Polarised Jet commondata implementation

nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/data.yaml

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+data_central:
+  - -0.0007
+  - 0.0039
+  - -0.0014
+  - -0.0005
+  - 0.0058
+  - 0.0034
+  - 0.0077
+  - -0.0181

nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/filter.py

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+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)

nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/kinematics.yaml

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+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

nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/metadata.yaml

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+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

nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/rawdata/Table_18.yaml

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+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: '$<p^{reco}_T>$ (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.'}

nnpdf_data/nnpdf_data/new_commondata/PHENIX_1JET_200GEV_ALL/uncertainties.yaml

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+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