94318483087237e-06 + sys_38: 1.0902669841416097e-05 + sys_39: 2.815442611641162e-05 + sys_40: 8.716604704809673e-06 + sys_41: 1.3011292809824433e-05 + sys_42: 0.0003835782150805355 + sys_43: -0.00017835749219236195 + sys_44: 0.00020537172042123266 + sys_45: 0.0005415425685795098 + sys_46: 0.0002153769320066205 + sys_47: -0.0007452497927747477 + sys_48: -0.0011326673440649542 + sys_49: 4.533599212664479e-05 + sys_50: -0.00012381849347931312 + sys_51: 0.00013057940388986467 + sys_52: -0.00010720017447701937 + sys_53: -0.00018765877295429063 + sys_54: -1.0501767095327602e-05 - stat: 0.019 - sys: 0.005 + lumi_ue: 0.0005 + pol: 0.0027949999999999997 + sys_0: -5.059630706571177e-08 + sys_1: 1.2790135144982453e-07 + sys_2: 6.01176495734771e-07 + sys_3: 1.1081866608276079e-06 + sys_4: -1.6936993939290043e-05 + sys_5: 7.80302589581492e-06 + sys_6: 0.0002875227664291038 + sys_7: 0.0003289006382011793 + sys_8: 7.074208692754919e-05 + sys_9: 0.0002985247010156405 + sys_10: 9.54622526202337e-07 + sys_11: -0.0049233818617512365 + sys_12: 0.0005955984622793759 + sys_13: -0.00015452172899206533 + sys_14: -0.0002324260055604672 + sys_15: 4.9969335282250655e-05 + sys_16: -1.0895282127002112e-05 + sys_17: -0.00013152223926116887 + sys_18: 0.00011244560993024392 + sys_19: -2.4194619826444506e-05 + sys_20: 6.925038405067329e-05 + sys_21: 4.4443553613451764e-06 + sys_22: 1.460045885992515e-06 + sys_23: 5.267048676923238e-05 + sys_24: -1.2679357566322691e-05 + sys_25: -5.3788376124349545e-06 + sys_26: 2.2556501340293656e-05 + sys_27: 3.6391062112839596e-07 + sys_28: -2.5518540000916356e-07 + sys_29: -1.1807290582931746e-06 + sys_30: 1.9104032943127303e-06 + sys_31: -9.768451641637831e-10 + sys_32: -1.7744018042422284e-06 + sys_33: -1.4659319693688153e-06 + sys_34: 1.8924887984890418e-06 + sys_35: 1.3391480273704412e-05 + sys_36: 3.5375941347592616e-06 + sys_37: 4.211536652405987e-07 + sys_38: 3.4584511451192077e-06 + sys_39: 5.961789956334218e-06 + sys_40: 4.1882620075485344e-06 + sys_41: -3.3173111346442998e-06 + sys_42: -1.029183717903699e-05 + sys_43: 3.4054910474689777e-06 + sys_44: -5.7433544986648665e-06 + sys_45: -6.787062035416489e-06 + sys_46: -5.094436087922082e-06 + sys_47: 7.65867780682076e-06 + sys_48: -6.076332406783621e-06 + sys_49: 8.972547788173023e-07 + sys_50: 6.963291129900146e-07 + sys_51: 5.493945053969731e-06 + sys_52: -9.133716289879922e-06 + sys_53: -1.4473789093860536e-05 + sys_54: -1.744460748470315e-07 - stat: 0.05 - sys: 0.007 + lumi_ue: 0.0005 + pol: 0.00507 + sys_0: -2.4232685952842607e-07 + sys_1: 1.0157362580817375e-06 + sys_2: 1.7156500786764186e-05 + sys_3: 2.8992291251996853e-06 + sys_4: -7.396643323921346e-05 + sys_5: 7.214508938238357e-05 + sys_6: 0.00220477412510644 + sys_7: 0.005723296417354439 + sys_8: -0.0033230839708849975 + sys_9: -0.0003358795297340469 + sys_10: -0.00025007752191702004 + sys_11: 0.0002656367243530907 + sys_12: 0.00019145662440158158 + sys_13: 2.313651272926471e-05 + sys_14: -0.00017125549159043477 + sys_15: 4.845795465222483e-05 + sys_16: -3.3458707368659046e-06 + sys_17: -9.19075958650047e-05 + sys_18: 5.621270359864918e-05 + sys_19: -3.275010645190823e-05 + sys_20: 3.0166182171973963e-05 + sys_21: 2.943580737639226e-06 + sys_22: 2.9854707249000015e-07 + sys_23: 1.1647225335360799e-05 + sys_24: -6.685719184157822e-06 + sys_25: 5.358562353315896e-06 + sys_26: 3.92115742548422e-06 + sys_27: 8.72458875180983e-08 + sys_28: -2.6674204584258594e-07 + sys_29: -5.700004510090731e-07 + sys_30: 1.2879840036544182e-06 + sys_31: 4.0550106966900514e-07 + sys_32: -1.2816768788905185e-06 + sys_33: -1.0198491730245402e-06 + sys_34: 3.2695810626716083e-06 + sys_35: 9.862021203173689e-06 + sys_36: 2.6655886576878888e-06 + sys_37: -1.6941769689844783e-06 + sys_38: 2.2921825836749792e-06 + sys_39: 2.2965850608352704e-06 + sys_40: 3.6296347721058574e-06 + sys_41: -3.589447521323151e-06 + sys_42: -2.208717546309076e-06 + sys_43: 1.9985784149339748e-07 + sys_44: -2.3081597583270086e-06 + sys_45: 1.3791555540965545e-06 + sys_46: -1.855760764584328e-06 + sys_47: 9.165712466557843e-06 + sys_48: -7.047354539374752e-07 + sys_49: 6.106047716564541e-08 + sys_50: 1.1156476773463763e-06 + sys_51: 7.256657009371757e-07 + sys_52: -5.826790798946408e-06 + sys_53: -8.302888789428519e-06 + sys_54: -1.9752758430189458e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py deleted file mode 100644 index 101ba76767..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/filter.py +++ /dev/null @@ -1,85 +0,0 @@ -import glob - -import pandas as pd -import yaml - - -def read_data(fnames): - df = pd.DataFrame() - for fname in fnames: - with open(fname, "r") as file: - data = yaml.safe_load(file) - - Msub = data["independent_variables"][0]["values"] - Gsub = data["dependent_variables"][0]["values"] - - for i in range(len(Msub)): - - df = pd.concat( - [ - df, - pd.DataFrame( - { - "m_low": [Msub[i]["low"]], - "m_high": [Msub[i]["high"]], - "G": [Gsub[i]["value"]], - "stat": [Gsub[i]["errors"][0]["symerror"]], - "sys": [Gsub[i]["errors"][1]["symerror"]], - } - ), - ], - ignore_index=True, - ) - - return df - - -def write_data(df): - data_central = [] - for i in range(len(df["G"])): - data_central.append(float(df.loc[i, "G"])) - - data_central_yaml = {"data_central": data_central} - with open("data.yaml", "w") as file: - yaml.dump(data_central_yaml, file, sort_keys=False) - - # Write kin file - kin = [] - for i in range(len(df["G"])): - kin_value = { - "m_jj": { - "min": float(df.loc[i, "m_low"]), - "mid": None, - "max": float(df.loc[i, "m_high"]), - }, - "sqrts": {"min": None, "mid": 200, "max": None}, - } - kin.append(kin_value) - - kinematics_yaml = {"bins": kin} - - with open("kinematics.yaml", "w") as file: - yaml.dump(kinematics_yaml, file, sort_keys=False) - - # Write unc file - error = [] - for idx, i in enumerate(range(len(df))): - e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} - error.append(e) - - error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, - } - - uncertainties_yaml = {"definitions": error_definition, "bins": error} - - with open("uncertainties.yaml", "w") as file: - yaml.dump(uncertainties_yaml, file, sort_keys=False) - - -if __name__ == "__main__": - fnames = glob.glob("rawdata/*.yaml") - nnames = sorted([i for i in fnames]) - df = read_data(nnames) - write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml index 17497d6cc1..a895b8bdcd 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml @@ -1,57 +1,57 @@ bins: - m_jj: - min: 17.06 - mid: null max: 19.82 + mid: 18.439999999999998 + min: 17.06 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 21.12 - mid: null max: 23.1 + mid: 22.11 + min: 21.12 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 25.41 - mid: null max: 27.73 + mid: 26.57 + min: 25.41 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 30.66 - mid: null max: 33.76 + mid: 32.21 + min: 30.66 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 36.95 - mid: null max: 39.75 + mid: 38.35 + min: 36.95 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 46.36 - mid: null max: 49.66 + mid: 48.01 + min: 46.36 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 63.58 - mid: null max: 67.88 + mid: 65.72999999999999 + min: 63.58 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml index 93d593d014..97bdff2589 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml @@ -5,9 +5,9 @@ nnpdf_metadata: nnpdf31_process: "DIJET" iNSPIRE: - url: "https://inspirehep.net/literature/1949588" + url: "https://inspirehep.net/literature/1674714" hepdata: - url: "https://www.hepdata.net/record/ins1949588" + url: "https://www.hepdata.net/record/ins1674714" version: 1 version: 1 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml deleted file mode 100644 index f3823ff792..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Figure9_Top.yaml +++ /dev/null @@ -1,44 +0,0 @@ -dependent_variables: -- header: {name: 'Dijet $A_{LL}$'} - qualifiers: - - {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$', value: East-Barrel - Endcap} - values: - - errors: - - {label: stat, symerror: 0.011} - - {label: sys, symerror: 0.001} - value: -0.0178 - - errors: - - {label: stat, symerror: 0.005} - - {label: sys, symerror: 0.0015} - value: 0.0058 - - errors: - - {label: stat, symerror: 0.004} - - {label: sys, symerror: 0.0016} - value: 0.0048 - - errors: - - {label: stat, symerror: 0.004} - - {label: sys, symerror: 0.0013} - value: 0.0017 - - errors: - - {label: stat, symerror: 0.006} - - {label: sys, symerror: 0.0017} - value: -0.0078 - - errors: - - {label: stat, symerror: 0.008} - - {label: sys, symerror: 0.0027} - value: 0.0099 - - errors: - - {label: stat, symerror: 0.03} - - {label: sys, symerror: 0.007} - value: 0.012 -independent_variables: -- header: {name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$'} - values: - - {high: 19.82, low: 17.06} - - {high: 23.1, low: 21.12} - - {high: 27.73, low: 25.41} - - {high: 33.76, low: 30.66} - - {high: 39.75, low: 36.95} - - {high: 49.66, low: 46.36} - - {high: 67.88, low: 63.58} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Table.yaml new file mode 100644 index 0000000000..2bfa28f8fa --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Table.yaml @@ -0,0 +1,47 @@ +dependent_variables: + - header: { name: "Dijet $A_{LL}$" } + qualifiers: + - { + name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$', + value: East-Barrel + Endcap, + } + values: + - errors: + - { label: stat, symerror: 0.011 } + - { label: sys, symerror: 0.001 } + value: -0.0178 + - errors: + - { label: stat, symerror: 0.005 } + - { label: sys, symerror: 0.0015 } + value: 0.0058 + - errors: + - { label: stat, symerror: 0.004 } + - { label: sys, symerror: 0.0016 } + value: 0.0048 + - errors: + - { label: stat, symerror: 0.004 } + - { label: sys, symerror: 0.0013 } + value: 0.0017 + - errors: + - { label: stat, symerror: 0.006 } + - { label: sys, symerror: 0.0017 } + value: -0.0078 + - errors: + - { label: stat, symerror: 0.008 } + - { label: sys, symerror: 0.0027 } + value: 0.0099 + - errors: + - { label: stat, symerror: 0.03 } + - { label: sys, symerror: 0.007 } + value: 0.012 +independent_variables: + - header: { name: 'Parton Level Dijet Invariant Mass $[\mathrm{GeV}/c^{2}]$' } + values: + - { high: 19.82, low: 17.06 } + - { high: 23.1, low: 21.12 } + - { high: 27.73, low: 25.41 } + - { high: 33.76, low: 30.66 } + - { high: 39.75, low: 36.95 } + - { high: 49.66, low: 46.36 } + - { high: 67.88, low: 63.58 } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml index ef5c867b0c..6fd70788e3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml @@ -3,22 +3,638 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - sys: - description: systematic uncertainty + lumi_ue: + description: underlying event and relative luminosity uncertainty treatment: ADD - type: UNCORR + type: STAR2009LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2009POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc47 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc48 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc49 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc50 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc51 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc52 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc53 + sys_54: + description: 54 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc54 bins: - stat: 0.011 - sys: 0.001 + lumi_ue: 0.0005 + pol: -0.001157 + sys_0: -4.317226197359961e-06 + sys_1: 2.804090271238005e-06 + sys_2: 1.533190350417471e-05 + sys_3: 1.3248894278471846e-05 + sys_4: -3.970792674888402e-05 + sys_5: 4.788682989170766e-05 + sys_6: 7.578860297473904e-05 + sys_7: -5.7394041588018426e-06 + sys_8: -1.56142470492857e-05 + sys_9: 4.311010634645096e-06 + sys_10: 7.33121982630672e-05 + sys_11: -2.8776976935821262e-05 + sys_12: -5.855778266321408e-05 + sys_13: -1.4093447273033849e-05 + sys_14: 4.4380327228231225e-05 + sys_15: -1.3325774225658374e-05 + sys_16: 6.033465417142239e-06 + sys_17: 2.7492494558396243e-05 + sys_18: -7.047541911660221e-06 + sys_19: 1.3581480851298853e-06 + sys_20: -6.476895181058512e-06 + sys_21: -8.663799729471592e-06 + sys_22: 9.482890274222627e-06 + sys_23: 1.1958307342849003e-06 + sys_24: 1.4732693280305999e-05 + sys_25: -3.736661882023755e-05 + sys_26: -1.9830366563764863e-07 + sys_27: -1.553315738442825e-07 + sys_28: -1.8588162038316192e-06 + sys_29: -1.968770444620996e-06 + sys_30: 9.328655465325135e-06 + sys_31: 6.46752420202747e-06 + sys_32: -1.2064441092415521e-05 + sys_33: -1.1880625565876203e-05 + sys_34: 0.00011678148359693366 + sys_35: -1.8705415738101596e-05 + sys_36: -3.917055645981012e-06 + sys_37: -0.0004691926175721868 + sys_38: -0.0008488325877041941 + sys_39: 3.0225098159074235e-05 + sys_40: -0.00010922194438715117 + sys_41: 3.7354292478016275e-05 + sys_42: 1.0403290630320354e-05 + sys_43: 4.197043306795975e-06 + sys_44: 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5.703715661054181e-06 + sys_31: -8.169340256564795e-07 + sys_32: -4.795403532441962e-06 + sys_33: -2.853175884147154e-06 + sys_34: 1.1584240152205662e-05 + sys_35: -2.2569249772080613e-05 + sys_36: -5.706117067153508e-05 + sys_37: -3.5284317461951802e-06 + sys_38: 1.0661345577600817e-05 + sys_39: 1.9953556702085435e-05 + sys_40: 1.993532373862722e-05 + sys_41: 5.6678259172511115e-06 + sys_42: 0.0010392579895385785 + sys_43: 0.0010333464739764925 + sys_44: -0.00030783338468971604 + sys_45: -0.0006386580370345584 + sys_46: -0.00021689735003593285 + sys_47: -8.506596749045021e-06 + sys_48: -0.00012247708511736196 + sys_49: 1.5833244174123838e-05 + sys_50: -2.8128960250032784e-05 + sys_51: 4.6334702261783204e-05 + sys_52: -6.774363893320339e-05 + sys_53: -9.456304860268702e-05 + sys_54: -1.5931049017313595e-06 - stat: 0.008 - sys: 0.0027 + lumi_ue: 0.0005 + pol: 0.0006435000000000001 + sys_0: -6.901268308944533e-08 + sys_1: 2.527111324707297e-07 + sys_2: 3.2856289314680365e-06 + sys_3: 1.0892908444965393e-06 + sys_4: -2.0175082380548047e-05 + sys_5: 8.28383498981574e-06 + sys_6: 0.0001408502469980937 + sys_7: 6.911474208786563e-05 + sys_8: -8.119989145541228e-08 + sys_9: 5.413061720595011e-05 + sys_10: 2.4948254992228395e-05 + sys_11: -0.00014680007157111854 + sys_12: -0.0002013903134546795 + sys_13: 8.771399009193773e-06 + sys_14: 0.00016920758954260982 + sys_15: -4.796543640104816e-05 + sys_16: 2.2776448829736588e-05 + sys_17: 0.0004575123406122964 + sys_18: -0.0019903515525818783 + sys_19: -0.0016802709590049575 + sys_20: 0.0003845451178901134 + sys_21: 5.2858141582602583e-05 + sys_22: 1.1791411945682977e-05 + sys_23: 0.0001258251449153481 + sys_24: -2.519812470752517e-05 + sys_25: 8.930199808043769e-06 + sys_26: 5.95196436722984e-06 + sys_27: 3.13406711084332e-07 + sys_28: -7.519852420414007e-07 + sys_29: -1.8146526032254e-06 + sys_30: 3.9287294872502916e-06 + sys_31: 1.0635185272796338e-06 + sys_32: -3.864095923560414e-06 + sys_33: -2.694686099855434e-06 + sys_34: 8.870830584739429e-06 + sys_35: 4.891346818891008e-05 + sys_36: 1.3270011458155981e-05 + sys_37: -5.232159249672709e-06 + sys_38: 5.894506392895543e-06 + sys_39: 5.8889935865413965e-06 + sys_40: 1.76412557731669e-05 + sys_41: -1.0603731634666803e-05 + sys_42: -1.1183018323177393e-05 + sys_43: 7.206890189749094e-07 + sys_44: -8.84791748818859e-06 + sys_45: -3.610497445740074e-06 + sys_46: -8.659518643602748e-06 + sys_47: 3.24489282994933e-05 + sys_48: -9.308519699482843e-06 + sys_49: 4.79806488041496e-07 + sys_50: 1.6103119364681663e-06 + sys_51: 1.252084850583123e-07 + sys_52: -2.3009925326515995e-05 + sys_53: -3.188310734160565e-05 + sys_54: -1.3725732071673286e-07 - stat: 0.03 - sys: 0.007 + lumi_ue: 0.0005 + pol: 0.0007800000000000001 + sys_0: -7.869315895733471e-06 + sys_1: 2.713017354609144e-06 + sys_2: 5.815729290616714e-05 + sys_3: 1.5378264683085485e-05 + sys_4: -0.00026239571153456175 + sys_5: 0.00017732214220446022 + sys_6: 0.003827902906537021 + sys_7: 0.0019087791495396272 + sys_8: 0.005479558381969708 + sys_9: -0.00020975904305892644 + sys_10: -0.0005857411196858181 + sys_11: 0.00025481059211819335 + sys_12: 0.00027426712303479917 + sys_13: 5.528844400738451e-05 + sys_14: -0.00019342000921775308 + sys_15: 5.989794861160316e-05 + sys_16: 3.6370250085725546e-06 + sys_17: -2.4391573739440564e-05 + sys_18: 3.2973632136779246e-05 + sys_19: -1.2863855987108255e-05 + sys_20: 2.3244065704666267e-06 + sys_21: 1.082310950067716e-05 + sys_22: -4.085331968169395e-06 + sys_23: 2.760811082903175e-06 + sys_24: -8.51032055704677e-06 + sys_25: 1.8290731537061998e-05 + sys_26: 4.962160519692829e-07 + sys_27: -1.0127300090336294e-08 + sys_28: -1.9275627626677515e-07 + sys_29: -2.3885919305788315e-07 + sys_30: 8.767113525614774e-07 + sys_31: 5.16101749416286e-07 + sys_32: -9.087213201847263e-07 + sys_33: -1.0375370255823438e-06 + sys_34: 3.5487170167904455e-06 + sys_35: 1.1006287422880045e-05 + sys_36: 1.532257503518036e-06 + sys_37: -2.970565600998253e-06 + sys_38: 1.2613941376566012e-06 + sys_39: -8.546875793871267e-07 + sys_40: 6.511445449227887e-06 + sys_41: -4.443679311057276e-06 + sys_42: -5.110368015222906e-06 + sys_43: -1.4837415323438934e-06 + sys_44: -1.58947201893724e-06 + sys_45: 2.827404061127901e-06 + sys_46: -1.1777475286104613e-06 + sys_47: 1.006124507569685e-05 + sys_48: 5.307416038106339e-07 + sys_49: -2.1418956485350758e-07 + sys_50: -7.265846869734679e-07 + sys_51: -3.7548722739803504e-06 + sys_52: -6.075513407388898e-06 + sys_53: -7.728853689758109e-06 + sys_54: -3.2270993758520353e-09 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py deleted file mode 100644 index 101ba76767..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/filter.py +++ /dev/null @@ -1,85 +0,0 @@ -import glob - -import pandas as pd -import yaml - - -def read_data(fnames): - df = pd.DataFrame() - for fname in fnames: - with open(fname, "r") as file: - data = yaml.safe_load(file) - - Msub = data["independent_variables"][0]["values"] - Gsub = data["dependent_variables"][0]["values"] - - for i in range(len(Msub)): - - df = pd.concat( - [ - df, - pd.DataFrame( - { - "m_low": [Msub[i]["low"]], - "m_high": [Msub[i]["high"]], - "G": [Gsub[i]["value"]], - "stat": [Gsub[i]["errors"][0]["symerror"]], - "sys": [Gsub[i]["errors"][1]["symerror"]], - } - ), - ], - ignore_index=True, - ) - - return df - - -def write_data(df): - data_central = [] - for i in range(len(df["G"])): - data_central.append(float(df.loc[i, "G"])) - - data_central_yaml = {"data_central": data_central} - with open("data.yaml", "w") as file: - yaml.dump(data_central_yaml, file, sort_keys=False) - - # Write kin file - kin = [] - for i in range(len(df["G"])): - kin_value = { - "m_jj": { - "min": float(df.loc[i, "m_low"]), - "mid": None, - "max": float(df.loc[i, "m_high"]), - }, - "sqrts": {"min": None, "mid": 200, "max": None}, - } - kin.append(kin_value) - - kinematics_yaml = {"bins": kin} - - with open("kinematics.yaml", "w") as file: - yaml.dump(kinematics_yaml, file, sort_keys=False) - - # Write unc file - error = [] - for idx, i in enumerate(range(len(df))): - e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} - error.append(e) - - error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, - } - - uncertainties_yaml = {"definitions": error_definition, "bins": error} - - with open("uncertainties.yaml", "w") as file: - yaml.dump(uncertainties_yaml, file, sort_keys=False) - - -if __name__ == "__main__": - fnames = glob.glob("rawdata/*.yaml") - nnames = sorted([i for i in fnames]) - df = read_data(nnames) - write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml index 2122d767e6..27677c4568 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml @@ -1,57 +1,57 @@ bins: - m_jj: - min: 17.31 - mid: null max: 19.71 + mid: 18.509999999999998 + min: 17.31 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 20.62 - mid: null max: 22.94 + mid: 21.78 + min: 20.62 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 24.83 - mid: null max: 27.21 + mid: 26.02 + min: 24.83 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 29.42 - mid: null max: 32.16 + mid: 30.79 + min: 29.42 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 36.62 - mid: null max: 39.28 + mid: 37.95 + min: 36.62 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 44.88 - mid: null max: 47.98 + mid: 46.43 + min: 44.88 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null - m_jj: - min: 59.6 - mid: null max: 66.04 + mid: 62.82000000000001 + min: 59.6 sqrts: - min: null - mid: 200 max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml index 675cf5256d..86feaca0a6 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml @@ -5,9 +5,9 @@ nnpdf_metadata: nnpdf31_process: "DIJET" iNSPIRE: - url: "https://inspirehep.net/literature/1949588" + url: "https://inspirehep.net/literature/1674714" hepdata: - url: "https://www.hepdata.net/record/ins1949588" + url: "https://www.hepdata.net/record/ins1674714" version: 1 version: 1 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Figure9_Mid.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Table.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Figure9_Mid.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Table.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml index 43934dead9..ee8ba234fd 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml @@ -3,22 +3,638 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - sys: - description: systematic uncertainty + lumi_ue: + description: underlying event and relative luminosity uncertainty treatment: ADD - type: UNCORR + type: STAR2009LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2009POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc47 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc48 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc49 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: 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a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/kinematics.yaml new file mode 100644 index 0000000000..58657f6130 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/kinematics.yaml @@ -0,0 +1,57 @@ +bins: +- m_jj: + max: null + mid: 17.99 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 21.58 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 26.29 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 31.72 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 38.38 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 48.79 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 67.32 + min: null + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml new file mode 100644 index 0000000000..82bca00604 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml @@ -0,0 +1,49 @@ +setname: "STAR_2009_2JET_OS_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1493842" +hepdata: + url: "https://www.hepdata.net/record/ins1493842" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL as function of $M_{inv}$, OS", + label: "$A_{LL}$", + units: "", + } + observable_name: ALL + process_type: DIJET_POL + ndata: 7 + tables: [9] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, OS" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_OS_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/rawdata/Table.yaml new file mode 100644 index 0000000000..17a08d70f9 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/rawdata/Table.yaml @@ -0,0 +1,81 @@ +dependent_variables: +- header: {name: DIJET MASS, units: GEV} + qualifiers: + - {name: JET ALGORITHM, value: Anti-kT R = 0.6} + - {name: PHASE SPACE, value: '|ETA_1,ETA_2| < 0.8'} + - {name: RE, value: P P --> JET JET X} + - {name: SQRT(s), value: 200 GEV} + values: + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 0.54} + value: 17.99 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 0.96} + value: 21.58 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 1.32} + value: 26.29 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 1.72} + value: 31.72 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 1.7} + value: 38.38 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 2.07} + value: 48.79 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 3.35} + value: 67.32 +- header: {name: ASYMMETRY} + qualifiers: + - {name: JET ALGORITHM, value: Anti-kT R = 0.6} + - {name: PHASE SPACE, value: Sign(ETA_1) != Sign(ETA_2)} + - {name: RE, value: P P --> JET JET X} + - {name: SQRT(s), value: 200 GEV} + values: + - errors: + - {label: stat, symerror: 0.0039} + - {label: sys, symerror: 0.0005} + value: 0.0059 + - errors: + - {label: stat, symerror: 0.0032} + - {label: sys, symerror: 0.0006} + value: 0.0096 + - errors: + - {label: stat, symerror: 0.0037} + - {label: sys, symerror: 0.0007} + value: 0.0068 + - errors: + - {label: stat, symerror: 0.005} + - {label: sys, symerror: 0.0009} + value: 0.0151 + - errors: + - {label: stat, symerror: 0.0077} + - {label: sys, symerror: 0.0013} + value: 0.0083 + - errors: + - {label: stat, symerror: 0.0109} + - {label: sys, symerror: 0.0022} + value: 0.0092 + - errors: + - {label: stat, symerror: 0.034} + - {label: sys, symerror: 0.0036} + value: -0.0282 +independent_variables: +- header: {name: Bin} + values: + - {value: 8.0} + - {value: 9.0} + - {value: 10.0} + - {value: 11.0} + - {value: 12.0} + - {value: 13.0} + - {value: 14.0} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..434c52b454 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml @@ -0,0 +1,640 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2009LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2009POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc47 + sys_48: + description: 48 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/data.yaml new file mode 100644 index 0000000000..0adfd014d1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/data.yaml @@ -0,0 +1,8 @@ +data_central: +- 0.0067 +- 0.0088 +- 0.0162 +- 0.0024 +- 0.013 +- 0.0336 +- 0.0755 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/kinematics.yaml new file mode 100644 index 0000000000..6aa1fcc389 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/kinematics.yaml @@ -0,0 +1,57 @@ +bins: +- m_jj: + max: null + mid: 17.7 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 21.34 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 26.02 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 31.66 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 38.25 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 48.28 + min: null + sqrts: + max: null + mid: 200.0 + min: null +- m_jj: + max: null + mid: 66.65 + min: null + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml new file mode 100644 index 0000000000..661703181b --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml @@ -0,0 +1,49 @@ +setname: "STAR_2009_2JET_SS_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +iNSPIRE: + url: "https://inspirehep.net/literature/1493842" +hepdata: + url: "https://www.hepdata.net/record/ins1493842" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL as function of $M_{inv}$, SS", + label: "$A_{LL}$", + units: "", + } + observable_name: ALL + process_type: DIJET_POL + ndata: 7 + tables: [7] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, SS" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_SS_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/rawdata/Table.yaml new file mode 100644 index 0000000000..00e274aa76 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/rawdata/Table.yaml @@ -0,0 +1,81 @@ +dependent_variables: +- header: {name: DIJET MASS, units: GEV} + qualifiers: + - {name: JET ALGORITHM, value: Anti-kT R = 0.6} + - {name: PHASE SPACE, value: '|ETA_1,ETA_2| < 0.8'} + - {name: RE, value: P P --> JET JET X} + - {name: SQRT(s), value: 200 GEV} + values: + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 0.56} + value: 17.7 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 1.07} + value: 21.34 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 1.33} + value: 26.02 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 1.39} + value: 31.66 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 1.79} + value: 38.25 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 2.17} + value: 48.28 + - errors: + - {label: stat, symerror: 0.0} + - {label: sys, symerror: 2.56} + value: 66.65 +- header: {name: ASYMMETRY} + qualifiers: + - {name: JET ALGORITHM, value: Anti-kT R = 0.6} + - {name: PHASE SPACE, value: Sign(ETA_1) = Sign(ETA_2)} + - {name: RE, value: P P --> JET JET X} + - {name: SQRT(s), value: 200 GEV} + values: + - errors: + - {label: stat, symerror: 0.0034} + - {label: sys, symerror: 0.0004} + value: 0.0067 + - errors: + - {label: stat, symerror: 0.0032} + - {label: sys, symerror: 0.0005} + value: 0.0088 + - errors: + - {label: stat, symerror: 0.0039} + - {label: sys, symerror: 0.0006} + value: 0.0162 + - errors: + - {label: stat, symerror: 0.0056} + - {label: sys, symerror: 0.001} + value: 0.0024 + - errors: + - {label: stat, symerror: 0.0089} + - {label: sys, symerror: 0.0015} + value: 0.013 + - errors: + - {label: stat, symerror: 0.0133} + - {label: sys, symerror: 0.0024} + value: 0.0336 + - errors: + - {label: stat, symerror: 0.046} + - {label: sys, symerror: 0.0041} + value: 0.0755 +independent_variables: +- header: {name: Bin} + values: + - {value: 1.0} + - {value: 2.0} + - {value: 3.0} + - {value: 4.0} + - {value: 5.0} + - {value: 6.0} + - {value: 7.0} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..bc1f0b4291 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml @@ -0,0 +1,640 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + lumi_ue: + description: underlying event and relative luminosity uncertainty + treatment: ADD + type: STAR2009LUMIUE + pol: + description: polarization uncertainty + treatment: MULT + type: STAR2009POL + sys_0: + description: 0 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc0 + sys_1: + description: 1 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc1 + sys_2: + description: 2 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc2 + sys_3: + description: 3 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc3 + sys_4: + description: 4 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc4 + sys_5: + description: 5 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc5 + sys_6: + description: 6 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc6 + sys_7: + description: 7 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc7 + sys_8: + description: 8 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc8 + sys_9: + description: 9 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc9 + sys_10: + description: 10 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc10 + sys_11: + description: 11 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc11 + sys_12: + description: 12 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc12 + sys_13: + description: 13 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc13 + sys_14: + description: 14 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc14 + sys_15: + description: 15 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc15 + sys_16: + description: 16 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc16 + sys_17: + description: 17 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc17 + sys_18: + description: 18 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc18 + sys_19: + description: 19 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc19 + sys_20: + description: 20 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc20 + sys_21: + description: 21 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc21 + sys_22: + description: 22 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc22 + sys_23: + description: 23 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc23 + sys_24: + description: 24 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc24 + sys_25: + description: 25 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc25 + sys_26: + description: 26 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc26 + sys_27: + description: 27 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc27 + sys_28: + description: 28 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc28 + sys_29: + description: 29 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc29 + sys_30: + description: 30 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc30 + sys_31: + description: 31 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc31 + sys_32: + description: 32 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc32 + sys_33: + description: 33 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc33 + sys_34: + description: 34 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc34 + sys_35: + description: 35 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc35 + sys_36: + description: 36 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc36 + sys_37: + description: 37 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc37 + sys_38: + description: 38 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc38 + sys_39: + description: 39 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc39 + sys_40: + description: 40 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc40 + sys_41: + description: 41 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc41 + sys_42: + description: 42 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc42 + sys_43: + description: 43 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc43 + sys_44: + description: 44 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc44 + sys_45: + description: 45 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc45 + sys_46: + description: 46 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc46 + sys_47: + description: 47 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc47 + sys_48: + description: 48 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc48 + sys_49: + description: 49 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc49 + sys_50: + description: 50 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc50 + sys_51: + description: 51 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc51 + sys_52: + description: 52 artificial correlated systematics uncertainty + treatment: ADD + type: STAR2009JETunc52 + sys_53: + description: 53 artificial correlated systematics uncertainty + treatment: ADD + type: 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8.351743182233937e-07 + sys_50: -8.909902905485869e-06 + sys_51: -2.500575195807621e-05 + sys_52: 1.5711433681084028e-05 + sys_53: 1.4611441526549152e-05 + sys_54: 1.8962497882455335e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml index b082cf20bd..273c010c6f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml @@ -5,9 +5,9 @@ nnpdf_metadata: nnpdf31_process: "JETS" iNSPIRE: - url: "https://inspirehep.net/literature/1738738" + url: "https://inspirehep.net/literature/1493842" hepdata: - url: "https://www.hepdata.net/record/ins1738738" + url: "https://www.hepdata.net/record/ins1493842" version: 1 arXiv: url: https://arxiv.org/abs/1906.02740 @@ -16,7 +16,12 @@ version: 1 version_comment: "Initial implementation, correlations from arXiv" implemented_observables: - - observable: { description: "$A_{LL}$ as function of $p_T$", label: "$A_{LL}$", units: "" } + - observable: + { + description: "$A_{LL}$ as function of $p_T$", + label: "$A_{LL}$", + units: "", + } observable_name: ALL process_type: JET_POL ndata: 14 From 6cc4020c8749f102ac3df96ef5fe0d094fc61e5b Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Mon, 29 Apr 2024 11:45:17 +0200 Subject: [PATCH 22/98] change back filter import --- .../new_commondata/STAR_2005_1JET_200GEV/filter.py | 5 ++--- .../new_commondata/STAR_2006_1JET_200GEV/filter.py | 5 ++--- 2 files changed, 4 insertions(+), 6 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py index b31a0748fc..96dbc30394 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py @@ -1,11 +1,10 @@ import glob +import sys import pandas as pd import yaml -import sys -sys.path.append('../../') -from filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def read_data(fnames): diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py index b31a0748fc..96dbc30394 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py @@ -1,11 +1,10 @@ import glob +import sys import pandas as pd import yaml -import sys -sys.path.append('../../') -from filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se def read_data(fnames): From 8687f8a812cbd0403a5a33de3aa7c9f5579c3b1d Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Wed, 1 May 2024 11:22:46 +0200 Subject: [PATCH 23/98] Giacomo's suggestions --- .../star/jet_dijet_2009_200gev.py | 109 +++++++++--------- .../STAR_2009_1JET_200GEV/kinematics.yaml | 44 +++---- .../STAR_2009_1JET_200GEV/metadata.yaml | 2 +- .../STAR_2009_1JET_200GEV/uncertainties.yaml | 96 ++++----------- .../uncertainties.yaml | 18 --- .../uncertainties.yaml | 22 ---- .../uncertainties.yaml | 22 ---- .../uncertainties.yaml | 11 -- .../uncertainties.yaml | 11 -- 9 files changed, 101 insertions(+), 234 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index 8b98c15ca7..2621d62c62 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -80,8 +80,6 @@ def read_1jet_data(): print("ERROR: Unknown table number detected! Check input files.") df = pd.concat([df3, df4], ignore_index=True) - df["pol"] = POL_UNC * df["ALL"] - df["lumi_ue"] = LUMI_UNC for i in range(len(df)): df.loc[i, "stat"] = df.loc[i, "stat_max"] @@ -111,8 +109,6 @@ def read_2jet_data(topology): "ALL": [Gsub[i]["value"]], "stat": [Gsub[i]["errors"][0]["symerror"]], "sys": [Gsub[i]["errors"][1]["symerror"]], - "pol": [POL_UNC * Gsub[i]["value"]], - "lumi_ue": [LUMI_UNC], } ), ], @@ -138,7 +134,6 @@ def read_2jet_data(topology): "stat": [Gsub[i]["errors"][0]["symerror"]], "sys": [Gsub[i]["errors"][1]["symerror"]], "pol": [POL_UNC * Gsub[i]["value"]], - "lumi_ue": [LUMI_UNC], } ), ], @@ -163,7 +158,7 @@ def write_1jet_data(df, art_sys): kin_value = { "pT": {"min": None, "mid": float(df.loc[i, "pT"]), "max": None}, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, - "eta": { + "eta_abs": { "min": float(df.loc[i, "abs_eta_min"]), "mid": float(df.loc[i, "abs_eta"]), "max": float(df.loc[i, "abs_eta_max"]), @@ -176,21 +171,10 @@ def write_1jet_data(df, art_sys): # Write unc file error = [] - error_definition = { - "lumi_ue": { - "description": "underlying event and relative luminosity uncertainty", - "treatment": "ADD", - "type": f"STAR2009LUMI", - }, - "pol": { - "description": "polarization uncertainty", - "treatment": "MULT", - "type": f"STAR2009POL", - }, - } + error_definition = {} # loop on data points for i, sys_i in enumerate(art_sys): - e = {"lumi_ue": float(df.loc[i, "lumi_ue"]), "pol": float(df.loc[i, "pol"])} + e = {} # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -243,42 +227,61 @@ def write_2jet_data(df, topology, art_sys): # Write unc file error = [] - error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "lumi_ue": { - "description": "underlying event and relative luminosity uncertainty", - "treatment": "ADD", - "type": f"STAR2009LUMIUE", - }, - "pol": { - "description": "polarization uncertainty", - "treatment": "MULT", - "type": f"STAR2009POL", - }, - } - # loop on data points - for i, sys_i in enumerate(art_sys): - e = { - "stat": float(df.loc[i, "stat"]), - "lumi_ue": float(df.loc[i, "lumi_ue"]), - "pol": float(df.loc[i, "pol"]), + if topology in ["A", "B", "C"]: + error_definition = { + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"} } - # loop on art sys - for j, val in enumerate(sys_i): - e[f"sys_{j}"] = val - error.append(e) - - if i == 0: - error_definition.update( - { - f"sys_{j}": { - "description": f"{j} artificial correlated systematics uncertainty", - "treatment": "ADD", - "type": f"STAR2009JETunc{j}", + # loop on data points + for i, sys_i in enumerate(art_sys): + e = {"stat": float(df.loc[i, "stat"])} + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + error.append(e) + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": f"STAR2009JETunc{j}", + } + for j in range(len(sys_i)) } - for j in range(len(sys_i)) - } - ) + ) + else: + error_definition = { + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "pol": { + "description": "polarization uncertainty", + "treatment": "MULT", + "type": f"STAR2009POL", + }, + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = {"stat": float(df.loc[i, "stat"]), "pol": float(df.loc[i, "pol"])} + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + error.append(e) + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": f"STAR2009JETunc{j}", + } + for j in range(len(sys_i)) + } + ) uncertainties_yaml = {"definitions": error_definition, "bins": error} with open(STORE_PATH + "uncertainties.yaml", "w", encoding="utf-8") as file: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml index 547551a6b9..2ccd4e689d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml @@ -1,5 +1,5 @@ bins: -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -11,7 +11,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -23,7 +23,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -35,7 +35,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -47,7 +47,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -59,7 +59,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -71,7 +71,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -83,7 +83,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -95,7 +95,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -107,7 +107,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -119,7 +119,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 0.5 mid: 0.25 min: 0.0 @@ -131,7 +131,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -143,7 +143,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -155,7 +155,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -167,7 +167,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -179,7 +179,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -191,7 +191,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -203,7 +203,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -215,7 +215,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -227,7 +227,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -239,7 +239,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 @@ -251,7 +251,7 @@ bins: max: null mid: 200.0 min: null -- eta: +- eta_abs: max: 1.0 mid: .nan min: 0.5 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml index 637a7143bf..f5197d9ddd 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml @@ -34,7 +34,7 @@ implemented_observables: label: '$\sqrt{s}$', units: "$GeV$", } - abs_eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + abs_eta: { description: "pseudorapidity", label: '$|\eta|$', units: "" } file: kinematics.yaml data_central: data.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml index 1b7e453a80..05ff44bb88 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml @@ -1,12 +1,4 @@ definitions: - lumi_ue: - description: underlying event and relative luminosity uncertainty - treatment: ADD - type: STAR2009LUMI - pol: - description: polarization uncertainty - treatment: MULT - type: STAR2009POL sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD @@ -228,9 +220,7 @@ definitions: treatment: ADD type: STAR2009JETunc54 bins: -- lumi_ue: 0.0005 - pol: 0.00013000000000000002 - sys_0: -1.6815813095948376e-06 +- sys_0: -1.6815813095948376e-06 sys_1: 3.135895236790491e-06 sys_2: 3.0444062961187053e-06 sys_3: 2.6704105981460463e-06 @@ -285,9 +275,7 @@ bins: sys_52: -2.72822541876334e-05 sys_53: 3.790511732903777e-05 sys_54: -2.204899854745883e-06 -- lumi_ue: 0.0005 - pol: 0.000364 - sys_0: -3.565571410375404e-06 +- sys_0: -3.565571410375404e-06 sys_1: 5.117077226393213e-06 sys_2: 6.682942299895229e-06 sys_3: 5.9002843574510094e-06 @@ -342,9 +330,7 @@ bins: sys_52: -9.75549326891594e-06 sys_53: 2.3269397014720622e-05 sys_54: -2.9519111032082817e-07 -- lumi_ue: 0.0005 - pol: 8.45e-05 - sys_0: -1.61281455065914e-06 +- sys_0: -1.61281455065914e-06 sys_1: 3.030697509306084e-06 sys_2: 3.0110611954230385e-06 sys_3: 4.115416724063551e-06 @@ -399,9 +385,7 @@ bins: sys_52: -8.946834604885945e-06 sys_53: -0.00017651083622737145 sys_54: 1.000558779429967e-05 -- lumi_ue: 0.0005 - pol: 0.00032500000000000004 - sys_0: -1.8407413602049194e-06 +- sys_0: -1.8407413602049194e-06 sys_1: 3.5086294377477786e-06 sys_2: 5.105734557078875e-06 sys_3: 4.622346972429554e-06 @@ -456,9 +440,7 @@ bins: sys_52: 1.4575479199335405e-05 sys_53: 0.00010787871513080272 sys_54: -1.1337620075822083e-06 -- lumi_ue: 0.0005 - pol: 0.000351 - sys_0: -4.52021480347908e-06 +- sys_0: -4.52021480347908e-06 sys_1: 6.6564565049703376e-06 sys_2: 1.0912861487887639e-05 sys_3: 1.2078608380689273e-05 @@ -513,9 +495,7 @@ bins: sys_52: 8.844632910624363e-06 sys_53: 3.1561356848547454e-05 sys_54: 2.2608316533250084e-07 -- lumi_ue: 0.0005 - pol: 0.000741 - sys_0: -8.756422781750881e-06 +- sys_0: -8.756422781750881e-06 sys_1: 1.170440227023131e-05 sys_2: 2.2889580686086998e-05 sys_3: 2.3952928171559695e-05 @@ -570,9 +550,7 @@ bins: sys_52: 2.487064666094441e-05 sys_53: 1.8255215937668907e-05 sys_54: 1.794373103684562e-06 -- lumi_ue: 0.0005 - pol: 0.0007475 - sys_0: -2.1732611873487286e-05 +- sys_0: -2.1732611873487286e-05 sys_1: 2.6253844886658937e-05 sys_2: 4.8205398802713783e-05 sys_3: 5.456978804540457e-05 @@ -627,9 +605,7 @@ bins: sys_52: 3.996705535110993e-05 sys_53: 1.103337030978199e-05 sys_54: 2.79909789128746e-06 -- lumi_ue: 0.0005 - pol: 0.000858 - sys_0: -5.7180392921169035e-05 +- sys_0: -5.7180392921169035e-05 sys_1: 8.263942734600955e-05 sys_2: 0.00012943581545866038 sys_3: 0.00016665874702259553 @@ -684,9 +660,7 @@ bins: sys_52: 2.5017894874311166e-05 sys_53: 1.535075168094847e-06 sys_54: 1.794035988279641e-06 -- lumi_ue: 0.0005 - pol: 0.0013455000000000001 - sys_0: -0.00019424520482539109 +- sys_0: -0.00019424520482539109 sys_1: 0.0003075116114880381 sys_2: 0.00038046984104447455 sys_3: 0.0006171668263760231 @@ -741,9 +715,7 @@ bins: sys_52: -1.4509332283946532e-06 sys_53: -6.6374392731381365e-06 sys_54: -1.0632760317774837e-06 -- lumi_ue: 0.0005 - pol: 0.002119 - sys_0: -0.0006617526466528271 +- sys_0: -0.0006617526466528271 sys_1: 0.0012401151252857446 sys_2: 0.0016160729058729542 sys_3: 0.016310751543155446 @@ -798,9 +770,7 @@ bins: sys_52: -7.5685984890394495e-06 sys_53: -6.810563298345871e-06 sys_54: -6.730488466504003e-06 -- lumi_ue: 0.0005 - pol: 0.002158 - sys_0: -0.002323760161340845 +- sys_0: -0.002323760161340845 sys_1: 0.029963477140346452 sys_2: -0.0011920788362439745 sys_3: -0.0006810916596646526 @@ -855,9 +825,7 @@ bins: sys_52: -2.990909124558309e-06 sys_53: -2.7518909580707517e-06 sys_54: -4.64511843266615e-06 -- lumi_ue: 0.0005 - pol: 0.000117 - sys_0: -1.7528273560955859e-06 +- sys_0: -1.7528273560955859e-06 sys_1: 1.7358653335865935e-06 sys_2: 3.3987748464787367e-06 sys_3: 3.0002444025136713e-06 @@ -912,9 +880,7 @@ bins: sys_52: 3.5277438928208386e-06 sys_53: -3.922693455229976e-06 sys_54: 1.155137891162881e-06 -- lumi_ue: 0.0005 - pol: 0.00026000000000000003 - sys_0: -2.1225227356543143e-06 +- sys_0: -2.1225227356543143e-06 sys_1: 5.755696701429583e-06 sys_2: 5.5463910213605755e-06 sys_3: 4.929651925845142e-06 @@ -969,9 +935,7 @@ bins: sys_52: 4.081671517430523e-06 sys_53: 2.20167678099804e-06 sys_54: 1.4381466598294058e-06 -- lumi_ue: 0.0005 - pol: 0.0003835 - sys_0: -3.5693042347555235e-06 +- sys_0: -3.5693042347555235e-06 sys_1: 5.129374194132518e-06 sys_2: 6.718052006157451e-06 sys_3: 6.012716996989462e-06 @@ -1026,9 +990,7 @@ bins: sys_52: 7.46296932922705e-05 sys_53: 1.0819209568389375e-05 sys_54: 1.6442472345123423e-05 -- lumi_ue: 0.0005 - pol: 0.0001755 - sys_0: -2.081646241989143e-06 +- sys_0: -2.081646241989143e-06 sys_1: 2.136155486137954e-06 sys_2: 6.020019211616544e-06 sys_3: 3.5137255025922627e-06 @@ -1083,9 +1045,7 @@ bins: sys_52: 3.846659296327778e-05 sys_53: -3.0101360026382423e-05 sys_54: 8.707078299613975e-06 -- lumi_ue: 0.0005 - pol: 0.0004485 - sys_0: -5.184126709819154e-06 +- sys_0: -5.184126709819154e-06 sys_1: 4.963078030169351e-06 sys_2: 5.194933560524388e-06 sys_3: 7.285631826240483e-06 @@ -1140,9 +1100,7 @@ bins: sys_52: 1.916292922244805e-05 sys_53: -1.0854053906487877e-05 sys_54: 4.0839301591071e-06 -- lumi_ue: 0.0005 - pol: 0.0005655 - sys_0: -3.7200216807568606e-06 +- sys_0: -3.7200216807568606e-06 sys_1: 7.293744242906698e-06 sys_2: 1.4120482879297658e-05 sys_3: 1.3449251818660538e-05 @@ -1197,9 +1155,7 @@ bins: sys_52: 1.4364761153745503e-05 sys_53: 1.7432978291364534e-06 sys_54: 2.004257241137291e-06 -- lumi_ue: 0.0005 - pol: 0.000975 - sys_0: -1.5617234504439125e-05 +- sys_0: -1.5617234504439125e-05 sys_1: 2.0912566748554055e-05 sys_2: 3.692789551711395e-05 sys_3: 4.1168778294445686e-05 @@ -1254,9 +1210,7 @@ bins: sys_52: 1.5824591228734433e-05 sys_53: 3.991394714317471e-06 sys_54: 1.2466275055350114e-06 -- lumi_ue: 0.0005 - pol: 0.0012675 - sys_0: -4.0508939063109485e-05 +- sys_0: -4.0508939063109485e-05 sys_1: 5.072784330802925e-05 sys_2: 9.662324917837414e-05 sys_3: 0.00014492208232847985 @@ -1311,9 +1265,7 @@ bins: sys_52: 4.241420316436655e-06 sys_53: -1.961214950387269e-06 sys_54: 1.9132508885647127e-06 -- lumi_ue: 0.0005 - pol: 0.0021645 - sys_0: -0.00011955383881854172 +- sys_0: -0.00011955383881854172 sys_1: 0.0002101907323503664 sys_2: 0.00032474930865977676 sys_3: 0.000738050744649477 @@ -1368,9 +1320,7 @@ bins: sys_52: -7.169697857358862e-06 sys_53: -5.811588290816765e-06 sys_54: 1.062755819240843e-06 -- lumi_ue: 0.0005 - pol: 0.0028405 - sys_0: -0.00047076105451365036 +- sys_0: -0.00047076105451365036 sys_1: 0.0014526378560851439 sys_2: 0.02233518479250741 sys_3: -0.001266350427591967 @@ -1425,9 +1375,7 @@ bins: sys_52: -5.37192147995637e-06 sys_53: -3.6939471220217518e-06 sys_54: -1.2740851741168651e-06 -- lumi_ue: 0.0005 - pol: 0.0003575 - sys_0: -0.0437806352349467 +- sys_0: -0.0437806352349467 sys_1: -0.0016494136220161217 sys_2: -0.0002124625432134228 sys_3: -0.00021644949663639752 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml index d614af1a44..ace19c9ccd 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml @@ -3,14 +3,6 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - lumi_ue: - description: underlying event and relative luminosity uncertainty - treatment: ADD - type: STAR2009LUMIUE - pol: - description: polarization uncertainty - treatment: MULT - type: STAR2009POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -233,8 +225,6 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.007 - lumi_ue: 0.0005 - pol: 0.0001235 sys_0: -2.9341441875924853e-09 sys_1: 5.662769814057847e-09 sys_2: 3.947516339994088e-08 @@ -291,8 +281,6 @@ bins: sys_53: -1.338375509238332e-05 sys_54: -1.8477958927331985e-06 - stat: 0.007 - lumi_ue: 0.0005 - pol: -0.0004485 sys_0: -5.89864323557035e-09 sys_1: 1.1973393934428427e-08 sys_2: 7.77965450612318e-08 @@ -349,8 +337,6 @@ bins: sys_53: -1.9343984302625813e-05 sys_54: 3.5154212080782464e-07 - stat: 0.01 - lumi_ue: 0.0005 - pol: 0.001378 sys_0: -6.415581388921306e-09 sys_1: 1.409642897031362e-08 sys_2: 7.746596134549398e-08 @@ -407,8 +393,6 @@ bins: sys_53: -0.00018765877295429063 sys_54: -1.0501767095327602e-05 - stat: 0.019 - lumi_ue: 0.0005 - pol: 0.0027949999999999997 sys_0: -5.059630706571177e-08 sys_1: 1.2790135144982453e-07 sys_2: 6.01176495734771e-07 @@ -465,8 +449,6 @@ bins: sys_53: -1.4473789093860536e-05 sys_54: -1.744460748470315e-07 - stat: 0.05 - lumi_ue: 0.0005 - pol: 0.00507 sys_0: -2.4232685952842607e-07 sys_1: 1.0157362580817375e-06 sys_2: 1.7156500786764186e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml index 6fd70788e3..3f7c426fec 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml @@ -3,14 +3,6 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - lumi_ue: - description: underlying event and relative luminosity uncertainty - treatment: ADD - type: STAR2009LUMIUE - pol: - description: polarization uncertainty - treatment: MULT - type: STAR2009POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -233,8 +225,6 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.011 - lumi_ue: 0.0005 - pol: -0.001157 sys_0: -4.317226197359961e-06 sys_1: 2.804090271238005e-06 sys_2: 1.533190350417471e-05 @@ -291,8 +281,6 @@ bins: sys_53: 2.9019923821037516e-05 sys_54: 1.2745340133222563e-06 - stat: 0.005 - lumi_ue: 0.0005 - pol: 0.000377 sys_0: -5.884903801804573e-05 sys_1: 5.801735835150301e-05 sys_2: 0.00011332689636974533 @@ -349,8 +337,6 @@ bins: sys_53: 0.00051937351259702 sys_54: -0.00036216568701533277 - stat: 0.004 - lumi_ue: 0.0005 - pol: 0.000312 sys_0: -5.507588305445084e-09 sys_1: 1.0422018848183888e-08 sys_2: 7.492745940520344e-08 @@ -407,8 +393,6 @@ bins: sys_53: -0.0002080613662468662 sys_54: -4.071863554111754e-06 - stat: 0.004 - lumi_ue: 0.0005 - pol: 0.0001105 sys_0: -5.8862909005794415e-09 sys_1: 1.2100437882802023e-08 sys_2: 7.449799394325233e-08 @@ -465,8 +449,6 @@ bins: sys_53: 0.00010281804050324829 sys_54: 1.5989602302143824e-06 - stat: 0.006 - lumi_ue: 0.0005 - pol: -0.000507 sys_0: -1.1948431354375845e-08 sys_1: 3.0725225774569505e-08 sys_2: 1.312113102857246e-07 @@ -523,8 +505,6 @@ bins: sys_53: -9.456304860268702e-05 sys_54: -1.5931049017313595e-06 - stat: 0.008 - lumi_ue: 0.0005 - pol: 0.0006435000000000001 sys_0: -6.901268308944533e-08 sys_1: 2.527111324707297e-07 sys_2: 3.2856289314680365e-06 @@ -581,8 +561,6 @@ bins: sys_53: -3.188310734160565e-05 sys_54: -1.3725732071673286e-07 - stat: 0.03 - lumi_ue: 0.0005 - pol: 0.0007800000000000001 sys_0: -7.869315895733471e-06 sys_1: 2.713017354609144e-06 sys_2: 5.815729290616714e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml index ee8ba234fd..4fefae556b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml @@ -3,14 +3,6 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - lumi_ue: - description: underlying event and relative luminosity uncertainty - treatment: ADD - type: STAR2009LUMIUE - pol: - description: polarization uncertainty - treatment: MULT - type: STAR2009POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -233,8 +225,6 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.005 - lumi_ue: 0.0005 - pol: -0.000221 sys_0: -1.6474452057447053e-05 sys_1: 9.040581896830352e-06 sys_2: 4.939301509717896e-05 @@ -291,8 +281,6 @@ bins: sys_53: 4.8322028300353735e-05 sys_54: -8.91251641089161e-06 - stat: 0.004 - lumi_ue: 0.0005 - pol: 0.0008515 sys_0: -7.579309266019555e-05 sys_1: 8.447972227411008e-05 sys_2: 3.7685066658696415e-05 @@ -349,8 +337,6 @@ bins: sys_53: 0.00028783257955775033 sys_54: 0.0014311795851842514 - stat: 0.004 - lumi_ue: 0.0005 - pol: 0.0001755 sys_0: -1.8762642251501937e-09 sys_1: 3.276722365520518e-09 sys_2: 2.664323373190657e-08 @@ -407,8 +393,6 @@ bins: sys_53: 1.2846016161625068e-05 sys_54: -3.979748473480607e-07 - stat: 0.006 - lumi_ue: 0.0005 - pol: 0.000429 sys_0: -5.230393648390167e-09 sys_1: 9.685571349990864e-09 sys_2: 7.13083002753033e-08 @@ -465,8 +449,6 @@ bins: sys_53: 0.0013090275115244018 sys_54: -0.00018158932078184587 - stat: 0.01 - lumi_ue: 0.0005 - pol: 0.0013585 sys_0: -1.0615455135826602e-08 sys_1: 2.43565277357043e-08 sys_2: 1.3082616706064876e-07 @@ -523,8 +505,6 @@ bins: sys_53: -5.966696302632403e-05 sys_54: 1.3121741007973295e-06 - stat: 0.016 - lumi_ue: 0.0005 - pol: 0.000715 sys_0: -6.674311553948635e-08 sys_1: 2.697782974960404e-07 sys_2: 4.625984158618274e-06 @@ -581,8 +561,6 @@ bins: sys_53: -1.4471039490052424e-05 sys_54: 6.118109563228437e-07 - stat: 0.09 - lumi_ue: 0.0005 - pol: 0.002015 sys_0: -6.382584535818189e-06 sys_1: 1.0096067398392718e-06 sys_2: 3.330969685392803e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml index 434c52b454..02767a2758 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml @@ -3,10 +3,6 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - lumi_ue: - description: underlying event and relative luminosity uncertainty - treatment: ADD - type: STAR2009LUMIUE pol: description: polarization uncertainty treatment: MULT @@ -233,7 +229,6 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.0039 - lumi_ue: 0.0005 pol: 0.0003835 sys_0: -2.4909807848076024e-09 sys_1: 1.0306276400047151e-08 @@ -291,7 +286,6 @@ bins: sys_53: -3.1956730705631123e-06 sys_54: 8.925434186554094e-07 - stat: 0.0032 - lumi_ue: 0.0005 pol: 0.000624 sys_0: -5.399208818729837e-09 sys_1: 2.106015380160125e-08 @@ -349,7 +343,6 @@ bins: sys_53: 5.398687096072461e-06 sys_54: 1.1006575438375338e-06 - stat: 0.0037 - lumi_ue: 0.0005 pol: 0.000442 sys_0: -1.3873223784397754e-08 sys_1: 4.574933734784567e-08 @@ -407,7 +400,6 @@ bins: sys_53: 6.3501830570232405e-06 sys_54: 1.8230448120602087e-06 - stat: 0.005 - lumi_ue: 0.0005 pol: 0.0009815000000000002 sys_0: -1.224498053657377e-07 sys_1: 1.2446185563927494e-06 @@ -465,7 +457,6 @@ bins: sys_53: 9.979986784457061e-06 sys_54: 2.7259451131805867e-06 - stat: 0.0077 - lumi_ue: 0.0005 pol: 0.0005395 sys_0: -4.464585764699799e-06 sys_1: 7.515486287618491e-06 @@ -523,7 +514,6 @@ bins: sys_53: 6.114896621832628e-06 sys_54: 4.106894880501085e-06 - stat: 0.0109 - lumi_ue: 0.0005 pol: 0.000598 sys_0: -4.8651532448888784e-05 sys_1: 0.00011184863084290111 @@ -581,7 +571,6 @@ bins: sys_53: 3.436424253953748e-05 sys_54: 1.733884802347807e-05 - stat: 0.034 - lumi_ue: 0.0005 pol: -0.001833 sys_0: -0.00047294389784732977 sys_1: 0.000889086372938183 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml index bc1f0b4291..f84280586b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml @@ -3,10 +3,6 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR - lumi_ue: - description: underlying event and relative luminosity uncertainty - treatment: ADD - type: STAR2009LUMIUE pol: description: polarization uncertainty treatment: MULT @@ -233,7 +229,6 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.0034 - lumi_ue: 0.0005 pol: 0.0004355 sys_0: -1.274586879789524e-09 sys_1: 5.120321055524734e-09 @@ -291,7 +286,6 @@ bins: sys_53: -1.7999739025718109e-06 sys_54: 8.495918057916394e-07 - stat: 0.0032 - lumi_ue: 0.0005 pol: 0.000572 sys_0: -3.6587585471182742e-09 sys_1: 1.2867903197577332e-08 @@ -349,7 +343,6 @@ bins: sys_53: 4.70309896667795e-06 sys_54: 8.843608116711028e-07 - stat: 0.0039 - lumi_ue: 0.0005 pol: 0.001053 sys_0: -2.2418452806231772e-08 sys_1: 8.56576330626395e-08 @@ -407,7 +400,6 @@ bins: sys_53: 5.313311141396147e-06 sys_54: 1.3627906934601516e-06 - stat: 0.0056 - lumi_ue: 0.0005 pol: 0.000156 sys_0: -1.202385957826787e-06 sys_1: 2.444051286185078e-06 @@ -465,7 +457,6 @@ bins: sys_53: 1.1614574371297151e-05 sys_54: 2.9061112984790858e-06 - stat: 0.0089 - lumi_ue: 0.0005 pol: 0.0008449999999999999 sys_0: -6.892063114839857e-06 sys_1: 1.2152085596139124e-05 @@ -523,7 +514,6 @@ bins: sys_53: -0.000176896602349904 sys_54: -6.238930518606783e-05 - stat: 0.0133 - lumi_ue: 0.0005 pol: 0.0021839999999999997 sys_0: -8.139536176397123e-05 sys_1: 0.00015709281529534093 @@ -581,7 +571,6 @@ bins: sys_53: 3.3976525227495266e-05 sys_54: 1.9371823289380078e-05 - stat: 0.046 - lumi_ue: 0.0005 pol: 0.0049075 sys_0: -0.0004911530256875754 sys_1: 0.0010960053747405697 From 7241f99e2840faf6817dfcee164267452572ff62 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 6 May 2024 15:10:30 +0200 Subject: [PATCH 24/98] minor fixes on syntax --- .../filter_utils/star/jet_dijet_2009_200gev.py | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index 2621d62c62..89287134b2 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -1,4 +1,4 @@ -"""This script provides the common filer to the jet and dijet STAR 2012 datasets. +"""This script provides the common filer to the jet and dijet STAR 2009 datasets. Files need to be parsed all together as there are correlations provided. """ @@ -36,10 +36,10 @@ def read_1jet_data(): elif "ALL" in fname: df3["ALL"] = dfi["$A_{LL}$"] - df3["stat_min"] = dfi["stat +"] - df3["stat_max"] = dfi["stat -"] - df3["sys_min"] = dfi["sys +"] - df3["sys_max"] = dfi["sys -"] + df3["stat_min"] = dfi["stat -"] + df3["stat_max"] = dfi["stat +"] + df3["sys_min"] = dfi["sys -"] + df3["sys_max"] = dfi["sys +"] df3["abs_eta_min"] = 0.0 df3["abs_eta_max"] = 0.5 @@ -53,10 +53,10 @@ def read_1jet_data(): if "ALL" in fname: df4["ALL"] = dfi["$A_{LL}$"] - df4["stat_min"] = dfi["stat +"] - df4["stat_max"] = dfi["stat -"] - df4["sys_min"] = dfi["sys +"] - df4["sys_max"] = dfi["sys -"] + df3["stat_min"] = dfi["stat -"] + df3["stat_max"] = dfi["stat +"] + df3["sys_min"] = dfi["sys -"] + df3["sys_max"] = dfi["sys +"] df4["abs_eta_min"] = 0.5 df4["abs_eta_max"] = 1.0 From 65a2728e780745c046541cc693fded7f8a9b7511 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Mon, 6 May 2024 18:02:40 +0200 Subject: [PATCH 25/98] fix kinematic label --- .../star/jet_dijet_2009_200gev.py | 2 +- .../STAR_2009_1JET_200GEV/kinematics.yaml | 44 +++++++++---------- 2 files changed, 23 insertions(+), 23 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index 89287134b2..80737e8f85 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -158,7 +158,7 @@ def write_1jet_data(df, art_sys): kin_value = { "pT": {"min": None, "mid": float(df.loc[i, "pT"]), "max": None}, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, - "eta_abs": { + "abs_eta": { "min": float(df.loc[i, "abs_eta_min"]), "mid": float(df.loc[i, "abs_eta"]), "max": float(df.loc[i, "abs_eta_max"]), diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml index 2ccd4e689d..1fbf402f69 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml @@ -1,5 +1,5 @@ bins: -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -11,7 +11,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -23,7 +23,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -35,7 +35,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -47,7 +47,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -59,7 +59,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -71,7 +71,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -83,7 +83,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -95,7 +95,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -107,7 +107,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -119,7 +119,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 0.5 mid: 0.25 min: 0.0 @@ -131,7 +131,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -143,7 +143,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -155,7 +155,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -167,7 +167,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -179,7 +179,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -191,7 +191,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -203,7 +203,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -215,7 +215,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -227,7 +227,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -239,7 +239,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 @@ -251,7 +251,7 @@ bins: max: null mid: 200.0 min: null -- eta_abs: +- abs_eta: max: 1.0 mid: .nan min: 0.5 From 6b15c86a1f4e4c892a565a59138c3b8147e75792 Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Tue, 7 May 2024 18:24:04 +0200 Subject: [PATCH 26/98] fixed STAR2015 polarised error --- .../star/jet_dijet_2015_200gev.py | 34 +- .../STAR_2015_1JET_200GEV/uncertainties.yaml | 1620 ++++++++--------- .../uncertainties.yaml | 504 ++--- .../uncertainties.yaml | 502 ++--- 4 files changed, 1322 insertions(+), 1338 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py index 24bd837143..2f3ca569da 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -1,27 +1,20 @@ """This script provides the common filer to the jet and dijet STAR 2015 datasets. -Files need to be parsed all together as there are correlations provided. +Files need to be parsed all together as there are correlations provided. """ + import pathlib import numpy as np import pandas as pd import yaml -from nnpdf_data.filter_utils.correlations import ( - compute_covmat, - upper_triangular_to_symmetric, -) +from nnpdf_data.filter_utils.correlations import compute_covmat, upper_triangular_to_symmetric # values from the paper SQRTS = 200 YEAR = 2015 # mapping between topologies, tables and abs_eta values -TOPOPLOGY_LIST = { - "CC": ("bottom", 0, 0.5), - "CF": ("top", 0.5, 1.0), - "OS": "bottom", - "SS": "top", -} +TOPOPLOGY_LIST = {"CC": ("bottom", 0, 0.5), "CF": ("top", 0.5, 1.0), "OS": "bottom", "SS": "top"} # mapping between correlations blocks and tables MAP_CORR_TABLE = { @@ -48,9 +41,7 @@ def read_1jet_data(topology): data_table = pathlib.Path(RAWDATA_PATH / f"Table1{table_label}.csv") with open(data_table, "r", encoding="utf-8") as file: - parton_jet_data = pd.read_csv( - file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 20) - ) + parton_jet_data = pd.read_csv(file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 20)) with open(data_table, "r", encoding="utf-8") as file: all_data = pd.read_csv(file, delimiter=",", skiprows=21) @@ -68,7 +59,7 @@ def read_1jet_data(topology): df["stat"] = all_data["Stat +"] df["syst"] = all_data["Syst +"] df["lumi"] = all_data["Lumi +"] - df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] + df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] / 100 print(f"1JET {topology} data loaded. Npoint: ", len(df)) return df @@ -78,9 +69,7 @@ def read_2jet_data(topology): table_label = TOPOPLOGY_LIST[topology] data_table = RAWDATA_PATH / f"Table2{table_label}.csv" with open(data_table, "r", encoding="utf-8") as file: - mjj_data = pd.read_csv( - file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 16) - ) + mjj_data = pd.read_csv(file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 16)) with open(data_table, "r", encoding="utf-8") as file: all_data = pd.read_csv(file, delimiter=",", skiprows=27) @@ -116,8 +105,7 @@ def read_correlations(ndata_dict): try: idx = MAP_CORR_TABLE[(a, b)] with open( - RAWDATA_PATH / f"Table{idx}SupplementalMaterial.csv", - encoding="utf-8", + RAWDATA_PATH / f"Table{idx}SupplementalMaterial.csv", encoding="utf-8" ) as file: corr_df = pd.read_csv(file, delimiter=",", skiprows=7) @@ -234,11 +222,7 @@ def write_2jet_data(df, topology, art_sys): # Write unc file error = [] error_definition = { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - }, + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, "lumi": { "description": "luminosity uncertainty", "treatment": "ADD", diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml index 1f69454720..2a4d71159e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -152,839 +152,839 @@ definitions: treatment: ADD type: STAR2015JETunc35 bins: -- sys_0: -1.2124945963636329e-05 - sys_1: 3.99763242964474e-05 - sys_2: -2.073300487801316e-05 - sys_3: 7.834205546114172e-05 - sys_4: 3.1966508959996434e-05 - sys_5: -0.00016212580597664398 - sys_6: -3.329223918283098e-05 - sys_7: 0.0003907426485886462 - sys_8: -7.57733494001071e-05 - sys_9: -0.0012673253983827423 - sys_10: -6.583425325388493e-06 - sys_11: -0.0009992509466134449 - sys_12: -2.5990693050432402e-05 - sys_13: 9.004274285127836e-05 - sys_14: 0.00029905774861508277 - sys_15: -7.291388700896354e-05 - sys_16: -4.981686266952964e-06 - sys_17: -1.1402064553276121e-06 - sys_18: -0.0007621712345388461 - sys_19: 0.00035365632303836357 - sys_20: -0.0005674020577193097 - sys_21: -0.00015127498178572223 - sys_22: -4.645538440838408e-05 - sys_23: -0.0004750829986177542 - sys_24: -2.724483686647165e-06 - sys_25: -0.00015374802290947704 - sys_26: -2.4886388914460886e-05 - sys_27: -1.290655211071111e-05 - sys_28: -3.1585659631538674e-06 - sys_29: 1.5775767380939687e-05 - sys_30: 1.7213875527544255e-05 - sys_31: -1.395843375973772e-05 - sys_32: -1.786999568403126e-05 - sys_33: -3.0106496090811998e-05 - sys_34: -3.940821208479835e-05 - sys_35: -9.25488815805122e-07 +- sys_0: -1.2124945963638899e-05 + sys_1: 3.9976324296444724e-05 + sys_2: -2.0733004878014164e-05 + sys_3: 7.834205546115549e-05 + sys_4: 3.196650896000173e-05 + sys_5: -0.00016212580597664444 + sys_6: -3.329223918283013e-05 + sys_7: 0.00039074264858864955 + sys_8: -7.577334940010563e-05 + sys_9: -0.0012673253983827547 + sys_10: -6.5834253253902296e-06 + sys_11: -0.0009992509466134494 + sys_12: -2.599069305043419e-05 + sys_13: 9.004274285127735e-05 + sys_14: 0.0002990577486150853 + sys_15: -7.291388700896279e-05 + sys_16: -4.981686266952649e-06 + sys_17: -1.1402064553258713e-06 + sys_18: -0.0007621712345388191 + sys_19: 0.0003536563230383579 + sys_20: -0.0005674020577193189 + sys_21: -0.00015127498178577192 + sys_22: -4.6455384408380834e-05 + sys_23: -0.0004750829986177653 + sys_24: -2.7244836866484633e-06 + sys_25: -0.00015374802290948824 + sys_26: -2.4886388914476245e-05 + sys_27: -1.2906552110711854e-05 + sys_28: -3.1585659631543493e-06 + sys_29: 1.577576738094043e-05 + sys_30: 1.7213875527545438e-05 + sys_31: -1.3958433759737807e-05 + sys_32: -1.786999568403209e-05 + sys_33: -3.010649609081415e-05 + sys_34: -3.9408212084800554e-05 + sys_35: -9.254888158050854e-07 lumi: 0.0007 - pol: 0.00122 -- sys_0: -7.696816897816436e-06 - sys_1: 3.158329891762911e-05 - sys_2: -1.4276093639918046e-05 - sys_3: 6.169333966668052e-05 - sys_4: 2.1035544732149187e-05 - sys_5: -0.0001296267097279665 - sys_6: -2.469319063415189e-05 - sys_7: 0.0003323603878512561 - sys_8: -6.151316638347651e-05 - sys_9: -0.0011682933016762716 - sys_10: -1.6173817620833752e-06 - sys_11: -0.001002980672779371 - sys_12: -3.726356415949347e-05 - sys_13: 0.00015814714793294262 - sys_14: 0.0005157890356567223 - sys_15: -0.00011105294949067897 - sys_16: 2.431542171680724e-06 - sys_17: -3.259536612973891e-05 - sys_18: 0.0012116821445728556 - sys_19: -0.00012872984442436638 - sys_20: 4.6075647077754845e-05 - sys_21: 1.1874650017780699e-05 - sys_22: -6.966355590922665e-06 - sys_23: -0.0001553490815108954 - sys_24: 1.2262272658708402e-06 - sys_25: -6.50460128889597e-05 - sys_26: -9.716264579150592e-06 - sys_27: -5.408068697263476e-06 - sys_28: -1.528857585750034e-07 - sys_29: 8.889278652906262e-06 - sys_30: 9.238658643099643e-06 - sys_31: -5.623944708346205e-06 - sys_32: -1.0457196593776984e-05 - sys_33: -1.0460776050192041e-05 - sys_34: -1.205550817839274e-05 - sys_35: -1.7326915567916684e-06 + pol: 1.22e-05 +- sys_0: -7.696816897814303e-06 + sys_1: 3.158329891763058e-05 + sys_2: -1.427609363991523e-05 + sys_3: 6.169333966668702e-05 + sys_4: 2.1035544732151826e-05 + sys_5: -0.00012962670972797077 + sys_6: -2.4693190634150012e-05 + sys_7: 0.000332360387851255 + sys_8: -6.151316638347184e-05 + sys_9: -0.00116829330167627 + sys_10: -1.6173817620822485e-06 + sys_11: -0.0010029806727793722 + sys_12: -3.726356415949269e-05 + sys_13: 0.00015814714793294202 + sys_14: 0.0005157890356567245 + sys_15: -0.00011105294949067365 + sys_16: 2.431542171677333e-06 + sys_17: -3.259536612974199e-05 + sys_18: 0.0012116821445728545 + sys_19: -0.0001287298444243841 + sys_20: 4.6075647077778995e-05 + sys_21: 1.1874650017792035e-05 + sys_22: -6.966355590920094e-06 + sys_23: -0.00015534908151088617 + sys_24: 1.2262272658702433e-06 + sys_25: -6.50460128889601e-05 + sys_26: -9.716264579156666e-06 + sys_27: -5.408068697263694e-06 + sys_28: -1.5288575857520076e-07 + sys_29: 8.889278652906353e-06 + sys_30: 9.238658643099813e-06 + sys_31: -5.62394470834605e-06 + sys_32: -1.0457196593776938e-05 + sys_33: -1.0460776050192295e-05 + sys_34: -1.2055508178392816e-05 + sys_35: -1.732691556791367e-06 lumi: 0.0007 - pol: 0.0036599999999999996 -- sys_0: -8.928271882845198e-06 - sys_1: 3.2189485897211125e-05 - sys_2: -1.8072701944326597e-05 - sys_3: 6.114437754903917e-05 - sys_4: 2.905458190652082e-05 - sys_5: -0.0001231059473849797 - sys_6: -2.9432600909104633e-05 - sys_7: 0.00028115469540829197 - sys_8: -6.003952446277604e-05 - sys_9: -0.0008371018429280262 - sys_10: -6.000692453921972e-06 - sys_11: -0.0006084636977295246 - sys_12: -4.407044437745515e-06 - sys_13: 3.1165303330130325e-05 - sys_14: 0.0001264666140737965 - sys_15: -4.396380418811727e-05 - sys_16: -4.935869608986907e-06 - sys_17: -1.0752946669885328e-06 - sys_18: -0.0002135639309143538 - sys_19: 1.1497573337094799e-05 - sys_20: -1.946263805629447e-05 - sys_21: -8.55232797230304e-06 - sys_22: 5.308018139207472e-05 - sys_23: 0.00046731229352457406 - sys_24: 2.5972867462133868e-06 - sys_25: 0.0008426116190859175 - sys_26: 0.0001753080716717489 - sys_27: 9.492732198398632e-06 - sys_28: 1.3211574672996724e-05 - sys_29: 1.2007781967987451e-05 - 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pol: 0.14127599999999998 + pol: 0.0014127599999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml index 5906e64bab..af678d51f5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml @@ -156,276 +156,276 @@ definitions: treatment: ADD type: STAR2015JETunc35 bins: -- sys_0: -1.1061320396018662e-06 - sys_1: 2.1718755370553993e-06 - sys_2: -2.5830445253971692e-06 - sys_3: 3.6296783741788805e-06 - sys_4: 3.5884643423664896e-06 - sys_5: -6.340663553404027e-06 - sys_6: -2.932279047662183e-06 - sys_7: 9.301109570577263e-06 - sys_8: -5.512984728106772e-06 - sys_9: -2.0168914484542983e-05 - sys_10: -1.460838365633757e-06 - sys_11: -1.169925377265643e-05 - sys_12: 5.298324927138824e-06 - sys_13: -1.3450370231347285e-05 - sys_14: 4.62112884404096e-06 - 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sys_32: -3.378806930895894e-07 - sys_33: 2.2001974670195147e-06 - sys_34: -7.33634436311964e-07 - sys_35: -5.440401898597821e-06 +- sys_0: -0.000388010599675008 + sys_1: 0.0008640577953892642 + sys_2: -0.0001822661645697009 + sys_3: 0.0004948026664088063 + sys_4: -1.1974979766117766e-05 + sys_5: -4.236222645377295e-05 + sys_6: 2.4144845967006375e-05 + sys_7: -4.01755166736122e-05 + sys_8: -1.4822330889113779e-05 + sys_9: 2.1646542285667626e-05 + sys_10: -0.0031093657822061278 + sys_11: 1.1480090486317943e-06 + sys_12: -1.6568127898619448e-05 + sys_13: 7.117750166471685e-06 + sys_14: 5.79700518677154e-06 + sys_15: 1.5795616706962763e-05 + sys_16: -0.00019544597017715957 + sys_17: -2.698740213896772e-06 + sys_18: 3.918585153982622e-06 + sys_19: 3.74275098090469e-06 + sys_20: 9.250134750067683e-06 + sys_21: -4.4099092014109344e-05 + sys_22: -1.8878824597274617e-06 + sys_23: -8.699164389319797e-07 + sys_24: 2.420494314996309e-05 + sys_25: -3.715661520176191e-06 + sys_26: 1.749179619738466e-05 + sys_27: 3.5347304839725723e-07 + sys_28: 1.349183196534462e-07 + sys_29: -7.779631996595798e-08 + sys_30: 6.633292161656212e-07 + sys_31: 1.0549760343094488e-06 + sys_32: -3.3788069308952495e-07 + sys_33: 2.2001974670194707e-06 + sys_34: -7.336344363120756e-07 + sys_35: -5.4404018985978565e-06 stat: 0.0418 lumi: 0.0007 pol: 0.13908 From 8218129f8d519951949feb125c24597446012265 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 8 May 2024 09:38:57 +0200 Subject: [PATCH 27/98] apply same fix also to dijet --- .../star/jet_dijet_2015_200gev.py | 31 +- .../STAR_2015_1JET_200GEV/uncertainties.yaml | 1576 ++++++++--------- .../uncertainties.yaml | 518 +++--- .../uncertainties.yaml | 516 +++--- 4 files changed, 1329 insertions(+), 1312 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py index 2f3ca569da..54eff99e2b 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -8,13 +8,21 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.correlations import compute_covmat, upper_triangular_to_symmetric +from nnpdf_data.filter_utils.correlations import ( + compute_covmat, + upper_triangular_to_symmetric, +) # values from the paper SQRTS = 200 YEAR = 2015 # mapping between topologies, tables and abs_eta values -TOPOPLOGY_LIST = {"CC": ("bottom", 0, 0.5), "CF": ("top", 0.5, 1.0), "OS": "bottom", "SS": "top"} +TOPOPLOGY_LIST = { + "CC": ("bottom", 0, 0.5), + "CF": ("top", 0.5, 1.0), + "OS": "bottom", + "SS": "top", +} # mapping between correlations blocks and tables MAP_CORR_TABLE = { @@ -41,7 +49,9 @@ def read_1jet_data(topology): data_table = pathlib.Path(RAWDATA_PATH / f"Table1{table_label}.csv") with open(data_table, "r", encoding="utf-8") as file: - parton_jet_data = pd.read_csv(file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 20)) + parton_jet_data = pd.read_csv( + file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 20) + ) with open(data_table, "r", encoding="utf-8") as file: all_data = pd.read_csv(file, delimiter=",", skiprows=21) @@ -69,7 +79,9 @@ def read_2jet_data(topology): table_label = TOPOPLOGY_LIST[topology] data_table = RAWDATA_PATH / f"Table2{table_label}.csv" with open(data_table, "r", encoding="utf-8") as file: - mjj_data = pd.read_csv(file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 16)) + mjj_data = pd.read_csv( + file, delimiter=",", skiprows=lambda x: (x <= 6 or x >= 16) + ) with open(data_table, "r", encoding="utf-8") as file: all_data = pd.read_csv(file, delimiter=",", skiprows=27) @@ -82,7 +94,7 @@ def read_2jet_data(topology): df["stat"] = all_data["Stat +"] df["syst"] = all_data["Syst +"] df["lumi"] = all_data["Lumi +"] - df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] + df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] / 100 print(f"2JET {topology} data loaded. Npoint: ", len(df)) return df @@ -105,7 +117,8 @@ def read_correlations(ndata_dict): try: idx = MAP_CORR_TABLE[(a, b)] with open( - RAWDATA_PATH / f"Table{idx}SupplementalMaterial.csv", encoding="utf-8" + RAWDATA_PATH / f"Table{idx}SupplementalMaterial.csv", + encoding="utf-8", ) as file: corr_df = pd.read_csv(file, delimiter=",", skiprows=7) @@ -222,7 +235,11 @@ def write_2jet_data(df, topology, art_sys): # Write unc file error = [] error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, "lumi": { "description": "luminosity uncertainty", "treatment": "ADD", diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml index 2a4d71159e..60b5034dc8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -152,839 +152,839 @@ definitions: treatment: ADD type: STAR2015JETunc35 bins: -- sys_0: -1.2124945963638899e-05 - sys_1: 3.9976324296444724e-05 - sys_2: -2.0733004878014164e-05 - sys_3: 7.834205546115549e-05 - sys_4: 3.196650896000173e-05 - sys_5: -0.00016212580597664444 - sys_6: -3.329223918283013e-05 - sys_7: 0.00039074264858864955 - sys_8: -7.577334940010563e-05 - sys_9: -0.0012673253983827547 - sys_10: -6.5834253253902296e-06 - sys_11: -0.0009992509466134494 - sys_12: -2.599069305043419e-05 - sys_13: 9.004274285127735e-05 - sys_14: 0.0002990577486150853 - sys_15: -7.291388700896279e-05 - sys_16: -4.981686266952649e-06 - sys_17: -1.1402064553258713e-06 - sys_18: -0.0007621712345388191 - sys_19: 0.0003536563230383579 - sys_20: -0.0005674020577193189 - sys_21: -0.00015127498178577192 - sys_22: -4.6455384408380834e-05 - 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-7.779631996597293e-08 + sys_30: 6.633292161656245e-07 + sys_31: 1.054976034309479e-06 + sys_32: -3.378806930895894e-07 + sys_33: 2.2001974670195147e-06 + sys_34: -7.33634436311964e-07 + sys_35: -5.440401898597821e-06 stat: 0.0418 lumi: 0.0007 - pol: 0.13908 + pol: 0.0013908000000000002 From 637e7d818c63cb4ec79612f199d60ec7469fe940 Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Tue, 14 May 2024 15:50:04 +0200 Subject: [PATCH 28/98] STAR_2012 correct correlations --- .../STAR_2012_1JET_510GEV/uncertainties.yaml | 1670 ++++++++--------- .../uncertainties.yaml | 1228 ++++++------ .../uncertainties.yaml | 1334 ++++++------- .../uncertainties.yaml | 1224 ++++++------ .../uncertainties.yaml | 1344 ++++++------- 5 files changed, 3400 insertions(+), 3400 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml index c882bbfc92..c739bb1293 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml @@ -10,1037 +10,1037 @@ definitions: sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc0 + type: STAR2012JETunc0 sys_1: description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc1 + type: STAR2012JETunc1 sys_2: description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc2 + type: STAR2012JETunc2 sys_3: description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD - type: 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systematics uncertainty treatment: ADD - type: STAR2013JETunc32 + type: STAR2012JETunc32 sys_33: description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc33 + type: STAR2012JETunc33 sys_34: description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc34 + type: STAR2012JETunc34 sys_35: description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD - type: 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a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml @@ -14,815 +14,815 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc0 + type: STAR2012JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc1 + type: STAR2012JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc2 + type: STAR2012JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc25 + type: STAR2012JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc26 + type: STAR2012JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc27 + type: STAR2012JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc28 + type: STAR2012JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc29 + type: STAR2012JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc30 + type: STAR2012JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc31 + type: STAR2012JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc32 + type: STAR2012JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc33 + type: STAR2012JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc34 + type: STAR2012JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc45 + type: STAR2012JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc46 + type: STAR2012JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc47 + type: STAR2012JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc48 + type: STAR2012JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc49 + type: STAR2012JETunc49 sys_50: description: 50 artificial correlated systematics 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treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc25 + type: STAR2012JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc26 + type: STAR2012JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc27 + type: STAR2012JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc28 + type: STAR2012JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc29 + type: STAR2012JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc30 + type: STAR2012JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc31 + type: STAR2012JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc32 + type: STAR2012JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc33 + type: STAR2012JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc34 + type: STAR2012JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc45 + type: STAR2012JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc46 + type: STAR2012JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc47 + type: 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sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 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5.937089612155706e-07 + sys_40: 6.162087831629744e-07 + sys_41: 9.206009972349796e-08 + sys_42: 4.8342680643373803e-08 + sys_43: -9.355065654867285e-09 + sys_44: 6.393413859155355e-08 + sys_45: -4.6977023058533314e-08 + sys_46: -1.4995361978283547e-08 + sys_47: -3.041193870623935e-07 + sys_48: 8.54692434612174e-08 + sys_49: -1.8316145562561607e-08 + sys_50: 6.202278518462283e-08 + sys_51: -1.649431626782716e-08 + sys_52: 1.1828217804672864e-08 + sys_53: -4.714010101532377e-09 + sys_54: -9.52101868262452e-09 + sys_55: -7.908290426298496e-09 From 72e496982baaf420e4be8ce954bffd9008345318 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 14 May 2024 16:05:57 +0200 Subject: [PATCH 29/98] correct wrong year label --- .../star/jet_dijet_2012_510gev.py | 4 +- .../STAR_2012_1JET_510GEV/uncertainties.yaml | 112 +++++++++--------- .../uncertainties.yaml | 112 +++++++++--------- .../uncertainties.yaml | 112 +++++++++--------- .../uncertainties.yaml | 112 +++++++++--------- .../uncertainties.yaml | 112 +++++++++--------- 6 files changed, 282 insertions(+), 282 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py index c932252b5b..a5e6c95dd2 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py @@ -175,7 +175,7 @@ def write_1jet_data(df, art_sys): f"sys_{j}": { "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", - "type": f"STAR2013JETunc{j}", + "type": f"STAR{YEAR}JETunc{j}", } for j in range(len(sys_i)) } @@ -246,7 +246,7 @@ def write_2jet_data(df, topology, art_sys): f"sys_{j}": { "description": f"{j} artificial correlated systematics uncertainty", "treatment": "ADD", - "type": f"STAR2013JETunc{j}", + "type": f"STAR{YEAR}JETunc{j}", } for j in range(len(sys_i)) } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml index c882bbfc92..e533032f69 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml @@ -10,227 +10,227 @@ definitions: sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc0 + type: STAR2012JETunc0 sys_1: description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc1 + type: STAR2012JETunc1 sys_2: description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc2 + type: STAR2012JETunc2 sys_3: description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc25 + type: STAR2012JETunc25 sys_26: description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc26 + type: STAR2012JETunc26 sys_27: description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc27 + type: STAR2012JETunc27 sys_28: description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc28 + type: STAR2012JETunc28 sys_29: description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc29 + type: STAR2012JETunc29 sys_30: description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc30 + type: STAR2012JETunc30 sys_31: description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc31 + type: STAR2012JETunc31 sys_32: description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc32 + type: STAR2012JETunc32 sys_33: description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc33 + type: STAR2012JETunc33 sys_34: description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc34 + type: STAR2012JETunc34 sys_35: description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc45 + type: STAR2012JETunc45 sys_46: description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc46 + type: STAR2012JETunc46 sys_47: description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc47 + type: STAR2012JETunc47 sys_48: description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc48 + type: STAR2012JETunc48 sys_49: description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc49 + type: STAR2012JETunc49 sys_50: description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc50 + type: STAR2012JETunc50 sys_51: description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc51 + type: STAR2012JETunc51 sys_52: description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc52 + type: STAR2012JETunc52 sys_53: description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc53 + type: STAR2012JETunc53 sys_54: description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc54 + type: STAR2012JETunc54 sys_55: description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD - type: STAR2013JETunc55 + type: STAR2012JETunc55 bins: - lumi_ue: 0.000364 pol: 1.1285999999999999e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml index f64d5a79c9..2f625a214c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml @@ -14,227 +14,227 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc0 + type: STAR2012JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc1 + type: STAR2012JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc2 + type: STAR2012JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc25 + type: STAR2012JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc26 + type: STAR2012JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc27 + type: STAR2012JETunc27 sys_28: description: 28 artificial 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type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc45 + type: STAR2012JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc46 + type: STAR2012JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc47 + type: STAR2012JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc48 + type: STAR2012JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc49 + type: STAR2012JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc50 + type: STAR2012JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc51 + type: STAR2012JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc52 + type: STAR2012JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc53 + type: STAR2012JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc54 + type: STAR2012JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc55 + type: STAR2012JETunc55 bins: - stat: 0.0066 lumi_ue: 0.00025 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml index a33894ad64..d40de5b28b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml @@ -14,227 +14,227 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc0 + type: STAR2012JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc1 + type: STAR2012JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc2 + type: STAR2012JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc25 + type: STAR2012JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc26 + type: STAR2012JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc27 + type: STAR2012JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc28 + type: STAR2012JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc29 + type: STAR2012JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc30 + type: STAR2012JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc31 + type: STAR2012JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc32 + type: STAR2012JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc33 + type: STAR2012JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc34 + type: STAR2012JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc45 + type: STAR2012JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc46 + type: STAR2012JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc47 + type: STAR2012JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc48 + type: STAR2012JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc49 + type: STAR2012JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc50 + type: STAR2012JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc51 + type: STAR2012JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc52 + type: STAR2012JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc53 + type: STAR2012JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc54 + type: STAR2012JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc55 + type: STAR2012JETunc55 bins: - stat: 0.0053 lumi_ue: 0.0004 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml index 16fe89f45b..0e9803b6f5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml @@ -14,227 +14,227 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc0 + type: STAR2012JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc1 + type: STAR2012JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc2 + type: STAR2012JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc25 + type: STAR2012JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc26 + type: STAR2012JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc27 + type: STAR2012JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc28 + type: STAR2012JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc29 + type: STAR2012JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc30 + type: STAR2012JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc31 + type: STAR2012JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc32 + type: STAR2012JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc33 + type: STAR2012JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc34 + type: STAR2012JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc45 + type: STAR2012JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc46 + type: STAR2012JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc47 + type: STAR2012JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc48 + type: STAR2012JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc49 + type: STAR2012JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc50 + type: STAR2012JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc51 + type: STAR2012JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc52 + type: STAR2012JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc53 + type: STAR2012JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc54 + type: STAR2012JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc55 + type: STAR2012JETunc55 bins: - stat: 0.0085 lumi_ue: 0.00026 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml index 38e92da673..7af2a2253a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml @@ -14,227 +14,227 @@ definitions: sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc0 + type: STAR2012JETunc0 sys_1: description: 1 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc1 + type: STAR2012JETunc1 sys_2: description: 2 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc2 + type: STAR2012JETunc2 sys_3: description: 3 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc3 + type: STAR2012JETunc3 sys_4: description: 4 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc4 + type: STAR2012JETunc4 sys_5: description: 5 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc5 + type: STAR2012JETunc5 sys_6: description: 6 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc6 + type: STAR2012JETunc6 sys_7: description: 7 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc7 + type: STAR2012JETunc7 sys_8: description: 8 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc8 + type: STAR2012JETunc8 sys_9: description: 9 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc9 + type: STAR2012JETunc9 sys_10: description: 10 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc10 + type: STAR2012JETunc10 sys_11: description: 11 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc11 + type: STAR2012JETunc11 sys_12: description: 12 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc12 + type: STAR2012JETunc12 sys_13: description: 13 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc13 + type: STAR2012JETunc13 sys_14: description: 14 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc14 + type: STAR2012JETunc14 sys_15: description: 15 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc15 + type: STAR2012JETunc15 sys_16: description: 16 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc16 + type: STAR2012JETunc16 sys_17: description: 17 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc17 + type: STAR2012JETunc17 sys_18: description: 18 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc18 + type: STAR2012JETunc18 sys_19: description: 19 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc19 + type: STAR2012JETunc19 sys_20: description: 20 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc20 + type: STAR2012JETunc20 sys_21: description: 21 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc21 + type: STAR2012JETunc21 sys_22: description: 22 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc22 + type: STAR2012JETunc22 sys_23: description: 23 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc23 + type: STAR2012JETunc23 sys_24: description: 24 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc24 + type: STAR2012JETunc24 sys_25: description: 25 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc25 + type: STAR2012JETunc25 sys_26: description: 26 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc26 + type: STAR2012JETunc26 sys_27: description: 27 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc27 + type: STAR2012JETunc27 sys_28: description: 28 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc28 + type: STAR2012JETunc28 sys_29: description: 29 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc29 + type: STAR2012JETunc29 sys_30: description: 30 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc30 + type: STAR2012JETunc30 sys_31: description: 31 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc31 + type: STAR2012JETunc31 sys_32: description: 32 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc32 + type: STAR2012JETunc32 sys_33: description: 33 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc33 + type: STAR2012JETunc33 sys_34: description: 34 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc34 + type: STAR2012JETunc34 sys_35: description: 35 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc35 + type: STAR2012JETunc35 sys_36: description: 36 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc36 + type: STAR2012JETunc36 sys_37: description: 37 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc37 + type: STAR2012JETunc37 sys_38: description: 38 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc38 + type: STAR2012JETunc38 sys_39: description: 39 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc39 + type: STAR2012JETunc39 sys_40: description: 40 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc40 + type: STAR2012JETunc40 sys_41: description: 41 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc41 + type: STAR2012JETunc41 sys_42: description: 42 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc42 + type: STAR2012JETunc42 sys_43: description: 43 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc43 + type: STAR2012JETunc43 sys_44: description: 44 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc44 + type: STAR2012JETunc44 sys_45: description: 45 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc45 + type: STAR2012JETunc45 sys_46: description: 46 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc46 + type: STAR2012JETunc46 sys_47: description: 47 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc47 + type: STAR2012JETunc47 sys_48: description: 48 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc48 + type: STAR2012JETunc48 sys_49: description: 49 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc49 + type: STAR2012JETunc49 sys_50: description: 50 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc50 + type: STAR2012JETunc50 sys_51: description: 51 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc51 + type: STAR2012JETunc51 sys_52: description: 52 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc52 + type: STAR2012JETunc52 sys_53: description: 53 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc53 + type: STAR2012JETunc53 sys_54: description: 54 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc54 + type: STAR2012JETunc54 sys_55: description: 55 artificial correlated systematics uncertainty treatment: ADD - type: STAR2013JETunc55 + type: STAR2012JETunc55 bins: - stat: 0.0161 lumi_ue: 0.00131 From 1b9a9cf9d41a882387256ce970f8039c83f9d190 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 14 May 2024 16:17:20 +0200 Subject: [PATCH 30/98] fix metadata --- .../new_commondata/STAR_2012_1JET_510GEV/metadata.yaml | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml index 273c010c6f..4095a4de8c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml @@ -5,9 +5,9 @@ nnpdf_metadata: nnpdf31_process: "JETS" iNSPIRE: - url: "https://inspirehep.net/literature/1493842" + url: "https://inspirehep.net/literature/1738738" hepdata: - url: "https://www.hepdata.net/record/ins1493842" + url: "https://www.hepdata.net/record/ins1738738" version: 1 arXiv: url: https://arxiv.org/abs/1906.02740 From de2a0650f8ddf25df3f23bf6f16eba420261dbaf Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 15 May 2024 13:35:05 +0200 Subject: [PATCH 31/98] init restore older filters --- .../nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py | 2 +- .../nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py | 2 +- .../new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py | 2 +- .../nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py | 2 +- .../nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py | 2 +- .../new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py | 2 +- .../new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py | 2 +- .../new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py | 2 +- .../new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py | 2 +- .../new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py | 2 +- 10 files changed, 10 insertions(+), 10 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py index b3442e89bd..ff222f5fea 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py index 47dee7baba..0655765b51 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py index 6798d7ae1b..37b78e0988 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py @@ -2,7 +2,7 @@ from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py index 85063e274e..b114623b64 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py @@ -5,7 +5,7 @@ import yaml from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py index 5e8c5db0bb..8643d38b07 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py @@ -4,7 +4,7 @@ from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py index 19325631d1..7f19469816 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py @@ -4,7 +4,7 @@ import yaml from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py index a3923e6b9f..ecf4dff877 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py @@ -4,7 +4,7 @@ import yaml from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py index b86614b230..e6c5b3fa0b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py index f992b7a8e6..1804a8e969 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py index dd930278b2..ce56dd4dab 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): From b262ebbcba0688ead6cb188c97f50cd3e7bb344f Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 15 May 2024 13:39:02 +0200 Subject: [PATCH 32/98] resotre previous atlas utils --- .../star/jet_dijet_2009_200gev.py | 2 +- .../ATLAS_TTBAR_13TEV_HADR_DIF/utils.py | 23 +++++++++++++++++++ .../CMS_TTBAR_8TEV_2L_DIF/filter.py | 2 +- 3 files changed, 25 insertions(+), 2 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index 80737e8f85..a22f88ab01 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -260,7 +260,7 @@ def write_2jet_data(df, topology, art_sys): "pol": { "description": "polarization uncertainty", "treatment": "MULT", - "type": f"STAR2009POL", + "type": "STAR2009POL", }, } # loop on data points diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py index 756b13f18c..def2a4f689 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py @@ -19,6 +19,29 @@ import numpy as np from numpy.linalg import eig + +def symmetrize_errors(delta_plus, delta_minus): + r"""Compute the symmterized uncertainty and the shift in data point. + Parameters + ---------- + delta_plus : float + The top/plus uncertainty with sign + delta_minus : float + The bottom/minus uncertainty with sign + Returns + ------- + se_delta : float + The value to be added to the data point + se_sigma : float + The symmetrized uncertainty to be used in commondata + """ + semi_diff = (delta_plus + delta_minus) / 2 + average = (delta_plus - delta_minus) / 2 + se_delta = semi_diff + se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff) + return se_delta, se_sigma + + def percentage_to_absolute(percentage, value): r"""Compute the absolute value of uncertainty from percentage. diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py index 8643d38b07..0cd577753c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py @@ -4,7 +4,7 @@ from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import trimat_to_fullmat as ttf def processData(): From 77ca9bbc20107f8c0d565b6fbec3f94ca4151a9c Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 15 May 2024 13:39:50 +0200 Subject: [PATCH 33/98] resotre previous atlas utils --- .../new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py | 3 +++ 1 file changed, 3 insertions(+) diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py index def2a4f689..dac59de537 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py @@ -22,18 +22,21 @@ def symmetrize_errors(delta_plus, delta_minus): r"""Compute the symmterized uncertainty and the shift in data point. + Parameters ---------- delta_plus : float The top/plus uncertainty with sign delta_minus : float The bottom/minus uncertainty with sign + Returns ------- se_delta : float The value to be added to the data point se_sigma : float The symmetrized uncertainty to be used in commondata + """ semi_diff = (delta_plus + delta_minus) / 2 average = (delta_plus - delta_minus) / 2 From 0ab33c1cfb34d41bc8de6b80ca6d676228b9bea3 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 15 May 2024 13:43:27 +0200 Subject: [PATCH 34/98] more cleaning --- .../nnpdf_data/filter_utils/manipulate.py | 21 ------------------- 1 file changed, 21 deletions(-) delete mode 100644 nnpdf_data/nnpdf_data/filter_utils/manipulate.py diff --git a/nnpdf_data/nnpdf_data/filter_utils/manipulate.py b/nnpdf_data/nnpdf_data/filter_utils/manipulate.py deleted file mode 100644 index 4fd31eae71..0000000000 --- a/nnpdf_data/nnpdf_data/filter_utils/manipulate.py +++ /dev/null @@ -1,21 +0,0 @@ - -def concatenate_dicts(multidict: list[dict]) -> dict: - """Given a list of dictionaries combined the values. - - Parameters - ---------- - multidict: list[dict] - list of dictionaries with the same keys - - Returns - ------- - dict: - dictionary whose keys are combined - """ - new_dict = {} - for key in multidict[0].keys(): - new_dict[key] = [] - for element in multidict: - new_dict[key] += element[key] - - return new_dict \ No newline at end of file From 533afecd4948cd4b429289069ae6d532343b95e6 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 15 May 2024 16:44:13 +0200 Subject: [PATCH 35/98] init renaming of DY star datasets --- .../data_wm.yaml} | 0 .../data_wp.yaml} | 0 .../filter.py | 41 +++++---- .../kinematics_wm.yaml} | 0 .../kinematics_wp.yaml} | 0 .../STAR_WMWP_510GEV/metadata.yaml | 90 +++++++++++++++++++ ...orW^+rightarrowe^+,combineddatasamples.csv | 0 ...orW^-rightarrowe^-,combineddatasamples.csv | 0 .../uncertainties_wm.yaml} | 0 .../uncertainties_wp.yaml} | 0 .../STAR_WM_510GEV/metadata.yaml | 54 ----------- .../new_commondata/STAR_WP_510GEV/filter.py | 60 ------------- .../STAR_WP_510GEV/metadata.yaml | 54 ----------- 13 files changed, 114 insertions(+), 185 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WM_510GEV/data.yaml => STAR_WMWP_510GEV/data_wm.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WP_510GEV/data.yaml => STAR_WMWP_510GEV/data_wp.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WM_510GEV => STAR_WMWP_510GEV}/filter.py (55%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WM_510GEV/kinematics.yaml => STAR_WMWP_510GEV/kinematics_wm.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WP_510GEV/kinematics.yaml => STAR_WMWP_510GEV/kinematics_wp.yaml} (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WP_510GEV => STAR_WMWP_510GEV}/rawdata/Figure5,A_LforW^+rightarrowe^+,combineddatasamples.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WM_510GEV => STAR_WMWP_510GEV}/rawdata/Figure5,A_LforW^-rightarrowe^-,combineddatasamples.csv (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WM_510GEV/uncertainties.yaml => STAR_WMWP_510GEV/uncertainties_wm.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_WP_510GEV/uncertainties.yaml => STAR_WMWP_510GEV/uncertainties_wp.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/filter.py delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/metadata.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/data_wm.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/data_wm.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/data_wp.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/data_wp.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/filter.py similarity index 55% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/filter.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/filter.py index 55841646fc..682767e90b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/filter.py @@ -1,5 +1,3 @@ -import glob - import pandas as pd import yaml @@ -7,19 +5,17 @@ MW = 80.398 -def read_data(fnames): - df = pd.DataFrame() - for fname in fnames: - df = pd.read_csv(fname, delimiter=",", skiprows=10) - df["M2"] = MW**2 - df["sqrts"] = ECM +def read_data(fname): + df = pd.read_csv(fname, delimiter=",", skiprows=10) + df["M2"] = MW**2 + df["sqrts"] = ECM return df -def write_data(df): +def write_data(df, boson): data_central = df["$A_L$"].tolist() data_central_yaml = {"data_central": data_central} - with open("data.yaml", "w", encoding="utf-8") as file: + with open(f"data_{boson}.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file, sort_keys=False) # Write kin file @@ -33,7 +29,7 @@ def write_data(df): kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open("kinematics.yaml", "w", encoding="utf-8") as file: + with open(f"kinematics_{boson}.yaml", "w", encoding="utf-8") as file: yaml.dump(kinematics_yaml, file, sort_keys=False) # Write unc file @@ -44,17 +40,28 @@ def write_data(df): error.append(e) error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "sys": { + "description": "systematic uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, } uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open("uncertainties.yaml", "w", encoding="utf-8") as file: + with open(f"uncertainties_{boson}.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) if __name__ == "__main__": - fnames = glob.glob("rawdata/*.csv") - df = read_data(fnames) - write_data(df) + # Wp + df = read_data("rawdata/Figure5,A_LforW^+rightarrowe^+,combineddatasamples.csv") + write_data(df, boson="wp") + # Wm + df = read_data("rawdata/Figure5,A_LforW^-rightarrowe^-,combineddatasamples.csv") + write_data(df, boson="wm") diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/kinematics_wm.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/kinematics_wm.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/kinematics_wp.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/kinematics_wp.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml new file mode 100644 index 0000000000..450e8bb43f --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml @@ -0,0 +1,90 @@ +# Generalia +setname: "STAR_WMWP_510GEV" + +version: 1 +version_comment: "Initial implementation" + +# References +arXiv: + url: "https://arxiv.org/abs/1812.04817" +iNSPIRE: + url: "https://inspirehep.net/literature/1708793" +hepdata: + url: "https://www.hepdata.net/record/ins1708793" + +nnpdf_metadata: + nnpdf31_process: "DY CC" + experiment: "STAR" + +implemented_observables: + - observable_name: "WM-AL" + observable: + description: "Longitudinal single-spin asymmetry $A_L$ for $W^-$ production as a function of the lepton pseudorapidity, $\eta_e$" + label: "$A_L$" + units: "" + process_type: "EWK_RAP" + ndata: 6 + tables: [5] + npoints: [6] + + # Plotting information + plotting: + kinematics_override: ewk_rap_sqrt_scale + dataset_label: "STAR $W^{-} \rightarrow e^{-}$" + y_label: "$A_L(\eta_{e})$" + plot_x: eta + line_by: [] + figure_by: [] + kinematic_coverage: [eta, M2, sqrts] + + kinematics: + variables: + eta: { description: "Lepton pseudorapidity", label: '$\eta$', units: "" } + M2: { description: "W boson Mass", label: "$M^2$", units: "$GeV^2$" } + sqrts: { description: "Center of Mass Energy", label: '$\sqrt{s}$', units: "$GeV$" } + file: kinematics_wm.yaml + + data_central: data_wm.yaml + data_uncertainties: + - uncertainties_wm.yaml + + theory: + FK_tables: + - - STAR_WMWP_510GEV_WM-AL + operation: "null" + + - observable_name: "WP-AL" + observable: + description: "Longitudinal single-spin asymmetry $A_L$ for $W^+$ production as a function of the lepton pseudorapidity, $\eta_e$" + label: "$A_L$" + units: "" + process_type: "EWK_RAP" + ndata: 6 + tables: [5] + npoints: [6] + + # Plotting information + plotting: + kinematics_override: ewk_rap_sqrt_scale + dataset_label: "STAR $W^{+} \rightarrow e^{+}$" + y_label: "$A_L(\eta_{e})$" + plot_x: eta + line_by: [] + figure_by: [] + kinematic_coverage: [eta, M2, sqrts] + + kinematics: + variables: + eta: { description: "Lepton pseudorapidity", label: '$\eta$', units: "" } + M2: { description: "W boson Mass", label: "$M^2$", units: "$GeV^2$" } + sqrts: { description: "Center of Mass Energy", label: '$\sqrt{s}$', units: "$GeV$" } + file: kinematics_wp.yaml + + data_central: data_wp.yaml + data_uncertainties: + - uncertainties_wp.yaml + + theory: + FK_tables: + - - STAR_WMWP_510GEV_WP-AL + operation: "null" diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/rawdata/Figure5,A_LforW^+rightarrowe^+,combineddatasamples.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/Figure5,A_LforW^+rightarrowe^+,combineddatasamples.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/rawdata/Figure5,A_LforW^+rightarrowe^+,combineddatasamples.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/Figure5,A_LforW^+rightarrowe^+,combineddatasamples.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/rawdata/Figure5,A_LforW^-rightarrowe^-,combineddatasamples.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/Figure5,A_LforW^-rightarrowe^-,combineddatasamples.csv similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/rawdata/Figure5,A_LforW^-rightarrowe^-,combineddatasamples.csv rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/Figure5,A_LforW^-rightarrowe^-,combineddatasamples.csv diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wm.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wm.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wp.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wp.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/metadata.yaml deleted file mode 100644 index eec81d1380..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WM_510GEV/metadata.yaml +++ /dev/null @@ -1,54 +0,0 @@ -# Generalia -setname: "STAR_WM_510GEV" - -version: 1 -version_comment: "Initial implementation" - -# References -arXiv: - url: "https://arxiv.org/abs/1812.04817" -iNSPIRE: - url: "https://inspirehep.net/literature/1708793" -hepdata: - url: "https://www.hepdata.net/record/ins1708793" - -nnpdf_metadata: - nnpdf31_process: "DY CC" - experiment: "STAR" - -implemented_observables: - - observable_name: "AL" - observable: - description: "Longitudinal single-spin asymmetry $A_L$ for $W^-$ production as a function of the lepton pseudorapidity, $\eta_e$" - label: "$A_L$" - units: "" - process_type: "EWK_RAP" - ndata: 6 - tables: [5] - npoints: [6] - - # Plotting information - plotting: - kinematics_override: ewk_rap_sqrt_scale - dataset_label: "STAR $W^{-} \rightarrow e^{-}$" - y_label: "$A_L(\eta_{e})$" - plot_x: eta - line_by: [] - figure_by: [] - kinematic_coverage: [eta, M2, sqrts] - - kinematics: - variables: - eta: { description: "Lepton pseudorapidity", label: '$\eta$', units: "" } - M2: { description: "W boson Mass", label: "$M^2$", units: "$GeV^2$" } - sqrts: { description: "Center of Mass Energy", label: '$\sqrt{s}$', units: "$GeV$" } - file: kinematics.yaml - - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - - theory: - FK_tables: - - - STAR_WM_510GEV_AL - operation: "null" diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/filter.py deleted file mode 100644 index 55841646fc..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/filter.py +++ /dev/null @@ -1,60 +0,0 @@ -import glob - -import pandas as pd -import yaml - -ECM = 510 -MW = 80.398 - - -def read_data(fnames): - df = pd.DataFrame() - for fname in fnames: - df = pd.read_csv(fname, delimiter=",", skiprows=10) - df["M2"] = MW**2 - df["sqrts"] = ECM - return df - - -def write_data(df): - data_central = df["$A_L$"].tolist() - data_central_yaml = {"data_central": data_central} - with open("data.yaml", "w", encoding="utf-8") as file: - yaml.dump(data_central_yaml, file, sort_keys=False) - - # Write kin file - kin = [] - for i in range(len(df)): - kin_value = { - "eta": {"min": None, "mid": float(df.loc[i, "$\eta_e$"]), "max": None}, - "M2": {"min": None, "mid": float(df.loc[i, "M2"]), "max": None}, - "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, - } - kin.append(kin_value) - kinematics_yaml = {"bins": kin} - - with open("kinematics.yaml", "w", encoding="utf-8") as file: - yaml.dump(kinematics_yaml, file, sort_keys=False) - - # Write unc file - error = [] - for i in range(len(df)): - # here uncertainties are symmetric - e = {"stat": float(df.loc[i, "stat +"]), "sys": float(df.loc[i, "syst +"])} - error.append(e) - - error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, - } - - uncertainties_yaml = {"definitions": error_definition, "bins": error} - - with open("uncertainties.yaml", "w", encoding="utf-8") as file: - yaml.dump(uncertainties_yaml, file, sort_keys=False) - - -if __name__ == "__main__": - fnames = glob.glob("rawdata/*.csv") - df = read_data(fnames) - write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/metadata.yaml deleted file mode 100644 index 67fb18f0f3..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WP_510GEV/metadata.yaml +++ /dev/null @@ -1,54 +0,0 @@ -# Generalia -setname: "STAR_WP_510GEV" - -version: 1 -version_comment: "Initial implementation" - -# References -arXiv: - url: "https://arxiv.org/abs/1812.04817" -iNSPIRE: - url: "https://inspirehep.net/literature/1708793" -hepdata: - url: "https://www.hepdata.net/record/ins1708793" - -nnpdf_metadata: - nnpdf31_process: "DY CC" - experiment: "STAR" - -implemented_observables: - - observable_name: "AL" - observable: - description: "Longitudinal single-spin asymmetry $A_L$ for $W^+$ production as a function of the lepton pseudorapidity, $\eta_e$" - label: "$A_L$" - units: "" - process_type: "EWK_RAP" - ndata: 6 - tables: [5] - npoints: [6] - - # Plotting information - plotting: - kinematics_override: ewk_rap_sqrt_scale - dataset_label: "STAR $W^{+} \rightarrow e^{+}$" - y_label: "$A_L(\eta_{e})$" - plot_x: eta - line_by: [] - figure_by: [] - kinematic_coverage: [eta, M2, sqrts] - - kinematics: - variables: - eta: { description: "Lepton pseudorapidity", label: '$\eta$', units: "" } - M2: { description: "W boson Mass", label: "$M^2$", units: "$GeV^2$" } - sqrts: { description: "Center of Mass Energy", label: '$\sqrt{s}$', units: "$GeV$" } - file: kinematics.yaml - - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - - theory: - FK_tables: - - - STAR_WP_510GEV_AL - operation: "null" From 77b1e60964bf6d00a62c6d30e3dfda119039cdac Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 16 May 2024 09:41:20 +0200 Subject: [PATCH 36/98] Add beam polarization unc --- .../new_commondata/STAR_WMWP_510GEV/filter.py | 20 ++++++++++++++++++- .../STAR_WMWP_510GEV/uncertainties_wm.yaml | 10 ++++++++++ .../STAR_WMWP_510GEV/uncertainties_wp.yaml | 10 ++++++++++ 3 files changed, 39 insertions(+), 1 deletion(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/filter.py index 682767e90b..3e73c56d19 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/filter.py @@ -1,14 +1,23 @@ +"""This script provides the common filer to the DY, WP, WM combined STAR 2011-2013 datasets. + +NOTE: + * The beam polarization uncertainty are not included in the systematics, + so it is added manually. + * Correlation are provided only for the 20213 data, so are not included. +""" import pandas as pd import yaml ECM = 510 MW = 80.398 +POL_UNC = 0.033 def read_data(fname): df = pd.read_csv(fname, delimiter=",", skiprows=10) df["M2"] = MW**2 df["sqrts"] = ECM + df["pol"] = abs(POL_UNC * df["$A_L$"]) return df @@ -36,7 +45,11 @@ def write_data(df, boson): error = [] for i in range(len(df)): # here uncertainties are symmetric - e = {"stat": float(df.loc[i, "stat +"]), "sys": float(df.loc[i, "syst +"])} + e = { + "stat": float(df.loc[i, "stat +"]), + "sys": float(df.loc[i, "syst +"]), + "pol": float(df.loc[i, "pol"]), + } error.append(e) error_definition = { @@ -50,6 +63,11 @@ def write_data(df, boson): "treatment": "ADD", "type": "UNCORR", }, + "pol": { + "description": "beam polarization uncertainty", + "treatment": "MULT", + "type": "STARWMWPPOL", + }, } uncertainties_yaml = {"definitions": error_definition, "bins": error} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wm.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wm.yaml index f46e9f5933..9361ba7be4 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wm.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wm.yaml @@ -7,16 +7,26 @@ definitions: description: systematic uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STARWMWPPOL bins: - stat: 0.146 sys: 0.002 + pol: 0.007953 - stat: 0.051 sys: 0.004 + pol: 0.00858 - stat: 0.056 sys: 0.001 + pol: 0.009273000000000002 - stat: 0.056 sys: 0.002 + pol: 0.007887 - stat: 0.051 sys: 0.004 + pol: 0.012705000000000001 - stat: 0.148 sys: 0.002 + pol: 0.006765 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wp.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wp.yaml index f6ac0e8f8c..b0904888ff 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wp.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/uncertainties_wp.yaml @@ -7,16 +7,26 @@ definitions: description: systematic uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STARWMWPPOL bins: - stat: 0.145 sys: 0.012 + pol: 0.010296000000000001 - stat: 0.03 sys: 0.011 + pol: 0.008283 - stat: 0.023 sys: 0.007 + pol: 0.010923 - stat: 0.023 sys: 0.005 + pol: 0.013596 - stat: 0.029 sys: 0.013 + pol: 0.017622000000000002 - stat: 0.14 sys: 0.014 + pol: 0.015906 From ede56cf07131f69f0e5dddd8d58482c9e1184139 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 16 May 2024 14:37:50 +0200 Subject: [PATCH 37/98] Adding pol unc to 2013 data --- .../star/jet_dijet_2013_510gev.py | 39 ++++++++--- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 46 +++++++++---- .../uncertainties.yaml | 64 ++++++++++------- .../uncertainties.yaml | 69 ++++++++++++------- .../uncertainties.yaml | 64 ++++++++++------- .../uncertainties.yaml | 64 ++++++++++------- .../STAR_WMWP_510GEV/rawdata/TableI.csv | 13 ++++ 7 files changed, 237 insertions(+), 122 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 638bcfe7e3..18375c10a7 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -15,10 +15,12 @@ # values from the paper https://arxiv.org/pdf/2110.11020.pdf SQRTS = 510 ETA_ABS = 0.9 +POL_UNC = 0.064 +YEAR = 2013 TOPOPLOGY_LIST = ["1JET", "A", "B", "C", "D"] HERE = pathlib.Path(__file__).parents[2] -RAWDATA_PATH = HERE / "new_commondata/STAR_2013_1JET_510GEV/rawdata/" +RAWDATA_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_510GEV/rawdata/" def read_1jet_data(): @@ -46,6 +48,7 @@ def read_1jet_data(): df["ALL"] = all_data[r"Inclusive Jet $A_{LL}$"] df["stat"] = all_data[r"stat +"] df["syst"] = all_data[r"syst +"] + df["pol"] = POL_UNC * df["ALL"] print("1JET data loaded. Npoint: ", len(df)) return df @@ -72,6 +75,7 @@ def read_2jet_data(topology): df["ALL"] = all_data[r"Dijet $A_{LL}$, topology " + topology] df["stat"] = all_data[r"stat +"] df["syst"] = all_data[r"syst +"] + df["pol"] = POL_UNC * df["ALL"] print(f"2JET {topology} data loaded. Npoint: ", len(df)) return df @@ -121,7 +125,7 @@ def read_correlations(ndata_dict): def write_1jet_data(df, art_sys): - STORE_PATH = HERE / "new_commondata/STAR_2013_1JET_510GEV/" + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_510GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} @@ -151,10 +155,18 @@ def write_1jet_data(df, art_sys): # Write unc file error = [] - error_definition = {} + error_definition = { + "pol": { + "description": "beam polarization uncertainty", + "treatment": "MULT", + "type": f"STAR{YEAR}POL", + }, + } # loop on data points for i, sys_i in enumerate(art_sys): - e = {} + e = { + "pol": float(df.loc[i, "pol"]) + } # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -165,7 +177,7 @@ def write_1jet_data(df, art_sys): f"sys_{j}": { "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", - "type": f"STAR2013JETunc{j}", + "type": f"STAR{YEAR}JETunc{j}", } for j in range(len(sys_i)) } @@ -178,7 +190,7 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_2013_2JET_{topology}_510GEV/" + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{topology}_510GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: @@ -207,15 +219,22 @@ def write_2jet_data(df, topology, art_sys): "description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR", - } + }, + "pol": { + "description": "beam polarization uncertainty", + "treatment": "MULT", + "type": f"STAR{YEAR}POL", + }, } # loop on data points for i, sys_i in enumerate(art_sys): - e = {} + e = { + "stat": float(df.loc[i, "stat"]), + "pol": float(df.loc[i, "pol"]), + } # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val - e["stat"] = float(df.loc[i, "stat"]) error.append(e) if i == 0: @@ -224,7 +243,7 @@ def write_2jet_data(df, topology, art_sys): f"sys_{j}": { "description": f"{j} artificial correlated systematics uncertainty", "treatment": "ADD", - "type": f"STAR2013JETunc{j}", + "type": f"STAR{YEAR}JETunc{j}", } for j in range(len(sys_i)) } diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml index 66f5ccb38f..b9a701233d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml @@ -1,4 +1,8 @@ definitions: + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2013POL sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD @@ -252,7 +256,8 @@ definitions: treatment: ADD type: STAR2013JETunc62 bins: -- sys_0: -8.959677092850805e-10 +- pol: 0.00040064 + sys_0: -8.959677092850805e-10 sys_1: 9.832716726753248e-09 sys_2: 6.730954169673362e-08 sys_3: -5.428657179727165e-07 @@ -315,7 +320,8 @@ bins: sys_60: -1.5836833053327163e-07 sys_61: 1.695949026719929e-08 sys_62: 4.068655178934001e-08 -- sys_0: -1.202440186311471e-09 +- pol: 0.00016512 + sys_0: -1.202440186311471e-09 sys_1: 1.2813446483400317e-08 sys_2: 8.81050970897512e-08 sys_3: -7.651365162959538e-07 @@ -378,7 +384,8 @@ bins: sys_60: -5.563404474063423e-07 sys_61: 1.5882781871113175e-07 sys_62: 1.476017840728621e-07 -- sys_0: -2.029626906402448e-09 +- pol: 0.00017728 + sys_0: -2.029626906402448e-09 sys_1: 1.7836760297927526e-08 sys_2: 1.0627274752256677e-07 sys_3: -6.054955069288028e-07 @@ -441,7 +448,8 @@ bins: sys_60: -2.0567211467696776e-06 sys_61: 8.583540740030501e-07 sys_62: 1.5503622047436774e-07 -- sys_0: -2.317611030883938e-09 +- pol: -4.8e-05 + sys_0: -2.317611030883938e-09 sys_1: 2.0103077754186072e-08 sys_2: 1.221490288409029e-07 sys_3: -7.422699405430424e-07 @@ -504,7 +512,8 @@ bins: sys_60: -1.967785012922417e-06 sys_61: 1.7222827306715096e-06 sys_62: -9.247304481271197e-07 -- sys_0: -5.794556391557737e-09 +- pol: -5.44e-05 + sys_0: -5.794556391557737e-09 sys_1: 4.184211349903503e-08 sys_2: 2.6618567237308233e-07 sys_3: -5.449466410914053e-06 @@ -567,7 +576,8 @@ bins: sys_60: -7.061283646972085e-07 sys_61: 2.2522518080254573e-06 sys_62: -1.0715258476286533e-06 -- sys_0: -1.3031478055734842e-06 +- pol: 0.00028416000000000004 + sys_0: -1.3031478055734842e-06 sys_1: 2.5765217725622465e-06 sys_2: 4.098773110280467e-06 sys_3: -8.01560224988077e-06 @@ -630,7 +640,8 @@ bins: sys_60: 8.270492503029772e-06 sys_61: 1.0653144764978103e-05 sys_62: -3.301748478993185e-06 -- sys_0: -1.3645531518127146e-06 +- pol: 0.00019711999999999998 + sys_0: -1.3645531518127146e-06 sys_1: 4.007352188193593e-06 sys_2: 7.118280416455643e-06 sys_3: -1.4958116315466263e-05 @@ -693,7 +704,8 @@ bins: sys_60: 1.8126001515459303e-05 sys_61: 8.110592685806155e-06 sys_62: -2.9470442625980592e-06 -- sys_0: -4.410061141775246e-06 +- pol: 0.00036608 + sys_0: -4.410061141775246e-06 sys_1: 8.827712539715316e-06 sys_2: 1.5915934216203423e-05 sys_3: -2.789440215473183e-05 @@ -756,7 +768,8 @@ bins: sys_60: 1.998243534936237e-05 sys_61: 1.9118831698037573e-06 sys_62: -3.1450946824362763e-06 -- sys_0: -9.131724744467474e-06 +- pol: 0.00064512 + sys_0: -9.131724744467474e-06 sys_1: 1.863235365253899e-05 sys_2: 3.3956019925427964e-05 sys_3: -6.41123490746426e-05 @@ -819,7 +832,8 @@ bins: sys_60: 1.2981714818282402e-05 sys_61: -2.652476147993337e-06 sys_62: -2.631173820600041e-06 -- sys_0: -2.435929877389478e-05 +- pol: 0.0006611200000000001 + sys_0: -2.435929877389478e-05 sys_1: 4.385340201952634e-05 sys_2: 8.054820474610805e-05 sys_3: -0.00016574335050612704 @@ -882,7 +896,8 @@ bins: sys_60: 5.8275712061147025e-06 sys_61: -3.855018491750307e-06 sys_62: -1.9427906611187093e-06 -- sys_0: -6.0544102812491e-05 +- pol: 0.0007993599999999999 + sys_0: -6.0544102812491e-05 sys_1: 0.00010598849026939544 sys_2: 0.00021379958305045062 sys_3: -0.003165879692769455 @@ -945,7 +960,8 @@ bins: sys_60: 1.6964110742333556e-06 sys_61: -3.2070331988170936e-06 sys_62: -1.2278020423447078e-06 -- sys_0: -0.0001577103692828836 +- pol: 0.0011673599999999999 + sys_0: -0.0001577103692828836 sys_1: 0.00029912242658556974 sys_2: 0.004808687956200867 sys_3: 0.0001884540779062149 @@ -1008,7 +1024,8 @@ bins: sys_60: 1.2190753075267697e-07 sys_61: -1.970881120092344e-06 sys_62: -5.924851514078511e-07 -- sys_0: -0.00045504371463879224 +- pol: 0.0014112 + sys_0: -0.00045504371463879224 sys_1: 0.007914936126560801 sys_2: -0.00022897842682166285 sys_3: 5.616507642207872e-05 @@ -1071,7 +1088,8 @@ bins: sys_60: -1.827586030334612e-07 sys_61: -8.847799754759238e-07 sys_62: -1.3186838446226118e-07 -- sys_0: -0.014037407329102298 +- pol: 0.00289728 + sys_0: -0.014037407329102298 sys_1: -0.0002905887232621964 sys_2: -6.535182661833837e-05 sys_3: 1.610446295864737e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml index 5446b65e5e..0999d0879c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2013POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -256,7 +260,9 @@ definitions: treatment: ADD type: STAR2013JETunc62 bins: -- sys_0: -1.8442665253564098e-08 +- stat: 0.00619 + pol: -0.00035072 + sys_0: -1.8442665253564098e-08 sys_1: 9.128062228545417e-08 sys_2: 3.0998812240715233e-07 sys_3: -8.292100410110618e-07 @@ -319,8 +325,9 @@ bins: sys_60: -3.1371552148566684e-05 sys_61: 1.2764542310865707e-05 sys_62: 4.157211360391717e-05 - stat: 0.00619 -- sys_0: -7.838875974830611e-08 +- stat: 0.00289 + pol: -7.04e-06 + sys_0: -7.838875974830611e-08 sys_1: 4.029804267681053e-07 sys_2: 1.4263812561994197e-06 sys_3: -3.8939531387546136e-06 @@ -383,8 +390,9 @@ bins: sys_60: -6.39056384823132e-07 sys_61: 2.510398468627605e-05 sys_62: -4.076207527766995e-05 - stat: 0.00289 -- sys_0: -2.8468150405070355e-08 +- stat: 0.00248 + pol: 0.0001056 + sys_0: -2.8468150405070355e-08 sys_1: 1.302892686669323e-07 sys_2: 4.2550586928508e-07 sys_3: -1.1352092280154899e-06 @@ -447,8 +455,9 @@ bins: sys_60: -1.659356688181353e-05 sys_61: -0.00011343535700925786 sys_62: 4.121418069420012e-05 - stat: 0.00248 -- sys_0: -4.6544610935439495e-08 +- stat: 0.00226 + pol: 8.256e-05 + sys_0: -4.6544610935439495e-08 sys_1: 2.3007219919492261e-07 sys_2: 7.952844513686009e-07 sys_3: -2.2010895231917295e-06 @@ -511,8 +520,9 @@ bins: sys_60: 0.00039882217593925715 sys_61: 7.783095322331932e-05 sys_62: 0.00021475672701815719 - stat: 0.00226 -- sys_0: -4.534138982447269e-08 +- stat: 0.00246 + pol: 0.00015872 + sys_0: -4.534138982447269e-08 sys_1: 2.2504896724296193e-07 sys_2: 7.917709026102204e-07 sys_3: -2.2773394791142846e-06 @@ -575,8 +585,9 @@ bins: sys_60: -0.00010081190334738222 sys_61: 5.942138370061235e-05 sys_62: 7.73366041438697e-05 - stat: 0.00246 -- sys_0: -4.500893914289471e-08 +- stat: 0.00311 + pol: 0.00037184 + sys_0: -4.500893914289471e-08 sys_1: 2.1858653897192284e-07 sys_2: 7.79153722769766e-07 sys_3: -3.8999508530680035e-06 @@ -639,8 +650,9 @@ bins: sys_60: -5.370716945167318e-05 sys_61: 4.2645383150428345e-05 sys_62: 3.0384184455649006e-05 - stat: 0.00311 -- sys_0: -5.7977978168794394e-08 +- stat: 0.00349 + pol: 0.00042624000000000004 + sys_0: -5.7977978168794394e-08 sys_1: 2.9729274345840024e-07 sys_2: 2.7849696168819077e-06 sys_3: -9.113767053801187e-06 @@ -703,8 +715,9 @@ bins: sys_60: -4.1975207047052955e-05 sys_61: 3.7530717355276765e-05 sys_62: 1.6831769406156224e-05 - stat: 0.00349 -- sys_0: -1.2307329310568736e-07 +- stat: 0.00472 + pol: 0.0007296000000000001 + sys_0: -1.2307329310568736e-07 sys_1: 1.8453058533627218e-06 sys_2: 8.128992279649453e-06 sys_3: -2.1360791660817124e-05 @@ -767,8 +780,9 @@ bins: sys_60: -1.543716474827684e-05 sys_61: 2.6851614975002303e-05 sys_62: 9.245856630486994e-06 - stat: 0.00472 -- sys_0: -2.012664434190439e-06 +- stat: 0.00659 + pol: 0.0011686399999999999 + sys_0: -2.012664434190439e-06 sys_1: 9.343738640456632e-06 sys_2: 2.656361359743435e-05 sys_3: -5.669800383147065e-05 @@ -831,8 +845,9 @@ bins: sys_60: -2.3889542914618593e-06 sys_61: 2.1225721477033618e-05 sys_62: 4.497841620233109e-06 - stat: 0.00659 -- sys_0: -1.1399876370921493e-05 +- stat: 0.01045 + pol: 0.00155584 + sys_0: -1.1399876370921493e-05 sys_1: 3.460208095882234e-05 sys_2: 8.128788330846539e-05 sys_3: -0.00012802581663518082 @@ -895,8 +910,9 @@ bins: sys_60: 3.63351039641335e-06 sys_61: 1.6236332789635498e-05 sys_62: 1.8094252933826653e-06 - stat: 0.01045 -- sys_0: -4.3391282027328335e-05 +- stat: 0.01633 + pol: 0.00232832 + sys_0: -4.3391282027328335e-05 sys_1: 0.00010733055374682666 sys_2: 0.00017349825516788553 sys_3: -0.0001483893206035633 @@ -959,8 +975,9 @@ bins: sys_60: 3.991462542170518e-06 sys_61: 1.1661958762446107e-05 sys_62: 1.6078432326039527e-06 - stat: 0.01633 -- sys_0: -0.0001582145343682221 +- stat: 0.02919 + pol: -0.0005049599999999999 + sys_0: -0.0001582145343682221 sys_1: 0.00023785644592245637 sys_2: 0.00018923810995146129 sys_3: -5.50796661204648e-05 @@ -1023,4 +1040,3 @@ bins: sys_60: 3.361462239576226e-06 sys_61: 7.42558601635741e-06 sys_62: 3.7190762696376226e-07 - stat: 0.02919 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml index 48671100f1..34be003f02 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2013POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -256,7 +260,9 @@ definitions: treatment: ADD type: STAR2013JETunc62 bins: -- sys_0: -3.468382363342568e-08 +- stat: 0.00533 + pol: 0.00024384 + sys_0: -3.468382363342568e-08 sys_1: 1.8121652909760799e-07 sys_2: 5.838496850963883e-07 sys_3: -1.278202755886677e-06 @@ -319,8 +325,9 @@ bins: sys_60: 4.047197054438378e-06 sys_61: 8.481225791663006e-06 sys_62: -2.2672083449213552e-05 - stat: 0.00533 -- sys_0: -9.090601444875332e-08 +- stat: 0.00213 + pol: 0.00019136 + sys_0: -9.090601444875332e-08 sys_1: 4.616157558012612e-07 sys_2: 1.473310204477202e-06 sys_3: -3.253544050445888e-06 @@ -383,8 +390,9 @@ bins: sys_60: -1.6689217101056417e-05 sys_61: -5.8887611946663265e-05 sys_62: 8.398314077938356e-05 - stat: 0.00213 -- sys_0: -8.530127204466283e-08 +- stat: 0.00173 + pol: -7.424000000000001e-05 + sys_0: -8.530127204466283e-08 sys_1: 4.29673266336131e-07 sys_2: 1.3304320577341956e-06 sys_3: -2.7424510030197946e-06 @@ -447,8 +455,9 @@ bins: sys_60: -1.0020824681028037e-05 sys_61: -3.614271020475976e-05 sys_62: 5.762533776139228e-05 - stat: 0.00173 -- sys_0: -1.1152205784023518e-07 +- stat: 0.00152 + pol: 0.00021504 + sys_0: -1.1152205784023518e-07 sys_1: 5.632982151226721e-07 sys_2: 1.7794589363130775e-06 sys_3: -3.901763354366608e-06 @@ -511,8 +520,9 @@ bins: sys_60: 6.696545217098689e-06 sys_61: -2.8427700023791145e-06 sys_62: -3.796889291143406e-05 - stat: 0.00152 -- sys_0: -1.1169536414096341e-07 +- stat: 0.00161 + pol: -3.84e-05 + sys_0: -1.1169536414096341e-07 sys_1: 5.629576028352181e-07 sys_2: 1.7886807965226788e-06 sys_3: -4.024141864189415e-06 @@ -575,8 +585,9 @@ bins: sys_60: 1.6886666669489538e-05 sys_61: -2.9083101908458806e-05 sys_62: -5.1363235548141263e-05 - stat: 0.00161 -- sys_0: -9.692271653941357e-08 +- stat: 0.00202 + pol: 9.855999999999999e-05 + sys_0: -9.692271653941357e-08 sys_1: 4.942929134532881e-07 sys_2: 1.6295369068757726e-06 sys_3: -5.38828173879068e-06 @@ -639,8 +650,9 @@ bins: sys_60: 6.0403851036709675e-05 sys_61: -0.0004464097568771295 sys_62: -0.0001278038928716919 - stat: 0.00202 -- sys_0: -1.1313231922673203e-07 +- stat: 0.00224 + pol: 0.0003968 + sys_0: -1.1313231922673203e-07 sys_1: 5.8776988624716e-07 sys_2: 3.6125771096691164e-06 sys_3: -1.1695883196356316e-05 @@ -703,8 +715,9 @@ bins: sys_60: -0.0003005852160424321 sys_61: 4.500395191151925e-05 sys_62: 4.6771652136488883e-05 - stat: 0.00224 -- sys_0: -1.765422887477046e-07 +- stat: 0.00297 + pol: 0.0005536 + sys_0: -1.765422887477046e-07 sys_1: 2.0551743805244367e-06 sys_2: 9.859150544691759e-06 sys_3: -2.5671912462627133e-05 @@ -767,8 +780,9 @@ bins: sys_60: -4.6494768247657085e-05 sys_61: 1.7096152684547416e-05 sys_62: 1.4871429582216254e-05 - stat: 0.00297 -- sys_0: -1.9304449086169784e-06 +- stat: 0.00406 + pol: 0.0005158399999999999 + sys_0: -1.9304449086169784e-06 sys_1: 1.0378470446209637e-05 sys_2: 3.1029803365074237e-05 sys_3: -6.549894697607971e-05 @@ -831,8 +845,9 @@ bins: sys_60: -1.7406162669139273e-05 sys_61: 1.327650826989918e-05 sys_62: 5.130470650393264e-06 - stat: 0.00406 -- sys_0: -1.2536445300773651e-05 +- stat: 0.00629 + pol: 0.00155392 + sys_0: -1.2536445300773651e-05 sys_1: 3.848548585424122e-05 sys_2: 8.518413112749595e-05 sys_3: -0.00013699497249401523 @@ -895,8 +910,9 @@ bins: sys_60: -5.1849677459285485e-06 sys_61: 9.499507298832599e-06 sys_62: 1.4754204121214294e-06 - stat: 0.00629 -- sys_0: -4.61630218202905e-05 +- stat: 0.00953 + pol: 0.0006803200000000001 + sys_0: -4.61630218202905e-05 sys_1: 0.00010734443625050014 sys_2: 0.0001717408755548584 sys_3: -0.00016221815284844744 @@ -959,8 +975,9 @@ bins: sys_60: -1.2876064761393513e-06 sys_61: 7.369730805066236e-06 sys_62: 1.6605655103780758e-06 - stat: 0.00953 -- sys_0: -0.0001384089360340667 +- stat: 0.01613 + pol: 0.00079872 + sys_0: -0.0001384089360340667 sys_1: 0.0002089501775235047 sys_2: 0.00017467888563264523 sys_3: -6.663960913198401e-05 @@ -1023,8 +1040,9 @@ bins: sys_60: 8.71874637829264e-07 sys_61: 5.524110967588213e-06 sys_62: -1.4181091930554394e-07 - stat: 0.01613 -- sys_0: -0.0005375590456296148 +- stat: 0.02978 + pol: 0.00322368 + sys_0: -0.0005375590456296148 sys_1: 0.0004247513096179986 sys_2: 0.00015231468989848919 sys_3: -9.557874948782496e-06 @@ -1087,4 +1105,3 @@ bins: sys_60: 1.1695134347538039e-06 sys_61: 2.658103853806848e-06 sys_62: -2.443905738359106e-06 - stat: 0.02978 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml index 5cad5c37f1..97100b4c63 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2013POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -256,7 +260,9 @@ definitions: treatment: ADD type: STAR2013JETunc62 bins: -- sys_0: -4.100959127774964e-07 +- stat: 0.00785 + pol: -0.0007392 + sys_0: -4.100959127774964e-07 sys_1: 1.222332698478793e-06 sys_2: 2.05687127807516e-06 sys_3: -2.77725532587735e-06 @@ -319,8 +325,9 @@ bins: sys_60: -1.0230387776613736e-06 sys_61: -3.751085452978378e-06 sys_62: 7.299765596649971e-06 - stat: 0.00785 -- sys_0: -1.8501931900701732e-06 +- stat: 0.00367 + pol: 4.8e-05 + sys_0: -1.8501931900701732e-06 sys_1: 5.816479741016232e-06 sys_2: 1.117343944426216e-05 sys_3: -1.943884003271612e-05 @@ -383,8 +390,9 @@ bins: sys_60: 2.731883101018434e-06 sys_61: 3.3264670285405464e-06 sys_62: -5.3538188824715525e-06 - stat: 0.00367 -- sys_0: -7.06985540704637e-07 +- stat: 0.00317 + pol: -0.00018752 + sys_0: -7.06985540704637e-07 sys_1: 2.047809323259492e-06 sys_2: 3.206126094091834e-06 sys_3: -3.778024757558471e-06 @@ -447,8 +455,9 @@ bins: sys_60: -3.418545784311553e-05 sys_61: -0.00010871292664295478 sys_62: 0.00022180010222988035 - stat: 0.00317 -- sys_0: -1.1394923825192585e-06 +- stat: 0.00291 + pol: 1.1520000000000002e-05 + sys_0: -1.1394923825192585e-06 sys_1: 3.3584175291326274e-06 sys_2: 5.517441427429289e-06 sys_3: -7.297753969531229e-06 @@ -511,8 +520,9 @@ bins: sys_60: -3.37279365826982e-06 sys_61: -1.4817865796535135e-05 sys_62: 2.8882203891701888e-05 - stat: 0.00291 -- sys_0: -1.0055431921622787e-06 +- stat: 0.00317 + pol: 0.00041920000000000005 + sys_0: -1.0055431921622787e-06 sys_1: 2.9559665736729617e-06 sys_2: 4.835313364366917e-06 sys_3: -6.410561126285684e-06 @@ -575,8 +585,9 @@ bins: sys_60: -6.186834091481266e-06 sys_61: -1.227527713162412e-05 sys_62: 2.2732328432324687e-05 - stat: 0.00317 -- sys_0: -7.982530653253943e-07 +- stat: 0.004 + pol: 0.00062016 + sys_0: -7.982530653253943e-07 sys_1: 2.3526122878835294e-06 sys_2: 3.903999488363647e-06 sys_3: -6.7250939136590844e-06 @@ -639,8 +650,9 @@ bins: sys_60: -8.397690773759385e-06 sys_61: -8.543634712615092e-06 sys_62: 1.3946435744793562e-05 - stat: 0.004 -- sys_0: -7.629582335717668e-07 +- stat: 0.00448 + pol: 0.00052288 + sys_0: -7.629582335717668e-07 sys_1: 2.2930528290573246e-06 sys_2: 5.4168186296954345e-06 sys_3: -1.1521822404605969e-05 @@ -703,8 +715,9 @@ bins: sys_60: -1.1344199970790662e-05 sys_61: -6.176472510453034e-06 sys_62: 1.1343586365878917e-05 - stat: 0.00448 -- sys_0: -7.196379769948711e-07 +- stat: 0.00603 + pol: 0.00084288 + sys_0: -7.196379769948711e-07 sys_1: 3.841066107188445e-06 sys_2: 1.055275654751577e-05 sys_3: -2.3505677078248793e-05 @@ -767,8 +780,9 @@ bins: sys_60: -9.657525107045734e-06 sys_61: -2.473546456533126e-06 sys_62: 9.664290940358064e-06 - stat: 0.00603 -- sys_0: -3.056381573146764e-06 +- stat: 0.00833 + pol: 0.00119424 + sys_0: -3.056381573146764e-06 sys_1: 1.2227822520879637e-05 sys_2: 3.067532258845744e-05 sys_3: -6.182161856473645e-05 @@ -831,8 +845,9 @@ bins: sys_60: -5.5805023499457726e-06 sys_61: -7.696888764256736e-07 sys_62: 8.032471762559063e-06 - stat: 0.00833 -- sys_0: -1.3933736532744972e-05 +- stat: 0.01292 + pol: 0.00109568 + sys_0: -1.3933736532744972e-05 sys_1: 4.263267579515523e-05 sys_2: 9.349430373992513e-05 sys_3: -0.00014947342696182536 @@ -895,8 +910,9 @@ bins: sys_60: -2.5687936172409604e-06 sys_61: -7.375829581369488e-07 sys_62: 6.7171731111360795e-06 - stat: 0.01292 -- sys_0: -5.2224816543540025e-05 +- stat: 0.01964 + pol: 0.00086848 + sys_0: -5.2224816543540025e-05 sys_1: 0.00011437109584364653 sys_2: 0.00017185485398267633 sys_3: -0.00015990244471292175 @@ -959,8 +975,9 @@ bins: sys_60: -1.4005437598397512e-06 sys_61: -3.8814180019798167e-07 sys_62: 5.229117363656164e-06 - stat: 0.01964 -- sys_0: -0.0001821538669113795 +- stat: 0.03322 + pol: -0.000368 + sys_0: -0.0001821538669113795 sys_1: 0.0002428086358083653 sys_2: 0.00019902420286007486 sys_3: -8.13456580794403e-05 @@ -1023,4 +1040,3 @@ bins: sys_60: -6.366318509114538e-07 sys_61: -5.462137045590656e-07 sys_62: 3.685235162290462e-06 - stat: 0.03322 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml index d42156ea47..0266f9664b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2013POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -256,7 +260,9 @@ definitions: treatment: ADD type: STAR2013JETunc62 bins: -- sys_0: -8.246189673601546e-07 +- stat: 0.00466 + pol: 0.00067072 + sys_0: -8.246189673601546e-07 sys_1: 2.7810751638783183e-06 sys_2: 5.956720831913832e-06 sys_3: -1.0838703833264454e-05 @@ -319,8 +325,9 @@ bins: sys_60: -3.0660881959271824e-06 sys_61: -3.6611611954781142e-06 sys_62: 1.0567798499199847e-05 - stat: 0.00466 -- sys_0: -4.997327691153951e-07 +- stat: 0.00302 + pol: 0.00018944 + sys_0: -4.997327691153951e-07 sys_1: 1.6284178687517042e-06 sys_2: 3.2440683053073596e-06 sys_3: -5.150821434796478e-06 @@ -383,8 +390,9 @@ bins: sys_60: 0.00010975604708626198 sys_61: 0.00013061098342344492 sys_62: -0.00035837619026315103 - stat: 0.00302 -- sys_0: -1.2322595716463065e-06 +- stat: 0.00235 + pol: 0.00019648 + sys_0: -1.2322595716463065e-06 sys_1: 4.141704840515627e-06 sys_2: 8.792691224674361e-06 sys_3: -1.5727344202989926e-05 @@ -447,8 +455,9 @@ bins: sys_60: 4.1388149825313535e-06 sys_61: 4.3081557252252836e-06 sys_62: -1.06050585369882e-05 - stat: 0.00235 -- sys_0: -1.0343763729771366e-06 +- stat: 0.00229 + pol: -4.6080000000000006e-05 + sys_0: -1.0343763729771366e-06 sys_1: 3.447940072340132e-06 sys_2: 7.205331797379565e-06 sys_3: -1.2592714587816732e-05 @@ -511,8 +520,9 @@ bins: sys_60: 1.8895635002081768e-06 sys_61: 6.068278459572265e-06 sys_62: -1.4121347509033479e-05 - stat: 0.00229 -- sys_0: -7.546643274499027e-07 +- stat: 0.00278 + pol: 0.00010816000000000001 + sys_0: -7.546643274499027e-07 sys_1: 2.5077908840206717e-06 sys_2: 5.232506125093797e-06 sys_3: -9.242299083827163e-06 @@ -575,8 +585,9 @@ bins: sys_60: -1.5149318940855e-06 sys_61: 6.264837756251943e-06 sys_62: -1.3227487664635489e-05 - stat: 0.00278 -- sys_0: -6.659628598028416e-07 +- stat: 0.003 + pol: 0.00032063999999999997 + sys_0: -6.659628598028416e-07 sys_1: 2.23116447955261e-06 sys_2: 5.5323214912652514e-06 sys_3: -1.171632503570118e-05 @@ -639,8 +650,9 @@ bins: sys_60: -6.85368884955029e-06 sys_61: 6.0148326976299154e-06 sys_62: -1.2085082539939634e-05 - stat: 0.003 -- sys_0: -5.326099380504057e-07 +- stat: 0.00382 + pol: 0.00028352 + sys_0: -5.326099380504057e-07 sys_1: 1.8430676926367074e-06 sys_2: 7.2716645021494255e-06 sys_3: -1.793980136868793e-05 @@ -703,8 +715,9 @@ bins: sys_60: -1.0294570952677303e-05 sys_61: 5.63901733156666e-06 sys_62: -7.81171189563106e-06 - stat: 0.00382 -- sys_0: -5.300674818349766e-07 +- stat: 0.005 + pol: 0.00056768 + sys_0: -5.300674818349766e-07 sys_1: 5.062211933315961e-06 sys_2: 1.4574894428516086e-05 sys_3: -3.456023453906574e-05 @@ -767,8 +780,9 @@ bins: sys_60: -1.0876528433439222e-05 sys_61: 5.7453234723213655e-06 sys_62: -3.899561231030796e-06 - stat: 0.005 -- sys_0: -3.5594850793009027e-06 +- stat: 0.00747 + pol: 0.0006303999999999999 + sys_0: -3.5594850793009027e-06 sys_1: 1.4357113530376482e-05 sys_2: 3.7395184608793296e-05 sys_3: -7.043219866239244e-05 @@ -831,8 +845,9 @@ bins: sys_60: -6.610002999156971e-06 sys_61: 5.333829130167809e-06 sys_62: -8.320501431985912e-07 - stat: 0.00747 -- sys_0: -1.5228455235119592e-05 +- stat: 0.01095 + pol: 0.00022464000000000002 + sys_0: -1.5228455235119592e-05 sys_1: 4.3147530546065046e-05 sys_2: 8.529090376974244e-05 sys_3: -0.00011654142142914013 @@ -895,8 +910,9 @@ bins: sys_60: -3.1398338596874393e-06 sys_61: 4.865736315018438e-06 sys_62: 2.5193919058972847e-07 - stat: 0.01095 -- sys_0: -5.221725858549406e-05 +- stat: 0.01797 + pol: 0.00201024 + sys_0: -5.221725858549406e-05 sys_1: 0.00011109036301678784 sys_2: 0.0001374635404968144 sys_3: -9.590510836923642e-05 @@ -959,8 +975,9 @@ bins: sys_60: -5.466021191329975e-07 sys_61: 3.588963334491905e-06 sys_62: 1.7969917942623896e-07 - stat: 0.01797 -- sys_0: -0.00022560839549655114 +- stat: 0.03187 + pol: 0.00071296 + sys_0: -0.00022560839549655114 sys_1: 0.00026503748033196044 sys_2: 0.00017282686211184703 sys_3: -5.236376776160493e-05 @@ -1023,4 +1040,3 @@ bins: sys_60: 8.255717064022164e-08 sys_61: 1.196554075827759e-06 sys_62: 5.0634969611676316e-08 - stat: 0.03187 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv new file mode 100644 index 0000000000..eae495e12d --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv @@ -0,0 +1,13 @@ +process, etae, W-, W-, W-, W-, W-, W-, W+, W+, W+, W+, W+, W+ +W-, -1.27, 1.0, 0.006, 0.009, 0.010, 0.019, 0.007, -0.229, -0.006, -0.021, -0.021, -0.021, -0.001 +W-, -0.74, 0, 1, 0.024, 0.023, 0.041, 0.008, -0.013, 0.003, -0.022, -0.050, -0.027, -0.005 +W-, -0.27, 0, 0, 1, 0.019, 0.037, 0.005, -0.014, -0.017, -0.041, -0.049, -0.055, -0.003 +W-, 0.27, 0, 0, 0, 1, 0.031, 0.001, -0.011, -0.009, -0.029, -0.040, -0.039, -0.009 +W-, 0.74, 0, 0, 0, 0, 1, 0.014, -0.017, -0.018, -0.054, -0.075, -0.062, -0.012 +W-, 1.27, 0, 0, 0, 0, 0, 1, -0.002, -0.004, -0.008, -0.015, -0.014, -0.238 +W+, -1.24, 0, 0, 0, 0, 0, 0, 1, 0.018, 0.035, 0.034, 0.040, 0.021 +W+, -0.72, 0, 0, 0, 0, 0, 0, 0, 1, 0.150, 0.146, 0.209, 0.010 +W+, -0.24, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.190, 0.232, 0.026 +W+, 0.24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.244, 0.030 +W+, 0.72, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.029 +W+, 1.24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 \ No newline at end of file From 030f63e90e2b336e00d3e351e881194537e4529b Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 16 May 2024 15:00:28 +0200 Subject: [PATCH 38/98] various fixes in 2009 1 JET data --- .../star/jet_dijet_2009_200gev.py | 155 +- .../star/jet_dijet_2013_510gev.py | 4 +- .../STAR_2009_1JET_200GEV/kinematics.yaml | 22 +- .../STAR_2009_1JET_200GEV/uncertainties.yaml | 2442 +++++++++-------- .../uncertainties.yaml | 559 ++-- .../uncertainties.yaml | 779 +++--- .../uncertainties.yaml | 773 +++--- .../uncertainties.yaml | 772 +++--- .../uncertainties.yaml | 768 +++--- 9 files changed, 3156 insertions(+), 3118 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index a22f88ab01..f4ddf73b2c 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -13,6 +13,7 @@ TOPOPLOGY_LIST = ["I", "SS", "OS", "A", "B", "C"] POL_UNC = 0.065 LUMI_UNC = 0.0005 +YEAR = 2009 HERE = pathlib.Path(__file__).parents[2] @@ -21,11 +22,11 @@ def read_1jet_data(): df4 = pd.DataFrame() fnames = [ - "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_ALL.csv", - "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_3_pT.csv", - "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_ALL.csv", - "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_4_pT.csv", - "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/Table_5.csv", + f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_3_ALL.csv", + f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_3_pT.csv", + f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_4_ALL.csv", + f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_4_pT.csv", + f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_5.csv", ] for fname in fnames: @@ -43,8 +44,6 @@ def read_1jet_data(): df3["abs_eta_min"] = 0.0 df3["abs_eta_max"] = 0.5 - df3["abs_eta"] = (df3["abs_eta_min"] + df3["abs_eta_max"]) / 2 - df3["sqrts"] = 200 elif "4" in fname: dfi = pd.read_csv(fname) @@ -53,14 +52,13 @@ def read_1jet_data(): if "ALL" in fname: df4["ALL"] = dfi["$A_{LL}$"] - df3["stat_min"] = dfi["stat -"] - df3["stat_max"] = dfi["stat +"] - df3["sys_min"] = dfi["sys -"] - df3["sys_max"] = dfi["sys +"] + df4["stat_min"] = dfi["stat -"] + df4["stat_max"] = dfi["stat +"] + df4["sys_min"] = dfi["sys -"] + df4["sys_max"] = dfi["sys +"] df4["abs_eta_min"] = 0.5 - df4["abs_eta_max"] = 1.0 - df4["sqrts"] = 200 + df4["abs_eta_max"] = 1.0 elif "5" in fname: dfc_col = pd.read_csv(fname) @@ -81,16 +79,20 @@ def read_1jet_data(): df = pd.concat([df3, df4], ignore_index=True) - for i in range(len(df)): - df.loc[i, "stat"] = df.loc[i, "stat_max"] - df.loc[i, "sys"] = df.loc[i, "sys_max"] + df["stat"] = df["stat_max"] + df["sys"] = df["sys_max"] + df["pol"] = POL_UNC * df["ALL"] + df["sqrts"] = 200 + df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 return df, dfc def read_2jet_data(topology): - fname = f"../../new_commondata/STAR_2009_2JET_{topology}_200GEV/rawdata/Table.yaml" + fname = ( + f"../../new_commondata/STAR_{YEAR}_2JET_{topology}_200GEV/rawdata/Table.yaml" + ) df = pd.DataFrame() - with open(fname, "r") as file: + with open(fname, "r", encoding="utf-8") as file: data = yaml.safe_load(file) if topology in ["A", "B", "C"]: @@ -98,7 +100,6 @@ def read_2jet_data(topology): Gsub = data["dependent_variables"][0]["values"] for i in range(len(Msub)): - df = pd.concat( [ df, @@ -109,21 +110,18 @@ def read_2jet_data(topology): "ALL": [Gsub[i]["value"]], "stat": [Gsub[i]["errors"][0]["symerror"]], "sys": [Gsub[i]["errors"][1]["symerror"]], + "pol": [POL_UNC * Gsub[i]["value"]], } ), ], ignore_index=True, ) - df["m"] = (df["m_low"] + df["m_high"]) / 2 - df["sqrts"] = 200 - else: Msub = data["dependent_variables"][0]["values"] Gsub = data["dependent_variables"][1]["values"] for i in range(len(Msub)): - df = pd.concat( [ df, @@ -139,13 +137,13 @@ def read_2jet_data(topology): ], ignore_index=True, ) - df["sqrts"] = 200 + df["sqrts"] = 200 return df def write_1jet_data(df, art_sys): - STORE_PATH = "../../new_commondata/STAR_2009_1JET_200GEV/" + STORE_PATH = f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} @@ -171,10 +169,16 @@ def write_1jet_data(df, art_sys): # Write unc file error = [] - error_definition = {} + error_definition = { + "pol": { + "description": "beam polarization uncertainty", + "treatment": "MULT", + "type": f"STAR{YEAR}POL", + } + } # loop on data points for i, sys_i in enumerate(art_sys): - e = {} + e = {"pol": float(df.loc[i, "pol"])} # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -185,7 +189,7 @@ def write_1jet_data(df, art_sys): f"sys_{j}": { "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", - "type": f"STAR2009JETunc{j}", + "type": f"STAR{YEAR}JETunc{j}", } for j in range(len(sys_i)) } @@ -197,7 +201,7 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = f"../../new_commondata/STAR_2009_2JET_{topology}_200GEV/" + STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_{topology}_200GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} with open(STORE_PATH + "data.yaml", "w", encoding="utf-8") as file: @@ -227,61 +231,37 @@ def write_2jet_data(df, topology, art_sys): # Write unc file error = [] - if topology in ["A", "B", "C"]: - error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"} - } - # loop on data points - for i, sys_i in enumerate(art_sys): - e = {"stat": float(df.loc[i, "stat"])} - # loop on art sys - for j, val in enumerate(sys_i): - e[f"sys_{j}"] = val - error.append(e) - - if i == 0: - error_definition.update( - { - f"sys_{j}": { - "description": f"{j} artificial correlated systematics uncertainty", - "treatment": "ADD", - "type": f"STAR2009JETunc{j}", - } - for j in range(len(sys_i)) - } - ) - else: - error_definition = { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - }, - "pol": { - "description": "polarization uncertainty", - "treatment": "MULT", - "type": "STAR2009POL", - }, - } - # loop on data points - for i, sys_i in enumerate(art_sys): - e = {"stat": float(df.loc[i, "stat"]), "pol": float(df.loc[i, "pol"])} - # loop on art sys - for j, val in enumerate(sys_i): - e[f"sys_{j}"] = val - error.append(e) - - if i == 0: - error_definition.update( - { - f"sys_{j}": { - "description": f"{j} artificial correlated systematics uncertainty", - "treatment": "ADD", - "type": f"STAR2009JETunc{j}", - } - for j in range(len(sys_i)) + error_definition = { + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "pol": { + "description": "beam polarization uncertainty", + "treatment": "MULT", + "type": f"STAR{YEAR}POL", + }, + } + # loop on data points + for i, sys_i in enumerate(art_sys): + e = {"stat": float(df.loc[i, "stat"]), "pol": float(df.loc[i, "pol"])} + # loop on art sys + for j, val in enumerate(sys_i): + e[f"sys_{j}"] = val + error.append(e) + + if i == 0: + error_definition.update( + { + f"sys_{j}": { + "description": f"{j} artificial correlated systematics uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}JETunc{j}", } - ) + for j in range(len(sys_i)) + } + ) uncertainties_yaml = {"definitions": error_definition, "bins": error} with open(STORE_PATH + "uncertainties.yaml", "w", encoding="utf-8") as file: @@ -290,7 +270,7 @@ def write_2jet_data(df, topology, art_sys): if __name__ == "__main__": # load all the data - df, dfc = read_1jet_data() + df, _ = read_1jet_data() dfs = {"I": df} for topo in TOPOPLOGY_LIST[1:]: dfs[topo] = read_2jet_data(topo) @@ -298,12 +278,15 @@ def write_2jet_data(df, topology, art_sys): # load correlations ndata_dict = {a: len(b) for a, b in dfs.items()} correlation_df = pd.read_csv( - "../../new_commondata/STAR_2009_1JET_200GEV/rawdata/correlation.csv", index_col=0 + f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/correlation.csv", + index_col=0, ) # from the paper we understand that stat dijet is not correlated # I-I (stat + sys) | I-D (stat + sys) # D-I (stat + sys) | D-D (sys) - correlated_unc = np.sqrt(dfs["I"]["sys"] ** 2 + dfs["I"]["stat"] ** 2).values.tolist() + correlated_unc = np.sqrt( + dfs["I"]["sys"] ** 2 + dfs["I"]["stat"] ** 2 + ).values.tolist() for a in TOPOPLOGY_LIST[1:]: correlated_unc.extend(dfs[a]["sys"].values) ndata_points = np.sum((*ndata_dict.values(),)) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 18375c10a7..0c78c18086 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -164,9 +164,7 @@ def write_1jet_data(df, art_sys): } # loop on data points for i, sys_i in enumerate(art_sys): - e = { - "pol": float(df.loc[i, "pol"]) - } + e = {"pol": float(df.loc[i, "pol"])} # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml index 1fbf402f69..aa80d7522d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml @@ -133,7 +133,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -145,7 +145,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -157,7 +157,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -169,7 +169,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -181,7 +181,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -193,7 +193,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -205,7 +205,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -217,7 +217,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -229,7 +229,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -241,7 +241,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null @@ -253,7 +253,7 @@ bins: min: null - abs_eta: max: 1.0 - mid: .nan + mid: 0.75 min: 0.5 pT: max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml index 05ff44bb88..3011139c8b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml @@ -1,4 +1,8 @@ definitions: + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2009POL sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD @@ -220,1213 +224,1235 @@ definitions: treatment: ADD type: STAR2009JETunc54 bins: -- sys_0: 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-1.6791417730059264e-06 + sys_53: -1.3564390794808867e-06 + sys_54: -2.14135327408643e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml index ace19c9ccd..316794bffb 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2009POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -225,282 +229,287 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.007 - sys_0: -2.9341441875924853e-09 - sys_1: 5.662769814057847e-09 - sys_2: 3.947516339994088e-08 - sys_3: 3.474259906408537e-08 - sys_4: -4.1987083112144685e-07 - sys_5: 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-5.8267907989462905e-06 + sys_53: -8.302888789428512e-06 + sys_54: -1.975275843016325e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml index 3f7c426fec..ec6c430437 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2009POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -225,394 +229,401 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.011 - sys_0: -4.317226197359961e-06 - sys_1: 2.804090271238005e-06 - sys_2: 1.533190350417471e-05 - sys_3: 1.3248894278471846e-05 - sys_4: -3.970792674888402e-05 - sys_5: 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1.5894720189337258e-06 + sys_45: 2.827404061128979e-06 + sys_46: -1.1777475286095222e-06 + sys_47: 1.0061245075697067e-05 + sys_48: 5.307416038113322e-07 + sys_49: -2.1418956485365814e-07 + sys_50: -7.265846869735079e-07 + sys_51: -3.754872273980297e-06 + sys_52: -6.075513407388858e-06 + sys_53: -7.728853689758051e-06 + sys_54: -3.22709937560555e-09 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml index 4fefae556b..4963e10c6c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2009POL sys_0: description: 0 artificial correlated systematics uncertainty treatment: 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml @@ -4,7 +4,7 @@ definitions: treatment: ADD type: UNCORR pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2009POL sys_0: @@ -230,400 +230,400 @@ definitions: bins: - stat: 0.0034 pol: 0.0004355 - sys_0: -1.274586879789524e-09 - sys_1: 5.120321055524734e-09 - sys_2: 6.386890279104146e-09 - sys_3: 1.6368391716771655e-08 - sys_4: -1.8765961851970036e-08 - sys_5: 5.2409634204267686e-08 - sys_6: 1.2667280621968831e-07 - sys_7: 1.0533077232802617e-07 - sys_8: -5.909593501639714e-08 - sys_9: -5.3705550597596395e-09 - sys_10: 1.878455105192114e-07 - sys_11: -6.805393160207615e-07 - sys_12: -2.1151478452123076e-07 - sys_13: -2.4291859665454397e-07 - sys_14: 3.4061535035915066e-07 - sys_15: -3.509073850662398e-07 - sys_16: -3.2485767379750544e-07 - sys_17: 1.281411980645475e-06 - sys_18: -3.6722707093442684e-06 - sys_19: 1.2322367810306649e-06 - 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sys_29: 2.8999198047488913e-07 + sys_30: -2.253258053254972e-07 + sys_31: 3.9601568719208075e-07 + sys_32: 1.5337045487717176e-07 + sys_33: -2.7504011631279344e-07 + sys_34: 1.2918837314709957e-06 + sys_35: -3.7971203852028345e-06 + sys_36: 5.698508820109633e-06 + sys_37: -3.018818384445657e-06 + sys_38: -9.12783504782493e-07 + sys_39: -1.0765605829953466e-05 + sys_40: 6.167187763725935e-06 + sys_41: -2.2195801791596086e-06 + sys_42: 4.406622240495831e-06 + sys_43: 1.982458690890039e-06 + sys_44: -2.4338295905271175e-07 + sys_45: -9.5816551240627e-07 + sys_46: -4.652151630609244e-07 + sys_47: -7.582886239261119e-06 + sys_48: -7.357573161494456e-07 + sys_49: 8.351743182244022e-07 + sys_50: -8.909902905486228e-06 + sys_51: -2.5005751958077052e-05 + sys_52: 1.5711433681083293e-05 + sys_53: 1.4611441526549908e-05 + sys_54: 1.8962497882454983e-05 From 0840309c55a9374df090d6351c78cf2d762d6fbe Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 16 May 2024 15:11:33 +0200 Subject: [PATCH 39/98] make notation more uniform --- .../star/jet_dijet_2012_510gev.py | 4 +- .../star/jet_dijet_2015_200gev.py | 4 +- .../STAR_2012_1JET_510GEV/uncertainties.yaml | 1560 ++++++++--------- .../uncertainties.yaml | 1118 ++++++------ .../uncertainties.yaml | 1224 ++++++------- .../uncertainties.yaml | 1114 ++++++------ .../uncertainties.yaml | 1234 ++++++------- .../STAR_2015_1JET_200GEV/uncertainties.yaml | 2 +- .../uncertainties.yaml | 2 +- .../uncertainties.yaml | 2 +- .../STAR_WMWP_510GEV/rawdata/TableI.csv | 13 - 11 files changed, 3132 insertions(+), 3145 deletions(-) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py index a5e6c95dd2..dbf8810e09 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py @@ -154,7 +154,7 @@ def write_1jet_data(df, art_sys): "type": f"STAR{YEAR}LUMIUE", }, "pol": { - "description": "polarization uncertainty", + "description": "beam polarization uncertainty", "treatment": "MULT", "type": f"STAR{YEAR}POL", }, @@ -223,7 +223,7 @@ def write_2jet_data(df, topology, art_sys): "type": f"STAR{YEAR}LUMIUE", }, "pol": { - "description": "polarization uncertainty", + "description": "beam polarization uncertainty", "treatment": "MULT", "type": f"STAR{YEAR}POL", }, diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py index 54eff99e2b..1ab48279a6 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -177,7 +177,7 @@ def write_1jet_data(df, art_sys): "type": f"STAR{YEAR}LUMI", }, "pol": { - "description": "polarization uncertainty", + "description": "beam polarization uncertainty", "treatment": "MULT", "type": f"STAR{YEAR}POL", }, @@ -246,7 +246,7 @@ def write_2jet_data(df, topology, art_sys): "type": f"STAR{YEAR}LUMI", }, "pol": { - "description": "polarization uncertainty", + "description": "beam polarization uncertainty", "treatment": "MULT", "type": f"STAR{YEAR}POL", }, diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml index c739bb1293..980bcb0d3e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml @@ -4,7 +4,7 @@ definitions: treatment: ADD type: STAR2012LUMIUE pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2012POL sys_0: @@ -234,813 +234,813 @@ definitions: bins: - lumi_ue: 0.000364 pol: 1.1285999999999999e-06 - sys_0: -8.307118087449861e-06 - sys_1: 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3.873154541500846e-10 + sys_53: 1.1239378569623433e-09 + sys_54: 1.3794245316759332e-09 + sys_55: 1.2540320616809989e-09 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml index b3d2a0bed4..5b579de570 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml @@ -8,7 +8,7 @@ definitions: treatment: ADD type: STAR2012LUMIUE pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2012POL sys_0: @@ -239,590 +239,590 @@ bins: - stat: 0.0066 lumi_ue: 0.00025 pol: -0.0008448 - sys_0: -2.805509704053403e-07 - sys_1: -9.080946026723136e-07 - sys_2: -1.407599060571745e-06 - sys_3: -2.58940752425597e-07 - sys_4: -1.0691808461563776e-06 - sys_5: -4.536010215287258e-07 - sys_6: 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5.057035821136519e-09 + sys_53: -4.73378897547653e-09 + sys_54: -7.625033692997295e-09 + sys_55: -5.714486455339293e-09 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml index 73ada91996..dcc2c25a2d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml @@ -8,7 +8,7 @@ definitions: treatment: ADD type: STAR2012LUMIUE pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2012POL sys_0: @@ -239,649 +239,649 @@ bins: - stat: 0.0053 lumi_ue: 0.0004 pol: -0.0001518 - sys_0: -4.902699695448591e-07 - sys_1: -9.667668405608408e-07 - sys_2: -1.5946010176743313e-06 - sys_3: -3.0465509550549473e-07 - sys_4: -1.2640171400177132e-06 - sys_5: -6.928951928115747e-07 - sys_6: 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a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml @@ -8,7 +8,7 @@ definitions: treatment: ADD type: STAR2012LUMIUE pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2012POL sys_0: @@ -239,649 +239,649 @@ bins: - stat: 0.0161 lumi_ue: 0.00131 pol: 0.00035640000000000004 - sys_0: -2.3154113365218819e-07 - sys_1: -3.7267138112821394e-07 - sys_2: -4.938278337538548e-07 - sys_3: -1.9105505580524943e-08 - sys_4: -3.71179059434131e-07 - sys_5: -2.661581999735158e-07 - sys_6: -4.0325055626736195e-07 - sys_7: 1.0504709968466284e-07 - sys_8: 4.0292269124092077e-07 - sys_9: -5.036540997113695e-07 - sys_10: 3.231699427928327e-07 - sys_11: 1.85288862173259e-07 - sys_12: -4.9996980553325e-07 - sys_13: 7.823987848697804e-07 - sys_14: 1.6657487304900722e-07 - sys_15: -1.0413202313613613e-06 - sys_16: 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sys_31: 5.319591825335949e-07 - sys_32: -5.3722987988595e-07 - sys_33: -1.118083000905433e-06 - sys_34: 1.4774644867346329e-07 - sys_35: -8.871044790525259e-07 - sys_36: 9.143889491935902e-09 - sys_37: 6.866520829349101e-07 - sys_38: 1.151286548066188e-08 - sys_39: 5.937089612155706e-07 - sys_40: 6.162087831629744e-07 - sys_41: 9.206009972349796e-08 - sys_42: 4.8342680643373803e-08 - sys_43: -9.355065654867285e-09 - sys_44: 6.393413859155355e-08 - sys_45: -4.6977023058533314e-08 - sys_46: -1.4995361978283547e-08 - sys_47: -3.041193870623935e-07 - sys_48: 8.54692434612174e-08 - sys_49: -1.8316145562561607e-08 - sys_50: 6.202278518462283e-08 - sys_51: -1.649431626782716e-08 - sys_52: 1.1828217804672864e-08 - sys_53: -4.714010101532377e-09 - sys_54: -9.52101868262452e-09 - sys_55: -7.908290426298496e-09 + sys_0: -0.0002353037952245309 + sys_1: -0.00036830730606138024 + sys_2: 9.291108786405641e-05 + sys_3: -0.00026115335142695966 + sys_4: 0.00021075523705060408 + sys_5: -9.676006479568943e-05 + sys_6: 0.00036373591523841453 + sys_7: 0.0026145815906941944 + sys_8: 0.0007305503029863315 + sys_9: -2.912491603867989e-05 + sys_10: -2.9078723566267203e-06 + sys_11: -9.61933362187506e-06 + sys_12: -8.094677789110515e-05 + sys_13: 6.489923988253502e-05 + sys_14: -5.440215890909567e-05 + sys_15: 1.2468583215232634e-05 + sys_16: -1.6536855235626036e-06 + sys_17: -1.4293319393960597e-05 + sys_18: 8.828802204183915e-06 + sys_19: 3.4938933554401847e-06 + sys_20: 1.7404826469641243e-06 + sys_21: -3.3525223975719524e-05 + sys_22: 6.07187336964375e-07 + sys_23: -6.498961405769061e-07 + sys_24: 8.704036262423727e-07 + sys_25: -9.914578391753282e-07 + sys_26: 5.404568769037833e-06 + sys_27: -4.1561505443783717e-07 + sys_28: -5.84640243140985e-06 + sys_29: 7.798725876953713e-07 + sys_30: -3.940788446788026e-07 + sys_31: 5.319591825335496e-07 + sys_32: -5.372298798859224e-07 + sys_33: -1.118083000905457e-06 + sys_34: 1.4774644867348388e-07 + sys_35: -8.871044790525757e-07 + sys_36: 9.143889491996847e-09 + sys_37: 6.866520829348929e-07 + sys_38: 1.1512865480641473e-08 + sys_39: 5.937089612155762e-07 + sys_40: 6.162087831629411e-07 + sys_41: 9.20600997234738e-08 + sys_42: 4.834268064336428e-08 + sys_43: -9.35506565487487e-09 + sys_44: 6.393413859152546e-08 + sys_45: -4.697702305855357e-08 + sys_46: -1.499536197825626e-08 + sys_47: 3.0411938706239006e-07 + sys_48: 8.546924346123226e-08 + sys_49: -1.8316145562551433e-08 + sys_50: 6.202278518461742e-08 + sys_51: -1.649431626780826e-08 + sys_52: 1.1828217804666922e-08 + sys_53: -4.714010101544476e-09 + sys_54: -9.521018682603238e-09 + sys_55: -7.908290426262239e-09 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml index 60b5034dc8..912fac3252 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -4,7 +4,7 @@ definitions: treatment: ADD type: STAR2015LUMI pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2015POL sys_0: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml index 81e755f78e..27059f57b1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml @@ -8,7 +8,7 @@ definitions: treatment: ADD type: STAR2015LUMI pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2015POL sys_0: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml index edb145df81..3f48767aa6 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml @@ -8,7 +8,7 @@ definitions: treatment: ADD type: STAR2015LUMI pol: - description: polarization uncertainty + description: beam polarization uncertainty treatment: MULT type: STAR2015POL sys_0: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv deleted file mode 100644 index eae495e12d..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/rawdata/TableI.csv +++ /dev/null @@ -1,13 +0,0 @@ -process, etae, W-, W-, W-, W-, W-, W-, W+, W+, W+, W+, W+, W+ -W-, -1.27, 1.0, 0.006, 0.009, 0.010, 0.019, 0.007, -0.229, -0.006, -0.021, -0.021, -0.021, -0.001 -W-, -0.74, 0, 1, 0.024, 0.023, 0.041, 0.008, -0.013, 0.003, -0.022, -0.050, -0.027, -0.005 -W-, -0.27, 0, 0, 1, 0.019, 0.037, 0.005, -0.014, -0.017, -0.041, -0.049, -0.055, -0.003 -W-, 0.27, 0, 0, 0, 1, 0.031, 0.001, -0.011, -0.009, -0.029, -0.040, -0.039, -0.009 -W-, 0.74, 0, 0, 0, 0, 1, 0.014, -0.017, -0.018, -0.054, -0.075, -0.062, -0.012 -W-, 1.27, 0, 0, 0, 0, 0, 1, -0.002, -0.004, -0.008, -0.015, -0.014, -0.238 -W+, -1.24, 0, 0, 0, 0, 0, 0, 1, 0.018, 0.035, 0.034, 0.040, 0.021 -W+, -0.72, 0, 0, 0, 0, 0, 0, 0, 1, 0.150, 0.146, 0.209, 0.010 -W+, -0.24, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.190, 0.232, 0.026 -W+, 0.24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.244, 0.030 -W+, 0.72, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0.029 -W+, 1.24, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 \ No newline at end of file From 63b17604b2ceaf55ea23dd6a5f2332ea63363b2f Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 16 May 2024 15:25:11 +0200 Subject: [PATCH 40/98] Add beam pol error to phenix --- .../PHENIX_1JET_200GEV/filter.py | 10 ++++-- .../PHENIX_1JET_200GEV/kinematics.yaml | 32 +++++++++---------- .../PHENIX_1JET_200GEV/uncertainties.yaml | 12 +++++++ 3 files changed, 36 insertions(+), 18 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py index 4542947712..354ca7c419 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py @@ -3,6 +3,7 @@ import pandas as pd import yaml +POL_UNC = 0.094 def read_data(fnames): df = pd.DataFrame() @@ -35,6 +36,7 @@ def read_data(fnames): ignore_index=True, ) + df["pol"] = POL_UNC * abs(df["ALL"]) return df @@ -73,11 +75,15 @@ def write_data(df): # Write unc file error = [] for i in range(len(df)): - e = {"stat": float(df.loc[i, "stat"])} + e = { + "stat": float(df.loc[i, "stat"]), + "pol": float(df.loc[i, "pol"]) + } error.append(e) error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"} + "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "pol": {"description": "beam polarization uncertainty", "treatment": "MULT", "type": "PHENIXPOL"} } uncertainties_yaml = {"definitions": error_definition, "bins": error} diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml index 45e1315eb4..0d4a0e41b3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml @@ -8,9 +8,9 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 - pT: min: 3.0 mid: 3.4 @@ -20,9 +20,9 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 - pT: min: 4.0 mid: 4.4 @@ -32,9 +32,9 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 - pT: min: 5.0 mid: 5.4 @@ -44,9 +44,9 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 - pT: min: 6.0 mid: 6.4 @@ -56,9 +56,9 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 - pT: min: 7.0 mid: 7.4 @@ -68,9 +68,9 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 - pT: min: 8.0 mid: 8.8 @@ -80,9 +80,9 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 - pT: min: 10.0 mid: 10.8 @@ -92,6 +92,6 @@ bins: mid: 200.0 max: null eta: - min: null + min: -0.35 mid: 0.0 - max: null + max: 0.35 diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml index 6b799cce3d..75b9112af7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml @@ -3,12 +3,24 @@ definitions: description: statistical uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: PHENIXPOL bins: - stat: 7.7e-05 + pol: 6.58e-05 - stat: 0.00082 + pol: 0.00036659999999999997 - stat: 0.00052 + pol: 0.0001316 - stat: 0.0003 + pol: 4.7000000000000004e-05 - stat: 0.0052 + pol: 0.0005451999999999999 - stat: 0.0045 + pol: 0.00031959999999999996 - stat: 0.012 + pol: 0.0007238 - stat: 0.051 + pol: 0.0017014 From 4f5460e084db5738d65a08ac9819922d7e97a6f1 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 16 May 2024 15:30:00 +0200 Subject: [PATCH 41/98] remove minus sign from pol unc --- .../filter_utils/star/jet_dijet_2009_200gev.py | 6 +++--- .../filter_utils/star/jet_dijet_2012_510gev.py | 4 ++-- .../filter_utils/star/jet_dijet_2013_510gev.py | 4 ++-- .../filter_utils/star/jet_dijet_2015_200gev.py | 4 ++-- .../STAR_2009_2JET_A_200GEV/uncertainties.yaml | 2 +- .../STAR_2009_2JET_B_200GEV/uncertainties.yaml | 4 ++-- .../STAR_2009_2JET_C_200GEV/uncertainties.yaml | 2 +- .../STAR_2009_2JET_OS_200GEV/uncertainties.yaml | 2 +- .../STAR_2012_1JET_510GEV/uncertainties.yaml | 4 ++-- .../STAR_2012_2JET_A_510GEV/uncertainties.yaml | 8 ++++---- .../STAR_2012_2JET_B_510GEV/uncertainties.yaml | 12 ++++++------ .../STAR_2012_2JET_C_510GEV/uncertainties.yaml | 6 +++--- .../STAR_2012_2JET_D_510GEV/uncertainties.yaml | 8 ++++---- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 4 ++-- .../STAR_2013_2JET_A_510GEV/uncertainties.yaml | 6 +++--- .../STAR_2013_2JET_B_510GEV/uncertainties.yaml | 4 ++-- .../STAR_2013_2JET_C_510GEV/uncertainties.yaml | 6 +++--- .../STAR_2013_2JET_D_510GEV/uncertainties.yaml | 2 +- .../STAR_2015_1JET_200GEV/uncertainties.yaml | 2 +- 19 files changed, 45 insertions(+), 45 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index f4ddf73b2c..83435af0a2 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -81,7 +81,7 @@ def read_1jet_data(): df["stat"] = df["stat_max"] df["sys"] = df["sys_max"] - df["pol"] = POL_UNC * df["ALL"] + df["pol"] = POL_UNC * abs(df["ALL"]) df["sqrts"] = 200 df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 return df, dfc @@ -110,7 +110,6 @@ def read_2jet_data(topology): "ALL": [Gsub[i]["value"]], "stat": [Gsub[i]["errors"][0]["symerror"]], "sys": [Gsub[i]["errors"][1]["symerror"]], - "pol": [POL_UNC * Gsub[i]["value"]], } ), ], @@ -131,12 +130,13 @@ def read_2jet_data(topology): "ALL": [Gsub[i]["value"]], "stat": [Gsub[i]["errors"][0]["symerror"]], "sys": [Gsub[i]["errors"][1]["symerror"]], - "pol": [POL_UNC * Gsub[i]["value"]], } ), ], ignore_index=True, ) + + df["pol"] = POL_UNC * abs(df["ALL"]) df["sqrts"] = 200 return df diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py index dbf8810e09..f9ed502523 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py @@ -41,7 +41,7 @@ def read_1jet_data(): df["ALL"] = all_data["Inclusive Jet $A_{LL}$"] df["stat"] = all_data["stat +"] df["syst"] = all_data["sys +"] - df["pol"] = POL_UNC * df["ALL"] + df["pol"] = POL_UNC * abs(df["ALL"]) df["lumi_ue"] = all_data["UE/RL sys +"] print("1JET data loaded. Npoint: ", len(df)) @@ -62,7 +62,7 @@ def read_2jet_data(topology): df["ALL"] = all_data[r"DiJet $A_{LL}$"] df["stat"] = all_data[r"stat +"] df["syst"] = all_data[r"sys +"] - df["pol"] = POL_UNC * df["ALL"] + df["pol"] = POL_UNC * abs(df["ALL"]) df["lumi_ue"] = all_data["UE/RL sys +"] print(f"2JET {topology} data loaded. Npoint: ", len(df)) return df diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 0c78c18086..0aa6270daa 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -48,7 +48,7 @@ def read_1jet_data(): df["ALL"] = all_data[r"Inclusive Jet $A_{LL}$"] df["stat"] = all_data[r"stat +"] df["syst"] = all_data[r"syst +"] - df["pol"] = POL_UNC * df["ALL"] + df["pol"] = POL_UNC * abs(df["ALL"]) print("1JET data loaded. Npoint: ", len(df)) return df @@ -75,7 +75,7 @@ def read_2jet_data(topology): df["ALL"] = all_data[r"Dijet $A_{LL}$, topology " + topology] df["stat"] = all_data[r"stat +"] df["syst"] = all_data[r"syst +"] - df["pol"] = POL_UNC * df["ALL"] + df["pol"] = POL_UNC * abs(df["ALL"]) print(f"2JET {topology} data loaded. Npoint: ", len(df)) return df diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py index 1ab48279a6..45b922e2b6 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -69,7 +69,7 @@ def read_1jet_data(topology): df["stat"] = all_data["Stat +"] df["syst"] = all_data["Syst +"] df["lumi"] = all_data["Lumi +"] - df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] / 100 + df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * abs(df["ALL"]) / 100 print(f"1JET {topology} data loaded. Npoint: ", len(df)) return df @@ -94,7 +94,7 @@ def read_2jet_data(topology): df["stat"] = all_data["Stat +"] df["syst"] = all_data["Syst +"] df["lumi"] = all_data["Lumi +"] - df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * df["ALL"] / 100 + df["pol"] = [float(a[:-1]) for a in all_data["Pol +"]] * abs(df["ALL"]) / 100 print(f"2JET {topology} data loaded. Npoint: ", len(df)) return df diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml index 316794bffb..3014e4ff94 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml @@ -286,7 +286,7 @@ bins: sys_53: -1.3383755092384615e-05 sys_54: -1.8477958927326992e-06 - stat: 0.007 - pol: -0.0004485 + pol: 0.0004485 sys_0: -5.898643235004763e-09 sys_1: 1.1973393935558007e-08 sys_2: 7.779654506237548e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml index ec6c430437..3a9c19699f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml @@ -229,7 +229,7 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.011 - pol: -0.001157 + pol: 0.001157 sys_0: -4.317226197359973e-06 sys_1: 2.804090271237943e-06 sys_2: 1.533190350417484e-05 @@ -457,7 +457,7 @@ bins: sys_53: 0.00010281804050324985 sys_54: 1.5989602302115842e-06 - stat: 0.006 - pol: -0.000507 + pol: 0.000507 sys_0: -1.1948431354382126e-08 sys_1: 3.0725225774528344e-08 sys_2: 1.3121131028579732e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml index 4963e10c6c..ce7cc0bb85 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml @@ -229,7 +229,7 @@ definitions: type: STAR2009JETunc54 bins: - stat: 0.005 - pol: -0.000221 + pol: 0.000221 sys_0: -1.6474452057447097e-05 sys_1: 9.040581896830213e-06 sys_2: 4.939301509717909e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml index effff006bf..c24405504c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml @@ -571,7 +571,7 @@ bins: sys_53: 3.436424253953864e-05 sys_54: 1.7338848023477177e-05 - stat: 0.034 - pol: -0.001833 + pol: 0.001833 sys_0: -0.0004729438978473299 sys_1: 0.0008890863729381828 sys_2: 0.0004354023436035268 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml index 980bcb0d3e..e8b010c7e7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml @@ -291,7 +291,7 @@ bins: sys_54: 6.642412401033884e-08 sys_55: 2.989440268976087e-08 - lumi_ue: 0.000326 - pol: -0.0001419 + pol: 0.0001419 sys_0: -2.0921351534260138e-05 sys_1: -5.210515573264161e-05 sys_2: -7.883883196479737e-05 @@ -871,7 +871,7 @@ bins: sys_54: 1.2768133354700673e-08 sys_55: 6.398558309347824e-09 - lumi_ue: 0.000229 - pol: -0.00032472 + pol: 0.00032472 sys_0: -0.0002343943549651195 sys_1: -0.0006912852647517847 sys_2: -0.0010950945884863734 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml index 5b579de570..162612712a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml @@ -238,7 +238,7 @@ definitions: bins: - stat: 0.0066 lumi_ue: 0.00025 - pol: -0.0008448 + pol: 0.0008448 sys_0: -2.805509704053412e-07 sys_1: -9.08094602672307e-07 sys_2: -1.4075990605717301e-06 @@ -415,7 +415,7 @@ bins: sys_55: -1.2004462998292904e-08 - stat: 0.0052 lumi_ue: 0.00056 - pol: -7.92e-05 + pol: 7.92e-05 sys_0: -1.5516363965195575e-06 sys_1: -3.819541974484555e-06 sys_2: -6.110267105737368e-06 @@ -533,7 +533,7 @@ bins: sys_55: -1.0343821375710476e-07 - stat: 0.0064 lumi_ue: 0.00046 - pol: -8.58e-05 + pol: 8.58e-05 sys_0: -3.2252909912886183e-06 sys_1: -9.621586241801297e-06 sys_2: -1.2612132861387332e-05 @@ -769,7 +769,7 @@ bins: sys_55: -2.7481844478537882e-08 - stat: 0.0264 lumi_ue: 0.00031 - pol: -0.0014388 + pol: 0.0014388 sys_0: -0.00037960228302466 sys_1: -0.0008299122305492342 sys_2: -6.834069276424717e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml index dcc2c25a2d..4237b0b490 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml @@ -238,7 +238,7 @@ definitions: bins: - stat: 0.0053 lumi_ue: 0.0004 - pol: -0.0001518 + pol: 0.0001518 sys_0: -4.902699695448577e-07 sys_1: -9.667668405608368e-07 sys_2: -1.5946010176743127e-06 @@ -474,7 +474,7 @@ bins: sys_55: 5.923882523477875e-07 - stat: 0.004 lumi_ue: 0.00035 - pol: -0.0004158 + pol: 0.0004158 sys_0: -3.225178777597023e-06 sys_1: -7.971143948508409e-06 sys_2: -1.2162407448165686e-05 @@ -651,7 +651,7 @@ bins: sys_55: 4.980004554119997e-08 - stat: 0.0065 lumi_ue: 0.00031 - pol: -0.0001452 + pol: 0.0001452 sys_0: -2.175773795117016e-05 sys_1: -6.100899570616473e-05 sys_2: -3.820341607560011e-05 @@ -710,7 +710,7 @@ bins: sys_55: 1.5964316831141426e-08 - stat: 0.0096 lumi_ue: 0.00028 - pol: -6.6e-05 + pol: 6.6e-05 sys_0: -5.6415492963582885e-05 sys_1: -0.00013037144102324703 sys_2: -2.5123448784175437e-05 @@ -769,7 +769,7 @@ bins: sys_55: -4.543637845044443e-09 - stat: 0.0143 lumi_ue: 0.00026 - pol: -0.001056 + pol: 0.001056 sys_0: -0.0001898264278735877 sys_1: -0.00032773442170312787 sys_2: 2.108926777342305e-05 @@ -828,7 +828,7 @@ bins: sys_55: 9.969069014003858e-10 - stat: 0.0242 lumi_ue: 0.00026 - pol: -0.001353 + pol: 0.001353 sys_0: -0.0005209612086173433 sys_1: -0.0005471459737548793 sys_2: 0.00017883143939242103 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml index 121a0a284f..a776bb33c5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml @@ -297,7 +297,7 @@ bins: sys_55: 5.72639189997753e-05 - stat: 0.0066 lumi_ue: 0.00063 - pol: -3.96e-05 + pol: 3.96e-05 sys_0: -3.1058702383039053e-06 sys_1: -8.047346121200812e-06 sys_2: -1.2619998147756938e-05 @@ -356,7 +356,7 @@ bins: sys_55: 1.604692861430179e-08 - stat: 0.0062 lumi_ue: 0.00074 - pol: -0.0002838 + pol: 0.0002838 sys_0: -1.5296553532175391e-06 sys_1: -3.699624474442674e-06 sys_2: -5.990225452511461e-06 @@ -592,7 +592,7 @@ bins: sys_55: -1.7909097782400058e-08 - stat: 0.0098 lumi_ue: 0.00053 - pol: -0.000297 + pol: 0.000297 sys_0: -9.535866036672388e-06 sys_1: -2.9383079086345657e-05 sys_2: -3.1764714114833526e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml index 5e73b78d7b..ff72eb9892 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml @@ -415,7 +415,7 @@ bins: sys_55: -8.067733278269338e-07 - stat: 0.0059 lumi_ue: 0.00052 - pol: -0.0002046 + pol: 0.0002046 sys_0: -7.983724791301123e-07 sys_1: -2.164374986572867e-06 sys_2: -3.488418996290781e-06 @@ -474,7 +474,7 @@ bins: sys_55: -4.1807390266790274e-07 - stat: 0.006 lumi_ue: 0.00054 - pol: -0.0001188 + pol: 0.0001188 sys_0: -1.536345762050751e-06 sys_1: -3.6865985845742023e-06 sys_2: -5.725658777249105e-06 @@ -533,7 +533,7 @@ bins: sys_55: -2.3167073502523317e-07 - stat: 0.007 lumi_ue: 0.00044 - pol: -0.000264 + pol: 0.000264 sys_0: -2.00200738328954e-06 sys_1: -5.577888629561237e-06 sys_2: -8.234306983075932e-06 @@ -828,7 +828,7 @@ bins: sys_55: -1.748120217185071e-08 - stat: 0.0461 lumi_ue: 0.00029 - pol: -0.000363 + pol: 0.000363 sys_0: -0.0002353037952245309 sys_1: -0.00036830730606138024 sys_2: 9.291108786405641e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml index b9a701233d..b75f70c586 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml @@ -448,7 +448,7 @@ bins: sys_60: -2.0567211467696776e-06 sys_61: 8.583540740030501e-07 sys_62: 1.5503622047436774e-07 -- pol: -4.8e-05 +- pol: 4.8e-05 sys_0: -2.317611030883938e-09 sys_1: 2.0103077754186072e-08 sys_2: 1.221490288409029e-07 @@ -512,7 +512,7 @@ bins: sys_60: -1.967785012922417e-06 sys_61: 1.7222827306715096e-06 sys_62: -9.247304481271197e-07 -- pol: -5.44e-05 +- pol: 5.44e-05 sys_0: -5.794556391557737e-09 sys_1: 4.184211349903503e-08 sys_2: 2.6618567237308233e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml index 0999d0879c..56115a4a24 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml @@ -261,7 +261,7 @@ definitions: type: STAR2013JETunc62 bins: - stat: 0.00619 - pol: -0.00035072 + pol: 0.00035072 sys_0: -1.8442665253564098e-08 sys_1: 9.128062228545417e-08 sys_2: 3.0998812240715233e-07 @@ -326,7 +326,7 @@ bins: sys_61: 1.2764542310865707e-05 sys_62: 4.157211360391717e-05 - stat: 0.00289 - pol: -7.04e-06 + pol: 7.04e-06 sys_0: -7.838875974830611e-08 sys_1: 4.029804267681053e-07 sys_2: 1.4263812561994197e-06 @@ -976,7 +976,7 @@ bins: sys_61: 1.1661958762446107e-05 sys_62: 1.6078432326039527e-06 - stat: 0.02919 - pol: -0.0005049599999999999 + pol: 0.0005049599999999999 sys_0: -0.0001582145343682221 sys_1: 0.00023785644592245637 sys_2: 0.00018923810995146129 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml index 34be003f02..dfa684d8e9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml @@ -391,7 +391,7 @@ bins: sys_61: -5.8887611946663265e-05 sys_62: 8.398314077938356e-05 - stat: 0.00173 - pol: -7.424000000000001e-05 + pol: 7.424000000000001e-05 sys_0: -8.530127204466283e-08 sys_1: 4.29673266336131e-07 sys_2: 1.3304320577341956e-06 @@ -521,7 +521,7 @@ bins: sys_61: -2.8427700023791145e-06 sys_62: -3.796889291143406e-05 - stat: 0.00161 - pol: -3.84e-05 + pol: 3.84e-05 sys_0: -1.1169536414096341e-07 sys_1: 5.629576028352181e-07 sys_2: 1.7886807965226788e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml index 97100b4c63..0d9d0e60ec 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml @@ -261,7 +261,7 @@ definitions: type: STAR2013JETunc62 bins: - stat: 0.00785 - pol: -0.0007392 + pol: 0.0007392 sys_0: -4.100959127774964e-07 sys_1: 1.222332698478793e-06 sys_2: 2.05687127807516e-06 @@ -391,7 +391,7 @@ bins: sys_61: 3.3264670285405464e-06 sys_62: -5.3538188824715525e-06 - stat: 0.00317 - pol: -0.00018752 + pol: 0.00018752 sys_0: -7.06985540704637e-07 sys_1: 2.047809323259492e-06 sys_2: 3.206126094091834e-06 @@ -976,7 +976,7 @@ bins: sys_61: -3.8814180019798167e-07 sys_62: 5.229117363656164e-06 - stat: 0.03322 - pol: -0.000368 + pol: 0.000368 sys_0: -0.0001821538669113795 sys_1: 0.0002428086358083653 sys_2: 0.00019902420286007486 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml index 0266f9664b..4aad0bb3f6 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml @@ -456,7 +456,7 @@ bins: sys_61: 4.3081557252252836e-06 sys_62: -1.06050585369882e-05 - stat: 0.00229 - pol: -4.6080000000000006e-05 + pol: 4.6080000000000006e-05 sys_0: -1.0343763729771366e-06 sys_1: 3.447940072340132e-06 sys_2: 7.205331797379565e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml index 912fac3252..0815fda9fb 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -607,7 +607,7 @@ bins: sys_34: -3.1959478982973937e-07 sys_35: -8.284104652471781e-07 lumi: 0.0007 - pol: -1.2810000000000001e-05 + pol: 1.2810000000000001e-05 - sys_0: -6.372141793123253e-06 sys_1: 1.0618676135602555e-05 sys_2: -1.4184286764078104e-05 From a565ab89ad7edca58cdfc7730046a9c32b560f80 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 16 May 2024 15:41:00 +0200 Subject: [PATCH 42/98] adding pol unc to 2005 and 2006 data --- .../new_commondata/PHENIX_1JET_200GEV/filter.py | 2 +- .../PHENIX_1JET_200GEV/uncertainties.yaml | 2 +- .../new_commondata/STAR_2005_1JET_200GEV/filter.py | 9 ++++++++- .../STAR_2005_1JET_200GEV/uncertainties.yaml | 14 ++++++++++++++ .../new_commondata/STAR_2006_1JET_200GEV/filter.py | 9 ++++++++- .../STAR_2006_1JET_200GEV/uncertainties.yaml | 13 +++++++++++++ 6 files changed, 45 insertions(+), 4 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py index 354ca7c419..0fcc8f88c4 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py @@ -83,7 +83,7 @@ def write_data(df): error_definition = { "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "pol": {"description": "beam polarization uncertainty", "treatment": "MULT", "type": "PHENIXPOL"} + "pol": {"description": "beam polarization uncertainty", "treatment": "MULT", "type": "RHIC2005POL"} } uncertainties_yaml = {"definitions": error_definition, "bins": error} diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml index 75b9112af7..576a619515 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml @@ -6,7 +6,7 @@ definitions: pol: description: beam polarization uncertainty treatment: MULT - type: PHENIXPOL + type: RHIC2005POL bins: - stat: 7.7e-05 pol: 6.58e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py index 96dbc30394..38673c4cd0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/filter.py @@ -6,6 +6,7 @@ from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +POL_UNC = 0.094 def read_data(fnames): df = pd.DataFrame() @@ -53,6 +54,7 @@ def read_data(fnames): df.loc[i, "sys"] = unc df.loc[i, "ALL"] += shift + df["pol"] = POL_UNC * abs(df["ALL"]) return df @@ -91,12 +93,17 @@ def write_data(df): # Write unc file error = [] for i in range(len(df)): - e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + e = { + "stat": float(df.loc[i, "stat"]), + "sys": float(df.loc[i, "sys"]), + "pol": float(df.loc[i, "pol"]) + } error.append(e) error_definition = { "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "pol": {"description": "beam polarization uncertainty", "treatment": "MULT", "type": "RHIC2005POL"} } uncertainties_yaml = {"definitions": error_definition, "bins": error} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/uncertainties.yaml index 8c448e3378..f5afbd72a1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/uncertainties.yaml @@ -7,24 +7,38 @@ definitions: description: systematic uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: RHIC2005POL bins: - stat: 0.005900000000000001 sys: 0.0024 + pol: 0.0004982 - stat: 0.0054 sys: 0.0018513508581573619 + pol: 0.0002585 - stat: 0.0057 sys: 0.0018055470085267787 + pol: 0.0002162 - stat: 0.0067 sys: 0.002597595041572108 + pol: 0.0013771 - stat: 0.0087 sys: 0.0022422087324778664 + pol: 0.0005875 - stat: 0.0127 sys: 0.002310844001658269 + pol: 0.00029140000000000004 - stat: 0.020300000000000002 sys: 0.002660826939130014 + pol: 0.0013348000000000001 - stat: 0.035 sys: 0.0029 + pol: 0.0049068 - stat: 0.06709999999999999 sys: 0.0040999999999999995 + pol: 0.0053486 - stat: 0.138 sys: 0.004908156476723211 + pol: 0.013817999999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py index 96dbc30394..d305bbb45c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/filter.py @@ -6,6 +6,7 @@ from nnpdf_data.filter_utils.uncertainties import symmetrize_errors as se +POL_UNC = 0.083 def read_data(fnames): df = pd.DataFrame() @@ -53,6 +54,7 @@ def read_data(fnames): df.loc[i, "sys"] = unc df.loc[i, "ALL"] += shift + df["pol"] = POL_UNC * abs(df["ALL"]) return df @@ -91,12 +93,17 @@ def write_data(df): # Write unc file error = [] for i in range(len(df)): - e = {"stat": float(df.loc[i, "stat"]), "sys": float(df.loc[i, "sys"])} + e = { + "stat": float(df.loc[i, "stat"]), + "sys": float(df.loc[i, "sys"]), + "pol": float(df.loc[i, "pol"]), + } error.append(e) error_definition = { "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, "sys": {"description": "systematic uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "pol": {"description": "beam polarization uncertainty", "treatment": "MULT", "type": "STAR2006POL"} } uncertainties_yaml = {"definitions": error_definition, "bins": error} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml index ad0bdfe9d1..5d183cf01f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/uncertainties.yaml @@ -7,22 +7,35 @@ definitions: description: systematic uncertainty treatment: ADD type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2006POL bins: - stat: 0.0053 sys: 0.00331058907144937 + pol: 0.0002739 - stat: 0.0043 sys: 0.002011839953873071 + pol: 0.00030295 - stat: 0.0040999999999999995 sys: 0.002011839953873071 + pol: 0.00085075 - stat: 0.0045000000000000005 sys: 0.001366565036871645 + pol: 0.00011205000000000001 - stat: 0.0058 sys: 0.0011521718621802911 + pol: 0.00076775 - stat: 0.0088 sys: 0.0015898113095584648 + pol: 0.00215385 - stat: 0.0154 sys: 0.0033537292675468 + pol: 0.00222855 - stat: 0.031 sys: 0.004576843890717707 + pol: 0.00197125 - stat: 0.0706 sys: 0.005853204250664759 + pol: 0.0011537 From fd9c6ed43ef08747c095342639700a4808455b7c Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Thu, 16 May 2024 17:42:12 +0200 Subject: [PATCH 43/98] uncorrelate PHENIX from STAR_2005 --- .../new_commondata/PHENIX_1JET_200GEV/data.yaml | 16 ++++++++-------- .../new_commondata/PHENIX_1JET_200GEV/filter.py | 12 +++++++----- .../PHENIX_1JET_200GEV/uncertainties.yaml | 2 +- 3 files changed, 16 insertions(+), 14 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml index a91ae42005..f690926b67 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml @@ -1,9 +1,9 @@ data_central: - - -0.0007 - - 0.0039 - - -0.0014 - - -0.0005 - - 0.0058 - - 0.0034 - - 0.0077 - - -0.0181 +- -0.0007 +- 0.0039 +- -0.0014 +- -0.0005 +- 0.0058 +- 0.0034 +- 0.0077 +- -0.0181 diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py index 0fcc8f88c4..ee7b608009 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py @@ -5,6 +5,7 @@ POL_UNC = 0.094 + def read_data(fnames): df = pd.DataFrame() for fname in fnames: @@ -75,15 +76,16 @@ def write_data(df): # Write unc file error = [] for i in range(len(df)): - e = { - "stat": float(df.loc[i, "stat"]), - "pol": float(df.loc[i, "pol"]) - } + e = {"stat": float(df.loc[i, "stat"]), "pol": float(df.loc[i, "pol"])} error.append(e) error_definition = { "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, - "pol": {"description": "beam polarization uncertainty", "treatment": "MULT", "type": "RHIC2005POL"} + "pol": { + "description": "beam polarization uncertainty", + "treatment": "MULT", + "type": "PHENIXPOL", + }, } uncertainties_yaml = {"definitions": error_definition, "bins": error} diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml index 576a619515..75b9112af7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml @@ -6,7 +6,7 @@ definitions: pol: description: beam polarization uncertainty treatment: MULT - type: RHIC2005POL + type: PHENIXPOL bins: - stat: 7.7e-05 pol: 6.58e-05 From f696309e4cd0ae719aee4828bbdf61a5b1936620 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 12:47:26 +0200 Subject: [PATCH 44/98] revert correlations in phenix and star 2005 --- .../nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py | 2 +- .../new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml | 2 +- 2 files changed, 2 insertions(+), 2 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py index ee7b608009..60170e44dd 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py @@ -84,7 +84,7 @@ def write_data(df): "pol": { "description": "beam polarization uncertainty", "treatment": "MULT", - "type": "PHENIXPOL", + "type": "RHIC2005POL", }, } diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml index 75b9112af7..576a619515 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml @@ -6,7 +6,7 @@ definitions: pol: description: beam polarization uncertainty treatment: MULT - type: PHENIXPOL + type: RHIC2005POL bins: - stat: 7.7e-05 pol: 6.58e-05 From 879fd2653cbf20c353d507a3c81b60c5b124098c Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 12:49:00 +0200 Subject: [PATCH 45/98] init collapsing 2012 dijets --- .../star/jet_dijet_2012_510gev.py | 8 +- .../data_A.yaml} | 0 .../data_B.yaml} | 0 .../data_C.yaml} | 0 .../data_D.yaml} | 0 .../kinematics_A.yaml} | 0 .../kinematics_B.yaml} | 0 .../kinematics_C.yaml} | 0 .../kinematics_D.yaml} | 0 .../STAR_2012_2JET_510GEV/metadata.yaml | 111 ++++++++++++++++++ .../uncertainties_A.yaml} | 0 .../uncertainties_B.yaml} | 0 .../uncertainties_C.yaml} | 0 .../uncertainties_D.yaml} | 0 .../STAR_2012_2JET_A_510GEV/metadata.yaml | 41 ------- .../STAR_2012_2JET_B_510GEV/metadata.yaml | 41 ------- .../STAR_2012_2JET_C_510GEV/metadata.yaml | 41 ------- .../STAR_2012_2JET_D_510GEV/metadata.yaml | 41 ------- 18 files changed, 115 insertions(+), 168 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_A_510GEV/data.yaml => STAR_2012_2JET_510GEV/data_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_B_510GEV/data.yaml => STAR_2012_2JET_510GEV/data_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_C_510GEV/data.yaml => STAR_2012_2JET_510GEV/data_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_D_510GEV/data.yaml => STAR_2012_2JET_510GEV/data_D.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_A_510GEV/kinematics.yaml => STAR_2012_2JET_510GEV/kinematics_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_B_510GEV/kinematics.yaml => STAR_2012_2JET_510GEV/kinematics_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_C_510GEV/kinematics.yaml => STAR_2012_2JET_510GEV/kinematics_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_D_510GEV/kinematics.yaml => STAR_2012_2JET_510GEV/kinematics_D.yaml} (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_A_510GEV/uncertainties.yaml => STAR_2012_2JET_510GEV/uncertainties_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_B_510GEV/uncertainties.yaml => STAR_2012_2JET_510GEV/uncertainties_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_C_510GEV/uncertainties.yaml => STAR_2012_2JET_510GEV/uncertainties_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2012_2JET_D_510GEV/uncertainties.yaml => STAR_2012_2JET_510GEV/uncertainties_D.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py index f9ed502523..dfbd04d786 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py @@ -187,10 +187,10 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{topology}_{SQRTS}GEV/" + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{SQRTS}GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} - with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file) # Write kin file @@ -206,7 +206,7 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -253,7 +253,7 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_D.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/data_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml new file mode 100644 index 0000000000..6be52d89cd --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml @@ -0,0 +1,111 @@ +setname: "STAR_2012_2JET_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +arXiv: + url: "https://arxiv.org/abs/1906.02740" +iNSPIRE: + url: "https://inspirehep.net/literature/1738738" +hepdata: + url: "https://www.hepdata.net/record/ins1738738" + version: 1 + + +version: 1 +version_comment: "Initial implementation, correlations from arXiv" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 10 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_A.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_A.yaml + data_uncertainties: + - uncertainties_A.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology A" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JET_510GEV_A_ALL + - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 11 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_B.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_B.yaml + data_uncertainties: + - uncertainties_C.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology B" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JET_510GEV_B_ALL + - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 10 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_C.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_C.yaml + data_uncertainties: + - uncertainties_C.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology C" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JET_510GEV_C_ALL + - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 11 + tables: [14] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_D.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_D.yaml + data_uncertainties: + - uncertainties_D.yaml + plotting: + dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology D" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2012_2JET_510GEV_D_ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_D.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml deleted file mode 100644 index 636cc9c53b..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_A_510GEV/metadata.yaml +++ /dev/null @@ -1,41 +0,0 @@ -setname: "STAR_2012_2JET_A_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "JETS" - -iNSPIRE: - url: "https://inspirehep.net/literature/1738738" -hepdata: - url: "https://www.hepdata.net/record/ins1738738" - version: 1 -arXiv: - url: https://arxiv.org/abs/1906.02740 - -version: 1 -version_comment: "Initial implementation, correlations from arXiv" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 10 - tables: [14] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology A" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2012_2JJET_A_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml deleted file mode 100644 index 6e31c91b59..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_B_510GEV/metadata.yaml +++ /dev/null @@ -1,41 +0,0 @@ -setname: "STAR_2012_2JET_B_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "JETS" - -iNSPIRE: - url: "https://inspirehep.net/literature/1738738" -hepdata: - url: "https://www.hepdata.net/record/ins1738738" - version: 1 -arXiv: - url: https://arxiv.org/abs/1906.02740 - -version: 1 -version_comment: "Initial implementation, correlations from arXiv" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 11 - tables: [14] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology B" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2012_2JJET_B_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml deleted file mode 100644 index 5a33d1227c..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_C_510GEV/metadata.yaml +++ /dev/null @@ -1,41 +0,0 @@ -setname: "STAR_2012_2JET_C_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "JETS" - -iNSPIRE: - url: "https://inspirehep.net/literature/1738738" -hepdata: - url: "https://www.hepdata.net/record/ins1738738" - version: 1 -arXiv: - url: https://arxiv.org/abs/1906.02740 - -version: 1 -version_comment: "Initial implementation, correlations from arXiv" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 10 - tables: [14] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology C" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2012_2JJET_C_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml deleted file mode 100644 index 2234430df2..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_D_510GEV/metadata.yaml +++ /dev/null @@ -1,41 +0,0 @@ -setname: "STAR_2012_2JET_D_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "JETS" - -iNSPIRE: - url: "https://inspirehep.net/literature/1738738" -hepdata: - url: "https://www.hepdata.net/record/ins1738738" - version: 1 -arXiv: - url: https://arxiv.org/abs/1906.02740 - -version: 1 -version_comment: "Initial implementation, correlations from arXiv" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 11 - tables: [14] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology D" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2012_2JJET_D_510GEV_ALL From 1e39f34118574822597f9646a350c2aca23daf05 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 12:57:59 +0200 Subject: [PATCH 46/98] init collapsing 2013 dijets --- .../star/jet_dijet_2013_510gev.py | 8 +- .../STAR_2013_1JET_510GEV/metadata.yaml | 2 + .../data_A.yaml} | 0 .../data_B.yaml} | 0 .../data_C.yaml} | 0 .../data_D.yaml} | 0 .../kinematics_A.yaml} | 0 .../kinematics_B.yaml} | 0 .../kinematics_C.yaml} | 0 .../kinematics_D.yaml} | 0 .../STAR_2013_2JET_510GEV/metadata.yaml | 110 ++++++++++++++++++ .../uncertainties_A.yaml} | 0 .../uncertainties_B.yaml} | 0 .../uncertainties_C.yaml} | 0 .../uncertainties_D.yaml} | 0 .../STAR_2013_2JET_A_510GEV/metadata.yaml | 39 ------- .../STAR_2013_2JET_B_510GEV/metadata.yaml | 39 ------- .../STAR_2013_2JET_C_510GEV/metadata.yaml | 39 ------- .../STAR_2013_2JET_D_510GEV/metadata.yaml | 39 ------- 19 files changed, 116 insertions(+), 160 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_A_510GEV/data.yaml => STAR_2013_2JET_510GEV/data_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_B_510GEV/data.yaml => STAR_2013_2JET_510GEV/data_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_C_510GEV/data.yaml => STAR_2013_2JET_510GEV/data_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_D_510GEV/data.yaml => STAR_2013_2JET_510GEV/data_D.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_A_510GEV/kinematics.yaml => STAR_2013_2JET_510GEV/kinematics_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_B_510GEV/kinematics.yaml => STAR_2013_2JET_510GEV/kinematics_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_C_510GEV/kinematics.yaml => STAR_2013_2JET_510GEV/kinematics_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_D_510GEV/kinematics.yaml => STAR_2013_2JET_510GEV/kinematics_D.yaml} (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_A_510GEV/uncertainties.yaml => STAR_2013_2JET_510GEV/uncertainties_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_B_510GEV/uncertainties.yaml => STAR_2013_2JET_510GEV/uncertainties_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_C_510GEV/uncertainties.yaml => STAR_2013_2JET_510GEV/uncertainties_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2013_2JET_D_510GEV/uncertainties.yaml => STAR_2013_2JET_510GEV/uncertainties_D.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 0aa6270daa..569cc899dc 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -188,10 +188,10 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{topology}_510GEV/" + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_510GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} - with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file) # Write kin file @@ -207,7 +207,7 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -248,7 +248,7 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml index 0713622d3e..086d96bbdb 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml @@ -4,6 +4,8 @@ nnpdf_metadata: experiment: "STAR" nnpdf31_process: "JETS" +arXiv: + url: https://arxiv.org/abs/2110.11020 iNSPIRE: url: "https://inspirehep.net/literature/1949588" hepdata: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_D.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/data_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml new file mode 100644 index 0000000000..4c0fdecac7 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml @@ -0,0 +1,110 @@ +setname: "STAR_2013_2JET_510GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +arXiv: + url: https://arxiv.org/abs/2110.11020 +iNSPIRE: + url: "https://inspirehep.net/literature/1949588" +hepdata: + url: "https://www.hepdata.net/record/ins1949588" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_A.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_A.yaml + data_uncertainties: + - uncertainties_A.yaml + plotting: + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology A" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JET_A_510GEV_ALL + - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 13 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_B.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_B.yaml + data_uncertainties: + - uncertainties_B.yaml + plotting: + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology B" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JET_B_510GEV_ALL + - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_C.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_C.yaml + data_uncertainties: + - uncertainties_C.yaml + plotting: + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology C" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JET_C_510GEV_ALL + - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 12 + tables: [5] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_D.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_D.yaml + data_uncertainties: + - uncertainties_D.yaml + plotting: + dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology D" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2013_2JET_D_510GEV_ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml deleted file mode 100644 index add2f35e89..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_A_510GEV/metadata.yaml +++ /dev/null @@ -1,39 +0,0 @@ -setname: "STAR_2013_2JET_A_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1949588" -hepdata: - url: "https://www.hepdata.net/record/ins1949588" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 12 - tables: [5] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology A" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2013_2JJET_A_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml deleted file mode 100644 index 01e3001a36..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_B_510GEV/metadata.yaml +++ /dev/null @@ -1,39 +0,0 @@ -setname: "STAR_2013_2JET_B_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1949588" -hepdata: - url: "https://www.hepdata.net/record/ins1949588" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 13 - tables: [5] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology B" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2013_2JJET_B_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml deleted file mode 100644 index 6f04416535..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_C_510GEV/metadata.yaml +++ /dev/null @@ -1,39 +0,0 @@ -setname: "STAR_2013_2JET_C_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1949588" -hepdata: - url: "https://www.hepdata.net/record/ins1949588" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 12 - tables: [5] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology C" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2013_2JJET_C_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml deleted file mode 100644 index 143c30b1f3..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_D_510GEV/metadata.yaml +++ /dev/null @@ -1,39 +0,0 @@ -setname: "STAR_2013_2JET_D_510GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1949588" -hepdata: - url: "https://www.hepdata.net/record/ins1949588" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 12 - tables: [5] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 510 GeV (2013) DIJET $A_{LL}$, topology D" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2013_2JJET_D_510GEV_ALL From 46ecd2ea94f9def9ec8f5455adbc169f53dc50cb Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 13:05:42 +0200 Subject: [PATCH 47/98] init collapsing 2015 dijets --- .../star/jet_dijet_2015_200gev.py | 8 +-- .../STAR_2015_1JET_200GEV/metadata.yaml | 2 + .../data_OS.yaml} | 0 .../data_SS.yaml} | 0 .../kinematics_OS.yaml} | 0 .../kinematics_SS.yaml} | 0 .../metadata.yaml | 64 +++++++++++++++++++ .../uncertainties_OS.yaml} | 0 .../uncertainties_SS.yaml} | 0 .../STAR_2015_2JET_OS_200GEV/metadata.yaml | 39 ----------- .../STAR_2015_2JET_SS_200GEV/metadata.yaml | 39 ----------- 11 files changed, 70 insertions(+), 82 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_2JET_OS_200GEV/data.yaml => STAR_2015_2JET_MIDRAP_200GEV/data_OS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_2JET_SS_200GEV/data.yaml => STAR_2015_2JET_MIDRAP_200GEV/data_SS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_2JET_OS_200GEV/kinematics.yaml => STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_2JET_SS_200GEV/kinematics.yaml => STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml} (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_2JET_OS_200GEV/uncertainties.yaml => STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2015_2JET_SS_200GEV/uncertainties.yaml => STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py index 45b922e2b6..9e6cbd6697 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py @@ -210,10 +210,10 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{topology}_{SQRTS}GEV/" + STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_MIDRAP_{SQRTS}GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} - with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file) # Write kin file @@ -229,7 +229,7 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -275,7 +275,7 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml index ec3fc04699..999d3d8d87 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml @@ -4,6 +4,8 @@ nnpdf_metadata: experiment: "STAR" nnpdf31_process: "JETS" +arXiv: + url: https://arxiv.org/abs/2103.05571 iNSPIRE: url: "https://inspirehep.net/literature/1850855" hepdata: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/data_OS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/data_OS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/data_SS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/data_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml new file mode 100644 index 0000000000..be6ec6eff5 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -0,0 +1,64 @@ +setname: "STAR_2015_2JET_MIDRAP_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +arXiv: + url: https://arxiv.org/abs/2103.05571 +iNSPIRE: + url: "https://inspirehep.net/literature/1850855" +hepdata: + url: "https://www.hepdata.net/record/ins1850855" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL as function of $M_{inv}$, opposite sign $\eta$ topology", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 7 + tables: [2] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_OS.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_OS.yaml + data_uncertainties: + - uncertainties_OS.yaml + plotting: + dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, opposite sign $\eta$ topology" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2015_2JET_MIDRAP_OS_510GEV_ALL + - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: DIJET_POL + ndata: 7 + tables: [2] + kinematics: + variables: + m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} + sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + file: kinematics_SS.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_SS.yaml + data_uncertainties: + - uncertainties_SS.yaml + plotting: + dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, same sign $\eta$ topology" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2015_2JET_MIDRAP_SS_510GEV_ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml deleted file mode 100644 index c93fd4edc9..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_OS_200GEV/metadata.yaml +++ /dev/null @@ -1,39 +0,0 @@ -setname: "STAR_2015_2JET_OS_200GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1850855" -hepdata: - url: "https://www.hepdata.net/record/ins1850855" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, opposite sign $\eta$ topology", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 7 - tables: [2] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, opposite sign $\eta$ topology" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2015_2JJET_OS_510GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml deleted file mode 100644 index 2f79c16f39..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_SS_200GEV/metadata.yaml +++ /dev/null @@ -1,39 +0,0 @@ -setname: "STAR_2015_2JET_SS_200GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1850855" -hepdata: - url: "https://www.hepdata.net/record/ins1850855" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", label: "$A_{LL}$", units: "" } - observable_name: ALL - process_type: DIJET_POL - ndata: 7 - tables: [2] - kinematics: - variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, same sign $\eta$ topology" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2015_2JJET_SS_510GEV_ALL From e5ed5285c69e8b8485ea5914099df9c8aadb4445 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 13:11:11 +0200 Subject: [PATCH 48/98] addind missing refs --- .../nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml | 2 ++ .../new_commondata/STAR_2005_1JET_200GEV/metadata.yaml | 2 ++ .../new_commondata/STAR_2006_1JET_200GEV/metadata.yaml | 2 ++ 3 files changed, 6 insertions(+) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml index d608a07978..6f4fdec05e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml @@ -4,6 +4,8 @@ nnpdf_metadata: experiment: "PHENIX" nnpdf31_process: "JETS" +arXiv: + url: https://arxiv.org/abs/1009.4921 iNSPIRE: url: "https://inspirehep.net/literature/870912" hepdata: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml index aa7892ff86..f0a2a5d56f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml @@ -4,6 +4,8 @@ nnpdf_metadata: experiment: "STAR" nnpdf31_process: "JETS" +arXiv: + url: https://arxiv.org/abs/1205.2735 iNSPIRE: url: "https://inspirehep.net/literature/1114529" hepdata: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml index b8dfe98236..fd33472a5b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml @@ -4,6 +4,8 @@ nnpdf_metadata: experiment: "STAR" nnpdf31_process: "JETS" +arXiv: + url: https://arxiv.org/abs/1205.2735 iNSPIRE: url: "https://inspirehep.net/literature/1114529" hepdata: From 31ab9c2f2067313accf40a64d8ffd665cf11050f Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 13:47:20 +0200 Subject: [PATCH 49/98] some fixes --- .../STAR_2012_2JET_510GEV/metadata.yaml | 10 +++++----- .../STAR_2013_2JET_510GEV/metadata.yaml | 16 ++++++++-------- .../STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml | 8 ++++---- 3 files changed, 17 insertions(+), 17 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml index 6be52d89cd..cc64232cd0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml @@ -18,7 +18,7 @@ version_comment: "Initial implementation, correlations from arXiv" implemented_observables: - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: A-ALL process_type: DIJET_POL ndata: 10 tables: [14] @@ -41,7 +41,7 @@ implemented_observables: FK_tables: - - STAR_2012_2JET_510GEV_A_ALL - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: B-ALL process_type: DIJET_POL ndata: 11 tables: [14] @@ -53,7 +53,7 @@ implemented_observables: kinematic_coverage: [m_jj, sqrts] data_central: data_B.yaml data_uncertainties: - - uncertainties_C.yaml + - uncertainties_B.yaml plotting: dataset_label: "STAR 510 GeV (2012) DIJET $A_{LL}$, topology B" kinematics_override: identity @@ -64,7 +64,7 @@ implemented_observables: FK_tables: - - STAR_2012_2JET_510GEV_B_ALL - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: C-ALL process_type: DIJET_POL ndata: 10 tables: [14] @@ -87,7 +87,7 @@ implemented_observables: FK_tables: - - STAR_2012_2JET_510GEV_C_ALL - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: D-ALL process_type: DIJET_POL ndata: 11 tables: [14] diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml index 4c0fdecac7..e9c6a3be9d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml @@ -17,7 +17,7 @@ version_comment: "Initial implementation" implemented_observables: - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: A-ALL process_type: DIJET_POL ndata: 12 tables: [5] @@ -38,9 +38,9 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_A_510GEV_ALL + - - STAR_2013_2JET_510GEV_A_ALL - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: B-ALL process_type: DIJET_POL ndata: 13 tables: [5] @@ -61,9 +61,9 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_B_510GEV_ALL + - - STAR_2013_2JET_510GEV_B_ALL - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: C-ALL process_type: DIJET_POL ndata: 12 tables: [5] @@ -84,9 +84,9 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_C_510GEV_ALL + - - STAR_2013_2JET_510GEV_C_ALL - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: D-ALL process_type: DIJET_POL ndata: 12 tables: [5] @@ -107,4 +107,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_D_510GEV_ALL \ No newline at end of file + - - STAR_2013_2JET_510GEV_D_ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index be6ec6eff5..fdd4d15b76 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -17,7 +17,7 @@ version_comment: "Initial implementation" implemented_observables: - observable: { description: "ALL as function of $M_{inv}$, opposite sign $\eta$ topology", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: OS-ALL process_type: DIJET_POL ndata: 7 tables: [2] @@ -38,9 +38,9 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_OS_510GEV_ALL + - - STAR_2015_2JET_MIDRAP_510GEV_OS_ALL - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", label: "$A_{LL}$", units: "" } - observable_name: ALL + observable_name: SS-ALL process_type: DIJET_POL ndata: 7 tables: [2] @@ -61,4 +61,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_SS_510GEV_ALL \ No newline at end of file + - - STAR_2015_2JET_MIDRAP_510GEV_SS_ALL \ No newline at end of file From 9347f457de030b53e1ca8d3066f34518bfb35ee5 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 14:02:44 +0200 Subject: [PATCH 50/98] Adding lumi shift to 2013 data --- .../star/jet_dijet_2013_510gev.py | 19 ++++++++++++++++++- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 18 ++++++++++++++++++ .../uncertainties_A.yaml | 16 ++++++++++++++++ .../uncertainties_B.yaml | 17 +++++++++++++++++ .../uncertainties_C.yaml | 16 ++++++++++++++++ .../uncertainties_D.yaml | 16 ++++++++++++++++ 6 files changed, 101 insertions(+), 1 deletion(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py index 569cc899dc..06ca98d32b 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py @@ -16,6 +16,7 @@ SQRTS = 510 ETA_ABS = 0.9 POL_UNC = 0.064 +LUMI_UNC = 0.00047 YEAR = 2013 TOPOPLOGY_LIST = ["1JET", "A", "B", "C", "D"] @@ -49,6 +50,7 @@ def read_1jet_data(): df["stat"] = all_data[r"stat +"] df["syst"] = all_data[r"syst +"] df["pol"] = POL_UNC * abs(df["ALL"]) + df["lumi"] = LUMI_UNC print("1JET data loaded. Npoint: ", len(df)) return df @@ -76,6 +78,7 @@ def read_2jet_data(topology): df["stat"] = all_data[r"stat +"] df["syst"] = all_data[r"syst +"] df["pol"] = POL_UNC * abs(df["ALL"]) + df["lumi"] = LUMI_UNC print(f"2JET {topology} data loaded. Npoint: ", len(df)) return df @@ -161,10 +164,18 @@ def write_1jet_data(df, art_sys): "treatment": "MULT", "type": f"STAR{YEAR}POL", }, + "lumi": { + "description": "luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}LUMI", + }, } # loop on data points for i, sys_i in enumerate(art_sys): - e = {"pol": float(df.loc[i, "pol"])} + e = { + "pol": float(df.loc[i, "pol"]), + "lumi": float(df.loc[i, "lumi"]) + } # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -223,12 +234,18 @@ def write_2jet_data(df, topology, art_sys): "treatment": "MULT", "type": f"STAR{YEAR}POL", }, + "lumi": { + "description": "luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}LUMI", + }, } # loop on data points for i, sys_i in enumerate(art_sys): e = { "stat": float(df.loc[i, "stat"]), "pol": float(df.loc[i, "pol"]), + "lumi": float(df.loc[i, "lumi"]), } # loop on art sys for j, val in enumerate(sys_i): diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml index b75f70c586..d53f02de56 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: beam polarization uncertainty treatment: MULT type: STAR2013POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2013LUMI sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD @@ -257,6 +261,7 @@ definitions: type: STAR2013JETunc62 bins: - pol: 0.00040064 + lumi: 0.00047 sys_0: -8.959677092850805e-10 sys_1: 9.832716726753248e-09 sys_2: 6.730954169673362e-08 @@ -321,6 +326,7 @@ bins: sys_61: 1.695949026719929e-08 sys_62: 4.068655178934001e-08 - pol: 0.00016512 + lumi: 0.00047 sys_0: -1.202440186311471e-09 sys_1: 1.2813446483400317e-08 sys_2: 8.81050970897512e-08 @@ -385,6 +391,7 @@ bins: sys_61: 1.5882781871113175e-07 sys_62: 1.476017840728621e-07 - pol: 0.00017728 + lumi: 0.00047 sys_0: -2.029626906402448e-09 sys_1: 1.7836760297927526e-08 sys_2: 1.0627274752256677e-07 @@ -449,6 +456,7 @@ bins: sys_61: 8.583540740030501e-07 sys_62: 1.5503622047436774e-07 - pol: 4.8e-05 + lumi: 0.00047 sys_0: -2.317611030883938e-09 sys_1: 2.0103077754186072e-08 sys_2: 1.221490288409029e-07 @@ -513,6 +521,7 @@ bins: sys_61: 1.7222827306715096e-06 sys_62: -9.247304481271197e-07 - pol: 5.44e-05 + lumi: 0.00047 sys_0: -5.794556391557737e-09 sys_1: 4.184211349903503e-08 sys_2: 2.6618567237308233e-07 @@ -577,6 +586,7 @@ bins: sys_61: 2.2522518080254573e-06 sys_62: -1.0715258476286533e-06 - pol: 0.00028416000000000004 + lumi: 0.00047 sys_0: -1.3031478055734842e-06 sys_1: 2.5765217725622465e-06 sys_2: 4.098773110280467e-06 @@ -641,6 +651,7 @@ bins: sys_61: 1.0653144764978103e-05 sys_62: -3.301748478993185e-06 - pol: 0.00019711999999999998 + lumi: 0.00047 sys_0: -1.3645531518127146e-06 sys_1: 4.007352188193593e-06 sys_2: 7.118280416455643e-06 @@ -705,6 +716,7 @@ bins: sys_61: 8.110592685806155e-06 sys_62: -2.9470442625980592e-06 - pol: 0.00036608 + lumi: 0.00047 sys_0: -4.410061141775246e-06 sys_1: 8.827712539715316e-06 sys_2: 1.5915934216203423e-05 @@ -769,6 +781,7 @@ bins: sys_61: 1.9118831698037573e-06 sys_62: -3.1450946824362763e-06 - pol: 0.00064512 + lumi: 0.00047 sys_0: -9.131724744467474e-06 sys_1: 1.863235365253899e-05 sys_2: 3.3956019925427964e-05 @@ -833,6 +846,7 @@ bins: sys_61: -2.652476147993337e-06 sys_62: -2.631173820600041e-06 - pol: 0.0006611200000000001 + lumi: 0.00047 sys_0: -2.435929877389478e-05 sys_1: 4.385340201952634e-05 sys_2: 8.054820474610805e-05 @@ -897,6 +911,7 @@ bins: sys_61: -3.855018491750307e-06 sys_62: -1.9427906611187093e-06 - pol: 0.0007993599999999999 + lumi: 0.00047 sys_0: -6.0544102812491e-05 sys_1: 0.00010598849026939544 sys_2: 0.00021379958305045062 @@ -961,6 +976,7 @@ bins: sys_61: -3.2070331988170936e-06 sys_62: -1.2278020423447078e-06 - pol: 0.0011673599999999999 + lumi: 0.00047 sys_0: -0.0001577103692828836 sys_1: 0.00029912242658556974 sys_2: 0.004808687956200867 @@ -1025,6 +1041,7 @@ bins: sys_61: -1.970881120092344e-06 sys_62: -5.924851514078511e-07 - pol: 0.0014112 + lumi: 0.00047 sys_0: -0.00045504371463879224 sys_1: 0.007914936126560801 sys_2: -0.00022897842682166285 @@ -1089,6 +1106,7 @@ bins: sys_61: -8.847799754759238e-07 sys_62: -1.3186838446226118e-07 - pol: 0.00289728 + lumi: 0.00047 sys_0: -0.014037407329102298 sys_1: -0.0002905887232621964 sys_2: -6.535182661833837e-05 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml index 56115a4a24..b04992730f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml @@ -7,6 +7,10 @@ definitions: description: beam polarization uncertainty treatment: MULT type: STAR2013POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2013LUMI sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -262,6 +266,7 @@ definitions: bins: - stat: 0.00619 pol: 0.00035072 + lumi: 0.00047 sys_0: -1.8442665253564098e-08 sys_1: 9.128062228545417e-08 sys_2: 3.0998812240715233e-07 @@ -327,6 +332,7 @@ bins: sys_62: 4.157211360391717e-05 - stat: 0.00289 pol: 7.04e-06 + lumi: 0.00047 sys_0: -7.838875974830611e-08 sys_1: 4.029804267681053e-07 sys_2: 1.4263812561994197e-06 @@ -392,6 +398,7 @@ bins: sys_62: -4.076207527766995e-05 - stat: 0.00248 pol: 0.0001056 + lumi: 0.00047 sys_0: -2.8468150405070355e-08 sys_1: 1.302892686669323e-07 sys_2: 4.2550586928508e-07 @@ -457,6 +464,7 @@ bins: sys_62: 4.121418069420012e-05 - stat: 0.00226 pol: 8.256e-05 + lumi: 0.00047 sys_0: -4.6544610935439495e-08 sys_1: 2.3007219919492261e-07 sys_2: 7.952844513686009e-07 @@ -522,6 +530,7 @@ bins: sys_62: 0.00021475672701815719 - stat: 0.00246 pol: 0.00015872 + lumi: 0.00047 sys_0: -4.534138982447269e-08 sys_1: 2.2504896724296193e-07 sys_2: 7.917709026102204e-07 @@ -587,6 +596,7 @@ bins: sys_62: 7.73366041438697e-05 - stat: 0.00311 pol: 0.00037184 + lumi: 0.00047 sys_0: -4.500893914289471e-08 sys_1: 2.1858653897192284e-07 sys_2: 7.79153722769766e-07 @@ -652,6 +662,7 @@ bins: sys_62: 3.0384184455649006e-05 - stat: 0.00349 pol: 0.00042624000000000004 + lumi: 0.00047 sys_0: -5.7977978168794394e-08 sys_1: 2.9729274345840024e-07 sys_2: 2.7849696168819077e-06 @@ -717,6 +728,7 @@ bins: sys_62: 1.6831769406156224e-05 - stat: 0.00472 pol: 0.0007296000000000001 + lumi: 0.00047 sys_0: -1.2307329310568736e-07 sys_1: 1.8453058533627218e-06 sys_2: 8.128992279649453e-06 @@ -782,6 +794,7 @@ bins: sys_62: 9.245856630486994e-06 - stat: 0.00659 pol: 0.0011686399999999999 + lumi: 0.00047 sys_0: -2.012664434190439e-06 sys_1: 9.343738640456632e-06 sys_2: 2.656361359743435e-05 @@ -847,6 +860,7 @@ bins: sys_62: 4.497841620233109e-06 - stat: 0.01045 pol: 0.00155584 + lumi: 0.00047 sys_0: -1.1399876370921493e-05 sys_1: 3.460208095882234e-05 sys_2: 8.128788330846539e-05 @@ -912,6 +926,7 @@ bins: sys_62: 1.8094252933826653e-06 - stat: 0.01633 pol: 0.00232832 + lumi: 0.00047 sys_0: -4.3391282027328335e-05 sys_1: 0.00010733055374682666 sys_2: 0.00017349825516788553 @@ -977,6 +992,7 @@ bins: sys_62: 1.6078432326039527e-06 - stat: 0.02919 pol: 0.0005049599999999999 + lumi: 0.00047 sys_0: -0.0001582145343682221 sys_1: 0.00023785644592245637 sys_2: 0.00018923810995146129 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml index dfa684d8e9..57f0656990 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml @@ -7,6 +7,10 @@ definitions: description: beam polarization uncertainty treatment: MULT type: STAR2013POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2013LUMI sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -262,6 +266,7 @@ definitions: bins: - stat: 0.00533 pol: 0.00024384 + lumi: 0.00047 sys_0: -3.468382363342568e-08 sys_1: 1.8121652909760799e-07 sys_2: 5.838496850963883e-07 @@ -327,6 +332,7 @@ bins: sys_62: -2.2672083449213552e-05 - stat: 0.00213 pol: 0.00019136 + lumi: 0.00047 sys_0: -9.090601444875332e-08 sys_1: 4.616157558012612e-07 sys_2: 1.473310204477202e-06 @@ -392,6 +398,7 @@ bins: sys_62: 8.398314077938356e-05 - stat: 0.00173 pol: 7.424000000000001e-05 + lumi: 0.00047 sys_0: -8.530127204466283e-08 sys_1: 4.29673266336131e-07 sys_2: 1.3304320577341956e-06 @@ -457,6 +464,7 @@ bins: sys_62: 5.762533776139228e-05 - stat: 0.00152 pol: 0.00021504 + lumi: 0.00047 sys_0: -1.1152205784023518e-07 sys_1: 5.632982151226721e-07 sys_2: 1.7794589363130775e-06 @@ -522,6 +530,7 @@ bins: sys_62: -3.796889291143406e-05 - stat: 0.00161 pol: 3.84e-05 + lumi: 0.00047 sys_0: -1.1169536414096341e-07 sys_1: 5.629576028352181e-07 sys_2: 1.7886807965226788e-06 @@ -587,6 +596,7 @@ bins: sys_62: -5.1363235548141263e-05 - stat: 0.00202 pol: 9.855999999999999e-05 + lumi: 0.00047 sys_0: -9.692271653941357e-08 sys_1: 4.942929134532881e-07 sys_2: 1.6295369068757726e-06 @@ -652,6 +662,7 @@ bins: sys_62: -0.0001278038928716919 - stat: 0.00224 pol: 0.0003968 + lumi: 0.00047 sys_0: -1.1313231922673203e-07 sys_1: 5.8776988624716e-07 sys_2: 3.6125771096691164e-06 @@ -717,6 +728,7 @@ bins: sys_62: 4.6771652136488883e-05 - stat: 0.00297 pol: 0.0005536 + lumi: 0.00047 sys_0: -1.765422887477046e-07 sys_1: 2.0551743805244367e-06 sys_2: 9.859150544691759e-06 @@ -782,6 +794,7 @@ bins: sys_62: 1.4871429582216254e-05 - stat: 0.00406 pol: 0.0005158399999999999 + lumi: 0.00047 sys_0: -1.9304449086169784e-06 sys_1: 1.0378470446209637e-05 sys_2: 3.1029803365074237e-05 @@ -847,6 +860,7 @@ bins: sys_62: 5.130470650393264e-06 - stat: 0.00629 pol: 0.00155392 + lumi: 0.00047 sys_0: -1.2536445300773651e-05 sys_1: 3.848548585424122e-05 sys_2: 8.518413112749595e-05 @@ -912,6 +926,7 @@ bins: sys_62: 1.4754204121214294e-06 - stat: 0.00953 pol: 0.0006803200000000001 + lumi: 0.00047 sys_0: -4.61630218202905e-05 sys_1: 0.00010734443625050014 sys_2: 0.0001717408755548584 @@ -977,6 +992,7 @@ bins: sys_62: 1.6605655103780758e-06 - stat: 0.01613 pol: 0.00079872 + lumi: 0.00047 sys_0: -0.0001384089360340667 sys_1: 0.0002089501775235047 sys_2: 0.00017467888563264523 @@ -1042,6 +1058,7 @@ bins: sys_62: -1.4181091930554394e-07 - stat: 0.02978 pol: 0.00322368 + lumi: 0.00047 sys_0: -0.0005375590456296148 sys_1: 0.0004247513096179986 sys_2: 0.00015231468989848919 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_C.yaml index 0d9d0e60ec..d1ad34dfca 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_C.yaml @@ -7,6 +7,10 @@ definitions: description: beam polarization uncertainty treatment: MULT type: STAR2013POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2013LUMI sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -262,6 +266,7 @@ definitions: bins: - stat: 0.00785 pol: 0.0007392 + lumi: 0.00047 sys_0: -4.100959127774964e-07 sys_1: 1.222332698478793e-06 sys_2: 2.05687127807516e-06 @@ -327,6 +332,7 @@ bins: sys_62: 7.299765596649971e-06 - stat: 0.00367 pol: 4.8e-05 + lumi: 0.00047 sys_0: -1.8501931900701732e-06 sys_1: 5.816479741016232e-06 sys_2: 1.117343944426216e-05 @@ -392,6 +398,7 @@ bins: sys_62: -5.3538188824715525e-06 - stat: 0.00317 pol: 0.00018752 + lumi: 0.00047 sys_0: -7.06985540704637e-07 sys_1: 2.047809323259492e-06 sys_2: 3.206126094091834e-06 @@ -457,6 +464,7 @@ bins: sys_62: 0.00022180010222988035 - stat: 0.00291 pol: 1.1520000000000002e-05 + lumi: 0.00047 sys_0: -1.1394923825192585e-06 sys_1: 3.3584175291326274e-06 sys_2: 5.517441427429289e-06 @@ -522,6 +530,7 @@ bins: sys_62: 2.8882203891701888e-05 - stat: 0.00317 pol: 0.00041920000000000005 + lumi: 0.00047 sys_0: -1.0055431921622787e-06 sys_1: 2.9559665736729617e-06 sys_2: 4.835313364366917e-06 @@ -587,6 +596,7 @@ bins: sys_62: 2.2732328432324687e-05 - stat: 0.004 pol: 0.00062016 + lumi: 0.00047 sys_0: -7.982530653253943e-07 sys_1: 2.3526122878835294e-06 sys_2: 3.903999488363647e-06 @@ -652,6 +662,7 @@ bins: sys_62: 1.3946435744793562e-05 - stat: 0.00448 pol: 0.00052288 + lumi: 0.00047 sys_0: -7.629582335717668e-07 sys_1: 2.2930528290573246e-06 sys_2: 5.4168186296954345e-06 @@ -717,6 +728,7 @@ bins: sys_62: 1.1343586365878917e-05 - stat: 0.00603 pol: 0.00084288 + lumi: 0.00047 sys_0: -7.196379769948711e-07 sys_1: 3.841066107188445e-06 sys_2: 1.055275654751577e-05 @@ -782,6 +794,7 @@ bins: sys_62: 9.664290940358064e-06 - stat: 0.00833 pol: 0.00119424 + lumi: 0.00047 sys_0: -3.056381573146764e-06 sys_1: 1.2227822520879637e-05 sys_2: 3.067532258845744e-05 @@ -847,6 +860,7 @@ bins: sys_62: 8.032471762559063e-06 - stat: 0.01292 pol: 0.00109568 + lumi: 0.00047 sys_0: -1.3933736532744972e-05 sys_1: 4.263267579515523e-05 sys_2: 9.349430373992513e-05 @@ -912,6 +926,7 @@ bins: sys_62: 6.7171731111360795e-06 - stat: 0.01964 pol: 0.00086848 + lumi: 0.00047 sys_0: -5.2224816543540025e-05 sys_1: 0.00011437109584364653 sys_2: 0.00017185485398267633 @@ -977,6 +992,7 @@ bins: sys_62: 5.229117363656164e-06 - stat: 0.03322 pol: 0.000368 + lumi: 0.00047 sys_0: -0.0001821538669113795 sys_1: 0.0002428086358083653 sys_2: 0.00019902420286007486 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml index 4aad0bb3f6..a56376bc19 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml @@ -7,6 +7,10 @@ definitions: description: beam polarization uncertainty treatment: MULT type: STAR2013POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2013LUMI sys_0: description: 0 artificial correlated systematics uncertainty treatment: ADD @@ -262,6 +266,7 @@ definitions: bins: - stat: 0.00466 pol: 0.00067072 + lumi: 0.00047 sys_0: -8.246189673601546e-07 sys_1: 2.7810751638783183e-06 sys_2: 5.956720831913832e-06 @@ -327,6 +332,7 @@ bins: sys_62: 1.0567798499199847e-05 - stat: 0.00302 pol: 0.00018944 + lumi: 0.00047 sys_0: -4.997327691153951e-07 sys_1: 1.6284178687517042e-06 sys_2: 3.2440683053073596e-06 @@ -392,6 +398,7 @@ bins: sys_62: -0.00035837619026315103 - stat: 0.00235 pol: 0.00019648 + lumi: 0.00047 sys_0: -1.2322595716463065e-06 sys_1: 4.141704840515627e-06 sys_2: 8.792691224674361e-06 @@ -457,6 +464,7 @@ bins: sys_62: -1.06050585369882e-05 - stat: 0.00229 pol: 4.6080000000000006e-05 + lumi: 0.00047 sys_0: -1.0343763729771366e-06 sys_1: 3.447940072340132e-06 sys_2: 7.205331797379565e-06 @@ -522,6 +530,7 @@ bins: sys_62: -1.4121347509033479e-05 - stat: 0.00278 pol: 0.00010816000000000001 + lumi: 0.00047 sys_0: -7.546643274499027e-07 sys_1: 2.5077908840206717e-06 sys_2: 5.232506125093797e-06 @@ -587,6 +596,7 @@ bins: sys_62: -1.3227487664635489e-05 - stat: 0.003 pol: 0.00032063999999999997 + lumi: 0.00047 sys_0: -6.659628598028416e-07 sys_1: 2.23116447955261e-06 sys_2: 5.5323214912652514e-06 @@ -652,6 +662,7 @@ bins: sys_62: -1.2085082539939634e-05 - stat: 0.00382 pol: 0.00028352 + lumi: 0.00047 sys_0: -5.326099380504057e-07 sys_1: 1.8430676926367074e-06 sys_2: 7.2716645021494255e-06 @@ -717,6 +728,7 @@ bins: sys_62: -7.81171189563106e-06 - stat: 0.005 pol: 0.00056768 + lumi: 0.00047 sys_0: -5.300674818349766e-07 sys_1: 5.062211933315961e-06 sys_2: 1.4574894428516086e-05 @@ -782,6 +794,7 @@ bins: sys_62: -3.899561231030796e-06 - stat: 0.00747 pol: 0.0006303999999999999 + lumi: 0.00047 sys_0: -3.5594850793009027e-06 sys_1: 1.4357113530376482e-05 sys_2: 3.7395184608793296e-05 @@ -847,6 +860,7 @@ bins: sys_62: -8.320501431985912e-07 - stat: 0.01095 pol: 0.00022464000000000002 + lumi: 0.00047 sys_0: -1.5228455235119592e-05 sys_1: 4.3147530546065046e-05 sys_2: 8.529090376974244e-05 @@ -912,6 +926,7 @@ bins: sys_62: 2.5193919058972847e-07 - stat: 0.01797 pol: 0.00201024 + lumi: 0.00047 sys_0: -5.221725858549406e-05 sys_1: 0.00011109036301678784 sys_2: 0.0001374635404968144 @@ -977,6 +992,7 @@ bins: sys_62: 1.7969917942623896e-07 - stat: 0.03187 pol: 0.00071296 + lumi: 0.00047 sys_0: -0.00022560839549655114 sys_1: 0.00026503748033196044 sys_2: 0.00017282686211184703 From fe6afde0707b75a4c85c65ea961cee5bcdc72ef9 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 14:30:26 +0200 Subject: [PATCH 51/98] collapse 2009 dijets --- .../star/jet_dijet_2009_200gev.py | 28 +++-- .../STAR_2009_1JET_200GEV/metadata.yaml | 2 + .../data_A.yaml} | 0 .../data_B.yaml} | 0 .../data_C.yaml} | 0 .../kinematics_A.yaml} | 0 .../kinematics_B.yaml} | 0 .../kinematics_C.yaml} | 0 .../STAR_2009_2JET_200GEV/metadata.yaml | 117 ++++++++++++++++++ .../rawdata/Table_A.yaml} | 0 .../rawdata/Table_B.yaml} | 0 .../rawdata/Table_C.yaml} | 0 .../uncertainties_A.yaml} | 0 .../uncertainties_B.yaml} | 0 .../uncertainties_C.yaml} | 0 .../STAR_2009_2JET_A_200GEV/metadata.yaml | 49 -------- .../STAR_2009_2JET_B_200GEV/metadata.yaml | 49 -------- .../STAR_2009_2JET_C_200GEV/metadata.yaml | 49 -------- .../data_OS.yaml} | 0 .../data_SS.yaml} | 0 .../kinematics_OS.yaml} | 0 .../kinematics_SS.yaml} | 0 .../metadata.yaml | 84 +++++++++++++ .../rawdata/Table_OS.yaml} | 0 .../rawdata/Table_SS.yaml} | 0 .../uncertainties_OS.yaml} | 0 .../uncertainties_SS.yaml} | 0 .../STAR_2009_2JET_OS_200GEV/metadata.yaml | 49 -------- .../STAR_2009_2JET_SS_200GEV/metadata.yaml | 49 -------- 29 files changed, 224 insertions(+), 252 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_A_200GEV/data.yaml => STAR_2009_2JET_200GEV/data_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_B_200GEV/data.yaml => STAR_2009_2JET_200GEV/data_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_C_200GEV/data.yaml => STAR_2009_2JET_200GEV/data_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_A_200GEV/kinematics.yaml => STAR_2009_2JET_200GEV/kinematics_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_B_200GEV/kinematics.yaml => STAR_2009_2JET_200GEV/kinematics_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_C_200GEV/kinematics.yaml => STAR_2009_2JET_200GEV/kinematics_C.yaml} (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_A_200GEV/rawdata/Table.yaml => STAR_2009_2JET_200GEV/rawdata/Table_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_B_200GEV/rawdata/Table.yaml => STAR_2009_2JET_200GEV/rawdata/Table_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_C_200GEV/rawdata/Table.yaml => STAR_2009_2JET_200GEV/rawdata/Table_C.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_A_200GEV/uncertainties.yaml => STAR_2009_2JET_200GEV/uncertainties_A.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_B_200GEV/uncertainties.yaml => STAR_2009_2JET_200GEV/uncertainties_B.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_C_200GEV/uncertainties.yaml => STAR_2009_2JET_200GEV/uncertainties_C.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_OS_200GEV/data.yaml => STAR_2009_2JET_MIDRAP_200GEV/data_OS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_SS_200GEV/data.yaml => STAR_2009_2JET_MIDRAP_200GEV/data_SS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_OS_200GEV/kinematics.yaml => STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_SS_200GEV/kinematics.yaml => STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml} (100%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_OS_200GEV/rawdata/Table.yaml => STAR_2009_2JET_MIDRAP_200GEV/rawdata/Table_OS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_SS_200GEV/rawdata/Table.yaml => STAR_2009_2JET_MIDRAP_200GEV/rawdata/Table_SS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_OS_200GEV/uncertainties.yaml => STAR_2009_2JET_MIDRAP_200GEV/uncertainties_OS.yaml} (100%) rename nnpdf_data/nnpdf_data/new_commondata/{STAR_2009_2JET_SS_200GEV/uncertainties.yaml => STAR_2009_2JET_MIDRAP_200GEV/uncertainties_SS.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index 83435af0a2..8e0758a020 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -88,9 +88,15 @@ def read_1jet_data(): def read_2jet_data(topology): - fname = ( - f"../../new_commondata/STAR_{YEAR}_2JET_{topology}_200GEV/rawdata/Table.yaml" - ) + + if "S" in topology: + fname = ( + f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/rawdata/Table_{topology}.yaml" + ) + else: + fname = ( + f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/rawdata/Table_{topology}.yaml" + ) df = pd.DataFrame() with open(fname, "r", encoding="utf-8") as file: data = yaml.safe_load(file) @@ -201,10 +207,18 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_{topology}_200GEV/" + STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/" + if "S" in topo: + STORE_PATH = ( + f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/" + ) + else: + STORE_PATH = ( + f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/" + ) # Write central data data_central_yaml = {"data_central": list(df["ALL"])} - with open(STORE_PATH + "data.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH + f"data_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file) # Write kin file @@ -226,7 +240,7 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH + "kinematics.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH + f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -264,7 +278,7 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH + "uncertainties.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH + f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml index f5197d9ddd..af8244f0c2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml @@ -4,6 +4,8 @@ nnpdf_metadata: experiment: "STAR" nnpdf31_process: "JETS" +arXiv: + url: https://arxiv.org/abs/1405.5134 iNSPIRE: url: "https://inspirehep.net/literature/1297229" hepdata: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/data_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/data_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/data_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/data_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/data_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/data_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml new file mode 100644 index 0000000000..74a50745a1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml @@ -0,0 +1,117 @@ +setname: "STAR_2009_2JET_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +arXiv: + url: https://arxiv.org/abs/1805.09742 +iNSPIRE: + url: "https://inspirehep.net/literature/1674714" +hepdata: + url: "https://www.hepdata.net/record/ins1674714" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL as function of $M_{inv}$, topology A", + label: "$A_{LL}$", + units: "", + } + observable_name: A-ALL + process_type: DIJET_POL + ndata: 5 + tables: [9] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics_A.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_A.yaml + data_uncertainties: + - uncertainties_A.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology A" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_200GEV_A_ALL + - observable: + { + description: "ALL as function of $M_{inv}$, topology B", + label: "$A_{LL}$", + units: "", + } + observable_name: B-ALL + process_type: DIJET_POL + ndata: 7 + tables: [9] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics_B.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_B.yaml + data_uncertainties: + - uncertainties_B.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology B" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_200GEV_B_ALL + - observable: + { + description: "ALL as function of $M_{inv}$, topology C", + label: "$A_{LL}$", + units: "", + } + observable_name: C-ALL + process_type: DIJET_POL + ndata: 7 + tables: [9] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics_C.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_C.yaml + data_uncertainties: + - uncertainties_C.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology C" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_200GEV_C_ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/rawdata/Table_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/rawdata/Table.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/rawdata/Table_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/rawdata/Table_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/rawdata/Table.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/rawdata/Table_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/rawdata/Table_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/rawdata/Table.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/rawdata/Table_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_A.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_A.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_B.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_B.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_C.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml deleted file mode 100644 index 469110bc80..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_A_200GEV/metadata.yaml +++ /dev/null @@ -1,49 +0,0 @@ -setname: "STAR_2009_2JET_A_200GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1674714" -hepdata: - url: "https://www.hepdata.net/record/ins1674714" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: - { - description: "ALL as function of $M_{inv}$, topology A", - label: "$A_{LL}$", - units: "", - } - observable_name: ALL - process_type: DIJET_POL - ndata: 5 - tables: [9] - kinematics: - variables: - m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology A" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2009_2JET_A_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml deleted file mode 100644 index 97bdff2589..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_B_200GEV/metadata.yaml +++ /dev/null @@ -1,49 +0,0 @@ -setname: "STAR_2009_2JET_B_200GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1674714" -hepdata: - url: "https://www.hepdata.net/record/ins1674714" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: - { - description: "ALL as function of $M_{inv}$, topology B", - label: "$A_{LL}$", - units: "", - } - observable_name: ALL - process_type: DIJET_POL - ndata: 7 - tables: [9] - kinematics: - variables: - m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology B" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2009_2JET_B_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml deleted file mode 100644 index 86feaca0a6..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_C_200GEV/metadata.yaml +++ /dev/null @@ -1,49 +0,0 @@ -setname: "STAR_2009_2JET_C_200GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1674714" -hepdata: - url: "https://www.hepdata.net/record/ins1674714" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: - { - description: "ALL as function of $M_{inv}$, topology C", - label: "$A_{LL}$", - units: "", - } - observable_name: ALL - process_type: DIJET_POL - ndata: 7 - tables: [9] - kinematics: - variables: - m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, topology C" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2009_2JET_C_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/data_OS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/data_OS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/data_SS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/data_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml new file mode 100644 index 0000000000..2393f73207 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -0,0 +1,84 @@ +setname: "STAR_2009_2JET_MIDRAP_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "DIJET" + +arXiv: + url: https://arxiv.org/pdf/1610.06616 +iNSPIRE: + url: "https://inspirehep.net/literature/1493842" +hepdata: + url: "https://www.hepdata.net/record/ins1493842" + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: + { + description: "ALL as function of $M_{inv}$, OS", + label: "$A_{LL}$", + units: "", + } + observable_name: OS-ALL + process_type: DIJET_POL + ndata: 7 + tables: [9] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics_OS.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_OS.yaml + data_uncertainties: + - uncertainties_OS.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, OS" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_MIDRAP_200GEV_OS_ALL + - observable: + { + description: "ALL as function of $M_{inv}$, SS", + label: "$A_{LL}$", + units: "", + } + observable_name: SS-ALL + process_type: DIJET_POL + ndata: 7 + tables: [7] + kinematics: + variables: + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } + file: kinematics_SS.yaml + kinematic_coverage: [m_jj, sqrts] + data_central: data_SS.yaml + data_uncertainties: + - uncertainties_SS.yaml + plotting: + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, SS" + kinematics_override: identity + plot_x: m_jj + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_2JET_MIDRAP_200GEV_SS_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/rawdata/Table_OS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/rawdata/Table.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/rawdata/Table_OS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/rawdata/Table.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/rawdata/Table_SS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/rawdata/Table.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/rawdata/Table_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_OS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_OS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_SS.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml deleted file mode 100644 index 82bca00604..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_OS_200GEV/metadata.yaml +++ /dev/null @@ -1,49 +0,0 @@ -setname: "STAR_2009_2JET_OS_200GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1493842" -hepdata: - url: "https://www.hepdata.net/record/ins1493842" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: - { - description: "ALL as function of $M_{inv}$, OS", - label: "$A_{LL}$", - units: "", - } - observable_name: ALL - process_type: DIJET_POL - ndata: 7 - tables: [9] - kinematics: - variables: - m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, OS" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2009_2JET_OS_200GEV_ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml deleted file mode 100644 index 661703181b..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_SS_200GEV/metadata.yaml +++ /dev/null @@ -1,49 +0,0 @@ -setname: "STAR_2009_2JET_SS_200GEV" - -nnpdf_metadata: - experiment: "STAR" - nnpdf31_process: "DIJET" - -iNSPIRE: - url: "https://inspirehep.net/literature/1493842" -hepdata: - url: "https://www.hepdata.net/record/ins1493842" - version: 1 - -version: 1 -version_comment: "Initial implementation" - -implemented_observables: - - observable: - { - description: "ALL as function of $M_{inv}$, SS", - label: "$A_{LL}$", - units: "", - } - observable_name: ALL - process_type: DIJET_POL - ndata: 7 - tables: [7] - kinematics: - variables: - m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } - file: kinematics.yaml - kinematic_coverage: [m_jj, sqrts] - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, SS" - kinematics_override: identity - plot_x: m_jj - x_scale: log - y_label: "$A_{LL}$" - theory: - FK_tables: - - - STAR_2009_2JET_SS_200GEV_ALL From 023a95faa120924a4d0e7783ddcdc250a6093325 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 14:43:06 +0200 Subject: [PATCH 52/98] fix lumi unc and stat in 2009 dijets --- .../star/jet_dijet_2009_200gev.py | 74 +- .../STAR_2009_1JET_200GEV/uncertainties.yaml | 2446 +++++++++-------- .../uncertainties_A.yaml | 688 ++--- .../uncertainties_B.yaml | 916 +++--- .../uncertainties_C.yaml | 916 +++--- .../uncertainties_OS.yaml | 916 +++--- .../uncertainties_SS.yaml | 916 +++--- 7 files changed, 3451 insertions(+), 3421 deletions(-) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py index 8e0758a020..cfdc7bf334 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py @@ -58,7 +58,7 @@ def read_1jet_data(): df4["sys_max"] = dfi["sys +"] df4["abs_eta_min"] = 0.5 - df4["abs_eta_max"] = 1.0 + df4["abs_eta_max"] = 1.0 elif "5" in fname: dfc_col = pd.read_csv(fname) @@ -82,21 +82,17 @@ def read_1jet_data(): df["stat"] = df["stat_max"] df["sys"] = df["sys_max"] df["pol"] = POL_UNC * abs(df["ALL"]) + df["lumi"] = LUMI_UNC df["sqrts"] = 200 df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 return df, dfc def read_2jet_data(topology): - if "S" in topology: - fname = ( - f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/rawdata/Table_{topology}.yaml" - ) + fname = f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/rawdata/Table_{topology}.yaml" else: - fname = ( - f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/rawdata/Table_{topology}.yaml" - ) + fname = f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/rawdata/Table_{topology}.yaml" df = pd.DataFrame() with open(fname, "r", encoding="utf-8") as file: data = yaml.safe_load(file) @@ -143,8 +139,8 @@ def read_2jet_data(topology): ) df["pol"] = POL_UNC * abs(df["ALL"]) + df["lumi"] = LUMI_UNC df["sqrts"] = 200 - return df @@ -180,11 +176,16 @@ def write_1jet_data(df, art_sys): "description": "beam polarization uncertainty", "treatment": "MULT", "type": f"STAR{YEAR}POL", - } + }, + "lumi": { + "description": "luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}LUMI", + }, } # loop on data points for i, sys_i in enumerate(art_sys): - e = {"pol": float(df.loc[i, "pol"])} + e = {"pol": float(df.loc[i, "pol"]), "lumi": float(df.loc[i, "lumi"])} # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -208,14 +209,10 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/" - if "S" in topo: - STORE_PATH = ( - f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/" - ) + if "S" in topology: + STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/" else: - STORE_PATH = ( - f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/" - ) + STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} with open(STORE_PATH + f"data_{topology}.yaml", "w", encoding="utf-8") as file: @@ -240,26 +237,31 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH + f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH + f"kinematics_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(kinematics_yaml, file) # Write unc file error = [] error_definition = { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - }, "pol": { "description": "beam polarization uncertainty", "treatment": "MULT", "type": f"STAR{YEAR}POL", }, + "lumi": { + "description": "luminosity uncertainty", + "treatment": "ADD", + "type": f"STAR{YEAR}LUMI", + }, } # loop on data points for i, sys_i in enumerate(art_sys): - e = {"stat": float(df.loc[i, "stat"]), "pol": float(df.loc[i, "pol"])} + e = { + "pol": float(df.loc[i, "pol"]), + "lumi": float(df.loc[i, "lumi"]), + } # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -269,7 +271,7 @@ def write_2jet_data(df, topology, art_sys): error_definition.update( { f"sys_{j}": { - "description": f"{j} artificial correlated systematics uncertainty", + "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", "type": f"STAR{YEAR}JETunc{j}", } @@ -278,7 +280,9 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH + f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH + f"uncertainties_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) @@ -295,14 +299,14 @@ def write_2jet_data(df, topology, art_sys): f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/correlation.csv", index_col=0, ) - # from the paper we understand that stat dijet is not correlated - # I-I (stat + sys) | I-D (stat + sys) - # D-I (stat + sys) | D-D (sys) - correlated_unc = np.sqrt( - dfs["I"]["sys"] ** 2 + dfs["I"]["stat"] ** 2 - ).values.tolist() - for a in TOPOPLOGY_LIST[1:]: - correlated_unc.extend(dfs[a]["sys"].values) + # from the supplement material: + # https://journals.aps.org/prd/supplemental/10.1103/PhysRevD.98.032011/Supplementalmaterial.pdf + # we understand that stat jet and dijet are correlated + correlated_unc = [] + for a in TOPOPLOGY_LIST: + correlated_unc.extend( + np.sqrt(dfs[a]["sys"] ** 2 + dfs[a]["stat"] ** 2).values.tolist() + ) ndata_points = np.sum((*ndata_dict.values(),)) # decompose uncertainties art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml index 3011139c8b..91ce9eae20 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml @@ -3,6 +3,10 @@ definitions: description: beam polarization uncertainty treatment: MULT type: STAR2009POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2009LUMI sys_0: description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD @@ -225,1234 +229,1256 @@ definitions: type: STAR2009JETunc54 bins: - pol: 0.00013000000000000002 - sys_0: -1.6815813095975663e-06 - sys_1: 3.135895236785411e-06 - sys_2: 3.0444062961120985e-06 - sys_3: 2.67041059814949e-06 - sys_4: -1.6254026811200712e-06 - sys_5: 4.518820864785692e-06 - sys_6: 3.4796028046599582e-06 - sys_7: -6.770314862767248e-07 - sys_8: -7.598472063589526e-07 - sys_9: -5.965911597211238e-07 - sys_10: 7.87606174724339e-06 - sys_11: -1.8697433978741537e-06 - sys_12: -8.558025850948974e-06 - sys_13: -5.488223477960642e-06 - sys_14: 7.659506917173365e-06 - sys_15: -1.5072213137030027e-06 - sys_16: 2.896566343178069e-06 - sys_17: 6.088365414884578e-06 - sys_18: -1.178950652163968e-05 - sys_19: 1.4150746356270292e-05 - sys_20: -1.8718606896711806e-05 - sys_21: -1.2531001123041228e-05 - sys_22: 2.299601733348714e-06 - sys_23: -3.4331170078360284e-05 - 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0.008003515837841282 + sys_5: -3.813740102301659e-05 + sys_6: 0.0016701056177554957 + sys_7: -0.00040765834137889074 + sys_8: -1.7737129262864104e-06 + sys_9: 2.0394080809534508e-05 + sys_10: 6.787560104914701e-06 + sys_11: 0.0001641059785509825 + sys_12: 4.708863366410807e-05 + sys_13: 6.224118370277068e-05 + sys_14: 3.08313575523923e-05 + sys_15: 1.8950480174166717e-06 + sys_16: -6.133377871660353e-08 + sys_17: 7.329579428766248e-06 + sys_18: -2.5443810548522317e-05 + sys_19: 9.118589876708405e-06 + sys_20: 4.2020390144850865e-06 + sys_21: 1.359261726746838e-06 + sys_22: 6.758100137681983e-07 + sys_23: -4.793114976627494e-06 + sys_24: -2.54766859105655e-06 + sys_25: -1.5271941226344646e-06 + sys_26: 1.0671919342521099e-08 + sys_27: -7.685967437978598e-06 + sys_28: 9.222131903998067e-06 + sys_29: 2.0422148006293946e-05 + sys_30: -1.3027245771655229e-05 + sys_31: -2.598688762849034e-06 + sys_32: 3.5439631001725985e-06 + sys_33: 2.1177186337386202e-05 + sys_34: -6.166277657691816e-06 + sys_35: 1.0765348093199076e-06 + sys_36: 1.3504894489862046e-06 + sys_37: 1.286873073837209e-07 + sys_38: 4.939571900975254e-07 + sys_39: 1.3572335039632471e-06 + sys_40: -4.508836659606546e-08 + sys_41: 1.4209188941054532e-07 + sys_42: 9.782771840926777e-08 + sys_43: 1.297144033846644e-07 + sys_44: 1.551932706389958e-07 + sys_45: -4.5351409065237435e-07 + sys_46: 2.3119338958952692e-07 + sys_47: 3.2643631158624316e-07 + sys_48: -1.0783881035789849e-07 + sys_49: 1.1462039465248088e-07 + sys_50: 2.5871992270863685e-08 + sys_51: 2.1207512424022603e-07 + sys_52: 1.7347859435983505e-07 + sys_53: -1.3260584191249427e-07 + sys_54: 2.1561410876753635e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_A.yaml index 3014e4ff94..b06ec55b25 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_A.yaml @@ -1,515 +1,515 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT type: STAR2009POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2009LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc54 bins: -- stat: 0.007 - pol: 0.0001235 - sys_0: -2.9341441873981826e-09 - sys_1: 5.6627698149798896e-09 - sys_2: 3.947516340013661e-08 - sys_3: 3.474259906358662e-08 - sys_4: -4.1987083112102747e-07 - sys_5: 4.6980584967290275e-07 - sys_6: 1.6895587313557647e-05 - sys_7: 2.2729048660248698e-05 - sys_8: 6.306184493593761e-06 - sys_9: 1.2710948031307183e-05 - sys_10: -2.57899638435861e-06 - sys_11: -2.170842429971376e-05 - sys_12: 5.276451607974814e-06 - sys_13: 1.9633555980511846e-05 - sys_14: 8.248512495993356e-06 - sys_15: -6.10832079518566e-07 - sys_16: 6.738396792361433e-07 - sys_17: -1.1506201628609424e-06 - sys_18: -2.752584957306258e-05 - sys_19: -3.2068457330891736e-05 - sys_20: -2.191822723485393e-05 - sys_21: -3.961252810440841e-05 - sys_22: 2.993957309004265e-06 - sys_23: -0.00014620739269360464 - sys_24: 0.0018703911141647383 - sys_25: 0.0002804395272254612 - sys_26: 0.000590495383676678 - sys_27: 3.683796655049163e-07 - sys_28: 2.3643381983081909e-07 - sys_29: -6.260419510115389e-07 - sys_30: 3.92220302207209e-07 - sys_31: -6.980061994118511e-07 - sys_32: -1.9276759791270645e-07 - sys_33: -1.4767912281297904e-06 - sys_34: -1.4303979803965499e-06 - sys_35: 5.432689448439198e-05 - sys_36: -0.0001527159727080056 - sys_37: 2.96992805324897e-06 - sys_38: 2.869195099968407e-06 - sys_39: 8.290721744552978e-06 - sys_40: -2.905286493609521e-07 - sys_41: -1.9047781516055614e-07 - sys_42: -0.00010916211043763547 - sys_43: -7.52430826795878e-05 - sys_44: 1.922501705386345e-05 - sys_45: 1.2009576127941234e-05 - sys_46: 1.8296228631547555e-05 - sys_47: -1.0545480744849093e-05 - sys_48: 6.924840530438227e-06 - sys_49: -6.415829585145627e-06 - sys_50: -3.39030655499407e-05 - sys_51: 2.607895989261243e-05 - sys_52: -1.0756716695096613e-05 - sys_53: -1.3383755092384615e-05 - sys_54: -1.8477958927326992e-06 -- stat: 0.007 - pol: 0.0004485 - sys_0: -5.898643235004763e-09 - sys_1: 1.1973393935558007e-08 - sys_2: 7.779654506237548e-08 - sys_3: 7.416871876183287e-08 - sys_4: -7.985574948954471e-07 - sys_5: 9.350155690483878e-07 - sys_6: 3.1855141517542e-05 - sys_7: 4.3910811305523595e-05 - sys_8: 9.864730425257653e-06 - sys_9: 2.7112519417977034e-05 - sys_10: -4.224954247158868e-06 - sys_11: -4.474742097944539e-05 - sys_12: 6.98717747124241e-06 - sys_13: 4.262870493519771e-05 - sys_14: 1.9538926909869434e-05 - sys_15: -1.7506689751754383e-06 - sys_16: 3.850469490877143e-06 - sys_17: 2.513419449449712e-05 - sys_18: -0.00011999000608407366 - sys_19: -0.0001317462702124781 - sys_20: -0.0008051443009821056 - sys_21: -0.002237237451738831 - sys_22: -9.350734904345509e-06 - sys_23: 0.00014680858912354921 - sys_24: -9.36143726308781e-05 - sys_25: -5.654955275033271e-06 - sys_26: 0.00013631967248046623 - sys_27: 9.467749479898878e-07 - sys_28: 7.921583079714555e-07 - sys_29: -1.1110591131740783e-06 - sys_30: 1.2371872104216964e-06 - sys_31: -3.0239114691411025e-07 - sys_32: -1.373878251139743e-06 - sys_33: -1.2858544208020643e-06 - sys_34: -4.897360598797665e-07 - sys_35: 5.259043975081113e-06 - sys_36: -5.1873893082470386e-05 - sys_37: 2.918387010924369e-06 - sys_38: 3.5704731996250466e-06 - sys_39: 9.867568097502067e-06 - sys_40: 2.5135937324472164e-08 - sys_41: -5.675751880516184e-07 - sys_42: -8.457840841293302e-05 - sys_43: -4.879840148646681e-05 - sys_44: 1.7480122125644174e-05 - sys_45: -2.7370554644651988e-05 - sys_46: 7.146573644995449e-07 - sys_47: -2.2824695088527443e-05 - sys_48: -8.770124010879494e-06 - sys_49: -9.698356405592685e-07 - sys_50: -4.0495428931683924e-05 - sys_51: 2.971385717258693e-05 - sys_52: -1.0565804858799547e-05 - sys_53: -1.9343984302626992e-05 - sys_54: 3.515421208084455e-07 -- stat: 0.01 - pol: 0.001378 - sys_0: -6.415581388916738e-09 - sys_1: 1.4096428970422604e-08 - sys_2: 7.746596134557551e-08 - sys_3: 9.330344876517887e-08 - sys_4: -7.235587446499357e-07 - sys_5: 1.0158306104352345e-06 - sys_6: 2.7904732797661333e-05 - sys_7: 3.2540996472369066e-05 - sys_8: 6.523577870461007e-06 - sys_9: 1.961341752112625e-05 - sys_10: -2.8030025648971397e-06 - sys_11: -3.5213919724601684e-05 - sys_12: -4.298086439903232e-06 - sys_13: 2.303362529879535e-05 - sys_14: 1.6507080226418848e-05 - sys_15: -2.57161940873938e-06 - sys_16: 3.52641270335741e-06 - sys_17: 3.517019381160366e-05 - sys_18: -5.867542307177785e-05 - sys_19: 2.503269583660243e-06 - sys_20: -9.169035007412772e-05 - sys_21: -9.062621376866101e-06 - sys_22: -1.105517616458322e-06 - sys_23: -0.0001745942744378507 - sys_24: 6.197017917920129e-05 - sys_25: 2.3523246179592155e-05 - sys_26: -0.00015740595874289465 - sys_27: 1.7226999534726353e-06 - sys_28: 1.996456091095738e-07 - sys_29: -3.8638786991048935e-06 - sys_30: 3.910199249854271e-06 - sys_31: -2.3827251325496483e-06 - sys_32: -2.9933104267906685e-06 - sys_33: -2.846855830380724e-06 - sys_34: 4.925307867909713e-06 - sys_35: -2.4601182028749984e-05 - sys_36: 2.4487832629383495e-05 - sys_37: 2.943184830872442e-06 - sys_38: 1.0902669841415779e-05 - sys_39: 2.8154426116411082e-05 - sys_40: 8.71660470480899e-06 - sys_41: 1.3011292809823739e-05 - sys_42: 0.00038357821508055095 - sys_43: 0.000178357492192417 - sys_44: -0.00020537172042153873 - sys_45: 0.0005415425685794158 - sys_46: 0.0002153769320066239 - sys_47: -0.0007452497927747695 - sys_48: 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-1.0511367959263173e-07 + sys_51: 6.263765489983346e-07 + sys_52: -3.3364707588337093e-07 + sys_53: 3.210077607322483e-07 + sys_54: 2.6116808349928885e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_B.yaml index 3a9c19699f..bfcea5c5f4 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_B.yaml @@ -1,629 +1,629 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT type: STAR2009POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2009LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty 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a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_C.yaml index ce7cc0bb85..7988a2b781 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/uncertainties_C.yaml @@ -1,629 +1,629 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT type: STAR2009POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2009LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: 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+ sys_31: 3.724329362896258e-06 + sys_32: 3.1608320406361226e-06 + sys_33: 5.942568995031885e-07 + sys_34: 1.3922357665635735e-06 + sys_35: -1.3149467933973128e-06 + sys_36: -5.533469628165044e-07 + sys_37: 1.1717996590198879e-07 + sys_38: 6.28114122908241e-08 + sys_39: 4.1053579749333116e-08 + sys_40: -1.2821684120675743e-07 + sys_41: 7.385676250905749e-08 + sys_42: -6.259294180845676e-07 + sys_43: 1.7974643342319183e-07 + sys_44: -6.097475316098167e-08 + sys_45: 2.0875666393910094e-07 + sys_46: -5.889768121013157e-08 + sys_47: -2.0740468523778816e-07 + sys_48: 1.1489386555461357e-08 + sys_49: -6.189557619298634e-08 + sys_50: 5.489500182566103e-09 + sys_51: -1.1661781533954086e-07 + sys_52: -3.4806557457335935e-08 + sys_53: 4.721529918790479e-08 + sys_54: 2.4071563483724825e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_OS.yaml index c24405504c..93521c42a2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_OS.yaml @@ -1,629 +1,629 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT type: STAR2009POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2009LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc54 bins: -- stat: 0.0039 - pol: 0.0003835 - sys_0: -2.490980784559569e-09 - sys_1: 1.0306276401031293e-08 - sys_2: 1.168861355951377e-08 - sys_3: 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4.087748499518048e-06 + sys_54: 1.0723921979698017e-07 +- pol: 0.000598 + lumi: 0.0005 + sys_0: -9.760510588081825e-07 + sys_1: 3.2982173523095426e-06 + sys_2: 0.0002461648753249573 + sys_3: -0.00014826066564818866 + sys_4: -0.00028721035642905834 + sys_5: 2.5307246977877084e-05 + sys_6: 0.0003329430723853257 + sys_7: -0.0009969834753114494 + sys_8: 1.085915500947733e-05 + sys_9: 0.0029145841838451305 + sys_10: 0.0006302103891965757 + sys_11: -0.0008385429249779247 + sys_12: 0.005332132548805452 + sys_13: -0.006513836745363104 + sys_14: -0.005372781033024831 + sys_15: -0.00021982626028653333 + sys_16: 9.608033508857557e-06 + sys_17: -0.0019908999130607073 + sys_18: 0.0026594608581895374 + sys_19: -0.0007641667663534264 + sys_20: 7.733495270018974e-05 + sys_21: -4.158103005843695e-05 + sys_22: -2.2096784079061853e-05 + sys_23: 0.0009037313990061078 + sys_24: 2.0452489273009423e-05 + sys_25: 1.4541308621169646e-05 + sys_26: -0.00027350533469576373 + sys_27: -0.0004328094545077054 + sys_28: -9.68146049479721e-05 + sys_29: -0.00015542762030084837 + sys_30: 0.0004081045532262642 + sys_31: 0.00024444080808111115 + sys_32: 2.337190779790684e-05 + sys_33: -5.8339688696582285e-05 + sys_34: 2.8044159776294532e-05 + sys_35: 3.72279540905547e-05 + sys_36: -3.9619999149580605e-05 + sys_37: -3.9758980568553805e-06 + sys_38: -5.514092091061613e-05 + sys_39: -0.00015982883603593822 + sys_40: 1.280449261976766e-05 + sys_41: -2.870726377210201e-05 + sys_42: -3.935948644132474e-05 + sys_43: 7.950298482475439e-06 + sys_44: 2.012591694092418e-05 + sys_45: -9.68067319800534e-06 + sys_46: 1.7522183443564621e-06 + sys_47: -1.2976108012021999e-06 + sys_48: 3.6223275203775305e-06 + sys_49: -1.7846117863936533e-06 + sys_50: -5.712729578145397e-07 + sys_51: -2.0749258371053974e-06 + sys_52: -2.8104278658360173e-06 + sys_53: 2.2589700272245316e-06 + sys_54: -1.633139895745711e-07 +- pol: 0.001833 + lumi: 0.0005 + sys_0: -3.980543092058885e-06 + sys_1: 1.3970398524194827e-05 + sys_2: 0.006698695525763587 + sys_3: -0.00793412613824112 + sys_4: -0.030445063700132294 + sys_5: -7.702880306314849e-05 + sys_6: -0.010664823694105978 + sys_7: 0.004045701935387951 + sys_8: -2.080986418097191e-06 + sys_9: -0.001778520371006865 + sys_10: -0.00039920864031923396 + sys_11: -0.0007148417922962354 + sys_12: -0.0003507484962298639 + sys_13: -0.000280310250052849 + sys_14: -0.00014604134545650934 + sys_15: -6.1379837546738025e-06 + sys_16: 5.348445281537037e-07 + sys_17: -7.909706169156667e-05 + sys_18: 0.0002184054704118239 + sys_19: -6.89376215888873e-05 + sys_20: -2.598450008067757e-05 + sys_21: -4.33509734711091e-06 + sys_22: -2.1736458644610068e-06 + sys_23: 5.326387141743868e-05 + sys_24: 5.116577685065594e-06 + sys_25: 2.8475504628413597e-06 + sys_26: -7.0262723636100016e-06 + sys_27: -3.2749443307112043e-06 + sys_28: -1.8661919913722762e-05 + sys_29: -3.3765339113065e-05 + sys_30: 4.0929143886329305e-05 + sys_31: 1.3633282072982091e-05 + sys_32: -1.1493360209342068e-06 + sys_33: -2.4010967050596406e-05 + sys_34: 8.18218511486655e-06 + sys_35: 4.814138112902533e-07 + sys_36: -3.6548531854894057e-06 + sys_37: -1.643184661524371e-06 + sys_38: -3.6461298588737134e-06 + sys_39: -7.848204247780759e-06 + sys_40: 8.640501022415997e-07 + sys_41: -2.1121208712118595e-06 + sys_42: -1.324611046806053e-06 + sys_43: -4.0264779842782366e-07 + sys_44: 1.9977230560802901e-07 + sys_45: 4.404127961440465e-07 + sys_46: -4.842444951624331e-07 + sys_47: -7.365413583612433e-07 + sys_48: 3.7846729672894614e-07 + sys_49: -3.4935933045267453e-07 + sys_50: -7.018020041527868e-08 + sys_51: -5.694394543822049e-07 + sys_52: -3.8742966940176704e-07 + sys_53: 2.964432619699536e-07 + sys_54: -4.5220944437680936e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_SS.yaml index cd676c7e58..6d2ed1a16f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/uncertainties_SS.yaml @@ -1,629 +1,629 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT type: STAR2009POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2009LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2009JETunc54 bins: -- stat: 0.0034 - pol: 0.0004355 - sys_0: -1.2745868794533312e-09 - sys_1: 5.120321056287781e-09 - sys_2: 6.386890279342732e-09 - sys_3: 1.636839171651797e-08 - sys_4: -1.876596185166426e-08 - sys_5: 5.240963420460901e-08 - sys_6: 1.2667280621917562e-07 - sys_7: 1.0533077232717144e-07 - sys_8: -5.909593501694135e-08 - sys_9: -5.370555059654927e-09 - sys_10: 1.8784551051893875e-07 - sys_11: -6.805393160204776e-07 - sys_12: -2.115147845212925e-07 - sys_13: -2.4291859665512185e-07 - sys_14: 3.406153503592616e-07 - sys_15: -3.5090738506470977e-07 - sys_16: -3.248576737969297e-07 - sys_17: 1.281411980643582e-06 - sys_18: -3.6722707093429534e-06 - sys_19: 1.2322367810287309e-06 - sys_20: -1.0719865566934256e-05 - sys_21: -1.885319851314969e-06 - sys_22: 6.071508772117032e-07 - sys_23: -1.9592001052782388e-05 - sys_24: 9.458591571518832e-06 - sys_25: 2.84295538950472e-06 - sys_26: -2.2035053122664686e-05 - sys_27: 0.00039111709520215553 - sys_28: -3.723149557826914e-06 - sys_29: 4.1367206480643e-05 - sys_30: -1.8593847733150164e-05 - sys_31: 9.596462511338796e-06 - sys_32: 6.7331431775377086e-06 - sys_33: 1.0542770059641744e-06 - sys_34: 7.534410009367287e-07 - sys_35: 7.957284888242403e-06 - sys_36: 1.1006736973337248e-05 - sys_37: -1.9061219870056966e-06 - sys_38: -1.3545978259841597e-06 - sys_39: -4.331648875645404e-06 - sys_40: 1.7546835696520169e-06 - sys_41: -1.3174078906600774e-05 - sys_42: 2.5203309227554118e-05 - sys_43: 2.0557721023596863e-05 - sys_44: -5.773983037994242e-06 - sys_45: 1.8283424891136337e-05 - sys_46: -1.9721829072765582e-06 - sys_47: 2.2853646239582307e-05 - sys_48: 8.81673476935858e-06 - sys_49: 1.803515701842365e-06 - sys_50: 3.151405309805501e-05 - sys_51: -1.7120709524932526e-05 - sys_52: 2.43002292968815e-06 - sys_53: -1.7999739025710678e-06 - sys_54: 8.495918057917717e-07 -- stat: 0.0032 - pol: 0.000572 - sys_0: -3.6587585470463116e-09 - sys_1: 1.2867903197716932e-08 - sys_2: 2.4517508347389007e-08 - sys_3: 5.817710305632352e-08 - sys_4: -1.082271024754738e-07 - sys_5: 2.9847872696186816e-07 - sys_6: 1.6133934715876545e-06 - sys_7: 9.366570452780046e-07 - sys_8: -2.0722094351624073e-07 - sys_9: -4.199594299714516e-08 - sys_10: 1.925952968818986e-06 - sys_11: -3.3267696622952146e-06 - sys_12: -6.215190765101206e-06 - sys_13: -5.068868278401309e-06 - sys_14: 8.076883728919418e-06 - sys_15: -2.6607318408289053e-06 - sys_16: 4.514668060561866e-07 - sys_17: 2.1220627237716343e-05 - sys_18: -2.30575513348619e-05 - sys_19: 2.3097400068499534e-05 - sys_20: -3.7246173904704516e-05 - sys_21: 2.938959153748784e-06 - sys_22: -5.965108372991939e-07 - sys_23: -5.4234248264774566e-05 - sys_24: 2.8803488100855046e-06 - sys_25: 1.1097086133668866e-05 - sys_26: -2.4140947100402166e-05 - sys_27: 2.5964475477153514e-05 - sys_28: -0.0002020739018161458 - sys_29: -0.00043333442484540615 - sys_30: -9.232496512322661e-05 - sys_31: -4.8220882182179985e-06 - sys_32: 3.350354434701201e-05 - sys_33: -1.4376087269335327e-06 - sys_34: -1.7068994879608797e-05 - sys_35: 9.606136763692325e-06 - sys_36: -1.2097597459274236e-06 - sys_37: 6.975368658095652e-06 - sys_38: -6.127785661849465e-06 - sys_39: 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6.850030180857224e-08 + sys_36: -1.9746487335832137e-06 + sys_37: -5.064178900521006e-07 + sys_38: -1.5364179170256934e-06 + sys_39: -3.872252042783669e-06 + sys_40: 5.253867234223082e-07 + sys_41: -9.277383719802631e-07 + sys_42: -6.126622792770463e-07 + sys_43: -1.8873070995916441e-07 + sys_44: 5.570752965623039e-08 + sys_45: 2.804371869898015e-07 + sys_46: -2.7537327727124625e-07 + sys_47: -4.019236265125793e-07 + sys_48: 2.1754650250370236e-07 + sys_49: -1.8662544883500077e-07 + sys_50: -4.319177183898664e-08 + sys_51: -3.0596987859297205e-07 + sys_52: -2.1576141744187774e-07 + sys_53: 1.655365569083554e-07 + sys_54: -2.6227567542193994e-08 From e3805a7874c258c9e5571e867434f7305e3ced38 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 17 May 2024 14:59:42 +0200 Subject: [PATCH 53/98] move filters closer to raw data --- .../STAR_2009_1JET_200GEV/filter.py} | 32 +++++++++---------- .../STAR_2012_1JET_510GEV/filter.py} | 16 ++++++---- .../STAR_2013_1JET_510GEV/filter.py} | 21 ++++++------ .../STAR_2015_1JET_200GEV/filter.py} | 16 ++++++---- 4 files changed, 46 insertions(+), 39 deletions(-) rename nnpdf_data/nnpdf_data/{filter_utils/star/jet_dijet_2009_200gev.py => new_commondata/STAR_2009_1JET_200GEV/filter.py} (88%) rename nnpdf_data/nnpdf_data/{filter_utils/star/jet_dijet_2012_510gev.py => new_commondata/STAR_2012_1JET_510GEV/filter.py} (95%) rename nnpdf_data/nnpdf_data/{filter_utils/star/jet_dijet_2013_510gev.py => new_commondata/STAR_2013_1JET_510GEV/filter.py} (94%) rename nnpdf_data/nnpdf_data/{filter_utils/star/jet_dijet_2015_200gev.py => new_commondata/STAR_2015_1JET_200GEV/filter.py} (95%) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py similarity index 88% rename from nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index cfdc7bf334..bdddca6e50 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2009_200gev.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -14,7 +14,7 @@ POL_UNC = 0.065 LUMI_UNC = 0.0005 YEAR = 2009 -HERE = pathlib.Path(__file__).parents[2] +HERE = pathlib.Path(__file__).parent def read_1jet_data(): @@ -22,11 +22,11 @@ def read_1jet_data(): df4 = pd.DataFrame() fnames = [ - f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_3_ALL.csv", - f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_3_pT.csv", - f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_4_ALL.csv", - f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_4_pT.csv", - f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/Table_5.csv", + f"rawdata/Table_3_ALL.csv", + f"rawdata/Table_3_pT.csv", + f"rawdata/Table_4_ALL.csv", + f"rawdata/Table_4_pT.csv", + f"rawdata/Table_5.csv", ] for fname in fnames: @@ -90,9 +90,9 @@ def read_1jet_data(): def read_2jet_data(topology): if "S" in topology: - fname = f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/rawdata/Table_{topology}.yaml" + fname = f"../STAR_{YEAR}_2JET_MIDRAP_200GEV/rawdata/Table_{topology}.yaml" else: - fname = f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/rawdata/Table_{topology}.yaml" + fname = f"../STAR_{YEAR}_2JET_200GEV/rawdata/Table_{topology}.yaml" df = pd.DataFrame() with open(fname, "r", encoding="utf-8") as file: data = yaml.safe_load(file) @@ -145,11 +145,11 @@ def read_2jet_data(topology): def write_1jet_data(df, art_sys): - STORE_PATH = f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/" + STORE_PATH = HERE # Write central data data_central_yaml = {"data_central": list(df["ALL"])} - with open(STORE_PATH + "data.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file) # Write kin file @@ -166,7 +166,7 @@ def write_1jet_data(df, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH + "kinematics.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -203,16 +203,14 @@ def write_1jet_data(df, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH + "uncertainties.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) def write_2jet_data(df, topology, art_sys): - STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/" + STORE_PATH = f"../STAR_{YEAR}_2JET_200GEV/" if "S" in topology: - STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_MIDRAP_200GEV/" - else: - STORE_PATH = f"../../new_commondata/STAR_{YEAR}_2JET_200GEV/" + STORE_PATH = f"../STAR_{YEAR}_2JET_MIDRAP_200GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} with open(STORE_PATH + f"data_{topology}.yaml", "w", encoding="utf-8") as file: @@ -296,7 +294,7 @@ def write_2jet_data(df, topology, art_sys): # load correlations ndata_dict = {a: len(b) for a, b in dfs.items()} correlation_df = pd.read_csv( - f"../../new_commondata/STAR_{YEAR}_1JET_200GEV/rawdata/correlation.csv", + "rawdata/correlation.csv", index_col=0, ) # from the supplement material: diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py similarity index 95% rename from nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py index dfbd04d786..16061682f8 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2012_510gev.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py @@ -20,8 +20,8 @@ POL_UNC = 0.066 TOPOPLOGY_LIST = ["I", "A", "B", "C", "D"] -HERE = pathlib.Path(__file__).parents[2] -RAWDATA_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/rawdata/" +HERE = pathlib.Path(__file__).parent +RAWDATA_PATH = HERE / "rawdata/" def read_1jet_data(): @@ -117,7 +117,7 @@ def read_correlations(ndata_dict): def write_1jet_data(df, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/" + STORE_PATH = HERE # Write central data data_central_yaml = {"data_central": list(df["ALL"])} @@ -187,7 +187,7 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_{SQRTS}GEV/" + STORE_PATH = HERE / f"../STAR_{YEAR}_2JET_{SQRTS}GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: @@ -206,7 +206,9 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -253,7 +255,9 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py similarity index 94% rename from nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py index 06ca98d32b..ab62928cc2 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2013_510gev.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py @@ -20,8 +20,8 @@ YEAR = 2013 TOPOPLOGY_LIST = ["1JET", "A", "B", "C", "D"] -HERE = pathlib.Path(__file__).parents[2] -RAWDATA_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_510GEV/rawdata/" +HERE = pathlib.Path(__file__).parent +RAWDATA_PATH = HERE / "rawdata/" def read_1jet_data(): @@ -128,7 +128,7 @@ def read_correlations(ndata_dict): def write_1jet_data(df, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_510GEV/" + STORE_PATH = HERE # Write central data data_central_yaml = {"data_central": list(df["ALL"])} @@ -172,10 +172,7 @@ def write_1jet_data(df, art_sys): } # loop on data points for i, sys_i in enumerate(art_sys): - e = { - "pol": float(df.loc[i, "pol"]), - "lumi": float(df.loc[i, "lumi"]) - } + e = {"pol": float(df.loc[i, "pol"]), "lumi": float(df.loc[i, "lumi"])} # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -199,7 +196,7 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_510GEV/" + STORE_PATH = HERE / f"../STAR_{YEAR}_2JET_510GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: @@ -218,7 +215,9 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -265,7 +264,9 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) diff --git a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py similarity index 95% rename from nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index 9e6cbd6697..121b6ebde6 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/star/jet_dijet_2015_200gev.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -38,8 +38,8 @@ ("SS", "SS"): 11, } -HERE = pathlib.Path(__file__).parents[2] -RAWDATA_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/rawdata/" +HERE = pathlib.Path(__file__).parent +RAWDATA_PATH = HERE / "rawdata/" def read_1jet_data(topology): @@ -140,7 +140,7 @@ def read_correlations(ndata_dict): def write_1jet_data(df, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_1JET_{SQRTS}GEV/" + STORE_PATH = HERE # Write central data data_central_yaml = {"data_central": list(df["ALL"])} @@ -210,7 +210,7 @@ def write_1jet_data(df, art_sys): def write_2jet_data(df, topology, art_sys): - STORE_PATH = HERE / f"new_commondata/STAR_{YEAR}_2JET_MIDRAP_{SQRTS}GEV/" + STORE_PATH = HERE / f"../STAR_{YEAR}_2JET_MIDRAP_{SQRTS}GEV/" # Write central data data_central_yaml = {"data_central": list(df["ALL"])} with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: @@ -229,7 +229,9 @@ def write_2jet_data(df, topology, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -275,7 +277,9 @@ def write_2jet_data(df, topology, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) From bbd5112af8b921c7417350f42b73aa2ebd92f201 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 23 May 2024 17:38:11 +0200 Subject: [PATCH 54/98] correct unc order in 2015 data --- .../STAR_2015_1JET_200GEV/filter.py | 13 +- .../STAR_2015_1JET_200GEV/uncertainties.yaml | 132 +++++++++--------- .../uncertainties_OS.yaml | 44 +++--- .../uncertainties_SS.yaml | 44 +++--- 4 files changed, 116 insertions(+), 117 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index 121b6ebde6..968cd66a91 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -184,7 +184,7 @@ def write_1jet_data(df, art_sys): } # loop on data points for i, sys_i in enumerate(art_sys): - e = {} + e = {"lumi": float(df.loc[i, "lumi"]), "pol": float(df.loc[i, "pol"])} # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val @@ -200,8 +200,6 @@ def write_1jet_data(df, art_sys): for j in range(len(sys_i)) } ) - e["lumi"] = float(df.loc[i, "lumi"]) - e["pol"] = float(df.loc[i, "pol"]) error.append(e) uncertainties_yaml = {"definitions": error_definition, "bins": error} @@ -255,13 +253,14 @@ def write_2jet_data(df, topology, art_sys): } # loop on data points for i, sys_i in enumerate(art_sys): - e = {} + e = { + "stat": float(df.loc[i, "stat"]), + "lumi": float(df.loc[i, "lumi"]), + "pol": float(df.loc[i, "pol"]), + } # loop on art sys for j, val in enumerate(sys_i): e[f"sys_{j}"] = val - e["stat"] = float(df.loc[i, "stat"]) - e["lumi"] = float(df.loc[i, "lumi"]) - e["pol"] = float(df.loc[i, "pol"]) error.append(e) if i == 0: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml index 0815fda9fb..76b929492c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml @@ -152,7 +152,9 @@ definitions: treatment: ADD type: STAR2015JETunc35 bins: -- sys_0: -1.2124945963636329e-05 +- lumi: 0.0007 + pol: 1.22e-05 + sys_0: -1.2124945963636329e-05 sys_1: 3.99763242964474e-05 sys_2: -2.073300487801316e-05 sys_3: 7.834205546114172e-05 @@ -188,9 +190,9 @@ bins: sys_33: -3.0106496090811998e-05 sys_34: -3.940821208479835e-05 sys_35: -9.25488815805122e-07 - lumi: 0.0007 - pol: 1.22e-05 -- sys_0: -7.696816897816436e-06 +- lumi: 0.0007 + pol: 3.6599999999999995e-05 + sys_0: -7.696816897816436e-06 sys_1: 3.158329891762911e-05 sys_2: -1.4276093639918046e-05 sys_3: 6.169333966668052e-05 @@ -226,9 +228,9 @@ bins: sys_33: -1.0460776050192041e-05 sys_34: -1.205550817839274e-05 sys_35: -1.7326915567916684e-06 - lumi: 0.0007 - pol: 3.6599999999999995e-05 -- sys_0: -8.928271882845198e-06 +- lumi: 0.0007 + pol: 0.00020739999999999997 + sys_0: -8.928271882845198e-06 sys_1: 3.2189485897211125e-05 sys_2: -1.8072701944326597e-05 sys_3: 6.114437754903917e-05 @@ -264,9 +266,9 @@ bins: sys_33: 1.6040914058375196e-05 sys_34: 5.679656267908188e-05 sys_35: -4.019081618240074e-05 - lumi: 0.0007 - pol: 0.00020739999999999997 -- sys_0: -8.338592642569744e-06 +- lumi: 0.0007 + pol: 0.0002501 + sys_0: -8.338592642569744e-06 sys_1: 2.617917607607148e-05 sys_2: -1.5692810293999932e-05 sys_3: 5.08686821586224e-05 @@ -302,9 +304,9 @@ bins: sys_33: 4.665788660243067e-05 sys_34: 6.327071886069236e-05 sys_35: -3.565453805427996e-05 - lumi: 0.0007 - pol: 0.0002501 -- sys_0: -1.102035219590501e-05 +- lumi: 0.0007 + pol: 0.000427 + sys_0: -1.102035219590501e-05 sys_1: 2.7991568409825474e-05 sys_2: -2.0944431656817954e-05 sys_3: 5.401419660453429e-05 @@ -340,9 +342,9 @@ bins: sys_33: 2.845084956211712e-05 sys_34: -6.39257320624614e-06 sys_35: -1.1410793563392638e-06 - lumi: 0.0007 - pol: 0.000427 -- sys_0: -1.3674843667800021e-05 +- lumi: 0.0007 + pol: 0.00027449999999999995 + sys_0: -1.3674843667800021e-05 sys_1: 3.0913815568366185e-05 sys_2: -2.8236049481321965e-05 sys_3: 5.934452019765229e-05 @@ -378,9 +380,9 @@ bins: sys_33: 2.2234460889475192e-05 sys_34: -1.2046685413134894e-05 sys_35: 4.144281777041136e-05 - lumi: 0.0007 - pol: 0.00027449999999999995 -- sys_0: -2.8989153926199464e-05 +- lumi: 0.0007 + pol: 0.0011102 + sys_0: -2.8989153926199464e-05 sys_1: 5.418810980982054e-05 sys_2: -5.917438350298771e-05 sys_3: 0.00010223703152275538 @@ -416,9 +418,9 @@ bins: sys_33: 7.12786764329618e-07 sys_34: 6.068042139452258e-06 sys_35: 5.331627034544395e-05 - lumi: 0.0007 - pol: 0.0011102 -- sys_0: -6.282312105818616e-05 +- lumi: 0.0007 + pol: 0.0013419999999999999 + sys_0: -6.282312105818616e-05 sys_1: 0.00010235921169198076 sys_2: -0.0001250611165520945 sys_3: 0.00020264051282595339 @@ -454,9 +456,9 @@ bins: sys_33: -7.744966400500296e-06 sys_34: 8.133443748848957e-06 sys_35: 3.3656216005843106e-05 - lumi: 0.0007 - pol: 0.0013419999999999999 -- sys_0: -0.0001865596034548736 +- lumi: 0.0007 + pol: 0.0011955999999999998 + sys_0: -0.0001865596034548736 sys_1: 0.0002777096776161295 sys_2: -0.00032258703013926776 sys_3: 0.0005809294410633857 @@ -492,9 +494,9 @@ bins: sys_33: -3.6960700075960874e-06 sys_34: 3.2641840370739155e-06 sys_35: 1.2362679925970823e-05 - lumi: 0.0007 - pol: 0.0011955999999999998 -- sys_0: -0.0004700112851671235 +- lumi: 0.0007 + pol: 0.0021227999999999998 + sys_0: -0.0004700112851671235 sys_1: 0.0009620707563561095 sys_2: -0.0009468978924169789 sys_3: 0.012673677482024638 @@ -530,9 +532,9 @@ bins: sys_33: -1.0984120173533775e-06 sys_34: 7.879208007930184e-07 sys_35: 3.3617657479900855e-06 - lumi: 0.0007 - pol: 0.0021227999999999998 -- sys_0: -0.0015533688718685544 +- lumi: 0.0007 + pol: 0.0031414999999999998 + sys_0: -0.0015533688718685544 sys_1: 0.02386976354434967 sys_2: 0.0009923420768127396 sys_3: -0.0005231263396747903 @@ -568,9 +570,9 @@ bins: sys_33: -2.600280551946243e-07 sys_34: 1.5749262377752516e-07 sys_35: 7.212885582617392e-07 - lumi: 0.0007 - pol: 0.0031414999999999998 -- sys_0: -5.723798549241382e-06 +- lumi: 0.0007 + pol: 1.2810000000000001e-05 + sys_0: -5.723798549241382e-06 sys_1: 9.519767702735362e-06 sys_2: -1.27072652067246e-05 sys_3: 1.644997190275843e-05 @@ -606,9 +608,9 @@ bins: sys_33: -4.90672716722918e-07 sys_34: -3.1959478982973937e-07 sys_35: -8.284104652471781e-07 - lumi: 0.0007 - pol: 1.2810000000000001e-05 -- sys_0: -6.372141793123253e-06 +- lumi: 0.0007 + pol: 5.5509999999999995e-05 + sys_0: -6.372141793123253e-06 sys_1: 1.0618676135602555e-05 sys_2: -1.4184286764078104e-05 sys_3: 1.8479492775187063e-05 @@ -644,9 +646,9 @@ bins: sys_33: 2.3060710759818616e-06 sys_34: 4.07222628215677e-06 sys_35: -9.638148723929519e-07 - lumi: 0.0007 - pol: 5.5509999999999995e-05 -- sys_0: -6.883019370244076e-06 +- lumi: 0.0007 + pol: 5.1240000000000004e-05 + sys_0: -6.883019370244076e-06 sys_1: 1.1003558621330908e-05 sys_2: -1.4444661657173362e-05 sys_3: 1.971365836321765e-05 @@ -682,9 +684,9 @@ bins: sys_33: 3.0554846486099124e-05 sys_34: 4.969212162931906e-05 sys_35: -1.2327423718436603e-05 - lumi: 0.0007 - pol: 5.1240000000000004e-05 -- sys_0: -9.471336297659553e-06 +- lumi: 0.0007 + pol: 0.00020313 + sys_0: -9.471336297659553e-06 sys_1: 1.4274548261633827e-05 sys_2: -1.9652809278312388e-05 sys_3: 2.5742472891751052e-05 @@ -720,9 +722,9 @@ bins: sys_33: 2.5238598526427057e-05 sys_34: 3.552091450700702e-05 sys_35: -1.2398305794429084e-05 - lumi: 0.0007 - pol: 0.00020313 -- sys_0: -1.0025507958493132e-05 +- lumi: 0.0007 + pol: 0.00014518 + sys_0: -1.0025507958493132e-05 sys_1: 1.5966373432219618e-05 sys_2: -1.924079064195383e-05 sys_3: 2.7315971371502272e-05 @@ -758,9 +760,9 @@ bins: sys_33: 1.2251701674935625e-05 sys_34: 6.492627009709344e-06 sys_35: 2.0707330919804266e-07 - lumi: 0.0007 - pol: 0.00014518 -- sys_0: -1.1173338612528268e-05 +- lumi: 0.0007 + pol: 0.00013054 + sys_0: -1.1173338612528268e-05 sys_1: 1.961048432764371e-05 sys_2: -2.6857840121337563e-05 sys_3: 3.827487028139256e-05 @@ -796,9 +798,9 @@ bins: sys_33: 7.5336045442300225e-06 sys_34: 2.312309112345567e-07 sys_35: 1.7638210086536075e-05 - lumi: 0.0007 - pol: 0.00013054 -- sys_0: -2.0570477258499703e-05 +- lumi: 0.0007 + pol: 0.0006960099999999999 + sys_0: -2.0570477258499703e-05 sys_1: 3.341772185543097e-05 sys_2: -4.488134242205468e-05 sys_3: 7.22681155104189e-05 @@ -834,9 +836,9 @@ bins: sys_33: 8.596633620516164e-07 sys_34: 3.3544762057573375e-06 sys_35: 2.0748792722128864e-05 - lumi: 0.0007 - pol: 0.0006960099999999999 -- sys_0: -3.9270091634046984e-05 +- lumi: 0.0007 + pol: 0.0007490799999999998 + sys_0: -3.9270091634046984e-05 sys_1: 6.762426798557228e-05 sys_2: -9.500115401585762e-05 sys_3: 0.0001662493026874323 @@ -872,9 +874,9 @@ bins: sys_33: -1.8827213363243646e-06 sys_34: 2.5310937188896434e-06 sys_35: 1.150124798434345e-05 - lumi: 0.0007 - pol: 0.0007490799999999998 -- sys_0: -0.00012846028769728705 +- lumi: 0.0007 + pol: 0.00125477 + sys_0: -0.00012846028769728705 sys_1: 0.00024121601804400018 sys_2: -0.00028844090043889206 sys_3: 0.000780111286063014 @@ -910,9 +912,9 @@ bins: sys_33: -8.843570008920012e-07 sys_34: 9.058648750522456e-07 sys_35: 3.6552706483788882e-06 - lumi: 0.0007 - pol: 0.00125477 -- sys_0: -0.00041642847232082193 +- lumi: 0.0007 + pol: 0.00324154 + sys_0: -0.00041642847232082193 sys_1: 0.001228477045927712 sys_2: -0.017984095958256955 sys_3: -0.0007360631397773987 @@ -948,9 +950,9 @@ bins: sys_33: -2.397396013195239e-07 sys_34: 2.2429290663413933e-07 sys_35: 8.388911008785556e-07 - lumi: 0.0007 - pol: 0.00324154 -- sys_0: -0.03571864759170568 +- lumi: 0.0007 + pol: 0.0014127599999999999 + sys_0: -0.03571864759170568 sys_1: -0.001080992033376142 sys_2: 0.00018610101689361095 sys_3: -0.00015040075674074282 @@ -986,5 +988,3 @@ bins: sys_33: -4.7218640493053443e-08 sys_34: 2.8007774467043292e-08 sys_35: 1.3924274174491083e-07 - lumi: 0.0007 - pol: 0.0014127599999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml index 27059f57b1..110235f85b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml @@ -156,7 +156,10 @@ definitions: treatment: ADD type: STAR2015JETunc35 bins: -- sys_0: -1.1061320396018662e-06 +- stat: 0.004 + lumi: 0.0007 + pol: 0.00040869999999999996 + sys_0: -1.1061320396018662e-06 sys_1: 2.1718755370553993e-06 sys_2: -2.5830445253971692e-06 sys_3: 3.6296783741788805e-06 @@ -192,10 +195,10 @@ bins: sys_33: 5.19964952240731e-06 sys_34: 9.60304630965654e-06 sys_35: -7.60469426007191e-06 - stat: 0.004 +- stat: 0.0027 lumi: 0.0007 - pol: 0.00040869999999999996 -- sys_0: -1.6340573248922996e-06 + pol: 0.00014639999999999998 + sys_0: -1.6340573248922996e-06 sys_1: 2.7041776919630667e-06 sys_2: -3.1173178937115303e-06 sys_3: 4.712942052475756e-06 @@ -231,10 +234,10 @@ bins: sys_33: 1.3229956462983903e-05 sys_34: 1.235315338187078e-05 sys_35: -4.490122223588943e-06 - stat: 0.0027 +- stat: 0.0032 lumi: 0.0007 - pol: 0.00014639999999999998 -- sys_0: -1.994515872365404e-06 + pol: 0.00031719999999999996 + sys_0: -1.994515872365404e-06 sys_1: 3.914843156851392e-06 sys_2: -4.394730722983546e-06 sys_3: 6.425295676120617e-06 @@ -270,10 +273,10 @@ bins: sys_33: 2.088399733065828e-05 sys_34: 9.726205441236005e-06 sys_35: 2.7812484922401876e-05 - stat: 0.0032 +- stat: 0.0044 lumi: 0.0007 - pol: 0.00031719999999999996 -- sys_0: -1.598029786007592e-06 + pol: 0.0006709999999999999 + sys_0: -1.598029786007592e-06 sys_1: 3.2433940050812422e-06 sys_2: -4.672594779356799e-06 sys_3: 8.135263445821254e-06 @@ -309,10 +312,10 @@ bins: sys_33: 2.234800750523832e-05 sys_34: 8.728947977780823e-06 sys_35: 0.00013824507611649616 - stat: 0.0044 +- stat: 0.0068 lumi: 0.0007 - pol: 0.0006709999999999999 -- sys_0: -3.15647672260929e-06 + pol: 0.0012261 + sys_0: -3.15647672260929e-06 sys_1: 7.330181090309398e-06 sys_2: -9.339034142974121e-06 sys_3: 2.0960959480340322e-05 @@ -348,10 +351,10 @@ bins: sys_33: 0.00043038462482193575 sys_34: -0.00036853205157917347 sys_35: -0.000587271811790324 - stat: 0.0068 +- stat: 0.0097 lumi: 0.0007 - pol: 0.0012261 -- sys_0: -2.489123364895397e-05 + pol: 0.001464 + sys_0: -2.489123364895397e-05 sys_1: 6.169901617600183e-05 sys_2: -7.407651152929401e-05 sys_3: 0.00017160806199955657 @@ -387,10 +390,10 @@ bins: sys_33: 3.094615585902205e-05 sys_34: -2.832481801089827e-05 sys_35: -0.00012936308511524305 - stat: 0.0097 +- stat: 0.0304 lumi: 0.0007 - pol: 0.001464 -- sys_0: -0.000262407865574758 + pol: 0.005697399999999999 + sys_0: -0.000262407865574758 sys_1: 0.0004999571511161691 sys_2: -0.00023742402104442333 sys_3: 0.0003395142113740446 @@ -426,6 +429,3 @@ bins: sys_33: 5.098291029822002e-06 sys_34: -3.140091470604209e-06 sys_35: -1.4394685825368486e-05 - stat: 0.0304 - lumi: 0.0007 - pol: 0.005697399999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml index 3f48767aa6..35bd6533dc 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml @@ -156,7 +156,10 @@ definitions: treatment: ADD type: STAR2015JETunc35 bins: -- sys_0: -1.993644240492427e-06 +- stat: 0.0036 + lumi: 0.0007 + pol: 0.0004331 + sys_0: -1.993644240492427e-06 sys_1: 3.920582178397754e-06 sys_2: -4.666612808032058e-06 sys_3: 6.586698567296014e-06 @@ -192,10 +195,10 @@ bins: sys_33: -0.0004512893694399416 sys_34: -0.000742256259048967 sys_35: 9.770342524098406e-05 - stat: 0.0036 +- stat: 0.0028 lumi: 0.0007 - pol: 0.0004331 -- sys_0: -2.2946739665773644e-06 + pol: 0.00029889999999999995 + sys_0: -2.2946739665773644e-06 sys_1: 3.824616739192873e-06 sys_2: -5.082877104928578e-06 sys_3: 6.6069315690319355e-06 @@ -231,10 +234,10 @@ bins: sys_33: -1.218867660774324e-05 sys_34: -1.8238734535990548e-05 sys_35: -1.456217645240252e-06 - stat: 0.0028 +- stat: 0.0035 lumi: 0.0007 - pol: 0.00029889999999999995 -- sys_0: -2.666045724383394e-06 + pol: 0.00010369999999999999 + sys_0: -2.666045724383394e-06 sys_1: 5.2463453306817116e-06 sys_2: -5.912910553741228e-06 sys_3: 8.775442918988407e-06 @@ -270,10 +273,10 @@ bins: sys_33: 3.1423339882602877e-07 sys_34: -3.862509868941909e-05 sys_35: 0.00021343760152247815 - stat: 0.0035 +- stat: 0.0051 lumi: 0.0007 - pol: 0.00010369999999999999 -- sys_0: -3.002152473240926e-06 + pol: 0.0008356999999999999 + sys_0: -3.002152473240926e-06 sys_1: 5.109338201378194e-06 sys_2: -6.965594896530206e-06 sys_3: 1.16222193788742e-05 @@ -309,10 +312,10 @@ bins: sys_33: -0.0006345514814103799 sys_34: 0.0002880588529425135 sys_35: -0.00048079450842349145 - stat: 0.0051 +- stat: 0.0081 lumi: 0.0007 - pol: 0.0008356999999999999 -- sys_0: -5.059763074576364e-06 + pol: 0.0019276000000000002 + sys_0: -5.059763074576364e-06 sys_1: 9.398095293551316e-06 sys_2: -1.850833515827543e-05 sys_3: 3.099237747411482e-05 @@ -348,10 +351,10 @@ bins: sys_33: 2.8170278505412898e-05 sys_34: -1.4808272155892904e-05 sys_35: -0.00015055826030636424 - stat: 0.0081 +- stat: 0.0121 lumi: 0.0007 - pol: 0.0019276000000000002 -- sys_0: -4.5501937423392515e-05 + pol: 0.0014151999999999997 + sys_0: -4.5501937423392515e-05 sys_1: 9.500547570473894e-05 sys_2: -0.00012884305671045153 sys_3: 0.00024992766515355685 @@ -387,10 +390,10 @@ bins: sys_33: 2.0298288219206972e-05 sys_34: -1.1889346818063713e-05 sys_35: -6.705658902668767e-05 - stat: 0.0121 +- stat: 0.0418 lumi: 0.0007 - pol: 0.0014151999999999997 -- sys_0: -0.0003880105996750081 + pol: 0.0013908000000000002 + sys_0: -0.0003880105996750081 sys_1: 0.0008640577953892648 sys_2: -0.00018226616456970055 sys_3: 0.0004948026664088059 @@ -426,6 +429,3 @@ bins: sys_33: 2.2001974670195147e-06 sys_34: -7.33634436311964e-07 sys_35: -5.440401898597821e-06 - stat: 0.0418 - lumi: 0.0007 - pol: 0.0013908000000000002 From 45bc92a37664716349c89eef2ce44de2b91471c8 Mon Sep 17 00:00:00 2001 From: Giacomo Magni Date: Tue, 4 Jun 2024 09:43:01 +0200 Subject: [PATCH 55/98] fix fktables names --- .../new_commondata/STAR_WMWP_510GEV/metadata.yaml | 10 ++++++---- 1 file changed, 6 insertions(+), 4 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml index 450e8bb43f..9546ba92cc 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml @@ -50,8 +50,9 @@ implemented_observables: theory: FK_tables: - - - STAR_WMWP_510GEV_WM-AL - operation: "null" + - - STAR_WMWP_510GEV_WM-AL-POL + - - STAR_WMWP_510GEV_WM-AL-UNPOL + operation: "ratio" - observable_name: "WP-AL" observable: @@ -86,5 +87,6 @@ implemented_observables: theory: FK_tables: - - - STAR_WMWP_510GEV_WP-AL - operation: "null" + - - STAR_WMWP_510GEV_WP-AL-POL + - - STAR_WMWP_510GEV_WP-AL-UNPOL + operation: "ratio" \ No newline at end of file From a5c84554a928cb2a688ca49d14b7b2a39570c3cd Mon Sep 17 00:00:00 2001 From: Giacomo Magni <39065935+giacomomagni@users.noreply.github.com> Date: Mon, 10 Jun 2024 09:13:53 +0200 Subject: [PATCH 56/98] Update nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml Co-authored-by: Tanjona Rabemananjara --- .../nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml index 9546ba92cc..ed9e43437d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml @@ -22,7 +22,7 @@ implemented_observables: description: "Longitudinal single-spin asymmetry $A_L$ for $W^-$ production as a function of the lepton pseudorapidity, $\eta_e$" label: "$A_L$" units: "" - process_type: "EWK_RAP" + process_type: "EWK_RAP_ASY" ndata: 6 tables: [5] npoints: [6] From 214da12710e688ddf68f964558aad684e0c72f8d Mon Sep 17 00:00:00 2001 From: Giacomo Magni <39065935+giacomomagni@users.noreply.github.com> Date: Mon, 10 Jun 2024 09:14:03 +0200 Subject: [PATCH 57/98] Update nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml Co-authored-by: Tanjona Rabemananjara --- .../nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml index ed9e43437d..9e1a181a75 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml @@ -59,7 +59,7 @@ implemented_observables: description: "Longitudinal single-spin asymmetry $A_L$ for $W^+$ production as a function of the lepton pseudorapidity, $\eta_e$" label: "$A_L$" units: "" - process_type: "EWK_RAP" + process_type: "EWK_RAP_ASY" ndata: 6 tables: [5] npoints: [6] From cb04dee169ea0a7d0e6d1a7d4a0260a846ab2be0 Mon Sep 17 00:00:00 2001 From: Giacomo Magni Date: Tue, 11 Jun 2024 11:07:32 +0200 Subject: [PATCH 58/98] fix latet DY metadata --- .../STAR_WMWP_510GEV/metadata.yaml | 18 +++++++++--------- 1 file changed, 9 insertions(+), 9 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml index 9e1a181a75..8f37e84988 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_WMWP_510GEV/metadata.yaml @@ -19,8 +19,8 @@ nnpdf_metadata: implemented_observables: - observable_name: "WM-AL" observable: - description: "Longitudinal single-spin asymmetry $A_L$ for $W^-$ production as a function of the lepton pseudorapidity, $\eta_e$" - label: "$A_L$" + description: Longitudinal single-spin asymmetry $A_L$ for $W^-$ production as a function of the lepton pseudorapidity, $\eta_e$ + label: $A_L$ units: "" process_type: "EWK_RAP_ASY" ndata: 6 @@ -30,8 +30,8 @@ implemented_observables: # Plotting information plotting: kinematics_override: ewk_rap_sqrt_scale - dataset_label: "STAR $W^{-} \rightarrow e^{-}$" - y_label: "$A_L(\eta_{e})$" + dataset_label: STAR $W^{-} \rightarrow e^{-}$ + y_label: $A_L(\eta_{e})$ plot_x: eta line_by: [] figure_by: [] @@ -39,7 +39,7 @@ implemented_observables: kinematics: variables: - eta: { description: "Lepton pseudorapidity", label: '$\eta$', units: "" } + eta: { description: "Lepton pseudorapidity", label: $\eta$, units: "" } M2: { description: "W boson Mass", label: "$M^2$", units: "$GeV^2$" } sqrts: { description: "Center of Mass Energy", label: '$\sqrt{s}$', units: "$GeV$" } file: kinematics_wm.yaml @@ -56,8 +56,8 @@ implemented_observables: - observable_name: "WP-AL" observable: - description: "Longitudinal single-spin asymmetry $A_L$ for $W^+$ production as a function of the lepton pseudorapidity, $\eta_e$" - label: "$A_L$" + description: Longitudinal single-spin asymmetry $A_L$ for $W^+$ production as a function of the lepton pseudorapidity, $\eta_e$ + label: $A_L$ units: "" process_type: "EWK_RAP_ASY" ndata: 6 @@ -67,8 +67,8 @@ implemented_observables: # Plotting information plotting: kinematics_override: ewk_rap_sqrt_scale - dataset_label: "STAR $W^{+} \rightarrow e^{+}$" - y_label: "$A_L(\eta_{e})$" + dataset_label: STAR $W^{+} \rightarrow e^{+}$ + y_label: $A_L(\eta_{e})$ plot_x: eta line_by: [] figure_by: [] From 4fc04c4a595bf7c6d70346a4eaa372526f2d60a6 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Fri, 14 Jun 2024 11:07:42 +0200 Subject: [PATCH 59/98] update 1jet fktables names --- .../new_commondata/STAR_2005_1JET_200GEV/metadata.yaml | 4 +++- .../new_commondata/STAR_2006_1JET_200GEV/metadata.yaml | 4 +++- .../new_commondata/STAR_2009_1JET_200GEV/metadata.yaml | 4 +++- .../new_commondata/STAR_2012_1JET_510GEV/metadata.yaml | 4 +++- .../new_commondata/STAR_2013_1JET_510GEV/metadata.yaml | 4 +++- .../new_commondata/STAR_2015_1JET_200GEV/metadata.yaml | 4 +++- 6 files changed, 18 insertions(+), 6 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml index f0a2a5d56f..0f02f2a65e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2005_1JET_200GEV/metadata.yaml @@ -51,4 +51,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2005_1JET_200GEV_ALL + - - STAR_2005_1JET_200GEV_ALL-POL + - - STAR_2005_1JET_200GEV_ALL-UNPOL + operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml index fd33472a5b..d8d069f9b8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2006_1JET_200GEV/metadata.yaml @@ -51,4 +51,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2006_1JET_200GEV_ALL + - - STAR_2006_1JET_200GEV_ALL-POL + - - STAR_2006_1JET_200GEV_ALL-UNPOL + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml index af8244f0c2..709bd799c2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml @@ -51,4 +51,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_1JET_200GEV_ALL + - - STAR_2009_1JET_200GEV_ALL-POL + - - STAR_2009_1JET_200GEV_ALL-UNPOL + operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml index 4095a4de8c..cc03bd80e2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/metadata.yaml @@ -54,4 +54,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_1JET_510GEV_ALL + - - STAR_2012_1JET_510GEV_ALL-POL + - - STAR_2012_1JET_510GEV_ALL-UNPOL + operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml index 086d96bbdb..10cfd57013 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/metadata.yaml @@ -49,4 +49,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_1JET_510GEV_ALL + - - STAR_2013_1JET_510GEV_ALL-POL + - - STAR_2013_1JET_510GEV_ALL-UNPOL + operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml index 999d3d8d87..3f63fe84f9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml @@ -49,4 +49,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_1JET_200GEV_ALL + - - STAR_2015_1JET_200GEV_ALL-POL + - - STAR_2015_1JET_200GEV_ALL-UNPOL + operation: "ratio" \ No newline at end of file From 49e15e7d6bac40521d16e0df8a55dd4a8825c489 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 18 Jun 2024 15:14:45 +0200 Subject: [PATCH 60/98] split 1jet 2009 and 2015 into 2 observables --- .../{data.yaml => data_CC.yaml} | 11 - .../STAR_2009_1JET_200GEV/data_CF.yaml | 12 + .../STAR_2009_1JET_200GEV/filter.py | 125 ++- .../STAR_2009_1JET_200GEV/kinematics.yaml | 265 ------ .../STAR_2009_1JET_200GEV/kinematics_CC.yaml | 133 +++ .../STAR_2009_1JET_200GEV/kinematics_CF.yaml | 133 +++ .../STAR_2009_1JET_200GEV/metadata.yaml | 58 +- ...certainties.yaml => uncertainties_CC.yaml} | 627 ------------- .../uncertainties_CF.yaml | 857 ++++++++++++++++++ .../STAR_2015_1JET_200GEV/data_CC.yaml | 12 + .../{data.yaml => data_CF.yaml} | 11 - .../STAR_2015_1JET_200GEV/filter.py | 34 +- .../{kinematics.yaml => kinematics_CC.yaml} | 132 --- .../STAR_2015_1JET_200GEV/kinematics_CF.yaml | 133 +++ .../STAR_2015_1JET_200GEV/metadata.yaml | 52 +- ...certainties.yaml => uncertainties_CC.yaml} | 418 --------- .../uncertainties_CF.yaml | 572 ++++++++++++ 17 files changed, 2018 insertions(+), 1567 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/{data.yaml => data_CC.yaml} (53%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data_CF.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CC.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CF.yaml rename nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/{uncertainties.yaml => uncertainties_CC.yaml} (58%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties_CF.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data_CC.yaml rename nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/{data.yaml => data_CF.yaml} (56%) rename nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/{kinematics.yaml => kinematics_CC.yaml} (50%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics_CF.yaml rename nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/{uncertainties.yaml => uncertainties_CC.yaml} (58%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CF.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data_CC.yaml similarity index 53% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data_CC.yaml index 56efa8beb3..df9f4f0e9d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data_CC.yaml @@ -10,14 +10,3 @@ data_central: - 0.0207 - 0.0326 - 0.0332 -- 0.0018 -- 0.004 -- 0.0059 -- 0.0027 -- 0.0069 -- 0.0087 -- 0.015 -- 0.0195 -- 0.0333 -- 0.0437 -- 0.0055 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data_CF.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data_CF.yaml new file mode 100644 index 0000000000..44f13d9a83 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/data_CF.yaml @@ -0,0 +1,12 @@ +data_central: +- 0.0018 +- 0.004 +- 0.0059 +- 0.0027 +- 0.0069 +- 0.0087 +- 0.015 +- 0.0195 +- 0.0333 +- 0.0437 +- 0.0055 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index bdddca6e50..38fa615406 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -10,74 +10,54 @@ from nnpdf_data.filter_utils.correlations import compute_covmat -TOPOPLOGY_LIST = ["I", "SS", "OS", "A", "B", "C"] +TOPOPLOGY_LIST = ["CC", "CF", "SS", "OS", "A", "B", "C"] POL_UNC = 0.065 LUMI_UNC = 0.0005 YEAR = 2009 HERE = pathlib.Path(__file__).parent -def read_1jet_data(): - df3 = pd.DataFrame() - df4 = pd.DataFrame() - +def read_1jet_data(topology): + tab_number = 3 if "CC" in topology else 4 fnames = [ - f"rawdata/Table_3_ALL.csv", - f"rawdata/Table_3_pT.csv", - f"rawdata/Table_4_ALL.csv", - f"rawdata/Table_4_pT.csv", + f"rawdata/Table_{tab_number}_ALL.csv", + f"rawdata/Table_{tab_number}_pT.csv", f"rawdata/Table_5.csv", ] + df = pd.DataFrame() for fname in fnames: - if "3" in fname: - dfi = pd.read_csv(fname) - if "pT" in fname: - df3["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] - - elif "ALL" in fname: - df3["ALL"] = dfi["$A_{LL}$"] - df3["stat_min"] = dfi["stat -"] - df3["stat_max"] = dfi["stat +"] - df3["sys_min"] = dfi["sys -"] - df3["sys_max"] = dfi["sys +"] - - df3["abs_eta_min"] = 0.0 - df3["abs_eta_max"] = 0.5 - - elif "4" in fname: - dfi = pd.read_csv(fname) - if "pT" in fname: - df4["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] - - if "ALL" in fname: - df4["ALL"] = dfi["$A_{LL}$"] - df4["stat_min"] = dfi["stat -"] - df4["stat_max"] = dfi["stat +"] - df4["sys_min"] = dfi["sys -"] - df4["sys_max"] = dfi["sys +"] - - df4["abs_eta_min"] = 0.5 - df4["abs_eta_max"] = 1.0 - - elif "5" in fname: - dfc_col = pd.read_csv(fname) - - dfc = pd.DataFrame() - biny = 1 - for i in range(len(dfc_col)): - if dfc_col.loc[i, "binx"] == "-": - biny = float(dfc_col.loc[i, "val"]) - else: - binx = float(dfc_col.loc[i, "binx"]) - dfc.loc[binx, biny] = dfc_col.loc[i, "val"] - - dfc = dfc.astype("float") - - else: - print("ERROR: Unknown table number detected! Check input files.") - - df = pd.concat([df3, df4], ignore_index=True) + dfi = pd.read_csv(fname) + if "pT" in fname: + df["pT"] = dfi["Parton Jet $p_T$ [GeV/c]"] + df["pT_min"] = df["pT"] - dfi["sys +"] + df["pT_max"] = df["pT"] + dfi["sys +"] + + elif "ALL" in fname: + df["ALL"] = dfi["$A_{LL}$"] + df["stat_min"] = dfi["stat -"] + df["stat_max"] = dfi["stat +"] + df["sys_min"] = dfi["sys -"] + df["sys_max"] = dfi["sys +"] + # elif "5" in fname: + # dfc_col = pd.read_csv(fname) + + # dfc = pd.DataFrame() + # biny = 1 + # for i in range(len(dfc_col)): + # if dfc_col.loc[i, "binx"] == "-": + # biny = float(dfc_col.loc[i, "val"]) + # else: + # binx = float(dfc_col.loc[i, "binx"]) + # dfc.loc[binx, biny] = dfc_col.loc[i, "val"] + # dfc = dfc.astype("float") + + if topology == "CC": + df["abs_eta_min"] = 0.0 + df["abs_eta_max"] = 0.5 + elif topology == "CF": + df["abs_eta_min"] = 0.5 + df["abs_eta_max"] = 1.0 df["stat"] = df["stat_max"] df["sys"] = df["sys_max"] @@ -85,7 +65,7 @@ def read_1jet_data(): df["lumi"] = LUMI_UNC df["sqrts"] = 200 df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 - return df, dfc + return df def read_2jet_data(topology): @@ -144,19 +124,23 @@ def read_2jet_data(topology): return df -def write_1jet_data(df, art_sys): +def write_1jet_data(df, topology, art_sys): STORE_PATH = HERE # Write central data data_central_yaml = {"data_central": list(df["ALL"])} - with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file) # Write kin file kin = [] for i in range(len(df)): kin_value = { - "pT": {"min": None, "mid": float(df.loc[i, "pT"]), "max": None}, + "pT": { + "min": float(df.loc[i, "pT_min"]), + "mid": float(df.loc[i, "pT"]), + "max": float(df.loc[i, "pT_max"]), + }, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, "abs_eta": { "min": float(df.loc[i, "abs_eta_min"]), @@ -166,7 +150,9 @@ def write_1jet_data(df, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -203,7 +189,9 @@ def write_1jet_data(df, art_sys): ) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) @@ -286,9 +274,10 @@ def write_2jet_data(df, topology, art_sys): if __name__ == "__main__": # load all the data - df, _ = read_1jet_data() - dfs = {"I": df} - for topo in TOPOPLOGY_LIST[1:]: + dfs = {} + for topo in TOPOPLOGY_LIST[:2]: + dfs[topo] = read_1jet_data(topo) + for topo in TOPOPLOGY_LIST[2:]: dfs[topo] = read_2jet_data(topo) # load correlations @@ -314,8 +303,8 @@ def write_2jet_data(df, topology, art_sys): for topo, df in dfs.items(): ndata = ndata_dict[topo] syst = art_sys[cnt : cnt + ndata, :].tolist() - if topo == "I": - write_1jet_data(df, syst) + if topo in ["CC", "CF"]: + write_1jet_data(df, topo, syst) else: write_2jet_data(df, topo, syst) cnt += ndata diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml deleted file mode 100644 index aa80d7522d..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics.yaml +++ /dev/null @@ -1,265 +0,0 @@ -bins: -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 5.5 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 6.49 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 8.25 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 10.08 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 12.26 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 14.78 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 17.23 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 20.56 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 23.61 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 27.78 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 0.5 - mid: 0.25 - min: 0.0 - pT: - max: null - mid: 32.46 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 5.61 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 6.62 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 8.48 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 10.17 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 12.2 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 14.57 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 16.99 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 20.16 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 23.35 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 27.13 - min: null - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: null - mid: 31.08 - min: null - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CC.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CC.yaml new file mode 100644 index 0000000000..fdf857b07d --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CC.yaml @@ -0,0 +1,133 @@ +bins: +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 6.29 + mid: 5.5 + min: 4.71 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 7.29 + mid: 6.49 + min: 5.69 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 8.95 + mid: 8.25 + min: 7.55 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 10.75 + mid: 10.08 + min: 9.41 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 12.93 + mid: 12.26 + min: 11.59 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 15.489999999999998 + mid: 14.78 + min: 14.07 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 18.0 + mid: 17.23 + min: 16.46 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 21.439999999999998 + mid: 20.56 + min: 19.68 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 24.55 + mid: 23.61 + min: 22.669999999999998 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 28.76 + mid: 27.78 + min: 26.8 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 0.5 + mid: 0.25 + min: 0.0 + pT: + max: 33.57 + mid: 32.46 + min: 31.35 + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CF.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CF.yaml new file mode 100644 index 0000000000..a0c92de0c5 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/kinematics_CF.yaml @@ -0,0 +1,133 @@ +bins: +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 6.42 + mid: 5.61 + min: 4.800000000000001 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 7.43 + mid: 6.62 + min: 5.8100000000000005 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 9.17 + mid: 8.48 + min: 7.790000000000001 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 10.82 + mid: 10.17 + min: 9.52 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 12.84 + mid: 12.2 + min: 11.559999999999999 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 15.18 + mid: 14.57 + min: 13.96 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 17.68 + mid: 16.99 + min: 16.299999999999997 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 21.06 + mid: 20.16 + min: 19.26 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 24.28 + mid: 23.35 + min: 22.42 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 28.22 + mid: 27.13 + min: 26.04 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 32.16 + mid: 31.08 + min: 30.0 + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml index 709bd799c2..891358614a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml @@ -16,12 +16,12 @@ version: 1 version_comment: "Initial implementation" implemented_observables: - - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } - observable_name: ALL + - observable: { description: "ALL w.r.t. pT, central region", label: "$A_{LL}$", units: "" } + observable_name: CC-ALL process_type: JET_POL - ndata: 22 - tables: [3, 4] - npoints: [11, 10] + ndata: 11 + tables: [3] + npoints: [11] kinematics: variables: pT: @@ -38,10 +38,10 @@ implemented_observables: } abs_eta: { description: "pseudorapidity", label: '$|\eta|$', units: "" } - file: kinematics.yaml - data_central: data.yaml + file: kinematics_CC.yaml + data_central: data_CC.yaml data_uncertainties: - - uncertainties.yaml + - uncertainties_CC.yaml kinematic_coverage: [pT, sqrts, abs_eta] plotting: kinematics_override: identity @@ -51,6 +51,44 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_1JET_200GEV_ALL-POL - - - STAR_2009_1JET_200GEV_ALL-UNPOL + - - STAR_2009_1JET_200GEV_CC_ALL-POL + - - STAR_2009_1JET_200GEV_CC_ALL-UNPOL + operation: "ratio" + - observable: { description: "ALL w.r.t. pT, forward region", label: "$A_{LL}$", units: "" } + observable_name: CF-ALL + process_type: JET_POL + ndata: 11 + tables: [4] + npoints: [11] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + abs_eta: { description: "pseudorapidity", label: '$|\eta|$', units: "" } + + file: kinematics_CF.yaml + data_central: data_CF.yaml + data_uncertainties: + - uncertainties_CF.yaml + kinematic_coverage: [pT, sqrts, abs_eta] + plotting: + kinematics_override: identity + dataset_label: "$A_{LL}$" + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2009_1JET_200GEV_CF_ALL-POL + - - STAR_2009_1JET_200GEV_CF_ALL-UNPOL operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties_CC.yaml similarity index 58% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties_CC.yaml index 91ce9eae20..87e5ac31d1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties_CC.yaml @@ -855,630 +855,3 @@ bins: sys_52: 4.2799381896690266e-07 sys_53: -3.531191147765054e-07 sys_54: 5.71579373781375e-08 -- pol: 0.000117 - lumi: 0.0005 - sys_0: -5.506821027750456e-09 - sys_1: 2.739252211864794e-08 - sys_2: 1.1137868577419495e-06 - sys_3: -1.2992980376070698e-06 - sys_4: -5.087499552713517e-07 - sys_5: 1.058952572342688e-07 - sys_6: 9.605686614058354e-07 - sys_7: -3.6379546498137694e-06 - sys_8: 1.3791167703116183e-07 - sys_9: 3.253049442198996e-06 - sys_10: 6.006400597813714e-07 - sys_11: 3.953712520603916e-07 - sys_12: 1.7681045060450807e-06 - sys_13: -7.639940358036286e-07 - sys_14: 3.4331642908065405e-07 - sys_15: -2.3258421629724617e-06 - sys_16: -2.7971493763970495e-06 - sys_17: 2.65588964002764e-06 - sys_18: -4.157757531814495e-06 - sys_19: 1.7493997308158419e-07 - sys_20: -1.1213394043393006e-06 - sys_21: -9.63882945264967e-06 - sys_22: -5.755520798266188e-06 - sys_23: -3.390650190918901e-06 - sys_24: 8.440681953506727e-07 - sys_25: 1.0938902531043213e-06 - sys_26: 4.623811527778041e-06 - sys_27: 3.722796766152232e-06 - sys_28: 3.4930777311396345e-06 - sys_29: 4.742985147702295e-07 - sys_30: -2.1809632310722423e-06 - sys_31: -6.235986392968818e-06 - sys_32: -1.7686237078010353e-05 - sys_33: 5.726486843199723e-06 - sys_34: -2.056539461722482e-06 - sys_35: -3.2256908598487226e-06 - sys_36: 1.060142703231449e-05 - sys_37: 1.9923449041793833e-05 - sys_38: 3.130718482924489e-06 - sys_39: 9.800093598912354e-06 - sys_40: -2.096099532405574e-05 - sys_41: 9.373740811821575e-06 - sys_42: 7.256731353875657e-06 - sys_43: 2.543380412717439e-07 - sys_44: 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sys_20: 0.00011740579183420667 - sys_21: 1.20081827781675e-05 - sys_22: 6.141698742651994e-06 - sys_23: -0.00017082864831847544 - sys_24: -2.392577751623796e-05 - sys_25: -1.0589689068815441e-05 - sys_26: -1.5539930182591537e-06 - sys_27: -4.6545982612664605e-05 - sys_28: 8.287208541220436e-05 - sys_29: 0.00015049120801443951 - sys_30: -0.00020976847756331234 - sys_31: -6.885039895191138e-05 - sys_32: -2.2608683432405345e-05 - sys_33: 3.0247541600462747e-05 - sys_34: -2.085118554443842e-05 - sys_35: -4.7135817897337285e-07 - sys_36: 1.2874591410517985e-05 - sys_37: -5.346321542997382e-07 - sys_38: 1.4300255360083174e-05 - sys_39: 4.131148047332628e-05 - sys_40: -2.1539718824862692e-06 - sys_41: 5.724904661585658e-06 - sys_42: 8.912710280591665e-06 - sys_43: -1.913862023203634e-06 - sys_44: -3.952857675054004e-06 - sys_45: 6.959301525076316e-07 - sys_46: 6.493784466529273e-07 - sys_47: 1.5404502800721786e-06 - sys_48: -1.2242577211467465e-06 - sys_49: 8.123210815364671e-07 - sys_50: 1.2236700414675673e-07 - sys_51: 1.3759105106236719e-06 - sys_52: 1.1663722121304543e-06 - sys_53: -1.1552386626513135e-06 - sys_54: 1.1214667092579576e-08 -- pol: 0.0028405 - lumi: 0.0005 - sys_0: -0.00012098225450670907 - sys_1: 6.0789693236933004e-05 - sys_2: 0.0022375170909480907 - sys_3: 0.00023739815901494 - sys_4: -0.0036887843920609185 - sys_5: 0.0003250303881546486 - sys_6: -0.005344332316351566 - sys_7: -0.02129126984565335 - sys_8: -8.827904845589508e-06 - sys_9: -0.0010693427313493659 - sys_10: -0.00019717534413783664 - sys_11: 0.0008914672490030538 - sys_12: 0.0001716461647427735 - sys_13: 0.00033585386710022734 - sys_14: 0.00015012419382282038 - sys_15: 4.4127091315889635e-06 - sys_16: -1.566006508273607e-07 - sys_17: 3.5566125083870905e-05 - sys_18: -0.00012580014177032033 - sys_19: 4.47014745068638e-05 - sys_20: 1.502862116186592e-05 - sys_21: 5.092215736576258e-06 - sys_22: 2.493995847713682e-06 - sys_23: -2.814856923149159e-05 - sys_24: -9.687603845898797e-06 - sys_25: -5.711515691392399e-06 - sys_26: -1.231224797385536e-06 - sys_27: -3.148990103265279e-05 - sys_28: 3.6129528848914096e-05 - sys_29: 7.645482870197614e-05 - sys_30: -6.586396964070428e-05 - sys_31: -1.5711982989908898e-05 - sys_32: -3.3584386828978814e-06 - sys_33: 2.7599942271847843e-05 - sys_34: -1.1581200810959032e-05 - sys_35: 2.1807710616622894e-06 - sys_36: 4.144659605302365e-06 - sys_37: 1.5591175236310132e-07 - sys_38: 2.9538550688622485e-06 - sys_39: 8.558108846044575e-06 - sys_40: -2.8192985483199423e-07 - sys_41: 8.055161363054198e-07 - sys_42: 8.537414357400066e-07 - sys_43: 2.0702845050676031e-07 - sys_44: 5.18700129868322e-07 - sys_45: -8.294386814415483e-07 - sys_46: 7.175736016930708e-07 - sys_47: 1.2673806876240145e-06 - sys_48: -5.75965879768399e-07 - sys_49: 4.193036372994683e-07 - sys_50: 9.83798369009177e-08 - sys_51: 8.260516473911181e-07 - sys_52: 6.452305132476701e-07 - sys_53: -4.7024574113328823e-07 - sys_54: 8.287956405008234e-08 -- pol: 0.0003575 - lumi: 0.0005 - sys_0: -5.851303888694402e-05 - sys_1: 2.7996178433072823e-05 - sys_2: 0.023224629640945512 - sys_3: -0.036237034818124646 - sys_4: 0.008003515837841282 - sys_5: -3.813740102301659e-05 - sys_6: 0.0016701056177554957 - sys_7: -0.00040765834137889074 - sys_8: -1.7737129262864104e-06 - sys_9: 2.0394080809534508e-05 - sys_10: 6.787560104914701e-06 - sys_11: 0.0001641059785509825 - sys_12: 4.708863366410807e-05 - sys_13: 6.224118370277068e-05 - sys_14: 3.08313575523923e-05 - sys_15: 1.8950480174166717e-06 - sys_16: -6.133377871660353e-08 - sys_17: 7.329579428766248e-06 - sys_18: -2.5443810548522317e-05 - sys_19: 9.118589876708405e-06 - sys_20: 4.2020390144850865e-06 - sys_21: 1.359261726746838e-06 - sys_22: 6.758100137681983e-07 - sys_23: -4.793114976627494e-06 - sys_24: -2.54766859105655e-06 - sys_25: -1.5271941226344646e-06 - sys_26: 1.0671919342521099e-08 - sys_27: -7.685967437978598e-06 - sys_28: 9.222131903998067e-06 - sys_29: 2.0422148006293946e-05 - sys_30: -1.3027245771655229e-05 - sys_31: -2.598688762849034e-06 - sys_32: 3.5439631001725985e-06 - sys_33: 2.1177186337386202e-05 - sys_34: -6.166277657691816e-06 - sys_35: 1.0765348093199076e-06 - sys_36: 1.3504894489862046e-06 - sys_37: 1.286873073837209e-07 - sys_38: 4.939571900975254e-07 - sys_39: 1.3572335039632471e-06 - sys_40: -4.508836659606546e-08 - sys_41: 1.4209188941054532e-07 - sys_42: 9.782771840926777e-08 - sys_43: 1.297144033846644e-07 - sys_44: 1.551932706389958e-07 - sys_45: -4.5351409065237435e-07 - sys_46: 2.3119338958952692e-07 - sys_47: 3.2643631158624316e-07 - sys_48: -1.0783881035789849e-07 - sys_49: 1.1462039465248088e-07 - sys_50: 2.5871992270863685e-08 - sys_51: 2.1207512424022603e-07 - sys_52: 1.7347859435983505e-07 - sys_53: -1.3260584191249427e-07 - sys_54: 2.1561410876753635e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties_CF.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties_CF.yaml new file mode 100644 index 0000000000..76e8bcfbd3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/uncertainties_CF.yaml @@ -0,0 +1,857 @@ +definitions: + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2009POL + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2009LUMI + sys_0: + description: 0 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc0 + sys_1: + description: 1 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc1 + sys_2: + description: 2 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc2 + sys_3: + description: 3 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc3 + sys_4: + description: 4 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc4 + sys_5: + description: 5 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc5 + sys_6: + description: 6 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc6 + sys_7: + description: 7 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc7 + sys_8: + description: 8 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc8 + sys_9: + description: 9 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc9 + sys_10: + description: 10 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc10 + sys_11: + description: 11 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc11 + sys_12: + description: 12 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc12 + sys_13: + description: 13 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc13 + sys_14: + description: 14 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc14 + sys_15: + description: 15 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc15 + sys_16: + description: 16 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc16 + sys_17: + description: 17 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc17 + sys_18: + description: 18 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc18 + sys_19: + description: 19 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc19 + sys_20: + description: 20 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc20 + sys_21: + description: 21 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc21 + sys_22: + description: 22 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc22 + sys_23: + description: 23 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc23 + sys_24: + description: 24 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc24 + sys_25: + description: 25 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc25 + sys_26: + description: 26 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc26 + sys_27: + description: 27 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc27 + sys_28: + description: 28 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc28 + sys_29: + description: 29 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc29 + sys_30: + description: 30 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc30 + sys_31: + description: 31 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc31 + sys_32: + description: 32 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc32 + sys_33: + description: 33 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc33 + sys_34: + description: 34 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc34 + sys_35: + description: 35 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc35 + sys_36: + description: 36 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc36 + sys_37: + description: 37 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc37 + sys_38: + description: 38 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc38 + sys_39: + description: 39 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc39 + sys_40: + description: 40 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc40 + sys_41: + description: 41 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc41 + sys_42: + description: 42 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc42 + sys_43: + description: 43 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc43 + sys_44: + description: 44 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc44 + sys_45: + description: 45 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc45 + sys_46: + description: 46 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc46 + sys_47: + description: 47 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc47 + sys_48: + description: 48 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc48 + sys_49: + description: 49 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc49 + sys_50: + description: 50 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc50 + sys_51: + description: 51 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc51 + sys_52: + description: 52 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc52 + sys_53: + description: 53 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc53 + sys_54: + description: 54 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2009JETunc54 +bins: +- pol: 0.000117 + lumi: 0.0005 + sys_0: -5.506821027750456e-09 + sys_1: 2.739252211864794e-08 + sys_2: 1.1137868577419495e-06 + sys_3: -1.2992980376070698e-06 + sys_4: -5.087499552713517e-07 + sys_5: 1.058952572342688e-07 + sys_6: 9.605686614058354e-07 + sys_7: -3.6379546498137694e-06 + sys_8: 1.3791167703116183e-07 + sys_9: 3.253049442198996e-06 + sys_10: 6.006400597813714e-07 + sys_11: 3.953712520603916e-07 + sys_12: 1.7681045060450807e-06 + sys_13: -7.639940358036286e-07 + sys_14: 3.4331642908065405e-07 + sys_15: -2.3258421629724617e-06 + sys_16: -2.7971493763970495e-06 + sys_17: 2.65588964002764e-06 + sys_18: -4.157757531814495e-06 + sys_19: 1.7493997308158419e-07 + sys_20: -1.1213394043393006e-06 + sys_21: -9.63882945264967e-06 + sys_22: -5.755520798266188e-06 + sys_23: -3.390650190918901e-06 + sys_24: 8.440681953506727e-07 + sys_25: 1.0938902531043213e-06 + sys_26: 4.623811527778041e-06 + sys_27: 3.722796766152232e-06 + sys_28: 3.4930777311396345e-06 + sys_29: 4.742985147702295e-07 + sys_30: -2.1809632310722423e-06 + sys_31: -6.235986392968818e-06 + sys_32: -1.7686237078010353e-05 + sys_33: 5.726486843199723e-06 + sys_34: -2.056539461722482e-06 + sys_35: -3.2256908598487226e-06 + sys_36: 1.060142703231449e-05 + sys_37: 1.9923449041793833e-05 + sys_38: 3.130718482924489e-06 + sys_39: 9.800093598912354e-06 + sys_40: -2.096099532405574e-05 + sys_41: 9.373740811821575e-06 + sys_42: 7.256731353875657e-06 + sys_43: 2.543380412717439e-07 + sys_44: -2.1714459422880685e-05 + sys_45: 1.6087047736703096e-05 + sys_46: -3.89548504047662e-05 + sys_47: -5.431434246191443e-05 + sys_48: 6.932791109463223e-05 + sys_49: 1.5474831855534645e-05 + sys_50: 0.00037113542494003274 + sys_51: 0.00013359733801602053 + sys_52: -0.001431996473686652 + sys_53: -0.0006691412348854212 + sys_54: 0.00023226151201889545 +- pol: 0.00026000000000000003 + lumi: 0.0005 + sys_0: -1.6713648631843347e-08 + sys_1: 8.507211557487013e-08 + sys_2: 1.9034110932635708e-06 + sys_3: -1.1910558281776848e-06 + sys_4: -2.1058523653469666e-06 + sys_5: 2.9864674166434496e-07 + sys_6: 4.226884208954114e-06 + sys_7: -6.544450063481272e-06 + sys_8: 4.074250963919467e-06 + sys_9: 5.707076639490448e-06 + sys_10: 1.2813744110015189e-06 + sys_11: 2.5559729003532106e-07 + sys_12: 3.7830117987222475e-06 + sys_13: -1.4372090803130597e-06 + sys_14: 1.1976095739202343e-06 + sys_15: -8.649686031399713e-06 + sys_16: -1.087470099546647e-05 + sys_17: 5.074088039905319e-06 + sys_18: -7.961320292181775e-06 + sys_19: 1.890517327436923e-07 + sys_20: -2.1009540827966806e-06 + sys_21: -2.6038125974001887e-05 + sys_22: -1.4481862054348523e-05 + sys_23: -5.720284402087226e-06 + sys_24: 4.289922931660878e-06 + sys_25: 3.5033359259920206e-06 + sys_26: 9.530666773555164e-06 + sys_27: 7.2030923186474694e-06 + sys_28: 7.425554777468945e-06 + sys_29: 3.050579694664354e-07 + sys_30: -2.572204371456083e-06 + sys_31: -1.3321261063110006e-05 + sys_32: -5.32542309620597e-05 + sys_33: 1.5330571680739146e-05 + sys_34: -1.0519058295030789e-05 + sys_35: -8.759016948095886e-06 + sys_36: 2.499441513020369e-05 + sys_37: 3.992095199103468e-05 + sys_38: 1.2844149140967452e-05 + sys_39: 1.8730208964982052e-05 + sys_40: -5.822611659064576e-05 + sys_41: 2.9278247161608315e-05 + sys_42: 1.0723165962028554e-05 + sys_43: 5.481015891147782e-06 + sys_44: -4.895761555351499e-05 + sys_45: 3.465089084961219e-05 + sys_46: -0.00014218771934916492 + sys_47: -0.00027194474632430415 + sys_48: 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-1.3027245771655229e-05 + sys_31: -2.598688762849034e-06 + sys_32: 3.5439631001725985e-06 + sys_33: 2.1177186337386202e-05 + sys_34: -6.166277657691816e-06 + sys_35: 1.0765348093199076e-06 + sys_36: 1.3504894489862046e-06 + sys_37: 1.286873073837209e-07 + sys_38: 4.939571900975254e-07 + sys_39: 1.3572335039632471e-06 + sys_40: -4.508836659606546e-08 + sys_41: 1.4209188941054532e-07 + sys_42: 9.782771840926777e-08 + sys_43: 1.297144033846644e-07 + sys_44: 1.551932706389958e-07 + sys_45: -4.5351409065237435e-07 + sys_46: 2.3119338958952692e-07 + sys_47: 3.2643631158624316e-07 + sys_48: -1.0783881035789849e-07 + sys_49: 1.1462039465248088e-07 + sys_50: 2.5871992270863685e-08 + sys_51: 2.1207512424022603e-07 + sys_52: 1.7347859435983505e-07 + sys_53: -1.3260584191249427e-07 + sys_54: 2.1561410876753635e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data_CC.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data_CC.yaml new file mode 100644 index 0000000000..35a7dd4ccc --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data_CC.yaml @@ -0,0 +1,12 @@ +data_central: +- 0.0002 +- 0.0006 +- 0.0034 +- 0.0041 +- 0.007 +- 0.0045 +- 0.0182 +- 0.022 +- 0.0196 +- 0.0348 +- 0.0515 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data_CF.yaml similarity index 56% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data_CF.yaml index 6258c337f7..163cd055e9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/data_CF.yaml @@ -1,15 +1,4 @@ data_central: -- 0.0002 -- 0.0006 -- 0.0034 -- 0.0041 -- 0.007 -- 0.0045 -- 0.0182 -- 0.022 -- 0.0196 -- 0.0348 -- 0.0515 - -0.00021 - 0.00091 - 0.00084 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index 968cd66a91..cca3b39e27 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -139,12 +139,12 @@ def read_correlations(ndata_dict): return tot_corr + tot_corr.T - np.eye(np.sum((*ndata_dict.values(),))) -def write_1jet_data(df, art_sys): +def write_1jet_data(df, topology, art_sys): STORE_PATH = HERE # Write central data data_central_yaml = {"data_central": list(df["ALL"])} - with open(STORE_PATH / "data.yaml", "w", encoding="utf-8") as file: + with open(STORE_PATH / f"data_{topology}.yaml", "w", encoding="utf-8") as file: yaml.dump(data_central_yaml, file) # Write kin file @@ -165,7 +165,9 @@ def write_1jet_data(df, art_sys): } kin.append(kin_value) kinematics_yaml = {"bins": kin} - with open(STORE_PATH / "kinematics.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"kinematics_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(kinematics_yaml, file) # Write unc file @@ -203,7 +205,9 @@ def write_1jet_data(df, art_sys): error.append(e) uncertainties_yaml = {"definitions": error_definition, "bins": error} - with open(STORE_PATH / "uncertainties.yaml", "w", encoding="utf-8") as file: + with open( + STORE_PATH / f"uncertainties_{topology}.yaml", "w", encoding="utf-8" + ) as file: yaml.dump(uncertainties_yaml, file, sort_keys=False) @@ -293,34 +297,30 @@ def write_2jet_data(df, topology, art_sys): ndata_dict = {a: len(b) for a, b in dfs.items()} correlation_df = read_correlations(ndata_dict) - # merge the 1JET topologies - new_dfs = { - "1JET": pd.concat([dfs["CC"], dfs["CF"]], ignore_index=True), - "OS": dfs["OS"], - "SS": dfs["SS"], - } - # from the paper we understand that stat dijet is not correlated # I-I (stat + sys) | I-D (stat + sys) # D-I (stat + sys) | D-D (sys) correlated_unc = np.sqrt( - new_dfs["1JET"]["syst"] ** 2 + new_dfs["1JET"]["stat"] ** 2 + dfs["CC"]["syst"] ** 2 + dfs["CC"]["stat"] ** 2 ).values.tolist() + correlated_unc.extend( + np.sqrt(dfs["CF"]["syst"] ** 2 + dfs["CF"]["stat"] ** 2).values.tolist() + ) for a in (*TOPOPLOGY_LIST,)[2:]: - correlated_unc.extend(new_dfs[a]["syst"].values) + correlated_unc.extend(dfs[a]["syst"].values) # decompose uncertainties - ndata_dict = {a: len(b) for a, b in new_dfs.items()} + ndata_dict = {a: len(b) for a, b in dfs.items()} ndata_points = np.sum((*ndata_dict.values(),)) art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) # write data cnt = 0 - for topo, df in new_dfs.items(): + for topo, df in dfs.items(): ndata = ndata_dict[topo] syst = art_sys[cnt : cnt + ndata, :].tolist() - if topo == "1JET": - write_1jet_data(df, syst) + if "C" in topo: + write_1jet_data(df, topo, syst) else: write_2jet_data(df, topo, syst) cnt += ndata diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics_CC.yaml similarity index 50% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics_CC.yaml index a4781fd3fd..978f9b6214 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics_CC.yaml @@ -131,135 +131,3 @@ bins: max: null mid: 200.0 min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 6.340000000000001 - mid: 6.15 - min: 5.96 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 7.54 - mid: 7.34 - min: 7.14 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 9.78 - mid: 9.5 - min: 9.22 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 11.62 - mid: 11.34 - min: 11.06 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 13.56 - mid: 13.25 - min: 12.94 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 15.83 - mid: 15.47 - min: 15.110000000000001 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 18.44 - mid: 18.07 - min: 17.7 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 21.57 - mid: 21.16 - min: 20.75 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 25.16 - mid: 24.68 - min: 24.2 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 29.09 - mid: 28.56 - min: 28.029999999999998 - sqrts: - max: null - mid: 200.0 - min: null -- abs_eta: - max: 1.0 - mid: 0.75 - min: 0.5 - pT: - max: 33.5 - mid: 32.9 - min: 32.3 - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics_CF.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics_CF.yaml new file mode 100644 index 0000000000..9cc95b9f2a --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/kinematics_CF.yaml @@ -0,0 +1,133 @@ +bins: +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 6.340000000000001 + mid: 6.15 + min: 5.96 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 7.54 + mid: 7.34 + min: 7.14 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 9.78 + mid: 9.5 + min: 9.22 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 11.62 + mid: 11.34 + min: 11.06 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 13.56 + mid: 13.25 + min: 12.94 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 15.83 + mid: 15.47 + min: 15.110000000000001 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 18.44 + mid: 18.07 + min: 17.7 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 21.57 + mid: 21.16 + min: 20.75 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 25.16 + mid: 24.68 + min: 24.2 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 29.09 + mid: 28.56 + min: 28.029999999999998 + sqrts: + max: null + mid: 200.0 + min: null +- abs_eta: + max: 1.0 + mid: 0.75 + min: 0.5 + pT: + max: 33.5 + mid: 32.9 + min: 32.3 + sqrts: + max: null + mid: 200.0 + min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml index 3f63fe84f9..53df4a3e9c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml @@ -16,10 +16,10 @@ version: 1 version_comment: "Initial implementation" implemented_observables: - - observable: { description: "$A_{LL}$ as function of $p_T$", label: "$A_{LL}$", units: "" } - observable_name: ALL + - observable: { description: "$A_{LL}$ as function of $p_T$, central region", label: "$A_{LL}$", units: "" } + observable_name: CC-ALL process_type: JET_POL - ndata: 22 + ndata: 11 tables: [1] kinematics: variables: @@ -36,10 +36,10 @@ implemented_observables: units: "$GeV$", } abs_eta: {description: "absolute pseudorapidity", label: '$|\eta|$', units: "" } - file: kinematics.yaml - data_central: data.yaml + file: kinematics_CC.yaml + data_central: data_CC.yaml data_uncertainties: - - uncertainties.yaml + - uncertainties_CC.yaml kinematic_coverage: [pT, sqrts, abs_eta] plotting: dataset_label: "STAR 200 GeV (2015) 1-JET $A_{LL}$" @@ -49,6 +49,42 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_1JET_200GEV_ALL-POL - - - STAR_2015_1JET_200GEV_ALL-UNPOL + - - STAR_2015_1JET_200GEV_CC_ALL-POL + - - STAR_2015_1JET_200GEV_CC_ALL-UNPOL + operation: "ratio" + - observable: { description: "$A_{LL}$ as function of $p_T$, forward region", label: "$A_{LL}$", units: "" } + observable_name: CF-ALL + process_type: JET_POL + ndata: 11 + tables: [1] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + abs_eta: {description: "absolute pseudorapidity", label: '$|\eta|$', units: "" } + file: kinematics_CF.yaml + data_central: data_CF.yaml + data_uncertainties: + - uncertainties_CF.yaml + kinematic_coverage: [pT, sqrts, abs_eta] + plotting: + dataset_label: "STAR 200 GeV (2015) 1-JET $A_{LL}$" + kinematics_override: identity + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2015_1JET_200GEV_CF_ALL-POL + - - STAR_2015_1JET_200GEV_CF_ALL-UNPOL operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CC.yaml similarity index 58% rename from nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml rename to nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CC.yaml index 76b929492c..9746ba001b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CC.yaml @@ -570,421 +570,3 @@ bins: sys_33: -2.600280551946243e-07 sys_34: 1.5749262377752516e-07 sys_35: 7.212885582617392e-07 -- lumi: 0.0007 - pol: 1.2810000000000001e-05 - sys_0: -5.723798549241382e-06 - sys_1: 9.519767702735362e-06 - sys_2: -1.27072652067246e-05 - sys_3: 1.644997190275843e-05 - sys_4: 1.9994450624172802e-05 - sys_5: -2.632354840093173e-05 - sys_6: -2.2318871892027695e-05 - sys_7: 3.72398800840353e-05 - sys_8: -4.2630941829004675e-05 - sys_9: -6.057863663567793e-05 - sys_10: -8.001652158350923e-06 - sys_11: -3.2642632373632507e-06 - sys_12: 8.533534195269332e-05 - sys_13: -0.0004277674166870059 - sys_14: -2.7611330881578593e-05 - sys_15: -0.0003390017721095608 - sys_16: -2.0320315927141983e-05 - sys_17: 0.0016407757690328712 - sys_18: 6.098346357525486e-05 - sys_19: 0.00017384758602892485 - sys_20: 4.4973181820176277e-05 - sys_21: 8.909162817025716e-06 - sys_22: -7.934387314981106e-05 - sys_23: 7.1143033483730245e-06 - sys_24: 8.033630691741578e-08 - sys_25: -7.32144473887315e-07 - sys_26: 2.0219124375336923e-07 - sys_27: 6.610808422489686e-07 - sys_28: 1.1275379466447069e-06 - sys_29: 3.4924261898678003e-07 - sys_30: 1.1062164135169474e-06 - sys_31: -1.5133763420764584e-07 - sys_32: -8.053200363789194e-07 - sys_33: -4.90672716722918e-07 - sys_34: -3.1959478982973937e-07 - sys_35: -8.284104652471781e-07 -- lumi: 0.0007 - pol: 5.5509999999999995e-05 - sys_0: -6.372141793123253e-06 - sys_1: 1.0618676135602555e-05 - sys_2: -1.4184286764078104e-05 - sys_3: 1.8479492775187063e-05 - sys_4: 2.2524228215963095e-05 - sys_5: -3.200586916275156e-05 - sys_6: -2.535449986267579e-05 - sys_7: 4.819449988222994e-05 - sys_8: -4.731217279217028e-05 - sys_9: -8.194342606282463e-05 - sys_10: -1.3006684464861885e-05 - sys_11: -7.783888352659517e-06 - sys_12: 0.00010236605803679663 - sys_13: -0.0017634478264169952 - sys_14: 0.00047661673441615286 - sys_15: 0.0005636869641451459 - sys_16: 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-6.142923084134423e-05 - sys_10: -8.016005781452263e-06 - sys_11: -4.379055814367362e-07 - sys_12: 6.0042067767847864e-05 - sys_13: -0.0001544258243380365 - sys_14: -2.624948279754923e-05 - sys_15: -8.257685001356346e-05 - sys_16: -6.823523944042364e-06 - sys_17: 0.00010309186595535929 - sys_18: -4.430814957552775e-05 - sys_19: -0.00023284951937222408 - sys_20: -3.6558144647956635e-05 - sys_21: -1.0640000217201206e-05 - sys_22: 0.0012084629365389152 - sys_23: -0.0001472018537927888 - sys_24: -9.478194068500891e-06 - sys_25: -5.8976779473307215e-06 - sys_26: -6.672500542689159e-06 - sys_27: 1.4990485319285577e-05 - sys_28: 7.644697794243218e-06 - sys_29: -8.624767772046603e-06 - sys_30: -4.5051424677839504e-06 - sys_31: 1.670832174407867e-05 - sys_32: 3.143234575016033e-06 - sys_33: 3.0554846486099124e-05 - sys_34: 4.969212162931906e-05 - sys_35: -1.2327423718436603e-05 -- lumi: 0.0007 - pol: 0.00020313 - sys_0: -9.471336297659553e-06 - sys_1: 1.4274548261633827e-05 - sys_2: 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1.608671528059383e-05 - sys_33: 2.5238598526427057e-05 - sys_34: 3.552091450700702e-05 - sys_35: -1.2398305794429084e-05 -- lumi: 0.0007 - pol: 0.00014518 - sys_0: -1.0025507958493132e-05 - sys_1: 1.5966373432219618e-05 - sys_2: -1.924079064195383e-05 - sys_3: 2.7315971371502272e-05 - sys_4: 3.306810902305761e-05 - sys_5: -4.849656867349004e-05 - sys_6: -3.796582732032685e-05 - sys_7: 7.71146905218416e-05 - sys_8: -6.648827537885452e-05 - sys_9: -0.00011413090947535914 - sys_10: -1.2532934282646395e-05 - sys_11: 1.6788873982441847e-05 - sys_12: 0.00012037927189817972 - sys_13: -0.0006086880450961896 - sys_14: -0.0004888592068557593 - sys_15: -0.0015796572293171637 - sys_16: -8.393610007151296e-05 - sys_17: -0.0004587425971143036 - sys_18: 7.49534296040938e-05 - sys_19: 0.0001516924825687493 - sys_20: -1.359481847705607e-05 - sys_21: -8.254099318243392e-06 - sys_22: -5.0297798240253604e-05 - sys_23: -9.443205439275323e-06 - sys_24: 2.431664895278696e-06 - sys_25: 3.402963792362288e-06 - sys_26: 6.5253797213655835e-06 - sys_27: 7.2716833998160356e-06 - sys_28: -1.167977484149494e-06 - sys_29: -1.732919308587867e-05 - sys_30: -1.897945865857099e-05 - sys_31: 8.882787803886751e-06 - sys_32: 2.1906878292371648e-05 - sys_33: 1.2251701674935625e-05 - sys_34: 6.492627009709344e-06 - sys_35: 2.0707330919804266e-07 -- lumi: 0.0007 - pol: 0.00013054 - sys_0: -1.1173338612528268e-05 - sys_1: 1.961048432764371e-05 - sys_2: -2.6857840121337563e-05 - sys_3: 3.827487028139256e-05 - sys_4: 4.423429497699072e-05 - sys_5: -7.10835135376822e-05 - sys_6: -5.804547432492576e-05 - sys_7: 0.00013099731385319508 - sys_8: -0.00012009894999786713 - sys_9: -0.00024074952266885276 - sys_10: -1.8946634684933544e-05 - sys_11: 0.00026277941797479566 - sys_12: 0.0024898629582047398 - sys_13: 0.00015053920196656382 - sys_14: 9.009166692239752e-05 - sys_15: 5.598923454193317e-05 - sys_16: 6.644410836538592e-07 - sys_17: -3.051011577300578e-05 - sys_18: 1.5909807367107793e-05 - sys_19: 4.394613588449434e-05 - sys_20: -9.703472601878044e-06 - sys_21: -9.375425380699124e-06 - sys_22: -1.573550044196328e-05 - sys_23: -9.354398070085112e-07 - sys_24: 5.202629627946813e-06 - sys_25: 3.978999539442078e-06 - sys_26: -1.5312978144700048e-07 - sys_27: 2.319759788198445e-06 - sys_28: -3.9434812777693575e-07 - sys_29: -1.061196220349803e-05 - sys_30: -1.734587290005614e-05 - sys_31: -1.5872453013705548e-06 - sys_32: 1.6110657786305862e-05 - sys_33: 7.5336045442300225e-06 - sys_34: 2.312309112345567e-07 - sys_35: 1.7638210086536075e-05 -- lumi: 0.0007 - pol: 0.0006960099999999999 - sys_0: -2.0570477258499703e-05 - sys_1: 3.341772185543097e-05 - sys_2: -4.488134242205468e-05 - sys_3: 7.22681155104189e-05 - sys_4: 8.428751847512784e-05 - sys_5: -0.00015035175726757814 - sys_6: -0.00014032270065812076 - sys_7: 0.0004909773533299127 - sys_8: -0.0036733421851369553 - sys_9: 0.00036381342231595585 - sys_10: 1.3348584069672862e-05 - sys_11: -6.974736507622733e-05 - sys_12: -7.371754299826048e-05 - sys_13: 4.047775663451585e-05 - sys_14: 3.4885670181742874e-05 - sys_15: 1.4465339796665258e-05 - sys_16: -3.801663085638533e-06 - sys_17: -8.639701572455416e-06 - sys_18: 4.456353015520969e-06 - sys_19: 1.730238504189686e-05 - sys_20: -4.011759591760285e-06 - sys_21: -3.1631855119091223e-06 - sys_22: -6.185519073959061e-06 - sys_23: 1.245418363665137e-06 - sys_24: 5.294298985790313e-07 - sys_25: 5.266954740378881e-06 - sys_26: -1.726263437096537e-05 - sys_27: 6.187112214650839e-07 - sys_28: -3.8017252558901683e-08 - sys_29: -4.2056012726145e-06 - sys_30: -9.273956450873987e-06 - sys_31: -3.103297218051952e-06 - sys_32: 7.905027522387452e-06 - sys_33: 8.596633620516164e-07 - sys_34: 3.3544762057573375e-06 - sys_35: 2.0748792722128864e-05 -- lumi: 0.0007 - pol: 0.0007490799999999998 - sys_0: -3.9270091634046984e-05 - sys_1: 6.762426798557228e-05 - sys_2: -9.500115401585762e-05 - sys_3: 0.0001662493026874323 - sys_4: 0.00019577391518242832 - sys_5: 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1.150124798434345e-05 -- lumi: 0.0007 - pol: 0.00125477 - sys_0: -0.00012846028769728705 - sys_1: 0.00024121601804400018 - sys_2: -0.00028844090043889206 - sys_3: 0.000780111286063014 - sys_4: 0.009898436613552393 - sys_5: 0.0004935543718898396 - sys_6: 0.00010386817101403044 - sys_7: -9.167202186926916e-05 - sys_8: 2.2582675908010654e-05 - sys_9: 1.7200050606279436e-05 - sys_10: 6.836457209030393e-07 - sys_11: -1.1588837804131314e-05 - sys_12: -6.839193616171013e-06 - sys_13: 6.127247541066035e-06 - sys_14: 4.221107056119776e-06 - sys_15: 1.4035227890297118e-06 - sys_16: 1.1759645112985e-05 - sys_17: -1.3338070869878688e-06 - sys_18: 5.046758544620424e-07 - sys_19: 3.0722205555238464e-06 - sys_20: -3.3134351610932586e-06 - sys_21: 1.5240802137157633e-05 - sys_22: -1.0825592731625422e-06 - sys_23: 3.3108811101596833e-07 - sys_24: -1.1424237646379552e-05 - sys_25: 2.1585670926564683e-06 - sys_26: -1.0711594484378511e-05 - sys_27: 6.34734219026506e-08 - sys_28: 2.293966660774329e-08 - sys_29: -2.5544186962040734e-07 - sys_30: -8.338288303039944e-07 - sys_31: -4.327988593710119e-07 - sys_32: 7.24260008558855e-07 - sys_33: -8.843570008920012e-07 - sys_34: 9.058648750522456e-07 - sys_35: 3.6552706483788882e-06 -- lumi: 0.0007 - pol: 0.00324154 - sys_0: -0.00041642847232082193 - sys_1: 0.001228477045927712 - sys_2: -0.017984095958256955 - sys_3: -0.0007360631397773987 - sys_4: -0.000145079851599146 - sys_5: 0.00012006984608663869 - sys_6: 2.184301540141452e-05 - sys_7: -2.4831690234329294e-05 - sys_8: 5.1918270718514964e-06 - sys_9: 3.84878714877754e-06 - sys_10: 2.576545214332644e-05 - sys_11: -3.4611519334290366e-06 - sys_12: -1.8594916499137197e-06 - sys_13: 2.224770110601432e-06 - sys_14: 6.940063138912486e-07 - sys_15: -7.560076394771358e-07 - sys_16: 2.3530771454710507e-05 - sys_17: -3.7415529231577963e-07 - sys_18: 3.0899986960582473e-09 - sys_19: 1.0943891127096202e-06 - sys_20: -1.6122851571435984e-06 - sys_21: 7.987794880083938e-06 - sys_22: -3.0848608135041213e-07 - sys_23: 1.3706560708502834e-07 - sys_24: -4.0899319930511726e-06 - sys_25: 6.285945057008323e-07 - sys_26: -3.1341958127798396e-06 - sys_27: 1.9851362578434293e-08 - sys_28: 1.5068021914064514e-08 - sys_29: -5.747155554964179e-08 - sys_30: -1.5845632379524562e-07 - sys_31: -6.850732474972011e-08 - sys_32: 1.448615014789753e-07 - sys_33: -2.397396013195239e-07 - sys_34: 2.2429290663413933e-07 - sys_35: 8.388911008785556e-07 -- lumi: 0.0007 - pol: 0.0014127599999999999 - sys_0: -0.03571864759170568 - sys_1: -0.001080992033376142 - sys_2: 0.00018610101689361095 - sys_3: -0.00015040075674074282 - sys_4: -2.6378230907067315e-05 - sys_5: 3.0231889282988006e-05 - sys_6: 2.787184417984091e-06 - sys_7: -4.492274135760221e-06 - sys_8: 9.29962514891808e-07 - sys_9: 3.631478704234014e-07 - sys_10: 2.4865567312126407e-05 - sys_11: -6.746235040401152e-07 - sys_12: -1.4975656378205749e-07 - sys_13: 5.311166437395012e-07 - sys_14: -2.0200150365243552e-08 - sys_15: -5.655524528239408e-07 - sys_16: 1.2381300895363607e-05 - sys_17: -5.287914177308551e-09 - sys_18: -1.6072814892748094e-08 - sys_19: 1.7636828330887583e-07 - sys_20: -3.894465099004591e-07 - sys_21: 1.9267455069348866e-06 - sys_22: -3.821343467030204e-08 - sys_23: 5.381873651840064e-08 - sys_24: -8.879441814499932e-07 - sys_25: 1.4196241157476987e-07 - sys_26: -5.824431659379597e-07 - sys_27: 1.6939561943101997e-09 - sys_28: 8.080215964499047e-10 - sys_29: 4.575466710839537e-10 - sys_30: -9.125797282529653e-09 - sys_31: -1.1001177784459176e-08 - sys_32: 1.4892114042624068e-08 - sys_33: -4.7218640493053443e-08 - sys_34: 2.8007774467043292e-08 - sys_35: 1.3924274174491083e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CF.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CF.yaml new file mode 100644 index 0000000000..7d81bc7c92 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CF.yaml @@ -0,0 +1,572 @@ +definitions: + lumi: + description: luminosity uncertainty + treatment: ADD + type: STAR2015LUMI + pol: + description: beam polarization uncertainty + treatment: MULT + type: STAR2015POL + sys_0: + description: 0 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc0 + sys_1: + description: 1 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc1 + sys_2: + description: 2 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc2 + sys_3: + description: 3 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc3 + sys_4: + description: 4 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc4 + sys_5: + description: 5 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc5 + sys_6: + description: 6 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc6 + sys_7: + description: 7 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc7 + sys_8: + description: 8 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc8 + sys_9: + description: 9 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc9 + sys_10: + description: 10 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc10 + sys_11: + description: 11 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc11 + sys_12: + description: 12 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc12 + sys_13: + description: 13 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc13 + sys_14: + description: 14 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc14 + sys_15: + description: 15 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc15 + sys_16: + description: 16 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc16 + sys_17: + description: 17 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc17 + sys_18: + description: 18 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc18 + sys_19: + description: 19 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc19 + sys_20: + description: 20 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc20 + sys_21: + description: 21 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc21 + sys_22: + description: 22 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc22 + sys_23: + description: 23 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc23 + sys_24: + description: 24 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc24 + sys_25: + description: 25 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc25 + sys_26: + description: 26 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc26 + sys_27: + description: 27 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc27 + sys_28: + description: 28 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc28 + sys_29: + description: 29 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc29 + sys_30: + description: 30 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc30 + sys_31: + description: 31 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc31 + sys_32: + description: 32 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc32 + sys_33: + description: 33 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc33 + sys_34: + description: 34 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc34 + sys_35: + description: 35 artificial correlated statistical + systematics uncertainty + treatment: ADD + type: STAR2015JETunc35 +bins: +- lumi: 0.0007 + pol: 1.2810000000000001e-05 + sys_0: 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-1.5845632379524562e-07 + sys_31: -6.850732474972011e-08 + sys_32: 1.448615014789753e-07 + sys_33: -2.397396013195239e-07 + sys_34: 2.2429290663413933e-07 + sys_35: 8.388911008785556e-07 +- lumi: 0.0007 + pol: 0.0014127599999999999 + sys_0: -0.03571864759170568 + sys_1: -0.001080992033376142 + sys_2: 0.00018610101689361095 + sys_3: -0.00015040075674074282 + sys_4: -2.6378230907067315e-05 + sys_5: 3.0231889282988006e-05 + sys_6: 2.787184417984091e-06 + sys_7: -4.492274135760221e-06 + sys_8: 9.29962514891808e-07 + sys_9: 3.631478704234014e-07 + sys_10: 2.4865567312126407e-05 + sys_11: -6.746235040401152e-07 + sys_12: -1.4975656378205749e-07 + sys_13: 5.311166437395012e-07 + sys_14: -2.0200150365243552e-08 + sys_15: -5.655524528239408e-07 + sys_16: 1.2381300895363607e-05 + sys_17: -5.287914177308551e-09 + sys_18: -1.6072814892748094e-08 + sys_19: 1.7636828330887583e-07 + sys_20: -3.894465099004591e-07 + sys_21: 1.9267455069348866e-06 + sys_22: -3.821343467030204e-08 + sys_23: 5.381873651840064e-08 + sys_24: -8.879441814499932e-07 + sys_25: 1.4196241157476987e-07 + sys_26: -5.824431659379597e-07 + sys_27: 1.6939561943101997e-09 + sys_28: 8.080215964499047e-10 + sys_29: 4.575466710839537e-10 + sys_30: -9.125797282529653e-09 + sys_31: -1.1001177784459176e-08 + sys_32: 1.4892114042624068e-08 + sys_33: -4.7218640493053443e-08 + sys_34: 2.8007774467043292e-08 + sys_35: 1.3924274174491083e-07 From d7f950750c1bd2287e27c7e6babc086393950217 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 18 Jun 2024 15:49:45 +0200 Subject: [PATCH 61/98] fix fktables names --- .../new_commondata/STAR_2009_1JET_200GEV/metadata.yaml | 8 ++++---- .../new_commondata/STAR_2009_2JET_200GEV/metadata.yaml | 6 +++--- .../STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml | 4 ++-- .../new_commondata/STAR_2012_2JET_510GEV/metadata.yaml | 8 ++++---- .../new_commondata/STAR_2013_2JET_510GEV/metadata.yaml | 8 ++++---- .../new_commondata/STAR_2015_1JET_200GEV/metadata.yaml | 8 ++++---- .../STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml | 4 ++-- 7 files changed, 23 insertions(+), 23 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml index 891358614a..c844d16563 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/metadata.yaml @@ -51,8 +51,8 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_1JET_200GEV_CC_ALL-POL - - - STAR_2009_1JET_200GEV_CC_ALL-UNPOL + - - STAR_2009_1JET_200GEV_CC-ALL-POL + - - STAR_2009_1JET_200GEV_CC-ALL-UNPOL operation: "ratio" - observable: { description: "ALL w.r.t. pT, forward region", label: "$A_{LL}$", units: "" } observable_name: CF-ALL @@ -89,6 +89,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_1JET_200GEV_CF_ALL-POL - - - STAR_2009_1JET_200GEV_CF_ALL-UNPOL + - - STAR_2009_1JET_200GEV_CF-ALL-POL + - - STAR_2009_1JET_200GEV_CF-ALL-UNPOL operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml index 74a50745a1..cd27814819 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml @@ -48,7 +48,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_200GEV_A_ALL + - - STAR_2009_2JET_200GEV_A-ALL - observable: { description: "ALL as function of $M_{inv}$, topology B", @@ -81,7 +81,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_200GEV_B_ALL + - - STAR_2009_2JET_200GEV_B-ALL - observable: { description: "ALL as function of $M_{inv}$, topology C", @@ -114,4 +114,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_200GEV_C_ALL \ No newline at end of file + - - STAR_2009_2JET_200GEV_C-ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml index 2393f73207..850913615d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -48,7 +48,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_MIDRAP_200GEV_OS_ALL + - - STAR_2009_2JET_MIDRAP_200GEV_OS-ALL - observable: { description: "ALL as function of $M_{inv}$, SS", @@ -81,4 +81,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_MIDRAP_200GEV_SS_ALL + - - STAR_2009_2JET_MIDRAP_200GEV_SS-ALL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml index cc64232cd0..ad29bd355b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml @@ -39,7 +39,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_A_ALL + - - STAR_2012_2JET_510GEV_A-ALL - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } observable_name: B-ALL process_type: DIJET_POL @@ -62,7 +62,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_B_ALL + - - STAR_2012_2JET_510GEV_B-ALL - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } observable_name: C-ALL process_type: DIJET_POL @@ -85,7 +85,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_C_ALL + - - STAR_2012_2JET_510GEV_C-ALL - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } observable_name: D-ALL process_type: DIJET_POL @@ -108,4 +108,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_D_ALL \ No newline at end of file + - - STAR_2012_2JET_510GEV_D-ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml index e9c6a3be9d..ecbbee323b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml @@ -38,7 +38,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_A_ALL + - - STAR_2013_2JET_510GEV_A-ALL - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } observable_name: B-ALL process_type: DIJET_POL @@ -61,7 +61,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_B_ALL + - - STAR_2013_2JET_510GEV_B-ALL - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } observable_name: C-ALL process_type: DIJET_POL @@ -84,7 +84,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_C_ALL + - - STAR_2013_2JET_510GEV_C-ALL - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } observable_name: D-ALL process_type: DIJET_POL @@ -107,4 +107,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_D_ALL \ No newline at end of file + - - STAR_2013_2JET_510GEV_D-ALL \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml index 53df4a3e9c..897f2f9269 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/metadata.yaml @@ -49,8 +49,8 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_1JET_200GEV_CC_ALL-POL - - - STAR_2015_1JET_200GEV_CC_ALL-UNPOL + - - STAR_2015_1JET_200GEV_CC-ALL-POL + - - STAR_2015_1JET_200GEV_CC-ALL-UNPOL operation: "ratio" - observable: { description: "$A_{LL}$ as function of $p_T$, forward region", label: "$A_{LL}$", units: "" } observable_name: CF-ALL @@ -85,6 +85,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_1JET_200GEV_CF_ALL-POL - - - STAR_2015_1JET_200GEV_CF_ALL-UNPOL + - - STAR_2015_1JET_200GEV_CF-ALL-POL + - - STAR_2015_1JET_200GEV_CF-ALL-UNPOL operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index fdd4d15b76..aa0caa4ff9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -38,7 +38,7 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_510GEV_OS_ALL + - - STAR_2015_2JET_MIDRAP_510GEV_OS-ALL - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", label: "$A_{LL}$", units: "" } observable_name: SS-ALL process_type: DIJET_POL @@ -61,4 +61,4 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_510GEV_SS_ALL \ No newline at end of file + - - STAR_2015_2JET_MIDRAP_510GEV_SS-ALL \ No newline at end of file From aa2c2a736d3716f276e00704b43d0d09ee8543e2 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 18 Jun 2024 16:43:33 +0200 Subject: [PATCH 62/98] fix phenix name --- .../nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml | 3 ++- 1 file changed, 2 insertions(+), 1 deletion(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml index 6f4fdec05e..8e063286d4 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml @@ -50,4 +50,5 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - PHENIX_1JET_200GEV_ALL + - - PHENIX_1JET_200GEV_ALL-POL + - - PHENIX_1JET_200GEV_ALL-UNPOL From b5ff1d5715571b8f8ccdd3c44169092801f6fa82 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 19 Jun 2024 16:47:09 +0200 Subject: [PATCH 63/98] correct PHENIX source table --- .../PHENIX_1JET_200GEV/data.yaml | 2 - .../PHENIX_1JET_200GEV/filter.py | 72 +++++++++---------- .../PHENIX_1JET_200GEV/kinematics.yaml | 24 ------- .../rawdata/{Table_18.yaml => Figure18.yaml} | 2 + .../PHENIX_1JET_200GEV/rawdata/Table4.yaml | 39 ++++++++++ .../PHENIX_1JET_200GEV/uncertainties.yaml | 16 ++--- 6 files changed, 82 insertions(+), 73 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/{Table_18.yaml => Figure18.yaml} (85%) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table4.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml index f690926b67..cd826a98f7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/data.yaml @@ -1,6 +1,4 @@ data_central: -- -0.0007 -- 0.0039 - -0.0014 - -0.0005 - 0.0058 diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py index 60170e44dd..2ab7f0a26d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/filter.py @@ -1,41 +1,39 @@ -import glob - import pandas as pd import yaml POL_UNC = 0.094 -def read_data(fnames): +def read_data(): df = pd.DataFrame() - for fname in fnames: - with open(fname, "r") as file: - data = yaml.safe_load(file) - - pTbsub = data["independent_variables"][0]["values"] - pTsub = data["dependent_variables"][0]["values"] - ALLsub = data["dependent_variables"][1]["values"] - - for i in range(len(ALLsub)): - df = pd.concat( - [ - df, - pd.DataFrame( - { - "pT": [pTsub[i]["value"]], - "pTmin": [pTbsub[i]["low"]], - "pTmax": [pTbsub[i]["high"]], - "eta": [0.0], - "eta_min": [-0.35], - "eta_max": [0.35], - "sqrts": [200], - "ALL": [ALLsub[i]["value"]], - "stat": [ALLsub[i]["errors"][0]["symerror"]], - } - ), - ], - ignore_index=True, - ) + + with open("rawdata/Table4.yaml", "r") as file: + data = yaml.safe_load(file) + + pTbsub = data["independent_variables"][0]["values"] + pTsub = data["dependent_variables"][0]["values"] + ALLsub = data["dependent_variables"][1]["values"] + + for i in range(len(ALLsub)): + df = pd.concat( + [ + df, + pd.DataFrame( + { + "pT": [pTsub[i]["value"]], + "pTmin": [pTbsub[i]["low"]], + "pTmax": [pTbsub[i]["high"]], + "eta": [0.0], + "eta_min": [-0.35], + "eta_max": [0.35], + "sqrts": [200], + "ALL": [ALLsub[i]["value"]], + "stat": [ALLsub[i]["errors"][0]["symerror"]], + } + ), + ], + ignore_index=True, + ) df["pol"] = POL_UNC * abs(df["ALL"]) return df @@ -80,7 +78,11 @@ def write_data(df): error.append(e) error_definition = { - "stat": {"description": "statistical uncertainty", "treatment": "ADD", "type": "UNCORR"}, + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, "pol": { "description": "beam polarization uncertainty", "treatment": "MULT", @@ -95,9 +97,5 @@ def write_data(df): if __name__ == "__main__": - # TODO: Need to generate `observable` cards and corresponding - # pineappl grids and FK tables as the orders have changed!!!! - fnames = glob.glob("rawdata/*.yaml") - nnames = sorted([i for i in fnames]) - df = read_data(nnames) + df = read_data() write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml index 0d4a0e41b3..c66d84ce98 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/kinematics.yaml @@ -1,28 +1,4 @@ bins: -- pT: - min: 2.0 - mid: 2.4 - max: 3.0 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: -0.35 - mid: 0.0 - max: 0.35 -- pT: - min: 3.0 - mid: 3.4 - max: 4.0 - sqrts: - min: null - mid: 200.0 - max: null - eta: - min: -0.35 - mid: 0.0 - max: 0.35 - pT: min: 4.0 mid: 4.4 diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table_18.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Figure18.yaml similarity index 85% rename from nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table_18.yaml rename to nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Figure18.yaml index 5dcc2a6066..acc552a160 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table_18.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Figure18.yaml @@ -1,3 +1,5 @@ +# This table is not correct presumably, as it contains two additional bins not shown in the figure +# and the stat error does not match with Table4 and Figure 18 of the paper. independent_variables: - header: {name: '$p^{reco}_T$ Bins (GeV/$c$)'} values: diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table4.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table4.yaml new file mode 100644 index 0000000000..2742edb4e7 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/rawdata/Table4.yaml @@ -0,0 +1,39 @@ +independent_variables: +# Manually copied from the paper +- header: {name: '$p^{reco}_T$ Bins (GeV/$c$)'} + values: + - {low: 4, high: 5} + - {low: 5, high: 6} + - {low: 6, high: 7} + - {low: 7, high: 8} + - {low: 8, high: 10} + - {low: 10, high: 12} +dependent_variables: +- header: {name: '$$ (GeV/$c$)'} + values: + - value: 4.4 + - value: 5.4 + - value: 6.4 + - value: 7.4 + - value: 8.8 + - value: 10.8 +- header: {name: 'Jet $A_{LL}$'} + values: + - value: -0.0014 + errors: + - {symerror: 0.0037, label: 'stat.'} + - value: -0.0005 + errors: + - {symerror: 0.0059, label: 'stat.'} + - value: 0.0058 + errors: + - {symerror: 0.0089, label: 'stat.'} + - value: 0.0034 + errors: + - {symerror: 0.0132, label: 'stat.'} + - value: 0.0077 + errors: + - {symerror: 0.0152, label: 'stat.'} + - value: -0.0181 + errors: + - {symerror: 0.0282, label: 'stat.'} diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml index 576a619515..c0c3d91ac8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/uncertainties.yaml @@ -8,19 +8,15 @@ definitions: treatment: MULT type: RHIC2005POL bins: -- stat: 7.7e-05 - pol: 6.58e-05 -- stat: 0.00082 - pol: 0.00036659999999999997 -- stat: 0.00052 +- stat: 0.0037 pol: 0.0001316 -- stat: 0.0003 +- stat: 0.0059 pol: 4.7000000000000004e-05 -- stat: 0.0052 +- stat: 0.0089 pol: 0.0005451999999999999 -- stat: 0.0045 +- stat: 0.0132 pol: 0.00031959999999999996 -- stat: 0.012 +- stat: 0.0152 pol: 0.0007238 -- stat: 0.051 +- stat: 0.0282 pol: 0.0017014 From 0c910137bbf5d0efb349446ebb228794b05a3c04 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 19 Jun 2024 17:03:12 +0200 Subject: [PATCH 64/98] add review comments --- .../new_commondata/PHENIX_1JET_200GEV/metadata.yaml | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml index 8e063286d4..e1d7611cc0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV/metadata.yaml @@ -19,8 +19,8 @@ implemented_observables: - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } observable_name: ALL process_type: JET_POL - ndata: 8 - tables: [18] + ndata: 6 + tables: [4] kinematics: variables: pT: @@ -52,3 +52,4 @@ implemented_observables: FK_tables: - - PHENIX_1JET_200GEV_ALL-POL - - PHENIX_1JET_200GEV_ALL-UNPOL + operation: "ratio" \ No newline at end of file From d8b78ece33e26bb5f9859045373e19bc716cb449 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 25 Jun 2024 14:40:32 +0200 Subject: [PATCH 65/98] Revert "Merge branch 'master' into DY_polarized_data" This reverts commit 8f50df7aff28666df0f77e56e57d54bec3374216, reversing changes made to cb04dee169ea0a7d0e6d1a7d4a0260a846ab2be0. --- doc/sphinx/source/n3fit/runcard_detailed.rst | 63 +- extra_tests/regression_fits/central_16.json | 23 +- .../regression_fits/diagonal_45.exportgrid | 1152 +++--- extra_tests/regression_fits/diagonal_45.json | 49 +- .../feature_scaling_81.exportgrid | 1166 +++--- .../regression_fits/feature_scaling_81.json | 49 +- .../regression_fits/flavour_29.exportgrid | 1164 +++--- extra_tests/regression_fits/flavour_29.json | 53 +- .../regression_fits/no_csr_613.exportgrid | 1170 +++--- extra_tests/regression_fits/no_csr_613.json | 49 +- .../regression_fits/no_lagrange_27.json | 23 +- .../regression_fits/no_msr_92.exportgrid | 1160 +++--- extra_tests/regression_fits/no_msr_92.json | 49 +- .../regression_fits/no_sumrules_18.exportgrid | 1166 +++--- .../regression_fits/no_sumrules_18.json | 49 +- .../regression_fits/no_vsr_54.exportgrid | 1148 +++--- extra_tests/regression_fits/no_vsr_54.json | 49 +- .../regression_fits/normal_fit_72.exportgrid | 1136 +++--- .../regression_fits/normal_fit_72.json | 53 +- .../polarized_evol_34.exportgrid | 784 ++-- .../regression_fits/polarized_evol_34.json | 47 +- .../regression_fits/single_dense_316.json | 23 +- .../regression_fits/trainable_prepro.yml | 3 - .../regression_fits/trainable_prepro_61.json | 23 +- n3fit/runcards/examples/Basic_runcard.yml | 6 - n3fit/runcards/examples/nnpdf40-like.yml | 5 +- .../hyperopt_studies/renew_hyperopt.yml | 3 + ...restricted_search_space_renew_hyperopt.yml | 3 + .../n3fit/backends/keras_backend/MetaLayer.py | 4 +- .../n3fit/backends/keras_backend/MetaModel.py | 4 +- .../backends/keras_backend/base_layers.py | 7 +- .../backends/keras_backend/multi_dense.py | 10 +- .../backends/keras_backend/operations.py | 13 +- n3fit/src/n3fit/checks.py | 2 +- n3fit/src/n3fit/hyper_optimization/rewards.py | 10 +- n3fit/src/n3fit/layers/mask.py | 5 +- n3fit/src/n3fit/model_gen.py | 41 +- n3fit/src/n3fit/model_trainer.py | 2 +- n3fit/src/n3fit/msr.py | 4 +- n3fit/src/n3fit/n3fit_checks_provider.py | 1 + n3fit/src/n3fit/scripts/n3fit_exec.py | 2 +- .../regressions/quickcard-sequential.yml | 2 - .../src/n3fit/tests/regressions/quickcard.yml | 2 - .../n3fit/tests/regressions/quickcard_pol.yml | 2 - .../n3fit/tests/regressions/quickcard_qed.yml | 2 - n3fit/src/n3fit/tests/test_multireplica.py | 4 +- n3fit/src/n3fit/tests/test_preprocessing.py | 2 +- nnpdf_data/nnpdf_data/filter_utils/utils.py | 364 +- .../ATLAS_1JET_13TEV_DIF/filter.py | 2 +- .../ATLAS_2JET_13TEV_DIF/filter.py | 2 +- .../ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py | 48 +- 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.../H1_1JET_319GEV_290PB-1_DIF/artUnc.py | 4 +- .../H1_1JET_319GEV_290PB-1_DIF/filter.py | 4 +- .../H1_1JET_319GEV_351PB-1_DIF/filter.py | 2 +- .../H1_1JET_319GEV_351PB-1_DIF/manual_impl.py | 3584 +---------------- .../H1_2JET_319GEV_290PB-1_DIF/artUnc.py | 4 +- .../H1_2JET_319GEV_290PB-1_DIF/filter.py | 4 +- .../H1_2JET_319GEV_351PB-1_DIF/filter.py | 2 +- .../H1_2JET_319GEV_351PB-1_DIF/manual_impl.py | 3584 +---------------- .../LHCB_DY_7TEV_MUON/filter.py | 2 +- .../LHCB_DY_8TEV_MUON/filter.py | 2 +- .../LHCB_WPWM_7TEV_MUON/filter.py | 2 +- .../LHCB_WPWM_8TEV_MUON/filter.py | 2 +- .../new_commondata/LHCB_Z0_13TEV/filter.py | 2 +- .../LHCB_Z0_7TEV_DIELECTRON/filter.py | 5 +- .../LHCB_Z0_7TEV_MUON/filter.py | 2 +- .../LHCB_Z0_8TEV_DIELECTRON/filter.py | 2 +- .../LHCB_Z0_8TEV_MUON/filter.py | 2 +- .../NNPDF_INTEG_1GEV/metadata.yaml | 8 +- .../kinematics_F2C-17PTS.yaml | 136 +- .../kinematics_F2C-CCE-17PTS.yaml | 136 +- .../kinematics_F2C-CCP-17PTS.yaml | 136 +- .../NNPDF_POS_2P24GEV/kinematics_F2C.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_F2D.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_F2S.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_F2U.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XCQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XDB.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XDQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XGL.yaml | 162 +- .../NNPDF_POS_2P24GEV/kinematics_XSB.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XSQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XUB.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XUQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/metadata.yaml | 393 +- .../ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py | 2 +- .../ZEUS_1JET_319GEV_82PB-1_DIF/filter.py | 2 +- .../ZEUS_2JET_319GEV_374PB-1_DIF/filter.py | 2 +- .../nnpdf_data/theory_cards/40002000.yaml | 47 - .../nnpdf_data/theory_cards/40002001.yaml | 47 - .../nnpdf_data/theory_cards/40002002.yaml | 47 - .../nnpdf_data/theory_cards/40002003.yaml | 47 - .../nnpdf_data/theory_cards/40002004.yaml | 47 - .../nnpdf_data/theory_cards/40002006.yaml | 47 - .../nnpdf_data/theory_cards/40002007.yaml | 47 - .../nnpdf_data/theory_cards/40002008.yaml | 47 - .../nnpdf_data/theory_cards/40002009.yaml | 47 - .../nnpdf_data/theory_cards/40002010.yaml | 47 - .../nnpdf_data/theory_cards/40002011.yaml | 47 - .../nnpdf_data/theory_cards/40002012.yaml | 47 - .../nnpdf_data/theory_cards/40002013.yaml | 47 - nnpdf_data/nnpdf_data/theory_cards/722.yaml | 67 +- nnpdf_data/nnpdf_data/theory_cards/723.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/724.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/725.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/726.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/727.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/728.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/729.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/730.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/731.yaml | 80 +- 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32 +- validphys2/src/validphys/loader.py | 64 +- validphys2/src/validphys/process_options.py | 9 +- validphys2/src/validphys/pseudodata.py | 24 +- .../regressions/test_art_rep_generation.csv | 532 +-- .../tests/regressions/test_mcreplica.csv | 532 +-- .../validphys/tests/test_commondataparser.py | 11 +- .../validphys/tests/test_overfit_metric.py | 1 - .../src/validphys/tests/test_pseudodata.py | 2 +- .../src/validphys/tests/test_pyfkdata.py | 4 +- .../theorycovariance/theorycovarianceutils.py | 17 +- validphys2/src/validphys/uploadutils.py | 7 +- 202 files changed, 10764 insertions(+), 18430 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002000.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002001.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002002.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002003.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002004.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002006.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002007.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002008.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002009.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002010.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002011.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002012.yaml delete mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002013.yaml diff --git a/doc/sphinx/source/n3fit/runcard_detailed.rst b/doc/sphinx/source/n3fit/runcard_detailed.rst index a498e7d84d..8f31d98af0 100644 --- a/doc/sphinx/source/n3fit/runcard_detailed.rst +++ b/doc/sphinx/source/n3fit/runcard_detailed.rst @@ -30,7 +30,7 @@ The first thing one finds when building a fit runcard for - { dataset: NMCPD_dw, frac: 0.5 } - { dataset: ATLASZPT8TEVMDIST, frac: 0.75, sys: 10, cfac: [QCD] } - + The `dataset_inputs` key contains a list of dictionaries defining the datasets to be used in the fit as well as their options (which are detailed in :ref:`datasetspec-core-label`). @@ -42,7 +42,7 @@ The fraction of events that are considered for the training and validation sets dataset_inputs: - { dataset: SLACP_dwsh, frac: 0.75} - + It is possible to run a fit with no validation set by setting the fraction to ``1.0``, in this case the training set will be used as validation set. The random seed for the training/validation split is defined by the variable ``trvlseed``. @@ -54,7 +54,7 @@ to fix it such that it is the same for all replicas with ``same_trvl_per_replica trvlseed: 7 same_trvl_per_replica: true - + .. _preprocessing-label: @@ -92,26 +92,26 @@ Setting the ``trainable`` flag to ``False`` is equivalent to recovering the old - { fl: t8, smallx: [0.56,1.29], largex: [1.45,3.03] } - { fl: cp, smallx: [0.12,1.19], largex: [1.83,6.70] } -It is important to determine the correct values for the ``largex`` and ``smallx`` preprocessing -ranges. For example setting a poor range for those parameters can result in a conflict with the -:ref:`positivity ` or :ref:`integrability ` constraints, making it such -that no replicas can satisfy those constraints. In most cases when changes are made to a runcard, -they will have a relatively small effect on the required preprocessing ranges. This includes common -variations to runcards such as changing the datasets, or settings related to the training of the -neural network. In these cases :ref:`running an iterated fit ` is likely the +It is important to determine the correct values for the ``largex`` and ``smallx`` preprocessing +ranges. For example setting a poor range for those parameters can result in a conflict with the +:ref:`positivity ` or :ref:`integrability ` constraints, making it such +that no replicas can satisfy those constraints. In most cases when changes are made to a runcard, +they will have a relatively small effect on the required preprocessing ranges. This includes common +variations to runcards such as changing the datasets, or settings related to the training of the +neural network. In these cases :ref:`running an iterated fit ` is likely the easiest way to obtain a satisfactory range of the preprocessing. However, in some cases, such as for -example a change of PDF basis where the preprocessing ranges obtain a different meaning entirely, -we don't know what a good starting point for the ranges would be. One way to identify good ranges -is by opening up the ``smallx`` and ``large`` parameters for large ranges and setting -``trainable: True``. This way the preprocessing exponents will be considered part of the free +example a change of PDF basis where the preprocessing ranges obtain a different meaning entirely, +we don't know what a good starting point for the ranges would be. One way to identify good ranges +is by opening up the ``smallx`` and ``large`` parameters for large ranges and setting +``trainable: True``. This way the preprocessing exponents will be considered part of the free parameters of the model, and as such they will be fitted by the optimization algorithm. -NNPDF4.0 fits are run with ``trainable: False``, because trainable preprocessing exponents can lead +NNPDF4.0 fits are run with ``trainable: False``, because trainable preprocessing exponents can lead to an underestimation of the PDF uncertainties in the extrapolation domain. So after determining a -reasonable range for the preprocessing exponents, a new runcard should be generated using -``vp-nextfitruncard`` as explained in :ref:_run-iterated-fit. In this runcard one should then -manually set ``trainable: False`` for all preprocessing exponents before running the iterated fit. -It can take more than one iteration before the iterated fits have converged to stable values for the +reasonable range for the preprocessing exponents, a new runcard should be generated using +``vp-nextfitruncard`` as explained in :ref:_run-iterated-fit. In this runcard one should then +manually set ``trainable: False`` for all preprocessing exponents before running the iterated fit. +It can take more than one iteration before the iterated fits have converged to stable values for the preprocessing ranges. Note that the script ``vp-nextfitruncard`` automatically enforces some constraints @@ -160,7 +160,7 @@ In this case the ``nodes_per_layer`` parameter represents the nodes each one of - **One network per flavour** (``layer_type: dense_per_flavour``): -This mode is designed to behave as the methodology for NNPDF before 3.1 where each flavour has a separated identical network. +This mode is designed to behave as the methodology for NNPDF before 3.1 where each flavour has a separated identical network. In this case the ``nodes_per_layer`` parameter represents the nodes each layer of each flavour has. For instance ``[5, 3, 8]`` means that the first step is a list of 8 layers of shape ``(2x5)``, while the second layer is again a list that matches the previous one (i.e., 8 layers) with layers of shape ``(5x3)`` while the last layer has two task. The output of each layer should be one single element (i.e., 8 ``(3x1)`` layers) and then concatenate them all so that the final output of the neural network will be a 8-elements tensor. A report comparing the ``dense`` and ``dense_per_flavour`` architectures can be found `here `_ @@ -219,7 +219,7 @@ Note that by defining the positivity in this way all datasets will share the sam It is also possible to not define the positivity hyperparameters (or define them only partially). In this case ``n3fit`` will set the initial Lagrange multiplier as ``initial`` (default: 1.0) -while the ``multiplier`` will be such that after the last epoch the final Lagrange multiplier +while the ``multiplier`` will be such that after the last epoch the final Lagrange multiplier equals the ``maxlambda`` defined for the dataset. Finally we have the positivity threshold, which is set to ``1e-6`` by default. @@ -233,11 +233,11 @@ this value, it will be tagged as ``POS_VETO`` and the replica removed from postf Integrability ------------- -Integrability in ``n3fit`` is enforced through a Lagrange multiplier, this is -the same basic concept as how positivity is enforced, and therefore the -input in the runcard is analogous to the case of positivity where one can -apply the integrability contraints through an optional ``integrability`` -dictionary as (not that as opposed to positivity, for integrability no +Integrability in ``n3fit`` is enforced through a Lagrange multiplier, this is +the same basic concept as how positivity is enforced, and therefore the +input in the runcard is analogous to the case of positivity where one can +apply the integrability contraints through an optional ``integrability`` +dictionary as (not that as opposed to positivity, for integrability no threshold value can be set): .. code-block:: yaml @@ -307,7 +307,7 @@ Logging details will include the value of the loss for each experiment over time the values of the weights of the NN, as well as a detailed analysis of the amount of time that TensorFlow spent on each operation. - + .. _parallel-label: Running fits in parallel @@ -325,8 +325,8 @@ this can be done with the `same_trvl_per_replica: true` runcard flag. In other words, in order to run several replicas in parallel in a machine (be it a big CPU or, most likely, a GPU) -it is necessary to modify the ``n3fit`` runcard by adding the following -top-level option: +it is necessary to modify the ``n3fit`` runcard by adding the following two +top-level options: .. code-block:: yaml @@ -337,7 +337,7 @@ And then run ``n3fit`` with a replica range to be parallelized (in this case from replica 1 to replica 4). .. code-block:: bash - + n3fit runcard.yml 1 -r 4 @@ -412,7 +412,8 @@ It is however possible to disable them by setting to false the ``sum_rules`` fla fitting: sum_rules: False - + It is also possible to impose just the valence or the momentum sum rules by using the ``VSR`` or ``MSR`` flags, respectively (``True`` is equal to ``All``). + diff --git a/extra_tests/regression_fits/central_16.json b/extra_tests/regression_fits/central_16.json index 6f2b9a68d7..39aa4f3cb3 100644 --- a/extra_tests/regression_fits/central_16.json +++ b/extra_tests/regression_fits/central_16.json @@ -71,25 +71,24 @@ ], "timing": { "walltime": { - "Total": 30.10047173500061, + "Total": 32.32825946807861, "start": 0.0, - "replica_set": 0.23421192169189453, - "replica_fitted": 30.100268602371216, - "replica_set_to_replica_fitted": 29.86605668067932 + "replica_set": 0.23800349235534668, + "replica_fitted": 32.32805871963501, + "replica_set_to_replica_fitted": 32.09005522727966 }, "cputime": { - "Total": 31.299373692000003, + "Total": 33.586156003, "start": 0.0, - "replica_set": 0.23228165799999978, - "replica_fitted": 31.299169341000002, - "replica_set_to_replica_fitted": 31.066887683000004 + "replica_set": 0.23583456399999925, + "replica_fitted": 33.585950811000004, + "replica_set_to_replica_fitted": 33.350116247 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/extra_tests/regression_fits/diagonal_45.exportgrid b/extra_tests/regression_fits/diagonal_45.exportgrid index 5bd55b2930..6d7218a619 100644 --- a/extra_tests/regression_fits/diagonal_45.exportgrid +++ b/extra_tests/regression_fits/diagonal_45.exportgrid @@ -1,590 +1,590 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -2.3768625259399414, 0.12396714091300964, 0.09738776087760925, 0.09743490070104599, - -15.360136985778809, 0.09758570790290833, 0.09754002839326859, 0.12372471392154694, - -2.3768625259399414, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.3018877506256104, 0.12483062595129013, 0.09718649834394455, 0.09724009782075882, - -15.36788558959961, 0.09740681946277618, 0.09735500067472458, 0.12456463277339935, - -2.301887273788452, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.2292845249176025, 0.1259201318025589, 0.09716733545064926, 0.0972282886505127, 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"replica_set_to_replica_fitted": 32.054713582 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/extra_tests/regression_fits/feature_scaling_81.exportgrid b/extra_tests/regression_fits/feature_scaling_81.exportgrid index 2f907ee9c1..bacc8df354 100644 --- a/extra_tests/regression_fits/feature_scaling_81.exportgrid +++ b/extra_tests/regression_fits/feature_scaling_81.exportgrid @@ -1,593 +1,593 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, 0.9970365762710571, 0.4224916696548462, 0.4242970049381256, 0.4242972135543823, - 0.06217101961374283, 0.42431578040122986, 0.4243162274360657, 0.42282170057296753, - 0.9970365762710571, 0.0, 0.0, 0.0] -- [0.0, 0.0, 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+ "erf_vl": 5.384581089019775, + "chi2": 3.8961896896362305, "pos_state": "POS_PASS", "arc_lengths": [ - 1.1047281554636061, - 1.2121893672897062, - 0.9906464941994304, - 0.9904916213693944, - 0.9907080935720707 + 1.1046909732525076, + 1.2122390889491175, + 0.9906464905279492, + 0.9904917309060217, + 0.9907080519677236 ], "integrability": [ - 0.4676448851823809, - 0.46764488518238057, - 0.0809117034077646, - 0.10038173198699943, - 0.5176680386066439 + 0.46764427423477195, + 0.4676442742347716, + 0.08089738525450241, + 0.1000113487243652, + 0.5176690220832826 ], "timing": { "walltime": { - "Total": 8.016386985778809, + "Total": 7.731718301773071, "start": 0.0, - "replica_set": 0.22813057899475098, - "replica_fitted": 8.016170024871826, - "replica_set_to_replica_fitted": 7.788039445877075 + "replica_set": 0.2266373634338379, + "replica_fitted": 7.731366872787476, + "replica_set_to_replica_fitted": 7.504729509353638 }, "cputime": { - "Total": 8.175631554, + "Total": 7.901237213, "start": 0.0, - "replica_set": 0.22713051000000029, - "replica_fitted": 8.175411814, - "replica_set_to_replica_fitted": 7.948281304 + "replica_set": 0.22565210800000024, + "replica_fitted": 7.900883664, + "replica_set_to_replica_fitted": 7.675231556 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/extra_tests/regression_fits/no_csr_613.exportgrid b/extra_tests/regression_fits/no_csr_613.exportgrid index daca363077..df82f2f8c5 100644 --- a/extra_tests/regression_fits/no_csr_613.exportgrid +++ b/extra_tests/regression_fits/no_csr_613.exportgrid @@ -1,590 +1,590 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -1.4231513738632202, 1.0134621858596802, 1.0247423648834229, 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a/extra_tests/regression_fits/no_msr_92.exportgrid +++ b/extra_tests/regression_fits/no_msr_92.exportgrid @@ -1,590 +1,590 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -2.4362943172454834, 0.49421271681785583, 0.46692922711372375, 0.4669736623764038, - -0.534435510635376, 0.46713539958000183, 0.467092365026474, 0.4939541518688202, - -2.4362943172454834, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.3590054512023926, 0.484237939119339, 0.4558606445789337, 0.45591118931770325, - -0.5343948006629944, 0.4560900926589966, 0.45604121685028076, 0.48395437002182007, - -2.3590054512023926, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.2841835021972656, 0.47482994198799133, 0.4453137516975403, 0.44537121057510376, - -0.5342838764190674, 0.4455690085887909, 0.4455135762691498, 0.47451889514923096, - -2.2841835021972656, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.2117512226104736, 0.4659785032272339, 0.43527624011039734, 0.4353415369987488, - -0.5340979099273682, 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0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] q20: 2.7224999999999997 replica: 92 diff --git a/extra_tests/regression_fits/no_msr_92.json b/extra_tests/regression_fits/no_msr_92.json index 97d5db7d15..bd743bd266 100644 --- a/extra_tests/regression_fits/no_msr_92.json +++ b/extra_tests/regression_fits/no_msr_92.json @@ -51,45 +51,44 @@ ], "stop_epoch": 1100, "best_epoch": 1099, - "erf_tr": 5.661350727081299, - "erf_vl": 5.671205043792725, - "chi2": 3.3254096508026123, + "erf_tr": 6.576594829559326, + "erf_vl": 5.858449935913086, + "chi2": 3.3300018310546875, "pos_state": "POS_PASS", "arc_lengths": [ - 1.3377684868747033, - 0.9939545216245528, - 1.1826499004778586, - 1.0015656903069137, - 1.1694081596657295 + 1.3370216319814459, + 0.9939697402767997, + 1.179148683250488, + 1.0013385209813972, + 1.175109752177304 ], "integrability": [ - 0.0009784702342583926, - 0.0009784702342586354, - 4.6017493104885676e-05, - 0.47618312388658507, - 0.007452807622030058 + 0.0009919884832926065, + 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100644 --- a/extra_tests/regression_fits/no_sumrules_18.json +++ b/extra_tests/regression_fits/no_sumrules_18.json @@ -51,45 +51,44 @@ ], "stop_epoch": 1100, "best_epoch": 1099, - "erf_tr": 5.234591484069824, - "erf_vl": 5.933958530426025, - "chi2": 3.2721149921417236, + "erf_tr": 5.30379056930542, + "erf_vl": 5.399439811706543, + "chi2": 3.260406017303467, "pos_state": "POS_PASS", "arc_lengths": [ - 1.3377847418174296, - 0.9938499771604175, - 1.0016840281484805, - 0.9905686298415103, - 1.0071484675459588 + 1.334838142106021, + 0.9938354360870493, + 1.0016686497444203, + 0.9905760062030213, + 1.0071507527276173 ], "integrability": [ - 0.00022827064094605581, - 0.00022827064094606275, - 1.0907395562656519e-05, - 0.47761861234903324, - 0.001831851579481382 + 0.00022732434808868385, + 0.00022732434808868385, + 1.0915414264803247e-05, + 0.47721657902002323, + 0.001817994620068597 ], "timing": { "walltime": { - "Total": 36.43538308143616, + "Total": 41.40428566932678, "start": 0.0, - "replica_set": 0.239013671875, - "replica_fitted": 36.43523669242859, - "replica_set_to_replica_fitted": 36.19622302055359 + "replica_set": 0.2421131134033203, + "replica_fitted": 41.40400695800781, + "replica_set_to_replica_fitted": 41.16189384460449 }, "cputime": { - "Total": 37.53883287, + "Total": 42.813383816, "start": 0.0, - "replica_set": 0.23726900299999976, - "replica_fitted": 37.538684784, - "replica_set_to_replica_fitted": 37.301415781 + "replica_set": 0.24098446600000045, + "replica_fitted": 42.813101980999996, + "replica_set_to_replica_fitted": 42.572117514999995 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/extra_tests/regression_fits/no_vsr_54.exportgrid b/extra_tests/regression_fits/no_vsr_54.exportgrid index d07089ddac..1a70c0d7de 100644 --- a/extra_tests/regression_fits/no_vsr_54.exportgrid +++ b/extra_tests/regression_fits/no_vsr_54.exportgrid @@ -1,590 +1,590 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -2.3508851528167725, 0.2019844502210617, 0.17533043026924133, 0.17537681758403778, - -16.43580436706543, 0.17541448771953583, 0.17536841332912445, 0.20192338526248932, - -2.3508851528167725, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.276609182357788, 0.2007421851158142, 0.1730288565158844, 0.17308156192302704, - -16.444120407104492, 0.17312322556972504, 0.17307090759277344, 0.20067520439624786, - -2.276609182357788, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.204685926437378, 0.19979439675807953, 0.1709788739681244, 0.17103877663612366, - -16.450881958007812, 0.17108483612537384, 0.17102545499801636, 0.19972087442874908, - -2.204685926437378, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.1350412368774414, 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41.631252642, + "replica_set_to_replica_fitted": 41.403256988 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/extra_tests/regression_fits/polarized_evol_34.exportgrid b/extra_tests/regression_fits/polarized_evol_34.exportgrid index 9a6961eb76..b0228e9f06 100644 --- a/extra_tests/regression_fits/polarized_evol_34.exportgrid +++ b/extra_tests/regression_fits/polarized_evol_34.exportgrid @@ -1,587 +1,583 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, 0.0, -0.18479739129543304, -0.18503735959529877, -0.18503735959529877, - -0.7364077568054199, -0.18503735959529877, -0.18503735959529877, -0.18479739129543304, +- [0.0, 0.0, 0.0, -0.10375979542732239, -0.10418701171875, 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+ -9.289818990509957e-05, 4.030536729260348e-05, 0.0015093344263732433, 3.359601032570936e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -0.00011214185360586271, 0.0025346805341541767, -0.00013386945647653192, - -0.00021137770090717822, -0.00013386945647653192, 0.0025346805341541767, -0.00011214185360586271, +- [0.0, 0.0, 0.0, 4.818113302462734e-05, 0.001176935387775302, 5.615298869088292e-05, + -6.642034713877365e-05, 5.615298869088292e-05, 0.001176935387775302, 4.818113302462734e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -6.997808668529615e-05, 0.002079180907458067, -8.93738106242381e-05, - -0.0001615692744962871, -8.93738106242381e-05, 0.002079180907458067, -6.997808668529615e-05, +- [0.0, 0.0, 0.0, 5.640164090436883e-05, 0.0008971710922196507, 6.487464270321652e-05, + -4.605400681612082e-05, 6.487464270321652e-05, 0.0008971710922196507, 5.640164090436883e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -3.5751054383581504e-05, 0.0016815672861412168, -5.2847190090687945e-05, - -0.00012122292537242174, -5.2847190090687945e-05, 0.0016815672861412168, -3.5751054383581504e-05, +- [0.0, 0.0, 0.0, 5.907891318202019e-05, 0.0006655191536992788, 6.745915743522346e-05, + -3.0761824746150523e-05, 6.745915743522346e-05, 0.0006655191536992788, 5.907891318202019e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -9.042513738677371e-06, 0.001337762805633247, -2.3656890334677882e-05, - -8.89973744051531e-05, -2.3656890334677882e-05, 0.001337762805633247, -9.042513738677371e-06, +- [0.0, 0.0, 0.0, 5.712369238608517e-05, 0.0004774775879923254, 6.493427645182237e-05, + -1.9616374629549682e-05, 6.493427645182237e-05, 0.0004774775879923254, 5.712369238608517e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 1.0682300853659399e-05, 0.0010438387980684638, -1.2417168591127847e-06, - -6.368313188431785e-05, -1.2417168591127847e-06, 0.0010438387980684638, 1.0682300853659399e-05, +- [0.0, 0.0, 0.0, 5.152165613253601e-05, 0.0003285413549747318, 5.838176002725959e-05, + -1.1792317309300415e-05, 5.838176002725959e-05, 0.0003285413549747318, 5.152165613253601e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 2.4065420802799053e-05, 0.0007959528011269867, 1.4940546861907933e-05, - -4.4190019252710044e-05, 1.4940546861907933e-05, 0.0007959528011269867, 2.4065420802799053e-05, +- [0.0, 0.0, 0.0, 4.331897071097046e-05, 0.0002141948789358139, 4.8946971219265833e-05, + -6.56032307233545e-06, 4.8946971219265833e-05, 0.0002141948789358139, 4.331897071097046e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 3.1842464522924274e-05, 0.0005903124692849815, 2.545257484598551e-05, - -2.953799776150845e-05, 2.545257484598551e-05, 0.0005903124692849815, 3.1842464522924274e-05, +- [0.0, 0.0, 0.0, 3.360482878633775e-05, 0.00012989896640647203, 3.7837718991795555e-05, + -3.2820951219036942e-06, 3.7837718991795555e-05, 0.00012989896640647203, 3.360482878633775e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 3.4832115488825366e-05, 0.0004231349448673427, 3.0915121897123754e-05, - -1.8848557374440134e-05, 3.0915121897123754e-05, 0.0004231349448673427, 3.4832115488825366e-05, +- [0.0, 0.0, 0.0, 2.3491662432206795e-05, 7.109759462764487e-05, 2.6312056434107944e-05, + -1.4074875025471556e-06, 2.6312056434107944e-05, 7.109759462764487e-05, 2.3491662432206795e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 3.392253347556107e-05, 0.00029060710221529007, 3.203889718861319e-05, - -1.1337729119986761e-05, 3.203889718861319e-05, 0.00029060710221529007, 3.392253347556107e-05, +- [0.0, 0.0, 0.0, 1.4088440366322175e-05, 3.3226398954866454e-05, 1.5646359315724112e-05, + -4.728907185835851e-07, 1.5646359315724112e-05, 3.3226398954866454e-05, 1.4088440366322175e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 3.0058350603212602e-05, 0.00018886571342591196, 2.9644339520018548e-05, - -6.310981461865595e-06, 2.9644339520018548e-05, 0.00018886571342591196, 3.0058350603212602e-05, +- [0.0, 0.0, 0.0, 6.461486464104382e-06, 1.1738436114683282e-05, 7.074640961945988e-06, + -1.0173076248065627e-07, 7.074640961945988e-06, 1.1738436114683282e-05, 6.461486464104382e-06, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 2.4225962988566607e-05, 0.00011397439084248617, 2.467361446178984e-05, - -3.1589656828145962e-06, 2.467361446178984e-05, 0.00011397439084248617, 2.4225962988566607e-05, - 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 1.743573375279084e-05, 6.192106229718775e-05, 1.818700366129633e-05, - -1.355306380901311e-06, 1.818700366129633e-05, 6.192106229718775e-05, 1.743573375279084e-05, - 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 1.0700179700506851e-05, 2.8622565878322348e-05, 1.13408777906443e-05, - -4.555448072096624e-07, 1.13408777906443e-05, 2.8622565878322348e-05, 1.0700179700506851e-05, - 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 5.000708824809408e-06, 9.94933634501649e-06, 5.334441539162071e-06, - -9.803432732269357e-08, 5.334441539162071e-06, 9.94933634501649e-06, 5.000708824809408e-06, - 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 1.2279158454475692e-06, 1.7719224842949188e-06, 1.2988150501769269e-06, - -7.095271481460941e-09, 1.2988150501769269e-06, 1.7719224842949188e-06, 1.2279158454475692e-06, +- [0.0, 0.0, 0.0, 1.5614931498930673e-06, 2.141876848327229e-06, 1.666849925641145e-06, + -7.360528631039642e-09, 1.666849925641145e-06, 2.141876848327229e-06, 1.5614931498930673e-06, 0.0, 0.0, 0.0, 0.0] - [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] q20: 1.0 diff --git a/extra_tests/regression_fits/polarized_evol_34.json b/extra_tests/regression_fits/polarized_evol_34.json index 1165450546..c185258ef1 100644 --- a/extra_tests/regression_fits/polarized_evol_34.json +++ b/extra_tests/regression_fits/polarized_evol_34.json @@ -25,47 +25,46 @@ "trainable": false } ], - "stop_epoch": 466, - "best_epoch": 354, - "erf_tr": 1.1801773309707642, - "erf_vl": 2.664975166320801, - "chi2": 1.2875453233718872, + "stop_epoch": 435, + "best_epoch": 323, + "erf_tr": 1.2238341569900513, + "erf_vl": 3.0599794387817383, + "chi2": 1.109000325202942, "pos_state": "POS_PASS", "arc_lengths": [ - 1.0365227251310736, - 1.0125186351030275, + 1.0326780832672715, + 1.014154549694492, 0.9899487587939698, 0.9899487587939698, 0.9899487587939698 ], "integrability": [ - 1.3183898417423734e-16, - 4.85722573273506e-17, - 4.85722573273506e-17, - 0.004581765737384488, - 2.0816681711721685e-16 + 1.0061396160665481e-16, + 1.734723475976807e-17, + 3.122502256758253e-17, + 0.008682500803843137, + 7.979727989493313e-17 ], "timing": { "walltime": { - "Total": 16.877962350845337, + "Total": 18.630010843276978, "start": 0.0, - "replica_set": 0.2315657138824463, - "replica_fitted": 16.87779140472412, - "replica_set_to_replica_fitted": 16.646225690841675 + "replica_set": 0.249741792678833, + "replica_fitted": 18.62974452972412, + "replica_set_to_replica_fitted": 18.380002737045288 }, "cputime": { - "Total": 17.490882718, + "Total": 19.099821179000003, "start": 0.0, - "replica_set": 0.2302778019999998, - "replica_fitted": 17.490709896, - "replica_set_to_replica_fitted": 17.260432094000002 + "replica_set": 0.24700718099999985, + "replica_fitted": 19.099551677, + "replica_set_to_replica_fitted": 18.852544496 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/extra_tests/regression_fits/single_dense_316.json b/extra_tests/regression_fits/single_dense_316.json index fee541f314..97bad55b75 100644 --- a/extra_tests/regression_fits/single_dense_316.json +++ b/extra_tests/regression_fits/single_dense_316.json @@ -71,25 +71,24 @@ ], "timing": { "walltime": { - "Total": 30.10720419883728, + "Total": 34.44913601875305, "start": 0.0, - "replica_set": 0.23196172714233398, - "replica_fitted": 30.106998682022095, - "replica_set_to_replica_fitted": 29.87503695487976 + "replica_set": 0.25393104553222656, + "replica_fitted": 34.448877811431885, + "replica_set_to_replica_fitted": 34.19494676589966 }, "cputime": { - "Total": 31.332164543999998, + "Total": 35.914583166, "start": 0.0, - "replica_set": 0.23007352200000053, - "replica_fitted": 31.331957337000002, - "replica_set_to_replica_fitted": 31.101883815 + "replica_set": 0.24511515099999936, + "replica_fitted": 35.914323130999996, + "replica_set_to_replica_fitted": 35.669207979999996 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/extra_tests/regression_fits/trainable_prepro.yml b/extra_tests/regression_fits/trainable_prepro.yml index 132620e0b7..5b5a69547b 100644 --- a/extra_tests/regression_fits/trainable_prepro.yml +++ b/extra_tests/regression_fits/trainable_prepro.yml @@ -35,9 +35,6 @@ mcseed: 1 load: "weights.weights.h5" -sampling: - separate_multiplicative: True - parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] activation_per_layer: ['sigmoid', 'tanh', 'linear'] diff --git a/extra_tests/regression_fits/trainable_prepro_61.json b/extra_tests/regression_fits/trainable_prepro_61.json index 71d35e6f10..5c426e7b05 100644 --- a/extra_tests/regression_fits/trainable_prepro_61.json +++ b/extra_tests/regression_fits/trainable_prepro_61.json @@ -71,25 +71,24 @@ ], "timing": { "walltime": { - "Total": 31.844950675964355, + "Total": 34.79690074920654, "start": 0.0, - "replica_set": 0.23360300064086914, - "replica_fitted": 31.844779014587402, - "replica_set_to_replica_fitted": 31.611176013946533 + "replica_set": 0.24268245697021484, + "replica_fitted": 34.79669666290283, + "replica_set_to_replica_fitted": 34.55401420593262 }, "cputime": { - "Total": 32.889014591, + "Total": 36.326103099, "start": 0.0, - "replica_set": 0.23132029399999965, - "replica_fitted": 32.888841699, - "replica_set_to_replica_fitted": 32.657521405 + "replica_set": 0.24133399599999983, + "replica_fitted": 36.325896654, + "replica_set_to_replica_fitted": 36.084562657999996 } }, "version": { - "keras": "3.3.3", - "tensorflow": "2.16.1, mkl=False", + "tensorflow": "2.16.1, mkl=??", "numpy": "1.26.4", - "nnpdf": "4.0.9.post910.dev0+670d39e81", - "validphys": "4.0.9.post910.dev0+670d39e81" + "nnpdf": "4.0.9.post576.dev0+47a077fe1", + "validphys": "4.0.9.post576.dev0+47a077fe1" } } diff --git a/n3fit/runcards/examples/Basic_runcard.yml b/n3fit/runcards/examples/Basic_runcard.yml index f315d80f45..e64260d3bd 100644 --- a/n3fit/runcards/examples/Basic_runcard.yml +++ b/n3fit/runcards/examples/Basic_runcard.yml @@ -73,18 +73,12 @@ positivity: posdatasets: - {dataset: NNPDF_POS_2P24GEV_F2U, maxlambda: 1e6} # Positivity Lagrange Multiplier - {dataset: NNPDF_POS_2P24GEV_FLL-19PTS, maxlambda: 1e6} - - {dataset: NNPDF_POS_2P24GEV_XGL, maxlambda: 1e6} ############################################################ integrability: integdatasets: - {dataset: NNPDF_INTEG_3GEV_XT3, maxlambda: 1e2} -# Apply a cut to a dataset or process type, in this case to the positivity dataset `NNPDF_POS_2P24GEV_XGL` which has process type: POS_XPDF -added_filter_rules: - - process_type: POS_XPDF - rule: "x > 0.1" - ############################################################ debug: True maxcores: 8 diff --git a/n3fit/runcards/examples/nnpdf40-like.yml b/n3fit/runcards/examples/nnpdf40-like.yml index f1d1ed1d91..434c6173f4 100644 --- a/n3fit/runcards/examples/nnpdf40-like.yml +++ b/n3fit/runcards/examples/nnpdf40-like.yml @@ -101,9 +101,8 @@ theory: theoryid: 40_000_000 # For fits <= 4.0 multiplicative and additive uncertainties were sampled separately -# and thus the flag `separate_multiplicative` needs to be set to True -# sampling: -# separate_multiplicative: True +sampling: + separate_multiplicative: False ################################################################################ trvlseed: 591866982 diff --git a/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml b/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml index f89604952a..30008f22b3 100644 --- a/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml +++ b/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml @@ -99,6 +99,9 @@ datacuts: theory: theoryid: 700 # database id +sampling: + separate_multiplicative: false + hyperscan_config: stopping: min_epochs: 15e3 diff --git a/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml b/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml index 3f343e6e3a..332247100d 100644 --- a/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml +++ b/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml @@ -99,6 +99,9 @@ datacuts: theory: theoryid: 700 # database id +sampling: + separate_multiplicative: false + hyperscan_config: architecture: n_layers: [2] diff --git a/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py b/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py index ed083983ff..31def842c4 100644 --- a/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py +++ b/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py @@ -8,8 +8,8 @@ For instance: np_to_tensor is just a call to K.constant """ -from tensorflow.keras.initializers import Constant, RandomUniform, glorot_normal, glorot_uniform from tensorflow.keras.layers import Layer +from tensorflow.keras.initializers import Constant, RandomUniform, glorot_normal, glorot_uniform # Define in this dictionary new initializers as well as the arguments they accept (with default values if needed be) initializers = { @@ -25,7 +25,7 @@ class MetaLayer(Layer): In order to write a custom Keras layer you usually need to override: - __init__ - - call + - meta_call """ initializers = initializers diff --git a/n3fit/src/n3fit/backends/keras_backend/MetaModel.py b/n3fit/src/n3fit/backends/keras_backend/MetaModel.py index 7ea2d5b9b1..21c858a181 100644 --- a/n3fit/src/n3fit/backends/keras_backend/MetaModel.py +++ b/n3fit/src/n3fit/backends/keras_backend/MetaModel.py @@ -8,10 +8,10 @@ from pathlib import Path import re +from keras import optimizers as Kopt +from keras.models import Model import numpy as np import tensorflow as tf -from tensorflow.keras import optimizers as Kopt -from tensorflow.keras.models import Model from tensorflow.python.keras.utils import tf_utils # pylint: disable=no-name-in-module import n3fit.backends.keras_backend.operations as op diff --git a/n3fit/src/n3fit/backends/keras_backend/base_layers.py b/n3fit/src/n3fit/backends/keras_backend/base_layers.py index e6afc6c5c6..a68f058c5a 100644 --- a/n3fit/src/n3fit/backends/keras_backend/base_layers.py +++ b/n3fit/src/n3fit/backends/keras_backend/base_layers.py @@ -135,6 +135,7 @@ def apply_dense(xinput): "dense": ( MultiDense, { + "input_shape": (1,), "replica_seeds": None, "base_seed": 0, "kernel_initializer": "glorot_normal", @@ -147,6 +148,7 @@ def apply_dense(xinput): "single_dense": ( Dense, { + "input_shape": (1,), "kernel_initializer": "glorot_normal", "units": 5, "activation": "sigmoid", @@ -156,6 +158,7 @@ def apply_dense(xinput): "dense_per_flavour": ( dense_per_flavour, { + "input_shape": (1,), "kernel_initializer": "glorot_normal", "units": 5, "activation": "sigmoid", @@ -191,7 +194,7 @@ def base_layer_selector(layer_name, **kwargs): layer_tuple = layers[layer_name] except KeyError as e: raise NotImplementedError( - f"Layer not implemented in keras_backend/base_layers.py: {layer_name}" + "Layer not implemented in keras_backend/base_layers.py: {0}".format(layer_name) ) from e layer_class = layer_tuple[0] @@ -231,7 +234,7 @@ def regularizer_selector(reg_name, **kwargs): reg_tuple = regularizers[reg_name] except KeyError: raise NotImplementedError( - f"Regularizer not implemented in keras_backend/base_layers.py: {reg_name}" + "Regularizer not implemented in keras_backend/base_layers.py: {0}".format(reg_name) ) reg_class = reg_tuple[0] diff --git a/n3fit/src/n3fit/backends/keras_backend/multi_dense.py b/n3fit/src/n3fit/backends/keras_backend/multi_dense.py index 07b045fb45..6d789de90e 100644 --- a/n3fit/src/n3fit/backends/keras_backend/multi_dense.py +++ b/n3fit/src/n3fit/backends/keras_backend/multi_dense.py @@ -4,9 +4,11 @@ Dense layer from Keras even in the single replica case. """ # Tested last: Feb 2024 +from typing import List + +from keras.initializers import Initializer +from keras.layers import Dense import tensorflow as tf -from tensorflow.keras.initializers import Initializer -from tensorflow.keras.layers import Dense # Note for developers: # This class plays with fire as it exploits the internals of Keras @@ -49,7 +51,7 @@ class MultiDense(Dense): def __init__( self, - replica_seeds: list[int], + replica_seeds: List[int], kernel_initializer: Initializer, is_first_layer: bool = False, base_seed: int = 0, @@ -174,7 +176,7 @@ class MultiInitializer(Initializer): Base seed for the single replica initializer to which the replica seeds are added. """ - def __init__(self, single_initializer: Initializer, replica_seeds: list[int], base_seed: int): + def __init__(self, single_initializer: Initializer, replica_seeds: List[int], base_seed: int): self.initializer_class = type(single_initializer) self.initializer_config = single_initializer.get_config() self.base_seed = base_seed diff --git a/n3fit/src/n3fit/backends/keras_backend/operations.py b/n3fit/src/n3fit/backends/keras_backend/operations.py index b6ad0e010e..844274379c 100644 --- a/n3fit/src/n3fit/backends/keras_backend/operations.py +++ b/n3fit/src/n3fit/backends/keras_backend/operations.py @@ -25,10 +25,10 @@ from typing import Optional +import keras import numpy as np import numpy.typing as npt import tensorflow as tf -from tensorflow import keras from tensorflow.keras import backend as K from tensorflow.keras.layers import Input from tensorflow.keras.layers import Lambda as keras_Lambda @@ -228,21 +228,14 @@ def reshape(x, shape): return tf.reshape(x, shape) -@tf.function -def boolean_mask(*args, target_shape=None, **kwargs): +def boolean_mask(*args, **kwargs): """ Applies a boolean mask to a tensor Relevant parameters: (tensor, mask, axis=None) see full `docs `_. - - tensorflow's masking concatenates the masked dimensions, it is possible to - provide a `target_shape` to reshape the output to the desired shape """ - ret = tf.boolean_mask(*args, **kwargs) - if target_shape is not None: - ret = reshape(ret, target_shape) - return ret + return tf.boolean_mask(*args, **kwargs) @tf.function diff --git a/n3fit/src/n3fit/checks.py b/n3fit/src/n3fit/checks.py index 9aa05dfae8..3ff404ffe5 100644 --- a/n3fit/src/n3fit/checks.py +++ b/n3fit/src/n3fit/checks.py @@ -417,7 +417,7 @@ def check_consistent_basis(sum_rules, fitbasis, basis, theoryid, parameters): @make_argcheck -def check_consistent_parallel(parameters, parallel_models): +def check_consistent_parallel(parameters, parallel_models, same_trvl_per_replica): """Checks whether the multiple-replica fit options are consistent among them i.e., that the trvl seed is fixed and the layer type is correct """ diff --git a/n3fit/src/n3fit/hyper_optimization/rewards.py b/n3fit/src/n3fit/hyper_optimization/rewards.py index 9f48208599..bba8057d89 100644 --- a/n3fit/src/n3fit/hyper_optimization/rewards.py +++ b/n3fit/src/n3fit/hyper_optimization/rewards.py @@ -32,7 +32,7 @@ """ import logging -from typing import Callable +from typing import Callable, Dict, List import numpy as np @@ -194,10 +194,10 @@ def __init__( def compute_loss( self, - penalties: dict[str, np.ndarray], + penalties: Dict[str, np.ndarray], experimental_loss: np.ndarray, pdf_model: MetaModel, - experimental_data: list[DataGroupSpec], + experimental_data: List[DataGroupSpec], fold_idx: int = 0, ) -> float: """ @@ -271,7 +271,7 @@ def _save_hyperopt_metrics( self, phi_per_fold: float, chi2_per_fold: np.ndarray, - penalties: dict[str, np.ndarray], + penalties: Dict[str, np.ndarray], fold_idx: int = 0, ) -> None: """ @@ -403,7 +403,7 @@ def _set_central_value(n3pdf, model): # Get the input x for key, grid in model.x_in.items(): - if key != "xgrid_integration": + if key != "integration_grid": input_x = grid.numpy() break diff --git a/n3fit/src/n3fit/layers/mask.py b/n3fit/src/n3fit/layers/mask.py index 3ed007a18f..2b0bff6c00 100644 --- a/n3fit/src/n3fit/layers/mask.py +++ b/n3fit/src/n3fit/layers/mask.py @@ -43,7 +43,7 @@ def build(self, input_shape): self.masked_output_shape = [-1 if d is None else d for d in input_shape] self.masked_output_shape[-1] = self.last_dim self.masked_output_shape[-2] = self.mask.shape[-2] - super().build(input_shape) + super(Mask, self).build(input_shape) def call(self, ret): """ @@ -58,7 +58,8 @@ def call(self, ret): Tensor of shape (batch_size, n_replicas, n_features) """ if self.mask is not None: - ret = op.boolean_mask(ret, self.mask, axis=1, target_shape=self.masked_output_shape) + flat_res = op.boolean_mask(ret, self.mask, axis=1) + ret = op.reshape(flat_res, shape=self.masked_output_shape) if self.c is not None: ret = ret * self.kernel return ret diff --git a/n3fit/src/n3fit/model_gen.py b/n3fit/src/n3fit/model_gen.py index e5a2cf55ba..f45a0f7205 100644 --- a/n3fit/src/n3fit/model_gen.py +++ b/n3fit/src/n3fit/model_gen.py @@ -11,7 +11,7 @@ """ from dataclasses import dataclass -from typing import Callable +from typing import Callable, List import numpy as np @@ -320,8 +320,8 @@ def observable_generator( def generate_pdf_model( - nodes: list[int] = None, - activations: list[str] = None, + nodes: List[int] = None, + activations: List[str] = None, initializer_name: str = "glorot_normal", layer_type: str = "dense", flav_info: dict = None, @@ -383,8 +383,8 @@ def generate_pdf_model( def pdfNN_layer_generator( - nodes: list[int] = None, - activations: list[str] = None, + nodes: List[int] = None, + activations: List[str] = None, initializer_name: str = "glorot_normal", layer_type: str = "dense", flav_info: dict = None, @@ -547,13 +547,13 @@ def pdfNN_layer_generator( # Define the main input do_nothing = lambda x: x if use_feature_scaling: - pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name="scaledx_x") + pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name='scaledx_x') process_input = do_nothing - extract_nn_input = Lambda(lambda x: op.op_gather_keep_dims(x, 0, axis=-1), name="x_scaled") - extract_original = Lambda(lambda x: op.op_gather_keep_dims(x, 1, axis=-1), name="pdf_input") + extract_nn_input = Lambda(lambda x: op.op_gather_keep_dims(x, 0, axis=-1), name='x_scaled') + extract_original = Lambda(lambda x: op.op_gather_keep_dims(x, 1, axis=-1), name='x') else: # add log(x) - pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name="pdf_input") - process_input = Lambda(lambda x: op.concatenate([x, op.op_log(x)], axis=-1), name="x_logx") + pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name='x') + process_input = Lambda(lambda x: op.concatenate([x, op.op_log(x)], axis=-1), name='x_logx') extract_original = do_nothing extract_nn_input = do_nothing @@ -564,12 +564,12 @@ def pdfNN_layer_generator( if use_feature_scaling: input_x_eq_1 = scaler(input_x_eq_1)[0] # the layer that subtracts 1 from the NN output - subtract_one_layer = Lambda(op.op_subtract, name="subtract_one") - layer_x_eq_1 = op.numpy_to_input(np.array(input_x_eq_1).reshape(1, 1), name="x_eq_1") + subtract_one_layer = Lambda(op.op_subtract, name='subtract_one') + layer_x_eq_1 = op.numpy_to_input(np.array(input_x_eq_1).reshape(1, 1), name='x_eq_1') model_input["layer_x_eq_1"] = layer_x_eq_1 # the layer that multiplies the NN output by the preprocessing factor - apply_preprocessing_factor = Lambda(op.op_multiply, name="prefactor_times_NN") + apply_preprocessing_factor = Lambda(op.op_multiply, name='prefactor_times_NN') # Photon layer layer_photon = AddPhoton(photons=photons, name="add_photon") @@ -580,19 +580,20 @@ def pdfNN_layer_generator( ) # Evolution layer - layer_evln = FkRotation(output_dim=out, name="pdf_FK_basis") + layer_evln = FkRotation(input_shape=(last_layer_nodes,), output_dim=out, name="pdf_FK_basis") # Normalization and sum rules if impose_sumrule: sumrule_layer, integrator_input = generate_msr_model_and_grid( fitbasis=fitbasis, mode=impose_sumrule, scaler=scaler, replica_seeds=seed ) - model_input["xgrid_integration"] = integrator_input + model_input["integrator_input"] = integrator_input else: sumrule_layer = lambda x: x compute_preprocessing_factor = Preprocessing( flav_info=flav_info, + input_shape=(1,), name=PREPROCESSING_LAYER_ALL_REPLICAS, replica_seeds=seed, large_x=not subtract_one, @@ -684,10 +685,10 @@ def compute_unnormalized_pdf(x): def generate_nn( layer_type: str, nodes_in: int, - nodes: list[int], - activations: list[str], + nodes: List[int], + activations: List[str], initializer_name: str, - replica_seeds: list[int], + replica_seeds: List[int], dropout: float, regularizer: str, regularizer_args: dict, @@ -726,7 +727,7 @@ def generate_nn( Single model containing all replicas. """ nodes_list = list(nodes) # so we can modify it - x_input = Input(shape=(None, nodes_in), batch_size=1, name="NN_input") + x_input = Input(shape=(None, nodes_in), batch_size=1, name='xgrids_processed') reg = regularizer_selector(regularizer, **regularizer_args) if layer_type == "dense_per_flavour": @@ -752,6 +753,7 @@ def layer_generator(i_layer, nodes_out, activation): kernel_initializer=initializers, units=int(nodes_out), activation=activation, + input_shape=(nodes_in,), basis_size=basis_size, ) layers.append(layer) @@ -773,6 +775,7 @@ def layer_generator(i_layer, nodes_out, activation): ), units=nodes_out, activation=activation, + input_shape=(nodes_in,), regularizer=reg, ) diff --git a/n3fit/src/n3fit/model_trainer.py b/n3fit/src/n3fit/model_trainer.py index 21da5d0d17..df2e0be917 100644 --- a/n3fit/src/n3fit/model_trainer.py +++ b/n3fit/src/n3fit/model_trainer.py @@ -352,7 +352,7 @@ def _xgrid_generation(self): if self._scaler: # Apply feature scaling if given input_arr = self._scaler(input_arr) - input_layer = op.numpy_to_input(input_arr, name="pdf_input") + input_layer = op.numpy_to_input(input_arr) # The PDF model will be called with a concatenation of all inputs # now the output needs to be splitted so that each experiment takes its corresponding input diff --git a/n3fit/src/n3fit/msr.py b/n3fit/src/n3fit/msr.py index a66e03a3fe..a9a30190c2 100644 --- a/n3fit/src/n3fit/msr.py +++ b/n3fit/src/n3fit/msr.py @@ -68,7 +68,7 @@ def generate_msr_model_and_grid( xgrid_integration = scaler(xgrid_integration) # Turn into input layer. - xgrid_integration = op.numpy_to_input(xgrid_integration, name="xgrid_integration") + xgrid_integration = op.numpy_to_input(xgrid_integration, name="integration_grid") # 1c Get the original grid if scaler: @@ -88,7 +88,7 @@ def generate_msr_model_and_grid( )([x_divided, pdf_xgrid_integration]) # 4. Integrate the pdf - pdf_integrated = xIntegrator(weights_array)(pdf_integrand) + pdf_integrated = xIntegrator(weights_array, input_shape=(nx,))(pdf_integrand) # 5. THe input for the photon integral, will be set to 0 if no photons photon_integral = Input(shape=(replicas, 1), batch_size=1, name='photon_integral') diff --git a/n3fit/src/n3fit/n3fit_checks_provider.py b/n3fit/src/n3fit/n3fit_checks_provider.py index a9a07ab4be..a06b3f0efd 100644 --- a/n3fit/src/n3fit/n3fit_checks_provider.py +++ b/n3fit/src/n3fit/n3fit_checks_provider.py @@ -28,6 +28,7 @@ def n3fit_checks_action( kfold=None, tensorboard=None, parallel_models=False, + same_trvl_per_replica=False, double_precision=False, ): return diff --git a/n3fit/src/n3fit/scripts/n3fit_exec.py b/n3fit/src/n3fit/scripts/n3fit_exec.py index 9c68bbb5e1..2a749fa846 100755 --- a/n3fit/src/n3fit/scripts/n3fit_exec.py +++ b/n3fit/src/n3fit/scripts/n3fit_exec.py @@ -180,7 +180,7 @@ def from_yaml(cls, o, *args, **kwargs): # Sampling flags if (sam_t0 := file_content.get('sampling')) is not None: N3FIT_FIXED_CONFIG['separate_multiplicative'] = sam_t0.get( - 'separate_multiplicative', False + 'separate_multiplicative', True ) # Fitting flag file_content.update(N3FIT_FIXED_CONFIG) diff --git a/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml b/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml index 4608267ee2..87ac1edaff 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml @@ -31,8 +31,6 @@ nnseed: 2 mcseed: 1 save: weights.weights.h5 -sampling: - separate_multiplicative: true parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] diff --git a/n3fit/src/n3fit/tests/regressions/quickcard.yml b/n3fit/src/n3fit/tests/regressions/quickcard.yml index 19b32652dc..ca51c9a339 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard.yml @@ -34,8 +34,6 @@ nnseed: 2 mcseed: 1 load: "weights.weights.h5" -sampling: - separate_multiplicative: true parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] diff --git a/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml b/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml index 8702cb5229..94bc90414f 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml @@ -32,8 +32,6 @@ nnseed: 2 mcseed: 1 load: "weights_pol.weights.h5" -sampling: - separate_multiplicative: true parameters: nodes_per_layer: [25, 20, 4] diff --git a/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml b/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml index 282f982876..684bb47afd 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml @@ -34,8 +34,6 @@ nnseed: 2 mcseed: 1 load: "weights.weights.h5" -sampling: - separate_multiplicative: true parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] diff --git a/n3fit/src/n3fit/tests/test_multireplica.py b/n3fit/src/n3fit/tests/test_multireplica.py index aa1893ff3f..61f40716a1 100644 --- a/n3fit/src/n3fit/tests/test_multireplica.py +++ b/n3fit/src/n3fit/tests/test_multireplica.py @@ -23,10 +23,10 @@ def test_replica_split(): eps = 1e-9 pdf_input = np.maximum(rng.random((1, 5, 1)), eps) int_input = np.maximum(rng.random((1, 2_000, 1)), eps) - + fake_input = { 'pdf_input': np.sort(pdf_input, axis=1), - 'xgrid_integration': np.sort(int_input, axis=1), + 'integrator_input': np.sort(int_input, axis=1), } output_full = pdf_model(fake_input) diff --git a/n3fit/src/n3fit/tests/test_preprocessing.py b/n3fit/src/n3fit/tests/test_preprocessing.py index 4a448172e5..2ed415df87 100644 --- a/n3fit/src/n3fit/tests/test_preprocessing.py +++ b/n3fit/src/n3fit/tests/test_preprocessing.py @@ -86,7 +86,7 @@ def test_constraint(): x = Input(shape=test_x.shape[1:]) prefactors = prepro(x) scalar = Lambda(lambda x: op.sum(x, axis=(1, 2, 3)))(prefactors) - model = MetaModel(input_tensors={'pdf_input': x}, output_tensors=scalar) + model = MetaModel(input_tensors={'x': x}, output_tensors=scalar) model.compile(loss='mse', learning_rate=1e-15) # Simulate training where weights of replica 1 are updated to violate the constraint diff --git a/nnpdf_data/nnpdf_data/filter_utils/utils.py b/nnpdf_data/nnpdf_data/filter_utils/utils.py index e38dacb70a..d59c197f86 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/utils.py +++ b/nnpdf_data/nnpdf_data/filter_utils/utils.py @@ -1,373 +1,11 @@ """ -General Python utilities for commondata implementation. - -This module provides helpful functions that automate a few -tasks that are regularly needed for the implementation of -experimental data to the commondata format. If there are -any additional functions that could be added here as they -could simplify some repetitve tasks, please do suggest. - -Before the usage of any functions, it is recommended to read -the docstrings of the function to understand the inputs and -outputs. +Module contains general utility functions for general use in implementing datasets. """ -from math import sqrt - import numpy as np -from numpy.linalg import eig import yaml -def symmetrize_errors(delta_plus, delta_minus): - r"""Compute the symmterized uncertainty and the shift in data point. - - Parameters - ---------- - delta_plus : float - The top/plus uncertainty with sign - delta_minus : float - The bottom/minus uncertainty with sign - - Returns - ------- - se_delta : float - The value to be added to the data point - se_sigma : float - The symmetrized uncertainty to be used in commondata - - """ - semi_diff = (delta_plus + delta_minus) / 2 - average = (delta_plus - delta_minus) / 2 - se_delta = semi_diff - se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff) - return se_delta, se_sigma - - -def percentage_to_absolute(percentage, value): - r"""Compute the absolute value of uncertainty from percentage. - - Parameters - ---------- - percentage : string/float - Experimental datasets can provide the percentage - uncertainties with a % sign or without one. - The function will autostrip % sign and convert to - a float type in case the percentage uncertainty - comes with a % sign. Else, it will directly perform - the computation. - value : float - The data point - - Returns - ------- - absolute : float - The absolute value of the uncertainty - - """ - if type(percentage) is str: - percentage = float(percentage.replace("%", "")) - absolute = percentage * value * 0.01 - return absolute - else: - absolute = percentage * value * 0.01 - return absolute - - -def cormat_to_covmat(err_list, cormat_list): - r"""Convert correlation matrix elements to covariance - matrix elements. - - Parameters - ---------- - err_list : list - A one dimensional list which contains the uncertainty - associated to each data point in order. - cormat_list : list - A one dimensional list which contains the elements of - the correlation matrix row by row. Since experimental - datasets provide these matrices in a list form, this - simplifies the implementation for the user. - - Returns - ------- - covmat_list : list - A one dimensional list which contains the elements of - the covariance matrix row by row. - - """ - covmat_list = [] - for i in range(len(cormat_list)): - a = i // len(err_list) - b = i % len(err_list) - covmat_list.append(cormat_list[i] * err_list[a] * err_list[b]) - return covmat_list - - -def covmat_to_artunc(ndata, covmat_list, no_of_norm_mat=0): - r"""Convert the covariance matrix to a matrix of - artificial uncertainties. - - Parameters - ---------- - ndata : integer - Number of data points - covmat_list : list - A one dimensional list which contains the elements of - the covariance matrix row by row. Since experimental - datasets provide these matrices in a list form, this - simplifies the implementation for the user. - no_of_norm_mat : int - Normalized covariance matrices may have an eigenvalue - of 0 due to the last data point not being linearly - independent. To allow for this, the user should input - the number of normalized matrices that are being treated - in an instance. For example, if a single covariance matrix - of a normalized distribution is being processed, the input - would be 1. If a covariance matrix contains pertains to - 3 normalized datasets (i.e. cross covmat for 3 - distributions), the input would be 3. The default value is - 0 for when the covariance matrix pertains to an absolute - distribution. - - Returns - ------- - artunc : list - A two dimensional matrix (given as a list of lists) - which contains artificial uncertainties to be added - to the commondata. i^th row (or list) contains the - artificial uncertainties of the i^th data point. - - """ - epsilon = -0.0000000001 - neg_eval_count = 0 - psd_check = True - covmat = np.zeros((ndata, ndata)) - artunc = np.zeros((ndata, ndata)) - for i in range(len(covmat_list)): - a = i // ndata - b = i % ndata - covmat[a][b] = covmat_list[i] - eigval, eigvec = eig(covmat) - for j in range(len(eigval)): - if eigval[j] < epsilon: - psd_check = False - elif eigval[j] > epsilon and eigval[j] <= 0: - neg_eval_count = neg_eval_count + 1 - if neg_eval_count == (no_of_norm_mat + 1): - psd_check = False - elif eigval[j] > 0: - continue - if not psd_check: - raise ValueError('The covariance matrix is not positive-semidefinite') - else: - for i in range(ndata): - for j in range(ndata): - if eigval[j] < 0: - continue - else: - artunc[i][j] = eigvec[i][j] * sqrt(eigval[j]) - return artunc.tolist() - - -def cross_cormat_to_covmat(row_err_list, col_err_list, cormat_list): - r"""Convert cross correlation matrix elements - (i.e. those between different different variables or - observables) to covariance matrix elements. - - Parameters - ---------- - row_err_list : list - A one dimensional list which contains the uncertainty - associated to each data point of the variable that is - given on the vertical axis. - col_err_list : list - A one dimensional list which contains the uncertainty - associated to each data point of the variable that is - given on the horizontal axis. - cormat_list : list - A one dimensional list which contains the elements of - the correlation matrix row by row. Since experimental - datasets provide these matrices in a list form, this - simplifies the implementation for the user. - - Returns - ------- - covmat_list : list - A one dimensional list which contains the elements of - the covariance matrix row by row. - - """ - covmat_list = [] - for i in range(len(cormat_list)): - a = i // len(col_err_list) - b = i % len(col_err_list) - covmat_list.append(cormat_list[i] * row_err_list[a] * col_err_list[b]) - return covmat_list - - -def matlist_to_matrix(rows, columns, mat_list): - r"""Convert a 1d list to a 2d matrix. - - Note: This utils function is not strictly needed for - data implementation, however, it is provided for - the aid of the user due to how matrices are treated - throughout all the other functions. This function - allows the user to convert a list that contains the - elemnets of matrix row by row to a proper matrix, if - need be for any reason. - - Parameters - ---------- - rows : int - No. of rows in the matrix - columns : int - No. of columns in the matrix - mat_list : list - A one dimensional list which contains the elements of - the matrix row by row. - - Returns - ------- - matrix : numpy.ndarray - The matrix as a numpy 2d array. - - """ - if rows * columns == len(mat_list): - matrix = np.zeros((rows, columns)) - for i in range(rows): - for j in range(columns): - matrix[i][j] = mat_list[j + i * columns] - matrix = np.array(matrix) - return matrix - else: - raise Exception('rows * columns != len(mat_list)') - - -def concat_matrices(rows, columns, list_of_matrices): - r"""Join smaller matrices into a large matrix. - - This function aims to simplify the process of joining multiple - smaller matrices into one large matrix. Such a need could arise, - for instance, when cross variable covariance matrices are provided - but the user needs to join all the matrices to generate the full - covariance matrix corresponding to the entire dataset. - - Parameters - ---------- - rows : int - No. of rows of matrices to be concatenated. E.g., if 6 - matrices: A, B, C, D, E, F need to be joined as - [[A, B, C], - [D, E, F]], - the number of rows would be 2. - columns : int - No. of columns of matrices to be concatenated. In the - above example, this would be 3. - list_of_matrices : list - A list of the matrices that have to concatenated row by - row. In the above example, this would be [A, B, C, D, E, F]. - The matrices themselves need to be provided as a list of lists, - or a numpy 2d array. If the user has the matrix in a 1d row by - row form, use matList_to_matrix() to convert it. It is assumed - the user verifies that all the input matrices have the correct - dimensions. Matrices with incompatible dimensions will lead to - undesired behavior. - - Returns - ------- - final_mat_list : list - A one dimensional list which contains the elements of - the final, fully concatenated matrix row by row. - - """ - for i in range(len(list_of_matrices)): - list_of_matrices[i] = np.array(list_of_matrices[i]) - col_list = [] - for i in range(rows): - row_list = [] - for j in range(columns): - row_list.append(list_of_matrices[j + i * columns]) - col_list.append(np.concatenate(tuple(row_list), axis=1)) - final_mat = np.concatenate(tuple(col_list), axis=0) - final_mat_list = [] - for i in range(len(final_mat)): - for j in range(len(final_mat[i])): - final_mat_list.append(final_mat[i][j]) - return final_mat_list - - -def trimat_to_fullmat(mode, tri_mat_list): - r"""Convert a list of values of a triangular matrix - to a symmetric matrix. - - Experimental datasets can provide the entries of - correlation or covariance matrices as a triangular - matrix, as these matrices are symmetric by their - very nature. This function can convert these list to - a complete symmetric matrix, that can be used for the - dataset implementation. - - mode : bool - Enter 0 or 1 based on the following scenarios: - Use mode 0 if matrix entries are given row by - row such as: - 0 1 2 3 - 4 5 6 - 7 8 - 9 - Use mode 1 if the matrix entries are given column - by column such as: - 0 1 3 6 - 2 4 7 - 5 8 - 9 - Please note that the numbers above (0-9) are not - entries of the matrix but rather the index of the - entries of the list which contains the elements of - the triangular matrix. - tri_mat_list : list - A list containing the elements of the triangular matrix, - for example, for a 4*4 matrix, the list of - triangular matrix entries could be: - [a, b, c, d, e, f, g, h, i, j] - - Returns - ------- - mat_list : list - A one dimensional list which contains the elements of - the fully populated, symmetric matrix row by row. - - """ - dim = int((np.sqrt(1 + 8 * len(tri_mat_list)) - 1) / 2) - matrix = np.zeros((dim, dim)) - if mode == 0: - for i in range(dim): - for j in range(i + 1): - list_el = len(tri_mat_list) - 1 - ((i * (i + 1)) // 2 + j) - if i == j: - matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] - else: - matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] - matrix[dim - 1 - j][dim - 1 - i] = tri_mat_list[list_el] - elif mode == 1: - for i in range(dim): - for j in range(i + 1): - list_el = (i * (i + 1)) // 2 + j - if i == j: - matrix[i][j] = tri_mat_list[list_el] - else: - matrix[i][j] = tri_mat_list[list_el] - matrix[j][i] = tri_mat_list[list_el] - else: - raise Exception('Mode should be 0 or 1, refer to the function for usage') - mat_list = [] - for i in range(dim): - for j in range(dim): - mat_list.append(matrix[i][j]) - return mat_list - - def correlation_to_covariance(correlation, uncertainties): """ Converts a correlation matrix into a covariance matrix diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py index b0606649fe..ff222f5fea 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py index 6ddd20bef2..0655765b51 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py index e8de287406..25e6371f66 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py @@ -1,9 +1,9 @@ -import numpy as np import yaml +import numpy as np +from utils import covmat_to_artunc as cta +from utils import matlist_to_matrix as mtm +from utils import concat_matrices as cm -from nnpdf_data.filter_utils.utils import concat_matrices as cm -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -from nnpdf_data.filter_utils.utils import matlist_to_matrix as mtm covmat_mtt = [] covmat_mtt_norm = [] @@ -22,7 +22,7 @@ covmat_496 = [] covmat_497 = [] -covariance_matrix_mtt = "rawdata/Table464.yaml" +covariance_matrix_mtt="rawdata/Table464.yaml" with open(covariance_matrix_mtt, 'r') as file1: input1 = yaml.safe_load(file1) for i in range(81): @@ -30,7 +30,7 @@ artunc_mtt = cta(9, covmat_mtt) -covariance_matrix_mtt_norm = "rawdata/Table462.yaml" +covariance_matrix_mtt_norm="rawdata/Table462.yaml" with open(covariance_matrix_mtt_norm, 'r') as file2: input2 = yaml.safe_load(file2) for i in range(81): @@ -38,14 +38,14 @@ artunc_mtt_norm = cta(9, covmat_mtt_norm, 1) -covariance_matrix_ytt = "rawdata/Table476.yaml" +covariance_matrix_ytt="rawdata/Table476.yaml" with open(covariance_matrix_ytt, 'r') as file3: input3 = yaml.safe_load(file3) for i in range(144): covmat_ytt.append(input3['dependent_variables'][0]['values'][i]['value']) artunc_ytt = cta(12, covmat_ytt) -covariance_matrix_ytt_norm = "rawdata/Table474.yaml" +covariance_matrix_ytt_norm="rawdata/Table474.yaml" with open(covariance_matrix_ytt_norm, 'r') as file4: input4 = yaml.safe_load(file4) for i in range(144): @@ -92,21 +92,7 @@ covmat_506.append(input10['dependent_variables'][0]['values'][i]['value']) covmat_506 = mtm(3, 3, covmat_506) -covmat_mtt_ytt = cm( - 3, - 3, - [ - covmat_501, - covmat_502t, - covmat_504t, - covmat_502, - covmat_503, - covmat_505t, - covmat_504, - covmat_505, - covmat_506, - ], -) +covmat_mtt_ytt = cm(3, 3, [covmat_501, covmat_502t, covmat_504t, covmat_502, covmat_503, covmat_505t, covmat_504, covmat_505, covmat_506]) artunc_mtt_ytt = cta(11, covmat_mtt_ytt) # abs mtt-ytt-norm @@ -149,19 +135,5 @@ covmat_497.append(input16['dependent_variables'][0]['values'][i]['value']) covmat_497 = mtm(3, 3, covmat_497) -covmat_mtt_ytt_norm = cm( - 3, - 3, - [ - covmat_492, - covmat_493t, - covmat_495t, - covmat_493, - covmat_494, - covmat_496t, - covmat_495, - covmat_496, - covmat_497, - ], -) +covmat_mtt_ytt_norm = cm(3, 3, [covmat_492, covmat_493t, covmat_495t, covmat_493, covmat_494, covmat_496t, covmat_495, covmat_496, covmat_497]) artunc_mtt_ytt_norm = cta(11, covmat_mtt_ytt_norm, 1) diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py new file mode 100644 index 0000000000..dac59de537 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py @@ -0,0 +1,369 @@ +""" +Python utilities for commondata implementation. + +This module provides helpful functions that automate a few +tasks that are regularly needed for the implementation of +experimental data to the commondata format. If there are +any additional functions that could be added here as they +could simplify some repetitve tasks, please do suggest. + +Before the usage of any functions, it is recommended to read +the docstrings of the function to understand the inputs and +outputs. + +@author: Tanishq Sharma +""" + +from math import sqrt + +import numpy as np +from numpy.linalg import eig + + +def symmetrize_errors(delta_plus, delta_minus): + r"""Compute the symmterized uncertainty and the shift in data point. + + Parameters + ---------- + delta_plus : float + The top/plus uncertainty with sign + delta_minus : float + The bottom/minus uncertainty with sign + + Returns + ------- + se_delta : float + The value to be added to the data point + se_sigma : float + The symmetrized uncertainty to be used in commondata + + """ + semi_diff = (delta_plus + delta_minus) / 2 + average = (delta_plus - delta_minus) / 2 + se_delta = semi_diff + se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff) + return se_delta, se_sigma + + +def percentage_to_absolute(percentage, value): + r"""Compute the absolute value of uncertainty from percentage. + + Parameters + ---------- + percentage : string/float + Experimental datasets can provide the percentage + uncertainties with a % sign or without one. + The function will autostrip % sign and convert to + a float type in case the percentage uncertainty + comes with a % sign. Else, it will directly perform + the computation. + value : float + The data point + + Returns + ------- + absolute : float + The absolute value of the uncertainty + + """ + if type(percentage) is str: + percentage = float(percentage.replace("%", "")) + absolute = percentage * value * 0.01 + return absolute + else: + absolute = percentage * value * 0.01 + return absolute + + +def cormat_to_covmat(err_list, cormat_list): + r"""Convert correlation matrix elements to covariance + matrix elements. + + Parameters + ---------- + err_list : list + A one dimensional list which contains the uncertainty + associated to each data point in order. + cormat_list : list + A one dimensional list which contains the elements of + the correlation matrix row by row. Since experimental + datasets provide these matrices in a list form, this + simplifies the implementation for the user. + + Returns + ------- + covmat_list : list + A one dimensional list which contains the elements of + the covariance matrix row by row. + + """ + covmat_list = [] + for i in range(len(cormat_list)): + a = i // len(err_list) + b = i % len(err_list) + covmat_list.append(cormat_list[i] * err_list[a] * err_list[b]) + return covmat_list + + +def covmat_to_artunc(ndata, covmat_list, no_of_norm_mat=0): + r"""Convert the covariance matrix to a matrix of + artificial uncertainties. + + Parameters + ---------- + ndata : integer + Number of data points + covmat_list : list + A one dimensional list which contains the elements of + the covariance matrix row by row. Since experimental + datasets provide these matrices in a list form, this + simplifies the implementation for the user. + no_of_norm_mat : int + Normalized covariance matrices may have an eigenvalue + of 0 due to the last data point not being linearly + independent. To allow for this, the user should input + the number of normalized matrices that are being treated + in an instance. For example, if a single covariance matrix + of a normalized distribution is being processed, the input + would be 1. If a covariance matrix contains pertains to + 3 normalized datasets (i.e. cross covmat for 3 + distributions), the input would be 3. The default value is + 0 for when the covariance matrix pertains to an absolute + distribution. + + Returns + ------- + artunc : list + A two dimensional matrix (given as a list of lists) + which contains artificial uncertainties to be added + to the commondata. i^th row (or list) contains the + artificial uncertainties of the i^th data point. + + """ + epsilon = -0.0000000001 + neg_eval_count = 0 + psd_check = True + covmat = np.zeros((ndata, ndata)) + artunc = np.zeros((ndata, ndata)) + for i in range(len(covmat_list)): + a = i // ndata + b = i % ndata + covmat[a][b] = covmat_list[i] + eigval, eigvec = eig(covmat) + for j in range(len(eigval)): + if eigval[j] < epsilon: + psd_check = False + elif eigval[j] > epsilon and eigval[j] <= 0: + neg_eval_count = neg_eval_count + 1 + if neg_eval_count == (no_of_norm_mat + 1): + psd_check = False + elif eigval[j] > 0: + continue + if psd_check == False: + raise ValueError('The covariance matrix is not positive-semidefinite') + else: + for i in range(ndata): + for j in range(ndata): + if eigval[j] < 0: + continue + else: + artunc[i][j] = eigvec[i][j] * sqrt(eigval[j]) + return artunc.tolist() + + +def cross_cormat_to_covmat(row_err_list, col_err_list, cormat_list): + r"""Convert cross correlation matrix elements + (i.e. those between different different variables or + observables) to covariance matrix elements. + + Parameters + ---------- + row_err_list : list + A one dimensional list which contains the uncertainty + associated to each data point of the variable that is + given on the vertical axis. + col_err_list : list + A one dimensional list which contains the uncertainty + associated to each data point of the variable that is + given on the horizontal axis. + cormat_list : list + A one dimensional list which contains the elements of + the correlation matrix row by row. Since experimental + datasets provide these matrices in a list form, this + simplifies the implementation for the user. + + Returns + ------- + covmat_list : list + A one dimensional list which contains the elements of + the covariance matrix row by row. + + """ + covmat_list = [] + for i in range(len(cormat_list)): + a = i // len(col_err_list) + b = i % len(col_err_list) + covmat_list.append(cormat_list[i] * row_err_list[a] * col_err_list[b]) + return covmat_list + + +def matlist_to_matrix(rows, columns, mat_list): + r"""Convert a 1d list to a 2d matrix. + + Note: This utils function is not strictly needed for + data implementation, however, it is provided for + the aid of the user due to how matrices are treated + throughout all the other functions. This function + allows the user to convert a list that contains the + elemnets of matrix row by row to a proper matrix, if + need be for any reason. + + Parameters + ---------- + rows : int + No. of rows in the matrix + columns : int + No. of columns in the matrix + mat_list : list + A one dimensional list which contains the elements of + the matrix row by row. + + Returns + ------- + matrix : numpy.ndarray + The matrix as a numpy 2d array. + + """ + if rows * columns == len(mat_list): + matrix = np.zeros((rows, columns)) + for i in range(rows): + for j in range(columns): + matrix[i][j] = mat_list[j + i * columns] + matrix = np.array(matrix) + return matrix + else: + raise Exception('rows * columns != len(mat_list)') + + +def concat_matrices(rows, columns, list_of_matrices): + r"""Join smaller matrices into a large matrix. + + This function aims to simplify the process of joining multiple + smaller matrices into one large matrix. Such a need could arise, + for instance, when cross variable covariance matrices are provided + but the user needs to join all the matrices to generate the full + covariance matrix corresponding to the entire dataset. + + Parameters + ---------- + rows : int + No. of rows of matrices to be concatenated. E.g., if 6 + matrices: A, B, C, D, E, F need to be joined as + [[A, B, C], + [D, E, F]], + the number of rows would be 2. + columns : int + No. of columns of matrices to be concatenated. In the + above example, this would be 3. + list_of_matrices : list + A list of the matrices that have to concatenated row by + row. In the above example, this would be [A, B, C, D, E, F]. + The matrices themselves need to be provided as a list of lists, + or a numpy 2d array. If the user has the matrix in a 1d row by + row form, use matList_to_matrix() to convert it. It is assumed + the user verifies that all the input matrices have the correct + dimensions. Matrices with incompatible dimensions will lead to + undesired behavior. + + Returns + ------- + final_mat_list : list + A one dimensional list which contains the elements of + the final, fully concatenated matrix row by row. + + """ + for i in range(len(list_of_matrices)): + list_of_matrices[i] = np.array(list_of_matrices[i]) + col_list = [] + for i in range(rows): + row_list = [] + for j in range(columns): + row_list.append(list_of_matrices[j + i * columns]) + col_list.append(np.concatenate(tuple(row_list), axis=1)) + final_mat = np.concatenate(tuple(col_list), axis=0) + final_mat_list = [] + for i in range(len(final_mat)): + for j in range(len(final_mat[i])): + final_mat_list.append(final_mat[i][j]) + return final_mat_list + + +def trimat_to_fullmat(mode, tri_mat_list): + r"""Convert a list of values of a triangular matrix + to a symmetric matrix. + + Experimental datasets can provide the entries of + correlation or covariance matrices as a triangular + matrix, as these matrices are symmetric by their + very nature. This function can convert these list to + a complete symmetric matrix, that can be used for the + dataset implementation. + + mode : bool + Enter 0 or 1 based on the following scenarios: + Use mode 0 if matrix entries are given row by + row such as: + 0 1 2 3 + 4 5 6 + 7 8 + 9 + Use mode 1 if the matrix entries are given column + by column such as: + 0 1 3 6 + 2 4 7 + 5 8 + 9 + Please note that the numbers above (0-9) are not + entries of the matrix but rather the index of the + entries of the list which contains the elements of + the triangular matrix. + tri_mat_list : list + A list containing the elements of the triangular matrix, + for example, for a 4*4 matrix, the list of + triangular matrix entries could be: + [a, b, c, d, e, f, g, h, i, j] + + Returns + ------- + mat_list : list + A one dimensional list which contains the elements of + the fully populated, symmetric matrix row by row. + + """ + dim = int((np.sqrt(1 + 8 * len(tri_mat_list)) - 1) / 2) + matrix = np.zeros((dim, dim)) + if mode == 0: + for i in range(dim): + for j in range(i + 1): + list_el = len(tri_mat_list) - 1 - ((i * (i + 1)) // 2 + j) + if i == j: + matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] + else: + matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] + matrix[dim - 1 - j][dim - 1 - i] = tri_mat_list[list_el] + elif mode == 1: + for i in range(dim): + for j in range(i + 1): + list_el = (i * (i + 1)) // 2 + j + if i == j: + matrix[i][j] = tri_mat_list[list_el] + else: + matrix[i][j] = tri_mat_list[list_el] + matrix[j][i] = tri_mat_list[list_el] + else: + raise Exception('Mode should be 0 or 1, refer to the function for usage') + mat_list = [] + for i in range(dim): + for j in range(dim): + mat_list.append(matrix[i][j]) + return mat_list diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py index f224ee8f3f..37b78e0988 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py @@ -1,8 +1,8 @@ import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py index e2c2a8fb2a..1458e3cd54 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py index 822d1367e9..a079949fa8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py @@ -2,80 +2,80 @@ from numpy.linalg import eig import yaml -from nnpdf_data.filter_utils.utils import concat_matrices as cm -from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -from nnpdf_data.filter_utils.utils import matlist_to_matrix as mtm -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import concat_matrices as cm +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import matlist_to_matrix as mtm +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta def artunc(): statArr = [] for i in [23, 29, 31, 27]: - with open('rawdata/Table_' + str(i) + '.yaml', 'r') as file: + with open('rawdata/Table_'+str(i)+'.yaml', 'r') as file: input = yaml.safe_load(file) for j in range(len(input['dependent_variables'][0]['values'])): datval = input['dependent_variables'][0]['values'][j]['value'] statperc = input['dependent_variables'][0]['values'][j]['errors'][0]['symerror'] statArr.append(pta(statperc, datval)) - - # mttbar(7)| pTt (8)| yt(5)| yttbar(5) - # mttbar| 179 174t 170t 177t - # pTt | 174 172 168t 173 - # yt | 170 168 167 169 - # yttbar| 177 173t 169t 176 + +# mttbar(7)| pTt (8)| yt(5)| yttbar(5) +# mttbar| 179 174t 170t 177t +# pTt | 174 172 168t 173 +# yt | 170 168 167 169 +# yttbar| 177 173t 169t 176 ml179, ml174, ml170, ml177, ml172, ml168, ml167, ml173, ml169, ml176 = ([] for i in range(10)) - + with open('rawdata/Table_179.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml179.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_174.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml174.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_170.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml170.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_177.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml177.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_172.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml172.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_168.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml168.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_167.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml167.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_173.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml173.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_169.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml169.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_176.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml176.append(input['dependent_variables'][0]['values'][i]['value']) - + mat179 = mtm(7, 7, ml179) mat174 = mtm(8, 7, ml174) mat174t = mat174.transpose() @@ -93,28 +93,8 @@ def artunc(): mat169t = mat169.transpose() mat176 = mtm(5, 5, ml176) - cormatlist = cm( - 4, - 4, - [ - mat179, - mat174t, - mat170t, - mat177t, - mat174, - mat172, - mat168t, - mat173, - mat170, - mat168, - mat167, - mat169, - mat177, - mat173t, - mat169t, - mat176, - ], - ) + cormatlist = cm(4, 4, [mat179, mat174t, mat170t, mat177t, mat174, mat172, mat168t, mat173, + mat170, mat168, mat167, mat169, mat177, mat173t, mat169t, mat176]) covmatlist = ctc(statArr, cormatlist) artunc = cta(25, covmatlist) @@ -124,70 +104,70 @@ def artunc(): def artunc_norm(): statArr = [] for i in [24, 30, 32, 28]: - with open('rawdata/Table_' + str(i) + '.yaml', 'r') as file: + with open('rawdata/Table_'+str(i)+'.yaml', 'r') as file: input = yaml.safe_load(file) for j in range(len(input['dependent_variables'][0]['values'])): datval = input['dependent_variables'][0]['values'][j]['value'] statperc = input['dependent_variables'][0]['values'][j]['errors'][0]['symerror'] statArr.append(pta(statperc, datval)) - - # mttbar(7)| pTt (8)| yt(5)| yttbar(5) - # mttbar| 234 229t 225t 232t - # pTt | 229 227 223t 228 - # yt | 225 223 222 224 - # yttbar| 232 228t 224t 231 + +# mttbar(7)| pTt (8)| yt(5)| yttbar(5) +# mttbar| 234 229t 225t 232t +# pTt | 229 227 223t 228 +# yt | 225 223 222 224 +# yttbar| 232 228t 224t 231 ml234, ml229, ml225, ml232, ml227, ml223, ml222, ml228, ml224, ml231 = ([] for i in range(10)) - + with open('rawdata/Table_234.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml234.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_229.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml229.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_225.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml225.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_232.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml232.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_227.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml227.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_223.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml223.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_222.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml222.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_228.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml228.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_224.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml224.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_231.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml231.append(input['dependent_variables'][0]['values'][i]['value']) - + mat234 = mtm(7, 7, ml234) mat229 = mtm(8, 7, ml229) mat229t = mat229.transpose() @@ -205,28 +185,8 @@ def artunc_norm(): mat224t = mat224.transpose() mat231 = mtm(5, 5, ml231) - cormatlist = cm( - 4, - 4, - [ - mat234, - mat229t, - mat225t, - mat232t, - mat229, - mat227, - mat223t, - mat228, - mat225, - mat223, - mat222, - mat224, - mat232, - mat228t, - mat224t, - mat231, - ], - ) + cormatlist = cm(4, 4, [mat234, mat229t, mat225t, mat232t, mat229, mat227, mat223t, mat228, + mat225, mat223, mat222, mat224, mat232, mat228t, mat224t, mat231]) covmatlist = ctc(statArr, cormatlist) artunc = cta(25, covmatlist, 4) diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py index 94b2dbb9c0..b114623b64 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py @@ -4,8 +4,8 @@ import artunc import yaml -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml index 62867cefa8..222ee7cdd4 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml @@ -26,7 +26,7 @@ implemented_observables: ndata: 38 - tables: [5] + tables: [26] process_type: DY_NC_PT plotting: diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml deleted file mode 100644 index 37eadd5649..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml +++ /dev/null @@ -1,8 +0,0 @@ -data_central: -- 353.152 -- 345.985 -- 336.195 -- 322.483 -- 303.973 -- 273.198 -- 173.171 diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py deleted file mode 100644 index 17f2c7c44a..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py +++ /dev/null @@ -1,91 +0,0 @@ - -import yaml -import numpy as np - -from filter_utils import get_kinematics, get_data_values, get_systematics - - -def filter_ATLAS_Z0_8TEV_data_kinetic(): - """ - writes data central values and kinematics - to respective .yaml file - """ - kin = get_kinematics() - central_values = get_data_values() - - data_central_yaml = {"data_central": central_values} - kinematics_yaml = {"bins": kin} - - # write central values and kinematics to yaml file - with open("data.yaml", "w") as file: - yaml.dump(data_central_yaml, file, sort_keys=False) - - with open("kinematics.yaml", "w") as file: - yaml.dump(kinematics_yaml, file, sort_keys=False) - - -def filter_ATLAS_Z0_8TEV_uncertainties(): - """ - writes uncertainties to respective .yaml file - """ - systematics = get_systematics() - - # load correlation matrix from .txt file - corr_matrix = np.loadtxt("rawdata/zy.txt") - - # generate covariance matrix from correlation matrix - tot_systematics = np.array([syst[0]['value'] for syst in systematics['tot']]) - - # TODO: this should be done with utils.correlation_to_covariance once that is merged in master - cov_matrix_no_lumi = np.outer(tot_systematics, tot_systematics) * corr_matrix - - # add lumi uncertainty - lumi_unc = np.array([syst[0]['value'] for syst in systematics['lumi']]) - lumi_cov = lumi_unc[:, None] @ lumi_unc[:, None].T - - # add covariances - cov_matrix = cov_matrix_no_lumi + lumi_cov - - # compute decomposition of covariance matrix so as to get artificial systematics - # TODO: use utils once merged in master - lamb, mat = np.linalg.eig(cov_matrix) - art_sys = np.multiply(np.sqrt(lamb), mat) - - uncertainties = [] - - for i, unc in enumerate(art_sys.T): - - name = f"artificial_uncertainty_{i+1}" - values = [unc[i] for i in range(len(unc))] - uncertainties.append([{"name": name, "values": values}]) - - # error definition - error_definitions = {} - errors = [] - - for sys in uncertainties: - - error_definitions[sys[0]['name']] = { - "description": f"{sys[0]['name']}", - "treatment": "ADD", - "type": "CORR", - } - - for i in range(cov_matrix.shape[0]): - error_value = {} - - for sys in uncertainties: - error_value[sys[0]['name']] = float(sys[0]['values'][i]) - - errors.append(error_value) - - uncertainties_yaml = {"definitions": error_definitions, "bins": errors} - - # write uncertainties - with open(f"uncertainties.yaml", 'w') as file: - yaml.dump(uncertainties_yaml, file, sort_keys=False) - - -if __name__ == "__main__": - filter_ATLAS_Z0_8TEV_data_kinetic() - filter_ATLAS_Z0_8TEV_uncertainties() \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py deleted file mode 100644 index 726b72d0e2..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py +++ /dev/null @@ -1,108 +0,0 @@ -import yaml - - -def get_kinematics(): - """ - returns the relevant kinematics values. - Parameters - ---------- - table : list - version : int - integer read from metadata.yaml that - indicated the version of the hepdata - tables - Returns - ------- - list - list containing the kinematic values for all - hepdata tables - """ - kin = [] - - hepdata_table = f"rawdata/HEPData-ins2698794-v1-Table_9.yaml" - - with open(hepdata_table, 'r') as file: - input = yaml.safe_load(file) - - for yll in input["independent_variables"][0]['values']: - kin_value = { - 'y': { - 'min': yll['low'], - 'mid': 0.5 * (yll['low'] + yll['high']), - 'max': yll['high'], - }, - 'm_Z2': {'min': None, 'mid': 8317.44, 'max': None}, - 'sqrts': {'min': None, 'mid': 8000.0, 'max': None}, - } - - kin.append(kin_value) - - return kin - - -def get_data_values(): - """ - returns the central data. - Parameters - ---------- - tables : list - list that enumerates the table number - version : int - integer read from metadata.yaml that - indicated the version of the hepdata - tables - Returns - ------- - list - list containing the central values for all - hepdata tables - """ - - data_central = [] - - hepdata_table = f"rawdata/HEPData-ins2698794-v1-Table_9.yaml" - - with open(hepdata_table, 'r') as file: - input = yaml.safe_load(file) - - values = input['dependent_variables'][0]['values'] - - for value in values: - data_central.append(value['value']) - - return data_central - - -def get_systematics(): - """ """ - tot_uncertainties = [] - lumi_uncertainties = [] - - hepdata_table = f"rawdata/HEPData-ins2698794-v1-Table_9.yaml" - - with open(hepdata_table, 'r') as file: - input = yaml.safe_load(file) - - dependent_vars = input['dependent_variables'][0] - - # skip 1st entry as these are central data values - for err_values in dependent_vars['values']: - - tot_uncertainties.append( - [ - { - "name": err_values['errors'][0]['label'], - "value": err_values['errors'][0]['symerror'], - } - ] - ) - lumi_uncertainties.append( - [ - { - "name": err_values['errors'][1]['label'], - "value": err_values['errors'][1]['symerror'], - } - ] - ) - - return {'tot': tot_uncertainties, 'lumi': lumi_uncertainties} diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml deleted file mode 100644 index 2fc461bc35..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml +++ /dev/null @@ -1,85 +0,0 @@ -bins: -- y: - min: 0.4 - mid: 0.6000000000000001 - max: 0.8 - m_Z2: - min: null - mid: 8317.44 - max: null - sqrts: - min: null - mid: 8000.0 - max: null -- y: - min: 0.8 - mid: 1.0 - max: 1.2 - m_Z2: - min: null - mid: 8317.44 - max: null - sqrts: - min: null - mid: 8000.0 - max: null -- y: - min: 1.2 - mid: 1.4 - max: 1.6 - m_Z2: - min: null - mid: 8317.44 - max: null - sqrts: - min: null - mid: 8000.0 - max: null -- y: - min: 1.6 - mid: 1.8 - max: 2 - m_Z2: - min: null - mid: 8317.44 - max: null - sqrts: - min: null - mid: 8000.0 - max: null -- y: - min: 2 - mid: 2.2 - max: 2.4 - m_Z2: - min: null - mid: 8317.44 - max: null - sqrts: - min: null - mid: 8000.0 - max: null -- y: - min: 2.4 - mid: 2.5999999999999996 - max: 2.8 - m_Z2: - min: null - mid: 8317.44 - max: null - sqrts: - min: null - mid: 8000.0 - max: null -- y: - min: 2.8 - mid: 3.2 - max: 3.6 - m_Z2: - min: null - mid: 8317.44 - max: null - sqrts: - min: null - mid: 8000.0 - max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml deleted file mode 100644 index 334c859db3..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml +++ /dev/null @@ -1,59 +0,0 @@ -# Generalia -setname: "ATLAS_Z0_8TEV_ZMASS" - -version: 1 - -version_comment: "Initial implementation" - -# References -arXiv: - url: "https://arxiv.org/pdf/2309.09318" -iNSPIRE: - url: "https://inspirehep.net/literature/2698794" -hepdata: - url: "https://www.hepdata.net/record/149333" - version: 1 - -nnpdf_metadata: - nnpdf31_process: "DY NC" - experiment: "ATLAS" - - -implemented_observables: - - - observable_name: "LL" - observable: - description: "ATLAS 8 TeV, Z boson rapidity distribution in full phase space of decay leptons" - label: r"$d\\sigma/d|\|y_{ll}||$" - units: "[pb]" - - ndata: 7 - - tables: [9] - process_type: DY_Z_Y - - plotting: - dataset_label: 'ATLAS 8 TeV $Z \to l^+ l^-$, absolute rapidity' - kinematics_override: identity - x_scale: linear - plot_x: y - - kinematic_coverage: [y, m_Z2, sqrts] - - kinematics: - variables: - y: {description: "Z > l+ l- absolute rapidity", label: '$|y_{ll}|$', units: ""} - m_Z2: {description: "Z boson mass squared", label: '$M_Z^2$', units: "GeV"} - sqrts: {description: "center of mass energy", label: '$\sqrt(s)$', units: "GeV"} - file: kinematics.yaml - - # Data - data_central: data.yaml - data_uncertainties: - - uncertainties.yaml - - # Theory - theory: - FK_tables: - - - ATLAS_Z0_8TEV_ZMASS - operation: 'null' \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml deleted file mode 100644 index 7e125d0135..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml +++ /dev/null @@ -1,71 +0,0 @@ -independent_variables: - - header: {name: '$|y|^{\ell\ell}$'} - values: - - {high: 0.8, low: 0.4} - - {high: 1.2, low: 0.8} - - {high: 1.6, low: 1.2} - - {high: 2, low: 1.6} - - {high: 2.4, low: 2} - - {high: 2.8, low: 2.4} - - {high: 3.6, low: 2.8} -dependent_variables: - - header: {name: '$d\sigma/d|y|^{\ell\ell}$ $\pm$ Total $\pm$ Luminosity', units: pb} - values: - - value: 353.152 - errors: - - {symerror: 0.612877, label: tot} - - {symerror: 6.35674, label: lumi} - - value: 345.985 - errors: - - {symerror: 0.614565, label: tot} - - {symerror: 6.22773, label: lumi} - - value: 336.195 - errors: - - {symerror: 0.631117, label: tot} - - {symerror: 6.05151, label: lumi} - - value: 322.483 - errors: - - {symerror: 0.867255, label: tot} - - {symerror: 5.80469, label: lumi} - - value: 303.973 - errors: - - {symerror: 1.2225, label: tot} - - {symerror: 5.47151, label: lumi} - - value: 273.198 - errors: - - {symerror: 1.47795, label: tot} - - {symerror: 4.91756, label: lumi} - - value: 173.171 - errors: - - {symerror: 1.44884, label: tot} - - {symerror: 3.11708, label: lumi} - - header: {name: 'N$^3$LO $\pm$ PDF $\pm$ scale var.', units: pb} - values: - - value: 343.835 - errors: - - {symerror: 5.0845, label: pdf} - - {symerror: 1.48899, label: scale} - - value: 337.198 - errors: - - {symerror: 4.9785, label: pdf} - - {symerror: 1.5366, label: scale} - - value: 327.154 - errors: - - {symerror: 4.8728, label: pdf} - - {symerror: 1.50239, label: scale} - - value: 312.773 - errors: - - {symerror: 4.6646, label: pdf} - - {symerror: 1.4265, label: scale} - - value: 292.641 - errors: - - {symerror: 4.3853, label: pdf} - - {symerror: 1.43681, label: scale} - - value: 260.733 - errors: - - {symerror: 4.0832, label: pdf} - - {symerror: 1.44803, label: scale} - - value: 168.482 - errors: - - {symerror: 3.1625, label: pdf} - - {symerror: 1.54132, label: scale} diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt deleted file mode 100644 index 4fe1bc9d51..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt +++ /dev/null @@ -1,7 +0,0 @@ -1.000000000000 0.771441698074 0.698377430439 0.470446109772 0.235730156302 0.135500997305 0.023962540552 -0.771441698074 1.000000000000 0.728683710098 0.490636169910 0.257601708174 0.143674910069 0.023399809375 -0.698377430439 0.728683710098 1.000000000000 0.524034738541 0.272780925035 0.151878938079 0.033453177661 -0.470446109772 0.490636169910 0.524034738541 0.999999940395 0.463345497847 0.285900026560 0.101109012961 -0.235730156302 0.257601708174 0.272780925035 0.463345497847 1.000000000000 0.564261615276 0.305788159370 -0.135500997305 0.143674910069 0.151878938079 0.285900026560 0.564261615276 1.000000119209 0.455123543739 -0.023962540552 0.023399809375 0.033453177661 0.101109012961 0.305788159370 0.455123543739 1.000000000000 diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml deleted file mode 100644 index 31706ee588..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml +++ /dev/null @@ -1,79 +0,0 @@ -definitions: - artificial_uncertainty_1: - description: artificial_uncertainty_1 - treatment: ADD - type: CORR - artificial_uncertainty_2: - description: artificial_uncertainty_2 - treatment: ADD - type: CORR - artificial_uncertainty_3: - description: artificial_uncertainty_3 - treatment: ADD - type: CORR - artificial_uncertainty_4: - description: artificial_uncertainty_4 - treatment: ADD - type: CORR - artificial_uncertainty_5: - description: artificial_uncertainty_5 - treatment: ADD - type: CORR - artificial_uncertainty_6: - description: artificial_uncertainty_6 - treatment: ADD - type: CORR - artificial_uncertainty_7: - description: artificial_uncertainty_7 - treatment: ADD - type: CORR -bins: -- artificial_uncertainty_1: 6.360849092233548 - artificial_uncertainty_2: -0.43736014852425575 - artificial_uncertainty_3: -0.17081282174067292 - artificial_uncertainty_4: 0.1343303399845492 - artificial_uncertainty_5: 0.1506396770871814 - artificial_uncertainty_6: 0.17839551357478534 - artificial_uncertainty_7: -0.17417703394997616 -- artificial_uncertainty_1: 6.233875520247695 - artificial_uncertainty_2: -0.42939370572372393 - artificial_uncertainty_3: -0.1581186015151157 - artificial_uncertainty_4: 0.12091345356933662 - artificial_uncertainty_5: 0.140047777147049 - artificial_uncertainty_6: -0.22584792937770715 - artificial_uncertainty_7: -0.08053516734437347 -- artificial_uncertainty_1: 6.060113000362857 - artificial_uncertainty_2: -0.4123698461117033 - artificial_uncertainty_3: -0.14680060602839212 - artificial_uncertainty_4: 0.10112405423267312 - artificial_uncertainty_5: 0.0894931999659005 - artificial_uncertainty_6: 0.04486740555676256 - artificial_uncertainty_7: 0.28681853399599 -- artificial_uncertainty_1: 5.836824335315856 - artificial_uncertainty_2: -0.27502106473581056 - artificial_uncertainty_3: 0.03159277272608425 - artificial_uncertainty_4: -0.12119507917842083 - artificial_uncertainty_5: -0.5349848732266431 - artificial_uncertainty_6: -0.0007764604112265232 - artificial_uncertainty_7: -0.02250579775755823 -- artificial_uncertainty_1: 5.539243636415269 - artificial_uncertainty_2: 0.31344828703761407 - artificial_uncertainty_3: 0.4545302042514127 - artificial_uncertainty_4: -0.6463383504190422 - artificial_uncertainty_5: 0.16156289938315516 - artificial_uncertainty_6: 0.0018754281204069558 - artificial_uncertainty_7: -0.0009901510871859873 -- artificial_uncertainty_1: 5.00099551940249 - artificial_uncertainty_2: 0.9002405764173007 - artificial_uncertainty_3: 0.5616642244049272 - artificial_uncertainty_4: 0.48016500342015245 - artificial_uncertainty_5: -0.017766174135644974 - artificial_uncertainty_6: -0.00035256711006794806 - artificial_uncertainty_7: 0.0016258067952645042 -- artificial_uncertainty_1: 3.1715884625027186 - artificial_uncertainty_2: 1.0482636206034448 - artificial_uncertainty_3: -0.8037615168161861 - artificial_uncertainty_4: -0.1055372371812821 - artificial_uncertainty_5: -0.017988003826124054 - artificial_uncertainty_6: -0.000893499833004754 - artificial_uncertainty_7: 0.0001651328837651984 diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py index 0b1c8e4dc1..0d358adae5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py index 87a9789fdc..fcda4a06a5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py index c22c00ee8d..0cd577753c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py @@ -1,10 +1,10 @@ import yaml -from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.utils import symmetrize_errors as se -from nnpdf_data.filter_utils.utils import trimat_to_fullmat as ttf +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import trimat_to_fullmat as ttf def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py index 0399a3049e..5f5c5af484 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py @@ -1,7 +1,7 @@ import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py index 13509f0a65..8397558851 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py index 86a9664109..d1bbb8538d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py index d61b7d3375..ba34402178 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MW_VALUE = 80.398 # GeV SQRT_S = 8_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py index d5cd43745e..040b44911f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc # MZ_VALUE = 91.1876 # GeV # MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py index b7a9b5b465..736ea6b856 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py @@ -1,8 +1,8 @@ import numpy import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta def artunc(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py index 7f3f74bacc..7f19469816 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py @@ -3,8 +3,8 @@ import artUnc import yaml -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py index 55bf4e9062..00505782ec 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py @@ -1,7 +1,7 @@ from manual_impl import artunc, jet_data, jet_sys import yaml -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py index 8a5176db0c..50e3f03421 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py @@ -1,3537 +1,74 @@ from math import sqrt -from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -jet_old_impl_list = [ - [ - '1', - 'DIS_1JET', - '1.750000000000e+02', - '9.000000000000e+00', - '3.190000000000e+02', - '7.042365878823e+01', - '1.901438787282e+00', - '7.042365878823e-01', - '1.000000000000e+00', - '7.130250486484e-01', - '1.010961455291e+00', - '6.718827732504e-01', - '9.531044964111e-01', - '2.517144109385e-01', - '3.572500464504e-01', - '2.515885537330e-01', - '3.572500464504e-01', - '3.521182939412e-01', - '5.000000000000e-01', - '4.225419527294e-01', - '6.000000000000e-01', - '2.042286104859e+00', - '2.900000000000e+00', - ], - [ - '2', - 'DIS_1JET', - '1.750000000000e+02', - '1.450000000000e+01', - '3.190000000000e+02', - '3.095350776162e+01', - '1.269093818226e+00', - '8.666982173254e-01', - '2.800000000000e+00', - '7.598162606841e-01', - '2.452246318915e+00', - '1.718173641914e-01', - '5.542497004702e-01', - '1.910967863178e-01', - '6.170584587557e-01', - '8.045980207445e-02', - '2.599375899303e-01', - '1.547675388081e-01', - '5.000000000000e-01', - '1.857210465697e-01', - '6.000000000000e-01', - '8.976517250870e-01', - '2.900000000000e+00', - ], - [ - '3', - 'DIS_1JET', - '1.750000000000e+02', - '2.400000000000e+01', - '3.190000000000e+02', - '8.082109035000e+00', - '5.172549782400e-01', - '2.828738162250e-01', - '3.500000000000e+00', - '2.743800000000e-01', - '3.400000000000e+00', - '1.976738222426e-02', - '2.447042700083e-01', - '3.679736009134e-02', - '4.552940319412e-01', - '8.082109035000e-03', - '1.000000000000e-01', - '4.041054517500e-02', - '5.000000000000e-01', - '4.849265421000e-02', - '6.000000000000e-01', - '2.343811620150e-01', - '2.900000000000e+00', - ], - [ - '4', - 'DIS_1JET', - '1.750000000000e+02', - '4.000000000000e+01', - 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sys_breakdown[i].append(float(old_impl[i][9])/2) + sys_breakdown[i].append(float(old_impl[i][11])/2) + sys_breakdown[i].append(float(old_impl[i][11])/2) sys_breakdown[i].append(float(old_impl[i][13])) sys_breakdown[i].append(float(old_impl[i][15])) sys_breakdown[i].append(float(old_impl[i][17])) - ( - sys_breakdown[i].append(float(old_impl[i][5]) * 0.005) - if is_jet - else sys_breakdown[i].append(float(old_impl[i][19])) - ) + sys_breakdown[i].append(float(old_impl[i][5])*0.005) if is_jet else sys_breakdown[i].append(float(old_impl[i][19])) sys_breakdown[i].append(float(old_impl[i][21])) return sys_breakdown @@ -3544,7 +81,6 @@ def sym_data(): dijet_data.append(float(dijet_old_impl_list[i][5])) return jet_data, dijet_data - def stat_lists(): jet_stat = [] dijet_stat = [] @@ -3553,12 +89,12 @@ def stat_lists(): dijet_stat.append(float(dijet_old_impl_list[i][6])) return jet_stat, dijet_stat - jet_data, dijet_data = sym_data() jet_stat, dijet_stat = stat_lists() jet_sys = sys_breakdown(jet_old_impl_list, True) dijet_sys = sys_breakdown(dijet_old_impl_list, False) -covmat = ctc(jet_stat + dijet_stat, [a / 100 for a in corMatArray]) +covmat = ctc(jet_stat + dijet_stat, [a/100 for a in corMatArray]) + +artunc = cta(48, covmat, ) -artunc = cta(48, covmat) diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py index b7a9b5b465..736ea6b856 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py @@ -1,8 +1,8 @@ import numpy import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta def artunc(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py index c638b42a41..ecf4dff877 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py @@ -3,8 +3,8 @@ import artUnc import yaml -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py index 8c3b997d5b..39f732434d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py @@ -1,7 +1,7 @@ from manual_impl import artunc, dijet_data, dijet_sys import yaml -from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py index 8a5176db0c..50e3f03421 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py @@ -1,3537 +1,74 @@ from math import sqrt -from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc -from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -jet_old_impl_list = [ - [ - '1', - 'DIS_1JET', - '1.750000000000e+02', - '9.000000000000e+00', - '3.190000000000e+02', - '7.042365878823e+01', - '1.901438787282e+00', - '7.042365878823e-01', - '1.000000000000e+00', - '7.130250486484e-01', - '1.010961455291e+00', - '6.718827732504e-01', - '9.531044964111e-01', - '2.517144109385e-01', - '3.572500464504e-01', - '2.515885537330e-01', - '3.572500464504e-01', - '3.521182939412e-01', - '5.000000000000e-01', - '4.225419527294e-01', - '6.000000000000e-01', - '2.042286104859e+00', - '2.900000000000e+00', - ], - [ - '2', - 'DIS_1JET', - '1.750000000000e+02', - '1.450000000000e+01', - '3.190000000000e+02', - '3.095350776162e+01', - '1.269093818226e+00', - '8.666982173254e-01', - '2.800000000000e+00', - '7.598162606841e-01', - '2.452246318915e+00', - '1.718173641914e-01', - '5.542497004702e-01', - '1.910967863178e-01', - '6.170584587557e-01', - '8.045980207445e-02', - '2.599375899303e-01', - '1.547675388081e-01', - '5.000000000000e-01', - '1.857210465697e-01', - '6.000000000000e-01', - '8.976517250870e-01', - '2.900000000000e+00', - ], - [ - '3', - 'DIS_1JET', - '1.750000000000e+02', - '2.400000000000e+01', - '3.190000000000e+02', - '8.082109035000e+00', - '5.172549782400e-01', - '2.828738162250e-01', - '3.500000000000e+00', - '2.743800000000e-01', - '3.400000000000e+00', - '1.976738222426e-02', - '2.447042700083e-01', - '3.679736009134e-02', - '4.552940319412e-01', - '8.082109035000e-03', - '1.000000000000e-01', - '4.041054517500e-02', - '5.000000000000e-01', - '4.849265421000e-02', - '6.000000000000e-01', - '2.343811620150e-01', - '2.900000000000e+00', - ], - [ - '4', - 'DIS_1JET', - '1.750000000000e+02', - '4.000000000000e+01', - '3.190000000000e+02', - '9.125014074304e-01', - '1.396127153368e-01', - '1.067626646694e-01', - '1.170000000000e+01', - '4.688994472166e-02', - '5.118073262173e+00', - '1.519286117216e-03', - '1.657483653351e-01', - '4.299338659215e-03', - '4.704529347867e-01', - '1.991738317891e-03', - '2.182723557106e-01', - '4.562507037152e-03', - '5.000000000000e-01', - '5.475008444582e-03', - '6.000000000000e-01', - '2.646254081548e-02', - '2.900000000000e+00', - ], - [ - '5', - 'DIS_1JET', - '2.350000000000e+02', - '9.000000000000e+00', - '3.190000000000e+02', - '5.493706846573e+01', - '1.648112053972e+00', - '-3.296224107944e-01', - '-6.000000000000e-01', - '5.220401134013e-01', - '9.531044964111e-01', - '6.074575198510e-01', - '1.107945704936e+00', - '4.273370774492e-01', - '7.782554801857e-01', - '1.960665379920e-01', - '3.568929749397e-01', - '2.746853423286e-01', - '5.000000000000e-01', - '3.296224107944e-01', - '6.000000000000e-01', - '1.593174985506e+00', - '2.900000000000e+00', - ], - [ - '6', - 'DIS_1JET', - '2.350000000000e+02', - '1.450000000000e+01', - '3.190000000000e+02', - '2.680000000000e+01', - '1.098800000000e+00', - '9.112000000000e-01', - '3.400000000000e+00', - '6.432000000000e-01', - '2.400000000000e+00', - '1.072000000000e-01', - '4.000000000000e-01', - '1.608000000000e-01', - '6.000000000000e-01', - '8.040000000000e-02', - '3.000000000000e-01', - '1.340000000000e-01', - '5.000000000000e-01', - '1.608000000000e-01', - '6.000000000000e-01', - '7.772000000000e-01', - '2.900000000000e+00', - ], - [ - '7', - 'DIS_1JET', - '2.350000000000e+02', - '2.400000000000e+01', - '3.190000000000e+02', - '7.013496240129e+00', - '4.628907518485e-01', - '3.366478195262e-01', - '4.800000000000e+00', - '2.492988998672e-01', - '3.551005871609e+00', - '1.404103000000e-02', - '2.000000000000e-01', - '3.893063895065e-02', - '5.548042274342e-01', - '2.505571857565e-02', - '3.572500464504e-01', - '3.506748120064e-02', - '5.000000000000e-01', - '4.208097744077e-02', - '6.000000000000e-01', - '2.033913909637e-01', - '2.900000000000e+00', - ], - [ - '8', - 'DIS_1JET', - 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sys_breakdown[i].append(float(old_impl[i][9])/2) + sys_breakdown[i].append(float(old_impl[i][11])/2) + sys_breakdown[i].append(float(old_impl[i][11])/2) sys_breakdown[i].append(float(old_impl[i][13])) sys_breakdown[i].append(float(old_impl[i][15])) sys_breakdown[i].append(float(old_impl[i][17])) - ( - sys_breakdown[i].append(float(old_impl[i][5]) * 0.005) - if is_jet - else sys_breakdown[i].append(float(old_impl[i][19])) - ) + sys_breakdown[i].append(float(old_impl[i][5])*0.005) if is_jet else sys_breakdown[i].append(float(old_impl[i][19])) sys_breakdown[i].append(float(old_impl[i][21])) return sys_breakdown @@ -3544,7 +81,6 @@ def sym_data(): dijet_data.append(float(dijet_old_impl_list[i][5])) return jet_data, dijet_data - def stat_lists(): jet_stat = [] dijet_stat = [] @@ -3553,12 +89,12 @@ def stat_lists(): dijet_stat.append(float(dijet_old_impl_list[i][6])) return jet_stat, dijet_stat - jet_data, dijet_data = sym_data() jet_stat, dijet_stat = stat_lists() jet_sys = sys_breakdown(jet_old_impl_list, True) dijet_sys = sys_breakdown(dijet_old_impl_list, False) -covmat = ctc(jet_stat + dijet_stat, [a / 100 for a in corMatArray]) +covmat = ctc(jet_stat + dijet_stat, [a/100 for a in corMatArray]) + +artunc = cta(48, covmat, ) -artunc = cta(48, covmat) diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py index 00f70cfbd5..cec61ffaac 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py index f0f14cb1a2..4b0d1a73e5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py index c61279cbe8..d63c7f9cab 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py index 87c54145aa..6a2a2cb286 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py index d7eba548ab..d485a62c81 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV SQRT_S = 13_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py index f875fa3478..ddab8f5a32 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py @@ -4,7 +4,10 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc, percentage_to_absolute +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import ( + covmat_to_artunc, + percentage_to_absolute, +) MZ_VALUE = 91.1876 # GeV SQRT_S = 7_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py index 91195801d9..a603f11e5b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py index 9bd9881e2e..8edf001649 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV SQRT_S = 8_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py index 4ecaf473a7..11f1899ddb 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.filter_utils.utils import covmat_to_artunc +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml index 878a047c2a..f023ef4eda 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml @@ -21,7 +21,7 @@ implemented_observables: description: Integrability dataset for Polarized Gluon label: 'polarized integrability: $x \delta g$ PDF $Q^2=1$ GeV$^2$' units: '' - process_type: INTEG_XDG + process_type: DIS_XDG tables: [] npoints: [] ndata: 1 @@ -60,7 +60,7 @@ implemented_observables: description: Integrability dataset for Polarized Singlet label: 'polarized integrability: $x \delta \Sigma$ PDF $Q^2=1$ GeV$^2$' units: '' - process_type: INTEG_XDSIGMA + process_type: DIS_XDSIGMA tables: [] npoints: [] ndata: 1 @@ -99,7 +99,7 @@ implemented_observables: description: Integrability to be used in the flavour basis label: 'integrability dataset: $xT_8$ PDF, Q=Q_1' units: '' - process_type: INTEG_XT8 + process_type: DIS_XT8 tables: [] npoints: [] ndata: 1 @@ -135,7 +135,7 @@ implemented_observables: description: Integrability to be used in the flavour basis label: 'integrability dataset: $xT_3$ PDF, Q=Q_1' units: '' - process_type: INTEG_XT8 + process_type: DIS_XT8 tables: [] npoints: [] ndata: 1 diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml index a42c79d69e..034ec37b7d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml @@ -1,137 +1,205 @@ bins: -- x: +- k1: min: null mid: 5.0e-07 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 1.940766723678e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 7.533150951473e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 2.924017738213e-05 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0001134967265154 max: 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b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-CCE-17PTS.yaml @@ -1,137 +1,205 @@ bins: -- x: +- k1: min: null mid: 5.0e-07 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 1.940766723678e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 7.533150951473e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 2.924017738213e-05 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0001134967265154 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0004405413401349 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.001709975946677 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.006637328831201 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.02576301385941 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.1 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.18 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.26 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.34 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.42 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.5 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.58 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.66 max: null - Q2: + k2: min: null mid: 5.0 max: null + k3: + min: null + mid: 0.0 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-CCP-17PTS.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-CCP-17PTS.yaml index a42c79d69e..034ec37b7d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-CCP-17PTS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-CCP-17PTS.yaml @@ -1,137 +1,205 @@ bins: -- x: +- k1: min: null mid: 5.0e-07 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 1.940766723678e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 7.533150951473e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 2.924017738213e-05 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0001134967265154 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0004405413401349 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.001709975946677 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.006637328831201 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.02576301385941 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 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max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C.yaml index 24b058bef1..26edc37705 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C.yaml @@ -1,161 +1,241 @@ bins: -- x: +- k1: min: null mid: 5.0e-07 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 1.940766723678e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 7.533150951473e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 2.924017738213e-05 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0001134967265154 max: null 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max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2D.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2D.yaml index 24b058bef1..26edc37705 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2D.yaml @@ -1,161 +1,241 @@ bins: -- x: +- k1: min: null mid: 5.0e-07 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 1.940766723678e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 7.533150951473e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 2.924017738213e-05 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0001134967265154 max: null 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max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2S.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2S.yaml index 24b058bef1..26edc37705 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2S.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2S.yaml @@ -1,161 +1,241 @@ bins: -- x: +- k1: min: null mid: 5.0e-07 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 1.940766723678e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 7.533150951473e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 2.924017738213e-05 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0001134967265154 max: null 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max: null + k3: + min: null + mid: 0.0 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUQ.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUQ.yaml index 24b058bef1..26edc37705 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUQ.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUQ.yaml @@ -1,161 +1,241 @@ bins: -- x: +- k1: min: null mid: 5.0e-07 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 1.940766723678e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 7.533150951473e-06 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 2.924017738213e-05 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0001134967265154 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.0004405413401349 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.001709975946677 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.006637328831201 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.02576301385941 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.1 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.18 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.26 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.34 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.42 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.5 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.58 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.66 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.74 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.82 max: null - Q2: + k2: min: null mid: 5.0 max: null -- x: + k3: + min: null + mid: 0.0 + max: null +- k1: min: null mid: 0.9 max: null - Q2: + k2: min: null mid: 5.0 max: null + k3: + min: null + mid: 0.0 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml index d9dffbdaa0..e12fcef16d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml @@ -17,7 +17,7 @@ implemented_observables: description: Fixed-Target Drell-Yan label: 'positivity dataset: DY cross section $\frac{d^2\sigma_{s\bar{s}}}{dM^2dy}$' units: '' - process_type: POS_PPY_CON_ST + process_type: DYP_PPY_CON_ST tables: [] npoints: [] ndata: 20 @@ -56,7 +56,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' units: '' - process_type: POS_F2 + process_type: DIS_F2C tables: [] npoints: [] ndata: 20 @@ -64,19 +64,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization Scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_F2C.yaml theory: @@ -91,7 +96,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c$ structure function $F_2^{W^-,c}$' units: '' - process_type: POS_F2 + process_type: DIS_F2C_CCE tables: [] npoints: [] ndata: 17 @@ -99,19 +104,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $c$ structure function $F_2^{W^-,c}$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization Scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_F2C-CCE-17PTS.yaml theory: @@ -126,7 +136,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $d+\bar{d}$ structure function $F_2^d$' units: '' - process_type: POS_F2 + process_type: DIS_F2d tables: [] npoints: [] ndata: 20 @@ -134,19 +144,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $d+\bar{d}$ structure function $F_2^d$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization Scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_F2D.yaml theory: @@ -161,7 +176,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $s+\bar{s}$ structure function $F_2^s$' units: '' - process_type: POS_F2 + process_type: DIS_F2S tables: [] npoints: [] ndata: 20 @@ -169,19 +184,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $s+\bar{s}$ structure function $F_2^s$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization Scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_F2S.yaml theory: @@ -196,7 +216,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS light quark longitudinal structure function $F_L^l$' units: '' - process_type: POS_FLL + process_type: DIS_FLL tables: [] npoints: [] ndata: 20 @@ -237,7 +257,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xc$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XCQ tables: [] npoints: [] ndata: 20 @@ -245,19 +265,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xc$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XCQ.yaml theory: @@ -271,7 +296,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xd$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XDQ tables: [] npoints: [] ndata: 20 @@ -279,19 +304,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xd$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XDQ.yaml theory: @@ -306,7 +336,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $x\bar{s}$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XSB tables: [] npoints: [] ndata: 20 @@ -314,19 +344,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $x\bar{s}$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XSB.yaml theory: @@ -341,7 +376,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $x\bar{u}$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XUB tables: [] npoints: [] ndata: 20 @@ -349,19 +384,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $x\bar{u}$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XUB.yaml theory: @@ -376,7 +416,7 @@ implemented_observables: description: Fixed-Target Drell-Yan label: 'positivity dataset: DY cross section $\frac{d^2\sigma_{d\bar{d}}}{dM^2dy}$' units: '' - process_type: POS_PPY_CON_DW + process_type: DYP_PPY_CON_DW tables: [] npoints: [] ndata: 20 @@ -415,7 +455,7 @@ implemented_observables: description: Fixed-Target Drell-Yan label: 'positivity dataset: DY cross section $\frac{d^2\sigma_{u\bar{u}}}{dM^2dy}$' units: '' - process_type: POS_PPY_CON_UP + process_type: DYP_PPY_CON_UP tables: [] npoints: [] ndata: 20 @@ -454,7 +494,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' units: '' - process_type: POS_F2 + process_type: DIS_F2C tables: [] npoints: [] ndata: 17 @@ -462,19 +502,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization Scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_F2C-17PTS.yaml theory: @@ -489,7 +534,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: CC DIS $\bar{c}$ structure function $F_2^{W^+,c}$' units: '' - process_type: POS_F2 + process_type: DIS_F2C_CCP tables: [] npoints: [] ndata: 17 @@ -497,19 +542,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: CC DIS $\bar{c}$ structure function $F_2^{W^+,c}$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization Scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_F2C-CCP-17PTS.yaml theory: @@ -524,7 +574,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $u+\bar{u}$ structure function $F_2^u$' units: '' - process_type: POS_F2 + process_type: DIS_F2U tables: [] npoints: [] ndata: 20 @@ -532,19 +582,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $u+\bar{u}$ structure function $F_2^u$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization Scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_F2U.yaml theory: @@ -559,7 +614,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS light quark longitudinal structure function $F_L^l$' units: '' - process_type: POS_FLL + process_type: DIS_FLL tables: [] npoints: [] ndata: 19 @@ -600,7 +655,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $x\bar{d}$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XDB tables: [] npoints: [] ndata: 20 @@ -608,19 +663,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $x\bar{d}$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XDB.yaml theory: @@ -635,7 +695,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xg$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XGL tables: [] npoints: [] ndata: 20 @@ -643,19 +703,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xg$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XGL.yaml theory: @@ -670,7 +735,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xs$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XSQ tables: [] npoints: [] ndata: 20 @@ -678,19 +743,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xs$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XSQ.yaml theory: @@ -705,7 +775,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xu$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XPDF + process_type: DIS_XUQ tables: [] npoints: [] ndata: 20 @@ -713,19 +783,24 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xu$ PDF $Q^2=5$ GeV$^2$' - plot_x: x + plot_x: k1 kinematic_coverage: - - x - - Q2 + - k1 + - k2 + - k3 kinematics: variables: - x: - description: Bjorken x - label: x + k1: + description: Variable k1 + label: k1 units: '' - Q2: - description: Factorization scale - label: Q2 + k2: + description: Variable k2 + label: k2 + units: '' + k3: + description: Variable k3 + label: k3 units: '' file: kinematics_XUQ.yaml theory: @@ -740,7 +815,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta g$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XDG + process_type: DIS_XDG tables: [] npoints: [] ndata: 20 @@ -780,7 +855,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta d$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XDDQ + process_type: DIS_XDDQ tables: [] npoints: [] ndata: 20 @@ -822,7 +897,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta s$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XDSQ + process_type: DIS_XDSQ tables: [] npoints: [] ndata: 20 @@ -864,7 +939,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta u$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: POS_XDUQ + process_type: DIS_XDUQ tables: [] npoints: [] ndata: 20 diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py index 66c931644a..e6c5b3fa0b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py index 9ecf7b5024..1804a8e969 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py index 3ab3b10a21..ce56dd4dab 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002000.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002000.yaml deleted file mode 100644 index afbab80d4b..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002000.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_000 -Comments: NNPDF4.0 N3LO alphas=0.106 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.106 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002001.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002001.yaml deleted file mode 100644 index b702ec67ce..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002001.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_001 -Comments: NNPDF4.0 N3LO alphas=0.114 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.114 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002002.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002002.yaml deleted file mode 100644 index 5c05cba3cb..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002002.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_002 -Comments: NNPDF4.0 N3LO alphas=0.115 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.115 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002003.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002003.yaml deleted file mode 100644 index 4ea32913ef..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002003.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_003 -Comments: NNPDF4.0 N3LO alphas=0.116 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.116 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002004.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002004.yaml deleted file mode 100644 index fd9c5e281b..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002004.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_004 -Comments: NNPDF4.0 N3LO alphas=0.117 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.117 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002006.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002006.yaml deleted file mode 100644 index 23d0bc8c5a..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002006.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_006 -Comments: NNPDF4.0 N3LO alphas=0.119 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.119 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002007.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002007.yaml deleted file mode 100644 index 2e626d7854..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002007.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_007 -Comments: NNPDF4.0 N3LO alphas=0.120 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.120 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002008.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002008.yaml deleted file mode 100644 index 96e2a12115..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002008.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_008 -Comments: NNPDF4.0 N3LO alphas=0.121 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.121 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002009.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002009.yaml deleted file mode 100644 index 7f02ea7f3a..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002009.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_009 -Comments: NNPDF4.0 N3LO alphas=0.122 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.122 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002010.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002010.yaml deleted file mode 100644 index c953c33a0a..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002010.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_010 -Comments: NNPDF4.0 N3LO alphas=0.123 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.123 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002011.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002011.yaml deleted file mode 100644 index 401637ce5c..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002011.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_011 -Comments: NNPDF4.0 N3LO alphas=0.124 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.124 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002012.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002012.yaml deleted file mode 100644 index 6cf2197209..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002012.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_012 -Comments: NNPDF4.0 N3LO alphas=0.125 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.125 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002013.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002013.yaml deleted file mode 100644 index ef948691e7..0000000000 --- a/nnpdf_data/nnpdf_data/theory_cards/40002013.yaml +++ /dev/null @@ -1,47 +0,0 @@ -ID: 40_002_013 -Comments: NNPDF4.0 N3LO alphas=0.130 -CKM: -- 0.97428 -- 0.2253 -- 0.00347 -- 0.2252 -- 0.97345 -- 0.041 -- 0.00862 -- 0.0403 -- 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 -MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 -SIN2TW: 0.23126 -TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.130 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/722.yaml b/nnpdf_data/nnpdf_data/theory_cards/722.yaml index f6bf79b6f1..2622647af3 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/722.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/722.yaml @@ -1,5 +1,32 @@ ID: 722 -Comments: NNPDF4.0 N3LO alphas=0.118 with new pipeline, no N3LO ad variation, XIF=1.0, XIR=1.0 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -10,38 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -DAMP: 0 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 4 -n3lo_ad_variation: [0,0,0,0,0,0,0] -n3lo_cf_variation: 0 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 0) +global_nx: 0 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/723.yaml b/nnpdf_data/nnpdf_data/theory_cards/723.yaml index fcebfdfb5d..cecf813beb 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/723.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/723.yaml @@ -1,3 +1,32 @@ +ID: 723 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [1, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 723 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (1, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 1 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/724.yaml b/nnpdf_data/nnpdf_data/theory_cards/724.yaml index bb7347197a..47b5e2d38e 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/724.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/724.yaml @@ -1,3 +1,32 @@ +ID: 724 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [2, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 724 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (2, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 2 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/725.yaml b/nnpdf_data/nnpdf_data/theory_cards/725.yaml index 1a5e8151cc..ba9ad896cd 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/725.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/725.yaml @@ -1,3 +1,32 @@ +ID: 725 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [3, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 725 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (3, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 3 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/726.yaml b/nnpdf_data/nnpdf_data/theory_cards/726.yaml index 5a8a18b279..535e3011e1 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/726.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/726.yaml @@ -1,3 +1,32 @@ +ID: 726 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [4, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 726 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (4, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 4 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/727.yaml b/nnpdf_data/nnpdf_data/theory_cards/727.yaml index d514adbe51..5160499720 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/727.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/727.yaml @@ -1,3 +1,32 @@ +ID: 727 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [5, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 727 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (5, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 5 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/728.yaml b/nnpdf_data/nnpdf_data/theory_cards/728.yaml index 2477d9802d..fbcd440bc0 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/728.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/728.yaml @@ -1,3 +1,32 @@ +ID: 728 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [6, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 728 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (6, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 6 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/729.yaml b/nnpdf_data/nnpdf_data/theory_cards/729.yaml index a69b74c025..0d90808126 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/729.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/729.yaml @@ -1,3 +1,32 @@ +ID: 729 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [7, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 729 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (7, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 7 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/730.yaml b/nnpdf_data/nnpdf_data/theory_cards/730.yaml index 70d2b061bf..e7d6ca94fa 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/730.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/730.yaml @@ -1,3 +1,32 @@ +ID: 730 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [8, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 730 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (8, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 8 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/731.yaml b/nnpdf_data/nnpdf_data/theory_cards/731.yaml index c0eb2ae0c9..7029054825 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/731.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/731.yaml @@ -1,3 +1,32 @@ +ID: 731 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [9, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 731 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (9, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 9 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/732.yaml b/nnpdf_data/nnpdf_data/theory_cards/732.yaml index c764fe73dd..fb57e9a65a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/732.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/732.yaml @@ -1,3 +1,32 @@ +ID: 732 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [10, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 732 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (10, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 10 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/733.yaml b/nnpdf_data/nnpdf_data/theory_cards/733.yaml index da82b7f030..ec4c6e9aeb 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/733.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/733.yaml @@ -1,3 +1,32 @@ +ID: 733 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [11, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 733 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (11, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 11 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/734.yaml b/nnpdf_data/nnpdf_data/theory_cards/734.yaml index 93f6f32920..aaa9922943 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/734.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/734.yaml @@ -1,3 +1,32 @@ +ID: 734 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [12, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 734 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (12, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 12 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/735.yaml b/nnpdf_data/nnpdf_data/theory_cards/735.yaml index 694156e6ba..fd4b41a0fc 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/735.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/735.yaml @@ -1,3 +1,32 @@ +ID: 735 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [13, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 735 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (13, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 13 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/736.yaml b/nnpdf_data/nnpdf_data/theory_cards/736.yaml index 6db47e08cd..6aad1ee57d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/736.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/736.yaml @@ -1,3 +1,32 @@ +ID: 736 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [14, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 736 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (14, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 14 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/737.yaml b/nnpdf_data/nnpdf_data/theory_cards/737.yaml index 5580d26da3..9f0c4b76b0 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/737.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/737.yaml @@ -1,3 +1,32 @@ +ID: 737 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [15, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 737 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (15, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 15 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/738.yaml b/nnpdf_data/nnpdf_data/theory_cards/738.yaml index d8dad59de7..cb56abf388 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/738.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/738.yaml @@ -1,3 +1,32 @@ +ID: 738 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [16, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 738 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (16, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 16 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/739.yaml b/nnpdf_data/nnpdf_data/theory_cards/739.yaml index 00ba87e480..64fb7ca703 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/739.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/739.yaml @@ -1,3 +1,32 @@ +ID: 739 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [17, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 739 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (17, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 17 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/740.yaml b/nnpdf_data/nnpdf_data/theory_cards/740.yaml index 1f4df3c2ce..0b1d10cdd2 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/740.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/740.yaml @@ -1,3 +1,32 @@ +ID: 740 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [18, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 740 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (18, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 18 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/741.yaml b/nnpdf_data/nnpdf_data/theory_cards/741.yaml index 612ace7ebb..7d65c647de 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/741.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/741.yaml @@ -1,3 +1,32 @@ +ID: 741 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [19, 0, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 741 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (19, 0, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 19 -- 0 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/742.yaml b/nnpdf_data/nnpdf_data/theory_cards/742.yaml index 0873e42030..2c31c5ba35 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/742.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/742.yaml @@ -1,3 +1,32 @@ +ID: 742 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 1, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 742 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 1, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 1 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/743.yaml b/nnpdf_data/nnpdf_data/theory_cards/743.yaml index 3a80bd656c..d8fcfa553a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/743.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/743.yaml @@ -1,3 +1,32 @@ +ID: 743 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 2, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 743 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 2, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 2 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/744.yaml b/nnpdf_data/nnpdf_data/theory_cards/744.yaml index aa8dfe9c32..31f3589b2d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/744.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/744.yaml @@ -1,3 +1,32 @@ +ID: 744 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 3, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 744 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 3, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 3 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/745.yaml b/nnpdf_data/nnpdf_data/theory_cards/745.yaml index 9aad630cfe..932b553768 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/745.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/745.yaml @@ -1,3 +1,32 @@ +ID: 745 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 4, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 745 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 4, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 4 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/746.yaml b/nnpdf_data/nnpdf_data/theory_cards/746.yaml index 1c26eb5e3d..8d42e6ae4b 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/746.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/746.yaml @@ -1,3 +1,32 @@ +ID: 746 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 5, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 746 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 5, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 5 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/747.yaml b/nnpdf_data/nnpdf_data/theory_cards/747.yaml index d65478bdbf..7f3d460769 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/747.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/747.yaml @@ -1,3 +1,32 @@ +ID: 747 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 6, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 747 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 6, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 6 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/748.yaml b/nnpdf_data/nnpdf_data/theory_cards/748.yaml index 1f08669a10..953ae6166e 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/748.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/748.yaml @@ -1,3 +1,32 @@ +ID: 748 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 7, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 748 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 7, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 7 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/749.yaml b/nnpdf_data/nnpdf_data/theory_cards/749.yaml index 9dd383454a..4620ef0c6a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/749.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/749.yaml @@ -1,3 +1,32 @@ +ID: 749 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 8, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 749 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 8, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 8 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/750.yaml b/nnpdf_data/nnpdf_data/theory_cards/750.yaml index c5615fcdf4..5df5608f59 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/750.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/750.yaml @@ -1,3 +1,32 @@ +ID: 750 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 9, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 750 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 9, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 9 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/751.yaml b/nnpdf_data/nnpdf_data/theory_cards/751.yaml index b95943b8f3..01f21d7880 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/751.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/751.yaml @@ -1,3 +1,32 @@ +ID: 751 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 10, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 751 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 10, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 10 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/752.yaml b/nnpdf_data/nnpdf_data/theory_cards/752.yaml index 389acd6ae4..fcf4a10f3e 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/752.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/752.yaml @@ -1,3 +1,32 @@ +ID: 752 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 11, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 752 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 11, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 11 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/753.yaml b/nnpdf_data/nnpdf_data/theory_cards/753.yaml index 0f85c1df2b..02b10dbf87 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/753.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/753.yaml @@ -1,3 +1,32 @@ +ID: 753 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 12, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 753 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 12, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 12 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/754.yaml b/nnpdf_data/nnpdf_data/theory_cards/754.yaml index 5820a38eb5..8ad96b61e8 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/754.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/754.yaml @@ -1,3 +1,32 @@ +ID: 754 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 13, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 754 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 13, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 13 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/755.yaml b/nnpdf_data/nnpdf_data/theory_cards/755.yaml index fabfe95b5d..25ca6d239b 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/755.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/755.yaml @@ -1,3 +1,32 @@ +ID: 755 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 14, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 755 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 14, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 14 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/756.yaml b/nnpdf_data/nnpdf_data/theory_cards/756.yaml index f218900170..1f9264aafd 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/756.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/756.yaml @@ -1,3 +1,32 @@ +ID: 756 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 15, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 756 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 15, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 15 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/757.yaml b/nnpdf_data/nnpdf_data/theory_cards/757.yaml index f147e573d7..64ecb6fd6e 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/757.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/757.yaml @@ -1,3 +1,32 @@ +ID: 757 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 16, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 757 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 16, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 16 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/758.yaml b/nnpdf_data/nnpdf_data/theory_cards/758.yaml index 0bf357dfd2..b5e354e2b8 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/758.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/758.yaml @@ -1,3 +1,32 @@ +ID: 758 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 17, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 758 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 17, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 17 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/759.yaml b/nnpdf_data/nnpdf_data/theory_cards/759.yaml index 48b7de68b2..41e1fc9941 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/759.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/759.yaml @@ -1,3 +1,32 @@ +ID: 759 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 18, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 759 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 18, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 18 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/760.yaml b/nnpdf_data/nnpdf_data/theory_cards/760.yaml index a0cb058203..38bb57c478 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/760.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/760.yaml @@ -1,3 +1,32 @@ +ID: 760 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 19, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 760 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 19, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 19 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/761.yaml b/nnpdf_data/nnpdf_data/theory_cards/761.yaml index 6846418361..7be08cffc0 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/761.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/761.yaml @@ -1,3 +1,32 @@ +ID: 761 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 20, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 761 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 20, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 20 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/762.yaml b/nnpdf_data/nnpdf_data/theory_cards/762.yaml index 2c0de30417..d26684046a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/762.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/762.yaml @@ -1,3 +1,32 @@ +ID: 762 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 21, 0, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 762 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 21, 0, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 21 -- 0 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/763.yaml b/nnpdf_data/nnpdf_data/theory_cards/763.yaml index c8d7874409..864788a535 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/763.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/763.yaml @@ -1,3 +1,32 @@ +ID: 763 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 1, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 763 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 1, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 1 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/764.yaml b/nnpdf_data/nnpdf_data/theory_cards/764.yaml index b36b8d58ee..f2900875d5 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/764.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/764.yaml @@ -1,3 +1,32 @@ +ID: 764 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 2, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 764 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 2, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 2 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/765.yaml b/nnpdf_data/nnpdf_data/theory_cards/765.yaml index e5fddcfa91..4a9bf2ccf1 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/765.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/765.yaml @@ -1,3 +1,32 @@ +ID: 765 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 3, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 765 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 3, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 3 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/766.yaml b/nnpdf_data/nnpdf_data/theory_cards/766.yaml index 0329045ddc..cd019666f6 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/766.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/766.yaml @@ -1,3 +1,32 @@ +ID: 766 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 4, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 766 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 4, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 4 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/767.yaml b/nnpdf_data/nnpdf_data/theory_cards/767.yaml index c27364bc6b..b472654ff8 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/767.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/767.yaml @@ -1,3 +1,32 @@ +ID: 767 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 5, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 767 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 5, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 5 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/768.yaml b/nnpdf_data/nnpdf_data/theory_cards/768.yaml index 898bfe0363..05a9660322 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/768.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/768.yaml @@ -1,3 +1,32 @@ +ID: 768 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 6, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 768 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 6, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 6 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/769.yaml b/nnpdf_data/nnpdf_data/theory_cards/769.yaml index f80f52b709..c258e4778f 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/769.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/769.yaml @@ -1,3 +1,32 @@ +ID: 769 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 7, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 769 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 7, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 7 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/770.yaml b/nnpdf_data/nnpdf_data/theory_cards/770.yaml index ec1fdabb98..6f707f1710 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/770.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/770.yaml @@ -1,3 +1,32 @@ +ID: 770 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 8, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 770 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 8, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 8 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/771.yaml b/nnpdf_data/nnpdf_data/theory_cards/771.yaml index 2e1d4d9acb..fe21592023 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/771.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/771.yaml @@ -1,3 +1,32 @@ +ID: 771 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 9, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 771 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 9, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 9 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/772.yaml b/nnpdf_data/nnpdf_data/theory_cards/772.yaml index 1b1b7cade1..73723224a5 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/772.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/772.yaml @@ -1,3 +1,32 @@ +ID: 772 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 10, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 772 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 10, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 10 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/773.yaml b/nnpdf_data/nnpdf_data/theory_cards/773.yaml index 123be4241b..48ace19288 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/773.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/773.yaml @@ -1,3 +1,32 @@ +ID: 773 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 11, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 773 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 11, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 11 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/774.yaml b/nnpdf_data/nnpdf_data/theory_cards/774.yaml index 9fe611943a..f3eeb0589a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/774.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/774.yaml @@ -1,3 +1,32 @@ +ID: 774 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 12, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 774 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 12, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 12 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/775.yaml b/nnpdf_data/nnpdf_data/theory_cards/775.yaml index 5b8d0d949a..d72aa8c7df 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/775.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/775.yaml @@ -1,3 +1,32 @@ +ID: 775 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 13, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 775 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 13, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 13 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/776.yaml b/nnpdf_data/nnpdf_data/theory_cards/776.yaml index 88b851725e..b83ca251e3 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/776.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/776.yaml @@ -1,3 +1,32 @@ +ID: 776 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 14, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 776 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 14, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 14 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/777.yaml b/nnpdf_data/nnpdf_data/theory_cards/777.yaml index 8283a89ba3..3bd23d3442 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/777.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/777.yaml @@ -1,3 +1,32 @@ +ID: 777 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 15, 0, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 777 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 15, 0) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 15 -- 0 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/778.yaml b/nnpdf_data/nnpdf_data/theory_cards/778.yaml index 350568fd08..3c19b90d47 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/778.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/778.yaml @@ -1,3 +1,32 @@ +ID: 778 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 1, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 778 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 1) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 0 -- 1 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/779.yaml b/nnpdf_data/nnpdf_data/theory_cards/779.yaml index 9c0c5f6939..bf3c68fc1e 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/779.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/779.yaml @@ -1,3 +1,32 @@ +ID: 779 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 2, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 779 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 2) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 0 -- 2 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/780.yaml b/nnpdf_data/nnpdf_data/theory_cards/780.yaml index 946a6e0b69..d03b7afb1b 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/780.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/780.yaml @@ -1,3 +1,32 @@ +ID: 780 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 3, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 780 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 3) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 0 -- 3 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/781.yaml b/nnpdf_data/nnpdf_data/theory_cards/781.yaml index f0887e5bfa..e3783bfab0 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/781.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/781.yaml @@ -1,3 +1,32 @@ +ID: 781 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 4, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 781 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 4) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 0 -- 4 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/782.yaml b/nnpdf_data/nnpdf_data/theory_cards/782.yaml index 108ba61d81..21438c9f97 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/782.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/782.yaml @@ -1,3 +1,32 @@ +ID: 782 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 5, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 782 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 5) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 0 -- 5 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/783.yaml b/nnpdf_data/nnpdf_data/theory_cards/783.yaml index 5277d3a956..4a8338e207 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/783.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/783.yaml @@ -1,3 +1,32 @@ +ID: 783 +PTO: 3 +FNS: FONLL-E +DAMP: 0 +IC: 1 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.65 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,53 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 6, 0, 0, 0] -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-E -GF: 1.1663787e-05 -HQ: POLE -IC: 1 -ID: 783 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: None -NfFF: 4 -PTO: 3 -Q0: 1.65 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 1 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 6) global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -n3lo_ad_variation: -- 0 -- 0 -- 0 -- 6 -- 0 -- 0 -- 0 -n3lo_cf_variation: 0 -nf0: 4 -nfref: 5 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/822.yaml b/nnpdf_data/nnpdf_data/theory_cards/822.yaml index d3ba6ecb09..552f9baa1d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/822.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/822.yaml @@ -1,3 +1,32 @@ +ID: 822 +PTO: 2 +FNS: FONLL-C +DAMP: 0 +IC: 0 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.0 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,45 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-C -GF: 1.1663787e-05 -HQ: POLE -IC: 0 -ID: 822 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: null -NfFF: 4 -PTO: 2 -Q0: 1.0 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 3 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: Baseline for Polarised NNPDFpol2.0 NNLO with nFONLL global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 3 -n3lo_cf_variation: 0 +EScaleVar: 1 diff --git a/nnpdf_data/nnpdf_data/theory_cards/823.yaml b/nnpdf_data/nnpdf_data/theory_cards/823.yaml index f47bd10e29..6ec9bc72f5 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/823.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/823.yaml @@ -1,3 +1,32 @@ +ID: 823 +PTO: 1 +FNS: FONLL-A +DAMP: 0 +IC: 0 +ModEv: TRN +XIR: 1.0 +XIF: 1.0 +NfFF: 5 +MaxNfAs: 5 +MaxNfPdf: 5 +Q0: 1.0 +alphas: 0.118 +Qref: 91.2 +QED: 0 +alphaqed: 0.007496252 +Qedref: 1.777 +SxRes: 0 +SxOrd: LL +HQ: POLE +mc: 1.51 +Qmc: 1.51 +kcThr: 1.0 +mb: 4.92 +Qmb: 4.92 +kbThr: 1.0 +mt: 172.5 +Qmt: 172.5 +ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -8,45 +37,12 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL -DAMP: 0 -EScaleVar: 1 -FNS: FONLL-A -GF: 1.1663787e-05 -HQ: POLE -IC: 0 -ID: 823 -MP: 0.938 -MW: 80.398 MZ: 91.1876 -MaxNfAs: 5 -MaxNfPdf: 5 -ModEv: TRN -ModSV: null -NfFF: 4 -PTO: 1 -Q0: 1.0 -QED: 0 -Qedref: 1.777 -Qmb: 4.92 -Qmc: 1.51 -Qmt: 172.5 -Qref: 91.2 +MW: 80.398 +GF: 1.1663787e-05 SIN2TW: 0.23126 -SxOrd: LL -SxRes: 0 TMC: 3 -XIF: 1.0 -XIR: 1.0 -alphaqed: 0.007496252 -alphas: 0.118 +MP: 0.938 +Comments: Baseline for Polarised NNPDFpol2.0 NLO with nFONLL global_nx: 0 -kbThr: 1.0 -kcThr: 1.0 -ktThr: 1.0 -mb: 4.92 -mc: 1.51 -mt: 172.5 -nfref: 5 -nf0: 3 -n3lo_cf_variation: 0 +EScaleVar: 1 diff --git a/validphys2/src/validphys/calcutils.py b/validphys2/src/validphys/calcutils.py index 8976de7b56..48e402f687 100644 --- a/validphys2/src/validphys/calcutils.py +++ b/validphys2/src/validphys/calcutils.py @@ -4,7 +4,6 @@ Low level utilities to calculate χ² and such. These are used to implement the higher level functions in results.py """ - import logging from typing import Callable @@ -16,7 +15,7 @@ def calc_chi2(sqrtcov, diffs): - r"""Elementary function to compute the chi², given a Cholesky decomposed + """Elementary function to compute the chi², given a Cholesky decomposed lower triangular part and a vector of differences. Parameters diff --git a/validphys2/src/validphys/config.py b/validphys2/src/validphys/config.py index 1880fda054..3b0a66398b 100644 --- a/validphys2/src/validphys/config.py +++ b/validphys2/src/validphys/config.py @@ -685,6 +685,15 @@ def produce_experiment_from_input(self, experiment_input, theoryid, use_cuts, fi ) } + def produce_sep_mult(self, separate_multiplicative=None): + """ + Specifies whether to separate the multiplicative errors in the + experimental covmat construction. The default is True. + """ + if separate_multiplicative is False: + return False + return True + @configparser.explicit_node def produce_dataset_inputs_fitting_covmat( self, theory_covmat_flag=False, use_thcovmat_in_fitting=False @@ -703,10 +712,7 @@ def produce_dataset_inputs_fitting_covmat( @configparser.explicit_node def produce_dataset_inputs_sampling_covmat( - self, - separate_multiplicative=False, - theory_covmat_flag=False, - use_thcovmat_in_sampling=False, + self, sep_mult, theory_covmat_flag=False, use_thcovmat_in_sampling=False ): """ Produces the correct covmat to be used in make_replica according @@ -716,12 +722,12 @@ def produce_dataset_inputs_sampling_covmat( from validphys import covmats if theory_covmat_flag and use_thcovmat_in_sampling: - if separate_multiplicative: + if sep_mult: return covmats.dataset_inputs_total_covmat_separate else: return covmats.dataset_inputs_total_covmat else: - if separate_multiplicative: + if sep_mult: return covmats.dataset_inputs_exp_covmat_separate else: return covmats.dataset_inputs_exp_covmat @@ -998,7 +1004,7 @@ def parse_fakepdf(self, name): """PDF set used to generate the fake data in a closure test.""" return self.parse_pdf(name) - def _parse_lagrange_multiplier(self, kind, theoryid, setdict, rules): + def _parse_lagrange_multiplier(self, kind, theoryid, setdict): """Lagrange multiplier constraints are mappings containing a `dataset` and a `maxlambda` argument which defines the maximum value allowed for the multiplier""" @@ -1021,17 +1027,17 @@ def _parse_lagrange_multiplier(self, kind, theoryid, setdict, rules): except ValueError as e: raise ConfigError(bad_msg) from e if kind == "posdataset": - return self.loader.check_posset(theoryno, name, maxlambda, rules) + return self.loader.check_posset(theoryno, name, maxlambda) elif kind == "integdataset": - return self.loader.check_integset(theoryno, name, maxlambda, rules) + return self.loader.check_integset(theoryno, name, maxlambda) else: raise ConfigError(f"The lagrange multiplier type {kind} is not understood") @element_of("posdatasets") - def parse_posdataset(self, posset: dict, *, theoryid, rules): + def parse_posdataset(self, posset: dict, *, theoryid): """An observable used as positivity constrain in the fit. It is a mapping containing 'dataset' and 'maxlambda'.""" - return self._parse_lagrange_multiplier("posdataset", theoryid, posset, rules) + return self._parse_lagrange_multiplier("posdataset", theoryid, posset) def produce_posdatasets(self, positivity): if not isinstance(positivity, dict) or "posdatasets" not in positivity: @@ -1041,11 +1047,11 @@ def produce_posdatasets(self, positivity): return positivity["posdatasets"] @element_of("integdatasets") - def parse_integdataset(self, integset: dict, *, theoryid, rules): + def parse_integdataset(self, integset: dict, *, theoryid): """An observable corresponding to a PDF in the evolution basis, used as integrability constrain in the fit. It is a mapping containing 'dataset' and 'maxlambda'.""" - return self._parse_lagrange_multiplier("integdataset", theoryid, integset, rules) + return self._parse_lagrange_multiplier("integdataset", theoryid, integset) def produce_integdatasets(self, integrability): if not isinstance(integrability, dict) or "integdatasets" not in integrability: diff --git a/validphys2/src/validphys/core.py b/validphys2/src/validphys/core.py index 97ea9d5260..1825fd18cc 100644 --- a/validphys2/src/validphys/core.py +++ b/validphys2/src/validphys/core.py @@ -393,9 +393,9 @@ def load(self): class InternalCutsWrapper(TupleComp): def __init__(self, commondata, rules): - self.rules = rules if rules else tuple() + self.rules = rules self.commondata = commondata - super().__init__(commondata, tuple(self.rules)) + super().__init__(commondata, tuple(rules)) def load(self): return np.atleast_1d( @@ -460,12 +460,9 @@ def cut_mask(cuts): class DataSetSpec(TupleComp): - def __init__( - self, *, name, commondata, fkspecs, thspec, cuts, frac=1, op=None, weight=1, rules=() - ): + def __init__(self, *, name, commondata, fkspecs, thspec, cuts, frac=1, op=None, weight=1): self.name = name self.commondata = commondata - self.rules = rules if isinstance(fkspecs, FKTableSpec): fkspecs = (fkspecs,) @@ -488,7 +485,7 @@ def __init__( self.op = op self.weight = weight - super().__init__(name, commondata, fkspecs, thspec, cuts, frac, op, weight, rules) + super().__init__(name, commondata, fkspecs, thspec, cuts, frac, op, weight) @functools.lru_cache def load_commondata(self): @@ -576,16 +573,11 @@ class LagrangeSetSpec(DataSetSpec): and other Lagrange Multiplier datasets. """ - def __init__(self, name, commondataspec, fkspec, maxlambda, thspec, rules): - cuts = InternalCutsWrapper(commondataspec, rules) + def __init__(self, name, commondataspec, fkspec, maxlambda, thspec): + cuts = Cuts(commondataspec, None) self.maxlambda = maxlambda super().__init__( - name=name, - commondata=commondataspec, - fkspecs=fkspec, - thspec=thspec, - cuts=cuts, - rules=rules, + name=name, commondata=commondataspec, fkspecs=fkspec, thspec=thspec, cuts=cuts ) def to_unweighted(self): @@ -594,6 +586,10 @@ def to_unweighted(self): ) return self + @functools.lru_cache + def load_commondata(self): + return self.commondata.load() + class PositivitySetSpec(LagrangeSetSpec): pass diff --git a/validphys2/src/validphys/filters.py b/validphys2/src/validphys/filters.py index 130047385e..ecdaef237a 100644 --- a/validphys2/src/validphys/filters.py +++ b/validphys2/src/validphys/filters.py @@ -189,7 +189,7 @@ def export_mask(path, mask): np.savetxt(path, mask, fmt='%d') -def filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, separate_multiplicative): +def filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, sep_mult): """Filter closure data. In addition to cutting data points, the data is generated from an underlying ``fakepdf``, applying a shift to the data if ``fakenoise`` is ``True``, which emulates the experimental central values @@ -197,19 +197,11 @@ def filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, separ """ log.info('Filtering closure-test data.') - return _filter_closure_data( - filter_path, data, fakepdf, fakenoise, filterseed, separate_multiplicative - ) + return _filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, sep_mult) def filter_closure_data_by_experiment( - filter_path, - experiments_data, - fakepdf, - fakenoise, - filterseed, - data_index, - separate_multiplicative, + filter_path, experiments_data, fakepdf, fakenoise, filterseed, data_index, sep_mult ): """ Like :py:func:`filter_closure_data` except filters data by experiment. @@ -226,13 +218,7 @@ def filter_closure_data_by_experiment( experiment_index = data_index[data_index.isin([exp.name], level=0)] res.append( _filter_closure_data( - filter_path, - exp, - fakepdf, - fakenoise, - filterseed, - experiment_index, - separate_multiplicative, + filter_path, exp, fakepdf, fakenoise, filterseed, experiment_index, sep_mult ) ) @@ -283,9 +269,7 @@ def _filter_real_data(filter_path, data): return total_data_points, total_cut_data_points -def _filter_closure_data( - filter_path, data, fakepdf, fakenoise, filterseed, data_index, separate_multiplicative -): +def _filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, data_index, sep_mult): """ This function is accessed within a closure test only, that is, the fakedata namespace has to be True (If fakedata = False, the _filter_real_data function @@ -350,9 +334,7 @@ def _filter_closure_data( if fakenoise: # ======= Level 1 closure test =======# - closure_data = make_level1_data( - data, closure_data, filterseed, data_index, separate_multiplicative - ) + closure_data = make_level1_data(data, closure_data, filterseed, data_index, sep_mult) # ====== write commondata and systype files ======# if fakenoise: @@ -409,7 +391,7 @@ def check_positivity(posdatasets): log.info('Verifying positivity tables:') for pos in posdatasets: pos.load_commondata() - log.info(f'{pos.name} checked, {len(pos.cuts.load())}/{pos.commondata.ndata} datapoints passed kinematic cuts.') + log.info(f'{pos.name} checked.') def check_integrability(integdatasets): diff --git a/validphys2/src/validphys/loader.py b/validphys2/src/validphys/loader.py index 7412281a8a..c238768bc7 100644 --- a/validphys2/src/validphys/loader.py +++ b/validphys2/src/validphys/loader.py @@ -14,6 +14,7 @@ import sys import tarfile import tempfile +from typing import List import urllib.parse as urls import requests @@ -295,7 +296,7 @@ def available_hyperscans(self): return [] @property - @functools.lru_cache + @functools.lru_cache() def available_theories(self): """Return a string token for each of the available theories""" theory_token = 'theory_' @@ -305,7 +306,7 @@ def available_theories(self): } @property - @functools.lru_cache + @functools.lru_cache() def available_ekos(self): """Return a string token for each of the available theories""" return { @@ -313,7 +314,7 @@ def available_ekos(self): } @property - @functools.lru_cache + @functools.lru_cache() def _available_old_datasets(self): """Provide all available datasets At the moment this means cominbing the new and olf format datasets @@ -328,7 +329,7 @@ def _available_old_datasets(self): } @property - @functools.lru_cache + @functools.lru_cache() def available_datasets(self): """Provide all available datasets other then positivitiy and integrability. At the moment this only returns old datasets for which we have a translation available @@ -338,7 +339,7 @@ def available_datasets(self): return set(old_datasets) @property - @functools.lru_cache + @functools.lru_cache() def implemented_datasets(self): """Provide all implemented datasets that can be found in the datafiles folder regardless of whether they can be used for fits (i.e., whether they include a theory), @@ -350,7 +351,7 @@ def implemented_datasets(self): return datasets @property - @functools.lru_cache + @functools.lru_cache() def available_pdfs(self): return lhaindex.expand_local_names('*') @@ -511,15 +512,17 @@ def check_commondata( setname, metadata, legacy=True, datafile=datafile, sysfile=sysfile, plotfiles=plotfiles ) - @functools.lru_cache + @functools.lru_cache() def check_theoryID(self, theoryID): theoryID = str(theoryID) theopath = self._theories_path / f"theory_{theoryID}" if not theopath.exists(): - raise TheoryNotFound(f"Could not find theory {theoryID}. Folder '{theopath}' not found") + raise TheoryNotFound( + "Could not find theory {}. Folder '{}' not found".format(theoryID, theopath) + ) return TheoryIDSpec(theoryID, theopath, self.theorydb_folder) - @functools.lru_cache + @functools.lru_cache() def check_eko(self, theoryID): """Check the eko (and the parent theory) both exists and returns the path to it""" theory = self.check_theoryID(theoryID) @@ -551,7 +554,7 @@ def check_fktable(self, theoryID, setname, cfac): fkpath = theopath / 'fastkernel' / ('FK_%s.dat' % setname) if not fkpath.exists(): raise FKTableNotFound( - f"Could not find FKTable for set '{setname}'. File '{fkpath}' not found" + "Could not find FKTable for set '{}'. File '{}' not found".format(setname, fkpath) ) cfactors = self.check_cfactor(theoryID, setname, cfac) @@ -633,18 +636,18 @@ def _check_lagrange_multiplier_set(self, theoryID, setname): fk, _ = self._check_theory_old_or_new(th, cd, []) return cd, fk, th - def check_posset(self, theoryID, setname, postlambda, rules): + def check_posset(self, theoryID, setname, postlambda): """Load a positivity dataset""" cd, fk, th = self._check_lagrange_multiplier_set(theoryID, setname) - return PositivitySetSpec(setname, cd, fk, postlambda, th, rules) + return PositivitySetSpec(setname, cd, fk, postlambda, th) - def check_integset(self, theoryID, setname, postlambda, rules): + def check_integset(self, theoryID, setname, postlambda): """Load an integrability dataset""" cd, fk, th = self._check_lagrange_multiplier_set(theoryID, setname) - return IntegrabilitySetSpec(setname, cd, fk, postlambda, th, rules) + return IntegrabilitySetSpec(setname, cd, fk, postlambda, th) - def get_posset(self, theoryID, setname, postlambda, rules): - return self.check_posset(theoryID, setname, postlambda, rules).load() + def get_posset(self, theoryID, setname, postlambda): + return self.check_posset(theoryID, setname, postlambda).load() def check_fit(self, fitname): resultspath = self.resultspath @@ -796,10 +799,9 @@ def check_dataset( frac=frac, op=op, weight=weight, - rules=rules, ) - def check_experiment(self, name: str, datasets: list[DataSetSpec]) -> DataGroupSpec: + def check_experiment(self, name: str, datasets: List[DataSetSpec]) -> DataGroupSpec: """Loader method for instantiating DataGroupSpec objects. The NNPDF::Experiment object can then be instantiated using the load method. @@ -947,11 +949,13 @@ def download_file(url, stream_or_path, make_parents=False, delete_on_failure=Fal if make_parents: p.parent.mkdir(exist_ok=True, parents=True) - with tempfile.NamedTemporaryFile( + download_target = tempfile.NamedTemporaryFile( delete=delete_on_failure, dir=p.parent, prefix=p.name, suffix='.part' - ) as f: + ) + + with download_target as f: _download_and_show(response, f) - shutil.move(f.name, p) + shutil.move(download_target.name, p) else: log.info("Downloading %s.", url) _download_and_show(response, stream_or_path) @@ -976,7 +980,7 @@ def download_and_extract(url, local_path, target_name=None): try: res_tar.extractall(path=dest_path, filter="data") except tarfile.LinkOutsideDestinationError as e: - if sys.version_info > (3, 11): + if sys.verson_info > (3, 11): raise e # For older versions of python ``filter=data`` might be too restrictive # for the links inside the ``postfit`` folder if you are using more than one disk @@ -1086,13 +1090,15 @@ def _remote_files_from_url(self, url, index, thing='files'): resp = requests.get(index_url) resp.raise_for_status() except Exception as e: - raise RemoteLoaderError(f"Failed to fetch remote {thing} index {index_url}: {e}") from e + raise RemoteLoaderError( + "Failed to fetch remote {} index {}: {}".format(thing, index_url, e) + ) from e try: info = resp.json()['files'] except Exception as e: raise RemoteLoaderError( - f"Malformed index {index_url}. Expecting json with a key 'files': {e}" + "Malformed index {}. Expecting json with a key 'files': {}".format(index_url, e) ) from e return {file.split('.')[0]: url + file for file in info} @@ -1107,31 +1113,31 @@ def remote_files(self, urls, index, thing='files'): return d @property - @functools.lru_cache + @functools.lru_cache() def remote_fits(self): return self.remote_files(self.fit_urls, self.fit_index, thing="fits") @property - @functools.lru_cache + @functools.lru_cache() def remote_hyperscans(self): return self.remote_files(self.hyperscan_url, self.hyperscan_index, thing="hyperscan") @property - @functools.lru_cache + @functools.lru_cache() def remote_theories(self): token = 'theory_' rt = self.remote_files(self.theory_urls, self.theory_index, thing="theories") return {k[len(token) :]: v for k, v in rt.items()} @property - @functools.lru_cache + @functools.lru_cache() def remote_ekos(self): token = 'eko_' rt = self.remote_files(self.eko_urls, self.eko_index, thing="ekos") return {k[len(token) :]: v for k, v in rt.items()} @property - @functools.lru_cache + @functools.lru_cache() def remote_nnpdf_pdfs(self): return self.remote_files(self.nnpdf_pdfs_urls, self.nnpdf_pdfs_index, thing="PDFs") diff --git a/validphys2/src/validphys/process_options.py b/validphys2/src/validphys/process_options.py index 059ddcd28e..4b13440dfe 100644 --- a/validphys2/src/validphys/process_options.py +++ b/validphys2/src/validphys/process_options.py @@ -206,7 +206,6 @@ def _displusjet_xq2map(kin_info): return x, q2 - def _dyboson_xq2map(kin_info): """ Computes x and q2 mapping for pseudo rapidity observables @@ -308,10 +307,6 @@ def _dybosonpt_xq2map(kin_dict): ) -POS_XPDF = _Process("POS_XPDF", "Positivity of MS bar PDFs", accepted_variables=(_Vars.x, _Vars.Q2)) - -POS_F2 = _Process("POS_F2", "Positivity of F2 structure functions", accepted_variables=(_Vars.x, _Vars.Q2)) - PROCESSES = { "DIS": DIS, "DIS_NC": dataclasses.replace(DIS, name="DIS_NC"), @@ -329,9 +324,7 @@ def _dybosonpt_xq2map(kin_dict): "HERADIJET": dataclasses.replace(HERAJET, name="HERADIJET", description="DIS + jj production"), "DY_Z_Y": dataclasses.replace(DY_2L, name="DY_Z_Y", description="DY Z -> ll (pseudo)rapidity"), "DY_W_ETA": dataclasses.replace(DY_2L, name="DY_W_ETA", description="DY W -> l nu (pseudo)rapidity"), - "DY_NC_PT": dataclasses.replace(DY_PT, name="DY_NC_PT", description="DY Z (ll) + j"), - "POS_XPDF": POS_XPDF, - "POS_F2": POS_F2, + "DY_NC_PT": dataclasses.replace(DY_PT, name="DY_NC_PT", description="DY Z (ll) + j") } diff --git a/validphys2/src/validphys/pseudodata.py b/validphys2/src/validphys/pseudodata.py index a0083bb803..c12368f13e 100644 --- a/validphys2/src/validphys/pseudodata.py +++ b/validphys2/src/validphys/pseudodata.py @@ -126,7 +126,7 @@ def make_replica( groups_dataset_inputs_loaded_cd_with_cuts, replica_mcseed, dataset_inputs_sampling_covmat, - separate_multiplicative=False, + sep_mult, genrep=True, max_tries=int(1e6), resample_negative_pseudodata=True, @@ -153,8 +153,8 @@ def make_replica( Full covmat to be used. It can be either only experimental or also theoretical. separate_multiplicative: bool - Specifies whether computing the shifts with the full covmat - or whether multiplicative errors should be separated + Specifies whether computing the shifts with the full covmat or separating multiplicative + errors (in the latter case remember to generate the covmat coherently) genrep: bool Specifies whether computing replicas or not @@ -221,7 +221,7 @@ def make_replica( pseudodatas.append(pseudodata) # Separation of multiplicative errors. If separate_multiplicative is True also the exp_covmat is produced # without multiplicative errors - if separate_multiplicative: + if sep_mult: mult_errors = cd.multiplicative_errors mult_uncorr_errors = mult_errors.loc[:, mult_errors.columns == "UNCORR"].to_numpy() mult_corr_errors = mult_errors.loc[:, mult_errors.columns == "CORR"].to_numpy() @@ -234,7 +234,7 @@ def make_replica( else: check_positive_masks.append(np.ones_like(pseudodata, dtype=bool)) # concatenating special multiplicative errors, pseudodatas and positive mask - if separate_multiplicative: + if sep_mult: special_mult_errors = pd.concat(special_mult, axis=0, sort=True).fillna(0).to_numpy() all_pseudodata = np.concatenate(pseudodatas, axis=0) full_mask = np.concatenate(check_positive_masks, axis=0) @@ -255,10 +255,10 @@ def make_replica( mult_shifts.append(mult_shift) - # If separate_multiplicative is true then the multiplicative shifts were not included in the covmat + # If sep_mult is true then the multiplicative shifts were not included in the covmat shifts = covmat_sqrt @ rng.normal(size=covmat.shape[1]) mult_part = 1.0 - if separate_multiplicative: + if sep_mult: special_mult = ( 1 + special_mult_errors * rng.normal(size=(1, special_mult_errors.shape[1])) / 100 ).prod(axis=1) @@ -329,7 +329,7 @@ def level0_commondata_wc(data, fakepdf): return level0_commondata_instances_wc -def make_level1_data(data, level0_commondata_wc, filterseed, data_index, separate_multiplicative): +def make_level1_data(data, level0_commondata_wc, filterseed, data_index, sep_mult): """ Given a list of Level 0 commondata instances, return the same list with central values replaced by Level 1 data. @@ -395,16 +395,12 @@ def make_level1_data(data, level0_commondata_wc, filterseed, data_index, separat use_weights_in_covmat=False, norm_threshold=None, _list_of_central_values=None, - _only_additive=separate_multiplicative, + _only_additive=sep_mult, ) # ================== generation of Level1 data ======================# level1_data = make_replica( - level0_commondata_wc, - filterseed, - covmat, - separate_multiplicative=separate_multiplicative, - genrep=True, + level0_commondata_wc, filterseed, covmat, sep_mult=sep_mult, genrep=True ) indexed_level1_data = indexed_make_replica(data_index, level1_data) diff --git a/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv b/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv index 0eecde74ff..f2b40b260b 100644 --- a/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv +++ b/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv @@ -1,267 +1,267 @@ rep0 -0 528379.7135890458 -1 543295.3961418747 -2 582514.4085198267 -3 569070.1688635555 -4 582787.3058009441 -5 593095.1745829878 -6 572349.809426662 -7 584229.813430836 -8 604850.9212466192 -9 563392.6550643881 -10 525871.1188417731 -11 418698.3045595662 -12 420917.4552611014 -13 430753.0310092146 -14 405309.84059753723 -15 405013.1498491817 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API.rules( - **{ - "dataset_input": "SLAC_NC_NOTFIXED_D_DW_EM-F2", - "variant": "legacy", - "theoryid": THEORYID_NEW, - "use_cuts": "internal", - } - ) + # Test a dataset with no systematics emptysyscd = l.check_posset( - theoryID=THEORYID_NEW, setname='NNPDF_POS_2P24GEV_XDQ', postlambda=1e-10, rules=rules + theoryID=THEORYID_NEW, setname='NNPDF_POS_2P24GEV_XDQ', postlambda=1e-10 ) emptysysres = load_commondata(emptysyscd.commondata) assert emptysysres.nsys == 0 diff --git a/validphys2/src/validphys/tests/test_overfit_metric.py b/validphys2/src/validphys/tests/test_overfit_metric.py index 342f21f79c..92b6a4332b 100644 --- a/validphys2/src/validphys/tests/test_overfit_metric.py +++ b/validphys2/src/validphys/tests/test_overfit_metric.py @@ -17,7 +17,6 @@ "t0pdfset": {"from_": "datacuts"}, "pdf": {"from_": "fit"}, "dataset_inputs": {"from_": "fit"}, - "separate_multiplicative": True } diff --git a/validphys2/src/validphys/tests/test_pseudodata.py b/validphys2/src/validphys/tests/test_pseudodata.py index be6e02ebe5..74f2dd87d0 100644 --- a/validphys2/src/validphys/tests/test_pseudodata.py +++ b/validphys2/src/validphys/tests/test_pseudodata.py @@ -74,7 +74,7 @@ def test_no_savepseudodata(): def test_read_matches_recreate(): reads = API.read_fit_pseudodata(fit=PSEUDODATA_FIT) - recreates = API.recreate_fit_pseudodata(fit=PSEUDODATA_FIT, separate_multiplicative=True) + recreates = API.recreate_fit_pseudodata(fit=PSEUDODATA_FIT) for read, recreate in zip(reads, recreates): # We ignore the absolute ordering of the dataframes and just check # that they contain identical elements. diff --git a/validphys2/src/validphys/tests/test_pyfkdata.py b/validphys2/src/validphys/tests/test_pyfkdata.py index b5a711c430..f1bb958b72 100644 --- a/validphys2/src/validphys/tests/test_pyfkdata.py +++ b/validphys2/src/validphys/tests/test_pyfkdata.py @@ -94,13 +94,13 @@ def test_positivity(pdf_name): pdf = l.check_pdf(pdf_name) for posset in POSITIVITIES: # Use the loader to load the positivity dataset - ps = l.check_posset(setname=posset, theoryID=THEORYID, postlambda=1e6, rules=()) + ps = l.check_posset(setname=posset, theoryID=THEORYID, postlambda=1e6) preds = predictions(ps, pdf) core_predictions = PositivityResult.from_convolution(pdf, ps) assert_allclose(preds.values, core_predictions.rawdata) # Now do the same with the API api_predictions = API.positivity_predictions_data_result( - theoryid=THEORYID, use_cuts="internal", pdf=pdf_name, posdataset={"dataset": posset, "maxlambda": 1e6} + theoryid=THEORYID, pdf=pdf_name, posdataset={"dataset": posset, "maxlambda": 1e6} ) assert_allclose(preds.values, api_predictions.rawdata) # And now check that the results are correct for any kind of PDF diff --git a/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py b/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py index d71db0644e..33fbe12f4d 100644 --- a/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py +++ b/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py @@ -3,7 +3,6 @@ Low level utilities for theorycovariance module """ - import logging from reportengine.checks import check, make_argcheck @@ -59,6 +58,9 @@ def check_correct_theory_combination_internal( correct_xirs = [1.0, 1.0, 1.0, 2.0, 0.5, 2.0, 0.5] elif l in [62, 64, 66, 70]: # check Anomalous dimensions variations + n3lo_vars_dict = {"gg": 19, "gq": 21, "qg": 15, "qq": 6} + # TODO: for the moment fish the n3lo_ad_variation from the comments + n3lo_vars_list = [] id_max = None if l == 70: id_max = -8 @@ -66,18 +68,11 @@ def check_correct_theory_combination_internal( id_max = -4 elif l == 64: id_max = -2 - n3lo_vars_list = [] for theoryid in theoryids[:id_max]: - n3lo_ad_variation = theoryid.get_description()["n3lo_ad_variation"] - # Only take the first 4, the last three are NS and only relevant for FHMRUVV - if any(n3lo_ad_variation[4:]): - raise ValueError( - f"Theory {theoryid.id} has non-zero entries in the last three (NS) elements " - "of n3lo_ad_variation, the covmat construction does not support this!" - ) - n3lo_vars_list.append(theoryid.get_description()["n3lo_ad_variation"][:4]) + n3lo_vars_list.append( + [int(val) for val in theoryid.get_description()["Comments"][28:-1].split(",")] + ) full_var_list = [[0, 0, 0, 0]] - n3lo_vars_dict = {"gg": 19, "gq": 21, "qg": 15, "qq": 6} for entry, max_var in enumerate(n3lo_vars_dict.values()): for idx in range(1, max_var + 1): base_var = [0, 0, 0, 0] diff --git a/validphys2/src/validphys/uploadutils.py b/validphys2/src/validphys/uploadutils.py index 2420845282..bc459c7a17 100644 --- a/validphys2/src/validphys/uploadutils.py +++ b/validphys2/src/validphys/uploadutils.py @@ -3,7 +3,6 @@ Tools to upload resources to remote servers. """ - import base64 import contextlib from glob import glob @@ -92,7 +91,7 @@ def check_auth(self): % str_line ) from e except OSError as e: - raise BadSSH(f"Could not run the command\n{str_line}\n: {e}") from e + raise BadSSH("Could not run the command\n%s\n: %s" % (str_line, e)) from e log.info("Connection seems OK.") @@ -300,7 +299,7 @@ def check_fit_md5(self, output_path): """ md5_path = output_path / "md5" try: - with open(md5_path) as f: + with open(md5_path, "r") as f: saved_md5 = f.read() except FileNotFoundError as e: log.error( @@ -432,7 +431,7 @@ def check_input(path): files = os.listdir(path) # Require that a .info file and replica 0 exist before admitting # the input is a valid LHAPDF set - info_reg, rep0_reg = map(re.compile, (r'.+\.info', r'.+0000\.dat')) + info_reg, rep0_reg = map(re.compile, ('.+\.info', '.+0000\.dat')) if 'meta.yaml' in files: return 'report' From d06980038e05c572615085b97373078dd053b337 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 25 Jun 2024 14:43:39 +0200 Subject: [PATCH 66/98] Reapply "Merge branch 'master' into DY_polarized_data" This reverts commit d8b78ece33e26bb5f9859045373e19bc716cb449. --- doc/sphinx/source/n3fit/runcard_detailed.rst | 63 +- extra_tests/regression_fits/central_16.json | 23 +- .../regression_fits/diagonal_45.exportgrid | 1152 +++--- extra_tests/regression_fits/diagonal_45.json | 49 +- .../feature_scaling_81.exportgrid | 1166 +++--- .../regression_fits/feature_scaling_81.json | 49 +- .../regression_fits/flavour_29.exportgrid | 1164 +++--- extra_tests/regression_fits/flavour_29.json | 53 +- .../regression_fits/no_csr_613.exportgrid | 1170 +++--- extra_tests/regression_fits/no_csr_613.json | 49 +- .../regression_fits/no_lagrange_27.json | 23 +- .../regression_fits/no_msr_92.exportgrid | 1160 +++--- extra_tests/regression_fits/no_msr_92.json | 49 +- .../regression_fits/no_sumrules_18.exportgrid | 1166 +++--- .../regression_fits/no_sumrules_18.json | 49 +- .../regression_fits/no_vsr_54.exportgrid | 1148 +++--- extra_tests/regression_fits/no_vsr_54.json | 49 +- .../regression_fits/normal_fit_72.exportgrid | 1136 +++--- .../regression_fits/normal_fit_72.json | 53 +- .../polarized_evol_34.exportgrid | 784 ++-- .../regression_fits/polarized_evol_34.json | 47 +- .../regression_fits/single_dense_316.json | 23 +- .../regression_fits/trainable_prepro.yml | 3 + .../regression_fits/trainable_prepro_61.json | 23 +- n3fit/runcards/examples/Basic_runcard.yml | 6 + n3fit/runcards/examples/nnpdf40-like.yml | 5 +- .../hyperopt_studies/renew_hyperopt.yml | 3 - ...restricted_search_space_renew_hyperopt.yml | 3 - .../n3fit/backends/keras_backend/MetaLayer.py | 4 +- .../n3fit/backends/keras_backend/MetaModel.py | 4 +- .../backends/keras_backend/base_layers.py | 7 +- .../backends/keras_backend/multi_dense.py | 10 +- .../backends/keras_backend/operations.py | 13 +- n3fit/src/n3fit/checks.py | 2 +- n3fit/src/n3fit/hyper_optimization/rewards.py | 10 +- n3fit/src/n3fit/layers/mask.py | 5 +- n3fit/src/n3fit/model_gen.py | 41 +- n3fit/src/n3fit/model_trainer.py | 2 +- n3fit/src/n3fit/msr.py | 4 +- n3fit/src/n3fit/n3fit_checks_provider.py | 1 - n3fit/src/n3fit/scripts/n3fit_exec.py | 2 +- .../regressions/quickcard-sequential.yml | 2 + .../src/n3fit/tests/regressions/quickcard.yml | 2 + .../n3fit/tests/regressions/quickcard_pol.yml | 2 + .../n3fit/tests/regressions/quickcard_qed.yml | 2 + n3fit/src/n3fit/tests/test_multireplica.py | 4 +- n3fit/src/n3fit/tests/test_preprocessing.py | 2 +- nnpdf_data/nnpdf_data/filter_utils/utils.py | 364 +- .../ATLAS_1JET_13TEV_DIF/filter.py | 2 +- .../ATLAS_2JET_13TEV_DIF/filter.py | 2 +- .../ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py | 48 +- .../ATLAS_TTBAR_13TEV_HADR_DIF/utils.py | 369 -- .../ATLAS_TTBAR_13TEV_LJ_DIF/filter.py | 6 +- .../ATLAS_TTBAR_8TEV_2L_DIF/filter.py | 2 +- .../ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py | 130 +- .../ATLAS_TTBAR_8TEV_LJ_DIF/filter.py | 4 +- .../ATLAS_Z0J_13TEV_PT/metadata.yaml | 2 +- .../ATLAS_Z0_8TEV_ZMASS/data.yaml | 8 + .../ATLAS_Z0_8TEV_ZMASS/filter.py | 91 + .../ATLAS_Z0_8TEV_ZMASS/filter_utils.py | 108 + .../ATLAS_Z0_8TEV_ZMASS/kinematics.yaml | 85 + .../ATLAS_Z0_8TEV_ZMASS/metadata.yaml | 59 + .../HEPData-ins2698794-v1-Table_9.yaml | 71 + .../ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt | 7 + .../ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml | 79 + .../CMS_TTBAR_13TEV_2L_DIF/filter.py | 2 +- .../CMS_TTBAR_13TEV_LJ_DIF/filter.py | 2 +- .../CMS_TTBAR_8TEV_2L_DIF/filter.py | 10 +- .../CMS_TTBAR_8TEV_LJ_DIF/filter.py | 4 +- .../CMS_WPWM_7TEV_ELECTRON/filter.py | 2 +- .../CMS_WPWM_7TEV_MUON/filter.py | 2 +- .../CMS_WPWM_8TEV_MUON/filter.py | 2 +- .../CMS_Z0_7TEV_DIMUON/filter.py | 2 +- .../H1_1JET_319GEV_290PB-1_DIF/artUnc.py | 4 +- .../H1_1JET_319GEV_290PB-1_DIF/filter.py | 4 +- .../H1_1JET_319GEV_351PB-1_DIF/filter.py | 2 +- .../H1_1JET_319GEV_351PB-1_DIF/manual_impl.py | 3584 ++++++++++++++++- .../H1_2JET_319GEV_290PB-1_DIF/artUnc.py | 4 +- .../H1_2JET_319GEV_290PB-1_DIF/filter.py | 4 +- .../H1_2JET_319GEV_351PB-1_DIF/filter.py | 2 +- .../H1_2JET_319GEV_351PB-1_DIF/manual_impl.py | 3584 ++++++++++++++++- .../LHCB_DY_7TEV_MUON/filter.py | 2 +- .../LHCB_DY_8TEV_MUON/filter.py | 2 +- .../LHCB_WPWM_7TEV_MUON/filter.py | 2 +- .../LHCB_WPWM_8TEV_MUON/filter.py | 2 +- .../new_commondata/LHCB_Z0_13TEV/filter.py | 2 +- .../LHCB_Z0_7TEV_DIELECTRON/filter.py | 5 +- .../LHCB_Z0_7TEV_MUON/filter.py | 2 +- .../LHCB_Z0_8TEV_DIELECTRON/filter.py | 2 +- .../LHCB_Z0_8TEV_MUON/filter.py | 2 +- .../NNPDF_INTEG_1GEV/metadata.yaml | 8 +- .../kinematics_F2C-17PTS.yaml | 136 +- .../kinematics_F2C-CCE-17PTS.yaml | 136 +- .../kinematics_F2C-CCP-17PTS.yaml | 136 +- .../NNPDF_POS_2P24GEV/kinematics_F2C.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_F2D.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_F2S.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_F2U.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XCQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XDB.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XDQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XGL.yaml | 162 +- .../NNPDF_POS_2P24GEV/kinematics_XSB.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XSQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XUB.yaml | 160 +- .../NNPDF_POS_2P24GEV/kinematics_XUQ.yaml | 160 +- .../NNPDF_POS_2P24GEV/metadata.yaml | 393 +- .../ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py | 2 +- .../ZEUS_1JET_319GEV_82PB-1_DIF/filter.py | 2 +- .../ZEUS_2JET_319GEV_374PB-1_DIF/filter.py | 2 +- .../nnpdf_data/theory_cards/40002000.yaml | 47 + .../nnpdf_data/theory_cards/40002001.yaml | 47 + .../nnpdf_data/theory_cards/40002002.yaml | 47 + .../nnpdf_data/theory_cards/40002003.yaml | 47 + .../nnpdf_data/theory_cards/40002004.yaml | 47 + .../nnpdf_data/theory_cards/40002006.yaml | 47 + .../nnpdf_data/theory_cards/40002007.yaml | 47 + .../nnpdf_data/theory_cards/40002008.yaml | 47 + .../nnpdf_data/theory_cards/40002009.yaml | 47 + .../nnpdf_data/theory_cards/40002010.yaml | 47 + .../nnpdf_data/theory_cards/40002011.yaml | 47 + .../nnpdf_data/theory_cards/40002012.yaml | 47 + .../nnpdf_data/theory_cards/40002013.yaml | 47 + nnpdf_data/nnpdf_data/theory_cards/722.yaml | 67 +- nnpdf_data/nnpdf_data/theory_cards/723.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/724.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/725.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/726.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/727.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/728.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/729.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/730.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/731.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/732.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/733.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/734.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/735.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/736.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/737.yaml | 80 +- 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nnpdf_data/nnpdf_data/theory_cards/776.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/777.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/778.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/779.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/780.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/781.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/782.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/783.yaml | 80 +- nnpdf_data/nnpdf_data/theory_cards/822.yaml | 72 +- nnpdf_data/nnpdf_data/theory_cards/823.yaml | 72 +- validphys2/src/validphys/calcutils.py | 3 +- validphys2/src/validphys/config.py | 32 +- validphys2/src/validphys/core.py | 26 +- validphys2/src/validphys/filters.py | 32 +- validphys2/src/validphys/loader.py | 64 +- validphys2/src/validphys/process_options.py | 9 +- validphys2/src/validphys/pseudodata.py | 24 +- .../regressions/test_art_rep_generation.csv | 532 +-- .../tests/regressions/test_mcreplica.csv | 532 +-- .../validphys/tests/test_commondataparser.py | 11 +- .../validphys/tests/test_overfit_metric.py | 1 + .../src/validphys/tests/test_pseudodata.py | 2 +- .../src/validphys/tests/test_pyfkdata.py | 4 +- .../theorycovariance/theorycovarianceutils.py | 17 +- validphys2/src/validphys/uploadutils.py | 7 +- 202 files changed, 18430 insertions(+), 10764 deletions(-) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt create mode 100644 nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002000.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002001.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002002.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002003.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002004.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002006.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002007.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002008.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002009.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002010.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002011.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002012.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/40002013.yaml diff --git a/doc/sphinx/source/n3fit/runcard_detailed.rst b/doc/sphinx/source/n3fit/runcard_detailed.rst index 8f31d98af0..a498e7d84d 100644 --- a/doc/sphinx/source/n3fit/runcard_detailed.rst +++ b/doc/sphinx/source/n3fit/runcard_detailed.rst @@ -30,7 +30,7 @@ The first thing one finds when building a fit runcard for - { dataset: NMCPD_dw, frac: 0.5 } - { dataset: ATLASZPT8TEVMDIST, frac: 0.75, sys: 10, cfac: [QCD] } - + The `dataset_inputs` key contains a list of dictionaries defining the datasets to be used in the fit as well as their options (which are detailed in :ref:`datasetspec-core-label`). @@ -42,7 +42,7 @@ The fraction of events that are considered for the training and validation sets dataset_inputs: - { dataset: SLACP_dwsh, frac: 0.75} - + It is possible to run a fit with no validation set by setting the fraction to ``1.0``, in this case the training set will be used as validation set. The random seed for the training/validation split is defined by the variable ``trvlseed``. @@ -54,7 +54,7 @@ to fix it such that it is the same for all replicas with ``same_trvl_per_replica trvlseed: 7 same_trvl_per_replica: true - + .. _preprocessing-label: @@ -92,26 +92,26 @@ Setting the ``trainable`` flag to ``False`` is equivalent to recovering the old - { fl: t8, smallx: [0.56,1.29], largex: [1.45,3.03] } - { fl: cp, smallx: [0.12,1.19], largex: [1.83,6.70] } -It is important to determine the correct values for the ``largex`` and ``smallx`` preprocessing -ranges. For example setting a poor range for those parameters can result in a conflict with the -:ref:`positivity ` or :ref:`integrability ` constraints, making it such -that no replicas can satisfy those constraints. In most cases when changes are made to a runcard, -they will have a relatively small effect on the required preprocessing ranges. This includes common -variations to runcards such as changing the datasets, or settings related to the training of the -neural network. In these cases :ref:`running an iterated fit ` is likely the +It is important to determine the correct values for the ``largex`` and ``smallx`` preprocessing +ranges. For example setting a poor range for those parameters can result in a conflict with the +:ref:`positivity ` or :ref:`integrability ` constraints, making it such +that no replicas can satisfy those constraints. In most cases when changes are made to a runcard, +they will have a relatively small effect on the required preprocessing ranges. This includes common +variations to runcards such as changing the datasets, or settings related to the training of the +neural network. In these cases :ref:`running an iterated fit ` is likely the easiest way to obtain a satisfactory range of the preprocessing. However, in some cases, such as for -example a change of PDF basis where the preprocessing ranges obtain a different meaning entirely, -we don't know what a good starting point for the ranges would be. One way to identify good ranges -is by opening up the ``smallx`` and ``large`` parameters for large ranges and setting -``trainable: True``. This way the preprocessing exponents will be considered part of the free +example a change of PDF basis where the preprocessing ranges obtain a different meaning entirely, +we don't know what a good starting point for the ranges would be. One way to identify good ranges +is by opening up the ``smallx`` and ``large`` parameters for large ranges and setting +``trainable: True``. This way the preprocessing exponents will be considered part of the free parameters of the model, and as such they will be fitted by the optimization algorithm. -NNPDF4.0 fits are run with ``trainable: False``, because trainable preprocessing exponents can lead +NNPDF4.0 fits are run with ``trainable: False``, because trainable preprocessing exponents can lead to an underestimation of the PDF uncertainties in the extrapolation domain. So after determining a -reasonable range for the preprocessing exponents, a new runcard should be generated using -``vp-nextfitruncard`` as explained in :ref:_run-iterated-fit. In this runcard one should then -manually set ``trainable: False`` for all preprocessing exponents before running the iterated fit. -It can take more than one iteration before the iterated fits have converged to stable values for the +reasonable range for the preprocessing exponents, a new runcard should be generated using +``vp-nextfitruncard`` as explained in :ref:_run-iterated-fit. In this runcard one should then +manually set ``trainable: False`` for all preprocessing exponents before running the iterated fit. +It can take more than one iteration before the iterated fits have converged to stable values for the preprocessing ranges. Note that the script ``vp-nextfitruncard`` automatically enforces some constraints @@ -160,7 +160,7 @@ In this case the ``nodes_per_layer`` parameter represents the nodes each one of - **One network per flavour** (``layer_type: dense_per_flavour``): -This mode is designed to behave as the methodology for NNPDF before 3.1 where each flavour has a separated identical network. +This mode is designed to behave as the methodology for NNPDF before 3.1 where each flavour has a separated identical network. In this case the ``nodes_per_layer`` parameter represents the nodes each layer of each flavour has. For instance ``[5, 3, 8]`` means that the first step is a list of 8 layers of shape ``(2x5)``, while the second layer is again a list that matches the previous one (i.e., 8 layers) with layers of shape ``(5x3)`` while the last layer has two task. The output of each layer should be one single element (i.e., 8 ``(3x1)`` layers) and then concatenate them all so that the final output of the neural network will be a 8-elements tensor. A report comparing the ``dense`` and ``dense_per_flavour`` architectures can be found `here `_ @@ -219,7 +219,7 @@ Note that by defining the positivity in this way all datasets will share the sam It is also possible to not define the positivity hyperparameters (or define them only partially). In this case ``n3fit`` will set the initial Lagrange multiplier as ``initial`` (default: 1.0) -while the ``multiplier`` will be such that after the last epoch the final Lagrange multiplier +while the ``multiplier`` will be such that after the last epoch the final Lagrange multiplier equals the ``maxlambda`` defined for the dataset. Finally we have the positivity threshold, which is set to ``1e-6`` by default. @@ -233,11 +233,11 @@ this value, it will be tagged as ``POS_VETO`` and the replica removed from postf Integrability ------------- -Integrability in ``n3fit`` is enforced through a Lagrange multiplier, this is -the same basic concept as how positivity is enforced, and therefore the -input in the runcard is analogous to the case of positivity where one can -apply the integrability contraints through an optional ``integrability`` -dictionary as (not that as opposed to positivity, for integrability no +Integrability in ``n3fit`` is enforced through a Lagrange multiplier, this is +the same basic concept as how positivity is enforced, and therefore the +input in the runcard is analogous to the case of positivity where one can +apply the integrability contraints through an optional ``integrability`` +dictionary as (not that as opposed to positivity, for integrability no threshold value can be set): .. code-block:: yaml @@ -307,7 +307,7 @@ Logging details will include the value of the loss for each experiment over time the values of the weights of the NN, as well as a detailed analysis of the amount of time that TensorFlow spent on each operation. - + .. _parallel-label: Running fits in parallel @@ -325,8 +325,8 @@ this can be done with the `same_trvl_per_replica: true` runcard flag. In other words, in order to run several replicas in parallel in a machine (be it a big CPU or, most likely, a GPU) -it is necessary to modify the ``n3fit`` runcard by adding the following two -top-level options: +it is necessary to modify the ``n3fit`` runcard by adding the following +top-level option: .. code-block:: yaml @@ -337,7 +337,7 @@ And then run ``n3fit`` with a replica range to be parallelized (in this case from replica 1 to replica 4). .. code-block:: bash - + n3fit runcard.yml 1 -r 4 @@ -412,8 +412,7 @@ It is however possible to disable them by setting to false the ``sum_rules`` fla fitting: sum_rules: False - + It is also possible to impose just the valence or the momentum sum rules by using the ``VSR`` or ``MSR`` flags, respectively (``True`` is equal to ``All``). - diff --git a/extra_tests/regression_fits/central_16.json b/extra_tests/regression_fits/central_16.json index 39aa4f3cb3..6f2b9a68d7 100644 --- a/extra_tests/regression_fits/central_16.json +++ b/extra_tests/regression_fits/central_16.json @@ -71,24 +71,25 @@ ], "timing": { "walltime": { - "Total": 32.32825946807861, + "Total": 30.10047173500061, "start": 0.0, - "replica_set": 0.23800349235534668, - "replica_fitted": 32.32805871963501, - "replica_set_to_replica_fitted": 32.09005522727966 + "replica_set": 0.23421192169189453, + "replica_fitted": 30.100268602371216, + "replica_set_to_replica_fitted": 29.86605668067932 }, "cputime": { - "Total": 33.586156003, + "Total": 31.299373692000003, "start": 0.0, - "replica_set": 0.23583456399999925, - "replica_fitted": 33.585950811000004, - "replica_set_to_replica_fitted": 33.350116247 + "replica_set": 0.23228165799999978, + "replica_fitted": 31.299169341000002, + "replica_set_to_replica_fitted": 31.066887683000004 } }, "version": { - "tensorflow": "2.16.1, mkl=??", + "keras": "3.3.3", + "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/diagonal_45.exportgrid b/extra_tests/regression_fits/diagonal_45.exportgrid index 6d7218a619..5bd55b2930 100644 --- a/extra_tests/regression_fits/diagonal_45.exportgrid +++ b/extra_tests/regression_fits/diagonal_45.exportgrid @@ -1,590 +1,590 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -2.30641508102417, 0.163417249917984, 0.13690946996212006, 0.1369563639163971, - -16.51403045654297, 0.13710814714431763, 0.13706272840499878, 0.16317303478717804, - -2.30641508102417, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.2335898876190186, 0.1631176918745041, 0.135547935962677, 0.1356012523174286, - -16.52284049987793, 0.1357690989971161, 0.1357174962759018, 0.16284973919391632, - -2.2335894107818604, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.1630706787109375, 0.16307905316352844, 0.13440349698066711, 0.1344641149044037, - 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--- a/extra_tests/regression_fits/feature_scaling_81.json +++ b/extra_tests/regression_fits/feature_scaling_81.json @@ -51,44 +51,45 @@ ], "stop_epoch": 1100, "best_epoch": 1099, - "erf_tr": 2.490978479385376, - "erf_vl": 2.056649684906006, - "chi2": 1.4108959436416626, + "erf_tr": 2.652923583984375, + "erf_vl": 2.124218463897705, + "chi2": 1.4108749628067017, "pos_state": "POS_VETO", "arc_lengths": [ - 1.970557910248621, - 1.5123234861956554, - 1.260815035320441, - 1.1147019998011942, - 2.9255811134208907 + 1.9705483952206988, + 1.5123030684994028, + 1.260816206108889, + 1.1146990683970068, + 2.9255388094206625 ], "integrability": [ - 0.0038688098720747743, - 0.003868809872073886, - 2.2851325695849578e-05, - 0.05472333077341318, - 0.006996780051849116 + 0.003868802072247407, + 0.0038688020722473515, + 2.285109872005031e-05, + 0.05472337454557391, + 0.006996958574744971 ], "timing": { "walltime": { - "Total": 33.15795373916626, + "Total": 31.037630796432495, "start": 0.0, - "replica_set": 0.24506402015686035, - "replica_fitted": 33.15779399871826, - "replica_set_to_replica_fitted": 32.9127299785614 + "replica_set": 0.23567628860473633, + "replica_fitted": 31.037489652633667, + "replica_set_to_replica_fitted": 30.80181336402893 }, "cputime": { - "Total": 32.71397760399999, + "Total": 31.200167627000003, "start": 0.0, - "replica_set": 0.2428332590000002, - "replica_fitted": 32.71381593300001, - "replica_set_to_replica_fitted": 32.470982674000005 + "replica_set": 0.23375433899999987, + "replica_fitted": 31.200025121, + "replica_set_to_replica_fitted": 30.966270782 } }, "version": { - "tensorflow": "2.16.1, mkl=??", + "keras": "3.3.3", + "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/flavour_29.exportgrid b/extra_tests/regression_fits/flavour_29.exportgrid index 271716b50f..f4457dc870 100644 --- a/extra_tests/regression_fits/flavour_29.exportgrid +++ b/extra_tests/regression_fits/flavour_29.exportgrid @@ -1,590 +1,590 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -0.08654723316431046, 0.25055235624313354, 0.2923140823841095, 0.11977867782115936, - -2.819517135620117, 0.18869705498218536, 0.3840413987636566, 0.24346856772899628, - -0.08654723316431046, 0.0, 0.0, 0.0] -- [0.0, 0.0, -0.08803417533636093, 0.25043755769729614, 0.2941674590110779, 0.11950505524873734, - -2.7912018299102783, 0.18826957046985626, 0.3861331343650818, 0.24350540339946747, - -0.08803416043519974, 0.0, 0.0, 0.0] -- [0.0, 0.0, -0.08956166356801987, 0.25032058358192444, 0.29606592655181885, 0.11921392381191254, - -2.7621140480041504, 0.1878201961517334, 0.3882754445075989, 0.2435428947210312, - -0.08956166356801987, 0.0, 0.0, 0.0] -- [0.0, 0.0, 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mkl=??", + "keras": "3.3.3", + "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/no_sumrules_18.exportgrid b/extra_tests/regression_fits/no_sumrules_18.exportgrid index 5ec50d519c..585e2a46fa 100644 --- a/extra_tests/regression_fits/no_sumrules_18.exportgrid +++ b/extra_tests/regression_fits/no_sumrules_18.exportgrid @@ -1,590 +1,590 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -2.4447736740112305, 0.48206278681755066, 0.4548843801021576, 0.4549284875392914, - -0.536359429359436, 0.4549674689769745, 0.45492371916770935, 0.4819997251033783, - -2.4447736740112305, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.3672444820404053, 0.47239094972610474, 0.44413238763809204, 0.44418248534202576, - -0.5363330841064453, 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a/extra_tests/regression_fits/no_sumrules_18.json b/extra_tests/regression_fits/no_sumrules_18.json index 92081e8302..1a66d31fbb 100644 --- a/extra_tests/regression_fits/no_sumrules_18.json +++ b/extra_tests/regression_fits/no_sumrules_18.json @@ -51,44 +51,45 @@ ], "stop_epoch": 1100, "best_epoch": 1099, - "erf_tr": 5.30379056930542, - "erf_vl": 5.399439811706543, - "chi2": 3.260406017303467, + "erf_tr": 5.234591484069824, + "erf_vl": 5.933958530426025, + "chi2": 3.2721149921417236, "pos_state": "POS_PASS", "arc_lengths": [ - 1.334838142106021, - 0.9938354360870493, - 1.0016686497444203, - 0.9905760062030213, - 1.0071507527276173 + 1.3377847418174296, + 0.9938499771604175, + 1.0016840281484805, + 0.9905686298415103, + 1.0071484675459588 ], "integrability": [ - 0.00022732434808868385, - 0.00022732434808868385, - 1.0915414264803247e-05, - 0.47721657902002323, - 0.001817994620068597 + 0.00022827064094605581, + 0.00022827064094606275, + 1.0907395562656519e-05, + 0.47761861234903324, + 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"replica_set_to_replica_fitted": 41.403256988 + "replica_set": 0.22130740499999924, + "replica_fitted": 88.582529111, + "replica_set_to_replica_fitted": 88.36122170600001 } }, "version": { - "tensorflow": "2.16.1, mkl=??", + "keras": "3.3.3", + "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/polarized_evol_34.exportgrid b/extra_tests/regression_fits/polarized_evol_34.exportgrid index b0228e9f06..9a6961eb76 100644 --- a/extra_tests/regression_fits/polarized_evol_34.exportgrid +++ b/extra_tests/regression_fits/polarized_evol_34.exportgrid @@ -1,583 +1,587 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, 0.0, -0.10375979542732239, -0.10418701171875, -0.10418701171875, -0.6372790932655334, - -0.10418701171875, 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-0.0003622868680395186, -0.00018074382387567312, 0.004123591352254152, -0.00015570360119454563, +- [0.0, 0.0, 0.0, -0.0005377781926654279, 0.006741677410900593, -0.0006248131976462901, + -0.0008041125256568193, -0.0006248131976462901, 0.006741677410900593, -0.0005377781926654279, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -0.00010097896301886067, 0.003457761136814952, -0.00011407534475438297, - -0.000285094982245937, -0.00011407534475438297, 0.003457761136814952, -0.00010097896301886067, +- [0.0, 0.0, 0.0, -0.00044709196663461626, 0.005839187186211348, -0.0005090857739560306, + -0.0006602173671126366, -0.0005090857739560306, 0.005839187186211348, -0.00044709196663461626, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -5.4951367928879336e-05, 0.0028683540876954794, -5.9777670685434714e-05, - -0.00022123436792753637, -5.9777670685434714e-05, 0.0028683540876954794, -5.4951367928879336e-05, +- [0.0, 0.0, 0.0, -0.0003638165653683245, 0.005024733021855354, -0.0004093599854968488, + -0.0005374069442041218, -0.0004093599854968488, 0.005024733021855354, -0.0003638165653683245, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -1.7429461877327412e-05, 0.0023503636475652456, -1.666152456891723e-05, - -0.00016894661530386657, -1.666152456891723e-05, 0.0023503636475652456, -1.7429461877327412e-05, +- [0.0, 0.0, 0.0, -0.0002884456771425903, 0.0042923856526613235, -0.0003235507174395025, + -0.0004332337703090161, -0.0003235507174395025, 0.0042923856526613235, -0.0002884456771425903, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 1.1927386367460713e-05, 0.0018989337841048837, 1.636104025237728e-05, - -0.00012664461974054575, 1.636104025237728e-05, 0.0018989337841048837, 1.1927386367460713e-05, +- [0.0, 0.0, 0.0, -0.0002212987601524219, 0.003636627923697233, -0.00024992681574076414, + -0.0003454787947703153, -0.00024992681574076414, 0.003636627923697233, -0.0002212987601524219, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 3.359601032570936e-05, 0.0015093344263732433, 4.030536729260348e-05, - 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-8.93738106242381e-05, 0.002079180907458067, -6.997808668529615e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 5.907891318202019e-05, 0.0006655191536992788, 6.745915743522346e-05, - -3.0761824746150523e-05, 6.745915743522346e-05, 0.0006655191536992788, 5.907891318202019e-05, +- [0.0, 0.0, 0.0, -3.5751054383581504e-05, 0.0016815672861412168, -5.2847190090687945e-05, + -0.00012122292537242174, -5.2847190090687945e-05, 0.0016815672861412168, -3.5751054383581504e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 5.712369238608517e-05, 0.0004774775879923254, 6.493427645182237e-05, - -1.9616374629549682e-05, 6.493427645182237e-05, 0.0004774775879923254, 5.712369238608517e-05, +- [0.0, 0.0, 0.0, -9.042513738677371e-06, 0.001337762805633247, -2.3656890334677882e-05, + -8.89973744051531e-05, -2.3656890334677882e-05, 0.001337762805633247, -9.042513738677371e-06, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 5.152165613253601e-05, 0.0003285413549747318, 5.838176002725959e-05, - -1.1792317309300415e-05, 5.838176002725959e-05, 0.0003285413549747318, 5.152165613253601e-05, +- [0.0, 0.0, 0.0, 1.0682300853659399e-05, 0.0010438387980684638, -1.2417168591127847e-06, + -6.368313188431785e-05, -1.2417168591127847e-06, 0.0010438387980684638, 1.0682300853659399e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 4.331897071097046e-05, 0.0002141948789358139, 4.8946971219265833e-05, - -6.56032307233545e-06, 4.8946971219265833e-05, 0.0002141948789358139, 4.331897071097046e-05, +- [0.0, 0.0, 0.0, 2.4065420802799053e-05, 0.0007959528011269867, 1.4940546861907933e-05, + -4.4190019252710044e-05, 1.4940546861907933e-05, 0.0007959528011269867, 2.4065420802799053e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 3.360482878633775e-05, 0.00012989896640647203, 3.7837718991795555e-05, - -3.2820951219036942e-06, 3.7837718991795555e-05, 0.00012989896640647203, 3.360482878633775e-05, +- [0.0, 0.0, 0.0, 3.1842464522924274e-05, 0.0005903124692849815, 2.545257484598551e-05, + -2.953799776150845e-05, 2.545257484598551e-05, 0.0005903124692849815, 3.1842464522924274e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 2.3491662432206795e-05, 7.109759462764487e-05, 2.6312056434107944e-05, - -1.4074875025471556e-06, 2.6312056434107944e-05, 7.109759462764487e-05, 2.3491662432206795e-05, +- [0.0, 0.0, 0.0, 3.4832115488825366e-05, 0.0004231349448673427, 3.0915121897123754e-05, + -1.8848557374440134e-05, 3.0915121897123754e-05, 0.0004231349448673427, 3.4832115488825366e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 1.4088440366322175e-05, 3.3226398954866454e-05, 1.5646359315724112e-05, - -4.728907185835851e-07, 1.5646359315724112e-05, 3.3226398954866454e-05, 1.4088440366322175e-05, +- [0.0, 0.0, 0.0, 3.392253347556107e-05, 0.00029060710221529007, 3.203889718861319e-05, + -1.1337729119986761e-05, 3.203889718861319e-05, 0.00029060710221529007, 3.392253347556107e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 6.461486464104382e-06, 1.1738436114683282e-05, 7.074640961945988e-06, - -1.0173076248065627e-07, 7.074640961945988e-06, 1.1738436114683282e-05, 6.461486464104382e-06, +- [0.0, 0.0, 0.0, 3.0058350603212602e-05, 0.00018886571342591196, 2.9644339520018548e-05, + -6.310981461865595e-06, 2.9644339520018548e-05, 0.00018886571342591196, 3.0058350603212602e-05, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, 1.5614931498930673e-06, 2.141876848327229e-06, 1.666849925641145e-06, - -7.360528631039642e-09, 1.666849925641145e-06, 2.141876848327229e-06, 1.5614931498930673e-06, +- [0.0, 0.0, 0.0, 2.4225962988566607e-05, 0.00011397439084248617, 2.467361446178984e-05, + -3.1589656828145962e-06, 2.467361446178984e-05, 0.00011397439084248617, 2.4225962988566607e-05, + 0.0, 0.0, 0.0, 0.0] +- [0.0, 0.0, 0.0, 1.743573375279084e-05, 6.192106229718775e-05, 1.818700366129633e-05, + -1.355306380901311e-06, 1.818700366129633e-05, 6.192106229718775e-05, 1.743573375279084e-05, + 0.0, 0.0, 0.0, 0.0] +- [0.0, 0.0, 0.0, 1.0700179700506851e-05, 2.8622565878322348e-05, 1.13408777906443e-05, + -4.555448072096624e-07, 1.13408777906443e-05, 2.8622565878322348e-05, 1.0700179700506851e-05, + 0.0, 0.0, 0.0, 0.0] +- [0.0, 0.0, 0.0, 5.000708824809408e-06, 9.94933634501649e-06, 5.334441539162071e-06, + -9.803432732269357e-08, 5.334441539162071e-06, 9.94933634501649e-06, 5.000708824809408e-06, + 0.0, 0.0, 0.0, 0.0] +- [0.0, 0.0, 0.0, 1.2279158454475692e-06, 1.7719224842949188e-06, 1.2988150501769269e-06, + -7.095271481460941e-09, 1.2988150501769269e-06, 1.7719224842949188e-06, 1.2279158454475692e-06, 0.0, 0.0, 0.0, 0.0] - [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] q20: 1.0 diff --git a/extra_tests/regression_fits/polarized_evol_34.json b/extra_tests/regression_fits/polarized_evol_34.json index c185258ef1..1165450546 100644 --- a/extra_tests/regression_fits/polarized_evol_34.json +++ b/extra_tests/regression_fits/polarized_evol_34.json @@ -25,46 +25,47 @@ "trainable": false } ], - "stop_epoch": 435, - "best_epoch": 323, - "erf_tr": 1.2238341569900513, - "erf_vl": 3.0599794387817383, - "chi2": 1.109000325202942, + "stop_epoch": 466, + "best_epoch": 354, + "erf_tr": 1.1801773309707642, + "erf_vl": 2.664975166320801, + "chi2": 1.2875453233718872, "pos_state": "POS_PASS", "arc_lengths": [ - 1.0326780832672715, - 1.014154549694492, + 1.0365227251310736, + 1.0125186351030275, 0.9899487587939698, 0.9899487587939698, 0.9899487587939698 ], "integrability": [ - 1.0061396160665481e-16, - 1.734723475976807e-17, - 3.122502256758253e-17, - 0.008682500803843137, - 7.979727989493313e-17 + 1.3183898417423734e-16, + 4.85722573273506e-17, + 4.85722573273506e-17, + 0.004581765737384488, + 2.0816681711721685e-16 ], "timing": { "walltime": { - "Total": 18.630010843276978, + "Total": 16.877962350845337, "start": 0.0, - "replica_set": 0.249741792678833, - "replica_fitted": 18.62974452972412, - "replica_set_to_replica_fitted": 18.380002737045288 + "replica_set": 0.2315657138824463, + "replica_fitted": 16.87779140472412, + "replica_set_to_replica_fitted": 16.646225690841675 }, "cputime": { - "Total": 19.099821179000003, + "Total": 17.490882718, "start": 0.0, - "replica_set": 0.24700718099999985, - "replica_fitted": 19.099551677, - "replica_set_to_replica_fitted": 18.852544496 + "replica_set": 0.2302778019999998, + "replica_fitted": 17.490709896, + "replica_set_to_replica_fitted": 17.260432094000002 } }, "version": { - "tensorflow": "2.16.1, mkl=??", + "keras": "3.3.3", + "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/single_dense_316.json b/extra_tests/regression_fits/single_dense_316.json index 97bad55b75..fee541f314 100644 --- a/extra_tests/regression_fits/single_dense_316.json +++ b/extra_tests/regression_fits/single_dense_316.json @@ -71,24 +71,25 @@ ], "timing": { "walltime": { - "Total": 34.44913601875305, + "Total": 30.10720419883728, "start": 0.0, - "replica_set": 0.25393104553222656, - "replica_fitted": 34.448877811431885, - "replica_set_to_replica_fitted": 34.19494676589966 + "replica_set": 0.23196172714233398, + "replica_fitted": 30.106998682022095, + "replica_set_to_replica_fitted": 29.87503695487976 }, "cputime": { - "Total": 35.914583166, + "Total": 31.332164543999998, "start": 0.0, - "replica_set": 0.24511515099999936, - "replica_fitted": 35.914323130999996, - "replica_set_to_replica_fitted": 35.669207979999996 + "replica_set": 0.23007352200000053, + "replica_fitted": 31.331957337000002, + "replica_set_to_replica_fitted": 31.101883815 } }, "version": { - "tensorflow": "2.16.1, mkl=??", + "keras": "3.3.3", + "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/trainable_prepro.yml b/extra_tests/regression_fits/trainable_prepro.yml index 5b5a69547b..132620e0b7 100644 --- a/extra_tests/regression_fits/trainable_prepro.yml +++ b/extra_tests/regression_fits/trainable_prepro.yml @@ -35,6 +35,9 @@ mcseed: 1 load: "weights.weights.h5" +sampling: + separate_multiplicative: True + parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] activation_per_layer: ['sigmoid', 'tanh', 'linear'] diff --git a/extra_tests/regression_fits/trainable_prepro_61.json b/extra_tests/regression_fits/trainable_prepro_61.json index 5c426e7b05..71d35e6f10 100644 --- a/extra_tests/regression_fits/trainable_prepro_61.json +++ b/extra_tests/regression_fits/trainable_prepro_61.json @@ -71,24 +71,25 @@ ], "timing": { "walltime": { - "Total": 34.79690074920654, + "Total": 31.844950675964355, "start": 0.0, - "replica_set": 0.24268245697021484, - "replica_fitted": 34.79669666290283, - "replica_set_to_replica_fitted": 34.55401420593262 + "replica_set": 0.23360300064086914, + "replica_fitted": 31.844779014587402, + "replica_set_to_replica_fitted": 31.611176013946533 }, "cputime": { - "Total": 36.326103099, + "Total": 32.889014591, "start": 0.0, - "replica_set": 0.24133399599999983, - "replica_fitted": 36.325896654, - "replica_set_to_replica_fitted": 36.084562657999996 + "replica_set": 0.23132029399999965, + "replica_fitted": 32.888841699, + "replica_set_to_replica_fitted": 32.657521405 } }, "version": { - "tensorflow": "2.16.1, mkl=??", + "keras": "3.3.3", + "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/n3fit/runcards/examples/Basic_runcard.yml b/n3fit/runcards/examples/Basic_runcard.yml index e64260d3bd..f315d80f45 100644 --- a/n3fit/runcards/examples/Basic_runcard.yml +++ b/n3fit/runcards/examples/Basic_runcard.yml @@ -73,12 +73,18 @@ positivity: posdatasets: - {dataset: NNPDF_POS_2P24GEV_F2U, maxlambda: 1e6} # Positivity Lagrange Multiplier - {dataset: NNPDF_POS_2P24GEV_FLL-19PTS, maxlambda: 1e6} + - {dataset: NNPDF_POS_2P24GEV_XGL, maxlambda: 1e6} ############################################################ integrability: integdatasets: - {dataset: NNPDF_INTEG_3GEV_XT3, maxlambda: 1e2} +# Apply a cut to a dataset or process type, in this case to the positivity dataset `NNPDF_POS_2P24GEV_XGL` which has process type: POS_XPDF +added_filter_rules: + - process_type: POS_XPDF + rule: "x > 0.1" + ############################################################ debug: True maxcores: 8 diff --git a/n3fit/runcards/examples/nnpdf40-like.yml b/n3fit/runcards/examples/nnpdf40-like.yml index 434c6173f4..f1d1ed1d91 100644 --- a/n3fit/runcards/examples/nnpdf40-like.yml +++ b/n3fit/runcards/examples/nnpdf40-like.yml @@ -101,8 +101,9 @@ theory: theoryid: 40_000_000 # For fits <= 4.0 multiplicative and additive uncertainties were sampled separately -sampling: - separate_multiplicative: False +# and thus the flag `separate_multiplicative` needs to be set to True +# sampling: +# separate_multiplicative: True ################################################################################ trvlseed: 591866982 diff --git a/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml b/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml index 30008f22b3..f89604952a 100644 --- a/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml +++ b/n3fit/runcards/hyperopt_studies/renew_hyperopt.yml @@ -99,9 +99,6 @@ datacuts: theory: theoryid: 700 # database id -sampling: - separate_multiplicative: false - hyperscan_config: stopping: min_epochs: 15e3 diff --git a/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml b/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml index 332247100d..3f343e6e3a 100644 --- a/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml +++ b/n3fit/runcards/hyperopt_studies/restricted_search_space_renew_hyperopt.yml @@ -99,9 +99,6 @@ datacuts: theory: theoryid: 700 # database id -sampling: - separate_multiplicative: false - hyperscan_config: architecture: n_layers: [2] diff --git a/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py b/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py index 31def842c4..ed083983ff 100644 --- a/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py +++ b/n3fit/src/n3fit/backends/keras_backend/MetaLayer.py @@ -8,8 +8,8 @@ For instance: np_to_tensor is just a call to K.constant """ -from tensorflow.keras.layers import Layer from tensorflow.keras.initializers import Constant, RandomUniform, glorot_normal, glorot_uniform +from tensorflow.keras.layers import Layer # Define in this dictionary new initializers as well as the arguments they accept (with default values if needed be) initializers = { @@ -25,7 +25,7 @@ class MetaLayer(Layer): In order to write a custom Keras layer you usually need to override: - __init__ - - meta_call + - call """ initializers = initializers diff --git a/n3fit/src/n3fit/backends/keras_backend/MetaModel.py b/n3fit/src/n3fit/backends/keras_backend/MetaModel.py index 21c858a181..7ea2d5b9b1 100644 --- a/n3fit/src/n3fit/backends/keras_backend/MetaModel.py +++ b/n3fit/src/n3fit/backends/keras_backend/MetaModel.py @@ -8,10 +8,10 @@ from pathlib import Path import re -from keras import optimizers as Kopt -from keras.models import Model import numpy as np import tensorflow as tf +from tensorflow.keras import optimizers as Kopt +from tensorflow.keras.models import Model from tensorflow.python.keras.utils import tf_utils # pylint: disable=no-name-in-module import n3fit.backends.keras_backend.operations as op diff --git a/n3fit/src/n3fit/backends/keras_backend/base_layers.py b/n3fit/src/n3fit/backends/keras_backend/base_layers.py index a68f058c5a..e6afc6c5c6 100644 --- a/n3fit/src/n3fit/backends/keras_backend/base_layers.py +++ b/n3fit/src/n3fit/backends/keras_backend/base_layers.py @@ -135,7 +135,6 @@ def apply_dense(xinput): "dense": ( MultiDense, { - "input_shape": (1,), "replica_seeds": None, "base_seed": 0, "kernel_initializer": "glorot_normal", @@ -148,7 +147,6 @@ def apply_dense(xinput): "single_dense": ( Dense, { - "input_shape": (1,), "kernel_initializer": "glorot_normal", "units": 5, "activation": "sigmoid", @@ -158,7 +156,6 @@ def apply_dense(xinput): "dense_per_flavour": ( dense_per_flavour, { - "input_shape": (1,), "kernel_initializer": "glorot_normal", "units": 5, "activation": "sigmoid", @@ -194,7 +191,7 @@ def base_layer_selector(layer_name, **kwargs): layer_tuple = layers[layer_name] except KeyError as e: raise NotImplementedError( - "Layer not implemented in keras_backend/base_layers.py: {0}".format(layer_name) + f"Layer not implemented in keras_backend/base_layers.py: {layer_name}" ) from e layer_class = layer_tuple[0] @@ -234,7 +231,7 @@ def regularizer_selector(reg_name, **kwargs): reg_tuple = regularizers[reg_name] except KeyError: raise NotImplementedError( - "Regularizer not implemented in keras_backend/base_layers.py: {0}".format(reg_name) + f"Regularizer not implemented in keras_backend/base_layers.py: {reg_name}" ) reg_class = reg_tuple[0] diff --git a/n3fit/src/n3fit/backends/keras_backend/multi_dense.py b/n3fit/src/n3fit/backends/keras_backend/multi_dense.py index 6d789de90e..07b045fb45 100644 --- a/n3fit/src/n3fit/backends/keras_backend/multi_dense.py +++ b/n3fit/src/n3fit/backends/keras_backend/multi_dense.py @@ -4,11 +4,9 @@ Dense layer from Keras even in the single replica case. """ # Tested last: Feb 2024 -from typing import List - -from keras.initializers import Initializer -from keras.layers import Dense import tensorflow as tf +from tensorflow.keras.initializers import Initializer +from tensorflow.keras.layers import Dense # Note for developers: # This class plays with fire as it exploits the internals of Keras @@ -51,7 +49,7 @@ class MultiDense(Dense): def __init__( self, - replica_seeds: List[int], + replica_seeds: list[int], kernel_initializer: Initializer, is_first_layer: bool = False, base_seed: int = 0, @@ -176,7 +174,7 @@ class MultiInitializer(Initializer): Base seed for the single replica initializer to which the replica seeds are added. """ - def __init__(self, single_initializer: Initializer, replica_seeds: List[int], base_seed: int): + def __init__(self, single_initializer: Initializer, replica_seeds: list[int], base_seed: int): self.initializer_class = type(single_initializer) self.initializer_config = single_initializer.get_config() self.base_seed = base_seed diff --git a/n3fit/src/n3fit/backends/keras_backend/operations.py b/n3fit/src/n3fit/backends/keras_backend/operations.py index 844274379c..b6ad0e010e 100644 --- a/n3fit/src/n3fit/backends/keras_backend/operations.py +++ b/n3fit/src/n3fit/backends/keras_backend/operations.py @@ -25,10 +25,10 @@ from typing import Optional -import keras import numpy as np import numpy.typing as npt import tensorflow as tf +from tensorflow import keras from tensorflow.keras import backend as K from tensorflow.keras.layers import Input from tensorflow.keras.layers import Lambda as keras_Lambda @@ -228,14 +228,21 @@ def reshape(x, shape): return tf.reshape(x, shape) -def boolean_mask(*args, **kwargs): +@tf.function +def boolean_mask(*args, target_shape=None, **kwargs): """ Applies a boolean mask to a tensor Relevant parameters: (tensor, mask, axis=None) see full `docs `_. + + tensorflow's masking concatenates the masked dimensions, it is possible to + provide a `target_shape` to reshape the output to the desired shape """ - return tf.boolean_mask(*args, **kwargs) + ret = tf.boolean_mask(*args, **kwargs) + if target_shape is not None: + ret = reshape(ret, target_shape) + return ret @tf.function diff --git a/n3fit/src/n3fit/checks.py b/n3fit/src/n3fit/checks.py index 3ff404ffe5..9aa05dfae8 100644 --- a/n3fit/src/n3fit/checks.py +++ b/n3fit/src/n3fit/checks.py @@ -417,7 +417,7 @@ def check_consistent_basis(sum_rules, fitbasis, basis, theoryid, parameters): @make_argcheck -def check_consistent_parallel(parameters, parallel_models, same_trvl_per_replica): +def check_consistent_parallel(parameters, parallel_models): """Checks whether the multiple-replica fit options are consistent among them i.e., that the trvl seed is fixed and the layer type is correct """ diff --git a/n3fit/src/n3fit/hyper_optimization/rewards.py b/n3fit/src/n3fit/hyper_optimization/rewards.py index bba8057d89..9f48208599 100644 --- a/n3fit/src/n3fit/hyper_optimization/rewards.py +++ b/n3fit/src/n3fit/hyper_optimization/rewards.py @@ -32,7 +32,7 @@ """ import logging -from typing import Callable, Dict, List +from typing import Callable import numpy as np @@ -194,10 +194,10 @@ def __init__( def compute_loss( self, - penalties: Dict[str, np.ndarray], + penalties: dict[str, np.ndarray], experimental_loss: np.ndarray, pdf_model: MetaModel, - experimental_data: List[DataGroupSpec], + experimental_data: list[DataGroupSpec], fold_idx: int = 0, ) -> float: """ @@ -271,7 +271,7 @@ def _save_hyperopt_metrics( self, phi_per_fold: float, chi2_per_fold: np.ndarray, - penalties: Dict[str, np.ndarray], + penalties: dict[str, np.ndarray], fold_idx: int = 0, ) -> None: """ @@ -403,7 +403,7 @@ def _set_central_value(n3pdf, model): # Get the input x for key, grid in model.x_in.items(): - if key != "integration_grid": + if key != "xgrid_integration": input_x = grid.numpy() break diff --git a/n3fit/src/n3fit/layers/mask.py b/n3fit/src/n3fit/layers/mask.py index 2b0bff6c00..3ed007a18f 100644 --- a/n3fit/src/n3fit/layers/mask.py +++ b/n3fit/src/n3fit/layers/mask.py @@ -43,7 +43,7 @@ def build(self, input_shape): self.masked_output_shape = [-1 if d is None else d for d in input_shape] self.masked_output_shape[-1] = self.last_dim self.masked_output_shape[-2] = self.mask.shape[-2] - super(Mask, self).build(input_shape) + super().build(input_shape) def call(self, ret): """ @@ -58,8 +58,7 @@ def call(self, ret): Tensor of shape (batch_size, n_replicas, n_features) """ if self.mask is not None: - flat_res = op.boolean_mask(ret, self.mask, axis=1) - ret = op.reshape(flat_res, shape=self.masked_output_shape) + ret = op.boolean_mask(ret, self.mask, axis=1, target_shape=self.masked_output_shape) if self.c is not None: ret = ret * self.kernel return ret diff --git a/n3fit/src/n3fit/model_gen.py b/n3fit/src/n3fit/model_gen.py index f45a0f7205..e5a2cf55ba 100644 --- a/n3fit/src/n3fit/model_gen.py +++ b/n3fit/src/n3fit/model_gen.py @@ -11,7 +11,7 @@ """ from dataclasses import dataclass -from typing import Callable, List +from typing import Callable import numpy as np @@ -320,8 +320,8 @@ def observable_generator( def generate_pdf_model( - nodes: List[int] = None, - activations: List[str] = None, + nodes: list[int] = None, + activations: list[str] = None, initializer_name: str = "glorot_normal", layer_type: str = "dense", flav_info: dict = None, @@ -383,8 +383,8 @@ def generate_pdf_model( def pdfNN_layer_generator( - nodes: List[int] = None, - activations: List[str] = None, + nodes: list[int] = None, + activations: list[str] = None, initializer_name: str = "glorot_normal", layer_type: str = "dense", flav_info: dict = None, @@ -547,13 +547,13 @@ def pdfNN_layer_generator( # Define the main input do_nothing = lambda x: x if use_feature_scaling: - pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name='scaledx_x') + pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name="scaledx_x") process_input = do_nothing - extract_nn_input = Lambda(lambda x: op.op_gather_keep_dims(x, 0, axis=-1), name='x_scaled') - extract_original = Lambda(lambda x: op.op_gather_keep_dims(x, 1, axis=-1), name='x') + extract_nn_input = Lambda(lambda x: op.op_gather_keep_dims(x, 0, axis=-1), name="x_scaled") + extract_original = Lambda(lambda x: op.op_gather_keep_dims(x, 1, axis=-1), name="pdf_input") else: # add log(x) - pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name='x') - process_input = Lambda(lambda x: op.concatenate([x, op.op_log(x)], axis=-1), name='x_logx') + pdf_input = Input(shape=(None, pdf_input_dimensions), batch_size=1, name="pdf_input") + process_input = Lambda(lambda x: op.concatenate([x, op.op_log(x)], axis=-1), name="x_logx") extract_original = do_nothing extract_nn_input = do_nothing @@ -564,12 +564,12 @@ def pdfNN_layer_generator( if use_feature_scaling: input_x_eq_1 = scaler(input_x_eq_1)[0] # the layer that subtracts 1 from the NN output - subtract_one_layer = Lambda(op.op_subtract, name='subtract_one') - layer_x_eq_1 = op.numpy_to_input(np.array(input_x_eq_1).reshape(1, 1), name='x_eq_1') + subtract_one_layer = Lambda(op.op_subtract, name="subtract_one") + layer_x_eq_1 = op.numpy_to_input(np.array(input_x_eq_1).reshape(1, 1), name="x_eq_1") model_input["layer_x_eq_1"] = layer_x_eq_1 # the layer that multiplies the NN output by the preprocessing factor - apply_preprocessing_factor = Lambda(op.op_multiply, name='prefactor_times_NN') + apply_preprocessing_factor = Lambda(op.op_multiply, name="prefactor_times_NN") # Photon layer layer_photon = AddPhoton(photons=photons, name="add_photon") @@ -580,20 +580,19 @@ def pdfNN_layer_generator( ) # Evolution layer - layer_evln = FkRotation(input_shape=(last_layer_nodes,), output_dim=out, name="pdf_FK_basis") + layer_evln = FkRotation(output_dim=out, name="pdf_FK_basis") # Normalization and sum rules if impose_sumrule: sumrule_layer, integrator_input = generate_msr_model_and_grid( fitbasis=fitbasis, mode=impose_sumrule, scaler=scaler, replica_seeds=seed ) - model_input["integrator_input"] = integrator_input + model_input["xgrid_integration"] = integrator_input else: sumrule_layer = lambda x: x compute_preprocessing_factor = Preprocessing( flav_info=flav_info, - input_shape=(1,), name=PREPROCESSING_LAYER_ALL_REPLICAS, replica_seeds=seed, large_x=not subtract_one, @@ -685,10 +684,10 @@ def compute_unnormalized_pdf(x): def generate_nn( layer_type: str, nodes_in: int, - nodes: List[int], - activations: List[str], + nodes: list[int], + activations: list[str], initializer_name: str, - replica_seeds: List[int], + replica_seeds: list[int], dropout: float, regularizer: str, regularizer_args: dict, @@ -727,7 +726,7 @@ def generate_nn( Single model containing all replicas. """ nodes_list = list(nodes) # so we can modify it - x_input = Input(shape=(None, nodes_in), batch_size=1, name='xgrids_processed') + x_input = Input(shape=(None, nodes_in), batch_size=1, name="NN_input") reg = regularizer_selector(regularizer, **regularizer_args) if layer_type == "dense_per_flavour": @@ -753,7 +752,6 @@ def layer_generator(i_layer, nodes_out, activation): kernel_initializer=initializers, units=int(nodes_out), activation=activation, - input_shape=(nodes_in,), basis_size=basis_size, ) layers.append(layer) @@ -775,7 +773,6 @@ def layer_generator(i_layer, nodes_out, activation): ), units=nodes_out, activation=activation, - input_shape=(nodes_in,), regularizer=reg, ) diff --git a/n3fit/src/n3fit/model_trainer.py b/n3fit/src/n3fit/model_trainer.py index df2e0be917..21da5d0d17 100644 --- a/n3fit/src/n3fit/model_trainer.py +++ b/n3fit/src/n3fit/model_trainer.py @@ -352,7 +352,7 @@ def _xgrid_generation(self): if self._scaler: # Apply feature scaling if given input_arr = self._scaler(input_arr) - input_layer = op.numpy_to_input(input_arr) + input_layer = op.numpy_to_input(input_arr, name="pdf_input") # The PDF model will be called with a concatenation of all inputs # now the output needs to be splitted so that each experiment takes its corresponding input diff --git a/n3fit/src/n3fit/msr.py b/n3fit/src/n3fit/msr.py index a9a30190c2..a66e03a3fe 100644 --- a/n3fit/src/n3fit/msr.py +++ b/n3fit/src/n3fit/msr.py @@ -68,7 +68,7 @@ def generate_msr_model_and_grid( xgrid_integration = scaler(xgrid_integration) # Turn into input layer. - xgrid_integration = op.numpy_to_input(xgrid_integration, name="integration_grid") + xgrid_integration = op.numpy_to_input(xgrid_integration, name="xgrid_integration") # 1c Get the original grid if scaler: @@ -88,7 +88,7 @@ def generate_msr_model_and_grid( )([x_divided, pdf_xgrid_integration]) # 4. Integrate the pdf - pdf_integrated = xIntegrator(weights_array, input_shape=(nx,))(pdf_integrand) + pdf_integrated = xIntegrator(weights_array)(pdf_integrand) # 5. THe input for the photon integral, will be set to 0 if no photons photon_integral = Input(shape=(replicas, 1), batch_size=1, name='photon_integral') diff --git a/n3fit/src/n3fit/n3fit_checks_provider.py b/n3fit/src/n3fit/n3fit_checks_provider.py index a06b3f0efd..a9a07ab4be 100644 --- a/n3fit/src/n3fit/n3fit_checks_provider.py +++ b/n3fit/src/n3fit/n3fit_checks_provider.py @@ -28,7 +28,6 @@ def n3fit_checks_action( kfold=None, tensorboard=None, parallel_models=False, - same_trvl_per_replica=False, double_precision=False, ): return diff --git a/n3fit/src/n3fit/scripts/n3fit_exec.py b/n3fit/src/n3fit/scripts/n3fit_exec.py index 2a749fa846..9c68bbb5e1 100755 --- a/n3fit/src/n3fit/scripts/n3fit_exec.py +++ b/n3fit/src/n3fit/scripts/n3fit_exec.py @@ -180,7 +180,7 @@ def from_yaml(cls, o, *args, **kwargs): # Sampling flags if (sam_t0 := file_content.get('sampling')) is not None: N3FIT_FIXED_CONFIG['separate_multiplicative'] = sam_t0.get( - 'separate_multiplicative', True + 'separate_multiplicative', False ) # Fitting flag file_content.update(N3FIT_FIXED_CONFIG) diff --git a/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml b/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml index 87ac1edaff..4608267ee2 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard-sequential.yml @@ -31,6 +31,8 @@ nnseed: 2 mcseed: 1 save: weights.weights.h5 +sampling: + separate_multiplicative: true parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] diff --git a/n3fit/src/n3fit/tests/regressions/quickcard.yml b/n3fit/src/n3fit/tests/regressions/quickcard.yml index ca51c9a339..19b32652dc 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard.yml @@ -34,6 +34,8 @@ nnseed: 2 mcseed: 1 load: "weights.weights.h5" +sampling: + separate_multiplicative: true parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] diff --git a/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml b/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml index 94bc90414f..8702cb5229 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard_pol.yml @@ -32,6 +32,8 @@ nnseed: 2 mcseed: 1 load: "weights_pol.weights.h5" +sampling: + separate_multiplicative: true parameters: nodes_per_layer: [25, 20, 4] diff --git a/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml b/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml index 684bb47afd..282f982876 100644 --- a/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml +++ b/n3fit/src/n3fit/tests/regressions/quickcard_qed.yml @@ -34,6 +34,8 @@ nnseed: 2 mcseed: 1 load: "weights.weights.h5" +sampling: + separate_multiplicative: true parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 8] diff --git a/n3fit/src/n3fit/tests/test_multireplica.py b/n3fit/src/n3fit/tests/test_multireplica.py index 61f40716a1..aa1893ff3f 100644 --- a/n3fit/src/n3fit/tests/test_multireplica.py +++ b/n3fit/src/n3fit/tests/test_multireplica.py @@ -23,10 +23,10 @@ def test_replica_split(): eps = 1e-9 pdf_input = np.maximum(rng.random((1, 5, 1)), eps) int_input = np.maximum(rng.random((1, 2_000, 1)), eps) - + fake_input = { 'pdf_input': np.sort(pdf_input, axis=1), - 'integrator_input': np.sort(int_input, axis=1), + 'xgrid_integration': np.sort(int_input, axis=1), } output_full = pdf_model(fake_input) diff --git a/n3fit/src/n3fit/tests/test_preprocessing.py b/n3fit/src/n3fit/tests/test_preprocessing.py index 2ed415df87..4a448172e5 100644 --- a/n3fit/src/n3fit/tests/test_preprocessing.py +++ b/n3fit/src/n3fit/tests/test_preprocessing.py @@ -86,7 +86,7 @@ def test_constraint(): x = Input(shape=test_x.shape[1:]) prefactors = prepro(x) scalar = Lambda(lambda x: op.sum(x, axis=(1, 2, 3)))(prefactors) - model = MetaModel(input_tensors={'x': x}, output_tensors=scalar) + model = MetaModel(input_tensors={'pdf_input': x}, output_tensors=scalar) model.compile(loss='mse', learning_rate=1e-15) # Simulate training where weights of replica 1 are updated to violate the constraint diff --git a/nnpdf_data/nnpdf_data/filter_utils/utils.py b/nnpdf_data/nnpdf_data/filter_utils/utils.py index d59c197f86..e38dacb70a 100644 --- a/nnpdf_data/nnpdf_data/filter_utils/utils.py +++ b/nnpdf_data/nnpdf_data/filter_utils/utils.py @@ -1,11 +1,373 @@ """ -Module contains general utility functions for general use in implementing datasets. +General Python utilities for commondata implementation. + +This module provides helpful functions that automate a few +tasks that are regularly needed for the implementation of +experimental data to the commondata format. If there are +any additional functions that could be added here as they +could simplify some repetitve tasks, please do suggest. + +Before the usage of any functions, it is recommended to read +the docstrings of the function to understand the inputs and +outputs. """ +from math import sqrt + import numpy as np +from numpy.linalg import eig import yaml +def symmetrize_errors(delta_plus, delta_minus): + r"""Compute the symmterized uncertainty and the shift in data point. + + Parameters + ---------- + delta_plus : float + The top/plus uncertainty with sign + delta_minus : float + The bottom/minus uncertainty with sign + + Returns + ------- + se_delta : float + The value to be added to the data point + se_sigma : float + The symmetrized uncertainty to be used in commondata + + """ + semi_diff = (delta_plus + delta_minus) / 2 + average = (delta_plus - delta_minus) / 2 + se_delta = semi_diff + se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff) + return se_delta, se_sigma + + +def percentage_to_absolute(percentage, value): + r"""Compute the absolute value of uncertainty from percentage. + + Parameters + ---------- + percentage : string/float + Experimental datasets can provide the percentage + uncertainties with a % sign or without one. + The function will autostrip % sign and convert to + a float type in case the percentage uncertainty + comes with a % sign. Else, it will directly perform + the computation. + value : float + The data point + + Returns + ------- + absolute : float + The absolute value of the uncertainty + + """ + if type(percentage) is str: + percentage = float(percentage.replace("%", "")) + absolute = percentage * value * 0.01 + return absolute + else: + absolute = percentage * value * 0.01 + return absolute + + +def cormat_to_covmat(err_list, cormat_list): + r"""Convert correlation matrix elements to covariance + matrix elements. + + Parameters + ---------- + err_list : list + A one dimensional list which contains the uncertainty + associated to each data point in order. + cormat_list : list + A one dimensional list which contains the elements of + the correlation matrix row by row. Since experimental + datasets provide these matrices in a list form, this + simplifies the implementation for the user. + + Returns + ------- + covmat_list : list + A one dimensional list which contains the elements of + the covariance matrix row by row. + + """ + covmat_list = [] + for i in range(len(cormat_list)): + a = i // len(err_list) + b = i % len(err_list) + covmat_list.append(cormat_list[i] * err_list[a] * err_list[b]) + return covmat_list + + +def covmat_to_artunc(ndata, covmat_list, no_of_norm_mat=0): + r"""Convert the covariance matrix to a matrix of + artificial uncertainties. + + Parameters + ---------- + ndata : integer + Number of data points + covmat_list : list + A one dimensional list which contains the elements of + the covariance matrix row by row. Since experimental + datasets provide these matrices in a list form, this + simplifies the implementation for the user. + no_of_norm_mat : int + Normalized covariance matrices may have an eigenvalue + of 0 due to the last data point not being linearly + independent. To allow for this, the user should input + the number of normalized matrices that are being treated + in an instance. For example, if a single covariance matrix + of a normalized distribution is being processed, the input + would be 1. If a covariance matrix contains pertains to + 3 normalized datasets (i.e. cross covmat for 3 + distributions), the input would be 3. The default value is + 0 for when the covariance matrix pertains to an absolute + distribution. + + Returns + ------- + artunc : list + A two dimensional matrix (given as a list of lists) + which contains artificial uncertainties to be added + to the commondata. i^th row (or list) contains the + artificial uncertainties of the i^th data point. + + """ + epsilon = -0.0000000001 + neg_eval_count = 0 + psd_check = True + covmat = np.zeros((ndata, ndata)) + artunc = np.zeros((ndata, ndata)) + for i in range(len(covmat_list)): + a = i // ndata + b = i % ndata + covmat[a][b] = covmat_list[i] + eigval, eigvec = eig(covmat) + for j in range(len(eigval)): + if eigval[j] < epsilon: + psd_check = False + elif eigval[j] > epsilon and eigval[j] <= 0: + neg_eval_count = neg_eval_count + 1 + if neg_eval_count == (no_of_norm_mat + 1): + psd_check = False + elif eigval[j] > 0: + continue + if not psd_check: + raise ValueError('The covariance matrix is not positive-semidefinite') + else: + for i in range(ndata): + for j in range(ndata): + if eigval[j] < 0: + continue + else: + artunc[i][j] = eigvec[i][j] * sqrt(eigval[j]) + return artunc.tolist() + + +def cross_cormat_to_covmat(row_err_list, col_err_list, cormat_list): + r"""Convert cross correlation matrix elements + (i.e. those between different different variables or + observables) to covariance matrix elements. + + Parameters + ---------- + row_err_list : list + A one dimensional list which contains the uncertainty + associated to each data point of the variable that is + given on the vertical axis. + col_err_list : list + A one dimensional list which contains the uncertainty + associated to each data point of the variable that is + given on the horizontal axis. + cormat_list : list + A one dimensional list which contains the elements of + the correlation matrix row by row. Since experimental + datasets provide these matrices in a list form, this + simplifies the implementation for the user. + + Returns + ------- + covmat_list : list + A one dimensional list which contains the elements of + the covariance matrix row by row. + + """ + covmat_list = [] + for i in range(len(cormat_list)): + a = i // len(col_err_list) + b = i % len(col_err_list) + covmat_list.append(cormat_list[i] * row_err_list[a] * col_err_list[b]) + return covmat_list + + +def matlist_to_matrix(rows, columns, mat_list): + r"""Convert a 1d list to a 2d matrix. + + Note: This utils function is not strictly needed for + data implementation, however, it is provided for + the aid of the user due to how matrices are treated + throughout all the other functions. This function + allows the user to convert a list that contains the + elemnets of matrix row by row to a proper matrix, if + need be for any reason. + + Parameters + ---------- + rows : int + No. of rows in the matrix + columns : int + No. of columns in the matrix + mat_list : list + A one dimensional list which contains the elements of + the matrix row by row. + + Returns + ------- + matrix : numpy.ndarray + The matrix as a numpy 2d array. + + """ + if rows * columns == len(mat_list): + matrix = np.zeros((rows, columns)) + for i in range(rows): + for j in range(columns): + matrix[i][j] = mat_list[j + i * columns] + matrix = np.array(matrix) + return matrix + else: + raise Exception('rows * columns != len(mat_list)') + + +def concat_matrices(rows, columns, list_of_matrices): + r"""Join smaller matrices into a large matrix. + + This function aims to simplify the process of joining multiple + smaller matrices into one large matrix. Such a need could arise, + for instance, when cross variable covariance matrices are provided + but the user needs to join all the matrices to generate the full + covariance matrix corresponding to the entire dataset. + + Parameters + ---------- + rows : int + No. of rows of matrices to be concatenated. E.g., if 6 + matrices: A, B, C, D, E, F need to be joined as + [[A, B, C], + [D, E, F]], + the number of rows would be 2. + columns : int + No. of columns of matrices to be concatenated. In the + above example, this would be 3. + list_of_matrices : list + A list of the matrices that have to concatenated row by + row. In the above example, this would be [A, B, C, D, E, F]. + The matrices themselves need to be provided as a list of lists, + or a numpy 2d array. If the user has the matrix in a 1d row by + row form, use matList_to_matrix() to convert it. It is assumed + the user verifies that all the input matrices have the correct + dimensions. Matrices with incompatible dimensions will lead to + undesired behavior. + + Returns + ------- + final_mat_list : list + A one dimensional list which contains the elements of + the final, fully concatenated matrix row by row. + + """ + for i in range(len(list_of_matrices)): + list_of_matrices[i] = np.array(list_of_matrices[i]) + col_list = [] + for i in range(rows): + row_list = [] + for j in range(columns): + row_list.append(list_of_matrices[j + i * columns]) + col_list.append(np.concatenate(tuple(row_list), axis=1)) + final_mat = np.concatenate(tuple(col_list), axis=0) + final_mat_list = [] + for i in range(len(final_mat)): + for j in range(len(final_mat[i])): + final_mat_list.append(final_mat[i][j]) + return final_mat_list + + +def trimat_to_fullmat(mode, tri_mat_list): + r"""Convert a list of values of a triangular matrix + to a symmetric matrix. + + Experimental datasets can provide the entries of + correlation or covariance matrices as a triangular + matrix, as these matrices are symmetric by their + very nature. This function can convert these list to + a complete symmetric matrix, that can be used for the + dataset implementation. + + mode : bool + Enter 0 or 1 based on the following scenarios: + Use mode 0 if matrix entries are given row by + row such as: + 0 1 2 3 + 4 5 6 + 7 8 + 9 + Use mode 1 if the matrix entries are given column + by column such as: + 0 1 3 6 + 2 4 7 + 5 8 + 9 + Please note that the numbers above (0-9) are not + entries of the matrix but rather the index of the + entries of the list which contains the elements of + the triangular matrix. + tri_mat_list : list + A list containing the elements of the triangular matrix, + for example, for a 4*4 matrix, the list of + triangular matrix entries could be: + [a, b, c, d, e, f, g, h, i, j] + + Returns + ------- + mat_list : list + A one dimensional list which contains the elements of + the fully populated, symmetric matrix row by row. + + """ + dim = int((np.sqrt(1 + 8 * len(tri_mat_list)) - 1) / 2) + matrix = np.zeros((dim, dim)) + if mode == 0: + for i in range(dim): + for j in range(i + 1): + list_el = len(tri_mat_list) - 1 - ((i * (i + 1)) // 2 + j) + if i == j: + matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] + else: + matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] + matrix[dim - 1 - j][dim - 1 - i] = tri_mat_list[list_el] + elif mode == 1: + for i in range(dim): + for j in range(i + 1): + list_el = (i * (i + 1)) // 2 + j + if i == j: + matrix[i][j] = tri_mat_list[list_el] + else: + matrix[i][j] = tri_mat_list[list_el] + matrix[j][i] = tri_mat_list[list_el] + else: + raise Exception('Mode should be 0 or 1, refer to the function for usage') + mat_list = [] + for i in range(dim): + for j in range(dim): + mat_list.append(matrix[i][j]) + return mat_list + + def correlation_to_covariance(correlation, uncertainties): """ Converts a correlation matrix into a covariance matrix diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py index ff222f5fea..b0606649fe 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_1JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py index 0655765b51..6ddd20bef2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_2JET_13TEV_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py index 25e6371f66..e8de287406 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/artunc.py @@ -1,9 +1,9 @@ -import yaml import numpy as np -from utils import covmat_to_artunc as cta -from utils import matlist_to_matrix as mtm -from utils import concat_matrices as cm +import yaml +from nnpdf_data.filter_utils.utils import concat_matrices as cm +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import matlist_to_matrix as mtm covmat_mtt = [] covmat_mtt_norm = [] @@ -22,7 +22,7 @@ covmat_496 = [] covmat_497 = [] -covariance_matrix_mtt="rawdata/Table464.yaml" +covariance_matrix_mtt = "rawdata/Table464.yaml" with open(covariance_matrix_mtt, 'r') as file1: input1 = yaml.safe_load(file1) for i in range(81): @@ -30,7 +30,7 @@ artunc_mtt = cta(9, covmat_mtt) -covariance_matrix_mtt_norm="rawdata/Table462.yaml" +covariance_matrix_mtt_norm = "rawdata/Table462.yaml" with open(covariance_matrix_mtt_norm, 'r') as file2: input2 = yaml.safe_load(file2) for i in range(81): @@ -38,14 +38,14 @@ artunc_mtt_norm = cta(9, covmat_mtt_norm, 1) -covariance_matrix_ytt="rawdata/Table476.yaml" +covariance_matrix_ytt = "rawdata/Table476.yaml" with open(covariance_matrix_ytt, 'r') as file3: input3 = yaml.safe_load(file3) for i in range(144): covmat_ytt.append(input3['dependent_variables'][0]['values'][i]['value']) artunc_ytt = cta(12, covmat_ytt) -covariance_matrix_ytt_norm="rawdata/Table474.yaml" +covariance_matrix_ytt_norm = "rawdata/Table474.yaml" with open(covariance_matrix_ytt_norm, 'r') as file4: input4 = yaml.safe_load(file4) for i in range(144): @@ -92,7 +92,21 @@ covmat_506.append(input10['dependent_variables'][0]['values'][i]['value']) covmat_506 = mtm(3, 3, covmat_506) -covmat_mtt_ytt = cm(3, 3, [covmat_501, covmat_502t, covmat_504t, covmat_502, covmat_503, covmat_505t, covmat_504, covmat_505, covmat_506]) +covmat_mtt_ytt = cm( + 3, + 3, + [ + covmat_501, + covmat_502t, + covmat_504t, + covmat_502, + covmat_503, + covmat_505t, + covmat_504, + covmat_505, + covmat_506, + ], +) artunc_mtt_ytt = cta(11, covmat_mtt_ytt) # abs mtt-ytt-norm @@ -135,5 +149,19 @@ covmat_497.append(input16['dependent_variables'][0]['values'][i]['value']) covmat_497 = mtm(3, 3, covmat_497) -covmat_mtt_ytt_norm = cm(3, 3, [covmat_492, covmat_493t, covmat_495t, covmat_493, covmat_494, covmat_496t, covmat_495, covmat_496, covmat_497]) +covmat_mtt_ytt_norm = cm( + 3, + 3, + [ + covmat_492, + covmat_493t, + covmat_495t, + covmat_493, + covmat_494, + covmat_496t, + covmat_495, + covmat_496, + covmat_497, + ], +) artunc_mtt_ytt_norm = cta(11, covmat_mtt_ytt_norm, 1) diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py deleted file mode 100644 index dac59de537..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_HADR_DIF/utils.py +++ /dev/null @@ -1,369 +0,0 @@ -""" -Python utilities for commondata implementation. - -This module provides helpful functions that automate a few -tasks that are regularly needed for the implementation of -experimental data to the commondata format. If there are -any additional functions that could be added here as they -could simplify some repetitve tasks, please do suggest. - -Before the usage of any functions, it is recommended to read -the docstrings of the function to understand the inputs and -outputs. - -@author: Tanishq Sharma -""" - -from math import sqrt - -import numpy as np -from numpy.linalg import eig - - -def symmetrize_errors(delta_plus, delta_minus): - r"""Compute the symmterized uncertainty and the shift in data point. - - Parameters - ---------- - delta_plus : float - The top/plus uncertainty with sign - delta_minus : float - The bottom/minus uncertainty with sign - - Returns - ------- - se_delta : float - The value to be added to the data point - se_sigma : float - The symmetrized uncertainty to be used in commondata - - """ - semi_diff = (delta_plus + delta_minus) / 2 - average = (delta_plus - delta_minus) / 2 - se_delta = semi_diff - se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff) - return se_delta, se_sigma - - -def percentage_to_absolute(percentage, value): - r"""Compute the absolute value of uncertainty from percentage. - - Parameters - ---------- - percentage : string/float - Experimental datasets can provide the percentage - uncertainties with a % sign or without one. - The function will autostrip % sign and convert to - a float type in case the percentage uncertainty - comes with a % sign. Else, it will directly perform - the computation. - value : float - The data point - - Returns - ------- - absolute : float - The absolute value of the uncertainty - - """ - if type(percentage) is str: - percentage = float(percentage.replace("%", "")) - absolute = percentage * value * 0.01 - return absolute - else: - absolute = percentage * value * 0.01 - return absolute - - -def cormat_to_covmat(err_list, cormat_list): - r"""Convert correlation matrix elements to covariance - matrix elements. - - Parameters - ---------- - err_list : list - A one dimensional list which contains the uncertainty - associated to each data point in order. - cormat_list : list - A one dimensional list which contains the elements of - the correlation matrix row by row. Since experimental - datasets provide these matrices in a list form, this - simplifies the implementation for the user. - - Returns - ------- - covmat_list : list - A one dimensional list which contains the elements of - the covariance matrix row by row. - - """ - covmat_list = [] - for i in range(len(cormat_list)): - a = i // len(err_list) - b = i % len(err_list) - covmat_list.append(cormat_list[i] * err_list[a] * err_list[b]) - return covmat_list - - -def covmat_to_artunc(ndata, covmat_list, no_of_norm_mat=0): - r"""Convert the covariance matrix to a matrix of - artificial uncertainties. - - Parameters - ---------- - ndata : integer - Number of data points - covmat_list : list - A one dimensional list which contains the elements of - the covariance matrix row by row. Since experimental - datasets provide these matrices in a list form, this - simplifies the implementation for the user. - no_of_norm_mat : int - Normalized covariance matrices may have an eigenvalue - of 0 due to the last data point not being linearly - independent. To allow for this, the user should input - the number of normalized matrices that are being treated - in an instance. For example, if a single covariance matrix - of a normalized distribution is being processed, the input - would be 1. If a covariance matrix contains pertains to - 3 normalized datasets (i.e. cross covmat for 3 - distributions), the input would be 3. The default value is - 0 for when the covariance matrix pertains to an absolute - distribution. - - Returns - ------- - artunc : list - A two dimensional matrix (given as a list of lists) - which contains artificial uncertainties to be added - to the commondata. i^th row (or list) contains the - artificial uncertainties of the i^th data point. - - """ - epsilon = -0.0000000001 - neg_eval_count = 0 - psd_check = True - covmat = np.zeros((ndata, ndata)) - artunc = np.zeros((ndata, ndata)) - for i in range(len(covmat_list)): - a = i // ndata - b = i % ndata - covmat[a][b] = covmat_list[i] - eigval, eigvec = eig(covmat) - for j in range(len(eigval)): - if eigval[j] < epsilon: - psd_check = False - elif eigval[j] > epsilon and eigval[j] <= 0: - neg_eval_count = neg_eval_count + 1 - if neg_eval_count == (no_of_norm_mat + 1): - psd_check = False - elif eigval[j] > 0: - continue - if psd_check == False: - raise ValueError('The covariance matrix is not positive-semidefinite') - else: - for i in range(ndata): - for j in range(ndata): - if eigval[j] < 0: - continue - else: - artunc[i][j] = eigvec[i][j] * sqrt(eigval[j]) - return artunc.tolist() - - -def cross_cormat_to_covmat(row_err_list, col_err_list, cormat_list): - r"""Convert cross correlation matrix elements - (i.e. those between different different variables or - observables) to covariance matrix elements. - - Parameters - ---------- - row_err_list : list - A one dimensional list which contains the uncertainty - associated to each data point of the variable that is - given on the vertical axis. - col_err_list : list - A one dimensional list which contains the uncertainty - associated to each data point of the variable that is - given on the horizontal axis. - cormat_list : list - A one dimensional list which contains the elements of - the correlation matrix row by row. Since experimental - datasets provide these matrices in a list form, this - simplifies the implementation for the user. - - Returns - ------- - covmat_list : list - A one dimensional list which contains the elements of - the covariance matrix row by row. - - """ - covmat_list = [] - for i in range(len(cormat_list)): - a = i // len(col_err_list) - b = i % len(col_err_list) - covmat_list.append(cormat_list[i] * row_err_list[a] * col_err_list[b]) - return covmat_list - - -def matlist_to_matrix(rows, columns, mat_list): - r"""Convert a 1d list to a 2d matrix. - - Note: This utils function is not strictly needed for - data implementation, however, it is provided for - the aid of the user due to how matrices are treated - throughout all the other functions. This function - allows the user to convert a list that contains the - elemnets of matrix row by row to a proper matrix, if - need be for any reason. - - Parameters - ---------- - rows : int - No. of rows in the matrix - columns : int - No. of columns in the matrix - mat_list : list - A one dimensional list which contains the elements of - the matrix row by row. - - Returns - ------- - matrix : numpy.ndarray - The matrix as a numpy 2d array. - - """ - if rows * columns == len(mat_list): - matrix = np.zeros((rows, columns)) - for i in range(rows): - for j in range(columns): - matrix[i][j] = mat_list[j + i * columns] - matrix = np.array(matrix) - return matrix - else: - raise Exception('rows * columns != len(mat_list)') - - -def concat_matrices(rows, columns, list_of_matrices): - r"""Join smaller matrices into a large matrix. - - This function aims to simplify the process of joining multiple - smaller matrices into one large matrix. Such a need could arise, - for instance, when cross variable covariance matrices are provided - but the user needs to join all the matrices to generate the full - covariance matrix corresponding to the entire dataset. - - Parameters - ---------- - rows : int - No. of rows of matrices to be concatenated. E.g., if 6 - matrices: A, B, C, D, E, F need to be joined as - [[A, B, C], - [D, E, F]], - the number of rows would be 2. - columns : int - No. of columns of matrices to be concatenated. In the - above example, this would be 3. - list_of_matrices : list - A list of the matrices that have to concatenated row by - row. In the above example, this would be [A, B, C, D, E, F]. - The matrices themselves need to be provided as a list of lists, - or a numpy 2d array. If the user has the matrix in a 1d row by - row form, use matList_to_matrix() to convert it. It is assumed - the user verifies that all the input matrices have the correct - dimensions. Matrices with incompatible dimensions will lead to - undesired behavior. - - Returns - ------- - final_mat_list : list - A one dimensional list which contains the elements of - the final, fully concatenated matrix row by row. - - """ - for i in range(len(list_of_matrices)): - list_of_matrices[i] = np.array(list_of_matrices[i]) - col_list = [] - for i in range(rows): - row_list = [] - for j in range(columns): - row_list.append(list_of_matrices[j + i * columns]) - col_list.append(np.concatenate(tuple(row_list), axis=1)) - final_mat = np.concatenate(tuple(col_list), axis=0) - final_mat_list = [] - for i in range(len(final_mat)): - for j in range(len(final_mat[i])): - final_mat_list.append(final_mat[i][j]) - return final_mat_list - - -def trimat_to_fullmat(mode, tri_mat_list): - r"""Convert a list of values of a triangular matrix - to a symmetric matrix. - - Experimental datasets can provide the entries of - correlation or covariance matrices as a triangular - matrix, as these matrices are symmetric by their - very nature. This function can convert these list to - a complete symmetric matrix, that can be used for the - dataset implementation. - - mode : bool - Enter 0 or 1 based on the following scenarios: - Use mode 0 if matrix entries are given row by - row such as: - 0 1 2 3 - 4 5 6 - 7 8 - 9 - Use mode 1 if the matrix entries are given column - by column such as: - 0 1 3 6 - 2 4 7 - 5 8 - 9 - Please note that the numbers above (0-9) are not - entries of the matrix but rather the index of the - entries of the list which contains the elements of - the triangular matrix. - tri_mat_list : list - A list containing the elements of the triangular matrix, - for example, for a 4*4 matrix, the list of - triangular matrix entries could be: - [a, b, c, d, e, f, g, h, i, j] - - Returns - ------- - mat_list : list - A one dimensional list which contains the elements of - the fully populated, symmetric matrix row by row. - - """ - dim = int((np.sqrt(1 + 8 * len(tri_mat_list)) - 1) / 2) - matrix = np.zeros((dim, dim)) - if mode == 0: - for i in range(dim): - for j in range(i + 1): - list_el = len(tri_mat_list) - 1 - ((i * (i + 1)) // 2 + j) - if i == j: - matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] - else: - matrix[dim - 1 - i][dim - 1 - j] = tri_mat_list[list_el] - matrix[dim - 1 - j][dim - 1 - i] = tri_mat_list[list_el] - elif mode == 1: - for i in range(dim): - for j in range(i + 1): - list_el = (i * (i + 1)) // 2 + j - if i == j: - matrix[i][j] = tri_mat_list[list_el] - else: - matrix[i][j] = tri_mat_list[list_el] - matrix[j][i] = tri_mat_list[list_el] - else: - raise Exception('Mode should be 0 or 1, refer to the function for usage') - mat_list = [] - for i in range(dim): - for j in range(dim): - mat_list.append(matrix[i][j]) - return mat_list diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py index 37b78e0988..f224ee8f3f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_13TEV_LJ_DIF/filter.py @@ -1,8 +1,8 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py index 1458e3cd54..e2c2a8fb2a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_2L_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py index a079949fa8..822d1367e9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/artunc.py @@ -2,80 +2,80 @@ from numpy.linalg import eig import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import concat_matrices as cm -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import matlist_to_matrix as mtm -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import concat_matrices as cm +from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import matlist_to_matrix as mtm +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta def artunc(): statArr = [] for i in [23, 29, 31, 27]: - with open('rawdata/Table_'+str(i)+'.yaml', 'r') as file: + with open('rawdata/Table_' + str(i) + '.yaml', 'r') as file: input = yaml.safe_load(file) for j in range(len(input['dependent_variables'][0]['values'])): datval = input['dependent_variables'][0]['values'][j]['value'] statperc = input['dependent_variables'][0]['values'][j]['errors'][0]['symerror'] statArr.append(pta(statperc, datval)) - -# mttbar(7)| pTt (8)| yt(5)| yttbar(5) -# mttbar| 179 174t 170t 177t -# pTt | 174 172 168t 173 -# yt | 170 168 167 169 -# yttbar| 177 173t 169t 176 + + # mttbar(7)| pTt (8)| yt(5)| yttbar(5) + # mttbar| 179 174t 170t 177t + # pTt | 174 172 168t 173 + # yt | 170 168 167 169 + # yttbar| 177 173t 169t 176 ml179, ml174, ml170, ml177, ml172, ml168, ml167, ml173, ml169, ml176 = ([] for i in range(10)) - + with open('rawdata/Table_179.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml179.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_174.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml174.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_170.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml170.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_177.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml177.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_172.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml172.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_168.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml168.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_167.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml167.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_173.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml173.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_169.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml169.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_176.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml176.append(input['dependent_variables'][0]['values'][i]['value']) - + mat179 = mtm(7, 7, ml179) mat174 = mtm(8, 7, ml174) mat174t = mat174.transpose() @@ -93,8 +93,28 @@ def artunc(): mat169t = mat169.transpose() mat176 = mtm(5, 5, ml176) - cormatlist = cm(4, 4, [mat179, mat174t, mat170t, mat177t, mat174, mat172, mat168t, mat173, - mat170, mat168, mat167, mat169, mat177, mat173t, mat169t, mat176]) + cormatlist = cm( + 4, + 4, + [ + mat179, + mat174t, + mat170t, + mat177t, + mat174, + mat172, + mat168t, + mat173, + mat170, + mat168, + mat167, + mat169, + mat177, + mat173t, + mat169t, + mat176, + ], + ) covmatlist = ctc(statArr, cormatlist) artunc = cta(25, covmatlist) @@ -104,70 +124,70 @@ def artunc(): def artunc_norm(): statArr = [] for i in [24, 30, 32, 28]: - with open('rawdata/Table_'+str(i)+'.yaml', 'r') as file: + with open('rawdata/Table_' + str(i) + '.yaml', 'r') as file: input = yaml.safe_load(file) for j in range(len(input['dependent_variables'][0]['values'])): datval = input['dependent_variables'][0]['values'][j]['value'] statperc = input['dependent_variables'][0]['values'][j]['errors'][0]['symerror'] statArr.append(pta(statperc, datval)) - -# mttbar(7)| pTt (8)| yt(5)| yttbar(5) -# mttbar| 234 229t 225t 232t -# pTt | 229 227 223t 228 -# yt | 225 223 222 224 -# yttbar| 232 228t 224t 231 + + # mttbar(7)| pTt (8)| yt(5)| yttbar(5) + # mttbar| 234 229t 225t 232t + # pTt | 229 227 223t 228 + # yt | 225 223 222 224 + # yttbar| 232 228t 224t 231 ml234, ml229, ml225, ml232, ml227, ml223, ml222, ml228, ml224, ml231 = ([] for i in range(10)) - + with open('rawdata/Table_234.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml234.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_229.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml229.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_225.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml225.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_232.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml232.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_227.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml227.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_223.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml223.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_222.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml222.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_228.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml228.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_224.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml224.append(input['dependent_variables'][0]['values'][i]['value']) - + with open('rawdata/Table_231.yaml', 'r') as file: input = yaml.safe_load(file) for i in range(len(input['dependent_variables'][0]['values'])): ml231.append(input['dependent_variables'][0]['values'][i]['value']) - + mat234 = mtm(7, 7, ml234) mat229 = mtm(8, 7, ml229) mat229t = mat229.transpose() @@ -185,8 +205,28 @@ def artunc_norm(): mat224t = mat224.transpose() mat231 = mtm(5, 5, ml231) - cormatlist = cm(4, 4, [mat234, mat229t, mat225t, mat232t, mat229, mat227, mat223t, mat228, - mat225, mat223, mat222, mat224, mat232, mat228t, mat224t, mat231]) + cormatlist = cm( + 4, + 4, + [ + mat234, + mat229t, + mat225t, + mat232t, + mat229, + mat227, + mat223t, + mat228, + mat225, + mat223, + mat222, + mat224, + mat232, + mat228t, + mat224t, + mat231, + ], + ) covmatlist = ctc(statArr, cormatlist) artunc = cta(25, covmatlist, 4) diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py index b114623b64..94b2dbb9c0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_TTBAR_8TEV_LJ_DIF/filter.py @@ -4,8 +4,8 @@ import artunc import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml index 222ee7cdd4..62867cefa8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0J_13TEV_PT/metadata.yaml @@ -26,7 +26,7 @@ implemented_observables: ndata: 38 - tables: [26] + tables: [5] process_type: DY_NC_PT plotting: diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml new file mode 100644 index 0000000000..37eadd5649 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/data.yaml @@ -0,0 +1,8 @@ +data_central: +- 353.152 +- 345.985 +- 336.195 +- 322.483 +- 303.973 +- 273.198 +- 173.171 diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py new file mode 100644 index 0000000000..17f2c7c44a --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter.py @@ -0,0 +1,91 @@ + +import yaml +import numpy as np + +from filter_utils import get_kinematics, get_data_values, get_systematics + + +def filter_ATLAS_Z0_8TEV_data_kinetic(): + """ + writes data central values and kinematics + to respective .yaml file + """ + kin = get_kinematics() + central_values = get_data_values() + + data_central_yaml = {"data_central": central_values} + kinematics_yaml = {"bins": kin} + + # write central values and kinematics to yaml file + with open("data.yaml", "w") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + with open("kinematics.yaml", "w") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + +def filter_ATLAS_Z0_8TEV_uncertainties(): + """ + writes uncertainties to respective .yaml file + """ + systematics = get_systematics() + + # load correlation matrix from .txt file + corr_matrix = np.loadtxt("rawdata/zy.txt") + + # generate covariance matrix from correlation matrix + tot_systematics = np.array([syst[0]['value'] for syst in systematics['tot']]) + + # TODO: this should be done with utils.correlation_to_covariance once that is merged in master + cov_matrix_no_lumi = np.outer(tot_systematics, tot_systematics) * corr_matrix + + # add lumi uncertainty + lumi_unc = np.array([syst[0]['value'] for syst in systematics['lumi']]) + lumi_cov = lumi_unc[:, None] @ lumi_unc[:, None].T + + # add covariances + cov_matrix = cov_matrix_no_lumi + lumi_cov + + # compute decomposition of covariance matrix so as to get artificial systematics + # TODO: use utils once merged in master + lamb, mat = np.linalg.eig(cov_matrix) + art_sys = np.multiply(np.sqrt(lamb), mat) + + uncertainties = [] + + for i, unc in enumerate(art_sys.T): + + name = f"artificial_uncertainty_{i+1}" + values = [unc[i] for i in range(len(unc))] + uncertainties.append([{"name": name, "values": values}]) + + # error definition + error_definitions = {} + errors = [] + + for sys in uncertainties: + + error_definitions[sys[0]['name']] = { + "description": f"{sys[0]['name']}", + "treatment": "ADD", + "type": "CORR", + } + + for i in range(cov_matrix.shape[0]): + error_value = {} + + for sys in uncertainties: + error_value[sys[0]['name']] = float(sys[0]['values'][i]) + + errors.append(error_value) + + uncertainties_yaml = {"definitions": error_definitions, "bins": errors} + + # write uncertainties + with open(f"uncertainties.yaml", 'w') as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + filter_ATLAS_Z0_8TEV_data_kinetic() + filter_ATLAS_Z0_8TEV_uncertainties() \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py new file mode 100644 index 0000000000..726b72d0e2 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/filter_utils.py @@ -0,0 +1,108 @@ +import yaml + + +def get_kinematics(): + """ + returns the relevant kinematics values. + Parameters + ---------- + table : list + version : int + integer read from metadata.yaml that + indicated the version of the hepdata + tables + Returns + ------- + list + list containing the kinematic values for all + hepdata tables + """ + kin = [] + + hepdata_table = f"rawdata/HEPData-ins2698794-v1-Table_9.yaml" + + with open(hepdata_table, 'r') as file: + input = yaml.safe_load(file) + + for yll in input["independent_variables"][0]['values']: + kin_value = { + 'y': { + 'min': yll['low'], + 'mid': 0.5 * (yll['low'] + yll['high']), + 'max': yll['high'], + }, + 'm_Z2': {'min': None, 'mid': 8317.44, 'max': None}, + 'sqrts': {'min': None, 'mid': 8000.0, 'max': None}, + } + + kin.append(kin_value) + + return kin + + +def get_data_values(): + """ + returns the central data. + Parameters + ---------- + tables : list + list that enumerates the table number + version : int + integer read from metadata.yaml that + indicated the version of the hepdata + tables + Returns + ------- + list + list containing the central values for all + hepdata tables + """ + + data_central = [] + + hepdata_table = f"rawdata/HEPData-ins2698794-v1-Table_9.yaml" + + with open(hepdata_table, 'r') as file: + input = yaml.safe_load(file) + + values = input['dependent_variables'][0]['values'] + + for value in values: + data_central.append(value['value']) + + return data_central + + +def get_systematics(): + """ """ + tot_uncertainties = [] + lumi_uncertainties = [] + + hepdata_table = f"rawdata/HEPData-ins2698794-v1-Table_9.yaml" + + with open(hepdata_table, 'r') as file: + input = yaml.safe_load(file) + + dependent_vars = input['dependent_variables'][0] + + # skip 1st entry as these are central data values + for err_values in dependent_vars['values']: + + tot_uncertainties.append( + [ + { + "name": err_values['errors'][0]['label'], + "value": err_values['errors'][0]['symerror'], + } + ] + ) + lumi_uncertainties.append( + [ + { + "name": err_values['errors'][1]['label'], + "value": err_values['errors'][1]['symerror'], + } + ] + ) + + return {'tot': tot_uncertainties, 'lumi': lumi_uncertainties} diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml new file mode 100644 index 0000000000..2fc461bc35 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/kinematics.yaml @@ -0,0 +1,85 @@ +bins: +- y: + min: 0.4 + mid: 0.6000000000000001 + max: 0.8 + m_Z2: + min: null + mid: 8317.44 + max: null + sqrts: + min: null + mid: 8000.0 + max: null +- y: + min: 0.8 + mid: 1.0 + max: 1.2 + m_Z2: + min: null + mid: 8317.44 + max: null + sqrts: + min: null + mid: 8000.0 + max: null +- y: + min: 1.2 + mid: 1.4 + max: 1.6 + m_Z2: + min: null + mid: 8317.44 + max: null + sqrts: + min: null + mid: 8000.0 + max: null +- y: + min: 1.6 + mid: 1.8 + max: 2 + m_Z2: + min: null + mid: 8317.44 + max: null + sqrts: + min: null + mid: 8000.0 + max: null +- y: + min: 2 + mid: 2.2 + max: 2.4 + m_Z2: + min: null + mid: 8317.44 + max: null + sqrts: + min: null + mid: 8000.0 + max: null +- y: + min: 2.4 + mid: 2.5999999999999996 + max: 2.8 + m_Z2: + min: null + mid: 8317.44 + max: null + sqrts: + min: null + mid: 8000.0 + max: null +- y: + min: 2.8 + mid: 3.2 + max: 3.6 + m_Z2: + min: null + mid: 8317.44 + max: null + sqrts: + min: null + mid: 8000.0 + max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml new file mode 100644 index 0000000000..334c859db3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/metadata.yaml @@ -0,0 +1,59 @@ +# Generalia +setname: "ATLAS_Z0_8TEV_ZMASS" + +version: 1 + +version_comment: "Initial implementation" + +# References +arXiv: + url: "https://arxiv.org/pdf/2309.09318" +iNSPIRE: + url: "https://inspirehep.net/literature/2698794" +hepdata: + url: "https://www.hepdata.net/record/149333" + version: 1 + +nnpdf_metadata: + nnpdf31_process: "DY NC" + experiment: "ATLAS" + + +implemented_observables: + + - observable_name: "LL" + observable: + description: "ATLAS 8 TeV, Z boson rapidity distribution in full phase space of decay leptons" + label: r"$d\\sigma/d|\|y_{ll}||$" + units: "[pb]" + + ndata: 7 + + tables: [9] + process_type: DY_Z_Y + + plotting: + dataset_label: 'ATLAS 8 TeV $Z \to l^+ l^-$, absolute rapidity' + kinematics_override: identity + x_scale: linear + plot_x: y + + kinematic_coverage: [y, m_Z2, sqrts] + + kinematics: + variables: + y: {description: "Z > l+ l- absolute rapidity", label: '$|y_{ll}|$', units: ""} + m_Z2: {description: "Z boson mass squared", label: '$M_Z^2$', units: "GeV"} + sqrts: {description: "center of mass energy", label: '$\sqrt(s)$', units: "GeV"} + file: kinematics.yaml + + # Data + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + + # Theory + theory: + FK_tables: + - - ATLAS_Z0_8TEV_ZMASS + operation: 'null' \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml new file mode 100644 index 0000000000..7e125d0135 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/HEPData-ins2698794-v1-Table_9.yaml @@ -0,0 +1,71 @@ +independent_variables: + - header: {name: '$|y|^{\ell\ell}$'} + values: + - {high: 0.8, low: 0.4} + - {high: 1.2, low: 0.8} + - {high: 1.6, low: 1.2} + - {high: 2, low: 1.6} + - {high: 2.4, low: 2} + - {high: 2.8, low: 2.4} + - {high: 3.6, low: 2.8} +dependent_variables: + - header: {name: '$d\sigma/d|y|^{\ell\ell}$ $\pm$ Total $\pm$ Luminosity', units: pb} + values: + - value: 353.152 + errors: + - {symerror: 0.612877, label: tot} + - {symerror: 6.35674, label: lumi} + - value: 345.985 + errors: + - {symerror: 0.614565, label: tot} + - {symerror: 6.22773, label: lumi} + - value: 336.195 + errors: + - {symerror: 0.631117, label: tot} + - {symerror: 6.05151, label: lumi} + - value: 322.483 + errors: + - {symerror: 0.867255, label: tot} + - {symerror: 5.80469, label: lumi} + - value: 303.973 + errors: + - {symerror: 1.2225, label: tot} + - {symerror: 5.47151, label: lumi} + - value: 273.198 + errors: + - {symerror: 1.47795, label: tot} + - {symerror: 4.91756, label: lumi} + - value: 173.171 + errors: + - {symerror: 1.44884, label: tot} + - {symerror: 3.11708, label: lumi} + - header: {name: 'N$^3$LO $\pm$ PDF $\pm$ scale var.', units: pb} + values: + - value: 343.835 + errors: + - {symerror: 5.0845, label: pdf} + - {symerror: 1.48899, label: scale} + - value: 337.198 + errors: + - {symerror: 4.9785, label: pdf} + - {symerror: 1.5366, label: scale} + - value: 327.154 + errors: + - {symerror: 4.8728, label: pdf} + - {symerror: 1.50239, label: scale} + - value: 312.773 + errors: + - {symerror: 4.6646, label: pdf} + - {symerror: 1.4265, label: scale} + - value: 292.641 + errors: + - {symerror: 4.3853, label: pdf} + - {symerror: 1.43681, label: scale} + - value: 260.733 + errors: + - {symerror: 4.0832, label: pdf} + - {symerror: 1.44803, label: scale} + - value: 168.482 + errors: + - {symerror: 3.1625, label: pdf} + - {symerror: 1.54132, label: scale} diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt new file mode 100644 index 0000000000..4fe1bc9d51 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/rawdata/zy.txt @@ -0,0 +1,7 @@ +1.000000000000 0.771441698074 0.698377430439 0.470446109772 0.235730156302 0.135500997305 0.023962540552 +0.771441698074 1.000000000000 0.728683710098 0.490636169910 0.257601708174 0.143674910069 0.023399809375 +0.698377430439 0.728683710098 1.000000000000 0.524034738541 0.272780925035 0.151878938079 0.033453177661 +0.470446109772 0.490636169910 0.524034738541 0.999999940395 0.463345497847 0.285900026560 0.101109012961 +0.235730156302 0.257601708174 0.272780925035 0.463345497847 1.000000000000 0.564261615276 0.305788159370 +0.135500997305 0.143674910069 0.151878938079 0.285900026560 0.564261615276 1.000000119209 0.455123543739 +0.023962540552 0.023399809375 0.033453177661 0.101109012961 0.305788159370 0.455123543739 1.000000000000 diff --git a/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml new file mode 100644 index 0000000000..31706ee588 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/ATLAS_Z0_8TEV_ZMASS/uncertainties.yaml @@ -0,0 +1,79 @@ +definitions: + artificial_uncertainty_1: + description: artificial_uncertainty_1 + treatment: ADD + type: CORR + artificial_uncertainty_2: + description: artificial_uncertainty_2 + treatment: ADD + type: CORR + artificial_uncertainty_3: + description: artificial_uncertainty_3 + treatment: ADD + type: CORR + artificial_uncertainty_4: + description: artificial_uncertainty_4 + treatment: ADD + type: CORR + artificial_uncertainty_5: + description: artificial_uncertainty_5 + treatment: ADD + type: CORR + artificial_uncertainty_6: + description: artificial_uncertainty_6 + treatment: ADD + type: CORR + artificial_uncertainty_7: + description: artificial_uncertainty_7 + treatment: ADD + type: CORR +bins: +- artificial_uncertainty_1: 6.360849092233548 + artificial_uncertainty_2: -0.43736014852425575 + artificial_uncertainty_3: -0.17081282174067292 + artificial_uncertainty_4: 0.1343303399845492 + artificial_uncertainty_5: 0.1506396770871814 + artificial_uncertainty_6: 0.17839551357478534 + artificial_uncertainty_7: -0.17417703394997616 +- artificial_uncertainty_1: 6.233875520247695 + artificial_uncertainty_2: -0.42939370572372393 + artificial_uncertainty_3: -0.1581186015151157 + artificial_uncertainty_4: 0.12091345356933662 + artificial_uncertainty_5: 0.140047777147049 + artificial_uncertainty_6: -0.22584792937770715 + artificial_uncertainty_7: -0.08053516734437347 +- artificial_uncertainty_1: 6.060113000362857 + artificial_uncertainty_2: -0.4123698461117033 + artificial_uncertainty_3: -0.14680060602839212 + artificial_uncertainty_4: 0.10112405423267312 + artificial_uncertainty_5: 0.0894931999659005 + artificial_uncertainty_6: 0.04486740555676256 + artificial_uncertainty_7: 0.28681853399599 +- artificial_uncertainty_1: 5.836824335315856 + artificial_uncertainty_2: -0.27502106473581056 + artificial_uncertainty_3: 0.03159277272608425 + artificial_uncertainty_4: -0.12119507917842083 + artificial_uncertainty_5: -0.5349848732266431 + artificial_uncertainty_6: -0.0007764604112265232 + artificial_uncertainty_7: -0.02250579775755823 +- artificial_uncertainty_1: 5.539243636415269 + artificial_uncertainty_2: 0.31344828703761407 + artificial_uncertainty_3: 0.4545302042514127 + artificial_uncertainty_4: -0.6463383504190422 + artificial_uncertainty_5: 0.16156289938315516 + artificial_uncertainty_6: 0.0018754281204069558 + artificial_uncertainty_7: -0.0009901510871859873 +- artificial_uncertainty_1: 5.00099551940249 + artificial_uncertainty_2: 0.9002405764173007 + artificial_uncertainty_3: 0.5616642244049272 + artificial_uncertainty_4: 0.48016500342015245 + artificial_uncertainty_5: -0.017766174135644974 + artificial_uncertainty_6: -0.00035256711006794806 + artificial_uncertainty_7: 0.0016258067952645042 +- artificial_uncertainty_1: 3.1715884625027186 + artificial_uncertainty_2: 1.0482636206034448 + artificial_uncertainty_3: -0.8037615168161861 + artificial_uncertainty_4: -0.1055372371812821 + artificial_uncertainty_5: -0.017988003826124054 + artificial_uncertainty_6: -0.000893499833004754 + artificial_uncertainty_7: 0.0001651328837651984 diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py index 0d358adae5..0b1c8e4dc1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_2L_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py index fcda4a06a5..87a9789fdc 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_13TEV_LJ_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py index 0cd577753c..c22c00ee8d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_2L_DIF/filter.py @@ -1,10 +1,10 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import trimat_to_fullmat as ttf +from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import trimat_to_fullmat as ttf def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py index 5f5c5af484..0399a3049e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_TTBAR_8TEV_LJ_DIF/filter.py @@ -1,7 +1,7 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py index 8397558851..13509f0a65 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_ELECTRON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py index d1bbb8538d..86a9664109 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py index ba34402178..d61b7d3375 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_WPWM_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MW_VALUE = 80.398 # GeV SQRT_S = 8_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py index 040b44911f..d5cd43745e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/CMS_Z0_7TEV_DIMUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc # MZ_VALUE = 91.1876 # GeV # MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py index 736ea6b856..b7a9b5b465 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/artUnc.py @@ -1,8 +1,8 @@ import numpy import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta def artunc(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py index 7f19469816..7f3f74bacc 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_290PB-1_DIF/filter.py @@ -3,8 +3,8 @@ import artUnc import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py index 00505782ec..55bf4e9062 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/filter.py @@ -1,7 +1,7 @@ from manual_impl import artunc, jet_data, jet_sys import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py index 50e3f03421..8a5176db0c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_1JET_319GEV_351PB-1_DIF/manual_impl.py @@ -1,74 +1,3537 @@ from math import sqrt -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -jet_old_impl_list = [['1', 'DIS_1JET', '1.750000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '7.042365878823e+01', '1.901438787282e+00', '7.042365878823e-01', '1.000000000000e+00', '7.130250486484e-01', '1.010961455291e+00', '6.718827732504e-01', '9.531044964111e-01', '2.517144109385e-01', '3.572500464504e-01', '2.515885537330e-01', '3.572500464504e-01', '3.521182939412e-01', '5.000000000000e-01', '4.225419527294e-01', '6.000000000000e-01', '2.042286104859e+00', '2.900000000000e+00'], ['2', 'DIS_1JET', '1.750000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '3.095350776162e+01', '1.269093818226e+00', '8.666982173254e-01', '2.800000000000e+00', '7.598162606841e-01', '2.452246318915e+00', '1.718173641914e-01', '5.542497004702e-01', '1.910967863178e-01', '6.170584587557e-01', '8.045980207445e-02', '2.599375899303e-01', '1.547675388081e-01', '5.000000000000e-01', '1.857210465697e-01', '6.000000000000e-01', '8.976517250870e-01', '2.900000000000e+00'], ['3', 'DIS_1JET', '1.750000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '8.082109035000e+00', '5.172549782400e-01', '2.828738162250e-01', '3.500000000000e+00', '2.743800000000e-01', '3.400000000000e+00', '1.976738222426e-02', '2.447042700083e-01', '3.679736009134e-02', '4.552940319412e-01', '8.082109035000e-03', '1.000000000000e-01', '4.041054517500e-02', '5.000000000000e-01', '4.849265421000e-02', '6.000000000000e-01', '2.343811620150e-01', '2.900000000000e+00'], ['4', 'DIS_1JET', '1.750000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '9.125014074304e-01', '1.396127153368e-01', '1.067626646694e-01', '1.170000000000e+01', '4.688994472166e-02', '5.118073262173e+00', '1.519286117216e-03', '1.657483653351e-01', '4.299338659215e-03', '4.704529347867e-01', '1.991738317891e-03', '2.182723557106e-01', '4.562507037152e-03', '5.000000000000e-01', '5.475008444582e-03', '6.000000000000e-01', '2.646254081548e-02', '2.900000000000e+00'], ['5', 'DIS_1JET', '2.350000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '5.493706846573e+01', '1.648112053972e+00', '-3.296224107944e-01', '-6.000000000000e-01', '5.220401134013e-01', '9.531044964111e-01', '6.074575198510e-01', '1.107945704936e+00', '4.273370774492e-01', '7.782554801857e-01', '1.960665379920e-01', '3.568929749397e-01', '2.746853423286e-01', '5.000000000000e-01', '3.296224107944e-01', '6.000000000000e-01', '1.593174985506e+00', '2.900000000000e+00'], ['6', 'DIS_1JET', '2.350000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '2.680000000000e+01', '1.098800000000e+00', '9.112000000000e-01', '3.400000000000e+00', '6.432000000000e-01', '2.400000000000e+00', '1.072000000000e-01', '4.000000000000e-01', '1.608000000000e-01', '6.000000000000e-01', '8.040000000000e-02', '3.000000000000e-01', '1.340000000000e-01', '5.000000000000e-01', '1.608000000000e-01', '6.000000000000e-01', '7.772000000000e-01', '2.900000000000e+00'], ['7', 'DIS_1JET', '2.350000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '7.013496240129e+00', '4.628907518485e-01', '3.366478195262e-01', '4.800000000000e+00', '2.492988998672e-01', '3.551005871609e+00', '1.404103000000e-02', '2.000000000000e-01', '3.893063895065e-02', '5.548042274342e-01', '2.505571857565e-02', '3.572500464504e-01', '3.506748120064e-02', '5.000000000000e-01', '4.208097744077e-02', '6.000000000000e-01', '2.033913909637e-01', '2.900000000000e+00'], ['8', 'DIS_1JET', '2.350000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '8.549775241245e-01', '1.299565836669e-01', '3.932896610973e-02', '4.600000000000e+00', '4.505743015308e-02', '5.264739441654e+00', '1.865246959223e-03', '2.182723557106e-01', '7.400622244443e-04', '8.655926074807e-02', '2.564932572373e-03', '3.000000000000e-01', '4.274887620623e-03', '5.000000000000e-01', '5.129865144747e-03', '6.000000000000e-01', '2.479434819961e-02', '2.900000000000e+00'], ['9', 'DIS_1JET', '3.450000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '5.209563915000e+01', '1.562869174500e+00', '7.814345872500e-01', '1.500000000000e+00', '4.972717868530e-01', '9.531044964111e-01', '5.217390000000e-01', '1.000000000000e+00', '4.570802892413e-01', '8.773868536773e-01', '1.562869174500e-01', '3.000000000000e-01', '2.604781957500e-01', '5.000000000000e-01', '3.125738349000e-01', '6.000000000000e-01', '1.510773535350e+00', '2.900000000000e+00'], ['10', 'DIS_1JET', '3.450000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '2.785563475695e+01', '1.114225390278e+00', '8.635246774655e-01', '3.100000000000e+00', '6.258088126577e-01', '2.249985843976e+00', '1.112556000000e-01', '4.000000000000e-01', '2.259611917827e-01', '8.115922482154e-01', '7.233489456689e-02', '2.596777822442e-01', '1.114225390278e-01', '4.000000000000e-01', '1.671338085417e-01', '6.000000000000e-01', '8.078134079515e-01', '2.900000000000e+00'], ['11', 'DIS_1JET', '3.450000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '6.962069709237e+00', '4.734207402281e-01', '1.322793244755e-01', '1.900000000000e+00', '2.518340918144e-01', '3.606383090020e+00', '1.158001203865e-02', '1.657483653351e-01', '5.928243109147e-02', '8.502285946131e-01', '1.811516043400e-02', '2.601979180124e-01', '2.784827883695e-02', '4.000000000000e-01', '4.177241825542e-02', '6.000000000000e-01', '2.019000215679e-01', '2.900000000000e+00'], ['12', 'DIS_1JET', '3.450000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '8.702993693220e-01', '1.314152047676e-01', '-2.610898107966e-02', '-3.000000000000e+00', '4.826471687216e-02', '5.562396168725e+00', '1.502894423550e-03', '1.733784592161e-01', '5.667628733710e-03', '6.522043307043e-01', '2.849193515760e-03', '3.273808549327e-01', '3.481197477288e-03', '4.000000000000e-01', '5.221796215932e-03', '6.000000000000e-01', '2.523868171034e-02', '2.900000000000e+00'], ['13', 'DIS_1JET', '5.500000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '4.877557560000e+01', '1.560818419200e+00', '7.316336340000e-01', '1.500000000000e+00', '6.381428053344e-01', '1.308978661724e+00', '3.412584000000e-01', '7.000000000000e-01', '5.616976088752e-01', '1.151596064148e+00', '9.755115120000e-02', '2.000000000000e-01', '1.951023024000e-01', '4.000000000000e-01', '2.926534536000e-01', '6.000000000000e-01', '1.414491692400e+00', '2.900000000000e+00'], ['14', 'DIS_1JET', '5.500000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '2.690000000000e+01', '1.102900000000e+00', '3.228000000000e-01', '1.200000000000e+00', '5.380000000000e-01', '2.000000000000e+00', '1.076000000000e-01', '4.000000000000e-01', '1.883000000000e-01', '7.000000000000e-01', '2.690000000000e-02', '1.000000000000e-01', '1.076000000000e-01', '4.000000000000e-01', '1.614000000000e-01', '6.000000000000e-01', '7.801000000000e-01', '2.900000000000e+00'], ['15', 'DIS_1JET', '5.500000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '7.949992050000e+00', '4.849495150500e-01', '2.782497217500e-01', '3.500000000000e+00', '2.943647864470e-01', '3.699002713601e+00', '2.639353425041e-02', '3.319944735090e-01', '6.359993640000e-02', '8.000000000000e-01', '7.949992050000e-03', '1.000000000000e-01', '2.384997615000e-02', '3.000000000000e-01', '4.769995230000e-02', '6.000000000000e-01', '2.305497694500e-01', '2.900000000000e+00'], ['16', 'DIS_1JET', '5.500000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '8.561421438570e-01', '1.412634537364e-01', '-7.619665080327e-02', '-8.900000000000e+00', '4.800730113222e-02', '5.596189240424e+00', '1.213193003977e-03', '1.415629191565e-01', '1.211979810973e-03', '1.415629191565e-01', '8.561421438570e-04', '1.000000000000e-01', '1.712284287714e-03', '2.000000000000e-01', '5.136852863142e-03', '6.000000000000e-01', '2.482812217185e-02', '2.900000000000e+00'], ['17', 'DIS_1JET', '2.850000000000e+03', '9.000000000000e+00', '3.190000000000e+02', '4.329996751417e+01', '1.515498862996e+00', '9.525992853119e-01', '2.200000000000e+00', '4.802202307275e-01', '1.110163814455e+00', '1.970436461015e-01', '4.552940319412e-01', '1.971421679245e-01', '4.552940319412e-01', '2.164998375709e-01', '5.000000000000e-01', '4.762996426559e-01', '1.100000000000e+00', '2.597998050850e-01', '6.000000000000e-01', '1.255699057911e+00', '2.900000000000e+00'], ['18', 'DIS_1JET', '2.850000000000e+03', '1.450000000000e+01', '3.190000000000e+02', '2.852850712500e+01', '1.141140285000e+00', '3.993990997500e-01', '1.400000000000e+00', '4.422094385017e-01', '1.550836646595e+00', '2.851425000000e-02', '1.000000000000e-01', '1.581191652889e-01', '5.542497004702e-01', '1.711710427500e-01', '6.000000000000e-01', '3.138135783750e-01', '1.100000000000e+00', '1.711710427500e-01', '6.000000000000e-01', '8.273267066250e-01', '2.900000000000e+00'], ['19', 'DIS_1JET', '2.850000000000e+03', '2.400000000000e+01', '3.190000000000e+02', '1.069999732500e+01', '5.242998689250e-01', '2.888999277750e-01', '2.700000000000e+00', '2.943472566544e-01', '2.752285083237e+00', '1.069465000000e-02', '1.000000000000e-01', '5.930470312414e-02', '5.542497004702e-01', '4.279998930000e-02', '4.000000000000e-01', '1.176999705750e-01', '1.100000000000e+00', '6.419998395000e-02', '6.000000000000e-01', '3.102999224250e-01', '2.900000000000e+00'], ['20', 'DIS_1JET', '2.850000000000e+03', '4.000000000000e+01', '3.190000000000e+02', '2.044081530000e+00', '1.737469300500e-01', '4.292571213000e-02', '2.100000000000e+00', '9.495865837300e-02', '4.647864398158e+00', '1.769341861456e-03', '8.655926074807e-02', '6.132244590000e-03', '3.000000000000e-01', '4.088163060000e-03', '2.000000000000e-01', '2.044081530000e-02', '1.000000000000e+00', '1.226448918000e-02', '6.000000000000e-01', '5.927836437000e-02', '2.900000000000e+00'], ['21', 'DIS_1JET', '1.000000000000e+04', '9.000000000000e+00', '3.190000000000e+02', '2.571395501979e+00', '3.779951387908e-01', '-7.714186505936e-02', '-3.000000000000e+00', '2.217633874200e-02', '8.533627868550e-01', '1.102535035362e-02', '4.246887574694e-01', '4.242064477684e-02', '1.652187526630e+00', '1.277337104494e-02', '4.967485956598e-01', '4.885651453759e-02', '1.900000000000e+00', '1.542837301187e-02', '6.000000000000e-01', '7.457046955738e-02', '2.900000000000e+00'], ['22', 'DIS_1JET', '1.000000000000e+04', '1.450000000000e+01', '3.190000000000e+02', '1.760953607685e+00', '2.887963916604e-01', '1.937048968454e-02', '1.100000000000e+00', '2.485217093133e-02', '1.425434816076e+00', '1.509897970990e-03', '8.655926074807e-02', '1.934579665249e-02', '1.101344240954e+00', '1.299737337559e-02', '7.380872113191e-01', '3.169716493834e-02', '1.800000000000e+00', '1.056572164611e-02', '6.000000000000e-01', '5.106765462288e-02', '2.900000000000e+00'], ['23', 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0, + -2, + 0, + 44, + -2, + 0, + 0, + 1, + 0, + 0, + 0, + -1, + 1, + 0, + 0, + -1, + 0, + 0, + 0, + 0, + 1, + 0, + 0, + -1, + 1, + 7, + -36, + 100, + -13, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 1, + 0, + 0, + 0, + -2, + -1, + -2, + -7, + 66, + 0, + 0, + 0, + 1, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 1, + 0, + 0, + -1, + 2, + 2, + -9, + -13, + 100, ] + def sys_breakdown(old_impl, is_jet): sys_breakdown = [[] for i in range(24)] for i in range(24): sys_breakdown[i].append(float(old_impl[i][7])) - sys_breakdown[i].append(float(old_impl[i][9])/2) - sys_breakdown[i].append(float(old_impl[i][9])/2) - sys_breakdown[i].append(float(old_impl[i][11])/2) - sys_breakdown[i].append(float(old_impl[i][11])/2) + sys_breakdown[i].append(float(old_impl[i][9]) / 2) + sys_breakdown[i].append(float(old_impl[i][9]) / 2) + sys_breakdown[i].append(float(old_impl[i][11]) / 2) + sys_breakdown[i].append(float(old_impl[i][11]) / 2) sys_breakdown[i].append(float(old_impl[i][13])) sys_breakdown[i].append(float(old_impl[i][15])) sys_breakdown[i].append(float(old_impl[i][17])) - sys_breakdown[i].append(float(old_impl[i][5])*0.005) if is_jet else sys_breakdown[i].append(float(old_impl[i][19])) + ( + sys_breakdown[i].append(float(old_impl[i][5]) * 0.005) + if is_jet + else sys_breakdown[i].append(float(old_impl[i][19])) + ) sys_breakdown[i].append(float(old_impl[i][21])) return sys_breakdown @@ -81,6 +3544,7 @@ def sym_data(): dijet_data.append(float(dijet_old_impl_list[i][5])) return jet_data, dijet_data + def stat_lists(): jet_stat = [] dijet_stat = [] @@ -89,12 +3553,12 @@ def stat_lists(): dijet_stat.append(float(dijet_old_impl_list[i][6])) return jet_stat, dijet_stat + jet_data, dijet_data = sym_data() jet_stat, dijet_stat = stat_lists() jet_sys = sys_breakdown(jet_old_impl_list, True) dijet_sys = sys_breakdown(dijet_old_impl_list, False) -covmat = ctc(jet_stat + dijet_stat, [a/100 for a in corMatArray]) - -artunc = cta(48, covmat, ) +covmat = ctc(jet_stat + dijet_stat, [a / 100 for a in corMatArray]) +artunc = cta(48, covmat) diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py index 736ea6b856..b7a9b5b465 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/artUnc.py @@ -1,8 +1,8 @@ import numpy import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta def artunc(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py index ecf4dff877..c638b42a41 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_290PB-1_DIF/filter.py @@ -3,8 +3,8 @@ import artUnc import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py index 39f732434d..8c3b997d5b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/filter.py @@ -1,7 +1,7 @@ from manual_impl import artunc, dijet_data, dijet_sys import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import percentage_to_absolute as pta +from nnpdf_data.filter_utils.utils import percentage_to_absolute as pta def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py index 50e3f03421..8a5176db0c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py +++ b/nnpdf_data/nnpdf_data/new_commondata/H1_2JET_319GEV_351PB-1_DIF/manual_impl.py @@ -1,74 +1,3537 @@ from math import sqrt -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import cormat_to_covmat as ctc -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc as cta +from nnpdf_data.filter_utils.utils import cormat_to_covmat as ctc +from nnpdf_data.filter_utils.utils import covmat_to_artunc as cta -jet_old_impl_list = [['1', 'DIS_1JET', '1.750000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '7.042365878823e+01', '1.901438787282e+00', '7.042365878823e-01', '1.000000000000e+00', '7.130250486484e-01', '1.010961455291e+00', '6.718827732504e-01', '9.531044964111e-01', '2.517144109385e-01', '3.572500464504e-01', '2.515885537330e-01', '3.572500464504e-01', '3.521182939412e-01', '5.000000000000e-01', '4.225419527294e-01', '6.000000000000e-01', '2.042286104859e+00', '2.900000000000e+00'], ['2', 'DIS_1JET', '1.750000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '3.095350776162e+01', '1.269093818226e+00', '8.666982173254e-01', '2.800000000000e+00', '7.598162606841e-01', '2.452246318915e+00', '1.718173641914e-01', '5.542497004702e-01', '1.910967863178e-01', '6.170584587557e-01', '8.045980207445e-02', '2.599375899303e-01', '1.547675388081e-01', '5.000000000000e-01', '1.857210465697e-01', '6.000000000000e-01', '8.976517250870e-01', '2.900000000000e+00'], ['3', 'DIS_1JET', '1.750000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '8.082109035000e+00', '5.172549782400e-01', '2.828738162250e-01', '3.500000000000e+00', '2.743800000000e-01', '3.400000000000e+00', '1.976738222426e-02', '2.447042700083e-01', '3.679736009134e-02', '4.552940319412e-01', '8.082109035000e-03', '1.000000000000e-01', '4.041054517500e-02', '5.000000000000e-01', '4.849265421000e-02', '6.000000000000e-01', '2.343811620150e-01', '2.900000000000e+00'], ['4', 'DIS_1JET', '1.750000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '9.125014074304e-01', '1.396127153368e-01', '1.067626646694e-01', '1.170000000000e+01', '4.688994472166e-02', '5.118073262173e+00', '1.519286117216e-03', '1.657483653351e-01', '4.299338659215e-03', '4.704529347867e-01', '1.991738317891e-03', '2.182723557106e-01', '4.562507037152e-03', '5.000000000000e-01', '5.475008444582e-03', '6.000000000000e-01', '2.646254081548e-02', '2.900000000000e+00'], ['5', 'DIS_1JET', '2.350000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '5.493706846573e+01', '1.648112053972e+00', '-3.296224107944e-01', '-6.000000000000e-01', '5.220401134013e-01', '9.531044964111e-01', '6.074575198510e-01', '1.107945704936e+00', '4.273370774492e-01', '7.782554801857e-01', '1.960665379920e-01', '3.568929749397e-01', '2.746853423286e-01', '5.000000000000e-01', '3.296224107944e-01', '6.000000000000e-01', '1.593174985506e+00', '2.900000000000e+00'], ['6', 'DIS_1JET', '2.350000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '2.680000000000e+01', '1.098800000000e+00', '9.112000000000e-01', '3.400000000000e+00', '6.432000000000e-01', '2.400000000000e+00', '1.072000000000e-01', '4.000000000000e-01', '1.608000000000e-01', '6.000000000000e-01', '8.040000000000e-02', '3.000000000000e-01', '1.340000000000e-01', '5.000000000000e-01', '1.608000000000e-01', '6.000000000000e-01', '7.772000000000e-01', '2.900000000000e+00'], ['7', 'DIS_1JET', '2.350000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '7.013496240129e+00', '4.628907518485e-01', '3.366478195262e-01', '4.800000000000e+00', '2.492988998672e-01', '3.551005871609e+00', '1.404103000000e-02', '2.000000000000e-01', '3.893063895065e-02', '5.548042274342e-01', '2.505571857565e-02', '3.572500464504e-01', '3.506748120064e-02', '5.000000000000e-01', '4.208097744077e-02', '6.000000000000e-01', '2.033913909637e-01', '2.900000000000e+00'], ['8', 'DIS_1JET', '2.350000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '8.549775241245e-01', '1.299565836669e-01', '3.932896610973e-02', '4.600000000000e+00', '4.505743015308e-02', '5.264739441654e+00', '1.865246959223e-03', '2.182723557106e-01', '7.400622244443e-04', '8.655926074807e-02', '2.564932572373e-03', '3.000000000000e-01', '4.274887620623e-03', '5.000000000000e-01', '5.129865144747e-03', '6.000000000000e-01', '2.479434819961e-02', '2.900000000000e+00'], ['9', 'DIS_1JET', '3.450000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '5.209563915000e+01', '1.562869174500e+00', '7.814345872500e-01', '1.500000000000e+00', '4.972717868530e-01', '9.531044964111e-01', '5.217390000000e-01', '1.000000000000e+00', '4.570802892413e-01', '8.773868536773e-01', '1.562869174500e-01', '3.000000000000e-01', '2.604781957500e-01', '5.000000000000e-01', '3.125738349000e-01', '6.000000000000e-01', '1.510773535350e+00', '2.900000000000e+00'], ['10', 'DIS_1JET', '3.450000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '2.785563475695e+01', '1.114225390278e+00', '8.635246774655e-01', '3.100000000000e+00', '6.258088126577e-01', '2.249985843976e+00', '1.112556000000e-01', '4.000000000000e-01', '2.259611917827e-01', '8.115922482154e-01', '7.233489456689e-02', '2.596777822442e-01', '1.114225390278e-01', '4.000000000000e-01', '1.671338085417e-01', '6.000000000000e-01', '8.078134079515e-01', '2.900000000000e+00'], ['11', 'DIS_1JET', '3.450000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '6.962069709237e+00', '4.734207402281e-01', '1.322793244755e-01', '1.900000000000e+00', '2.518340918144e-01', '3.606383090020e+00', '1.158001203865e-02', '1.657483653351e-01', '5.928243109147e-02', '8.502285946131e-01', '1.811516043400e-02', '2.601979180124e-01', '2.784827883695e-02', '4.000000000000e-01', '4.177241825542e-02', '6.000000000000e-01', '2.019000215679e-01', '2.900000000000e+00'], ['12', 'DIS_1JET', '3.450000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '8.702993693220e-01', '1.314152047676e-01', '-2.610898107966e-02', '-3.000000000000e+00', '4.826471687216e-02', '5.562396168725e+00', '1.502894423550e-03', '1.733784592161e-01', '5.667628733710e-03', '6.522043307043e-01', '2.849193515760e-03', '3.273808549327e-01', '3.481197477288e-03', '4.000000000000e-01', '5.221796215932e-03', '6.000000000000e-01', '2.523868171034e-02', '2.900000000000e+00'], ['13', 'DIS_1JET', '5.500000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '4.877557560000e+01', '1.560818419200e+00', '7.316336340000e-01', '1.500000000000e+00', '6.381428053344e-01', '1.308978661724e+00', '3.412584000000e-01', '7.000000000000e-01', '5.616976088752e-01', '1.151596064148e+00', '9.755115120000e-02', '2.000000000000e-01', '1.951023024000e-01', '4.000000000000e-01', '2.926534536000e-01', '6.000000000000e-01', '1.414491692400e+00', '2.900000000000e+00'], ['14', 'DIS_1JET', '5.500000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '2.690000000000e+01', '1.102900000000e+00', '3.228000000000e-01', '1.200000000000e+00', '5.380000000000e-01', '2.000000000000e+00', '1.076000000000e-01', '4.000000000000e-01', '1.883000000000e-01', '7.000000000000e-01', '2.690000000000e-02', '1.000000000000e-01', '1.076000000000e-01', '4.000000000000e-01', '1.614000000000e-01', '6.000000000000e-01', '7.801000000000e-01', '2.900000000000e+00'], ['15', 'DIS_1JET', '5.500000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '7.949992050000e+00', '4.849495150500e-01', '2.782497217500e-01', '3.500000000000e+00', '2.943647864470e-01', '3.699002713601e+00', '2.639353425041e-02', '3.319944735090e-01', '6.359993640000e-02', '8.000000000000e-01', '7.949992050000e-03', '1.000000000000e-01', '2.384997615000e-02', '3.000000000000e-01', '4.769995230000e-02', '6.000000000000e-01', '2.305497694500e-01', '2.900000000000e+00'], ['16', 'DIS_1JET', '5.500000000000e+02', '4.000000000000e+01', '3.190000000000e+02', '8.561421438570e-01', '1.412634537364e-01', '-7.619665080327e-02', '-8.900000000000e+00', '4.800730113222e-02', '5.596189240424e+00', '1.213193003977e-03', '1.415629191565e-01', '1.211979810973e-03', '1.415629191565e-01', '8.561421438570e-04', '1.000000000000e-01', '1.712284287714e-03', '2.000000000000e-01', '5.136852863142e-03', '6.000000000000e-01', '2.482812217185e-02', '2.900000000000e+00'], ['17', 'DIS_1JET', '2.850000000000e+03', '9.000000000000e+00', '3.190000000000e+02', '4.329996751417e+01', '1.515498862996e+00', '9.525992853119e-01', '2.200000000000e+00', '4.802202307275e-01', '1.110163814455e+00', '1.970436461015e-01', '4.552940319412e-01', '1.971421679245e-01', '4.552940319412e-01', '2.164998375709e-01', '5.000000000000e-01', '4.762996426559e-01', '1.100000000000e+00', '2.597998050850e-01', '6.000000000000e-01', '1.255699057911e+00', '2.900000000000e+00'], ['18', 'DIS_1JET', '2.850000000000e+03', '1.450000000000e+01', '3.190000000000e+02', '2.852850712500e+01', '1.141140285000e+00', '3.993990997500e-01', '1.400000000000e+00', '4.422094385017e-01', '1.550836646595e+00', '2.851425000000e-02', '1.000000000000e-01', '1.581191652889e-01', '5.542497004702e-01', '1.711710427500e-01', '6.000000000000e-01', '3.138135783750e-01', '1.100000000000e+00', '1.711710427500e-01', '6.000000000000e-01', '8.273267066250e-01', '2.900000000000e+00'], ['19', 'DIS_1JET', '2.850000000000e+03', '2.400000000000e+01', '3.190000000000e+02', '1.069999732500e+01', '5.242998689250e-01', '2.888999277750e-01', '2.700000000000e+00', '2.943472566544e-01', '2.752285083237e+00', '1.069465000000e-02', '1.000000000000e-01', '5.930470312414e-02', '5.542497004702e-01', '4.279998930000e-02', '4.000000000000e-01', '1.176999705750e-01', '1.100000000000e+00', '6.419998395000e-02', '6.000000000000e-01', '3.102999224250e-01', '2.900000000000e+00'], ['20', 'DIS_1JET', '2.850000000000e+03', '4.000000000000e+01', '3.190000000000e+02', '2.044081530000e+00', '1.737469300500e-01', '4.292571213000e-02', '2.100000000000e+00', '9.495865837300e-02', '4.647864398158e+00', '1.769341861456e-03', '8.655926074807e-02', '6.132244590000e-03', '3.000000000000e-01', '4.088163060000e-03', '2.000000000000e-01', '2.044081530000e-02', '1.000000000000e+00', '1.226448918000e-02', '6.000000000000e-01', '5.927836437000e-02', '2.900000000000e+00'], ['21', 'DIS_1JET', '1.000000000000e+04', '9.000000000000e+00', '3.190000000000e+02', '2.571395501979e+00', '3.779951387908e-01', '-7.714186505936e-02', '-3.000000000000e+00', '2.217633874200e-02', '8.533627868550e-01', '1.102535035362e-02', '4.246887574694e-01', '4.242064477684e-02', '1.652187526630e+00', '1.277337104494e-02', '4.967485956598e-01', '4.885651453759e-02', '1.900000000000e+00', '1.542837301187e-02', '6.000000000000e-01', '7.457046955738e-02', '2.900000000000e+00'], ['22', 'DIS_1JET', '1.000000000000e+04', '1.450000000000e+01', '3.190000000000e+02', '1.760953607685e+00', '2.887963916604e-01', '1.937048968454e-02', '1.100000000000e+00', '2.485217093133e-02', '1.425434816076e+00', '1.509897970990e-03', '8.655926074807e-02', '1.934579665249e-02', '1.101344240954e+00', '1.299737337559e-02', '7.380872113191e-01', '3.169716493834e-02', '1.800000000000e+00', '1.056572164611e-02', '6.000000000000e-01', '5.106765462288e-02', '2.900000000000e+00'], ['23', 'DIS_1JET', '1.000000000000e+04', '2.400000000000e+01', '3.190000000000e+02', '6.709991612502e-01', '1.449358188300e-01', '-8.655889180127e-02', '-1.290000000000e+01', '1.412291623568e-02', '2.102653864121e+00', '1.745052446956e-03', '2.599375899303e-01', '1.162786613822e-03', '1.733784592161e-01', '3.719010841387e-03', '5.542497004702e-01', '1.207798490250e-02', '1.800000000000e+00', '4.025994967501e-03', '6.000000000000e-01', '1.945897567625e-02', '2.900000000000e+00'], ['24', 'DIS_1JET', '1.000000000000e+04', '4.000000000000e+01', '3.190000000000e+02', '3.085353405933e-01', '6.078146209687e-02', '-6.016439141569e-02', '-1.950000000000e+01', '8.809210109312e-03', '2.849452331864e+00', '2.677356506943e-04', '8.655926074807e-02', '2.272948236221e-03', '7.370580971263e-01', '2.670659099641e-04', '8.655926074807e-02', '5.553636130679e-03', '1.800000000000e+00', '1.851212043560e-03', '6.000000000000e-01', '8.947524877205e-03', '2.900000000000e+00']] -dijet_old_impl_list = [['1', 'DIS_2JET', '1.750000000000e+02', '9.000000000000e+00', '3.190000000000e+02', '2.332986433245e+01', '8.398751159682e-01', '4.899271509815e-01', '2.100000000000e+00', '5.731805998113e-02', '2.451941684468e-01', '3.038958000000e-01', '1.300000000000e+00', '9.567285880348e-02', '4.098824622871e-01', '8.334595116449e-02', '3.572500464504e-01', '1.166493216623e-01', '5.000000000000e-01', '1.399791859947e-01', '6.000000000000e-01', '6.765660656411e-01', '2.900000000000e+00'], ['2', 'DIS_2JET', '1.750000000000e+02', '1.450000000000e+01', '3.190000000000e+02', '1.359998980340e+01', '7.887994085972e-01', '4.759996431190e-01', '3.500000000000e+00', '2.517837167094e-01', '1.852276996656e+00', '3.531616955617e-02', '2.599375899303e-01', '2.717280680000e-02', '2.000000000000e-01', '4.506100232821e-02', '3.313311478877e-01', '6.799994901700e-02', '5.000000000000e-01', '8.159993882040e-02', '6.000000000000e-01', '3.943997042986e-01', '2.900000000000e+00'], ['3', 'DIS_2JET', '1.750000000000e+02', '2.400000000000e+01', '3.190000000000e+02', '3.569995537501e+00', '2.391897010126e-01', '1.427998215000e-01', '4.000000000000e+00', 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0, + 0, + -1, + 1, + 7, + -36, + 100, + -13, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 1, + 0, + 0, + 0, + -2, + -1, + -2, + -7, + 66, + 0, + 0, + 0, + 1, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 0, + 1, + 0, + 0, + -1, + 2, + 2, + -9, + -13, + 100, ] + def sys_breakdown(old_impl, is_jet): sys_breakdown = [[] for i in range(24)] for i in range(24): sys_breakdown[i].append(float(old_impl[i][7])) - sys_breakdown[i].append(float(old_impl[i][9])/2) - sys_breakdown[i].append(float(old_impl[i][9])/2) - sys_breakdown[i].append(float(old_impl[i][11])/2) - sys_breakdown[i].append(float(old_impl[i][11])/2) + sys_breakdown[i].append(float(old_impl[i][9]) / 2) + sys_breakdown[i].append(float(old_impl[i][9]) / 2) + sys_breakdown[i].append(float(old_impl[i][11]) / 2) + sys_breakdown[i].append(float(old_impl[i][11]) / 2) sys_breakdown[i].append(float(old_impl[i][13])) sys_breakdown[i].append(float(old_impl[i][15])) sys_breakdown[i].append(float(old_impl[i][17])) - sys_breakdown[i].append(float(old_impl[i][5])*0.005) if is_jet else sys_breakdown[i].append(float(old_impl[i][19])) + ( + sys_breakdown[i].append(float(old_impl[i][5]) * 0.005) + if is_jet + else sys_breakdown[i].append(float(old_impl[i][19])) + ) sys_breakdown[i].append(float(old_impl[i][21])) return sys_breakdown @@ -81,6 +3544,7 @@ def sym_data(): dijet_data.append(float(dijet_old_impl_list[i][5])) return jet_data, dijet_data + def stat_lists(): jet_stat = [] dijet_stat = [] @@ -89,12 +3553,12 @@ def stat_lists(): dijet_stat.append(float(dijet_old_impl_list[i][6])) return jet_stat, dijet_stat + jet_data, dijet_data = sym_data() jet_stat, dijet_stat = stat_lists() jet_sys = sys_breakdown(jet_old_impl_list, True) dijet_sys = sys_breakdown(dijet_old_impl_list, False) -covmat = ctc(jet_stat + dijet_stat, [a/100 for a in corMatArray]) - -artunc = cta(48, covmat, ) +covmat = ctc(jet_stat + dijet_stat, [a / 100 for a in corMatArray]) +artunc = cta(48, covmat) diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py index cec61ffaac..00f70cfbd5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py index 4b0d1a73e5..f0f14cb1a2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_DY_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py index d63c7f9cab..c61279cbe8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py index 6a2a2cb286..87c54145aa 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_WPWM_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py index d485a62c81..d7eba548ab 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_13TEV/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV SQRT_S = 13_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py index ddab8f5a32..f875fa3478 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_DIELECTRON/filter.py @@ -4,10 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import ( - covmat_to_artunc, - percentage_to_absolute, -) +from nnpdf_data.filter_utils.utils import covmat_to_artunc, percentage_to_absolute MZ_VALUE = 91.1876 # GeV SQRT_S = 7_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py index a603f11e5b..91195801d9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_7TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py index 8edf001649..9bd9881e2e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_DIELECTRON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV SQRT_S = 8_000.0 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py index 11f1899ddb..4ecaf473a7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/LHCB_Z0_8TEV_MUON/filter.py @@ -4,7 +4,7 @@ import pandas as pd import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import covmat_to_artunc +from nnpdf_data.filter_utils.utils import covmat_to_artunc MZ_VALUE = 91.1876 # GeV MW_VALUE = 80.398 # GeV diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml index f023ef4eda..878a047c2a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml @@ -21,7 +21,7 @@ implemented_observables: description: Integrability dataset for Polarized Gluon label: 'polarized integrability: $x \delta g$ PDF $Q^2=1$ GeV$^2$' units: '' - process_type: DIS_XDG + process_type: INTEG_XDG tables: [] npoints: [] ndata: 1 @@ -60,7 +60,7 @@ implemented_observables: description: Integrability dataset for Polarized Singlet label: 'polarized integrability: $x \delta \Sigma$ PDF $Q^2=1$ GeV$^2$' units: '' - process_type: DIS_XDSIGMA + process_type: INTEG_XDSIGMA tables: [] npoints: [] ndata: 1 @@ -99,7 +99,7 @@ implemented_observables: description: Integrability to be used in the flavour basis label: 'integrability dataset: $xT_8$ PDF, Q=Q_1' units: '' - process_type: DIS_XT8 + process_type: INTEG_XT8 tables: [] npoints: [] ndata: 1 @@ -135,7 +135,7 @@ implemented_observables: description: Integrability to be used in the flavour basis label: 'integrability dataset: $xT_3$ PDF, Q=Q_1' units: '' - process_type: DIS_XT8 + process_type: INTEG_XT8 tables: [] npoints: [] ndata: 1 diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml index 034ec37b7d..a42c79d69e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_F2C-17PTS.yaml @@ -1,205 +1,137 @@ bins: -- k1: +- x: min: null mid: 5.0e-07 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 1.940766723678e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 7.533150951473e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 2.924017738213e-05 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0001134967265154 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0004405413401349 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - 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index 26edc37705..24b058bef1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XSB.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XSB.yaml @@ -1,241 +1,161 @@ bins: -- k1: +- x: min: null mid: 5.0e-07 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 1.940766723678e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 7.533150951473e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 2.924017738213e-05 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0001134967265154 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0004405413401349 max: null - k2: + Q2: min: null mid: 5.0 max: 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26edc37705..24b058bef1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XSQ.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XSQ.yaml @@ -1,241 +1,161 @@ bins: -- k1: +- x: min: null mid: 5.0e-07 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 1.940766723678e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 7.533150951473e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 2.924017738213e-05 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0001134967265154 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0004405413401349 max: null - k2: + Q2: min: null mid: 5.0 max: null 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26edc37705..24b058bef1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUB.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUB.yaml @@ -1,241 +1,161 @@ bins: -- k1: +- x: min: null mid: 5.0e-07 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 1.940766723678e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 7.533150951473e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 2.924017738213e-05 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0001134967265154 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0004405413401349 max: null - k2: + Q2: min: null mid: 5.0 max: null 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26edc37705..24b058bef1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUQ.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_XUQ.yaml @@ -1,241 +1,161 @@ bins: -- k1: +- x: min: null mid: 5.0e-07 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 1.940766723678e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 7.533150951473e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 2.924017738213e-05 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0001134967265154 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0004405413401349 max: null - k2: + Q2: min: null mid: 5.0 max: null 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k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.5 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.58 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.66 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.74 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.82 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.9 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml index e12fcef16d..d9dffbdaa0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml @@ -17,7 +17,7 @@ implemented_observables: description: Fixed-Target Drell-Yan label: 'positivity dataset: DY cross section $\frac{d^2\sigma_{s\bar{s}}}{dM^2dy}$' units: '' - process_type: DYP_PPY_CON_ST + process_type: POS_PPY_CON_ST tables: [] npoints: [] ndata: 20 @@ -56,7 +56,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' units: '' - process_type: DIS_F2C + process_type: POS_F2 tables: [] npoints: [] ndata: 20 @@ -64,24 +64,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization Scale + label: Q2 units: '' file: kinematics_F2C.yaml theory: @@ -96,7 +91,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c$ structure function $F_2^{W^-,c}$' units: '' - process_type: DIS_F2C_CCE + process_type: POS_F2 tables: [] npoints: [] ndata: 17 @@ -104,24 +99,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $c$ structure function $F_2^{W^-,c}$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization Scale + label: Q2 units: '' file: kinematics_F2C-CCE-17PTS.yaml theory: @@ -136,7 +126,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $d+\bar{d}$ structure function $F_2^d$' units: '' - process_type: DIS_F2d + process_type: POS_F2 tables: [] npoints: [] ndata: 20 @@ -144,24 +134,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $d+\bar{d}$ structure function $F_2^d$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization Scale + label: Q2 units: '' file: kinematics_F2D.yaml theory: @@ -176,7 +161,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $s+\bar{s}$ structure function $F_2^s$' units: '' - process_type: DIS_F2S + process_type: POS_F2 tables: [] npoints: [] ndata: 20 @@ -184,24 +169,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $s+\bar{s}$ structure function $F_2^s$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization Scale + label: Q2 units: '' file: kinematics_F2S.yaml theory: @@ -216,7 +196,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS light quark longitudinal structure function $F_L^l$' units: '' - process_type: DIS_FLL + process_type: POS_FLL tables: [] npoints: [] ndata: 20 @@ -257,7 +237,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xc$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XCQ + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -265,24 +245,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xc$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XCQ.yaml theory: @@ -296,7 +271,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xd$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XDQ + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -304,24 +279,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xd$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XDQ.yaml theory: @@ -336,7 +306,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $x\bar{s}$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XSB + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -344,24 +314,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $x\bar{s}$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XSB.yaml theory: @@ -376,7 +341,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $x\bar{u}$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XUB + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -384,24 +349,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $x\bar{u}$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XUB.yaml theory: @@ -416,7 +376,7 @@ implemented_observables: description: Fixed-Target Drell-Yan label: 'positivity dataset: DY cross section $\frac{d^2\sigma_{d\bar{d}}}{dM^2dy}$' units: '' - process_type: DYP_PPY_CON_DW + process_type: POS_PPY_CON_DW tables: [] npoints: [] ndata: 20 @@ -455,7 +415,7 @@ implemented_observables: description: Fixed-Target Drell-Yan label: 'positivity dataset: DY cross section $\frac{d^2\sigma_{u\bar{u}}}{dM^2dy}$' units: '' - process_type: DYP_PPY_CON_UP + process_type: POS_PPY_CON_UP tables: [] npoints: [] ndata: 20 @@ -494,7 +454,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' units: '' - process_type: DIS_F2C + process_type: POS_F2 tables: [] npoints: [] ndata: 17 @@ -502,24 +462,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization Scale + label: Q2 units: '' file: kinematics_F2C-17PTS.yaml theory: @@ -534,7 +489,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: CC DIS $\bar{c}$ structure function $F_2^{W^+,c}$' units: '' - process_type: DIS_F2C_CCP + process_type: POS_F2 tables: [] npoints: [] ndata: 17 @@ -542,24 +497,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: CC DIS $\bar{c}$ structure function $F_2^{W^+,c}$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization Scale + label: Q2 units: '' file: kinematics_F2C-CCP-17PTS.yaml theory: @@ -574,7 +524,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $u+\bar{u}$ structure function $F_2^u$' units: '' - process_type: DIS_F2U + process_type: POS_F2 tables: [] npoints: [] ndata: 20 @@ -582,24 +532,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: DIS $u+\bar{u}$ structure function $F_2^u$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization Scale + label: Q2 units: '' file: kinematics_F2U.yaml theory: @@ -614,7 +559,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS light quark longitudinal structure function $F_L^l$' units: '' - process_type: DIS_FLL + process_type: POS_FLL tables: [] npoints: [] ndata: 19 @@ -655,7 +600,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $x\bar{d}$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XDB + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -663,24 +608,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $x\bar{d}$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XDB.yaml theory: @@ -695,7 +635,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xg$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XGL + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -703,24 +643,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xg$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XGL.yaml theory: @@ -735,7 +670,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xs$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XSQ + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -743,24 +678,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xs$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XSQ.yaml theory: @@ -775,7 +705,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: $xu$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XUQ + process_type: POS_XPDF tables: [] npoints: [] ndata: 20 @@ -783,24 +713,19 @@ implemented_observables: kinematics_override: dis_sqrt_scale theory_reference: Bertone:2013vaa dataset_label: 'positivity dataset: $xu$ PDF $Q^2=5$ GeV$^2$' - plot_x: k1 + plot_x: x kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_XUQ.yaml theory: @@ -815,7 +740,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta g$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XDG + process_type: POS_XDG tables: [] npoints: [] ndata: 20 @@ -855,7 +780,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta d$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XDDQ + process_type: POS_XDDQ tables: [] npoints: [] ndata: 20 @@ -897,7 +822,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta s$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XDSQ + process_type: POS_XDSQ tables: [] npoints: [] ndata: 20 @@ -939,7 +864,7 @@ implemented_observables: description: DIS positivity Boundary Condition label: 'polarized positivity: $x \delta u$ PDF $Q^2=5$ GeV$^2$' units: '' - process_type: DIS_XDUQ + process_type: POS_XDUQ tables: [] npoints: [] ndata: 20 diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py index e6c5b3fa0b..66c931644a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_300GEV_38P6PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py index 1804a8e969..9ecf7b5024 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_1JET_319GEV_82PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py index ce56dd4dab..3ab3b10a21 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/ZEUS_2JET_319GEV_374PB-1_DIF/filter.py @@ -1,6 +1,6 @@ import yaml -from nnpdf_data.new_commondata.ATLAS_TTBAR_13TEV_HADR_DIF.utils import symmetrize_errors as se +from nnpdf_data.filter_utils.utils import symmetrize_errors as se def processData(): diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002000.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002000.yaml new file mode 100644 index 0000000000..afbab80d4b --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002000.yaml @@ -0,0 +1,47 @@ +ID: 40_002_000 +Comments: NNPDF4.0 N3LO alphas=0.106 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.106 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002001.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002001.yaml new file mode 100644 index 0000000000..b702ec67ce --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002001.yaml @@ -0,0 +1,47 @@ +ID: 40_002_001 +Comments: NNPDF4.0 N3LO alphas=0.114 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.114 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002002.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002002.yaml new file mode 100644 index 0000000000..5c05cba3cb --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002002.yaml @@ -0,0 +1,47 @@ +ID: 40_002_002 +Comments: NNPDF4.0 N3LO alphas=0.115 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.115 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002003.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002003.yaml new file mode 100644 index 0000000000..4ea32913ef --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002003.yaml @@ -0,0 +1,47 @@ +ID: 40_002_003 +Comments: NNPDF4.0 N3LO alphas=0.116 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.116 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002004.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002004.yaml new file mode 100644 index 0000000000..fd9c5e281b --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002004.yaml @@ -0,0 +1,47 @@ +ID: 40_002_004 +Comments: NNPDF4.0 N3LO alphas=0.117 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.117 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002006.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002006.yaml new file mode 100644 index 0000000000..23d0bc8c5a --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002006.yaml @@ -0,0 +1,47 @@ +ID: 40_002_006 +Comments: NNPDF4.0 N3LO alphas=0.119 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.119 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002007.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002007.yaml new file mode 100644 index 0000000000..2e626d7854 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002007.yaml @@ -0,0 +1,47 @@ +ID: 40_002_007 +Comments: NNPDF4.0 N3LO alphas=0.120 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.120 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002008.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002008.yaml new file mode 100644 index 0000000000..96e2a12115 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002008.yaml @@ -0,0 +1,47 @@ +ID: 40_002_008 +Comments: NNPDF4.0 N3LO alphas=0.121 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.121 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002009.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002009.yaml new file mode 100644 index 0000000000..7f02ea7f3a --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002009.yaml @@ -0,0 +1,47 @@ +ID: 40_002_009 +Comments: NNPDF4.0 N3LO alphas=0.122 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.122 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002010.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002010.yaml new file mode 100644 index 0000000000..c953c33a0a --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002010.yaml @@ -0,0 +1,47 @@ +ID: 40_002_010 +Comments: NNPDF4.0 N3LO alphas=0.123 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.123 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002011.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002011.yaml new file mode 100644 index 0000000000..401637ce5c --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002011.yaml @@ -0,0 +1,47 @@ +ID: 40_002_011 +Comments: NNPDF4.0 N3LO alphas=0.124 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.124 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002012.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002012.yaml new file mode 100644 index 0000000000..6cf2197209 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002012.yaml @@ -0,0 +1,47 @@ +ID: 40_002_012 +Comments: NNPDF4.0 N3LO alphas=0.125 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.125 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/40002013.yaml b/nnpdf_data/nnpdf_data/theory_cards/40002013.yaml new file mode 100644 index 0000000000..ef948691e7 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/40002013.yaml @@ -0,0 +1,47 @@ +ID: 40_002_013 +Comments: NNPDF4.0 N3LO alphas=0.130 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-E +GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.130 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/722.yaml b/nnpdf_data/nnpdf_data/theory_cards/722.yaml index 2622647af3..f6bf79b6f1 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/722.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/722.yaml @@ -1,32 +1,5 @@ ID: 722 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 +Comments: NNPDF4.0 N3LO alphas=0.118 with new pipeline, no N3LO ad variation, XIF=1.0, XIR=1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +10,38 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +DAMP: 0 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 0) -global_nx: 0 -EScaleVar: 1 +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 4 +n3lo_ad_variation: [0,0,0,0,0,0,0] +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/723.yaml b/nnpdf_data/nnpdf_data/theory_cards/723.yaml index cecf813beb..fcebfdfb5d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/723.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/723.yaml @@ -1,32 +1,3 @@ -ID: 723 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [1, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 723 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (1, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 1 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/724.yaml b/nnpdf_data/nnpdf_data/theory_cards/724.yaml index 47b5e2d38e..bb7347197a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/724.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/724.yaml @@ -1,32 +1,3 @@ -ID: 724 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [2, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 724 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (2, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 2 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/725.yaml b/nnpdf_data/nnpdf_data/theory_cards/725.yaml index ba9ad896cd..1a5e8151cc 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/725.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/725.yaml @@ -1,32 +1,3 @@ -ID: 725 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [3, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 725 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (3, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 3 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/726.yaml b/nnpdf_data/nnpdf_data/theory_cards/726.yaml index 535e3011e1..5a8a18b279 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/726.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/726.yaml @@ -1,32 +1,3 @@ -ID: 726 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [4, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 726 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (4, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 4 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/727.yaml b/nnpdf_data/nnpdf_data/theory_cards/727.yaml index 5160499720..d514adbe51 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/727.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/727.yaml @@ -1,32 +1,3 @@ -ID: 727 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [5, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 727 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (5, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 5 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/728.yaml b/nnpdf_data/nnpdf_data/theory_cards/728.yaml index fbcd440bc0..2477d9802d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/728.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/728.yaml @@ -1,32 +1,3 @@ -ID: 728 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [6, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 728 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (6, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 6 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/729.yaml b/nnpdf_data/nnpdf_data/theory_cards/729.yaml index 0d90808126..a69b74c025 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/729.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/729.yaml @@ -1,32 +1,3 @@ -ID: 729 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [7, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 729 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (7, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 7 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/730.yaml b/nnpdf_data/nnpdf_data/theory_cards/730.yaml index e7d6ca94fa..70d2b061bf 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/730.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/730.yaml @@ -1,32 +1,3 @@ -ID: 730 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [8, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 730 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (8, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 8 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/731.yaml b/nnpdf_data/nnpdf_data/theory_cards/731.yaml index 7029054825..c0eb2ae0c9 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/731.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/731.yaml @@ -1,32 +1,3 @@ -ID: 731 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [9, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 731 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (9, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 9 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/732.yaml b/nnpdf_data/nnpdf_data/theory_cards/732.yaml index fb57e9a65a..c764fe73dd 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/732.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/732.yaml @@ -1,32 +1,3 @@ -ID: 732 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [10, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 732 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (10, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 10 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/733.yaml b/nnpdf_data/nnpdf_data/theory_cards/733.yaml index ec4c6e9aeb..da82b7f030 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/733.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/733.yaml @@ -1,32 +1,3 @@ -ID: 733 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [11, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 733 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (11, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 11 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/734.yaml b/nnpdf_data/nnpdf_data/theory_cards/734.yaml index aaa9922943..93f6f32920 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/734.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/734.yaml @@ -1,32 +1,3 @@ -ID: 734 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [12, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 734 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (12, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 12 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/735.yaml b/nnpdf_data/nnpdf_data/theory_cards/735.yaml index fd4b41a0fc..694156e6ba 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/735.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/735.yaml @@ -1,32 +1,3 @@ -ID: 735 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [13, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 735 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (13, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 13 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/736.yaml b/nnpdf_data/nnpdf_data/theory_cards/736.yaml index 6aad1ee57d..6db47e08cd 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/736.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/736.yaml @@ -1,32 +1,3 @@ -ID: 736 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [14, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 736 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (14, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 14 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/737.yaml b/nnpdf_data/nnpdf_data/theory_cards/737.yaml index 9f0c4b76b0..5580d26da3 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/737.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/737.yaml @@ -1,32 +1,3 @@ -ID: 737 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [15, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 737 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (15, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 15 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/738.yaml b/nnpdf_data/nnpdf_data/theory_cards/738.yaml index cb56abf388..d8dad59de7 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/738.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/738.yaml @@ -1,32 +1,3 @@ -ID: 738 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [16, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 738 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (16, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 16 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/739.yaml b/nnpdf_data/nnpdf_data/theory_cards/739.yaml index 64fb7ca703..00ba87e480 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/739.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/739.yaml @@ -1,32 +1,3 @@ -ID: 739 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [17, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 739 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (17, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 17 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/740.yaml b/nnpdf_data/nnpdf_data/theory_cards/740.yaml index 0b1d10cdd2..1f4df3c2ce 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/740.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/740.yaml @@ -1,32 +1,3 @@ -ID: 740 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [18, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 740 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (18, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 18 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/741.yaml b/nnpdf_data/nnpdf_data/theory_cards/741.yaml index 7d65c647de..612ace7ebb 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/741.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/741.yaml @@ -1,32 +1,3 @@ -ID: 741 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [19, 0, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 741 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (19, 0, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 19 +- 0 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/742.yaml b/nnpdf_data/nnpdf_data/theory_cards/742.yaml index 2c31c5ba35..0873e42030 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/742.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/742.yaml @@ -1,32 +1,3 @@ -ID: 742 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 1, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 742 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 1, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 1 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/743.yaml b/nnpdf_data/nnpdf_data/theory_cards/743.yaml index d8fcfa553a..3a80bd656c 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/743.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/743.yaml @@ -1,32 +1,3 @@ -ID: 743 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 2, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 743 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 2, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 2 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/744.yaml b/nnpdf_data/nnpdf_data/theory_cards/744.yaml index 31f3589b2d..aa8dfe9c32 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/744.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/744.yaml @@ -1,32 +1,3 @@ -ID: 744 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 3, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 744 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 3, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 3 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/745.yaml b/nnpdf_data/nnpdf_data/theory_cards/745.yaml index 932b553768..9aad630cfe 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/745.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/745.yaml @@ -1,32 +1,3 @@ -ID: 745 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 4, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 745 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 4, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 4 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/746.yaml b/nnpdf_data/nnpdf_data/theory_cards/746.yaml index 8d42e6ae4b..1c26eb5e3d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/746.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/746.yaml @@ -1,32 +1,3 @@ -ID: 746 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 5, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 746 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 5, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 5 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/747.yaml b/nnpdf_data/nnpdf_data/theory_cards/747.yaml index 7f3d460769..d65478bdbf 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/747.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/747.yaml @@ -1,32 +1,3 @@ -ID: 747 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 6, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 747 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 6, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 6 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/748.yaml b/nnpdf_data/nnpdf_data/theory_cards/748.yaml index 953ae6166e..1f08669a10 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/748.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/748.yaml @@ -1,32 +1,3 @@ -ID: 748 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 7, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 748 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 7, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 7 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/749.yaml b/nnpdf_data/nnpdf_data/theory_cards/749.yaml index 4620ef0c6a..9dd383454a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/749.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/749.yaml @@ -1,32 +1,3 @@ -ID: 749 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 8, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 749 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 8, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 8 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/750.yaml b/nnpdf_data/nnpdf_data/theory_cards/750.yaml index 5df5608f59..c5615fcdf4 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/750.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/750.yaml @@ -1,32 +1,3 @@ -ID: 750 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 9, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 750 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 9, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 9 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/751.yaml b/nnpdf_data/nnpdf_data/theory_cards/751.yaml index 01f21d7880..b95943b8f3 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/751.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/751.yaml @@ -1,32 +1,3 @@ -ID: 751 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 10, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 751 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 10, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 10 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/752.yaml b/nnpdf_data/nnpdf_data/theory_cards/752.yaml index fcf4a10f3e..389acd6ae4 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/752.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/752.yaml @@ -1,32 +1,3 @@ -ID: 752 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 11, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 752 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 11, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 11 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/753.yaml b/nnpdf_data/nnpdf_data/theory_cards/753.yaml index 02b10dbf87..0f85c1df2b 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/753.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/753.yaml @@ -1,32 +1,3 @@ -ID: 753 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 12, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 753 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 12, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 12 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/754.yaml b/nnpdf_data/nnpdf_data/theory_cards/754.yaml index 8ad96b61e8..5820a38eb5 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/754.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/754.yaml @@ -1,32 +1,3 @@ -ID: 754 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 13, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 754 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 13, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 13 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/755.yaml b/nnpdf_data/nnpdf_data/theory_cards/755.yaml index 25ca6d239b..fabfe95b5d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/755.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/755.yaml @@ -1,32 +1,3 @@ -ID: 755 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 14, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 755 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 14, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 14 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/756.yaml b/nnpdf_data/nnpdf_data/theory_cards/756.yaml index 1f9264aafd..f218900170 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/756.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/756.yaml @@ -1,32 +1,3 @@ -ID: 756 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 15, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 756 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 15, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 15 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/757.yaml b/nnpdf_data/nnpdf_data/theory_cards/757.yaml index 64ecb6fd6e..f147e573d7 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/757.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/757.yaml @@ -1,32 +1,3 @@ -ID: 757 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 16, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 757 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 16, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 16 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/758.yaml b/nnpdf_data/nnpdf_data/theory_cards/758.yaml index b5e354e2b8..0bf357dfd2 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/758.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/758.yaml @@ -1,32 +1,3 @@ -ID: 758 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 17, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 758 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 17, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 17 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/759.yaml b/nnpdf_data/nnpdf_data/theory_cards/759.yaml index 41e1fc9941..48b7de68b2 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/759.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/759.yaml @@ -1,32 +1,3 @@ -ID: 759 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 18, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 759 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 18, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 18 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/760.yaml b/nnpdf_data/nnpdf_data/theory_cards/760.yaml index 38bb57c478..a0cb058203 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/760.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/760.yaml @@ -1,32 +1,3 @@ -ID: 760 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 19, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 760 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 19, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 19 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/761.yaml b/nnpdf_data/nnpdf_data/theory_cards/761.yaml index 7be08cffc0..6846418361 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/761.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/761.yaml @@ -1,32 +1,3 @@ -ID: 761 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 20, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 761 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 20, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 20 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/762.yaml b/nnpdf_data/nnpdf_data/theory_cards/762.yaml index d26684046a..2c0de30417 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/762.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/762.yaml @@ -1,32 +1,3 @@ -ID: 762 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 21, 0, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 762 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 21, 0, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 21 +- 0 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/763.yaml b/nnpdf_data/nnpdf_data/theory_cards/763.yaml index 864788a535..c8d7874409 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/763.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/763.yaml @@ -1,32 +1,3 @@ -ID: 763 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 1, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 763 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 1, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 1 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/764.yaml b/nnpdf_data/nnpdf_data/theory_cards/764.yaml index f2900875d5..b36b8d58ee 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/764.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/764.yaml @@ -1,32 +1,3 @@ -ID: 764 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 2, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 764 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 2, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 2 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/765.yaml b/nnpdf_data/nnpdf_data/theory_cards/765.yaml index 4a9bf2ccf1..e5fddcfa91 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/765.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/765.yaml @@ -1,32 +1,3 @@ -ID: 765 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 3, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 765 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 3, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 3 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/766.yaml b/nnpdf_data/nnpdf_data/theory_cards/766.yaml index cd019666f6..0329045ddc 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/766.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/766.yaml @@ -1,32 +1,3 @@ -ID: 766 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 4, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 766 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 4, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 4 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/767.yaml b/nnpdf_data/nnpdf_data/theory_cards/767.yaml index b472654ff8..c27364bc6b 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/767.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/767.yaml @@ -1,32 +1,3 @@ -ID: 767 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 5, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 767 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 5, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 5 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/768.yaml b/nnpdf_data/nnpdf_data/theory_cards/768.yaml index 05a9660322..898bfe0363 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/768.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/768.yaml @@ -1,32 +1,3 @@ -ID: 768 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 6, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 768 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 6, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 6 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/769.yaml b/nnpdf_data/nnpdf_data/theory_cards/769.yaml index c258e4778f..f80f52b709 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/769.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/769.yaml @@ -1,32 +1,3 @@ -ID: 769 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 7, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 769 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 7, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 7 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/770.yaml b/nnpdf_data/nnpdf_data/theory_cards/770.yaml index 6f707f1710..ec1fdabb98 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/770.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/770.yaml @@ -1,32 +1,3 @@ -ID: 770 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 8, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 770 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 8, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 8 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/771.yaml b/nnpdf_data/nnpdf_data/theory_cards/771.yaml index fe21592023..2e1d4d9acb 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/771.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/771.yaml @@ -1,32 +1,3 @@ -ID: 771 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 9, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 771 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 9, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 9 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/772.yaml b/nnpdf_data/nnpdf_data/theory_cards/772.yaml index 73723224a5..1b1b7cade1 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/772.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/772.yaml @@ -1,32 +1,3 @@ -ID: 772 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 10, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 772 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 10, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 10 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/773.yaml b/nnpdf_data/nnpdf_data/theory_cards/773.yaml index 48ace19288..123be4241b 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/773.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/773.yaml @@ -1,32 +1,3 @@ -ID: 773 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 11, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 773 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 11, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 11 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/774.yaml b/nnpdf_data/nnpdf_data/theory_cards/774.yaml index f3eeb0589a..9fe611943a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/774.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/774.yaml @@ -1,32 +1,3 @@ -ID: 774 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 12, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 774 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 12, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 12 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/775.yaml b/nnpdf_data/nnpdf_data/theory_cards/775.yaml index d72aa8c7df..5b8d0d949a 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/775.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/775.yaml @@ -1,32 +1,3 @@ -ID: 775 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 13, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 775 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 13, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 13 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/776.yaml b/nnpdf_data/nnpdf_data/theory_cards/776.yaml index b83ca251e3..88b851725e 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/776.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/776.yaml @@ -1,32 +1,3 @@ -ID: 776 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 14, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 776 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 14, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 14 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/777.yaml b/nnpdf_data/nnpdf_data/theory_cards/777.yaml index 3bd23d3442..8283a89ba3 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/777.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/777.yaml @@ -1,32 +1,3 @@ -ID: 777 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 15, 0, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 777 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 15, 0) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 15 +- 0 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/778.yaml b/nnpdf_data/nnpdf_data/theory_cards/778.yaml index 3c19b90d47..350568fd08 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/778.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/778.yaml @@ -1,32 +1,3 @@ -ID: 778 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 1, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 778 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 1) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 0 +- 1 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/779.yaml b/nnpdf_data/nnpdf_data/theory_cards/779.yaml index bf3c68fc1e..9c0c5f6939 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/779.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/779.yaml @@ -1,32 +1,3 @@ -ID: 779 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 2, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 779 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 2) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 0 +- 2 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/780.yaml b/nnpdf_data/nnpdf_data/theory_cards/780.yaml index d03b7afb1b..946a6e0b69 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/780.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/780.yaml @@ -1,32 +1,3 @@ -ID: 780 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 3, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 780 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 3) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 0 +- 3 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/781.yaml b/nnpdf_data/nnpdf_data/theory_cards/781.yaml index e3783bfab0..f0887e5bfa 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/781.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/781.yaml @@ -1,32 +1,3 @@ -ID: 781 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 4, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 781 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 4) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 0 +- 4 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/782.yaml b/nnpdf_data/nnpdf_data/theory_cards/782.yaml index 21438c9f97..108ba61d81 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/782.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/782.yaml @@ -1,32 +1,3 @@ -ID: 782 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 5, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 782 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 5) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 0 +- 5 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/783.yaml b/nnpdf_data/nnpdf_data/theory_cards/783.yaml index 4a8338e207..5277d3a956 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/783.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/783.yaml @@ -1,32 +1,3 @@ -ID: 783 -PTO: 3 -FNS: FONLL-E -DAMP: 0 -IC: 1 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.65 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,53 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: NNPDF4.0 N3LO alphas=0.118, N3LO ad variation [0, 0, 0, 6, 0, 0, 0] +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-E GF: 1.1663787e-05 +HQ: POLE +IC: 1 +ID: 783 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: None +NfFF: 4 +PTO: 3 +Q0: 1.65 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 1 -MP: 0.938 -Comments: NNPDF4.0 N3LO ad variation (0, 0, 0, 6) +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +n3lo_ad_variation: +- 0 +- 0 +- 0 +- 6 +- 0 +- 0 +- 0 +n3lo_cf_variation: 0 +nf0: 4 +nfref: 5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/822.yaml b/nnpdf_data/nnpdf_data/theory_cards/822.yaml index 552f9baa1d..d3ba6ecb09 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/822.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/822.yaml @@ -1,32 +1,3 @@ -ID: 822 -PTO: 2 -FNS: FONLL-C -DAMP: 0 -IC: 0 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.0 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,45 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-C GF: 1.1663787e-05 +HQ: POLE +IC: 0 +ID: 822 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 3 -MP: 0.938 -Comments: Baseline for Polarised NNPDFpol2.0 NNLO with nFONLL +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/823.yaml b/nnpdf_data/nnpdf_data/theory_cards/823.yaml index 6ec9bc72f5..f47bd10e29 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/823.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/823.yaml @@ -1,32 +1,3 @@ -ID: 823 -PTO: 1 -FNS: FONLL-A -DAMP: 0 -IC: 0 -ModEv: TRN -XIR: 1.0 -XIF: 1.0 -NfFF: 5 -MaxNfAs: 5 -MaxNfPdf: 5 -Q0: 1.0 -alphas: 0.118 -Qref: 91.2 -QED: 0 -alphaqed: 0.007496252 -Qedref: 1.777 -SxRes: 0 -SxOrd: LL -HQ: POLE -mc: 1.51 -Qmc: 1.51 -kcThr: 1.0 -mb: 4.92 -Qmb: 4.92 -kbThr: 1.0 -mt: 172.5 -Qmt: 172.5 -ktThr: 1.0 CKM: - 0.97428 - 0.2253 @@ -37,12 +8,45 @@ CKM: - 0.00862 - 0.0403 - 0.999152 -MZ: 91.1876 -MW: 80.398 +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL +DAMP: 0 +EScaleVar: 1 +FNS: FONLL-A GF: 1.1663787e-05 +HQ: POLE +IC: 0 +ID: 823 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfAs: 5 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qedref: 1.777 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 SIN2TW: 0.23126 +SxOrd: LL +SxRes: 0 TMC: 3 -MP: 0.938 -Comments: Baseline for Polarised NNPDFpol2.0 NLO with nFONLL +XIF: 1.0 +XIR: 1.0 +alphaqed: 0.007496252 +alphas: 0.118 global_nx: 0 -EScaleVar: 1 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 diff --git a/validphys2/src/validphys/calcutils.py b/validphys2/src/validphys/calcutils.py index 48e402f687..8976de7b56 100644 --- a/validphys2/src/validphys/calcutils.py +++ b/validphys2/src/validphys/calcutils.py @@ -4,6 +4,7 @@ Low level utilities to calculate χ² and such. These are used to implement the higher level functions in results.py """ + import logging from typing import Callable @@ -15,7 +16,7 @@ def calc_chi2(sqrtcov, diffs): - """Elementary function to compute the chi², given a Cholesky decomposed + r"""Elementary function to compute the chi², given a Cholesky decomposed lower triangular part and a vector of differences. Parameters diff --git a/validphys2/src/validphys/config.py b/validphys2/src/validphys/config.py index 3b0a66398b..1880fda054 100644 --- a/validphys2/src/validphys/config.py +++ b/validphys2/src/validphys/config.py @@ -685,15 +685,6 @@ def produce_experiment_from_input(self, experiment_input, theoryid, use_cuts, fi ) } - def produce_sep_mult(self, separate_multiplicative=None): - """ - Specifies whether to separate the multiplicative errors in the - experimental covmat construction. The default is True. - """ - if separate_multiplicative is False: - return False - return True - @configparser.explicit_node def produce_dataset_inputs_fitting_covmat( self, theory_covmat_flag=False, use_thcovmat_in_fitting=False @@ -712,7 +703,10 @@ def produce_dataset_inputs_fitting_covmat( @configparser.explicit_node def produce_dataset_inputs_sampling_covmat( - self, sep_mult, theory_covmat_flag=False, use_thcovmat_in_sampling=False + self, + separate_multiplicative=False, + theory_covmat_flag=False, + use_thcovmat_in_sampling=False, ): """ Produces the correct covmat to be used in make_replica according @@ -722,12 +716,12 @@ def produce_dataset_inputs_sampling_covmat( from validphys import covmats if theory_covmat_flag and use_thcovmat_in_sampling: - if sep_mult: + if separate_multiplicative: return covmats.dataset_inputs_total_covmat_separate else: return covmats.dataset_inputs_total_covmat else: - if sep_mult: + if separate_multiplicative: return covmats.dataset_inputs_exp_covmat_separate else: return covmats.dataset_inputs_exp_covmat @@ -1004,7 +998,7 @@ def parse_fakepdf(self, name): """PDF set used to generate the fake data in a closure test.""" return self.parse_pdf(name) - def _parse_lagrange_multiplier(self, kind, theoryid, setdict): + def _parse_lagrange_multiplier(self, kind, theoryid, setdict, rules): """Lagrange multiplier constraints are mappings containing a `dataset` and a `maxlambda` argument which defines the maximum value allowed for the multiplier""" @@ -1027,17 +1021,17 @@ def _parse_lagrange_multiplier(self, kind, theoryid, setdict): except ValueError as e: raise ConfigError(bad_msg) from e if kind == "posdataset": - return self.loader.check_posset(theoryno, name, maxlambda) + return self.loader.check_posset(theoryno, name, maxlambda, rules) elif kind == "integdataset": - return self.loader.check_integset(theoryno, name, maxlambda) + return self.loader.check_integset(theoryno, name, maxlambda, rules) else: raise ConfigError(f"The lagrange multiplier type {kind} is not understood") @element_of("posdatasets") - def parse_posdataset(self, posset: dict, *, theoryid): + def parse_posdataset(self, posset: dict, *, theoryid, rules): """An observable used as positivity constrain in the fit. It is a mapping containing 'dataset' and 'maxlambda'.""" - return self._parse_lagrange_multiplier("posdataset", theoryid, posset) + return self._parse_lagrange_multiplier("posdataset", theoryid, posset, rules) def produce_posdatasets(self, positivity): if not isinstance(positivity, dict) or "posdatasets" not in positivity: @@ -1047,11 +1041,11 @@ def produce_posdatasets(self, positivity): return positivity["posdatasets"] @element_of("integdatasets") - def parse_integdataset(self, integset: dict, *, theoryid): + def parse_integdataset(self, integset: dict, *, theoryid, rules): """An observable corresponding to a PDF in the evolution basis, used as integrability constrain in the fit. It is a mapping containing 'dataset' and 'maxlambda'.""" - return self._parse_lagrange_multiplier("integdataset", theoryid, integset) + return self._parse_lagrange_multiplier("integdataset", theoryid, integset, rules) def produce_integdatasets(self, integrability): if not isinstance(integrability, dict) or "integdatasets" not in integrability: diff --git a/validphys2/src/validphys/core.py b/validphys2/src/validphys/core.py index 1825fd18cc..97ea9d5260 100644 --- a/validphys2/src/validphys/core.py +++ b/validphys2/src/validphys/core.py @@ -393,9 +393,9 @@ def load(self): class InternalCutsWrapper(TupleComp): def __init__(self, commondata, rules): - self.rules = rules + self.rules = rules if rules else tuple() self.commondata = commondata - super().__init__(commondata, tuple(rules)) + super().__init__(commondata, tuple(self.rules)) def load(self): return np.atleast_1d( @@ -460,9 +460,12 @@ def cut_mask(cuts): class DataSetSpec(TupleComp): - def __init__(self, *, name, commondata, fkspecs, thspec, cuts, frac=1, op=None, weight=1): + def __init__( + self, *, name, commondata, fkspecs, thspec, cuts, frac=1, op=None, weight=1, rules=() + ): self.name = name self.commondata = commondata + self.rules = rules if isinstance(fkspecs, FKTableSpec): fkspecs = (fkspecs,) @@ -485,7 +488,7 @@ def __init__(self, *, name, commondata, fkspecs, thspec, cuts, frac=1, op=None, self.op = op self.weight = weight - super().__init__(name, commondata, fkspecs, thspec, cuts, frac, op, weight) + super().__init__(name, commondata, fkspecs, thspec, cuts, frac, op, weight, rules) @functools.lru_cache def load_commondata(self): @@ -573,11 +576,16 @@ class LagrangeSetSpec(DataSetSpec): and other Lagrange Multiplier datasets. """ - def __init__(self, name, commondataspec, fkspec, maxlambda, thspec): - cuts = Cuts(commondataspec, None) + def __init__(self, name, commondataspec, fkspec, maxlambda, thspec, rules): + cuts = InternalCutsWrapper(commondataspec, rules) self.maxlambda = maxlambda super().__init__( - name=name, commondata=commondataspec, fkspecs=fkspec, thspec=thspec, cuts=cuts + name=name, + commondata=commondataspec, + fkspecs=fkspec, + thspec=thspec, + cuts=cuts, + rules=rules, ) def to_unweighted(self): @@ -586,10 +594,6 @@ def to_unweighted(self): ) return self - @functools.lru_cache - def load_commondata(self): - return self.commondata.load() - class PositivitySetSpec(LagrangeSetSpec): pass diff --git a/validphys2/src/validphys/filters.py b/validphys2/src/validphys/filters.py index ecdaef237a..130047385e 100644 --- a/validphys2/src/validphys/filters.py +++ b/validphys2/src/validphys/filters.py @@ -189,7 +189,7 @@ def export_mask(path, mask): np.savetxt(path, mask, fmt='%d') -def filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, sep_mult): +def filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, separate_multiplicative): """Filter closure data. In addition to cutting data points, the data is generated from an underlying ``fakepdf``, applying a shift to the data if ``fakenoise`` is ``True``, which emulates the experimental central values @@ -197,11 +197,19 @@ def filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, sep_m """ log.info('Filtering closure-test data.') - return _filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, sep_mult) + return _filter_closure_data( + filter_path, data, fakepdf, fakenoise, filterseed, separate_multiplicative + ) def filter_closure_data_by_experiment( - filter_path, experiments_data, fakepdf, fakenoise, filterseed, data_index, sep_mult + filter_path, + experiments_data, + fakepdf, + fakenoise, + filterseed, + data_index, + separate_multiplicative, ): """ Like :py:func:`filter_closure_data` except filters data by experiment. @@ -218,7 +226,13 @@ def filter_closure_data_by_experiment( experiment_index = data_index[data_index.isin([exp.name], level=0)] res.append( _filter_closure_data( - filter_path, exp, fakepdf, fakenoise, filterseed, experiment_index, sep_mult + filter_path, + exp, + fakepdf, + fakenoise, + filterseed, + experiment_index, + separate_multiplicative, ) ) @@ -269,7 +283,9 @@ def _filter_real_data(filter_path, data): return total_data_points, total_cut_data_points -def _filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, data_index, sep_mult): +def _filter_closure_data( + filter_path, data, fakepdf, fakenoise, filterseed, data_index, separate_multiplicative +): """ This function is accessed within a closure test only, that is, the fakedata namespace has to be True (If fakedata = False, the _filter_real_data function @@ -334,7 +350,9 @@ def _filter_closure_data(filter_path, data, fakepdf, fakenoise, filterseed, data if fakenoise: # ======= Level 1 closure test =======# - closure_data = make_level1_data(data, closure_data, filterseed, data_index, sep_mult) + closure_data = make_level1_data( + data, closure_data, filterseed, data_index, separate_multiplicative + ) # ====== write commondata and systype files ======# if fakenoise: @@ -391,7 +409,7 @@ def check_positivity(posdatasets): log.info('Verifying positivity tables:') for pos in posdatasets: pos.load_commondata() - log.info(f'{pos.name} checked.') + log.info(f'{pos.name} checked, {len(pos.cuts.load())}/{pos.commondata.ndata} datapoints passed kinematic cuts.') def check_integrability(integdatasets): diff --git a/validphys2/src/validphys/loader.py b/validphys2/src/validphys/loader.py index c238768bc7..7412281a8a 100644 --- a/validphys2/src/validphys/loader.py +++ b/validphys2/src/validphys/loader.py @@ -14,7 +14,6 @@ import sys import tarfile import tempfile -from typing import List import urllib.parse as urls import requests @@ -296,7 +295,7 @@ def available_hyperscans(self): return [] @property - @functools.lru_cache() + @functools.lru_cache def available_theories(self): """Return a string token for each of the available theories""" theory_token = 'theory_' @@ -306,7 +305,7 @@ def available_theories(self): } @property - @functools.lru_cache() + @functools.lru_cache def available_ekos(self): """Return a string token for each of the available theories""" return { @@ -314,7 +313,7 @@ def available_ekos(self): } @property - @functools.lru_cache() + @functools.lru_cache def _available_old_datasets(self): """Provide all available datasets At the moment this means cominbing the new and olf format datasets @@ -329,7 +328,7 @@ def _available_old_datasets(self): } @property - @functools.lru_cache() + @functools.lru_cache def available_datasets(self): """Provide all available datasets other then positivitiy and integrability. At the moment this only returns old datasets for which we have a translation available @@ -339,7 +338,7 @@ def available_datasets(self): return set(old_datasets) @property - @functools.lru_cache() + @functools.lru_cache def implemented_datasets(self): """Provide all implemented datasets that can be found in the datafiles folder regardless of whether they can be used for fits (i.e., whether they include a theory), @@ -351,7 +350,7 @@ def implemented_datasets(self): return datasets @property - @functools.lru_cache() + @functools.lru_cache def available_pdfs(self): return lhaindex.expand_local_names('*') @@ -512,17 +511,15 @@ def check_commondata( setname, metadata, legacy=True, datafile=datafile, sysfile=sysfile, plotfiles=plotfiles ) - @functools.lru_cache() + @functools.lru_cache def check_theoryID(self, theoryID): theoryID = str(theoryID) theopath = self._theories_path / f"theory_{theoryID}" if not theopath.exists(): - raise TheoryNotFound( - "Could not find theory {}. Folder '{}' not found".format(theoryID, theopath) - ) + raise TheoryNotFound(f"Could not find theory {theoryID}. Folder '{theopath}' not found") return TheoryIDSpec(theoryID, theopath, self.theorydb_folder) - @functools.lru_cache() + @functools.lru_cache def check_eko(self, theoryID): """Check the eko (and the parent theory) both exists and returns the path to it""" theory = self.check_theoryID(theoryID) @@ -554,7 +551,7 @@ def check_fktable(self, theoryID, setname, cfac): fkpath = theopath / 'fastkernel' / ('FK_%s.dat' % setname) if not fkpath.exists(): raise FKTableNotFound( - "Could not find FKTable for set '{}'. File '{}' not found".format(setname, fkpath) + f"Could not find FKTable for set '{setname}'. File '{fkpath}' not found" ) cfactors = self.check_cfactor(theoryID, setname, cfac) @@ -636,18 +633,18 @@ def _check_lagrange_multiplier_set(self, theoryID, setname): fk, _ = self._check_theory_old_or_new(th, cd, []) return cd, fk, th - def check_posset(self, theoryID, setname, postlambda): + def check_posset(self, theoryID, setname, postlambda, rules): """Load a positivity dataset""" cd, fk, th = self._check_lagrange_multiplier_set(theoryID, setname) - return PositivitySetSpec(setname, cd, fk, postlambda, th) + return PositivitySetSpec(setname, cd, fk, postlambda, th, rules) - def check_integset(self, theoryID, setname, postlambda): + def check_integset(self, theoryID, setname, postlambda, rules): """Load an integrability dataset""" cd, fk, th = self._check_lagrange_multiplier_set(theoryID, setname) - return IntegrabilitySetSpec(setname, cd, fk, postlambda, th) + return IntegrabilitySetSpec(setname, cd, fk, postlambda, th, rules) - def get_posset(self, theoryID, setname, postlambda): - return self.check_posset(theoryID, setname, postlambda).load() + def get_posset(self, theoryID, setname, postlambda, rules): + return self.check_posset(theoryID, setname, postlambda, rules).load() def check_fit(self, fitname): resultspath = self.resultspath @@ -799,9 +796,10 @@ def check_dataset( frac=frac, op=op, weight=weight, + rules=rules, ) - def check_experiment(self, name: str, datasets: List[DataSetSpec]) -> DataGroupSpec: + def check_experiment(self, name: str, datasets: list[DataSetSpec]) -> DataGroupSpec: """Loader method for instantiating DataGroupSpec objects. The NNPDF::Experiment object can then be instantiated using the load method. @@ -949,13 +947,11 @@ def download_file(url, stream_or_path, make_parents=False, delete_on_failure=Fal if make_parents: p.parent.mkdir(exist_ok=True, parents=True) - download_target = tempfile.NamedTemporaryFile( + with tempfile.NamedTemporaryFile( delete=delete_on_failure, dir=p.parent, prefix=p.name, suffix='.part' - ) - - with download_target as f: + ) as f: _download_and_show(response, f) - shutil.move(download_target.name, p) + shutil.move(f.name, p) else: log.info("Downloading %s.", url) _download_and_show(response, stream_or_path) @@ -980,7 +976,7 @@ def download_and_extract(url, local_path, target_name=None): try: res_tar.extractall(path=dest_path, filter="data") except tarfile.LinkOutsideDestinationError as e: - if sys.verson_info > (3, 11): + if sys.version_info > (3, 11): raise e # For older versions of python ``filter=data`` might be too restrictive # for the links inside the ``postfit`` folder if you are using more than one disk @@ -1090,15 +1086,13 @@ def _remote_files_from_url(self, url, index, thing='files'): resp = requests.get(index_url) resp.raise_for_status() except Exception as e: - raise RemoteLoaderError( - "Failed to fetch remote {} index {}: {}".format(thing, index_url, e) - ) from e + raise RemoteLoaderError(f"Failed to fetch remote {thing} index {index_url}: {e}") from e try: info = resp.json()['files'] except Exception as e: raise RemoteLoaderError( - "Malformed index {}. Expecting json with a key 'files': {}".format(index_url, e) + f"Malformed index {index_url}. Expecting json with a key 'files': {e}" ) from e return {file.split('.')[0]: url + file for file in info} @@ -1113,31 +1107,31 @@ def remote_files(self, urls, index, thing='files'): return d @property - @functools.lru_cache() + @functools.lru_cache def remote_fits(self): return self.remote_files(self.fit_urls, self.fit_index, thing="fits") @property - @functools.lru_cache() + @functools.lru_cache def remote_hyperscans(self): return self.remote_files(self.hyperscan_url, self.hyperscan_index, thing="hyperscan") @property - @functools.lru_cache() + @functools.lru_cache def remote_theories(self): token = 'theory_' rt = self.remote_files(self.theory_urls, self.theory_index, thing="theories") return {k[len(token) :]: v for k, v in rt.items()} @property - @functools.lru_cache() + @functools.lru_cache def remote_ekos(self): token = 'eko_' rt = self.remote_files(self.eko_urls, self.eko_index, thing="ekos") return {k[len(token) :]: v for k, v in rt.items()} @property - @functools.lru_cache() + @functools.lru_cache def remote_nnpdf_pdfs(self): return self.remote_files(self.nnpdf_pdfs_urls, self.nnpdf_pdfs_index, thing="PDFs") diff --git a/validphys2/src/validphys/process_options.py b/validphys2/src/validphys/process_options.py index 4b13440dfe..059ddcd28e 100644 --- a/validphys2/src/validphys/process_options.py +++ b/validphys2/src/validphys/process_options.py @@ -206,6 +206,7 @@ def _displusjet_xq2map(kin_info): return x, q2 + def _dyboson_xq2map(kin_info): """ Computes x and q2 mapping for pseudo rapidity observables @@ -307,6 +308,10 @@ def _dybosonpt_xq2map(kin_dict): ) +POS_XPDF = _Process("POS_XPDF", "Positivity of MS bar PDFs", accepted_variables=(_Vars.x, _Vars.Q2)) + +POS_F2 = _Process("POS_F2", "Positivity of F2 structure functions", accepted_variables=(_Vars.x, _Vars.Q2)) + PROCESSES = { "DIS": DIS, "DIS_NC": dataclasses.replace(DIS, name="DIS_NC"), @@ -324,7 +329,9 @@ def _dybosonpt_xq2map(kin_dict): "HERADIJET": dataclasses.replace(HERAJET, name="HERADIJET", description="DIS + jj production"), "DY_Z_Y": dataclasses.replace(DY_2L, name="DY_Z_Y", description="DY Z -> ll (pseudo)rapidity"), "DY_W_ETA": dataclasses.replace(DY_2L, name="DY_W_ETA", description="DY W -> l nu (pseudo)rapidity"), - "DY_NC_PT": dataclasses.replace(DY_PT, name="DY_NC_PT", description="DY Z (ll) + j") + "DY_NC_PT": dataclasses.replace(DY_PT, name="DY_NC_PT", description="DY Z (ll) + j"), + "POS_XPDF": POS_XPDF, + "POS_F2": POS_F2, } diff --git a/validphys2/src/validphys/pseudodata.py b/validphys2/src/validphys/pseudodata.py index c12368f13e..a0083bb803 100644 --- a/validphys2/src/validphys/pseudodata.py +++ b/validphys2/src/validphys/pseudodata.py @@ -126,7 +126,7 @@ def make_replica( groups_dataset_inputs_loaded_cd_with_cuts, replica_mcseed, dataset_inputs_sampling_covmat, - sep_mult, + separate_multiplicative=False, genrep=True, max_tries=int(1e6), resample_negative_pseudodata=True, @@ -153,8 +153,8 @@ def make_replica( Full covmat to be used. It can be either only experimental or also theoretical. separate_multiplicative: bool - Specifies whether computing the shifts with the full covmat or separating multiplicative - errors (in the latter case remember to generate the covmat coherently) + Specifies whether computing the shifts with the full covmat + or whether multiplicative errors should be separated genrep: bool Specifies whether computing replicas or not @@ -221,7 +221,7 @@ def make_replica( pseudodatas.append(pseudodata) # Separation of multiplicative errors. If separate_multiplicative is True also the exp_covmat is produced # without multiplicative errors - if sep_mult: + if separate_multiplicative: mult_errors = cd.multiplicative_errors mult_uncorr_errors = mult_errors.loc[:, mult_errors.columns == "UNCORR"].to_numpy() mult_corr_errors = mult_errors.loc[:, mult_errors.columns == "CORR"].to_numpy() @@ -234,7 +234,7 @@ def make_replica( else: check_positive_masks.append(np.ones_like(pseudodata, dtype=bool)) # concatenating special multiplicative errors, pseudodatas and positive mask - if sep_mult: + if separate_multiplicative: special_mult_errors = pd.concat(special_mult, axis=0, sort=True).fillna(0).to_numpy() all_pseudodata = np.concatenate(pseudodatas, axis=0) full_mask = np.concatenate(check_positive_masks, axis=0) @@ -255,10 +255,10 @@ def make_replica( mult_shifts.append(mult_shift) - # If sep_mult is true then the multiplicative shifts were not included in the covmat + # If separate_multiplicative is true then the multiplicative shifts were not included in the covmat shifts = covmat_sqrt @ rng.normal(size=covmat.shape[1]) mult_part = 1.0 - if sep_mult: + if separate_multiplicative: special_mult = ( 1 + special_mult_errors * rng.normal(size=(1, special_mult_errors.shape[1])) / 100 ).prod(axis=1) @@ -329,7 +329,7 @@ def level0_commondata_wc(data, fakepdf): return level0_commondata_instances_wc -def make_level1_data(data, level0_commondata_wc, filterseed, data_index, sep_mult): +def make_level1_data(data, level0_commondata_wc, filterseed, data_index, separate_multiplicative): """ Given a list of Level 0 commondata instances, return the same list with central values replaced by Level 1 data. @@ -395,12 +395,16 @@ def make_level1_data(data, level0_commondata_wc, filterseed, data_index, sep_mul use_weights_in_covmat=False, norm_threshold=None, _list_of_central_values=None, - _only_additive=sep_mult, + _only_additive=separate_multiplicative, ) # ================== generation of Level1 data ======================# level1_data = make_replica( - level0_commondata_wc, filterseed, covmat, sep_mult=sep_mult, genrep=True + level0_commondata_wc, + filterseed, + covmat, + separate_multiplicative=separate_multiplicative, + genrep=True, ) indexed_level1_data = indexed_make_replica(data_index, level1_data) diff --git a/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv b/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv index f2b40b260b..0eecde74ff 100644 --- a/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv +++ b/validphys2/src/validphys/tests/regressions/test_art_rep_generation.csv @@ -1,267 +1,267 @@ rep0 -0 572338.2619436508 -1 596772.0069843959 -2 622904.7201631162 -3 607453.75642249 -4 637687.7926100292 -5 648667.2363033721 -6 627358.5180855879 -7 635201.25311407 -8 641790.2072383957 -9 612196.3033407939 -10 566873.4104745645 -11 459963.15651932725 -12 449188.0970550337 -13 465168.9144436549 -14 437789.5177336811 -15 423294.806643127 -16 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+252 17.275678372438687 +253 7.552105345945224 +254 3.3133791467805516 +255 1.4247464276948372 +256 0.6186284513940463 +257 0.26209112451049466 +258 0.09464069542821087 +259 0.03582452036000859 +260 0.011756450233868202 +261 0.0042710206106938015 +262 0.0012396496869583667 +263 0.00017932373935161937 +264 2.1066841195216407e-05 +265 7.1113806035161245e-06 diff --git a/validphys2/src/validphys/tests/regressions/test_mcreplica.csv b/validphys2/src/validphys/tests/regressions/test_mcreplica.csv index 68fbb927b7..9c3a0836b4 100644 --- a/validphys2/src/validphys/tests/regressions/test_mcreplica.csv +++ b/validphys2/src/validphys/tests/regressions/test_mcreplica.csv @@ -1,267 +1,267 @@ group dataset id data -ATLAS ATLASWZRAP36PB 0 632751.995285571 -ATLAS ATLASWZRAP36PB 1 617041.3770628204 -ATLAS ATLASWZRAP36PB 2 657031.1685434954 -ATLAS ATLASWZRAP36PB 3 632499.3965744593 -ATLAS ATLASWZRAP36PB 4 654675.1207168144 -ATLAS ATLASWZRAP36PB 5 671000.2517548004 -ATLAS ATLASWZRAP36PB 6 664492.5507759772 -ATLAS ATLASWZRAP36PB 7 673032.1212200349 -ATLAS ATLASWZRAP36PB 8 665215.788381472 -ATLAS ATLASWZRAP36PB 9 658123.0178381058 -ATLAS ATLASWZRAP36PB 10 597391.6454749889 -ATLAS ATLASWZRAP36PB 11 444047.30792477645 -ATLAS ATLASWZRAP36PB 12 461624.00308643933 -ATLAS ATLASWZRAP36PB 13 466682.65352411283 -ATLAS ATLASWZRAP36PB 14 443015.00625158753 -ATLAS ATLASWZRAP36PB 15 445907.12168187584 -ATLAS ATLASWZRAP36PB 16 434486.1014580558 -ATLAS ATLASWZRAP36PB 17 409162.7570787424 -ATLAS ATLASWZRAP36PB 18 391449.7144861298 -ATLAS ATLASWZRAP36PB 19 382191.8381592813 -ATLAS ATLASWZRAP36PB 20 370809.4669654236 -ATLAS ATLASWZRAP36PB 21 353657.9867115815 -ATLAS ATLASWZRAP36PB 22 134625.48129342342 -ATLAS ATLASWZRAP36PB 23 135958.30317018856 -ATLAS ATLASWZRAP36PB 24 132213.084983002 -ATLAS ATLASWZRAP36PB 25 125052.71400189628 -ATLAS ATLASWZRAP36PB 26 119121.54397226803 -ATLAS ATLASWZRAP36PB 27 108213.68507780871 -ATLAS ATLASWZRAP36PB 28 96961.99666273188 -ATLAS ATLASWZRAP36PB 29 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+ "dataset_input": "SLAC_NC_NOTFIXED_D_DW_EM-F2", + "variant": "legacy", + "theoryid": THEORYID_NEW, + "use_cuts": "internal", + } + ) # Test a dataset with no systematics emptysyscd = l.check_posset( - theoryID=THEORYID_NEW, setname='NNPDF_POS_2P24GEV_XDQ', postlambda=1e-10 + theoryID=THEORYID_NEW, setname='NNPDF_POS_2P24GEV_XDQ', postlambda=1e-10, rules=rules ) emptysysres = load_commondata(emptysyscd.commondata) assert emptysysres.nsys == 0 diff --git a/validphys2/src/validphys/tests/test_overfit_metric.py b/validphys2/src/validphys/tests/test_overfit_metric.py index 92b6a4332b..342f21f79c 100644 --- a/validphys2/src/validphys/tests/test_overfit_metric.py +++ b/validphys2/src/validphys/tests/test_overfit_metric.py @@ -17,6 +17,7 @@ "t0pdfset": {"from_": "datacuts"}, "pdf": {"from_": "fit"}, "dataset_inputs": {"from_": "fit"}, + "separate_multiplicative": True } diff --git a/validphys2/src/validphys/tests/test_pseudodata.py b/validphys2/src/validphys/tests/test_pseudodata.py index 74f2dd87d0..be6e02ebe5 100644 --- a/validphys2/src/validphys/tests/test_pseudodata.py +++ b/validphys2/src/validphys/tests/test_pseudodata.py @@ -74,7 +74,7 @@ def test_no_savepseudodata(): def test_read_matches_recreate(): reads = API.read_fit_pseudodata(fit=PSEUDODATA_FIT) - recreates = API.recreate_fit_pseudodata(fit=PSEUDODATA_FIT) + recreates = API.recreate_fit_pseudodata(fit=PSEUDODATA_FIT, separate_multiplicative=True) for read, recreate in zip(reads, recreates): # We ignore the absolute ordering of the dataframes and just check # that they contain identical elements. diff --git a/validphys2/src/validphys/tests/test_pyfkdata.py b/validphys2/src/validphys/tests/test_pyfkdata.py index f1bb958b72..b5a711c430 100644 --- a/validphys2/src/validphys/tests/test_pyfkdata.py +++ b/validphys2/src/validphys/tests/test_pyfkdata.py @@ -94,13 +94,13 @@ def test_positivity(pdf_name): pdf = l.check_pdf(pdf_name) for posset in POSITIVITIES: # Use the loader to load the positivity dataset - ps = l.check_posset(setname=posset, theoryID=THEORYID, postlambda=1e6) + ps = l.check_posset(setname=posset, theoryID=THEORYID, postlambda=1e6, rules=()) preds = predictions(ps, pdf) core_predictions = PositivityResult.from_convolution(pdf, ps) assert_allclose(preds.values, core_predictions.rawdata) # Now do the same with the API api_predictions = API.positivity_predictions_data_result( - theoryid=THEORYID, pdf=pdf_name, posdataset={"dataset": posset, "maxlambda": 1e6} + theoryid=THEORYID, use_cuts="internal", pdf=pdf_name, posdataset={"dataset": posset, "maxlambda": 1e6} ) assert_allclose(preds.values, api_predictions.rawdata) # And now check that the results are correct for any kind of PDF diff --git a/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py b/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py index 33fbe12f4d..d71db0644e 100644 --- a/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py +++ b/validphys2/src/validphys/theorycovariance/theorycovarianceutils.py @@ -3,6 +3,7 @@ Low level utilities for theorycovariance module """ + import logging from reportengine.checks import check, make_argcheck @@ -58,9 +59,6 @@ def check_correct_theory_combination_internal( correct_xirs = [1.0, 1.0, 1.0, 2.0, 0.5, 2.0, 0.5] elif l in [62, 64, 66, 70]: # check Anomalous dimensions variations - n3lo_vars_dict = {"gg": 19, "gq": 21, "qg": 15, "qq": 6} - # TODO: for the moment fish the n3lo_ad_variation from the comments - n3lo_vars_list = [] id_max = None if l == 70: id_max = -8 @@ -68,11 +66,18 @@ def check_correct_theory_combination_internal( id_max = -4 elif l == 64: id_max = -2 + n3lo_vars_list = [] for theoryid in theoryids[:id_max]: - n3lo_vars_list.append( - [int(val) for val in theoryid.get_description()["Comments"][28:-1].split(",")] - ) + n3lo_ad_variation = theoryid.get_description()["n3lo_ad_variation"] + # Only take the first 4, the last three are NS and only relevant for FHMRUVV + if any(n3lo_ad_variation[4:]): + raise ValueError( + f"Theory {theoryid.id} has non-zero entries in the last three (NS) elements " + "of n3lo_ad_variation, the covmat construction does not support this!" + ) + n3lo_vars_list.append(theoryid.get_description()["n3lo_ad_variation"][:4]) full_var_list = [[0, 0, 0, 0]] + n3lo_vars_dict = {"gg": 19, "gq": 21, "qg": 15, "qq": 6} for entry, max_var in enumerate(n3lo_vars_dict.values()): for idx in range(1, max_var + 1): base_var = [0, 0, 0, 0] diff --git a/validphys2/src/validphys/uploadutils.py b/validphys2/src/validphys/uploadutils.py index bc459c7a17..2420845282 100644 --- a/validphys2/src/validphys/uploadutils.py +++ b/validphys2/src/validphys/uploadutils.py @@ -3,6 +3,7 @@ Tools to upload resources to remote servers. """ + import base64 import contextlib from glob import glob @@ -91,7 +92,7 @@ def check_auth(self): % str_line ) from e except OSError as e: - raise BadSSH("Could not run the command\n%s\n: %s" % (str_line, e)) from e + raise BadSSH(f"Could not run the command\n{str_line}\n: {e}") from e log.info("Connection seems OK.") @@ -299,7 +300,7 @@ def check_fit_md5(self, output_path): """ md5_path = output_path / "md5" try: - with open(md5_path, "r") as f: + with open(md5_path) as f: saved_md5 = f.read() except FileNotFoundError as e: log.error( @@ -431,7 +432,7 @@ def check_input(path): files = os.listdir(path) # Require that a .info file and replica 0 exist before admitting # the input is a valid LHAPDF set - info_reg, rep0_reg = map(re.compile, ('.+\.info', '.+0000\.dat')) + info_reg, rep0_reg = map(re.compile, (r'.+\.info', r'.+0000\.dat')) if 'meta.yaml' in files: return 'report' From cf5e384ae745f5f67cc73d6fff5b4f7e18b25a58 Mon Sep 17 00:00:00 2001 From: RoyStegeman Date: Wed, 26 Jun 2024 10:58:31 +0100 Subject: [PATCH 67/98] replace deprecated scipy.integrate.simps with simpson --- validphys2/src/validphys/arclength.py | 5 +++-- 1 file changed, 3 insertions(+), 2 deletions(-) diff --git a/validphys2/src/validphys/arclength.py b/validphys2/src/validphys/arclength.py index 88169ae77b..48258f52d3 100644 --- a/validphys2/src/validphys/arclength.py +++ b/validphys2/src/validphys/arclength.py @@ -3,6 +3,7 @@ Module for the computation and presentation of arclengths. """ + from collections import namedtuple from collections.abc import Sequence import numbers @@ -78,7 +79,7 @@ def arc_lengths( # PDFs evaluated on grid, use the entire thing, the Stats class will chose later xfgrid = xplotting_grid(pdf, Q, ixgrid, basis, flavours).grid_values.data * ixgrid[1] fdiff = np.diff(xfgrid) / eps # Compute forward differences - res += integrate.simps(np.sqrt(1 + np.square(fdiff)), ixgrid[1][1:]) + res += integrate.simpson(np.sqrt(1 + np.square(fdiff)), x=ixgrid[1][1:]) stats = pdf.stats_class(res) return ArcLengthGrid(pdf, basis, flavours, stats) @@ -150,7 +151,7 @@ def integrability_number( basis: (str, Basis) = "evolution", flavours: (list, tuple, type(None)) = None, ): - """Return \sum_i |x_i*f(x_i)|, x_i = {1e-9, 1e-8, 1e-7} + r"""Return \sum_i |x_i*f(x_i)|, x_i = {1e-9, 1e-8, 1e-7} for selected flavours """ checked = check_basis(basis, flavours) From 40ccac54ffa85d477943c49de6182abaad23d13d Mon Sep 17 00:00:00 2001 From: RoyStegeman Date: Mon, 24 Jun 2024 15:58:55 +0100 Subject: [PATCH 68/98] add POS_DIS process instead of POS_F2 --- .../NNPDF_POS_2P24GEV/metadata.yaml | 18 +++++++++--------- validphys2/src/validphys/process_options.py | 6 +++--- 2 files changed, 12 insertions(+), 12 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml index d9dffbdaa0..b135bc2715 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml @@ -56,7 +56,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' units: '' - process_type: POS_F2 + process_type: POS_DIS tables: [] npoints: [] ndata: 20 @@ -91,7 +91,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c$ structure function $F_2^{W^-,c}$' units: '' - process_type: POS_F2 + process_type: POS_DIS tables: [] npoints: [] ndata: 17 @@ -126,7 +126,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $d+\bar{d}$ structure function $F_2^d$' units: '' - process_type: POS_F2 + process_type: POS_DIS tables: [] npoints: [] ndata: 20 @@ -161,7 +161,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $s+\bar{s}$ structure function $F_2^s$' units: '' - process_type: POS_F2 + process_type: POS_DIS tables: [] npoints: [] ndata: 20 @@ -196,7 +196,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS light quark longitudinal structure function $F_L^l$' units: '' - process_type: POS_FLL + process_type: POS_DIS tables: [] npoints: [] ndata: 20 @@ -454,7 +454,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $c+\bar{c}$ structure function $F_2^c$' units: '' - process_type: POS_F2 + process_type: POS_DIS tables: [] npoints: [] ndata: 17 @@ -489,7 +489,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: CC DIS $\bar{c}$ structure function $F_2^{W^+,c}$' units: '' - process_type: POS_F2 + process_type: POS_DIS tables: [] npoints: [] ndata: 17 @@ -524,7 +524,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS $u+\bar{u}$ structure function $F_2^u$' units: '' - process_type: POS_F2 + process_type: POS_DIS tables: [] npoints: [] ndata: 20 @@ -559,7 +559,7 @@ implemented_observables: description: Deep Inelastic Scattering label: 'positivity dataset: DIS light quark longitudinal structure function $F_L^l$' units: '' - process_type: POS_FLL + process_type: POS_DIS tables: [] npoints: [] ndata: 19 diff --git a/validphys2/src/validphys/process_options.py b/validphys2/src/validphys/process_options.py index 059ddcd28e..15460d1993 100644 --- a/validphys2/src/validphys/process_options.py +++ b/validphys2/src/validphys/process_options.py @@ -180,7 +180,7 @@ def _hqp_ptq_xq2map(kin_info): def _hqp_mqq_xq2map(kin_info): # Compute x, Q2 # - # Theory predictions computed with HT/4 ~ m_ttbar/4 + # Theory predictions computed with HT/4 ~ m_ttbar/4 Q = kin_info[_Vars.m_ttBar] / 4 return Q / kin_info[_Vars.sqrts], Q * Q @@ -310,7 +310,7 @@ def _dybosonpt_xq2map(kin_dict): POS_XPDF = _Process("POS_XPDF", "Positivity of MS bar PDFs", accepted_variables=(_Vars.x, _Vars.Q2)) -POS_F2 = _Process("POS_F2", "Positivity of F2 structure functions", accepted_variables=(_Vars.x, _Vars.Q2)) +POS_DIS = _Process("POS_DIS", "Positivity of F2 structure functions", accepted_variables=(_Vars.x, _Vars.Q2)) PROCESSES = { "DIS": DIS, @@ -331,7 +331,7 @@ def _dybosonpt_xq2map(kin_dict): "DY_W_ETA": dataclasses.replace(DY_2L, name="DY_W_ETA", description="DY W -> l nu (pseudo)rapidity"), "DY_NC_PT": dataclasses.replace(DY_PT, name="DY_NC_PT", description="DY Z (ll) + j"), "POS_XPDF": POS_XPDF, - "POS_F2": POS_F2, + "POS_DIS": POS_DIS, } From a2e31221e4d5586d5144b61965a30a9d8f1f4886 Mon Sep 17 00:00:00 2001 From: RoyStegeman Date: Mon, 24 Jun 2024 15:59:38 +0100 Subject: [PATCH 69/98] pre-commit --- validphys2/src/validphys/process_options.py | 22 +++++++++++++++------ 1 file changed, 16 insertions(+), 6 deletions(-) diff --git a/validphys2/src/validphys/process_options.py b/validphys2/src/validphys/process_options.py index 15460d1993..eed200002a 100644 --- a/validphys2/src/validphys/process_options.py +++ b/validphys2/src/validphys/process_options.py @@ -5,7 +5,7 @@ """ import dataclasses -from typing import Callable, Optional, Tuple, Union +from typing import Callable, Optional, Union import numpy as np from validobj.custom import Parser @@ -71,7 +71,7 @@ def __getitem__(self, key): class _Process: name: str description: str - accepted_variables: Tuple[str] + accepted_variables: tuple[str] xq2map_function: Optional[Callable] = None def __hash__(self): @@ -206,7 +206,6 @@ def _displusjet_xq2map(kin_info): return x, q2 - def _dyboson_xq2map(kin_info): """ Computes x and q2 mapping for pseudo rapidity observables @@ -259,7 +258,14 @@ def _dybosonpt_xq2map(kin_dict): HQP_YQ = _Process( "HQP_YQ", "(absolute) rapidity of top quark in top pair production", - accepted_variables=(_Vars.y_t, _Vars.y_ttBar, _Vars.m_t2, _Vars.sqrts, _Vars.m_ttBar, _Vars.pT_t), + accepted_variables=( + _Vars.y_t, + _Vars.y_ttBar, + _Vars.m_t2, + _Vars.sqrts, + _Vars.m_ttBar, + _Vars.pT_t, + ), xq2map_function=_hqp_yq_xq2map, ) @@ -310,7 +316,9 @@ def _dybosonpt_xq2map(kin_dict): POS_XPDF = _Process("POS_XPDF", "Positivity of MS bar PDFs", accepted_variables=(_Vars.x, _Vars.Q2)) -POS_DIS = _Process("POS_DIS", "Positivity of F2 structure functions", accepted_variables=(_Vars.x, _Vars.Q2)) +POS_DIS = _Process( + "POS_DIS", "Positivity of F2 structure functions", accepted_variables=(_Vars.x, _Vars.Q2) +) PROCESSES = { "DIS": DIS, @@ -328,7 +336,9 @@ def _dybosonpt_xq2map(kin_dict): "HERAJET": HERAJET, "HERADIJET": dataclasses.replace(HERAJET, name="HERADIJET", description="DIS + jj production"), "DY_Z_Y": dataclasses.replace(DY_2L, name="DY_Z_Y", description="DY Z -> ll (pseudo)rapidity"), - "DY_W_ETA": dataclasses.replace(DY_2L, name="DY_W_ETA", description="DY W -> l nu (pseudo)rapidity"), + "DY_W_ETA": dataclasses.replace( + DY_2L, name="DY_W_ETA", description="DY W -> l nu (pseudo)rapidity" + ), "DY_NC_PT": dataclasses.replace(DY_PT, name="DY_NC_PT", description="DY Z (ll) + j"), "POS_XPDF": POS_XPDF, "POS_DIS": POS_DIS, From 7b1cb494fe3665ece86628c966704f7f8eecd170 Mon Sep 17 00:00:00 2001 From: RoyStegeman Date: Wed, 26 Jun 2024 13:47:48 +0100 Subject: [PATCH 70/98] update k1,k2,k3 to x,Q2 in POS_DIS kinematics metadata --- .../NNPDF_POS_2P24GEV/metadata.yaml | 42 +++++++------------ 1 file changed, 16 insertions(+), 26 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml index b135bc2715..ef5971153c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/metadata.yaml @@ -207,22 +207,17 @@ implemented_observables: $F_L^l$' plot_x: k1 kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_FLL.yaml theory: @@ -570,22 +565,17 @@ implemented_observables: $F_L^l$' plot_x: k1 kinematic_coverage: - - k1 - - k2 - - k3 + - x + - Q2 kinematics: variables: - k1: - description: Variable k1 - label: k1 - units: '' - k2: - description: Variable k2 - label: k2 + x: + description: Bjorken x + label: x units: '' - k3: - description: Variable k3 - label: k3 + Q2: + description: Factorization scale + label: Q2 units: '' file: kinematics_FLL-19PTS.yaml theory: From 598bca0ca0157effd99ee1019b6d2943c0f435b2 Mon Sep 17 00:00:00 2001 From: RoyStegeman Date: Wed, 26 Jun 2024 14:23:06 +0100 Subject: [PATCH 71/98] replace k1,k2,k3 with x,Q2 in kinematics files for POS_FLL --- .../kinematics_FLL-19PTS.yaml | 152 +++++------------ .../NNPDF_POS_2P24GEV/kinematics_FLL.yaml | 160 +++++------------- 2 files changed, 78 insertions(+), 234 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL-19PTS.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL-19PTS.yaml index 9f78a90ce2..fe53ed59c0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL-19PTS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL-19PTS.yaml @@ -1,229 +1,153 @@ bins: -- k1: +- x: min: null mid: 1.940766723678e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 7.533150951473e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 2.924017738213e-05 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0001134967265154 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0004405413401349 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.001709975946677 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.006637328831201 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.02576301385941 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.1 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.18 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.26 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.34 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.42 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.5 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.58 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.66 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.74 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.82 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.9 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL.yaml index 26edc37705..24b058bef1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_POS_2P24GEV/kinematics_FLL.yaml @@ -1,241 +1,161 @@ bins: -- k1: +- x: min: null mid: 5.0e-07 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 1.940766723678e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 7.533150951473e-06 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 2.924017738213e-05 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0001134967265154 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.0004405413401349 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.001709975946677 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.006637328831201 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.02576301385941 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.1 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.18 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.26 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.34 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.42 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.5 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.58 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.66 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.74 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.82 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null -- k1: +- x: min: null mid: 0.9 max: null - k2: + Q2: min: null mid: 5.0 max: null - k3: - min: null - mid: 0.0 - max: null From c3877dfefb993ee52321453fda64f32e74a950e7 Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Fri, 28 Jun 2024 14:30:12 +0200 Subject: [PATCH 72/98] account for pol/unpol distinction in dijets --- .../metadata.yaml | 6 +- .../STAR_2012_2JET_510GEV/metadata.yaml | 77 +++++++++++++++---- .../STAR_2013_2JET_510GEV/metadata.yaml | 76 ++++++++++++++---- .../metadata.yaml | 38 +++++++-- 4 files changed, 154 insertions(+), 43 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml index 850913615d..ce49c1f6e3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -48,7 +48,8 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_MIDRAP_200GEV_OS-ALL + - - STAR_2009_2JET_MIDRAP_200GEV_OS-ALL-POL + - - STAR_2009_2JET_MIDRAP_200GEV_OS-ALL-UNPOL - observable: { description: "ALL as function of $M_{inv}$, SS", @@ -81,4 +82,5 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_MIDRAP_200GEV_SS-ALL + - - STAR_2009_2JET_MIDRAP_200GEV_SS-ALL-POL + - - STAR_2009_2JET_MIDRAP_200GEV_SS-ALL-UNPOL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml index ad29bd355b..b9ed51871a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml @@ -12,20 +12,29 @@ hepdata: url: "https://www.hepdata.net/record/ins1738738" version: 1 - version: 1 version_comment: "Initial implementation, correlations from arXiv" implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } + - observable: + { + description: "ALL as function of $M_{inv}$, topology A", + label: "$A_{LL}$", + units: "", + } observable_name: A-ALL process_type: DIJET_POL ndata: 10 tables: [14] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_A.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_A.yaml @@ -39,16 +48,27 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_A-ALL - - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } + - - STAR_2012_2JET_510GEV_A-ALL-POL + - - STAR_2012_2JET_510GEV_A-ALL-UNPOL + - observable: + { + description: "ALL as function of $M_{inv}$, topology B", + label: "$A_{LL}$", + units: "", + } observable_name: B-ALL process_type: DIJET_POL ndata: 11 tables: [14] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_B.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_B.yaml @@ -62,16 +82,27 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_B-ALL - - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } + - - STAR_2012_2JET_510GEV_B-ALL-POL + - - STAR_2012_2JET_510GEV_B-ALL-UNPOL + - observable: + { + description: "ALL as function of $M_{inv}$, topology C", + label: "$A_{LL}$", + units: "", + } observable_name: C-ALL process_type: DIJET_POL ndata: 10 tables: [14] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_C.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_C.yaml @@ -85,16 +116,27 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_C-ALL - - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } + - - STAR_2012_2JET_510GEV_C-ALL-POL + - - STAR_2012_2JET_510GEV_C-ALL-UNPOL + - observable: + { + description: "ALL as function of $M_{inv}$, topology D", + label: "$A_{LL}$", + units: "", + } observable_name: D-ALL process_type: DIJET_POL ndata: 11 tables: [14] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_D.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_D.yaml @@ -108,4 +150,5 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2012_2JET_510GEV_D-ALL \ No newline at end of file + - - STAR_2012_2JET_510GEV_D-ALL-POL + - - STAR_2012_2JET_510GEV_D-ALL-UNPOL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml index ecbbee323b..03b62b444e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml @@ -16,15 +16,25 @@ version: 1 version_comment: "Initial implementation" implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, topology A", label: "$A_{LL}$", units: "" } + - observable: + { + description: "ALL as function of $M_{inv}$, topology A", + label: "$A_{LL}$", + units: "", + } observable_name: A-ALL process_type: DIJET_POL ndata: 12 tables: [5] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_A.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_A.yaml @@ -38,16 +48,27 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_A-ALL - - observable: { description: "ALL as function of $M_{inv}$, topology B", label: "$A_{LL}$", units: "" } + - - STAR_2013_2JET_510GEV_A-ALL-POL + - - STAR_2013_2JET_510GEV_A-ALL-UNPOL + - observable: + { + description: "ALL as function of $M_{inv}$, topology B", + label: "$A_{LL}$", + units: "", + } observable_name: B-ALL process_type: DIJET_POL ndata: 13 tables: [5] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_B.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_B.yaml @@ -61,16 +82,27 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_B-ALL - - observable: { description: "ALL as function of $M_{inv}$, topology C", label: "$A_{LL}$", units: "" } + - - STAR_2013_2JET_510GEV_B-ALL-POL + - - STAR_2013_2JET_510GEV_B-ALL-UNPOL + - observable: + { + description: "ALL as function of $M_{inv}$, topology C", + label: "$A_{LL}$", + units: "", + } observable_name: C-ALL process_type: DIJET_POL ndata: 12 tables: [5] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_C.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_C.yaml @@ -84,16 +116,27 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_C-ALL - - observable: { description: "ALL as function of $M_{inv}$, topology D", label: "$A_{LL}$", units: "" } + - - STAR_2013_2JET_510GEV_C-ALL-POL + - - STAR_2013_2JET_510GEV_C-ALL-UNPOL + - observable: + { + description: "ALL as function of $M_{inv}$, topology D", + label: "$A_{LL}$", + units: "", + } observable_name: D-ALL process_type: DIJET_POL ndata: 12 tables: [5] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_D.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_D.yaml @@ -107,4 +150,5 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2013_2JET_510GEV_D-ALL \ No newline at end of file + - - STAR_2013_2JET_510GEV_D-ALL-POL + - - STAR_2013_2JET_510GEV_D-ALL-UNPOL diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index aa0caa4ff9..b2970ade34 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -16,15 +16,25 @@ version: 1 version_comment: "Initial implementation" implemented_observables: - - observable: { description: "ALL as function of $M_{inv}$, opposite sign $\eta$ topology", label: "$A_{LL}$", units: "" } + - observable: + { + description: "ALL as function of $M_{inv}$, opposite sign $\eta$ topology", + label: "$A_{LL}$", + units: "", + } observable_name: OS-ALL process_type: DIJET_POL ndata: 7 tables: [2] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_OS.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_OS.yaml @@ -38,16 +48,27 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_510GEV_OS-ALL - - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", label: "$A_{LL}$", units: "" } + - - STAR_2015_2JET_MIDRAP_510GEV_OS-ALL-POL + - - STAR_2015_2JET_MIDRAP_510GEV_OS-ALL-UNPOL + - observable: + { + description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", + label: "$A_{LL}$", + units: "", + } observable_name: SS-ALL process_type: DIJET_POL ndata: 7 tables: [2] kinematics: variables: - m_jj: {description: "dijet mass", label: "$m_{jj}$", units: "GeV"} - sqrts: {description: "center of mass energy", label: r"$\sqrt(s)$", units: "GeV"} + m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } + sqrts: + { + description: "center of mass energy", + label: r"$\sqrt(s)$", + units: "GeV", + } file: kinematics_SS.yaml kinematic_coverage: [m_jj, sqrts] data_central: data_SS.yaml @@ -61,4 +82,5 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_510GEV_SS-ALL \ No newline at end of file + - - STAR_2015_2JET_MIDRAP_510GEV_SS-ALL-POL + - - STAR_2015_2JET_MIDRAP_510GEV_SS-ALL-UNPOL From 80b9fbb125868142a85182fc61409392674cc9ca Mon Sep 17 00:00:00 2001 From: toonhasenack Date: Fri, 28 Jun 2024 16:00:50 +0200 Subject: [PATCH 73/98] 510-->200 --- .../STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index b2970ade34..ea159cfc4c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -48,8 +48,8 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_510GEV_OS-ALL-POL - - - STAR_2015_2JET_MIDRAP_510GEV_OS-ALL-UNPOL + - - STAR_2015_2JET_MIDRAP_200GEV_OS-ALL-POL + - - STAR_2015_2JET_MIDRAP_200GEV_OS-ALL-UNPOL - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", @@ -82,5 +82,5 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2015_2JET_MIDRAP_510GEV_SS-ALL-POL - - - STAR_2015_2JET_MIDRAP_510GEV_SS-ALL-UNPOL + - - STAR_2015_2JET_MIDRAP_200GEV_SS-ALL-POL + - - STAR_2015_2JET_MIDRAP_200GEV_SS-ALL-UNPOL From 71865efb2a005b3d96db9018de38ea75cdbd9e70 Mon Sep 17 00:00:00 2001 From: RoyStegeman Date: Thu, 27 Jun 2024 16:57:32 +0100 Subject: [PATCH 74/98] add pos cuts through added_filter_rules instead of independent dataset --- n3fit/runcards/examples/nnpdf40-like.yml | 17 +++++++++++++---- 1 file changed, 13 insertions(+), 4 deletions(-) diff --git a/n3fit/runcards/examples/nnpdf40-like.yml b/n3fit/runcards/examples/nnpdf40-like.yml index f1d1ed1d91..dd6a52b5ec 100644 --- a/n3fit/runcards/examples/nnpdf40-like.yml +++ b/n3fit/runcards/examples/nnpdf40-like.yml @@ -148,15 +148,17 @@ fitting: ################################################################################ positivity: posdatasets: - - {dataset: NNPDF_POS_2P24GEV_F2U, maxlambda: 1e6} # Positivity Lagrange Multiplier + # Positivity Lagrange Multiplier + - {dataset: NNPDF_POS_2P24GEV_F2U, maxlambda: 1e6} - {dataset: NNPDF_POS_2P24GEV_F2D, maxlambda: 1e6} - {dataset: NNPDF_POS_2P24GEV_F2S, maxlambda: 1e6} - - {dataset: NNPDF_POS_2P24GEV_FLL-19PTS, maxlambda: 1e6} + - {dataset: NNPDF_POS_2P24GEV_FLL, maxlambda: 1e6} - {dataset: NNPDF_POS_2P24GEV_DYU, maxlambda: 1e10} - {dataset: NNPDF_POS_2P24GEV_DYD, maxlambda: 1e10} - {dataset: NNPDF_POS_2P24GEV_DYS, maxlambda: 1e10} - - {dataset: NNPDF_POS_2P24GEV_F2C-17PTS, maxlambda: 1e6} - - {dataset: NNPDF_POS_2P24GEV_XUQ, maxlambda: 1e6} # Positivity of MSbar PDFs + - {dataset: NNPDF_POS_2P24GEV_F2C, maxlambda: 1e6} + # Positivity of MSbar PDFs + - {dataset: NNPDF_POS_2P24GEV_XUQ, maxlambda: 1e6} - {dataset: NNPDF_POS_2P24GEV_XUB, maxlambda: 1e6} - {dataset: NNPDF_POS_2P24GEV_XDQ, maxlambda: 1e6} - {dataset: NNPDF_POS_2P24GEV_XDB, maxlambda: 1e6} @@ -164,6 +166,13 @@ positivity: - {dataset: NNPDF_POS_2P24GEV_XSB, maxlambda: 1e6} - {dataset: NNPDF_POS_2P24GEV_XGL, maxlambda: 1e6} +added_filter_rules: + - dataset: NNPDF_POS_2P24GEV_FLL + rule: "x > 5.0e-7" + + - dataset: NNPDF_POS_2P24GEV_F2C + rule: "x < 0.74" + integrability: integdatasets: - {dataset: NNPDF_INTEG_3GEV_XT8, maxlambda: 1e2} From 75a7c2693f74474fdbcbe0c85b607963b46b4a03 Mon Sep 17 00:00:00 2001 From: RoyStegeman Date: Mon, 1 Jul 2024 11:24:40 +0100 Subject: [PATCH 75/98] cut small-x xPDF pos points from example card --- n3fit/runcards/examples/nnpdf40-like.yml | 15 ++++++++++++++- 1 file changed, 14 insertions(+), 1 deletion(-) diff --git a/n3fit/runcards/examples/nnpdf40-like.yml b/n3fit/runcards/examples/nnpdf40-like.yml index dd6a52b5ec..1908b56442 100644 --- a/n3fit/runcards/examples/nnpdf40-like.yml +++ b/n3fit/runcards/examples/nnpdf40-like.yml @@ -169,9 +169,22 @@ positivity: added_filter_rules: - dataset: NNPDF_POS_2P24GEV_FLL rule: "x > 5.0e-7" - - dataset: NNPDF_POS_2P24GEV_F2C rule: "x < 0.74" + - dataset: NNPDF_POS_2P24GEV_XGL + rule: "x > 0.1" + - dataset: NNPDF_POS_2P24GEV_XUQ + rule: "x > 0.1" + - dataset: NNPDF_POS_2P24GEV_XUB + rule: "x > 0.1" + - dataset: NNPDF_POS_2P24GEV_XDQ + rule: "x > 0.1" + - dataset: NNPDF_POS_2P24GEV_XDB + rule: "x > 0.1" + - dataset: NNPDF_POS_2P24GEV_XSQ + rule: "x > 0.1" + - dataset: NNPDF_POS_2P24GEV_XSB + rule: "x > 0.1" integrability: integdatasets: From 769a26bfac9b332779c5e1ebeaf7d0391db9fcde Mon Sep 17 00:00:00 2001 From: Roy Stegeman Date: Tue, 2 Jul 2024 13:19:38 +0100 Subject: [PATCH 76/98] iterate nnpdf40-like.yml --- n3fit/runcards/examples/nnpdf40-like.yml | 20 ++++++++++---------- 1 file changed, 10 insertions(+), 10 deletions(-) diff --git a/n3fit/runcards/examples/nnpdf40-like.yml b/n3fit/runcards/examples/nnpdf40-like.yml index 1908b56442..160e10e631 100644 --- a/n3fit/runcards/examples/nnpdf40-like.yml +++ b/n3fit/runcards/examples/nnpdf40-like.yml @@ -2,7 +2,7 @@ # Configuration file for n3fit # ################################################################################ -description: NNPDF4.0 NNLO baseline fit (nFONLL). Comparable to NNPDF40_nnlo_as_01180_qcd +description: NNLO baseline fit, NNPDF4.0 dataset ################################################################################ dataset_inputs: @@ -91,7 +91,7 @@ dataset_inputs: ################################################################################ datacuts: - t0pdfset: NNPDF40_nnlo_as_01180 + t0pdfset: 240701-02-rs-nnpdf40-baseline q2min: 3.49 w2min: 12.5 @@ -136,14 +136,14 @@ fitting: fitbasis: EVOL savepseudodata: True basis: - - {fl: sng, trainable: false, smallx: [1.091, 1.119], largex: [1.471, 3.021]} - - {fl: g, trainable: false, smallx: [0.7795, 1.095], largex: [2.742, 5.547]} - - {fl: v, trainable: false, smallx: [0.472, 0.7576], largex: [1.571, 3.559]} - - {fl: v3, trainable: false, smallx: [0.07483, 0.4501], largex: [1.714, 3.467]} - - {fl: v8, trainable: false, smallx: [0.5731, 0.779], largex: [1.555, 3.465]} - - {fl: t3, trainable: false, smallx: [-0.5498, 1.0], largex: [1.778, 3.5]} - - {fl: t8, trainable: false, smallx: [0.5469, 0.857], largex: [1.555, 3.391]} - - {fl: t15, trainable: false, smallx: [1.081, 1.142], largex: [1.491, 3.092]} + - {fl: sng, trainable: false, smallx: [1.089, 1.119], largex: [1.475, 3.119]} + - {fl: g, trainable: false, smallx: [0.7504, 1.098], largex: [2.814, 5.669]} + - {fl: v, trainable: false, smallx: [0.479, 0.7384], largex: [1.549, 3.532]} + - {fl: v3, trainable: false, smallx: [0.1073, 0.4397], largex: [1.733, 3.458]} + - {fl: v8, trainable: false, smallx: [0.5507, 0.7837], largex: [1.516, 3.356]} + - {fl: t3, trainable: false, smallx: [-0.4506, 0.9305], largex: [1.745, 3.424]} + - {fl: t8, trainable: false, smallx: [0.5877, 0.8687], largex: [1.522, 3.515]} + - {fl: t15, trainable: false, smallx: [1.089, 1.141], largex: [1.492, 3.222]} ################################################################################ positivity: From a516d7a1bfba5c27fe94f93d52a1cbb0ffbe52cf Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 3 Jul 2024 09:35:14 +0200 Subject: [PATCH 77/98] implement E. Aschenauer suggestion --- .../STAR_2009_1JET_200GEV/filter.py | 3 +- .../STAR_2012_1JET_510GEV/filter.py | 23 +- .../STAR_2012_1JET_510GEV/uncertainties.yaml | 1568 +++++++------- .../uncertainties_A.yaml | 1266 ++++++------ .../uncertainties_B.yaml | 1381 +++++++------ .../uncertainties_C.yaml | 1266 ++++++------ .../uncertainties_D.yaml | 1381 +++++++------ .../STAR_2013_1JET_510GEV/filter.py | 23 +- .../STAR_2013_1JET_510GEV/uncertainties.yaml | 1764 ++++++++-------- .../uncertainties_A.yaml | 1678 ++++++++------- .../uncertainties_B.yaml | 1807 ++++++++--------- .../uncertainties_C.yaml | 1678 ++++++++------- .../uncertainties_D.yaml | 1678 ++++++++------- .../STAR_2015_1JET_200GEV/filter.py | 30 +- .../uncertainties_CC.yaml | 792 ++++---- .../uncertainties_CF.yaml | 792 ++++---- .../uncertainties_OS.yaml | 601 +++--- .../uncertainties_SS.yaml | 601 +++--- 18 files changed, 9080 insertions(+), 9252 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index 38fa615406..8fb1f5345a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -288,7 +288,8 @@ def write_2jet_data(df, topology, art_sys): ) # from the supplement material: # https://journals.aps.org/prd/supplemental/10.1103/PhysRevD.98.032011/Supplementalmaterial.pdf - # we understand that stat jet and dijet are correlated + # we understand that stat jet and dijet are correlated, + # see also https://github.com/NNPDF/nnpdf/pull/2035#issuecomment-2201979662 correlated_unc = [] for a in TOPOPLOGY_LIST: correlated_unc.extend( diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py index 16061682f8..e03571dedc 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py @@ -214,11 +214,6 @@ def write_2jet_data(df, topology, art_sys): # Write unc file error = [] error_definition = { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - }, "lumi_ue": { "description": "underlying event and relative luminosity uncertainty", "treatment": "ADD", @@ -233,7 +228,6 @@ def write_2jet_data(df, topology, art_sys): # loop on data points for i, sys_i in enumerate(art_sys): e = { - "stat": float(df.loc[i, "stat"]), "lumi_ue": float(df.loc[i, "lumi_ue"]), "pol": float(df.loc[i, "pol"]), } @@ -246,7 +240,7 @@ def write_2jet_data(df, topology, art_sys): error_definition.update( { f"sys_{j}": { - "description": f"{j} artificial correlated systematics uncertainty", + "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", "type": f"STAR{YEAR}JETunc{j}", } @@ -270,14 +264,13 @@ def write_2jet_data(df, topology, art_sys): # load correlations ndata_dict = {a: len(b) for a, b in dfs.items()} correlation_df = read_correlations(ndata_dict) - # from the paper we understand that stat dijet is not correlated - # I-I (stat + sys) | I-D (stat + sys) - # D-I (stat + sys) | D-D (sys) - correlated_unc = np.sqrt( - dfs["I"]["syst"] ** 2 + dfs["I"]["stat"] ** 2 - ).values.tolist() - for a in TOPOPLOGY_LIST[1:]: - correlated_unc.extend(dfs[a]["syst"].values) + # sum stat and syst for both jet and dijets as recommended + # by E.Aschenauer, see https://github.com/NNPDF/nnpdf/pull/2035#issuecomment-2201979662 + correlated_unc = [] + for a in TOPOPLOGY_LIST: + correlated_unc.extend( + np.sqrt(dfs[a]["syst"] ** 2 + dfs[a]["stat"] ** 2).values.tolist() + ) ndata_points = np.sum((*ndata_dict.values(),)) # decompose uncertainties art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml index e8b010c7e7..bde5d73776 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/uncertainties.yaml @@ -234,813 +234,813 @@ definitions: bins: - lumi_ue: 0.000364 pol: 1.1285999999999999e-06 - sys_0: -8.307118087449961e-06 - sys_1: -1.923606975816457e-05 - sys_2: -2.7493288657714626e-05 - sys_3: -9.197046126805024e-06 - sys_4: -1.9676681454977926e-05 - sys_5: -1.7898280334048527e-05 - sys_6: -2.88199505107653e-05 - sys_7: 6.785010539251133e-06 - sys_8: 1.748689814956224e-05 - sys_9: -1.4440769025165626e-05 - sys_10: 4.33726375037121e-05 - sys_11: 6.187839493929042e-06 - sys_12: -3.320762550943015e-05 - sys_13: 7.68573157775859e-05 - sys_14: 5.4133132866737156e-05 - sys_15: -0.00017189096919798216 - sys_16: 1.2223399030256558e-05 - sys_17: 0.000344945788485751 - sys_18: 1.6755545305731354e-05 - sys_19: 1.6153776732296275e-05 - sys_20: 0.0010969169650801528 - sys_21: 0.0001371582737296083 - sys_22: 0.0005936320162272282 - sys_23: -5.529932439582105e-06 - sys_24: 0.00012462056765152226 - sys_25: -1.8940872412003985e-06 - sys_26: -1.1689271572807888e-05 - sys_27: -7.167698501070261e-05 - sys_28: 7.338187610003712e-06 - sys_29: -3.383872935466266e-06 - sys_30: 7.300731607728807e-07 - sys_31: -3.6336142151568466e-06 - sys_32: 2.0011710786003518e-07 - sys_33: -1.5315816375251268e-06 - sys_34: 5.28887677104233e-07 - sys_35: -3.223051865125062e-07 - sys_36: -9.72174487914799e-07 - sys_37: 4.395093640361111e-07 - sys_38: -4.41107750833724e-08 - sys_39: 2.4034517933802395e-08 - sys_40: -4.422257459408995e-07 - sys_41: -2.047345571773379e-07 - sys_42: -8.758373205138124e-08 - sys_43: -1.4367957854733877e-07 - sys_44: 3.366414466389085e-08 - sys_45: 7.415754618423778e-09 - sys_46: 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_A.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR lumi_ue: description: underlying event and relative luminosity uncertainty treatment: ADD @@ -12,817 +8,807 @@ definitions: treatment: MULT type: STAR2012POL sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc54 sys_55: - description: 55 artificial correlated systematics uncertainty + description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc55 bins: -- stat: 0.0066 - lumi_ue: 0.00025 +- lumi_ue: 0.00025 pol: 0.0008448 - sys_0: -2.805509704053412e-07 - sys_1: 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sys_31: 5.0203583153153494e-06 + sys_32: -2.3421783741994973e-05 + sys_33: -9.025178934615913e-06 + sys_34: 4.2335792137158006e-05 + sys_35: 8.289782073710602e-05 + sys_36: 9.744460777358795e-06 + sys_37: 3.6232481611322447e-06 + sys_38: -2.418408063129908e-05 + sys_39: 7.355571483698593e-05 + sys_40: -5.239095749914436e-06 + sys_41: 4.34537298705802e-05 + sys_42: -2.8262819553516286e-06 + sys_43: 1.1214076775988322e-05 + sys_44: 6.044502073620967e-06 + sys_45: 1.3205074553314394e-05 + sys_46: 6.682743656005294e-06 + sys_47: 2.301466092029081e-06 + sys_48: -1.6933593116356689e-06 + sys_49: 5.908634843708989e-06 + sys_50: 4.719193782923559e-07 + sys_51: -1.987798644157024e-06 + sys_52: 4.5521097068499716e-05 + sys_53: 0.00011224136455724005 + sys_54: 5.451735887218823e-05 + sys_55: -1.2886999446169458e-06 +- lumi_ue: 0.00031 pol: 0.0014388 - sys_0: -0.00037960228302466 - sys_1: -0.0008299122305492342 - sys_2: -6.834069276424717e-05 - sys_3: -0.002023099603413346 - sys_4: 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5.642091881810538e-05 + sys_40: -3.18085093238913e-06 + sys_41: 2.21849379780013e-05 + sys_42: 1.280307130991647e-06 + sys_43: 9.696158481974046e-06 + sys_44: 6.828633656818436e-06 + sys_45: 9.621909518221789e-06 + sys_46: 8.211077321872226e-06 + sys_47: 4.522588630807568e-06 + sys_48: -2.4338542460818716e-06 + sys_49: 2.5614497431731453e-06 + sys_50: -2.851921557332187e-07 + sys_51: 3.462668505870031e-07 + sys_52: 3.3948045387218256e-05 + sys_53: 0.00010743765255831472 + sys_54: 5.040516348405297e-05 + sys_55: -2.3407043539685785e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_B.yaml index 4237b0b490..0f56358218 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_B.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR lumi_ue: description: underlying event and relative luminosity uncertainty treatment: ADD @@ -12,876 +8,865 @@ definitions: treatment: MULT type: STAR2012POL sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc54 sys_55: - description: 55 artificial correlated systematics uncertainty + description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc55 bins: -- stat: 0.0053 - lumi_ue: 0.0004 +- lumi_ue: 0.0004 pol: 0.0001518 - sys_0: -4.902699695448577e-07 - sys_1: -9.667668405608368e-07 - sys_2: -1.5946010176743127e-06 - sys_3: -3.046550955055064e-07 - sys_4: -1.2640171400176975e-06 - sys_5: -6.928951928115611e-07 - 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2.6783883136333852e-05 + sys_53: 8.862616698716669e-05 + sys_54: 4.2062318472610274e-05 + sys_55: 1.615685814096234e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_C.yaml index a776bb33c5..7d41c7e4a7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_C.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR lumi_ue: description: underlying event and relative luminosity uncertainty treatment: ADD @@ -12,817 +8,807 @@ definitions: treatment: MULT type: STAR2012POL sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc54 sys_55: - description: 55 artificial correlated systematics uncertainty + description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc55 bins: -- stat: 0.0085 - lumi_ue: 0.00026 +- lumi_ue: 0.00026 pol: 0.0003828 - sys_0: -2.5482830979737217e-07 - sys_1: -5.769850292115005e-07 - sys_2: -1.1005432363669914e-06 - sys_3: -2.1294360101953275e-07 - sys_4: -7.07382830391889e-07 - sys_5: -4.415644960601962e-07 - sys_6: -6.243926684259909e-07 - sys_7: 1.270069928119173e-07 - sys_8: 4.3293345872659486e-07 - sys_9: -4.1689903309478285e-07 - sys_10: 4.7049236943574365e-07 - sys_11: 2.646114670357675e-07 - sys_12: -7.296458330855937e-07 - sys_13: 1.3828811400533153e-06 - sys_14: 4.209609174083622e-07 - sys_15: -1.9209884197366687e-06 - sys_16: 3.4681919776983286e-07 - sys_17: 5.124420657605955e-06 - sys_18: 1.1347940087052614e-07 - 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ff72eb9892..87fc6c8595 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/uncertainties_D.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR lumi_ue: description: underlying event and relative luminosity uncertainty treatment: ADD @@ -12,876 +8,865 @@ definitions: treatment: MULT type: STAR2012POL sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2012JETunc54 sys_55: - description: 55 artificial correlated systematics uncertainty + description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD type: 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4.084882989852301e-06 + sys_42: 3.0666212214045293e-07 + sys_43: 2.5713801311965486e-06 + sys_44: 9.808223463882108e-07 + sys_45: 1.284987809126998e-06 + sys_46: 1.3037533924412506e-06 + sys_47: 1.0729894999489885e-06 + sys_48: 1.947332071953631e-06 + sys_49: -2.7804275701445893e-06 + sys_50: -6.605960073625057e-07 + sys_51: 2.5895911737392207e-06 + sys_52: 1.1995123905200005e-05 + sys_53: 5.110122403018106e-05 + sys_54: 2.5550192779393124e-05 + sys_55: 6.295289324677969e-07 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py index ab62928cc2..eb4d67f8c7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py @@ -223,11 +223,6 @@ def write_2jet_data(df, topology, art_sys): # Write unc file error = [] error_definition = { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - }, "pol": { "description": "beam polarization uncertainty", "treatment": "MULT", @@ -242,7 +237,6 @@ def write_2jet_data(df, topology, art_sys): # loop on data points for i, sys_i in enumerate(art_sys): e = { - "stat": float(df.loc[i, "stat"]), "pol": float(df.loc[i, "pol"]), "lumi": float(df.loc[i, "lumi"]), } @@ -255,7 +249,7 @@ def write_2jet_data(df, topology, art_sys): error_definition.update( { f"sys_{j}": { - "description": f"{j} artificial correlated systematics uncertainty", + "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", "type": f"STAR{YEAR}JETunc{j}", } @@ -279,14 +273,13 @@ def write_2jet_data(df, topology, art_sys): # load correlations ndata_dict = {a: len(b) for a, b in dfs.items()} correlation_df = read_correlations(ndata_dict) - # from the paper we understand that stat dijet is not correlated - # I-I (stat + sys) | I-D (stat + sys) - # D-I (stat + sys) | D-D (sys) - correlated_unc = np.sqrt( - dfs["1JET"]["syst"] ** 2 + dfs["1JET"]["stat"] ** 2 - ).values.tolist() - for a in TOPOPLOGY_LIST[1:]: - correlated_unc.extend(dfs[a]["syst"].values) + # sum stat and syst for both jet and dijets as recommended + # by E.Aschenauer, see https://github.com/NNPDF/nnpdf/pull/2035#issuecomment-2201979662 + correlated_unc = [] + for a in TOPOPLOGY_LIST: + correlated_unc.extend( + np.sqrt(dfs[a]["syst"] ** 2 + dfs[a]["stat"] ** 2).values.tolist() + ) ndata_points = np.sum((*ndata_dict.values(),)) # decompose uncertainties art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml index d53f02de56..919b3d048e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/uncertainties.yaml @@ -262,911 +262,911 @@ definitions: bins: - pol: 0.00040064 lumi: 0.00047 - sys_0: -8.959677092850805e-10 - sys_1: 9.832716726753248e-09 - sys_2: 6.730954169673362e-08 - sys_3: -5.428657179727165e-07 - sys_4: 1.849151226465547e-05 - sys_5: -0.00033425279444213827 - sys_6: -0.002460403929534158 - sys_7: 1.0596623541335071e-05 - sys_8: -7.09332292192478e-06 - sys_9: -3.217314418564714e-05 - sys_10: 2.5920662962455683e-06 - sys_11: 1.4170133072198724e-05 - sys_12: 1.537393509964682e-05 - sys_13: 1.332332354554299e-05 - sys_14: 9.522602492308007e-06 - sys_15: -1.5924891360184378e-06 - sys_16: -1.8351701803258442e-05 - sys_17: 2.9743013494868743e-06 - sys_18: 2.594986914432465e-06 - sys_19: -1.280641734419468e-06 - sys_20: -4.784476270442007e-06 - sys_21: -5.189564847497854e-06 - sys_22: -2.724363769753915e-06 - sys_23: -3.3100747565082005e-06 - sys_24: 3.0073944777895753e-06 - sys_25: -4.779140471867104e-06 - 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a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_A.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT @@ -12,1047 +8,1035 @@ definitions: treatment: ADD type: STAR2013LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc54 sys_55: - description: 55 artificial correlated systematics uncertainty + description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc55 sys_56: - description: 56 artificial correlated systematics uncertainty + description: 56 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc56 sys_57: - description: 57 artificial correlated systematics uncertainty + description: 57 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc57 sys_58: - description: 58 artificial correlated systematics uncertainty + description: 58 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc58 sys_59: - description: 59 artificial correlated systematics uncertainty + description: 59 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc59 sys_60: - description: 60 artificial correlated systematics uncertainty + description: 60 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc60 sys_61: - description: 61 artificial correlated systematics uncertainty + description: 61 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc61 sys_62: - description: 62 artificial correlated systematics uncertainty + description: 62 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc62 bins: -- stat: 0.00619 - pol: 0.00035072 +- pol: 0.00035072 lumi: 0.00047 - sys_0: -1.8442665253564098e-08 - sys_1: 9.128062228545417e-08 - sys_2: 3.0998812240715233e-07 - sys_3: -8.292100410110618e-07 - sys_4: 4.1694931675558475e-06 - sys_5: -6.482800205140772e-06 - sys_6: -1.1692842322760786e-05 - sys_7: -2.188055990118648e-06 - sys_8: 2.083391360676885e-06 - sys_9: 5.909177404229857e-07 - sys_10: -2.8997469651552793e-06 - sys_11: -7.82161091633219e-06 - sys_12: 2.243074184845698e-07 - sys_13: -2.5016530549814917e-06 - sys_14: -1.3392143113036963e-05 - sys_15: 9.360375582483164e-07 - sys_16: 2.34039418446079e-05 - sys_17: -2.4844788219751617e-06 - sys_18: -1.3673114871106006e-06 - sys_19: 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6.464743605381797e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml index 57f0656990..f91b9050ba 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_B.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT @@ -12,1113 +8,1100 @@ definitions: treatment: ADD type: STAR2013LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: 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b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_C.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT @@ -12,1047 +8,1035 @@ definitions: treatment: ADD type: STAR2013LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc54 sys_55: - description: 55 artificial correlated systematics uncertainty + description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc55 sys_56: - description: 56 artificial correlated systematics uncertainty + description: 56 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc56 sys_57: - description: 57 artificial correlated systematics uncertainty + description: 57 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc57 sys_58: - description: 58 artificial correlated systematics uncertainty + description: 58 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc58 sys_59: - description: 59 artificial correlated systematics uncertainty + description: 59 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc59 sys_60: - description: 60 artificial correlated systematics uncertainty + description: 60 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc60 sys_61: - description: 61 artificial correlated systematics uncertainty + description: 61 artificial correlated statistical + systematics uncertainty treatment: ADD type: 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a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml index a56376bc19..d549887942 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/uncertainties_D.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR pol: description: beam polarization uncertainty treatment: MULT @@ -12,1047 +8,1035 @@ definitions: treatment: ADD type: STAR2013LUMI sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc35 sys_36: - description: 36 artificial correlated systematics uncertainty + description: 36 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc36 sys_37: - description: 37 artificial correlated systematics uncertainty + description: 37 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc37 sys_38: - description: 38 artificial correlated systematics uncertainty + description: 38 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc38 sys_39: - description: 39 artificial correlated systematics uncertainty + description: 39 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc39 sys_40: - description: 40 artificial correlated systematics uncertainty + description: 40 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc40 sys_41: - description: 41 artificial correlated systematics uncertainty + description: 41 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc41 sys_42: - description: 42 artificial correlated systematics uncertainty + description: 42 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc42 sys_43: - description: 43 artificial correlated systematics uncertainty + description: 43 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc43 sys_44: - description: 44 artificial correlated systematics uncertainty + description: 44 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc44 sys_45: - description: 45 artificial correlated systematics uncertainty + description: 45 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc45 sys_46: - description: 46 artificial correlated systematics uncertainty + description: 46 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc46 sys_47: - description: 47 artificial correlated systematics uncertainty + description: 47 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc47 sys_48: - description: 48 artificial correlated systematics uncertainty + description: 48 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc48 sys_49: - description: 49 artificial correlated systematics uncertainty + description: 49 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc49 sys_50: - description: 50 artificial correlated systematics uncertainty + description: 50 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc50 sys_51: - description: 51 artificial correlated systematics uncertainty + description: 51 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc51 sys_52: - description: 52 artificial correlated systematics uncertainty + description: 52 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc52 sys_53: - description: 53 artificial correlated systematics uncertainty + description: 53 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc53 sys_54: - description: 54 artificial correlated systematics uncertainty + description: 54 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc54 sys_55: - description: 55 artificial correlated systematics uncertainty + description: 55 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc55 sys_56: - description: 56 artificial correlated systematics uncertainty + description: 56 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc56 sys_57: - description: 57 artificial correlated systematics uncertainty + description: 57 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc57 sys_58: - description: 58 artificial correlated systematics uncertainty + description: 58 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc58 sys_59: - description: 59 artificial correlated systematics uncertainty + description: 59 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2013JETunc59 sys_60: - description: 60 artificial correlated systematics uncertainty + 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1.8784142519920598e-06 + sys_52: -6.10510110992285e-07 + sys_53: -1.1228199344917284e-06 + sys_54: -3.6508076465715218e-06 + sys_55: -8.270562802482827e-07 + sys_56: -3.4320316637608945e-06 + sys_57: -2.438266732148096e-06 + sys_58: -2.665392448752788e-06 + sys_59: -5.654915820305557e-07 + sys_60: 6.253765161472477e-07 + sys_61: -5.82714158106794e-07 + sys_62: 1.2561227554127553e-06 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index cca3b39e27..a7d08351d6 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -239,11 +239,6 @@ def write_2jet_data(df, topology, art_sys): # Write unc file error = [] error_definition = { - "stat": { - "description": "statistical uncertainty", - "treatment": "ADD", - "type": "UNCORR", - }, "lumi": { "description": "luminosity uncertainty", "treatment": "ADD", @@ -258,7 +253,6 @@ def write_2jet_data(df, topology, art_sys): # loop on data points for i, sys_i in enumerate(art_sys): e = { - "stat": float(df.loc[i, "stat"]), "lumi": float(df.loc[i, "lumi"]), "pol": float(df.loc[i, "pol"]), } @@ -271,7 +265,7 @@ def write_2jet_data(df, topology, art_sys): error_definition.update( { f"sys_{j}": { - "description": f"{j} artificial correlated systematics uncertainty", + "description": f"{j} artificial correlated statistical + systematics uncertainty", "treatment": "ADD", "type": f"STAR{YEAR}JETunc{j}", } @@ -296,21 +290,13 @@ def write_2jet_data(df, topology, art_sys): # load correlations ndata_dict = {a: len(b) for a, b in dfs.items()} correlation_df = read_correlations(ndata_dict) - - # from the paper we understand that stat dijet is not correlated - # I-I (stat + sys) | I-D (stat + sys) - # D-I (stat + sys) | D-D (sys) - correlated_unc = np.sqrt( - dfs["CC"]["syst"] ** 2 + dfs["CC"]["stat"] ** 2 - ).values.tolist() - correlated_unc.extend( - np.sqrt(dfs["CF"]["syst"] ** 2 + dfs["CF"]["stat"] ** 2).values.tolist() - ) - for a in (*TOPOPLOGY_LIST,)[2:]: - correlated_unc.extend(dfs[a]["syst"].values) - - # decompose uncertainties - ndata_dict = {a: len(b) for a, b in dfs.items()} + # sum stat and syst for both jet and dijets as recommended + # by E.Aschenauer, see https://github.com/NNPDF/nnpdf/pull/2035#issuecomment-2201979662 + correlated_unc = [] + for a in TOPOPLOGY_LIST: + correlated_unc.extend( + np.sqrt(dfs[a]["syst"] ** 2 + dfs[a]["stat"] ** 2).values.tolist() + ) ndata_points = np.sum((*ndata_dict.values(),)) art_sys = np.array(compute_covmat(correlation_df, correlated_unc, ndata_points)) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CC.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CC.yaml index 9746ba001b..e9f0e63bde 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/uncertainties_CC.yaml +++ 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sys_26: -2.7187395489441307e-08 + sys_27: -1.5800123345631692e-09 + sys_28: -5.97458953517806e-08 + sys_29: 9.891048794493751e-08 + sys_30: 1.216510795388191e-07 + sys_31: 6.430903620001199e-08 + sys_32: -1.8781384964506675e-07 + sys_33: 8.320391742769609e-08 + sys_34: 2.3072498123408804e-07 + sys_35: -2.8885604034905375e-08 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml index 110235f85b..9099d415c4 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_OS.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR lumi: description: luminosity uncertainty treatment: ADD @@ -12,420 +8,413 @@ definitions: treatment: MULT type: STAR2015POL sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc35 bins: -- stat: 0.004 - lumi: 0.0007 +- lumi: 0.0007 pol: 0.00040869999999999996 - sys_0: -1.1061320396018662e-06 - sys_1: 2.1718755370553993e-06 - sys_2: -2.5830445253971692e-06 - sys_3: 3.6296783741788805e-06 - sys_4: 3.5884643423664896e-06 - sys_5: 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-4.2882155736304875e-05 + sys_13: -5.62898129946584e-06 + sys_14: -4.391190605927062e-06 + sys_15: 1.3679684584656604e-05 + sys_16: -1.0929965747918132e-05 + sys_17: 3.248069246700459e-07 + sys_18: -3.6970779578645243e-06 + sys_19: -4.823180645610675e-06 + sys_20: -1.8777073287709331e-06 + sys_21: -3.058748592871662e-06 + sys_22: -1.1655689871601464e-06 + sys_23: -1.5037257067537078e-07 + sys_24: -4.02190507576274e-06 + sys_25: 1.1889694206987331e-06 + sys_26: -2.777419405467811e-08 + sys_27: 1.126440180656962e-07 + sys_28: -4.187989741644149e-08 + sys_29: -3.1900853225573806e-08 + sys_30: 7.527460311725738e-08 + sys_31: -1.3181370397918372e-07 + sys_32: -1.3089386915970926e-07 + sys_33: -2.3655852829065698e-07 + sys_34: 3.832321675464542e-07 + sys_35: 6.289476894114971e-10 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml index 35bd6533dc..69af9aac46 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/uncertainties_SS.yaml @@ -1,8 +1,4 @@ definitions: - stat: - description: statistical uncertainty - treatment: ADD - type: UNCORR lumi: description: luminosity uncertainty treatment: ADD @@ -12,420 +8,413 @@ definitions: treatment: MULT type: STAR2015POL sys_0: - description: 0 artificial correlated systematics uncertainty + description: 0 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc0 sys_1: - description: 1 artificial correlated systematics uncertainty + description: 1 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc1 sys_2: - description: 2 artificial correlated systematics uncertainty + description: 2 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc2 sys_3: - description: 3 artificial correlated systematics uncertainty + description: 3 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc3 sys_4: - description: 4 artificial correlated systematics uncertainty + description: 4 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc4 sys_5: - description: 5 artificial correlated systematics uncertainty + description: 5 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc5 sys_6: - description: 6 artificial correlated systematics uncertainty + description: 6 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc6 sys_7: - description: 7 artificial correlated systematics uncertainty + description: 7 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc7 sys_8: - description: 8 artificial correlated systematics uncertainty + description: 8 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc8 sys_9: - description: 9 artificial correlated systematics uncertainty + description: 9 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc9 sys_10: - description: 10 artificial correlated systematics uncertainty + description: 10 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc10 sys_11: - description: 11 artificial correlated systematics uncertainty + description: 11 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc11 sys_12: - description: 12 artificial correlated systematics uncertainty + description: 12 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc12 sys_13: - description: 13 artificial correlated systematics uncertainty + description: 13 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc13 sys_14: - description: 14 artificial correlated systematics uncertainty + description: 14 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc14 sys_15: - description: 15 artificial correlated systematics uncertainty + description: 15 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc15 sys_16: - description: 16 artificial correlated systematics uncertainty + description: 16 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc16 sys_17: - description: 17 artificial correlated systematics uncertainty + description: 17 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc17 sys_18: - description: 18 artificial correlated systematics uncertainty + description: 18 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc18 sys_19: - description: 19 artificial correlated systematics uncertainty + description: 19 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc19 sys_20: - description: 20 artificial correlated systematics uncertainty + description: 20 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc20 sys_21: - description: 21 artificial correlated systematics uncertainty + description: 21 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc21 sys_22: - description: 22 artificial correlated systematics uncertainty + description: 22 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc22 sys_23: - description: 23 artificial correlated systematics uncertainty + description: 23 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc23 sys_24: - description: 24 artificial correlated systematics uncertainty + description: 24 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc24 sys_25: - description: 25 artificial correlated systematics uncertainty + description: 25 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc25 sys_26: - description: 26 artificial correlated systematics uncertainty + description: 26 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc26 sys_27: - description: 27 artificial correlated systematics uncertainty + description: 27 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc27 sys_28: - description: 28 artificial correlated systematics uncertainty + description: 28 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc28 sys_29: - description: 29 artificial correlated systematics uncertainty + description: 29 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc29 sys_30: - description: 30 artificial correlated systematics uncertainty + description: 30 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc30 sys_31: - description: 31 artificial correlated systematics uncertainty + description: 31 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc31 sys_32: - description: 32 artificial correlated systematics uncertainty + description: 32 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc32 sys_33: - description: 33 artificial correlated systematics uncertainty + description: 33 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc33 sys_34: - description: 34 artificial correlated systematics uncertainty + description: 34 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc34 sys_35: - description: 35 artificial correlated systematics uncertainty + description: 35 artificial correlated statistical + systematics uncertainty treatment: ADD type: STAR2015JETunc35 bins: -- stat: 0.0036 - lumi: 0.0007 +- lumi: 0.0007 pol: 0.0004331 - sys_0: -1.993644240492427e-06 - sys_1: 3.920582178397754e-06 - sys_2: -4.666612808032058e-06 - sys_3: 6.586698567296014e-06 - sys_4: 6.5349662941488195e-06 - sys_5: -1.16515450884791e-05 - sys_6: -5.496785522473897e-06 - sys_7: 1.762865211871457e-05 - sys_8: -1.0821835182250246e-05 - sys_9: -3.891856621967208e-05 - sys_10: -3.880832371662888e-06 - sys_11: -2.1666813619539386e-05 - sys_12: 1.2134046155466599e-05 - sys_13: -3.788947274399712e-05 - sys_14: 9.343191317613612e-07 - sys_15: -3.2595563303084586e-05 - sys_16: -2.6269747717531737e-06 - sys_17: 6.884391026037052e-06 - sys_18: -2.612679198588861e-05 - sys_19: -9.659403622314088e-05 - sys_20: 6.744908859540219e-06 - sys_21: 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sys_28: -9.36392593651474e-08 + sys_29: 2.1710453159270453e-08 + sys_30: 2.0820040688300134e-07 + sys_31: 1.1228233543167254e-08 + sys_32: -3.96824653172278e-07 + sys_33: -6.644355315771639e-10 + sys_34: 2.792066496877991e-07 + sys_35: -6.980638791207585e-08 From a2941ae9d8602c229eb1d81f190e116b076a97bd Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 3 Jul 2024 10:07:26 +0200 Subject: [PATCH 78/98] implement 2004 1JET data --- .../STAR_2004_1JET_200GEV/data.yaml | 7 ++ .../STAR_2004_1JET_200GEV/filter.py | 93 +++++++++++++++++++ .../STAR_2004_1JET_200GEV/kinematics.yaml | 73 +++++++++++++++ .../STAR_2004_1JET_200GEV/metadata.yaml | 56 +++++++++++ .../rawdata/HEPData-ins723509-v1-Figure_3.csv | 16 ++++ .../STAR_2004_1JET_200GEV/uncertainties.yaml | 32 +++++++ 6 files changed, 277 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/data.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/filter.py create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/kinematics.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/metadata.yaml create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/rawdata/HEPData-ins723509-v1-Figure_3.csv create mode 100644 nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/uncertainties.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/data.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/data.yaml new file mode 100644 index 0000000000..4223da7b92 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/data.yaml @@ -0,0 +1,7 @@ +data_central: +- 0.014 +- -0.066 +- -0.019 +- -0.015 +- -0.009 +- 0.004 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/filter.py new file mode 100644 index 0000000000..67d95de3e1 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/filter.py @@ -0,0 +1,93 @@ +"""This script provides the filer to the inclusive jet STAR 2004 dataset.""" +import pandas as pd +import yaml + +POL_UNC = 0.25 +SQRTS = 200 +ETA_MIN = 0.2 +ETA_MAX = 0.8 + + +def read_data(): + df = pd.DataFrame() + file_raw = "HEPData-ins723509-v1-Figure_3.csv" + with open(f"rawdata/{file_raw}", "r", encoding="utf-8") as file: + df = pd.read_csv(file, skiprows=8) + + df["stat"] = df["stat +"] + df["sys"] = df["syst +"] + df["pol"] = POL_UNC * abs(df["$A_{LL}$"]) + df["sqrts"] = SQRTS + df["eta"] = (ETA_MAX + ETA_MIN) / 2 + return df + + +def write_data(df): + data_central = [] + for i in range(len(df["$A_{LL}$"])): + data_central.append(float(df.loc[i, "$A_{LL}$"])) + + data_central_yaml = {"data_central": data_central} + with open("data.yaml", "w", encoding="utf-8") as file: + yaml.dump(data_central_yaml, file, sort_keys=False) + + # Write kin file + kin = [] + for i in range(len(df["$A_{LL}$"])): + kin_value = { + "pT": { + "min": float(df.loc[i, "$p_T (GeV/c)$ LOW"]), + "mid": float(df.loc[i, "$p_T (GeV/c)$"]), + "max": float(df.loc[i, "$p_T (GeV/c)$ HIGH"]), + }, + "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta": { + "min": ETA_MIN, + "mid": float(df.loc[i, "eta"]), + "max": ETA_MAX, + }, + } + kin.append(kin_value) + + kinematics_yaml = {"bins": kin} + + with open("kinematics.yaml", "w", encoding="utf-8") as file: + yaml.dump(kinematics_yaml, file, sort_keys=False) + + # Write unc file + error = [] + for i in range(len(df)): + e = { + "stat": float(df.loc[i, "stat"]), + "sys": float(df.loc[i, "sys"]), + "pol": float(df.loc[i, "pol"]), + } + error.append(e) + + error_definition = { + "stat": { + "description": "statistical uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "sys": { + "description": "systematic uncertainty", + "treatment": "ADD", + "type": "UNCORR", + }, + "pol": { + "description": "beam polarization uncertainty", + "treatment": "MULT", + "type": "RHIC2004POL", + }, + } + + uncertainties_yaml = {"definitions": error_definition, "bins": error} + + with open("uncertainties.yaml", "w", encoding="utf-8") as file: + yaml.dump(uncertainties_yaml, file, sort_keys=False) + + +if __name__ == "__main__": + df = read_data() + write_data(df) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/kinematics.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/kinematics.yaml new file mode 100644 index 0000000000..b44cdedd5e --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/kinematics.yaml @@ -0,0 +1,73 @@ +bins: +- pT: + min: 5.0 + mid: 5.5 + max: 6.2 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 6.2 + mid: 6.8 + max: 7.6 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 7.6 + mid: 8.3 + max: 9.3 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 9.3 + mid: 10.2 + max: 11.4 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 11.4 + mid: 12.6 + max: 14.1 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 +- pT: + min: 14.1 + mid: 15.4 + max: 17.3 + sqrts: + min: null + mid: 200.0 + max: null + eta: + min: 0.2 + mid: 0.5 + max: 0.8 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/metadata.yaml new file mode 100644 index 0000000000..fb20c359a6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/metadata.yaml @@ -0,0 +1,56 @@ +setname: "STAR_2004_1JET_200GEV" + +nnpdf_metadata: + experiment: "STAR" + nnpdf31_process: "JETS" + +arXiv: + url: https://arxiv.org/abs/hep-ex/0608030 +iNSPIRE: + url: https://inspirehep.net/literature/723509 +hepdata: + url: https://www.hepdata.net/record/ins723509 + version: 1 + +version: 1 +version_comment: "Initial implementation" + +implemented_observables: + - observable: { description: "ALL w.r.t. pT", label: "$A_{LL}$", units: "" } + observable_name: ALL + process_type: JET_POL + ndata: 6 + tables: [3] + npoints: [6] + kinematics: + variables: + pT: + { + description: "mean transverse momentum", + label: '$\langle pT \rangle$', + units: "$GeV$", + } + sqrts: + { + description: "center of mass energy", + label: '$\sqrt{s}$', + units: "$GeV$", + } + eta: { description: "pseudorapidity", label: '$\eta$', units: "" } + + file: kinematics.yaml + data_central: data.yaml + data_uncertainties: + - uncertainties.yaml + kinematic_coverage: [pT, sqrts, eta] + plotting: + kinematics_override: identity + dataset_label: "$A_{LL}$" + plot_x: pT + x_scale: log + y_label: "$A_{LL}$" + theory: + FK_tables: + - - STAR_2004_1JET_200GEV_ALL-POL + - - STAR_2004_1JET_200GEV_ALL-UNPOL + operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/rawdata/HEPData-ins723509-v1-Figure_3.csv b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/rawdata/HEPData-ins723509-v1-Figure_3.csv new file mode 100644 index 0000000000..4dbeeb23ae --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/rawdata/HEPData-ins723509-v1-Figure_3.csv @@ -0,0 +1,16 @@ +8#: table_doi: 10.17182/hepdata.104928.v1/t3 +#: name: Figure 3 +#: description: The longitudinal double-spin asymmetry ALL in p+p-> jet +X at sqrt(s) = 200 GeV versus jet pT. The uncertainties on the data points are statistical. The gray band indicates the systematic uncertainty from the beam polarization measurement, and the hatched band the total systematic uncertainty. The curves show predictions based on deep-inelastic scattering parametrizations of gluon polarization. +#: data_file: Figure_3.yaml +#: keyword reactions: pp --> jet + X +#: keyword cmenergies: 200 +#: keyword phrases: jets | RHIC | STAR +#: $p_T (GeV/c)$,,,Filled circles (high tower trigger) +$p_T (GeV/c)$,$p_T (GeV/c)$ LOW,$p_T (GeV/c)$ HIGH,$A_{LL}$,stat +,stat -,syst +,syst - +5.5,5.0,6.2,0.014,0.022,-0.022,0.015,-0.015 +6.8,6.2,7.6,-0.066,0.024,-0.024,0.022,-0.022 +8.3,7.6,9.3,-0.019,0.029,-0.029,0.015,-0.015 +10.2,9.3,11.4,-0.015,0.038,-0.038,0.015,-0.015 +12.6,11.4,14.1,-0.009,0.052,-0.052,0.015,-0.015 +15.4,14.1,17.3,0.004,0.075,-0.075,0.015,-0.015 + diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/uncertainties.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/uncertainties.yaml new file mode 100644 index 0000000000..fdef3b1d93 --- /dev/null +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2004_1JET_200GEV/uncertainties.yaml @@ -0,0 +1,32 @@ +definitions: + stat: + description: statistical uncertainty + treatment: ADD + type: UNCORR + sys: + description: systematic uncertainty + treatment: ADD + type: UNCORR + pol: + description: beam polarization uncertainty + treatment: MULT + type: RHIC2004POL +bins: +- stat: 0.022 + sys: 0.015 + pol: 0.0035 +- stat: 0.024 + sys: 0.022 + pol: 0.0165 +- stat: 0.029 + sys: 0.015 + pol: 0.00475 +- stat: 0.038 + sys: 0.015 + pol: 0.00375 +- stat: 0.052 + sys: 0.015 + pol: 0.00225 +- stat: 0.075 + sys: 0.015 + pol: 0.001 From d19e4cc2e8462b3237eec81a68ebe71cd40abcb9 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Wed, 3 Jul 2024 18:25:50 +0200 Subject: [PATCH 79/98] allow for F1 FKtables in G1F1 ratio --- .../nnpdf_data/new_commondata/E155_NC_9GEV_EN/metadata.yaml | 3 ++- .../nnpdf_data/new_commondata/E155_NC_9GEV_EP/metadata.yaml | 3 ++- .../nnpdf_data/new_commondata/JLABE06_NC_3GEV_EN/metadata.yaml | 3 ++- .../nnpdf_data/new_commondata/JLABE99_NC_3GEV_EN/metadata.yaml | 3 ++- .../new_commondata/JLABEG1B_NC_NOTFIXED_ED/metadata.yaml | 3 ++- .../new_commondata/JLABEG1B_NC_NOTFIXED_EP/metadata.yaml | 3 ++- .../new_commondata/JLABEG1DVCS_NC_3GEV_EP/metadata.yaml | 3 ++- .../new_commondata/JLABEG1DVCS_NC_5GEV_ED/metadata.yaml | 3 ++- .../nnpdf_data/new_commondata/SMCSX_NC_17GEV_MUP/metadata.yaml | 3 ++- .../nnpdf_data/new_commondata/SMCSX_NC_24GEV_MUD/metadata.yaml | 3 ++- 10 files changed, 20 insertions(+), 10 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EN/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EN/metadata.yaml index 87fa3503bf..5467420fa9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EN/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EN/metadata.yaml @@ -52,4 +52,5 @@ implemented_observables: theory: FK_tables: - - E155_NC_9GEV_EN_G1 - operation: 'null' + - - E155_NC_9GEV_EN_F1 + operation: 'ratio' diff --git a/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EP/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EP/metadata.yaml index 3bac0742e8..a5e8861802 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EP/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/E155_NC_9GEV_EP/metadata.yaml @@ -52,4 +52,5 @@ implemented_observables: theory: FK_tables: - - E155_NC_9GEV_EP_G1 - operation: 'null' + - - E155_NC_9GEV_EP_F1 + operation: 'ratio' diff --git a/nnpdf_data/nnpdf_data/new_commondata/JLABE06_NC_3GEV_EN/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/JLABE06_NC_3GEV_EN/metadata.yaml index a43024e975..78e06b689c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/JLABE06_NC_3GEV_EN/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/JLABE06_NC_3GEV_EN/metadata.yaml @@ -48,4 +48,5 @@ implemented_observables: theory: FK_tables: - - JLABE06_NC_3GEV_EN_G1 - operation: "null" + - - JLABE06_NC_3GEV_EN_F1 + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/JLABE99_NC_3GEV_EN/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/JLABE99_NC_3GEV_EN/metadata.yaml index 8331a2efec..83278fb38c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/JLABE99_NC_3GEV_EN/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/JLABE99_NC_3GEV_EN/metadata.yaml @@ -49,4 +49,5 @@ implemented_observables: theory: FK_tables: - - JLABE99_NC_3GEV_EN_G1 - operation: "null" + - - JLABE99_NC_3GEV_EN_F1 + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_ED/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_ED/metadata.yaml index 8154422330..7b4c605ad2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_ED/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_ED/metadata.yaml @@ -528,4 +528,5 @@ implemented_observables: theory: FK_tables: - - JLABEG1B_NC_NOTFIXED_ED_G1 - operation: "null" + - - JLABEG1B_NC_NOTFIXED_ED_F1 + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_EP/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_EP/metadata.yaml index 51e55178d3..75f21d130b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_EP/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1B_NC_NOTFIXED_EP/metadata.yaml @@ -188,4 +188,5 @@ implemented_observables: theory: FK_tables: - - JLABEG1B_NC_NOTFIXED_EP_G1 - operation: "null" + - - JLABEG1B_NC_NOTFIXED_EP_F1 + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_3GEV_EP/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_3GEV_EP/metadata.yaml index 79c3dc797d..9ca752132f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_3GEV_EP/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_3GEV_EP/metadata.yaml @@ -52,4 +52,5 @@ implemented_observables: theory: FK_tables: - - JLABEG1DVCS_NC_3GEV_EP_G1 - operation: "null" + - - JLABEG1DVCS_NC_3GEV_EP_F1 + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_5GEV_ED/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_5GEV_ED/metadata.yaml index 9d6436f913..d065f515f1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_5GEV_ED/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/JLABEG1DVCS_NC_5GEV_ED/metadata.yaml @@ -52,4 +52,5 @@ implemented_observables: theory: FK_tables: - - JLABEG1DVCS_NC_5GEV_ED_G1 - operation: "null" + - - JLABEG1DVCS_NC_5GEV_ED_F1 + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_17GEV_MUP/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_17GEV_MUP/metadata.yaml index 9f20a88259..1384356a78 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_17GEV_MUP/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_17GEV_MUP/metadata.yaml @@ -51,4 +51,5 @@ implemented_observables: theory: FK_tables: - - SMCSX_NC_17GEV_MUP_G1 - operation: "null" + - - SMCSX_NC_17GEV_MUP_F1 + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_24GEV_MUD/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_24GEV_MUD/metadata.yaml index 971407221f..414b631b91 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_24GEV_MUD/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/SMCSX_NC_24GEV_MUD/metadata.yaml @@ -51,4 +51,5 @@ implemented_observables: theory: FK_tables: - - SMCSX_NC_24GEV_MUD_G1 - operation: "null" + - - SMCSX_NC_24GEV_MUD_F1 + operation: "ratio" From 388663128a1c7c7c3507924dc4430d52680ce7b6 Mon Sep 17 00:00:00 2001 From: Gijs van Seeventer Date: Thu, 4 Jul 2024 11:10:25 +0200 Subject: [PATCH 80/98] created baseline --- .../nnpdf_data/theory_cards/20000000.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001000.yaml | 47 +++++++++++++++++++ 2 files changed, 94 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20000000.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001000.yaml diff --git a/nnpdf_data/nnpdf_data/theory_cards/20000000.yaml b/nnpdf_data/nnpdf_data/theory_cards/20000000.yaml new file mode 100644 index 0000000000..d37af2e2f7 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20000000.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL +ID: 20_000_000 +XIF: 1.0 +XIR: 1.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001000.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001000.yaml new file mode 100644 index 0000000000..baae0ae973 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001000.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL +ID: 20_001_000 +XIF: 1.0 +XIR: 1.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file From e7f74b779c417c94749145e041ef14f80213b54c Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 4 Jul 2024 11:23:07 +0200 Subject: [PATCH 81/98] fix nlo name --- .../nnpdf_data/theory_cards/{20001000.yaml => 20000001.yaml} | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) rename nnpdf_data/nnpdf_data/theory_cards/{20001000.yaml => 20000001.yaml} (97%) diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001000.yaml b/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml similarity index 97% rename from nnpdf_data/nnpdf_data/theory_cards/20001000.yaml rename to nnpdf_data/nnpdf_data/theory_cards/20000001.yaml index baae0ae973..9372e66f49 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001000.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml @@ -1,5 +1,5 @@ Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL -ID: 20_001_000 +ID: 20_000_001 XIF: 1.0 XIR: 1.0 CKM: From f08cda89e1cdb5867710f6d521a12d20cb44a0df Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 4 Jul 2024 11:27:20 +0200 Subject: [PATCH 82/98] add NLO sv --- .../nnpdf_data/theory_cards/20002001.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20002002.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20002003.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20002004.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20002005.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20002006.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20002007.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20002008.yaml | 47 +++++++++++++++++++ 8 files changed, 376 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002001.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002002.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002003.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002004.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002005.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002006.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002007.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20002008.yaml diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml new file mode 100644 index 0000000000..6e938e06f0 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=0.5, XIR=0.5 +ID: 20_002_001 +XIF: 0.5 +XIR: 0.5 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml new file mode 100644 index 0000000000..dff15d3ad6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=0.5, XIR=1.0 +ID: 20_002_002 +XIF: 0.5 +XIR: 1.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml new file mode 100644 index 0000000000..984fc88e5c --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=0.5, XIR=2.0 +ID: 20_002_003 +XIF: 0.5 +XIR: 2.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml new file mode 100644 index 0000000000..056323baf3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=1.0, XIR=0.5 +ID: 20_002_004 +XIF: 1.0 +XIR: 0.5 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml new file mode 100644 index 0000000000..f6bb2b8770 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=1.0, XIR=2.0 +ID: 20_002_005 +XIF: 1.0 +XIR: 2.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml new file mode 100644 index 0000000000..fdc4833ecd --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=2.0, XIR=0.5 +ID: 20_002_006 +XIF: 2.0 +XIR: 0.5 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml new file mode 100644 index 0000000000..4e9048fb90 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=2.0, XIR=1.0 +ID: 20_002_007 +XIF: 2.0 +XIR: 1.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml new file mode 100644 index 0000000000..34071d1e09 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NLO alphas=0.118 with nFONLL, XIF=2.0, XIR=2.0 +ID: 20_002_008 +XIF: 2.0 +XIR: 2.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 1 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file From 14f5e33a5f23054ed8801e5406a2d0cde354ae5f Mon Sep 17 00:00:00 2001 From: Gijs van Seeventer Date: Thu, 4 Jul 2024 11:27:31 +0200 Subject: [PATCH 83/98] Added NNLO 9 point scale variation --- .../nnpdf_data/theory_cards/20001001.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001002.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001003.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001004.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001005.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001006.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001007.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001008.yaml | 47 +++++++++++++++++++ 8 files changed, 376 insertions(+) create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001001.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001002.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001003.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001004.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001005.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001006.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001007.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001008.yaml diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml new file mode 100644 index 0000000000..8348c170da --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 0.5,.05 +ID: 20_001_001 +XIF: 0.5 +XIR: 0.5 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml new file mode 100644 index 0000000000..885f924273 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 0.5,1 +ID: 20_001_002 +XIF: 0.5 +XIR: 1.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml new file mode 100644 index 0000000000..c02f48b3a6 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 05,2 +ID: 20_001_003 +XIF: 0.5 +XIR: 2.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml new file mode 100644 index 0000000000..2a1d91eb42 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 1,0.5 +ID: 20_001_004 +XIF: 1.0 +XIR: 0.5 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml new file mode 100644 index 0000000000..18305a9084 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 1,2 +ID: 20_001_005 +XIF: 1.0 +XIR: 2.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml new file mode 100644 index 0000000000..06edfbde26 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 2,0.5 +ID: 20_001_006 +XIF: 2.0 +XIR: 0.5 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml new file mode 100644 index 0000000000..3e71de0efa --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 2,1 +ID: 20_001_007 +XIF: 2.0 +XIR: 1.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml new file mode 100644 index 0000000000..c7a448f3a3 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 2,2 +ID: 20_001_008 +XIF: 2.0 +XIR: 2.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file From 27f9f16c1721d479510ee774ba9e28f679e3bf75 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 4 Jul 2024 11:37:58 +0200 Subject: [PATCH 84/98] fix fonll scheme for NLO --- nnpdf_data/nnpdf_data/theory_cards/20002001.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002002.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002003.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002004.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002005.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002006.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002007.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002008.yaml | 2 +- 8 files changed, 8 insertions(+), 8 deletions(-) diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml index 6e938e06f0..08ce0b20e9 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml index dff15d3ad6..6b6fdabd27 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml index 984fc88e5c..da6a01d8b7 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml index 056323baf3..044442c002 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml index f6bb2b8770..d68fba8439 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml index fdc4833ecd..3dec9fe066 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml index 4e9048fb90..8c9569821d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml index 34071d1e09..23973b110d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 From d75c352634ba57c856f6c34b13fdc6130787526e Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 4 Jul 2024 11:40:58 +0200 Subject: [PATCH 85/98] add sv theories to vp --- .../nnpdf_data/theory_cards/20000001.yaml | 2 +- .../scalevariationtheoryids.yaml | 28 ++++++++++++++++++- 2 files changed, 28 insertions(+), 2 deletions(-) diff --git a/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml index 9372e66f49..978cb83ba9 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml @@ -13,7 +13,7 @@ CKM: - 0.0403 - 0.999152 DAMP: 0 -FNS: FONLL-C +FNS: FONLL-A GF: 1.1663787e-05 HQ: POLE IC: 0 diff --git a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml index 98031c3498..868b2e9c0f 100644 --- a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml +++ b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml @@ -260,4 +260,30 @@ scale_variations_for: (1, 1): 1024 # IHOU + MHOU missing prescription (1, 0.5 hadronic): 1025 # As 1018 but DIS from 1000 - (1, 2 hadronic): 1026 # As 1021 but DIS from 1000 \ No newline at end of file + (1, 2 hadronic): 1026 # As 1021 but DIS from 1000 + + # NNLO polarized SV + - theoryid: 20_000_000 + variations: + (0.5, 0.5): 20_001_001 + (0.5, 1): 20_001_002 + (0.5, 2): 20_001_003 + (1, 0.5): 20_001_004 + (1, 1): 20_000_000 + (1, 2): 20_001_005 + (2, 0.5): 20_001_006 + (2, 1): 20_001_007 + (2, 2): 20_001_008 + + # NLO polarized SV + - theoryid: 20_000_001 + variations: + (0.5, 0.5): 20_002_001 + (0.5, 1): 20_002_002 + (0.5, 2): 20_002_003 + (1, 0.5): 20_002_004 + (1, 1): 20_000_001 + (1, 2): 20_002_005 + (2, 0.5): 20_002_006 + (2, 1): 20_002_007 + (2, 2): 20_002_008 \ No newline at end of file From 3669754e80763a92fa644c1c2657820c4a0dca79 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 4 Jul 2024 12:04:15 +0200 Subject: [PATCH 86/98] add missing point prescription for NNLO --- .../nnpdf_data/theory_cards/20001001.yaml | 2 +- .../nnpdf_data/theory_cards/20001002.yaml | 2 +- .../nnpdf_data/theory_cards/20001003.yaml | 3 +- .../nnpdf_data/theory_cards/20001004.yaml | 2 +- .../nnpdf_data/theory_cards/20001005.yaml | 2 +- .../nnpdf_data/theory_cards/20001006.yaml | 2 +- .../nnpdf_data/theory_cards/20001007.yaml | 2 +- .../nnpdf_data/theory_cards/20001008.yaml | 2 +- .../nnpdf_data/theory_cards/20001009.yaml | 47 +++++++++++++++++++ .../nnpdf_data/theory_cards/20001010.yaml | 47 +++++++++++++++++++ .../scalevariations/pointprescriptions.yaml | 8 ++-- .../scalevariationtheoryids.yaml | 2 + 12 files changed, 109 insertions(+), 12 deletions(-) create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001009.yaml create mode 100644 nnpdf_data/nnpdf_data/theory_cards/20001010.yaml diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml index 8348c170da..e9919f0034 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml @@ -1,4 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 0.5,.05 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=0.5, XIR=0.5 ID: 20_001_001 XIF: 0.5 XIR: 0.5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml index 885f924273..282d6de1d4 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml @@ -1,4 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 0.5,1 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=0.5, XIR=1.0 ID: 20_001_002 XIF: 0.5 XIR: 1.0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml index c02f48b3a6..64e9cd302d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml @@ -1,5 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 05,2 -ID: 20_001_003 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=0.5, XIR=2.0 XIF: 0.5 XIR: 2.0 CKM: diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml index 2a1d91eb42..e2a2d8e951 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml @@ -1,4 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 1,0.5 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=1.0, XIR=0.5 ID: 20_001_004 XIF: 1.0 XIR: 0.5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml index 18305a9084..d5c24733ce 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml @@ -1,4 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 1,2 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=1.0, XIR=2.0 ID: 20_001_005 XIF: 1.0 XIR: 2.0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml index 06edfbde26..b4a418cd81 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml @@ -1,4 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 2,0.5 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=2.0 XIR=0.5 ID: 20_001_006 XIF: 2.0 XIR: 0.5 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml index 3e71de0efa..aa9bfcc656 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml @@ -1,4 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 2,1 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=2.0, XIR=1.0 ID: 20_001_007 XIF: 2.0 XIR: 1.0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml index c7a448f3a3..7dd5f21813 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml @@ -1,4 +1,4 @@ -Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, 9-point scheme 2,2 +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=2.0, XIR=2.0 ID: 20_001_008 XIF: 2.0 XIR: 2.0 diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001009.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001009.yaml new file mode 100644 index 0000000000..bbeb993170 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001009.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=1.0 XIR=0.5 only for JETS and DIJETS +ID: 20_001_009 +XIF: 1.0 +XIR: 0.5 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001010.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001010.yaml new file mode 100644 index 0000000000..31d92e39e0 --- /dev/null +++ b/nnpdf_data/nnpdf_data/theory_cards/20001010.yaml @@ -0,0 +1,47 @@ +Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=1.0 XIR=2.0 only for JETS and DIJETS +ID: 20_001_010 +XIF: 1.0 +XIR: 2.0 +CKM: +- 0.97428 +- 0.2253 +- 0.00347 +- 0.2252 +- 0.97345 +- 0.041 +- 0.00862 +- 0.0403 +- 0.999152 +DAMP: 0 +FNS: FONLL-C +GF: 1.1663787e-05 +HQ: POLE +IC: 0 +MP: 0.938 +MW: 80.398 +MZ: 91.1876 +MaxNfPdf: 5 +ModEv: TRN +ModSV: null +NfFF: 4 +PTO: 2 +Q0: 1.0 +QED: 0 +Qmb: 4.92 +Qmc: 1.51 +Qmt: 172.5 +Qref: 91.2 +SIN2TW: 0.23126 +TMC: 3 +alphaqed: 0.007496252 +alphas: 0.118 +kbThr: 1.0 +kcThr: 1.0 +ktThr: 1.0 +mb: 4.92 +mc: 1.51 +mt: 172.5 +nfref: 5 +nf0: 3 +n3lo_cf_variation: 0 +n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file diff --git a/validphys2/src/validphys/scalevariations/pointprescriptions.yaml b/validphys2/src/validphys/scalevariations/pointprescriptions.yaml index d76d2ca400..2d861c3d1e 100644 --- a/validphys2/src/validphys/scalevariations/pointprescriptions.yaml +++ b/validphys2/src/validphys/scalevariations/pointprescriptions.yaml @@ -15,13 +15,15 @@ 'n3lo ihou': ['(0, 0, 0, 0)','(1, 0, 0, 0)','(2, 0, 0, 0)','(3, 0, 0, 0)','(4, 0, 0, 0)','(5, 0, 0, 0)','(6, 0, 0, 0)','(7, 0, 0, 0)','(8, 0, 0, 0)','(9, 0, 0, 0)','(10, 0, 0, 0)','(11, 0, 0, 0)','(12, 0, 0, 0)','(13, 0, 0, 0)','(14, 0, 0, 0)','(15, 0, 0, 0)','(16, 0, 0, 0)','(17, 0, 0, 0)','(18, 0, 0, 0)','(19, 0, 0, 0)','(0, 1, 0, 0)','(0, 2, 0, 0)','(0, 3, 0, 0)','(0, 4, 0, 0)','(0, 5, 0, 0)','(0, 6, 0, 0)','(0, 7, 0, 0)','(0, 8, 0, 0)','(0, 9, 0, 0)','(0, 10, 0, 0)','(0, 11, 0, 0)','(0, 12, 0, 0)','(0, 13, 0, 0)','(0, 14, 0, 0)','(0, 15, 0, 0)','(0, 16, 0, 0)','(0, 17, 0, 0)','(0, 18, 0, 0)','(0, 19, 0, 0)','(0, 20, 0, 0)','(0, 21, 0, 0)','(0, 0, 1, 0)','(0, 0, 2, 0)','(0, 0, 3, 0)','(0, 0, 4, 0)','(0, 0, 5, 0)','(0, 0, 6, 0)','(0, 0, 7, 0)','(0, 0, 8, 0)','(0, 0, 9, 0)','(0, 0, 10, 0)','(0, 0, 11, 0)','(0, 0, 12, 0)','(0, 0, 13, 0)','(0, 0, 14, 0)','(0, 0, 15, 0)','(0, 0, 0, 1)','(0, 0, 0, 2)','(0, 0, 0, 3)','(0, 0, 0, 4)','(0, 0, 0, 5)','(0, 0, 0, 6)','(-1, -1)','(1, 1)'] # N3LO full IHOU + 7 point scale variations 'n3lo full thcovmat': ['(0, 0, 0, 0)','(1, 0, 0, 0)','(2, 0, 0, 0)','(3, 0, 0, 0)','(4, 0, 0, 0)','(5, 0, 0, 0)','(6, 0, 0, 0)','(7, 0, 0, 0)','(8, 0, 0, 0)','(9, 0, 0, 0)','(10, 0, 0, 0)','(11, 0, 0, 0)','(12, 0, 0, 0)','(13, 0, 0, 0)','(14, 0, 0, 0)','(15, 0, 0, 0)','(16, 0, 0, 0)','(17, 0, 0, 0)','(18, 0, 0, 0)','(19, 0, 0, 0)','(0, 1, 0, 0)','(0, 2, 0, 0)','(0, 3, 0, 0)','(0, 4, 0, 0)','(0, 5, 0, 0)','(0, 6, 0, 0)','(0, 7, 0, 0)','(0, 8, 0, 0)','(0, 9, 0, 0)','(0, 10, 0, 0)','(0, 11, 0, 0)','(0, 12, 0, 0)','(0, 13, 0, 0)','(0, 14, 0, 0)','(0, 15, 0, 0)','(0, 16, 0, 0)','(0, 17, 0, 0)','(0, 18, 0, 0)','(0, 19, 0, 0)','(0, 20, 0, 0)','(0, 21, 0, 0)','(0, 0, 1, 0)','(0, 0, 2, 0)','(0, 0, 3, 0)','(0, 0, 4, 0)','(0, 0, 5, 0)','(0, 0, 6, 0)','(0, 0, 7, 0)','(0, 0, 8, 0)','(0, 0, 9, 0)','(0, 0, 10, 0)','(0, 0, 11, 0)','(0, 0, 12, 0)','(0, 0, 13, 0)','(0, 0, 14, 0)','(0, 0, 15, 0)','(0, 0, 0, 1)','(0, 0, 0, 2)','(0, 0, 0, 3)','(0, 0, 0, 4)','(0, 0, 0, 5)','(0, 0, 0, 6)','(2, 1)', '(0.5, 1)', '(1, 2)', '(1, 0.5)', '(2, 2)', '(0.5, 0.5)','(-1, -1)','(1, 1)'] -# N3LO full IHOU + 3 point scale variations for datasets with no N3LO correcttions +# N3LO full IHOU + 3 point scale variations for datasets with no N3LO corrections 'n3lo 3pt missing': ['(0, 0, 0, 0)','(1, 0, 0, 0)','(2, 0, 0, 0)','(3, 0, 0, 0)','(4, 0, 0, 0)','(5, 0, 0, 0)','(6, 0, 0, 0)','(7, 0, 0, 0)','(8, 0, 0, 0)','(9, 0, 0, 0)','(10, 0, 0, 0)','(11, 0, 0, 0)','(12, 0, 0, 0)','(13, 0, 0, 0)','(14, 0, 0, 0)','(15, 0, 0, 0)','(16, 0, 0, 0)','(17, 0, 0, 0)','(18, 0, 0, 0)','(19, 0, 0, 0)','(0, 1, 0, 0)','(0, 2, 0, 0)','(0, 3, 0, 0)','(0, 4, 0, 0)','(0, 5, 0, 0)','(0, 6, 0, 0)','(0, 7, 0, 0)','(0, 8, 0, 0)','(0, 9, 0, 0)','(0, 10, 0, 0)','(0, 11, 0, 0)','(0, 12, 0, 0)','(0, 13, 0, 0)','(0, 14, 0, 0)','(0, 15, 0, 0)','(0, 16, 0, 0)','(0, 17, 0, 0)','(0, 18, 0, 0)','(0, 19, 0, 0)','(0, 20, 0, 0)','(0, 21, 0, 0)','(0, 0, 1, 0)','(0, 0, 2, 0)','(0, 0, 3, 0)','(0, 0, 4, 0)','(0, 0, 5, 0)','(0, 0, 6, 0)','(0, 0, 7, 0)','(0, 0, 8, 0)','(0, 0, 9, 0)','(0, 0, 10, 0)','(0, 0, 11, 0)','(0, 0, 12, 0)','(0, 0, 13, 0)','(0, 0, 14, 0)','(0, 0, 15, 0)','(0, 0, 0, 1)','(0, 0, 0, 2)','(0, 0, 0, 3)','(0, 0, 0, 4)','(0, 0, 0, 5)','(0, 0, 0, 6)', '(1, 0.5 missing)', '(1, 2 missing)','(-1, -1)','(1, 1)'] -# N3LO full IHOU + 3 point scale variations for hadronic dasasets +# N3LO full IHOU + 3 point scale variations for hadronic datasets 'n3lo 3pt hadronic': ['(0, 0, 0, 0)','(1, 0, 0, 0)','(2, 0, 0, 0)','(3, 0, 0, 0)','(4, 0, 0, 0)','(5, 0, 0, 0)','(6, 0, 0, 0)','(7, 0, 0, 0)','(8, 0, 0, 0)','(9, 0, 0, 0)','(10, 0, 0, 0)','(11, 0, 0, 0)','(12, 0, 0, 0)','(13, 0, 0, 0)','(14, 0, 0, 0)','(15, 0, 0, 0)','(16, 0, 0, 0)','(17, 0, 0, 0)','(18, 0, 0, 0)','(19, 0, 0, 0)','(0, 1, 0, 0)','(0, 2, 0, 0)','(0, 3, 0, 0)','(0, 4, 0, 0)','(0, 5, 0, 0)','(0, 6, 0, 0)','(0, 7, 0, 0)','(0, 8, 0, 0)','(0, 9, 0, 0)','(0, 10, 0, 0)','(0, 11, 0, 0)','(0, 12, 0, 0)','(0, 13, 0, 0)','(0, 14, 0, 0)','(0, 15, 0, 0)','(0, 16, 0, 0)','(0, 17, 0, 0)','(0, 18, 0, 0)','(0, 19, 0, 0)','(0, 20, 0, 0)','(0, 21, 0, 0)','(0, 0, 1, 0)','(0, 0, 2, 0)','(0, 0, 3, 0)','(0, 0, 4, 0)','(0, 0, 5, 0)','(0, 0, 6, 0)','(0, 0, 7, 0)','(0, 0, 8, 0)','(0, 0, 9, 0)','(0, 0, 10, 0)','(0, 0, 11, 0)','(0, 0, 12, 0)','(0, 0, 13, 0)','(0, 0, 14, 0)','(0, 0, 15, 0)','(0, 0, 0, 1)','(0, 0, 0, 2)','(0, 0, 0, 3)','(0, 0, 0, 4)','(0, 0, 0, 5)','(0, 0, 0, 6)', '(1, 0.5 hadronic)', '(1, 2 hadronic)','(-1, -1)','(1, 1)'] # N3LO 7 point scale variations 'n3lo 7 point': ['(0, 0, 0, 0)', '(2, 1)', '(0.5, 1)', '(1, 2)', '(1, 0.5)', '(2, 2)', '(0.5, 0.5)'] # N3LO full IHOU + 7 point scale variations with FHMV splittings 'n3lo fhmv full thcovmat': ['(0, 0, 0, 0, 0, 0, 0)','(1, 0, 0, 0, 0, 0, 0)','(2, 0, 0, 0, 0, 0, 0)','(0, 1, 0, 0, 0, 0, 0)','(0, 2, 0, 0, 0, 0, 0)', '(0, 0, 1, 0, 0, 0, 0)','(0, 0, 2, 0, 0, 0, 0)','(0, 0, 0, 1, 0, 0, 0)','(0, 0, 0, 2, 0, 0, 0)','(0, 0, 0, 0, 1, 0, 0)','(0, 0, 0, 0, 2, 0, 0)','(0, 0, 0, 0, 0, 1, 0)','(0, 0, 0, 0, 0, 2, 0)','(0, 0, 0, 0, 0, 0, 1)','(0, 0, 0, 0, 0, 0, 2)','(2, 1)', '(0.5, 1)', '(1, 2)', '(1, 0.5)', '(2, 2)', '(0.5, 0.5)','(-1, -1)','(1, 1)'] -# N3LO full IHOU + 3 point scale variations for hadronic dasasets with FHMV splittings +# N3LO full IHOU + 3 point scale variations for hadronic datasets with FHMV splittings 'n3lo fhmv 3pt hadronic': ['(0, 0, 0, 0, 0, 0, 0)','(1, 0, 0, 0, 0, 0, 0)','(2, 0, 0, 0, 0, 0, 0)','(0, 1, 0, 0, 0, 0, 0)','(0, 2, 0, 0, 0, 0, 0)', '(0, 0, 1, 0, 0, 0, 0)','(0, 0, 2, 0, 0, 0, 0)','(0, 0, 0, 1, 0, 0, 0)','(0, 0, 0, 2, 0, 0, 0)','(0, 0, 0, 0, 1, 0, 0)','(0, 0, 0, 0, 2, 0, 0)','(0, 0, 0, 0, 0, 1, 0)','(0, 0, 0, 0, 0, 2, 0)','(0, 0, 0, 0, 0, 0, 1)','(0, 0, 0, 0, 0, 0, 2)','(1, 0.5 hadronic)', '(1, 2 hadronic)','(-1, -1)','(1, 1)'] +# Polarized missing: 3 point renormalization scales for JETS and DIJETS +'3pt missing': ['(1, 1)', '(1, 0.5 missing)', '(1, 2 missing)'] diff --git a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml index 868b2e9c0f..8821dbe4c0 100644 --- a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml +++ b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml @@ -274,6 +274,8 @@ scale_variations_for: (2, 0.5): 20_001_006 (2, 1): 20_001_007 (2, 2): 20_001_008 + (1, 0.5 missing): 20_001_009 # As 20_001_004 but DIS and DY from 20_000_000 + (1, 2 missing): 20_001_010 # As 20_001_005 but DIS and DY from 20_000_000 # NLO polarized SV - theoryid: 20_000_001 From 2760bf4b9628e767fc41dc97e883a07dded64dc1 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 4 Jul 2024 12:58:35 +0200 Subject: [PATCH 87/98] fix blank line --- nnpdf_data/nnpdf_data/theory_cards/20000000.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20000001.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001001.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001002.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001003.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001004.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001005.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001006.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001007.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001008.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001009.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20001010.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002001.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002002.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002003.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002004.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002005.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002006.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002007.yaml | 2 +- nnpdf_data/nnpdf_data/theory_cards/20002008.yaml | 2 +- 20 files changed, 20 insertions(+), 20 deletions(-) diff --git a/nnpdf_data/nnpdf_data/theory_cards/20000000.yaml b/nnpdf_data/nnpdf_data/theory_cards/20000000.yaml index d37af2e2f7..45468d8eb1 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20000000.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20000000.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml index 978cb83ba9..43d82c8ef2 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20000001.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml index e9919f0034..ff27ad9e94 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001001.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml index 282d6de1d4..274fca779c 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001002.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml index 64e9cd302d..58034b8088 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml @@ -43,4 +43,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml index e2a2d8e951..b7f199ce99 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001004.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml index d5c24733ce..4348d54f33 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001005.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml index b4a418cd81..678a6b1e8d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001006.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml index aa9bfcc656..d92bee9d71 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001007.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml index 7dd5f21813..99b7d0c07d 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001008.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001009.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001009.yaml index bbeb993170..5a7f4fc0d5 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001009.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001009.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001010.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001010.yaml index 31d92e39e0..ffeb91d7c4 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001010.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001010.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml index 08ce0b20e9..5e403d8ab1 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002001.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml index 6b6fdabd27..a5493933e4 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002002.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml index da6a01d8b7..226e852eb7 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002003.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml index 044442c002..7f86455b88 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002004.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml index d68fba8439..c06643b75b 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002005.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml index 3dec9fe066..7d4bfc4790 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002006.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml index 8c9569821d..b08ab4c242 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002007.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] diff --git a/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml b/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml index 23973b110d..ff0fd8ae60 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20002008.yaml @@ -44,4 +44,4 @@ mt: 172.5 nfref: 5 nf0: 3 n3lo_cf_variation: 0 -n3lo_ad_variation: [0,0,0,0,0,0,0] \ No newline at end of file +n3lo_ad_variation: [0,0,0,0,0,0,0] From 594ae9a6d3488affaa79616472524ce814c05e50 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Thu, 4 Jul 2024 18:13:55 +0200 Subject: [PATCH 88/98] fix typos --- nnpdf_data/nnpdf_data/theory_cards/20001003.yaml | 1 + .../src/validphys/scalevariations/scalevariationtheoryids.yaml | 2 +- 2 files changed, 2 insertions(+), 1 deletion(-) diff --git a/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml index 58034b8088..c1df5858a8 100644 --- a/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml +++ b/nnpdf_data/nnpdf_data/theory_cards/20001003.yaml @@ -1,4 +1,5 @@ Comments: Polarised NNPDF2.0 NNLO alphas=0.118 with nFONLL, XIF=0.5, XIR=2.0 +ID: 20_001_003 XIF: 0.5 XIR: 2.0 CKM: diff --git a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml index 8821dbe4c0..75217d611d 100644 --- a/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml +++ b/validphys2/src/validphys/scalevariations/scalevariationtheoryids.yaml @@ -288,4 +288,4 @@ scale_variations_for: (1, 2): 20_002_005 (2, 0.5): 20_002_006 (2, 1): 20_002_007 - (2, 2): 20_002_008 \ No newline at end of file + (2, 2): 20_002_008 From 241c61dad1f7da877b9a527b6242cd9ad67a75dd Mon Sep 17 00:00:00 2001 From: Radonirinaunimi Date: Fri, 5 Jul 2024 21:03:25 +0200 Subject: [PATCH 89/98] add integrability dataset for DV and DV3 & clean a bit --- ...cs_XDELTAG.yaml => kinematics_XDELTA.yaml} | 0 .../kinematics_XDELTASIGMA.yaml | 13 --- .../NNPDF_INTEG_1GEV/metadata.yaml | 82 ++++++++++++++++++- 3 files changed, 80 insertions(+), 15 deletions(-) rename nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/{kinematics_XDELTAG.yaml => kinematics_XDELTA.yaml} (100%) delete mode 100644 nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTASIGMA.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTAG.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTA.yaml similarity index 100% rename from nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTAG.yaml rename to nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTA.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTASIGMA.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTASIGMA.yaml deleted file mode 100644 index cba7884c13..0000000000 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/kinematics_XDELTASIGMA.yaml +++ /dev/null @@ -1,13 +0,0 @@ -bins: -- x: - min: null - mid: 1.0e-05 - max: null - Q2: - min: null - mid: 1.0 - max: null - y: - min: null - mid: 0.0 - max: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml index 878a047c2a..3181a118e6 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml @@ -48,7 +48,7 @@ implemented_observables: description: "inelasticity" label: "$y$" units: "" - file: kinematics_XDELTAG.yaml + file: kinematics_XDELTA.yaml theory: conversion_factor: 1.0 operation: 'null' @@ -87,7 +87,85 @@ implemented_observables: description: "inelasticity" label: "$y$" units: "" - file: kinematics_XDELTASIGMA.yaml + file: kinematics_XDELTA.yaml + theory: + conversion_factor: 1.0 + operation: 'null' + FK_tables: + - - NNPDF_INTEG_DSIGMA + data_uncertainties: [] +- observable_name: XV-POLARIZED + observable: + description: Integrability dataset for Polarized Valence + label: 'polarized integrability: $x \delta V$ PDF $Q^2=1$ GeV$^2$' + units: '' + process_type: INTEG_XDV + tables: [] + npoints: [] + ndata: 1 + plotting: + kinematics_override: dis_sqrt_scale + theory_reference: Ball:2013lla + dataset_label: 'polarized integrability: $x \delta V$ PDF $Q^2=1$ GeV$^2$' + plot_x: x + kinematic_coverage: + - x + - Q2 + - y + kinematics: + variables: + x: + description: "momentum fraction" + label: "$x$" + units: "" + Q2: + description: "virtuality" + label: "$Q^2$" + units: "$GeV^2$" + y: + description: "inelasticity" + label: "$y$" + units: "" + file: kinematics_XDELTA.yaml + theory: + conversion_factor: 1.0 + operation: 'null' + FK_tables: + - - NNPDF_INTEG_DV + data_uncertainties: [] +- observable_name: XV3-POLARIZED + observable: + description: Integrability dataset for Polarized V3 + label: 'polarized integrability: $x \delta V_3$ PDF $Q^2=1$ GeV$^2$' + units: '' + process_type: INTEG_XDV3 + tables: [] + npoints: [] + ndata: 1 + plotting: + kinematics_override: dis_sqrt_scale + theory_reference: Ball:2013lla + dataset_label: 'polarized integrability: $x \delta V_3$ PDF $Q^2=1$ GeV$^2$' + plot_x: x + kinematic_coverage: + - x + - Q2 + - y + kinematics: + variables: + x: + description: "momentum fraction" + label: "$x$" + units: "" + Q2: + description: "virtuality" + label: "$Q^2$" + units: "$GeV^2$" + y: + description: "inelasticity" + label: "$y$" + units: "" + file: kinematics_XDELTA.yaml theory: conversion_factor: 1.0 operation: 'null' From e1be056ae3f41e7489f2d4ab70d132f3a69352aa Mon Sep 17 00:00:00 2001 From: Radonirinaunimi Date: Fri, 5 Jul 2024 21:06:28 +0200 Subject: [PATCH 90/98] fix minor typo --- .../nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml index 3181a118e6..94f19ce2b7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/NNPDF_INTEG_1GEV/metadata.yaml @@ -170,7 +170,7 @@ implemented_observables: conversion_factor: 1.0 operation: 'null' FK_tables: - - - NNPDF_INTEG_DSIGMA + - - NNPDF_INTEG_DV3 data_uncertainties: [] - observable_name: T8-543 observable: From 9b90f155ca0966d879100bb081e2e46038fb43a1 Mon Sep 17 00:00:00 2001 From: Giacomo Magni Date: Fri, 12 Jul 2024 23:35:14 +0200 Subject: [PATCH 91/98] init dijet eta implementation --- .../STAR_2009_1JET_200GEV/filter.py | 51 ++++++++++++++++--- validphys2/src/validphys/process_options.py | 6 ++- 2 files changed, 48 insertions(+), 9 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index 8fb1f5345a..a2703b3db3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -17,6 +17,17 @@ HERE = pathlib.Path(__file__).parent +DIJET_TOPO_DEF = { + "B": {"eta1_min": -0.8, "eta1_max": 0, "eta2_min": 0.8, "eta2_max": 1.8}, + "C": {"eta1_min": 0, "eta1_max": 0.8, "eta2_min": 0.8, "eta2_max": 1.8}, + "A": {"eta1_min": 0.8, "eta1_max": 1.8, "eta2_min": 0.8, "eta2_max": 1.8}, + "SS": {"abs_eta_min": 0, "abs_eta_max": 0.8}, + "OS": {"abs_eta_min": 0, "abs_eta_max": 0.8}, + "CC": {"abs_eta_min": 0, "abs_eta_max": 0.5}, + "CF": {"abs_eta_min": 0.5, "abs_eta_max": 1.0}, +} + + def read_1jet_data(topology): tab_number = 3 if "CC" in topology else 4 fnames = [ @@ -52,13 +63,8 @@ def read_1jet_data(topology): # dfc.loc[binx, biny] = dfc_col.loc[i, "val"] # dfc = dfc.astype("float") - if topology == "CC": - df["abs_eta_min"] = 0.0 - df["abs_eta_max"] = 0.5 - elif topology == "CF": - df["abs_eta_min"] = 0.5 - df["abs_eta_max"] = 1.0 - + df["abs_eta_min"] = DIJET_TOPO_DEF[topology]["abs_eta_min"] + df["abs_eta_max"] = DIJET_TOPO_DEF[topology]["abs_eta_max"] df["stat"] = df["stat_max"] df["sys"] = df["sys_max"] df["pol"] = POL_UNC * abs(df["ALL"]) @@ -98,6 +104,12 @@ def read_2jet_data(topology): ignore_index=True, ) df["m"] = (df["m_low"] + df["m_high"]) / 2 + df["eta1_min"] = DIJET_TOPO_DEF[topology]["eta1_min"] + df["eta1_max"] = DIJET_TOPO_DEF[topology]["eta1_max"] + df["eta2_min"] = DIJET_TOPO_DEF[topology]["eta2_min"] + df["eta2_max"] = DIJET_TOPO_DEF[topology]["eta2_max"] + df["eta1"] = (df["eta1_min"] + df["eta1_max"]) / 2 + df["eta2"] = (df["eta2_min"] + df["eta2_max"]) / 2 else: Msub = data["dependent_variables"][0]["values"] Gsub = data["dependent_variables"][1]["values"] @@ -112,6 +124,8 @@ def read_2jet_data(topology): "ALL": [Gsub[i]["value"]], "stat": [Gsub[i]["errors"][0]["symerror"]], "sys": [Gsub[i]["errors"][1]["symerror"]], + "abs_eta_min": DIJET_TOPO_DEF[topology]["abs_eta_min"], + "abs_eta_max": DIJET_TOPO_DEF[topology]["abs_eta_max"], } ), ], @@ -215,11 +229,32 @@ def write_2jet_data(df, topology, art_sys): "max": float(df.loc[i, "m_high"]), }, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "eta_1": { + "min": float(df.loc[i, "eta1_min"]), + "mid": float(df.loc[i, "eta1"]), + "max": float(df.loc[i, "eta1_max"]), + }, + "eta_2": { + "min": float(df.loc[i, "eta1_min"]), + "mid": float(df.loc[i, "eta1"]), + "max": float(df.loc[i, "eta1_max"]), + }, } except: + df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 kin_value = { "m_jj": {"min": None, "mid": float(df.loc[i, "m"]), "max": None}, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "abs_eta_1": { + "min": float(df.loc[i, "abs_eta_min"]), + "mid": float(df.loc[i, "abs_eta"]), + "max": float(df.loc[i, "abs_eta_max"]), + }, + "abs_eta_2": { + "min": float(df.loc[i, "abs_eta_min"]), + "mid": float(df.loc[i, "abs_eta"]), + "max": float(df.loc[i, "abs_eta_max"]), + }, } kin.append(kin_value) kinematics_yaml = {"bins": kin} @@ -288,7 +323,7 @@ def write_2jet_data(df, topology, art_sys): ) # from the supplement material: # https://journals.aps.org/prd/supplemental/10.1103/PhysRevD.98.032011/Supplementalmaterial.pdf - # we understand that stat jet and dijet are correlated, + # we understand that stat jet and dijet are correlated, # see also https://github.com/NNPDF/nnpdf/pull/2035#issuecomment-2201979662 correlated_unc = [] for a in TOPOPLOGY_LIST: diff --git a/validphys2/src/validphys/process_options.py b/validphys2/src/validphys/process_options.py index 7e7fd0a583..26bbe6875a 100644 --- a/validphys2/src/validphys/process_options.py +++ b/validphys2/src/validphys/process_options.py @@ -32,6 +32,10 @@ class _Vars: abs_eta = "abs_eta" m_W2 = "m_W2" m_Z2 = "m_Z2" + abs_eta_1 = "abs_eta_1" + abs_eta_2 = "abs_eta_2" + eta_1 = "eta_1" + eta_2 = "eta_2" class _KinematicsInformation: @@ -266,7 +270,7 @@ def _dybosonpt_xq2map(kin_dict): DIJET_POL = _Process( "DIJET_POL", "Longitudinal double-spin asymmetry in dijets production", - accepted_variables=(_Vars.m_jj, _Vars.sqrts), + accepted_variables=(_Vars.m_jj, _Vars.sqrts, _Vars.abs_eta_2, _Vars.abs_eta_1, _Vars.eta_1, _Vars.eta_2), xq2map_function=_dijets_xq2map, ) From 45b9f90f56546bab4621ea1ae5354689834c88f9 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Sat, 13 Jul 2024 00:46:35 +0200 Subject: [PATCH 92/98] add eta variables to star data --- .../STAR_2009_1JET_200GEV/filter.py | 26 ++-- .../STAR_2009_2JET_200GEV/kinematics_A.yaml | 50 ++++++- .../STAR_2009_2JET_200GEV/kinematics_B.yaml | 70 +++++++++- .../STAR_2009_2JET_200GEV/kinematics_C.yaml | 70 +++++++++- .../STAR_2009_2JET_200GEV/metadata.yaml | 12 +- .../kinematics_OS.yaml | 70 +++++++++- .../kinematics_SS.yaml | 70 +++++++++- .../metadata.yaml | 8 +- .../STAR_2012_1JET_510GEV/filter.py | 51 ++++++- .../STAR_2012_2JET_510GEV/kinematics_A.yaml | 100 ++++++++++++-- .../STAR_2012_2JET_510GEV/kinematics_B.yaml | 110 +++++++++++++-- .../STAR_2012_2JET_510GEV/kinematics_C.yaml | 100 ++++++++++++-- .../STAR_2012_2JET_510GEV/kinematics_D.yaml | 110 +++++++++++++-- .../STAR_2012_2JET_510GEV/metadata.yaml | 16 ++- .../STAR_2013_1JET_510GEV/filter.py | 29 +++- .../STAR_2013_2JET_510GEV/kinematics_A.yaml | 120 ++++++++++++++-- .../STAR_2013_2JET_510GEV/kinematics_B.yaml | 130 ++++++++++++++++-- .../STAR_2013_2JET_510GEV/kinematics_C.yaml | 120 ++++++++++++++-- .../STAR_2013_2JET_510GEV/kinematics_D.yaml | 120 ++++++++++++++-- .../STAR_2013_2JET_510GEV/metadata.yaml | 16 ++- .../STAR_2015_1JET_200GEV/filter.py | 36 ++++- .../kinematics_OS.yaml | 70 +++++++++- .../kinematics_SS.yaml | 70 +++++++++- .../metadata.yaml | 8 +- 24 files changed, 1403 insertions(+), 179 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index a2703b3db3..9f85dfe8c9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -16,8 +16,10 @@ YEAR = 2009 HERE = pathlib.Path(__file__).parent - -DIJET_TOPO_DEF = { +# NOTE: this is not the full relevant as the observable is symmetric +# for jet1 and jet2, so 1 and 2 are not ordered in pT and the +# information about the sign in missing. +TOPO_DEF = { "B": {"eta1_min": -0.8, "eta1_max": 0, "eta2_min": 0.8, "eta2_max": 1.8}, "C": {"eta1_min": 0, "eta1_max": 0.8, "eta2_min": 0.8, "eta2_max": 1.8}, "A": {"eta1_min": 0.8, "eta1_max": 1.8, "eta2_min": 0.8, "eta2_max": 1.8}, @@ -63,14 +65,14 @@ def read_1jet_data(topology): # dfc.loc[binx, biny] = dfc_col.loc[i, "val"] # dfc = dfc.astype("float") - df["abs_eta_min"] = DIJET_TOPO_DEF[topology]["abs_eta_min"] - df["abs_eta_max"] = DIJET_TOPO_DEF[topology]["abs_eta_max"] + df["abs_eta_min"] = TOPO_DEF[topology]["abs_eta_min"] + df["abs_eta_max"] = TOPO_DEF[topology]["abs_eta_max"] + df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 df["stat"] = df["stat_max"] df["sys"] = df["sys_max"] df["pol"] = POL_UNC * abs(df["ALL"]) df["lumi"] = LUMI_UNC df["sqrts"] = 200 - df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 return df @@ -104,10 +106,10 @@ def read_2jet_data(topology): ignore_index=True, ) df["m"] = (df["m_low"] + df["m_high"]) / 2 - df["eta1_min"] = DIJET_TOPO_DEF[topology]["eta1_min"] - df["eta1_max"] = DIJET_TOPO_DEF[topology]["eta1_max"] - df["eta2_min"] = DIJET_TOPO_DEF[topology]["eta2_min"] - df["eta2_max"] = DIJET_TOPO_DEF[topology]["eta2_max"] + df["eta1_min"] = TOPO_DEF[topology]["eta1_min"] + df["eta1_max"] = TOPO_DEF[topology]["eta1_max"] + df["eta2_min"] = TOPO_DEF[topology]["eta2_min"] + df["eta2_max"] = TOPO_DEF[topology]["eta2_max"] df["eta1"] = (df["eta1_min"] + df["eta1_max"]) / 2 df["eta2"] = (df["eta2_min"] + df["eta2_max"]) / 2 else: @@ -124,8 +126,8 @@ def read_2jet_data(topology): "ALL": [Gsub[i]["value"]], "stat": [Gsub[i]["errors"][0]["symerror"]], "sys": [Gsub[i]["errors"][1]["symerror"]], - "abs_eta_min": DIJET_TOPO_DEF[topology]["abs_eta_min"], - "abs_eta_max": DIJET_TOPO_DEF[topology]["abs_eta_max"], + "abs_eta_min": TOPO_DEF[topology]["abs_eta_min"], + "abs_eta_max": TOPO_DEF[topology]["abs_eta_max"], } ), ], @@ -240,7 +242,7 @@ def write_2jet_data(df, topology, art_sys): "max": float(df.loc[i, "eta1_max"]), }, } - except: + except KeyError: df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 kin_value = { "m_jj": {"min": None, "mid": float(df.loc[i, "m"]), "max": None}, diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml index 23089be979..e138d46f01 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- eta_1: + max: 1.8 + mid: 1.3 + min: 0.8 + eta_2: + max: 1.8 + mid: 1.3 + min: 0.8 + m_jj: max: 19.38 mid: 18.5 min: 17.62 @@ -7,7 +15,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 1.8 + mid: 1.3 + min: 0.8 + eta_2: + max: 1.8 + mid: 1.3 + min: 0.8 + m_jj: max: 22.9 mid: 21.7 min: 20.5 @@ -15,7 +31,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 1.8 + mid: 1.3 + min: 0.8 + eta_2: + max: 1.8 + mid: 1.3 + min: 0.8 + m_jj: max: 27.59 mid: 26.310000000000002 min: 25.03 @@ -23,7 +47,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 1.8 + mid: 1.3 + min: 0.8 + eta_2: + max: 1.8 + mid: 1.3 + min: 0.8 + m_jj: max: 33.48 mid: 31.74 min: 30.0 @@ -31,7 +63,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 1.8 + mid: 1.3 + min: 0.8 + eta_2: + max: 1.8 + mid: 1.3 + min: 0.8 + m_jj: max: 40.39 mid: 38.879999999999995 min: 37.37 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml index a895b8bdcd..a7e4f147bb 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- eta_1: + max: 0.0 + mid: -0.4 + min: -0.8 + eta_2: + max: 0.0 + mid: -0.4 + min: -0.8 + m_jj: max: 19.82 mid: 18.439999999999998 min: 17.06 @@ -7,7 +15,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.0 + mid: -0.4 + min: -0.8 + eta_2: + max: 0.0 + mid: -0.4 + min: -0.8 + m_jj: max: 23.1 mid: 22.11 min: 21.12 @@ -15,7 +31,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.0 + mid: -0.4 + min: -0.8 + eta_2: + max: 0.0 + mid: -0.4 + min: -0.8 + m_jj: max: 27.73 mid: 26.57 min: 25.41 @@ -23,7 +47,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.0 + mid: -0.4 + min: -0.8 + eta_2: + max: 0.0 + mid: -0.4 + min: -0.8 + m_jj: max: 33.76 mid: 32.21 min: 30.66 @@ -31,7 +63,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.0 + mid: -0.4 + min: -0.8 + eta_2: + max: 0.0 + mid: -0.4 + min: -0.8 + m_jj: max: 39.75 mid: 38.35 min: 36.95 @@ -39,7 +79,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.0 + mid: -0.4 + min: -0.8 + eta_2: + max: 0.0 + mid: -0.4 + min: -0.8 + m_jj: max: 49.66 mid: 48.01 min: 46.36 @@ -47,7 +95,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.0 + mid: -0.4 + min: -0.8 + eta_2: + max: 0.0 + mid: -0.4 + min: -0.8 + m_jj: max: 67.88 mid: 65.72999999999999 min: 63.58 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml index 27677c4568..9732669e14 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: 19.71 mid: 18.509999999999998 min: 17.31 @@ -7,7 +15,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: 22.94 mid: 21.78 min: 20.62 @@ -15,7 +31,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: 27.21 mid: 26.02 min: 24.83 @@ -23,7 +47,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: 32.16 mid: 30.79 min: 29.42 @@ -31,7 +63,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: 39.28 mid: 37.95 min: 36.62 @@ -39,7 +79,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: 47.98 mid: 46.43 min: 44.88 @@ -47,7 +95,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: 66.04 mid: 62.82000000000001 min: 59.6 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml index cd27814819..9fe0c6ce63 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml @@ -35,8 +35,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + eta_1: { description: "eta jet", label: r"$\eta_j$", units: "" } + eta_2: { description: "eta jet", label: r"$\eta_j$", units: "" } file: kinematics_A.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, eta_1, eta_2] data_central: data_A.yaml data_uncertainties: - uncertainties_A.yaml @@ -68,8 +70,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + eta_1: { description: "eta jet", label: r"$\eta_j$", units: "" } + eta_2: { description: "eta jet", label: r"$\eta_j$", units: "" } file: kinematics_B.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, eta_1, eta_2] data_central: data_B.yaml data_uncertainties: - uncertainties_B.yaml @@ -101,8 +105,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + eta_1: { description: "eta jet", label: r"$\eta_j$", units: "" } + eta_2: { description: "eta jet", label: r"$\eta_j$", units: "" } file: kinematics_C.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, eta_1, eta_2] data_central: data_C.yaml data_uncertainties: - uncertainties_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml index 58657f6130..1b03e5e1e7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 17.99 min: null @@ -7,7 +15,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 21.58 min: null @@ -15,7 +31,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 26.29 min: null @@ -23,7 +47,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 31.72 min: null @@ -31,7 +63,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 38.38 min: null @@ -39,7 +79,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 48.79 min: null @@ -47,7 +95,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 67.32 min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml index 6aa1fcc389..14509ea0f7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 17.7 min: null @@ -7,7 +15,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 21.34 min: null @@ -15,7 +31,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 26.02 min: null @@ -23,7 +47,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 31.66 min: null @@ -31,7 +63,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 38.25 min: null @@ -39,7 +79,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 48.28 min: null @@ -47,7 +95,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.4 + min: 0.0 + abs_eta_2: + max: 0.8 + mid: 0.4 + min: 0.0 + m_jj: max: null mid: 66.65 min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml index ce49c1f6e3..bf925b6b8d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -35,8 +35,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_OS.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_OS.yaml data_uncertainties: - uncertainties_OS.yaml @@ -69,8 +71,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_SS.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_SS.yaml data_uncertainties: - uncertainties_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py index e03571dedc..e9ccc7daf9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py @@ -16,13 +16,42 @@ # values from the paper https://arxiv.org/abs/1906.02740 SQRTS = 510 YEAR = 2012 -ETA_ABS = 0.9 POL_UNC = 0.066 TOPOPLOGY_LIST = ["I", "A", "B", "C", "D"] HERE = pathlib.Path(__file__).parent RAWDATA_PATH = HERE / "rawdata/" +# NOTE: the observable is symmetric for jet1 and jet2, +# so 1 and 2 are not ordered in pT. +TOPO_DEF = { + "A": { + "abs_eta1_min": 0.3, + "abs_eta1_max": 0.9, + "abs_eta2_min": 0.3, + "abs_eta2_max": 0.9, + }, + "B": { + "abs_eta1_min": 0, + "abs_eta1_max": 0.3, + "abs_eta2_min": 0.3, + "abs_eta2_max": 0.9, + }, + "C": { + "abs_eta1_min": 0, + "abs_eta1_max": 0.3, + "abs_eta2_min": 0, + "abs_eta2_max": 0.3, + }, + "D": { + "abs_eta1_min": 0.3, + "abs_eta1_max": 0.9, + "abs_eta2_min": 0.3, + "abs_eta2_max": 0.9, + }, + "I": {"abs_eta_min": 0, "abs_eta_max": 0.9}, +} + def read_1jet_data(): data_table = pathlib.Path(RAWDATA_PATH / "Figure12(Run12).csv") @@ -35,8 +64,8 @@ def read_1jet_data(): df["pT_min"] = all_data["Parton Jet $p_{T}$ [GeV/c] LOW"] df["pT_max"] = all_data["Parton Jet $p_{T}$ [GeV/c] HIGH"] df["eta"] = 0.0 - df["eta_min"] = -ETA_ABS - df["eta_max"] = +ETA_ABS + df["eta_min"] = -TOPO_DEF["I"]["abs_eta_max"] + df["eta_max"] = +TOPO_DEF["I"]["abs_eta_max"] df["sqrts"] = SQRTS df["ALL"] = all_data["Inclusive Jet $A_{LL}$"] df["stat"] = all_data["stat +"] @@ -58,6 +87,12 @@ def read_2jet_data(topology): df["mjj"] = all_data["Parton DiJet $M_{inv}$ [$GeV/c^{2}$]"] df["mjj_min"] = all_data["Parton DiJet $M_{inv}$ [$GeV/c^{2}$] LOW"] df["mjj_max"] = all_data["Parton DiJet $M_{inv}$ [$GeV/c^{2}$] HIGH"] + + for p in ["1", "2"]: + df[f"abs_eta{p}_min"] = TOPO_DEF[topology][f"abs_eta{p}_max"] + df[f"abs_eta{p}_max"] = TOPO_DEF[topology][f"abs_eta{p}_max"] + df[f"abs_eta{p}"] = (df[f"abs_eta{p}_min"] + df[f"abs_eta{p}_max"]) / 2 + df["sqrts"] = SQRTS df["ALL"] = all_data[r"DiJet $A_{LL}$"] df["stat"] = all_data[r"stat +"] @@ -203,6 +238,16 @@ def write_2jet_data(df, topology, art_sys): "max": float(df.loc[i, "mjj_max"]), }, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "abs_eta_1": { + "min": float(df.loc[i, "abs_eta1_min"]), + "mid": float(df.loc[i, "abs_eta1"]), + "max": float(df.loc[i, "abs_eta1_max"]), + }, + "abs_eta_2": { + "min": float(df.loc[i, "abs_eta2_min"]), + "mid": float(df.loc[i, "abs_eta2"]), + "max": float(df.loc[i, "abs_eta2_max"]), + }, } kin.append(kin_value) kinematics_yaml = {"bins": kin} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml index aa74b03509..e9347809b7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 19.86 mid: 19.04 min: 18.22 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 22.58 mid: 21.62 min: 20.66 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 27.46 mid: 26.380000000000003 min: 25.3 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 33.46 mid: 32.3 min: 31.14 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 39.62 mid: 38.42 min: 37.22 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 46.66 mid: 45.18 min: 43.7 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 54.97 mid: 53.42 min: 51.87 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 65.32 mid: 63.52 min: 61.72 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 77.76 mid: 75.55000000000001 min: 73.34 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 91.5 mid: 89.12 min: 86.74 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml index 069748b5f1..cfa751350a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 19.61 mid: 18.8 min: 17.99 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 22.74 mid: 21.8 min: 20.86 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 27.46 mid: 26.37 min: 25.28 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 33.31 mid: 32.24 min: 31.17 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 39.73 mid: 38.42 min: 37.11 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 47.24 mid: 45.83 min: 44.42 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 55.83 mid: 54.14 min: 52.45 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 66.0 mid: 64.17 min: 62.34 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 78.19 mid: 76.06 min: 73.93 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 92.29 mid: 89.81 min: 87.33 @@ -79,7 +159,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 110.81 mid: 107.92 min: 105.03 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml index 3249f1848e..4bd0bdfbc3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 20.62 mid: 19.81 min: 19.0 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 23.13 mid: 22.01 min: 20.89 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 27.24 mid: 26.16 min: 25.08 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 33.89 mid: 32.7 min: 31.51 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 40.05 mid: 38.71 min: 37.37 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 47.37 mid: 46.01 min: 44.65 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 55.67 mid: 53.89 min: 52.11 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 66.49 mid: 64.75 min: 63.01 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 79.42 mid: 77.15 min: 74.88 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 93.72 mid: 91.14 min: 88.56 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml index abb28d91f6..4636085044 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 22.68 mid: 20.54 min: 18.4 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 23.04 mid: 22.09 min: 21.14 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 27.29 mid: 26.31 min: 25.33 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 32.94 mid: 31.72 min: 30.5 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 39.79 mid: 38.48 min: 37.17 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 46.76 mid: 45.21 min: 43.66 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 55.84 mid: 54.150000000000006 min: 52.46 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 66.22 mid: 64.3 min: 62.38 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 78.81 mid: 76.66 min: 74.51 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 92.19 mid: 89.57 min: 86.95 @@ -79,7 +159,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 109.83 mid: 106.86 min: 103.89 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml index b9ed51871a..24c834e8f5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml @@ -35,8 +35,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_A.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_A.yaml data_uncertainties: - uncertainties_A.yaml @@ -69,8 +71,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_B.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_B.yaml data_uncertainties: - uncertainties_B.yaml @@ -103,8 +107,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_C.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_C.yaml data_uncertainties: - uncertainties_C.yaml @@ -137,8 +143,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_D.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_D.yaml data_uncertainties: - uncertainties_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py index eb4d67f8c7..58d6c4b509 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py @@ -11,6 +11,7 @@ compute_covmat, upper_triangular_to_symmetric, ) +from nnpdf_data.new_commondata.STAR_2012_1JET_510GEV.filter import TOPO_DEF # values from the paper https://arxiv.org/pdf/2110.11020.pdf SQRTS = 510 @@ -18,7 +19,7 @@ POL_UNC = 0.064 LUMI_UNC = 0.00047 YEAR = 2013 -TOPOPLOGY_LIST = ["1JET", "A", "B", "C", "D"] +TOPOPLOGY_LIST = ["I", "A", "B", "C", "D"] HERE = pathlib.Path(__file__).parent RAWDATA_PATH = HERE / "rawdata/" @@ -43,8 +44,8 @@ def read_1jet_data(): parton_jet_data[r"Parton Jet $p_{T}$ (GeV/$c$)"] + parton_jet_data["syst +"] ) df["eta"] = 0.0 - df["eta_min"] = -ETA_ABS - df["eta_max"] = +ETA_ABS + df["eta_min"] = -TOPO_DEF["I"]["abs_eta_max"] + df["eta_max"] = +TOPO_DEF["I"]["abs_eta_max"] df["sqrts"] = SQRTS df["ALL"] = all_data[r"Inclusive Jet $A_{LL}$"] df["stat"] = all_data[r"stat +"] @@ -73,6 +74,12 @@ def read_2jet_data(topology): df["mjj_max"] = ( mjj_data[r"Parton Dijet $M_{inv}$ (GeV/$c^{2}$)"] + mjj_data["syst +"] ) + + for p in ["1", "2"]: + df[f"abs_eta{p}_min"] = TOPO_DEF[topology][f"abs_eta{p}_max"] + df[f"abs_eta{p}_max"] = TOPO_DEF[topology][f"abs_eta{p}_max"] + df[f"abs_eta{p}"] = (df[f"abs_eta{p}_min"] + df[f"abs_eta{p}_max"]) / 2 + df["sqrts"] = SQRTS df["ALL"] = all_data[r"Dijet $A_{LL}$, topology " + topology] df["stat"] = all_data[r"stat +"] @@ -85,7 +92,7 @@ def read_2jet_data(topology): def get_correlation_label(a): - if a == "1JET": + if a == "I": return "Inclusivejet" return f"Dijettopology{a}" @@ -212,6 +219,16 @@ def write_2jet_data(df, topology, art_sys): "max": float(df.loc[i, "mjj_max"]), }, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "abs_eta_1": { + "min": float(df.loc[i, "abs_eta1_min"]), + "mid": float(df.loc[i, "abs_eta1"]), + "max": float(df.loc[i, "abs_eta1_max"]), + }, + "abs_eta_2": { + "min": float(df.loc[i, "abs_eta2_min"]), + "mid": float(df.loc[i, "abs_eta2"]), + "max": float(df.loc[i, "abs_eta2_max"]), + }, } kin.append(kin_value) kinematics_yaml = {"bins": kin} @@ -266,7 +283,7 @@ def write_2jet_data(df, topology, art_sys): if __name__ == "__main__": # load all the data - dfs = {"1JET": read_1jet_data()} + dfs = {"I": read_1jet_data()} for topo in TOPOPLOGY_LIST[1:]: dfs[topo] = read_2jet_data(topo) @@ -289,7 +306,7 @@ def write_2jet_data(df, topology, art_sys): for topo, df in dfs.items(): ndata = ndata_dict[topo] syst = art_sys[cnt : cnt + ndata, :].tolist() - if topo == "1JET": + if topo == "I": write_1jet_data(df, syst) else: write_2jet_data(df, topo, syst) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml index 20be3d2291..19be678f81 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 17.16 mid: 15.74 min: 14.32 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 19.64 mid: 18.5 min: 17.36 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 22.91 mid: 21.96 min: 21.01 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 27.110000000000003 mid: 26.17 min: 25.23 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 32.67 mid: 31.63 min: 30.59 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 39.16 mid: 37.8 min: 36.44 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 46.1 mid: 44.75 min: 43.4 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 54.81 mid: 53.31 min: 51.81 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 65.37 mid: 63.64 min: 61.910000000000004 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 77.38 mid: 75.32 min: 73.25999999999999 @@ -79,7 +159,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 92.17 mid: 89.66 min: 87.14999999999999 @@ -87,7 +175,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 108.53 mid: 105.63 min: 102.72999999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml index 50a3d5933a..52e909021b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 16.96 mid: 15.49 min: 14.02 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 19.31 mid: 18.48 min: 17.650000000000002 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 23.08 mid: 22.33 min: 21.58 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 27.580000000000002 mid: 26.67 min: 25.76 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 33.15 mid: 32.16 min: 31.169999999999998 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 39.760000000000005 mid: 38.59 min: 37.42 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 47.06999999999999 mid: 45.66 min: 44.25 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 56.0 mid: 54.49 min: 52.980000000000004 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 66.77 mid: 65.02 min: 63.269999999999996 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 79.22999999999999 mid: 77.16 min: 75.09 @@ -79,7 +159,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 93.89999999999999 mid: 91.33 min: 88.76 @@ -87,7 +175,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 112.25 mid: 109.2 min: 106.15 @@ -95,7 +191,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 133.2 mid: 129.75 min: 126.3 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml index c11cf4363b..d4e97ff6e2 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 17.26 mid: 15.72 min: 14.18 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 19.889999999999997 mid: 18.9 min: 17.91 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 23.259999999999998 mid: 22.24 min: 21.22 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 28.12 mid: 27.14 min: 26.16 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 34.120000000000005 mid: 33.03 min: 31.94 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 40.78 mid: 39.35 min: 37.92 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 48.16 mid: 46.62 min: 45.08 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 57.45 mid: 55.74 min: 54.03 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 68.32000000000001 mid: 66.39 min: 64.46 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 81.23 mid: 78.97 min: 76.71 @@ -79,7 +159,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 97.07 mid: 94.22 min: 91.37 @@ -87,7 +175,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.3 + mid: 0.3 + min: 0.3 + abs_eta_2: + max: 0.3 + mid: 0.3 + min: 0.3 + m_jj: max: 114.7 mid: 111.48 min: 108.26 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml index 1fd76f3d0e..c0b3fc00f6 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 19.349999999999998 mid: 18.2 min: 17.05 @@ -7,7 +15,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 22.71 mid: 21.67 min: 20.630000000000003 @@ -15,7 +31,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 27.16 mid: 26.12 min: 25.080000000000002 @@ -23,7 +47,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 32.440000000000005 mid: 31.42 min: 30.400000000000002 @@ -31,7 +63,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 38.58 mid: 37.33 min: 36.08 @@ -39,7 +79,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 46.11 mid: 44.6 min: 43.09 @@ -47,7 +95,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 55.3 mid: 53.61 min: 51.92 @@ -55,7 +111,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 65.31 mid: 63.38 min: 61.45 @@ -63,7 +127,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 77.78999999999999 mid: 75.52 min: 73.25 @@ -71,7 +143,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 92.3 mid: 89.6 min: 86.89999999999999 @@ -79,7 +159,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 109.83 mid: 106.63 min: 103.42999999999999 @@ -87,7 +175,15 @@ bins: max: null mid: 510.0 min: null -- m_jj: +- abs_eta_1: + max: 0.9 + mid: 0.9 + min: 0.9 + abs_eta_2: + max: 0.9 + mid: 0.9 + min: 0.9 + m_jj: max: 130.99 mid: 127.17 min: 123.35000000000001 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml index 03b62b444e..5162c189cb 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml @@ -35,8 +35,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_A.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_A.yaml data_uncertainties: - uncertainties_A.yaml @@ -69,8 +71,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_B.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_B.yaml data_uncertainties: - uncertainties_B.yaml @@ -103,8 +107,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_C.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_C.yaml data_uncertainties: - uncertainties_C.yaml @@ -137,8 +143,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_D.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_D.yaml data_uncertainties: - uncertainties_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index a7d08351d6..eeba7ca9ea 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -18,8 +18,8 @@ YEAR = 2015 # mapping between topologies, tables and abs_eta values TOPOPLOGY_LIST = { - "CC": ("bottom", 0, 0.5), - "CF": ("top", 0.5, 1.0), + "CC": "bottom", + "CF": "top", "OS": "bottom", "SS": "top", } @@ -38,14 +38,25 @@ ("SS", "SS"): 11, } +# NOTE: this is not the full relevant as the observable is symmetric +# for jet1 and jet2, so 1 and 2 are not ordered in pT and the +# information about the sign in missing. +TOPO_DEF = { + "SS": {"abs_eta_min": 0, "abs_eta_max": 0.8}, + "OS": {"abs_eta_min": 0, "abs_eta_max": 0.8}, + "CC": {"abs_eta_min": 0, "abs_eta_max": 0.5}, + "CF": {"abs_eta_min": 0.5, "abs_eta_max": 1.0}, +} + + HERE = pathlib.Path(__file__).parent RAWDATA_PATH = HERE / "rawdata/" def read_1jet_data(topology): - table_label = TOPOPLOGY_LIST[topology][0] - max_eta = TOPOPLOGY_LIST[topology][2] - min_eta = TOPOPLOGY_LIST[topology][1] + table_label = TOPOPLOGY_LIST[topology] + max_eta = TOPO_DEF[topology]["abs_eta_max"] + min_eta = TOPO_DEF[topology]["abs_eta_min"] data_table = pathlib.Path(RAWDATA_PATH / f"Table1{table_label}.csv") with open(data_table, "r", encoding="utf-8") as file: @@ -89,6 +100,11 @@ def read_2jet_data(topology): df["mjj"] = mjj_data["Dijet invariant mass $M_{inv}$ at the parton level [GeV/$c$]"] df["mjj_min"] = df["mjj"] + mjj_data["Syst -"] df["mjj_max"] = df["mjj"] + mjj_data["Syst +"] + + df["abs_eta_min"] = TOPO_DEF[topology]["abs_eta_max"] + df["abs_eta_max"] = TOPO_DEF[topology]["abs_eta_max"] + df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 + df["sqrts"] = SQRTS df["ALL"] = all_data[r"Double spin asymmetry $A_{LL}$"] df["stat"] = all_data["Stat +"] @@ -228,6 +244,16 @@ def write_2jet_data(df, topology, art_sys): "max": float(df.loc[i, "mjj_max"]), }, "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + "abs_eta_1": { + "min": float(df.loc[i, "abs_eta_min"]), + "mid": float(df.loc[i, "abs_eta"]), + "max": float(df.loc[i, "abs_eta_max"]), + }, + "abs_eta_2": { + "min": float(df.loc[i, "abs_eta_min"]), + "mid": float(df.loc[i, "abs_eta"]), + "max": float(df.loc[i, "abs_eta_max"]), + }, } kin.append(kin_value) kinematics_yaml = {"bins": kin} diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml index de1e3b24f5..46e7556f74 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 21.1 mid: 20.48 min: 19.86 @@ -7,7 +15,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 24.24 mid: 23.65 min: 23.06 @@ -15,7 +31,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 29.19 mid: 28.5 min: 27.81 @@ -23,7 +47,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 35.17 mid: 34.38 min: 33.59 @@ -31,7 +63,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 42.300000000000004 mid: 41.38 min: 40.46 @@ -39,7 +79,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 52.33 mid: 51.25 min: 50.17 @@ -47,7 +95,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 71.27 mid: 69.96 min: 68.64999999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml index 9475f1c9e1..105c7da02a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml @@ -1,5 +1,13 @@ bins: -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 20.82 mid: 20.29 min: 19.759999999999998 @@ -7,7 +15,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 24.11 mid: 23.5 min: 22.89 @@ -15,7 +31,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 28.94 mid: 28.28 min: 27.62 @@ -23,7 +47,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 34.93 mid: 34.15 min: 33.37 @@ -31,7 +63,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 41.85 mid: 40.96 min: 40.07 @@ -39,7 +79,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 51.78 mid: 50.75 min: 49.72 @@ -47,7 +95,15 @@ bins: max: null mid: 200.0 min: null -- m_jj: +- abs_eta_1: + max: 0.8 + mid: 0.8 + min: 0.8 + abs_eta_2: + max: 0.8 + mid: 0.8 + min: 0.8 + m_jj: max: 70.42 mid: 69.11 min: 67.8 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index ea159cfc4c..39ccc5f2a7 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -35,8 +35,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_OS.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_OS.yaml data_uncertainties: - uncertainties_OS.yaml @@ -69,8 +71,10 @@ implemented_observables: label: r"$\sqrt(s)$", units: "GeV", } + abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } + abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_SS.yaml - kinematic_coverage: [m_jj, sqrts] + kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] data_central: data_SS.yaml data_uncertainties: - uncertainties_SS.yaml From 6cfdbf385b5a897fab1761856a32e4d91e373d28 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Sat, 13 Jul 2024 01:03:38 +0200 Subject: [PATCH 93/98] varius typos fixes --- .../STAR_2009_1JET_200GEV/filter.py | 6 +- .../STAR_2009_2JET_200GEV/kinematics_B.yaml | 42 +++---- .../STAR_2009_2JET_200GEV/kinematics_C.yaml | 42 +++---- .../STAR_2012_1JET_510GEV/filter.py | 2 +- .../STAR_2012_2JET_510GEV/kinematics_A.yaml | 80 +++++++------- .../STAR_2012_2JET_510GEV/kinematics_B.yaml | 88 +++++++-------- .../STAR_2012_2JET_510GEV/kinematics_C.yaml | 80 +++++++------- .../STAR_2012_2JET_510GEV/kinematics_D.yaml | 88 +++++++-------- .../STAR_2013_1JET_510GEV/filter.py | 2 +- .../STAR_2013_2JET_510GEV/kinematics_A.yaml | 96 ++++++++-------- .../STAR_2013_2JET_510GEV/kinematics_B.yaml | 104 +++++++++--------- .../STAR_2013_2JET_510GEV/kinematics_C.yaml | 96 ++++++++-------- .../STAR_2013_2JET_510GEV/kinematics_D.yaml | 96 ++++++++-------- .../STAR_2015_1JET_200GEV/filter.py | 2 +- .../kinematics_OS.yaml | 56 +++++----- .../kinematics_SS.yaml | 56 +++++----- 16 files changed, 468 insertions(+), 468 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index 9f85dfe8c9..51b0f451bf 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -237,9 +237,9 @@ def write_2jet_data(df, topology, art_sys): "max": float(df.loc[i, "eta1_max"]), }, "eta_2": { - "min": float(df.loc[i, "eta1_min"]), - "mid": float(df.loc[i, "eta1"]), - "max": float(df.loc[i, "eta1_max"]), + "min": float(df.loc[i, "eta2_min"]), + "mid": float(df.loc[i, "eta2"]), + "max": float(df.loc[i, "eta2_max"]), }, } except KeyError: diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml index a7e4f147bb..130698868f 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml @@ -4,9 +4,9 @@ bins: mid: -0.4 min: -0.8 eta_2: - max: 0.0 - mid: -0.4 - min: -0.8 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 19.82 mid: 18.439999999999998 @@ -20,9 +20,9 @@ bins: mid: -0.4 min: -0.8 eta_2: - max: 0.0 - mid: -0.4 - min: -0.8 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 23.1 mid: 22.11 @@ -36,9 +36,9 @@ bins: mid: -0.4 min: -0.8 eta_2: - max: 0.0 - mid: -0.4 - min: -0.8 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 27.73 mid: 26.57 @@ -52,9 +52,9 @@ bins: mid: -0.4 min: -0.8 eta_2: - max: 0.0 - mid: -0.4 - min: -0.8 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 33.76 mid: 32.21 @@ -68,9 +68,9 @@ bins: mid: -0.4 min: -0.8 eta_2: - max: 0.0 - mid: -0.4 - min: -0.8 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 39.75 mid: 38.35 @@ -84,9 +84,9 @@ bins: mid: -0.4 min: -0.8 eta_2: - max: 0.0 - mid: -0.4 - min: -0.8 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 49.66 mid: 48.01 @@ -100,9 +100,9 @@ bins: mid: -0.4 min: -0.8 eta_2: - max: 0.0 - mid: -0.4 - min: -0.8 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 67.88 mid: 65.72999999999999 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml index 9732669e14..df13c3d8a1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml @@ -4,9 +4,9 @@ bins: mid: 0.4 min: 0.0 eta_2: - max: 0.8 - mid: 0.4 - min: 0.0 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 19.71 mid: 18.509999999999998 @@ -20,9 +20,9 @@ bins: mid: 0.4 min: 0.0 eta_2: - max: 0.8 - mid: 0.4 - min: 0.0 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 22.94 mid: 21.78 @@ -36,9 +36,9 @@ bins: mid: 0.4 min: 0.0 eta_2: - max: 0.8 - mid: 0.4 - min: 0.0 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 27.21 mid: 26.02 @@ -52,9 +52,9 @@ bins: mid: 0.4 min: 0.0 eta_2: - max: 0.8 - mid: 0.4 - min: 0.0 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 32.16 mid: 30.79 @@ -68,9 +68,9 @@ bins: mid: 0.4 min: 0.0 eta_2: - max: 0.8 - mid: 0.4 - min: 0.0 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 39.28 mid: 37.95 @@ -84,9 +84,9 @@ bins: mid: 0.4 min: 0.0 eta_2: - max: 0.8 - mid: 0.4 - min: 0.0 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 47.98 mid: 46.43 @@ -100,9 +100,9 @@ bins: mid: 0.4 min: 0.0 eta_2: - max: 0.8 - mid: 0.4 - min: 0.0 + max: 1.8 + mid: 1.3 + min: 0.8 m_jj: max: 66.04 mid: 62.82000000000001 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py index e9ccc7daf9..6cdbd85c9d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py @@ -89,7 +89,7 @@ def read_2jet_data(topology): df["mjj_max"] = all_data["Parton DiJet $M_{inv}$ [$GeV/c^{2}$] HIGH"] for p in ["1", "2"]: - df[f"abs_eta{p}_min"] = TOPO_DEF[topology][f"abs_eta{p}_max"] + df[f"abs_eta{p}_min"] = TOPO_DEF[topology][f"abs_eta{p}_min"] df[f"abs_eta{p}_max"] = TOPO_DEF[topology][f"abs_eta{p}_max"] df[f"abs_eta{p}"] = (df[f"abs_eta{p}_min"] + df[f"abs_eta{p}_max"]) / 2 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml index e9347809b7..8fdbf6618e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 19.86 mid: 19.04 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 22.58 mid: 21.62 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 27.46 mid: 26.380000000000003 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 33.46 mid: 32.3 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 39.62 mid: 38.42 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 46.66 mid: 45.18 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 54.97 mid: 53.42 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 65.32 mid: 63.52 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 77.76 mid: 75.55000000000001 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 91.5 mid: 89.12 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml index cfa751350a..822d45d812 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 19.61 mid: 18.8 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 22.74 mid: 21.8 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 27.46 mid: 26.37 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 33.31 mid: 32.24 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 39.73 mid: 38.42 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 47.24 mid: 45.83 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 55.83 mid: 54.14 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 66.0 mid: 64.17 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 78.19 mid: 76.06 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 92.29 mid: 89.81 @@ -161,12 +161,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 110.81 mid: 107.92 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml index 4bd0bdfbc3..f53d1d79c8 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 20.62 mid: 19.81 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 23.13 mid: 22.01 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 27.24 mid: 26.16 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 33.89 mid: 32.7 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 40.05 mid: 38.71 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 47.37 mid: 46.01 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 55.67 mid: 53.89 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 66.49 mid: 64.75 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 79.42 mid: 77.15 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 93.72 mid: 91.14 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml index 4636085044..d37026f003 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 22.68 mid: 20.54 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 23.04 mid: 22.09 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 27.29 mid: 26.31 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 32.94 mid: 31.72 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 39.79 mid: 38.48 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 46.76 mid: 45.21 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 55.84 mid: 54.150000000000006 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 66.22 mid: 64.3 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 78.81 mid: 76.66 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 92.19 mid: 89.57 @@ -161,12 +161,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 109.83 mid: 106.86 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py index 58d6c4b509..767303d341 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py @@ -76,7 +76,7 @@ def read_2jet_data(topology): ) for p in ["1", "2"]: - df[f"abs_eta{p}_min"] = TOPO_DEF[topology][f"abs_eta{p}_max"] + df[f"abs_eta{p}_min"] = TOPO_DEF[topology][f"abs_eta{p}_min"] df[f"abs_eta{p}_max"] = TOPO_DEF[topology][f"abs_eta{p}_max"] df[f"abs_eta{p}"] = (df[f"abs_eta{p}_min"] + df[f"abs_eta{p}_max"]) / 2 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml index 19be678f81..c9bf9779e0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 17.16 mid: 15.74 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 19.64 mid: 18.5 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 22.91 mid: 21.96 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 27.110000000000003 mid: 26.17 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 32.67 mid: 31.63 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 39.16 mid: 37.8 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 46.1 mid: 44.75 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 54.81 mid: 53.31 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 65.37 mid: 63.64 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 77.38 mid: 75.32 @@ -161,12 +161,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 92.17 mid: 89.66 @@ -177,12 +177,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 108.53 mid: 105.63 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml index 52e909021b..97c0332a04 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 16.96 mid: 15.49 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 19.31 mid: 18.48 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 23.08 mid: 22.33 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 27.580000000000002 mid: 26.67 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 33.15 mid: 32.16 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 39.760000000000005 mid: 38.59 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 47.06999999999999 mid: 45.66 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 56.0 mid: 54.49 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 66.77 mid: 65.02 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 79.22999999999999 mid: 77.16 @@ -161,12 +161,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 93.89999999999999 mid: 91.33 @@ -177,12 +177,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 112.25 mid: 109.2 @@ -193,12 +193,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 133.2 mid: 129.75 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml index d4e97ff6e2..7cc7d58977 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 17.26 mid: 15.72 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 19.889999999999997 mid: 18.9 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 23.259999999999998 mid: 22.24 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 28.12 mid: 27.14 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 34.120000000000005 mid: 33.03 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 40.78 mid: 39.35 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 48.16 mid: 46.62 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 57.45 mid: 55.74 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 68.32000000000001 mid: 66.39 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 81.23 mid: 78.97 @@ -161,12 +161,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 97.07 mid: 94.22 @@ -177,12 +177,12 @@ bins: min: null - abs_eta_1: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 abs_eta_2: max: 0.3 - mid: 0.3 - min: 0.3 + mid: 0.15 + min: 0.0 m_jj: max: 114.7 mid: 111.48 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml index c0b3fc00f6..fce33b81ae 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 19.349999999999998 mid: 18.2 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 22.71 mid: 21.67 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 27.16 mid: 26.12 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 32.440000000000005 mid: 31.42 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 38.58 mid: 37.33 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 46.11 mid: 44.6 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 55.3 mid: 53.61 @@ -113,12 +113,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 65.31 mid: 63.38 @@ -129,12 +129,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 77.78999999999999 mid: 75.52 @@ -145,12 +145,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 92.3 mid: 89.6 @@ -161,12 +161,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 109.83 mid: 106.63 @@ -177,12 +177,12 @@ bins: min: null - abs_eta_1: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 abs_eta_2: max: 0.9 - mid: 0.9 - min: 0.9 + mid: 0.6 + min: 0.3 m_jj: max: 130.99 mid: 127.17 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index eeba7ca9ea..2f812d9ae3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -101,7 +101,7 @@ def read_2jet_data(topology): df["mjj_min"] = df["mjj"] + mjj_data["Syst -"] df["mjj_max"] = df["mjj"] + mjj_data["Syst +"] - df["abs_eta_min"] = TOPO_DEF[topology]["abs_eta_max"] + df["abs_eta_min"] = TOPO_DEF[topology]["abs_eta_min"] df["abs_eta_max"] = TOPO_DEF[topology]["abs_eta_max"] df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml index 46e7556f74..b23acc1713 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 21.1 mid: 20.48 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 24.24 mid: 23.65 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 29.19 mid: 28.5 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 35.17 mid: 34.38 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 42.300000000000004 mid: 41.38 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 52.33 mid: 51.25 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 71.27 mid: 69.96 diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml index 105c7da02a..5eda6b0240 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml @@ -1,12 +1,12 @@ bins: - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 20.82 mid: 20.29 @@ -17,12 +17,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 24.11 mid: 23.5 @@ -33,12 +33,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 28.94 mid: 28.28 @@ -49,12 +49,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 34.93 mid: 34.15 @@ -65,12 +65,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 41.85 mid: 40.96 @@ -81,12 +81,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 51.78 mid: 50.75 @@ -97,12 +97,12 @@ bins: min: null - abs_eta_1: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 abs_eta_2: max: 0.8 - mid: 0.8 - min: 0.8 + mid: 0.4 + min: 0.0 m_jj: max: 70.42 mid: 69.11 From 03bdb010aad8ea162746cfa8a8dbcc795977d9cf Mon Sep 17 00:00:00 2001 From: Giacomo Magni Date: Sun, 14 Jul 2024 23:27:27 +0200 Subject: [PATCH 94/98] some fixes to metadata --- .../STAR_2009_2JET_200GEV/metadata.yaml | 12 +++++++++--- .../STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml | 2 ++ .../STAR_2012_2JET_510GEV/metadata.yaml | 4 ++++ .../STAR_2013_2JET_510GEV/metadata.yaml | 4 ++++ .../STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml | 2 ++ 5 files changed, 21 insertions(+), 3 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml index 9fe0c6ce63..de2d2ff67c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml @@ -50,7 +50,9 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_200GEV_A-ALL + - - STAR_2009_2JET_200GEV_A-ALL-POL + - - STAR_2009_2JET_200GEV_A-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology B", @@ -85,7 +87,9 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_200GEV_B-ALL + - - STAR_2009_2JET_200GEV_B-ALL-POL + - - STAR_2009_2JET_200GEV_B-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology C", @@ -120,4 +124,6 @@ implemented_observables: y_label: "$A_{LL}$" theory: FK_tables: - - - STAR_2009_2JET_200GEV_C-ALL \ No newline at end of file + - - STAR_2009_2JET_200GEV_C-ALL-POL + - - STAR_2009_2JET_200GEV_C-ALL-UNPOL + operation: "ratio" \ No newline at end of file diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml index bf925b6b8d..27eff73545 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -52,6 +52,7 @@ implemented_observables: FK_tables: - - STAR_2009_2JET_MIDRAP_200GEV_OS-ALL-POL - - STAR_2009_2JET_MIDRAP_200GEV_OS-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, SS", @@ -88,3 +89,4 @@ implemented_observables: FK_tables: - - STAR_2009_2JET_MIDRAP_200GEV_SS-ALL-POL - - STAR_2009_2JET_MIDRAP_200GEV_SS-ALL-UNPOL + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml index 24c834e8f5..1599129e76 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml @@ -52,6 +52,7 @@ implemented_observables: FK_tables: - - STAR_2012_2JET_510GEV_A-ALL-POL - - STAR_2012_2JET_510GEV_A-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology B", @@ -88,6 +89,7 @@ implemented_observables: FK_tables: - - STAR_2012_2JET_510GEV_B-ALL-POL - - STAR_2012_2JET_510GEV_B-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology C", @@ -124,6 +126,7 @@ implemented_observables: FK_tables: - - STAR_2012_2JET_510GEV_C-ALL-POL - - STAR_2012_2JET_510GEV_C-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology D", @@ -160,3 +163,4 @@ implemented_observables: FK_tables: - - STAR_2012_2JET_510GEV_D-ALL-POL - - STAR_2012_2JET_510GEV_D-ALL-UNPOL + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml index 5162c189cb..90b0b54a9e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml @@ -52,6 +52,7 @@ implemented_observables: FK_tables: - - STAR_2013_2JET_510GEV_A-ALL-POL - - STAR_2013_2JET_510GEV_A-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology B", @@ -88,6 +89,7 @@ implemented_observables: FK_tables: - - STAR_2013_2JET_510GEV_B-ALL-POL - - STAR_2013_2JET_510GEV_B-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology C", @@ -124,6 +126,7 @@ implemented_observables: FK_tables: - - STAR_2013_2JET_510GEV_C-ALL-POL - - STAR_2013_2JET_510GEV_C-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, topology D", @@ -160,3 +163,4 @@ implemented_observables: FK_tables: - - STAR_2013_2JET_510GEV_D-ALL-POL - - STAR_2013_2JET_510GEV_D-ALL-UNPOL + operation: "ratio" diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index 39ccc5f2a7..06457ba09c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -52,6 +52,7 @@ implemented_observables: FK_tables: - - STAR_2015_2JET_MIDRAP_200GEV_OS-ALL-POL - - STAR_2015_2JET_MIDRAP_200GEV_OS-ALL-UNPOL + operation: "ratio" - observable: { description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", @@ -88,3 +89,4 @@ implemented_observables: FK_tables: - - STAR_2015_2JET_MIDRAP_200GEV_SS-ALL-POL - - STAR_2015_2JET_MIDRAP_200GEV_SS-ALL-UNPOL + operation: "ratio" From c2d94019a853f980b122e519e17e98f014243799 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 16 Jul 2024 00:25:56 +0200 Subject: [PATCH 95/98] remove sqrts from dijets --- .../STAR_2009_1JET_200GEV/filter.py | 4 +- .../STAR_2009_2JET_200GEV/kinematics_A.yaml | 20 ------- .../STAR_2009_2JET_200GEV/kinematics_B.yaml | 28 ---------- .../STAR_2009_2JET_200GEV/kinematics_C.yaml | 28 ---------- .../STAR_2009_2JET_200GEV/metadata.yaml | 42 +++++++------- .../kinematics_OS.yaml | 28 ---------- .../kinematics_SS.yaml | 28 ---------- .../metadata.yaml | 28 +++++----- .../STAR_2012_1JET_510GEV/filter.py | 2 +- .../STAR_2012_2JET_510GEV/kinematics_A.yaml | 40 ------------- .../STAR_2012_2JET_510GEV/kinematics_B.yaml | 44 --------------- .../STAR_2012_2JET_510GEV/kinematics_C.yaml | 40 ------------- .../STAR_2012_2JET_510GEV/kinematics_D.yaml | 44 --------------- .../STAR_2012_2JET_510GEV/metadata.yaml | 56 +++++++++---------- .../STAR_2013_1JET_510GEV/filter.py | 2 +- .../STAR_2013_2JET_510GEV/kinematics_A.yaml | 48 ---------------- .../STAR_2013_2JET_510GEV/kinematics_B.yaml | 52 ----------------- .../STAR_2013_2JET_510GEV/kinematics_C.yaml | 48 ---------------- .../STAR_2013_2JET_510GEV/kinematics_D.yaml | 48 ---------------- .../STAR_2013_2JET_510GEV/metadata.yaml | 56 +++++++++---------- .../STAR_2015_1JET_200GEV/filter.py | 2 +- .../kinematics_OS.yaml | 28 ---------- .../kinematics_SS.yaml | 28 ---------- .../metadata.yaml | 28 +++++----- 24 files changed, 110 insertions(+), 662 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py index 51b0f451bf..eaaccbadda 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_1JET_200GEV/filter.py @@ -230,7 +230,7 @@ def write_2jet_data(df, topology, art_sys): "mid": float(df.loc[i, "m"]), "max": float(df.loc[i, "m_high"]), }, - "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + # "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, "eta_1": { "min": float(df.loc[i, "eta1_min"]), "mid": float(df.loc[i, "eta1"]), @@ -246,7 +246,7 @@ def write_2jet_data(df, topology, art_sys): df["abs_eta"] = (df["abs_eta_min"] + df["abs_eta_max"]) / 2 kin_value = { "m_jj": {"min": None, "mid": float(df.loc[i, "m"]), "max": None}, - "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + # "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, "abs_eta_1": { "min": float(df.loc[i, "abs_eta_min"]), "mid": float(df.loc[i, "abs_eta"]), diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml index e138d46f01..9f24498bec 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_A.yaml @@ -11,10 +11,6 @@ bins: max: 19.38 mid: 18.5 min: 17.62 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 1.8 mid: 1.3 @@ -27,10 +23,6 @@ bins: max: 22.9 mid: 21.7 min: 20.5 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 1.8 mid: 1.3 @@ -43,10 +35,6 @@ bins: max: 27.59 mid: 26.310000000000002 min: 25.03 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 1.8 mid: 1.3 @@ -59,10 +47,6 @@ bins: max: 33.48 mid: 31.74 min: 30.0 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 1.8 mid: 1.3 @@ -75,7 +59,3 @@ bins: max: 40.39 mid: 38.879999999999995 min: 37.37 - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml index 130698868f..462e9c811c 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_B.yaml @@ -11,10 +11,6 @@ bins: max: 19.82 mid: 18.439999999999998 min: 17.06 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.0 mid: -0.4 @@ -27,10 +23,6 @@ bins: max: 23.1 mid: 22.11 min: 21.12 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.0 mid: -0.4 @@ -43,10 +35,6 @@ bins: max: 27.73 mid: 26.57 min: 25.41 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.0 mid: -0.4 @@ -59,10 +47,6 @@ bins: max: 33.76 mid: 32.21 min: 30.66 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.0 mid: -0.4 @@ -75,10 +59,6 @@ bins: max: 39.75 mid: 38.35 min: 36.95 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.0 mid: -0.4 @@ -91,10 +71,6 @@ bins: max: 49.66 mid: 48.01 min: 46.36 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.0 mid: -0.4 @@ -107,7 +83,3 @@ bins: max: 67.88 mid: 65.72999999999999 min: 63.58 - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml index df13c3d8a1..1351f99837 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/kinematics_C.yaml @@ -11,10 +11,6 @@ bins: max: 19.71 mid: 18.509999999999998 min: 17.31 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.8 mid: 0.4 @@ -27,10 +23,6 @@ bins: max: 22.94 mid: 21.78 min: 20.62 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.8 mid: 0.4 @@ -43,10 +35,6 @@ bins: max: 27.21 mid: 26.02 min: 24.83 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.8 mid: 0.4 @@ -59,10 +47,6 @@ bins: max: 32.16 mid: 30.79 min: 29.42 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.8 mid: 0.4 @@ -75,10 +59,6 @@ bins: max: 39.28 mid: 37.95 min: 36.62 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.8 mid: 0.4 @@ -91,10 +71,6 @@ bins: max: 47.98 mid: 46.43 min: 44.88 - sqrts: - max: null - mid: 200.0 - min: null - eta_1: max: 0.8 mid: 0.4 @@ -107,7 +83,3 @@ bins: max: 66.04 mid: 62.82000000000001 min: 59.6 - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml index de2d2ff67c..14289e5a5a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_200GEV/metadata.yaml @@ -29,16 +29,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } eta_1: { description: "eta jet", label: r"$\eta_j$", units: "" } eta_2: { description: "eta jet", label: r"$\eta_j$", units: "" } file: kinematics_A.yaml - kinematic_coverage: [m_jj, sqrts, eta_1, eta_2] + kinematic_coverage: [m_jj, eta_1, eta_2] data_central: data_A.yaml data_uncertainties: - uncertainties_A.yaml @@ -66,16 +66,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } eta_1: { description: "eta jet", label: r"$\eta_j$", units: "" } eta_2: { description: "eta jet", label: r"$\eta_j$", units: "" } file: kinematics_B.yaml - kinematic_coverage: [m_jj, sqrts, eta_1, eta_2] + kinematic_coverage: [m_jj, eta_1, eta_2] data_central: data_B.yaml data_uncertainties: - uncertainties_B.yaml @@ -103,16 +103,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } eta_1: { description: "eta jet", label: r"$\eta_j$", units: "" } eta_2: { description: "eta jet", label: r"$\eta_j$", units: "" } file: kinematics_C.yaml - kinematic_coverage: [m_jj, sqrts, eta_1, eta_2] + kinematic_coverage: [m_jj, eta_1, eta_2] data_central: data_C.yaml data_uncertainties: - uncertainties_C.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml index 1b03e5e1e7..7ad694d6b5 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_OS.yaml @@ -11,10 +11,6 @@ bins: max: null mid: 17.99 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -27,10 +23,6 @@ bins: max: null mid: 21.58 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -43,10 +35,6 @@ bins: max: null mid: 26.29 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -59,10 +47,6 @@ bins: max: null mid: 31.72 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -75,10 +59,6 @@ bins: max: null mid: 38.38 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -91,10 +71,6 @@ bins: max: null mid: 48.79 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -107,7 +83,3 @@ bins: max: null mid: 67.32 min: null - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml index 14509ea0f7..cc0479a1c9 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/kinematics_SS.yaml @@ -11,10 +11,6 @@ bins: max: null mid: 17.7 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -27,10 +23,6 @@ bins: max: null mid: 21.34 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -43,10 +35,6 @@ bins: max: null mid: 26.02 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -59,10 +47,6 @@ bins: max: null mid: 31.66 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -75,10 +59,6 @@ bins: max: null mid: 38.25 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -91,10 +71,6 @@ bins: max: null mid: 48.28 min: null - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -107,7 +83,3 @@ bins: max: null mid: 66.65 min: null - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml index 27eff73545..25437191bd 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -29,16 +29,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_OS.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_OS.yaml data_uncertainties: - uncertainties_OS.yaml @@ -66,16 +66,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_SS.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_SS.yaml data_uncertainties: - uncertainties_SS.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py index 6cdbd85c9d..ff41a0d9e1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_1JET_510GEV/filter.py @@ -237,7 +237,7 @@ def write_2jet_data(df, topology, art_sys): "mid": float(df.loc[i, "mjj"]), "max": float(df.loc[i, "mjj_max"]), }, - "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + # "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, "abs_eta_1": { "min": float(df.loc[i, "abs_eta1_min"]), "mid": float(df.loc[i, "abs_eta1"]), diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml index 8fdbf6618e..50c243e4c3 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_A.yaml @@ -11,10 +11,6 @@ bins: max: 19.86 mid: 19.04 min: 18.22 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -27,10 +23,6 @@ bins: max: 22.58 mid: 21.62 min: 20.66 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -43,10 +35,6 @@ bins: max: 27.46 mid: 26.380000000000003 min: 25.3 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -59,10 +47,6 @@ bins: max: 33.46 mid: 32.3 min: 31.14 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -75,10 +59,6 @@ bins: max: 39.62 mid: 38.42 min: 37.22 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -91,10 +71,6 @@ bins: max: 46.66 mid: 45.18 min: 43.7 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -107,10 +83,6 @@ bins: max: 54.97 mid: 53.42 min: 51.87 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -123,10 +95,6 @@ bins: max: 65.32 mid: 63.52 min: 61.72 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -139,10 +107,6 @@ bins: max: 77.76 mid: 75.55000000000001 min: 73.34 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -155,7 +119,3 @@ bins: max: 91.5 mid: 89.12 min: 86.74 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml index 822d45d812..1c66a3548a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_B.yaml @@ -11,10 +11,6 @@ bins: max: 19.61 mid: 18.8 min: 17.99 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -27,10 +23,6 @@ bins: max: 22.74 mid: 21.8 min: 20.86 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -43,10 +35,6 @@ bins: max: 27.46 mid: 26.37 min: 25.28 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -59,10 +47,6 @@ bins: max: 33.31 mid: 32.24 min: 31.17 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -75,10 +59,6 @@ bins: max: 39.73 mid: 38.42 min: 37.11 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -91,10 +71,6 @@ bins: max: 47.24 mid: 45.83 min: 44.42 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -107,10 +83,6 @@ bins: max: 55.83 mid: 54.14 min: 52.45 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -123,10 +95,6 @@ bins: max: 66.0 mid: 64.17 min: 62.34 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -139,10 +107,6 @@ bins: max: 78.19 mid: 76.06 min: 73.93 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -155,10 +119,6 @@ bins: max: 92.29 mid: 89.81 min: 87.33 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -171,7 +131,3 @@ bins: max: 110.81 mid: 107.92 min: 105.03 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml index f53d1d79c8..3ae84e0b49 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_C.yaml @@ -11,10 +11,6 @@ bins: max: 20.62 mid: 19.81 min: 19.0 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -27,10 +23,6 @@ bins: max: 23.13 mid: 22.01 min: 20.89 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -43,10 +35,6 @@ bins: max: 27.24 mid: 26.16 min: 25.08 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -59,10 +47,6 @@ bins: max: 33.89 mid: 32.7 min: 31.51 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -75,10 +59,6 @@ bins: max: 40.05 mid: 38.71 min: 37.37 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -91,10 +71,6 @@ bins: max: 47.37 mid: 46.01 min: 44.65 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -107,10 +83,6 @@ bins: max: 55.67 mid: 53.89 min: 52.11 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -123,10 +95,6 @@ bins: max: 66.49 mid: 64.75 min: 63.01 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -139,10 +107,6 @@ bins: max: 79.42 mid: 77.15 min: 74.88 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -155,7 +119,3 @@ bins: max: 93.72 mid: 91.14 min: 88.56 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml index d37026f003..4a58097629 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/kinematics_D.yaml @@ -11,10 +11,6 @@ bins: max: 22.68 mid: 20.54 min: 18.4 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -27,10 +23,6 @@ bins: max: 23.04 mid: 22.09 min: 21.14 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -43,10 +35,6 @@ bins: max: 27.29 mid: 26.31 min: 25.33 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -59,10 +47,6 @@ bins: max: 32.94 mid: 31.72 min: 30.5 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -75,10 +59,6 @@ bins: max: 39.79 mid: 38.48 min: 37.17 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -91,10 +71,6 @@ bins: max: 46.76 mid: 45.21 min: 43.66 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -107,10 +83,6 @@ bins: max: 55.84 mid: 54.150000000000006 min: 52.46 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -123,10 +95,6 @@ bins: max: 66.22 mid: 64.3 min: 62.38 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -139,10 +107,6 @@ bins: max: 78.81 mid: 76.66 min: 74.51 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -155,10 +119,6 @@ bins: max: 92.19 mid: 89.57 min: 86.95 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -171,7 +131,3 @@ bins: max: 109.83 mid: 106.86 min: 103.89 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml index 1599129e76..c08e5f0256 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2012_2JET_510GEV/metadata.yaml @@ -29,16 +29,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_A.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_A.yaml data_uncertainties: - uncertainties_A.yaml @@ -66,16 +66,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_B.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_B.yaml data_uncertainties: - uncertainties_B.yaml @@ -103,16 +103,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_C.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_C.yaml data_uncertainties: - uncertainties_C.yaml @@ -140,16 +140,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_D.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_D.yaml data_uncertainties: - uncertainties_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py index 767303d341..bd8c787d1e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_1JET_510GEV/filter.py @@ -218,7 +218,7 @@ def write_2jet_data(df, topology, art_sys): "mid": float(df.loc[i, "mjj"]), "max": float(df.loc[i, "mjj_max"]), }, - "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + # "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, "abs_eta_1": { "min": float(df.loc[i, "abs_eta1_min"]), "mid": float(df.loc[i, "abs_eta1"]), diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml index c9bf9779e0..d9f1292209 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_A.yaml @@ -11,10 +11,6 @@ bins: max: 17.16 mid: 15.74 min: 14.32 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -27,10 +23,6 @@ bins: max: 19.64 mid: 18.5 min: 17.36 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -43,10 +35,6 @@ bins: max: 22.91 mid: 21.96 min: 21.01 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -59,10 +47,6 @@ bins: max: 27.110000000000003 mid: 26.17 min: 25.23 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -75,10 +59,6 @@ bins: max: 32.67 mid: 31.63 min: 30.59 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -91,10 +71,6 @@ bins: max: 39.16 mid: 37.8 min: 36.44 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -107,10 +83,6 @@ bins: max: 46.1 mid: 44.75 min: 43.4 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -123,10 +95,6 @@ bins: max: 54.81 mid: 53.31 min: 51.81 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -139,10 +107,6 @@ bins: max: 65.37 mid: 63.64 min: 61.910000000000004 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -155,10 +119,6 @@ bins: max: 77.38 mid: 75.32 min: 73.25999999999999 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -171,10 +131,6 @@ bins: max: 92.17 mid: 89.66 min: 87.14999999999999 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -187,7 +143,3 @@ bins: max: 108.53 mid: 105.63 min: 102.72999999999999 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml index 97c0332a04..d38da4d369 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_B.yaml @@ -11,10 +11,6 @@ bins: max: 16.96 mid: 15.49 min: 14.02 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -27,10 +23,6 @@ bins: max: 19.31 mid: 18.48 min: 17.650000000000002 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -43,10 +35,6 @@ bins: max: 23.08 mid: 22.33 min: 21.58 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -59,10 +47,6 @@ bins: max: 27.580000000000002 mid: 26.67 min: 25.76 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -75,10 +59,6 @@ bins: max: 33.15 mid: 32.16 min: 31.169999999999998 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -91,10 +71,6 @@ bins: max: 39.760000000000005 mid: 38.59 min: 37.42 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -107,10 +83,6 @@ bins: max: 47.06999999999999 mid: 45.66 min: 44.25 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -123,10 +95,6 @@ bins: max: 56.0 mid: 54.49 min: 52.980000000000004 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -139,10 +107,6 @@ bins: max: 66.77 mid: 65.02 min: 63.269999999999996 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -155,10 +119,6 @@ bins: max: 79.22999999999999 mid: 77.16 min: 75.09 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -171,10 +131,6 @@ bins: max: 93.89999999999999 mid: 91.33 min: 88.76 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -187,10 +143,6 @@ bins: max: 112.25 mid: 109.2 min: 106.15 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -203,7 +155,3 @@ bins: max: 133.2 mid: 129.75 min: 126.3 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml index 7cc7d58977..c62299f9ff 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_C.yaml @@ -11,10 +11,6 @@ bins: max: 17.26 mid: 15.72 min: 14.18 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -27,10 +23,6 @@ bins: max: 19.889999999999997 mid: 18.9 min: 17.91 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -43,10 +35,6 @@ bins: max: 23.259999999999998 mid: 22.24 min: 21.22 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -59,10 +47,6 @@ bins: max: 28.12 mid: 27.14 min: 26.16 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -75,10 +59,6 @@ bins: max: 34.120000000000005 mid: 33.03 min: 31.94 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -91,10 +71,6 @@ bins: max: 40.78 mid: 39.35 min: 37.92 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -107,10 +83,6 @@ bins: max: 48.16 mid: 46.62 min: 45.08 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -123,10 +95,6 @@ bins: max: 57.45 mid: 55.74 min: 54.03 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -139,10 +107,6 @@ bins: max: 68.32000000000001 mid: 66.39 min: 64.46 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -155,10 +119,6 @@ bins: max: 81.23 mid: 78.97 min: 76.71 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -171,10 +131,6 @@ bins: max: 97.07 mid: 94.22 min: 91.37 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.3 mid: 0.15 @@ -187,7 +143,3 @@ bins: max: 114.7 mid: 111.48 min: 108.26 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml index fce33b81ae..fed9c68a44 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/kinematics_D.yaml @@ -11,10 +11,6 @@ bins: max: 19.349999999999998 mid: 18.2 min: 17.05 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -27,10 +23,6 @@ bins: max: 22.71 mid: 21.67 min: 20.630000000000003 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -43,10 +35,6 @@ bins: max: 27.16 mid: 26.12 min: 25.080000000000002 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -59,10 +47,6 @@ bins: max: 32.440000000000005 mid: 31.42 min: 30.400000000000002 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -75,10 +59,6 @@ bins: max: 38.58 mid: 37.33 min: 36.08 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -91,10 +71,6 @@ bins: max: 46.11 mid: 44.6 min: 43.09 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -107,10 +83,6 @@ bins: max: 55.3 mid: 53.61 min: 51.92 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -123,10 +95,6 @@ bins: max: 65.31 mid: 63.38 min: 61.45 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -139,10 +107,6 @@ bins: max: 77.78999999999999 mid: 75.52 min: 73.25 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -155,10 +119,6 @@ bins: max: 92.3 mid: 89.6 min: 86.89999999999999 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -171,10 +131,6 @@ bins: max: 109.83 mid: 106.63 min: 103.42999999999999 - sqrts: - max: null - mid: 510.0 - min: null - abs_eta_1: max: 0.9 mid: 0.6 @@ -187,7 +143,3 @@ bins: max: 130.99 mid: 127.17 min: 123.35000000000001 - sqrts: - max: null - mid: 510.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml index 90b0b54a9e..3381f9db6e 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2013_2JET_510GEV/metadata.yaml @@ -29,16 +29,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_A.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_A.yaml data_uncertainties: - uncertainties_A.yaml @@ -66,16 +66,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_B.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_B.yaml data_uncertainties: - uncertainties_B.yaml @@ -103,16 +103,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_C.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_C.yaml data_uncertainties: - uncertainties_C.yaml @@ -140,16 +140,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_D.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_D.yaml data_uncertainties: - uncertainties_D.yaml diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py index 2f812d9ae3..bf90362675 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_1JET_200GEV/filter.py @@ -243,7 +243,7 @@ def write_2jet_data(df, topology, art_sys): "mid": float(df.loc[i, "mjj"]), "max": float(df.loc[i, "mjj_max"]), }, - "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, + # "sqrts": {"min": None, "mid": float(df.loc[i, "sqrts"]), "max": None}, "abs_eta_1": { "min": float(df.loc[i, "abs_eta_min"]), "mid": float(df.loc[i, "abs_eta"]), diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml index b23acc1713..4e30f535e0 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_OS.yaml @@ -11,10 +11,6 @@ bins: max: 21.1 mid: 20.48 min: 19.86 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -27,10 +23,6 @@ bins: max: 24.24 mid: 23.65 min: 23.06 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -43,10 +35,6 @@ bins: max: 29.19 mid: 28.5 min: 27.81 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -59,10 +47,6 @@ bins: max: 35.17 mid: 34.38 min: 33.59 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -75,10 +59,6 @@ bins: max: 42.300000000000004 mid: 41.38 min: 40.46 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -91,10 +71,6 @@ bins: max: 52.33 mid: 51.25 min: 50.17 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -107,7 +83,3 @@ bins: max: 71.27 mid: 69.96 min: 68.64999999999999 - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml index 5eda6b0240..c185447fb1 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/kinematics_SS.yaml @@ -11,10 +11,6 @@ bins: max: 20.82 mid: 20.29 min: 19.759999999999998 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -27,10 +23,6 @@ bins: max: 24.11 mid: 23.5 min: 22.89 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -43,10 +35,6 @@ bins: max: 28.94 mid: 28.28 min: 27.62 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -59,10 +47,6 @@ bins: max: 34.93 mid: 34.15 min: 33.37 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -75,10 +59,6 @@ bins: max: 41.85 mid: 40.96 min: 40.07 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -91,10 +71,6 @@ bins: max: 51.78 mid: 50.75 min: 49.72 - sqrts: - max: null - mid: 200.0 - min: null - abs_eta_1: max: 0.8 mid: 0.4 @@ -107,7 +83,3 @@ bins: max: 70.42 mid: 69.11 min: 67.8 - sqrts: - max: null - mid: 200.0 - min: null diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index 06457ba09c..e4f8afa66d 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -29,16 +29,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_OS.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_OS.yaml data_uncertainties: - uncertainties_OS.yaml @@ -66,16 +66,16 @@ implemented_observables: kinematics: variables: m_jj: { description: "dijet mass", label: "$m_{jj}$", units: "GeV" } - sqrts: - { - description: "center of mass energy", - label: r"$\sqrt(s)$", - units: "GeV", - } + # sqrts: + # { + # description: "center of mass energy", + # label: r"$\sqrt(s)$", + # units: "GeV", + # } abs_eta_1: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } abs_eta_2: { description: "abs eta jet", label: r"$|\eta_j|$", units: "" } file: kinematics_SS.yaml - kinematic_coverage: [m_jj, sqrts, abs_eta_1, abs_eta_2] + kinematic_coverage: [m_jj, abs_eta_1, abs_eta_2] data_central: data_SS.yaml data_uncertainties: - uncertainties_SS.yaml From 2c1feb4aa55313bcee92c7ce32946a4701335156 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 16 Jul 2024 00:32:41 +0200 Subject: [PATCH 96/98] minor fixes --- validphys2/src/validphys/commondataparser.py | 6 +++--- validphys2/src/validphys/filters.py | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/validphys2/src/validphys/commondataparser.py b/validphys2/src/validphys/commondataparser.py index f24558dda6..3fb3d3f22d 100644 --- a/validphys2/src/validphys/commondataparser.py +++ b/validphys2/src/validphys/commondataparser.py @@ -110,7 +110,7 @@ def _quick_yaml_load(filepath): "PHT": ("$\\eta_\\gamma$", "$E_{T,\\gamma}^2 (GeV^2)$", "$\\sqrt{s} (GeV)$"), "SIA": ("$z$", "$Q^2 (GeV^2)$", "$y$"), "JET_POL": ("$\\eta$", "$p_T^2 (GeV^2)$", "$\\sqrt{s} (GeV)$"), - "DIJET_POL": ("\\eta", "$\\m_{1,2} (GeV)", "$\\sqrt{s} (GeV)"), + "DIJET_POL": ("$\\m_{1,2} (GeV)", "$\\eta_1$", "$\\eta_2$"), } PROCESS_DESCRIPTION_LABEL = { @@ -135,8 +135,8 @@ def _quick_yaml_load(filepath): "EWK_MLL": "Drell-Yan Mass Distribution", "DIJET": "Dijets Invariant Mass and Rapidity Distribution", "DYP": "Fixed-Target Drell-Yan", - "JET_POL": "Longitudinal double-spin asymmetry", - "DIJET_POL": "Longitudinal double-spin asymmetry", + "JET_POL": "Inclusive Jet longitudinal double-spin asymmetry", + "DIJET_POL": "Dijets longitudinal double-spin asymmetry", } diff --git a/validphys2/src/validphys/filters.py b/validphys2/src/validphys/filters.py index 31971bc0b0..5a9a73e470 100644 --- a/validphys2/src/validphys/filters.py +++ b/validphys2/src/validphys/filters.py @@ -46,7 +46,7 @@ "HIG_RAP": ("y", "M_H2", "sqrts"), "SIA": ("z", "Q2", "y"), "JET_POL": ("eta", "pT2", "sqrts"), - "DIJET_POL": ("eta", "m_12", "sqrts"), + "DIJET_POL": ("m_12", "eta_1", "eta_2"), } From a7d8d54f7bbcb2bbb82c8e39cb8b6283b4b39706 Mon Sep 17 00:00:00 2001 From: giacomomagni Date: Tue, 16 Jul 2024 09:22:33 +0200 Subject: [PATCH 97/98] minor fix on plot labels --- .../new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml | 4 ++-- .../new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml index 25437191bd..865ad92581 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -43,7 +43,7 @@ implemented_observables: data_uncertainties: - uncertainties_OS.yaml plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, OS" + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, opposite sign $\eta$ topology" kinematics_override: identity plot_x: m_jj x_scale: log @@ -80,7 +80,7 @@ implemented_observables: data_uncertainties: - uncertainties_SS.yaml plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, SS" + dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, same sign $\eta$ topology" kinematics_override: identity plot_x: m_jj x_scale: log diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index e4f8afa66d..fb0242253b 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -43,7 +43,7 @@ implemented_observables: data_uncertainties: - uncertainties_OS.yaml plotting: - dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, opposite sign $\eta$ topology" + dataset_label: "STAR 200 GeV (2015) DIJET $A_{LL}$, opposite sign $\eta$ topology" kinematics_override: identity plot_x: m_jj x_scale: log @@ -80,7 +80,7 @@ implemented_observables: data_uncertainties: - uncertainties_SS.yaml plotting: - dataset_label: r"STAR 200 GeV (2015) DIJET $A_{LL}$, same sign $\eta$ topology" + dataset_label: "STAR 200 GeV (2015) DIJET $A_{LL}$, same sign $\eta$ topology" kinematics_override: identity plot_x: m_jj x_scale: log From 9925e4d8deebd1497d018a401a685506a56d41c7 Mon Sep 17 00:00:00 2001 From: Giacomo Magni Date: Tue, 16 Jul 2024 10:59:39 +0200 Subject: [PATCH 98/98] another attempt on plot labels, now working --- .../STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml | 8 ++++---- .../STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml | 8 ++++---- 2 files changed, 8 insertions(+), 8 deletions(-) diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml index 865ad92581..951800568a 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2009_2JET_MIDRAP_200GEV/metadata.yaml @@ -18,7 +18,7 @@ version_comment: "Initial implementation" implemented_observables: - observable: { - description: "ALL as function of $M_{inv}$, OS", + description: 'ALL as function of $M_{inv}$, opposite sign $\eta$ topology', label: "$A_{LL}$", units: "", } @@ -43,7 +43,7 @@ implemented_observables: data_uncertainties: - uncertainties_OS.yaml plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, opposite sign $\eta$ topology" + dataset_label: 'STAR 200 GeV (2009) DIJET $A_{LL}$, opposite sign $\eta$ topology' kinematics_override: identity plot_x: m_jj x_scale: log @@ -55,7 +55,7 @@ implemented_observables: operation: "ratio" - observable: { - description: "ALL as function of $M_{inv}$, SS", + description: 'ALL as function of $M_{inv}$, same sign $\eta$ topology', label: "$A_{LL}$", units: "", } @@ -80,7 +80,7 @@ implemented_observables: data_uncertainties: - uncertainties_SS.yaml plotting: - dataset_label: "STAR 200 GeV (2009) DIJET $A_{LL}$, same sign $\eta$ topology" + dataset_label: 'STAR 200 GeV (2009) DIJET $A_{LL}$, same sign $\eta$ topology' kinematics_override: identity plot_x: m_jj x_scale: log diff --git a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml index fb0242253b..8457a92e91 100644 --- a/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml +++ b/nnpdf_data/nnpdf_data/new_commondata/STAR_2015_2JET_MIDRAP_200GEV/metadata.yaml @@ -18,7 +18,7 @@ version_comment: "Initial implementation" implemented_observables: - observable: { - description: "ALL as function of $M_{inv}$, opposite sign $\eta$ topology", + description: 'ALL as function of $M_{inv}$, opposite sign $\eta$ topology', label: "$A_{LL}$", units: "", } @@ -43,7 +43,7 @@ implemented_observables: data_uncertainties: - uncertainties_OS.yaml plotting: - dataset_label: "STAR 200 GeV (2015) DIJET $A_{LL}$, opposite sign $\eta$ topology" + dataset_label: 'STAR 200 GeV (2015) DIJET $A_{LL}$, opposite sign $\eta$ topology' kinematics_override: identity plot_x: m_jj x_scale: log @@ -55,7 +55,7 @@ implemented_observables: operation: "ratio" - observable: { - description: "ALL as function of $M_{inv}$, same sign $\eta$ topology", + description: 'ALL as function of $M_{inv}$, same sign $\eta$ topology', label: "$A_{LL}$", units: "", } @@ -80,7 +80,7 @@ implemented_observables: data_uncertainties: - uncertainties_SS.yaml plotting: - dataset_label: "STAR 200 GeV (2015) DIJET $A_{LL}$, same sign $\eta$ topology" + dataset_label: 'STAR 200 GeV (2015) DIJET $A_{LL}$, same sign $\eta$ topology' kinematics_override: identity plot_x: m_jj x_scale: log