From 0b16d429e90f07a3edb79373d7dc4084e269ffea Mon Sep 17 00:00:00 2001 From: juacrumar Date: Thu, 6 Jun 2024 12:56:08 +0200 Subject: [PATCH 1/5] make separate_multiplicative=False the default behaviour --- n3fit/runcards/examples/nnpdf40-like.yml | 5 ++-- .../hyperopt_studies/renew_hyperopt.yml | 3 -- ...restricted_search_space_renew_hyperopt.yml | 3 -- 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 ++ validphys2/src/validphys/config.py | 18 ++++------- validphys2/src/validphys/filters.py | 30 +++++++++++++++---- validphys2/src/validphys/pseudodata.py | 24 ++++++++------- 11 files changed, 56 insertions(+), 37 deletions(-) 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/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/validphys2/src/validphys/config.py b/validphys2/src/validphys/config.py index 9b3c749e31..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 diff --git a/validphys2/src/validphys/filters.py b/validphys2/src/validphys/filters.py index 6288af4dc1..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: 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) From dd98198940dd3911e2ba8b18e8014886c737ca25 Mon Sep 17 00:00:00 2001 From: juacrumar Date: Thu, 6 Jun 2024 13:02:08 +0200 Subject: [PATCH 2/5] commit with regression test hopefully passing before regenerating --- extra_tests/regression_fits/diagonal.yml | 2 ++ extra_tests/regression_fits/feature_scaling.yml | 2 ++ extra_tests/regression_fits/flavour.yml | 2 ++ extra_tests/regression_fits/no_csr.yml | 2 ++ extra_tests/regression_fits/no_lagrange.yml | 2 ++ extra_tests/regression_fits/no_msr.yml | 2 ++ extra_tests/regression_fits/no_sumrules.yml | 2 ++ extra_tests/regression_fits/no_vsr.yml | 2 ++ extra_tests/regression_fits/normal_fit.yml | 2 ++ extra_tests/regression_fits/polarized_evol.yml | 2 ++ extra_tests/regression_fits/single_dense.yml | 2 ++ extra_tests/regression_fits/trainable_prepro.yml | 2 ++ validphys2/src/validphys/tests/conftest.py | 2 +- validphys2/src/validphys/tests/test_overfit_metric.py | 1 + validphys2/src/validphys/tests/test_pseudodata.py | 2 +- 15 files changed, 27 insertions(+), 2 deletions(-) diff --git a/extra_tests/regression_fits/diagonal.yml b/extra_tests/regression_fits/diagonal.yml index 8c4ba68d9c..ed1999c9e6 100644 --- a/extra_tests/regression_fits/diagonal.yml +++ b/extra_tests/regression_fits/diagonal.yml @@ -34,6 +34,8 @@ mcseed: 1 diagonal_basis: True 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/extra_tests/regression_fits/feature_scaling.yml b/extra_tests/regression_fits/feature_scaling.yml index 7bb3a9687b..bb809b5310 100644 --- a/extra_tests/regression_fits/feature_scaling.yml +++ b/extra_tests/regression_fits/feature_scaling.yml @@ -34,6 +34,8 @@ mcseed: 1 load: "weights_feature.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/flavour.yml b/extra_tests/regression_fits/flavour.yml index 8e4fc6f058..33b10443ea 100644 --- a/extra_tests/regression_fits/flavour.yml +++ b/extra_tests/regression_fits/flavour.yml @@ -33,6 +33,8 @@ mcseed: 1 load: "weights_flavour.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/no_csr.yml b/extra_tests/regression_fits/no_csr.yml index 47e7d4bd02..0446404ff2 100644 --- a/extra_tests/regression_fits/no_csr.yml +++ b/extra_tests/regression_fits/no_csr.yml @@ -35,6 +35,8 @@ sum_rules: "ALLBUTCSR" save: "weights_casymm.weights.h5" +sampling: + separate_multiplicative: True parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 9] activation_per_layer: ['sigmoid', 'tanh', 'linear'] diff --git a/extra_tests/regression_fits/no_lagrange.yml b/extra_tests/regression_fits/no_lagrange.yml index 4a58652996..aebf67eab6 100644 --- a/extra_tests/regression_fits/no_lagrange.yml +++ b/extra_tests/regression_fits/no_lagrange.yml @@ -35,6 +35,8 @@ 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/no_msr.yml b/extra_tests/regression_fits/no_msr.yml index 64ce255cf9..e84357ca5b 100644 --- a/extra_tests/regression_fits/no_msr.yml +++ b/extra_tests/regression_fits/no_msr.yml @@ -35,6 +35,8 @@ mcseed: 1 sum_rules: "VSR" 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/extra_tests/regression_fits/no_sumrules.yml b/extra_tests/regression_fits/no_sumrules.yml index a42d4efde9..df2933ed90 100644 --- a/extra_tests/regression_fits/no_sumrules.yml +++ b/extra_tests/regression_fits/no_sumrules.yml @@ -36,6 +36,8 @@ sum_rules: False 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/no_vsr.yml b/extra_tests/regression_fits/no_vsr.yml index 0fd296acdc..d7ae02d4a3 100644 --- a/extra_tests/regression_fits/no_vsr.yml +++ b/extra_tests/regression_fits/no_vsr.yml @@ -36,6 +36,8 @@ sum_rules: "MSR" 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/normal_fit.yml b/extra_tests/regression_fits/normal_fit.yml index bcedeb053e..e943b124c6 100644 --- a/extra_tests/regression_fits/normal_fit.yml +++ b/extra_tests/regression_fits/normal_fit.yml @@ -27,6 +27,8 @@ mcseed: 1 save: "normal_fit.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/polarized_evol.yml b/extra_tests/regression_fits/polarized_evol.yml index cea9ccd333..4190fc1c89 100644 --- a/extra_tests/regression_fits/polarized_evol.yml +++ b/extra_tests/regression_fits/polarized_evol.yml @@ -32,6 +32,8 @@ mcseed: 746898422 genrep: true load: "weights_polevol.weights.h5" +sampling: + separate_multiplicative: True parameters: nodes_per_layer: [25, 20, 4] diff --git a/extra_tests/regression_fits/single_dense.yml b/extra_tests/regression_fits/single_dense.yml index 8c9165597e..2317d01166 100644 --- a/extra_tests/regression_fits/single_dense.yml +++ b/extra_tests/regression_fits/single_dense.yml @@ -37,6 +37,8 @@ mcseed: 1 save: "single_dense.weights.h5" load: "single_dense.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.yml b/extra_tests/regression_fits/trainable_prepro.yml index 5b5a69547b..b20d70c29e 100644 --- a/extra_tests/regression_fits/trainable_prepro.yml +++ b/extra_tests/regression_fits/trainable_prepro.yml @@ -35,6 +35,8 @@ 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/validphys2/src/validphys/tests/conftest.py b/validphys2/src/validphys/tests/conftest.py index b80f64d9c5..a56cf31583 100644 --- a/validphys2/src/validphys/tests/conftest.py +++ b/validphys2/src/validphys/tests/conftest.py @@ -76,7 +76,7 @@ def tmp(tmpdir): PSEUDODATA_FIT = "pseudodata_test_fit_n3fit_221130" -base_config = dict(pdf=PDF, use_cuts='nocuts', dataset_inputs=DATA, theoryid=THEORYID, Q=10) +base_config = dict(pdf=PDF, use_cuts='nocuts', dataset_inputs=DATA, theoryid=THEORYID, Q=10, separate_multiplicative=True) @pytest.fixture(scope='module') 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. From 5a9efd55dc13f9fa93fe72e2c069c8382da59b3d Mon Sep 17 00:00:00 2001 From: juacrumar Date: Thu, 6 Jun 2024 15:42:41 +0200 Subject: [PATCH 3/5] update regression runcards, and regenerate some of the tests --- extra_tests/regression_fits/diagonal.yml | 2 - .../regression_fits/feature_scaling.yml | 2 - extra_tests/regression_fits/flavour.yml | 2 - extra_tests/regression_fits/no_csr.yml | 2 - extra_tests/regression_fits/no_lagrange.yml | 2 - extra_tests/regression_fits/no_msr.yml | 2 - extra_tests/regression_fits/no_sumrules.yml | 2 - extra_tests/regression_fits/no_vsr.yml | 2 - extra_tests/regression_fits/normal_fit.yml | 2 - .../regression_fits/polarized_evol.yml | 2 - extra_tests/regression_fits/single_dense.yml | 2 - .../regression_fits/trainable_prepro.yml | 1 + validphys2/src/validphys/tests/conftest.py | 2 +- .../regressions/test_art_rep_generation.csv | 532 +++++++++--------- .../tests/regressions/test_mcreplica.csv | 532 +++++++++--------- 15 files changed, 534 insertions(+), 555 deletions(-) diff --git a/extra_tests/regression_fits/diagonal.yml b/extra_tests/regression_fits/diagonal.yml index ed1999c9e6..8c4ba68d9c 100644 --- a/extra_tests/regression_fits/diagonal.yml +++ b/extra_tests/regression_fits/diagonal.yml @@ -34,8 +34,6 @@ mcseed: 1 diagonal_basis: True 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/extra_tests/regression_fits/feature_scaling.yml b/extra_tests/regression_fits/feature_scaling.yml index bb809b5310..7bb3a9687b 100644 --- a/extra_tests/regression_fits/feature_scaling.yml +++ b/extra_tests/regression_fits/feature_scaling.yml @@ -34,8 +34,6 @@ mcseed: 1 load: "weights_feature.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/flavour.yml b/extra_tests/regression_fits/flavour.yml index 33b10443ea..8e4fc6f058 100644 --- a/extra_tests/regression_fits/flavour.yml +++ b/extra_tests/regression_fits/flavour.yml @@ -33,8 +33,6 @@ mcseed: 1 load: "weights_flavour.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/no_csr.yml b/extra_tests/regression_fits/no_csr.yml index 0446404ff2..47e7d4bd02 100644 --- a/extra_tests/regression_fits/no_csr.yml +++ b/extra_tests/regression_fits/no_csr.yml @@ -35,8 +35,6 @@ sum_rules: "ALLBUTCSR" save: "weights_casymm.weights.h5" -sampling: - separate_multiplicative: True parameters: # This defines the parameter dictionary that is passed to the Model Trainer nodes_per_layer: [15, 10, 9] activation_per_layer: ['sigmoid', 'tanh', 'linear'] diff --git a/extra_tests/regression_fits/no_lagrange.yml b/extra_tests/regression_fits/no_lagrange.yml index aebf67eab6..4a58652996 100644 --- a/extra_tests/regression_fits/no_lagrange.yml +++ b/extra_tests/regression_fits/no_lagrange.yml @@ -35,8 +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/no_msr.yml b/extra_tests/regression_fits/no_msr.yml index e84357ca5b..64ce255cf9 100644 --- a/extra_tests/regression_fits/no_msr.yml +++ b/extra_tests/regression_fits/no_msr.yml @@ -35,8 +35,6 @@ mcseed: 1 sum_rules: "VSR" 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/extra_tests/regression_fits/no_sumrules.yml b/extra_tests/regression_fits/no_sumrules.yml index df2933ed90..a42d4efde9 100644 --- a/extra_tests/regression_fits/no_sumrules.yml +++ b/extra_tests/regression_fits/no_sumrules.yml @@ -36,8 +36,6 @@ sum_rules: False 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/no_vsr.yml b/extra_tests/regression_fits/no_vsr.yml index d7ae02d4a3..0fd296acdc 100644 --- a/extra_tests/regression_fits/no_vsr.yml +++ b/extra_tests/regression_fits/no_vsr.yml @@ -36,8 +36,6 @@ sum_rules: "MSR" 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/normal_fit.yml b/extra_tests/regression_fits/normal_fit.yml index e943b124c6..bcedeb053e 100644 --- a/extra_tests/regression_fits/normal_fit.yml +++ b/extra_tests/regression_fits/normal_fit.yml @@ -27,8 +27,6 @@ mcseed: 1 save: "normal_fit.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/polarized_evol.yml b/extra_tests/regression_fits/polarized_evol.yml index 4190fc1c89..cea9ccd333 100644 --- a/extra_tests/regression_fits/polarized_evol.yml +++ b/extra_tests/regression_fits/polarized_evol.yml @@ -32,8 +32,6 @@ mcseed: 746898422 genrep: true load: "weights_polevol.weights.h5" -sampling: - separate_multiplicative: True parameters: nodes_per_layer: [25, 20, 4] diff --git a/extra_tests/regression_fits/single_dense.yml b/extra_tests/regression_fits/single_dense.yml index 2317d01166..8c9165597e 100644 --- a/extra_tests/regression_fits/single_dense.yml +++ b/extra_tests/regression_fits/single_dense.yml @@ -37,8 +37,6 @@ mcseed: 1 save: "single_dense.weights.h5" load: "single_dense.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.yml b/extra_tests/regression_fits/trainable_prepro.yml index b20d70c29e..132620e0b7 100644 --- a/extra_tests/regression_fits/trainable_prepro.yml +++ b/extra_tests/regression_fits/trainable_prepro.yml @@ -37,6 +37,7 @@ 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/validphys2/src/validphys/tests/conftest.py b/validphys2/src/validphys/tests/conftest.py index a56cf31583..b80f64d9c5 100644 --- a/validphys2/src/validphys/tests/conftest.py +++ b/validphys2/src/validphys/tests/conftest.py @@ -76,7 +76,7 @@ def tmp(tmpdir): PSEUDODATA_FIT = "pseudodata_test_fit_n3fit_221130" -base_config = dict(pdf=PDF, use_cuts='nocuts', dataset_inputs=DATA, theoryid=THEORYID, Q=10, separate_multiplicative=True) +base_config = dict(pdf=PDF, use_cuts='nocuts', dataset_inputs=DATA, theoryid=THEORYID, Q=10) @pytest.fixture(scope='module') 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 424770.8407629348 -17 384322.06275548146 -18 383728.5860944929 -19 379658.20346904657 -20 358425.79045571556 -21 336036.764622581 -22 128270.33907424095 -23 127313.63435401936 -24 121747.84807633635 -25 116081.26162372652 -26 112542.18223029248 -27 109322.01308160098 -28 94651.56123910741 -29 49971.329309147884 -30 214.5479042739518 -31 97.06060692325975 -32 47.9983713987643 -33 26.299866399550105 -34 16.94687166264714 -35 10.674622552292847 -36 8.784023835631519 -37 4.4048614269844775 -38 1.6682536560225298 -39 0.421406486396608 -40 0.1376189308949718 -41 0.02252926875035294 -42 0.00018468057557725955 -43 11910.238104190781 -44 22369.93892247344 -45 14797.936272861301 -46 6556.219118746482 -47 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.../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_61.json | 23 +- 22 files changed, 5301 insertions(+), 5284 deletions(-) diff --git a/extra_tests/regression_fits/central_16.json b/extra_tests/regression_fits/central_16.json index 39aa4f3cb3..d607d3b395 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": 33.35334396362305, "start": 0.0, - "replica_set": 0.23800349235534668, - "replica_fitted": 32.32805871963501, - "replica_set_to_replica_fitted": 32.09005522727966 + "replica_set": 0.23613405227661133, + "replica_fitted": 33.3531174659729, + "replica_set_to_replica_fitted": 33.11698341369629 }, 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b/extra_tests/regression_fits/diagonal_45.json index 4fcf18d09c..6c24b69486 100644 --- a/extra_tests/regression_fits/diagonal_45.json +++ b/extra_tests/regression_fits/diagonal_45.json @@ -51,44 +51,45 @@ ], "stop_epoch": 1100, "best_epoch": 1099, - "erf_tr": 3.3770647048950195, - "erf_vl": 3.232318639755249, - "chi2": 2.2297277450561523, + "erf_tr": 3.7433674335479736, + "erf_vl": 3.06573224067688, + "chi2": 2.1767020225524902, "pos_state": "POS_VETO", "arc_lengths": [ - 1.318226246486323, - 1.5444156168391867, - 1.1791073597859465, - 1.0015316307958235, - 1.2179144267244248 + 1.3174401174899257, + 1.5070530572454897, + 1.1761948219147023, + 1.0013647421970557, + 1.2246977365119018 ], "integrability": [ - 0.0008988644076473595, - 0.0008988644076458607, - 4.7246509779275137e-05, - 0.46261498332023554, - 0.00705060712061667 + 0.0008957563404708435, + 0.0008957563404695668, + 4.806763138198722e-05, + 0.4638940915465348, + 0.007004071318077343 ], "timing": { "walltime": { - "Total": 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a/extra_tests/regression_fits/feature_scaling_81.exportgrid b/extra_tests/regression_fits/feature_scaling_81.exportgrid index bacc8df354..2f907ee9c1 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, 0.9970256090164185, 0.4224754869937897, 0.4242808222770691, 0.4242810308933258, - 0.06217297911643982, 0.42429959774017334, 0.42430004477500916, 0.422805517911911, - 0.9970256090164185, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.965130090713501, 0.4109417796134949, 0.4129239618778229, 0.41292423009872437, - 0.06504666060209274, 0.4129442572593689, 0.4129447638988495, 0.41131123900413513, - 0.965130090713501, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.9341123104095459, 0.39977285265922546, 0.4019491970539093, 0.4019494354724884, - 0.06804729998111725, 0.40197113156318665, 0.4019717574119568, 0.4001863896846771, - 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0.0, 0.0, 0.0, 0.0, 0.0, 0.0] q20: 2.7224999999999997 replica: 29 diff --git a/extra_tests/regression_fits/flavour_29.json b/extra_tests/regression_fits/flavour_29.json index 045396ff1e..b9a7bf3879 100644 --- a/extra_tests/regression_fits/flavour_29.json +++ b/extra_tests/regression_fits/flavour_29.json @@ -49,46 +49,47 @@ "trainable": false } ], - "stop_epoch": 140, - "best_epoch": 28, - "erf_tr": 5.085887432098389, - "erf_vl": 5.384581089019775, - "chi2": 3.8961896896362305, + "stop_epoch": 181, + "best_epoch": 69, + "erf_tr": 4.977456092834473, + "erf_vl": 5.562390327453613, + "chi2": 3.896981954574585, "pos_state": "POS_PASS", "arc_lengths": [ - 1.1046909732525076, - 1.2122390889491175, - 0.9906464905279492, - 0.9904917309060217, - 0.9907080519677236 + 1.1047281554636061, + 1.2121893672897062, + 0.9906464941994304, + 0.9904916213693944, + 0.9907080935720707 ], "integrability": [ - 0.46764427423477195, - 0.4676442742347716, - 0.08089738525450241, - 0.1000113487243652, - 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0.0, 0.0, 0.0, 0.0, 0.0, 0.0] q20: 2.7224999999999997 replica: 613 diff --git a/extra_tests/regression_fits/no_csr_613.json b/extra_tests/regression_fits/no_csr_613.json index 29319b0842..22bad86cbe 100644 --- a/extra_tests/regression_fits/no_csr_613.json +++ b/extra_tests/regression_fits/no_csr_613.json @@ -57,44 +57,45 @@ ], "stop_epoch": 1100, "best_epoch": 1099, - "erf_tr": 52.448638916015625, - "erf_vl": 52.265071868896484, - "chi2": 29.3955078125, + "erf_tr": 50.92805862426758, + "erf_vl": 50.83631134033203, + "chi2": 29.386581420898438, "pos_state": "POS_VETO", "arc_lengths": [ - 0.9916716082991431, - 1.925850885881192, - 1.3551547641298252, - 1.0247357422266838, - 1.3300020695083878 + 0.9916593109635676, + 1.8120037933717692, + 1.3579849560807138, + 1.0247125754536226, + 1.3362143325718208 ], "integrability": [ - 0.0005367029261819367, - 0.002806974167469556, - 1.8677989657267524e-05, - 0.002482869982487257, - 0.016741260187701057 + 0.0005673111809293141, + 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b/extra_tests/regression_fits/no_msr_92.json @@ -51,44 +51,45 @@ ], "stop_epoch": 1100, "best_epoch": 1099, - "erf_tr": 6.576594829559326, - "erf_vl": 5.858449935913086, - "chi2": 3.3300018310546875, + "erf_tr": 5.661350727081299, + "erf_vl": 5.671205043792725, + "chi2": 3.3254096508026123, "pos_state": "POS_PASS", "arc_lengths": [ - 1.3370216319814459, - 0.9939697402767997, - 1.179148683250488, - 1.0013385209813972, - 1.175109752177304 + 1.3377684868747033, + 0.9939545216245528, + 1.1826499004778586, + 1.0015656903069137, + 1.1694081596657295 ], "integrability": [ - 0.0009919884832926065, - 0.0009919884832925857, - 4.6653166691515424e-05, - 0.4762776866555214, - 0.007486372429411588 + 0.0009784702342583926, + 0.0009784702342586354, + 4.6017493104885676e-05, + 0.47618312388658507, + 0.007452807622030058 ], "timing": { "walltime": { - "Total": 46.0448694229126, + "Total": 45.44354581832886, "start": 0.0, - "replica_set": 0.23608732223510742, - "replica_fitted": 46.04460954666138, - 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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, 0.4442256689071655, 0.44417592883110046, 0.4723217785358429, - -2.3672444820404053, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.2921900749206543, 0.4632742702960968, 0.43389198184013367, 0.43394893407821655, - -0.5362372994422913, 0.43399667739868164, 0.43394026160240173, 0.46319839358329773, - -2.2921900749206543, 0.0, 0.0, 0.0] -- [0.0, 0.0, -2.219531536102295, 0.4547019600868225, 0.4241504371166229, 0.4242151379585266, - -0.5360674858093262, 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mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post576.dev0+47a077fe1", - "validphys": "4.0.9.post576.dev0+47a077fe1" + "nnpdf": "4.0.9.post909.dev0+d8a530032", + "validphys": "4.0.9.post909.dev0+d8a530032" } } diff --git a/extra_tests/regression_fits/normal_fit_72.exportgrid b/extra_tests/regression_fits/normal_fit_72.exportgrid index 8d42665be6..1058c8e826 100644 --- a/extra_tests/regression_fits/normal_fit_72.exportgrid +++ b/extra_tests/regression_fits/normal_fit_72.exportgrid @@ -1,591 +1,591 @@ labels: [TBAR, BBAR, CBAR, SBAR, UBAR, DBAR, GLUON, D, U, S, C, B, T, PHT] pdfgrid: -- [0.0, 0.0, -1.136602759361267, 0.7716962695121765, 0.7504222393035889, 0.7926294207572937, - -25.532499313354492, 0.7929382920265198, 0.7507315874099731, 0.7718683481216431, - -1.136602759361267, 0.0, 0.0, 0.0] -- [0.0, 0.0, -1.1071027517318726, 0.7551030516624451, 0.7332092523574829, 0.7766196727752686, - -25.423473358154297, 0.776973307132721, 0.7335633635520935, 0.7553030848503113, - 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b/extra_tests/regression_fits/normal_fit_72.json index adb403c767..8288fca89c 100644 --- a/extra_tests/regression_fits/normal_fit_72.json +++ b/extra_tests/regression_fits/normal_fit_72.json @@ -49,46 +49,47 @@ "trainable": false } ], - "stop_epoch": 1485, - "best_epoch": 183, - "erf_tr": 4.598884105682373, - "erf_vl": 5.284733772277832, - "chi2": 3.2790424823760986, + "stop_epoch": 3449, + "best_epoch": 2147, + "erf_tr": 4.3604960441589355, + "erf_vl": 5.548332691192627, + "chi2": 2.8331196308135986, "pos_state": "POS_PASS", "arc_lengths": [ - 1.1169308148774457, - 1.2720392456218312, - 4.3550092339885556, - 1.0073990149237644, - 1.0536516407475909 + 1.0489743427459048, + 1.3840237758432037, + 7.447239029040191, + 1.2081939349795308, + 1.0586443187696393 ], "integrability": [ - 0.012613800994590169, - 0.012613800994586644, - 1.785231125861486e-05, - 0.003321282420073568, - 0.003176734346196919 + 0.013233038480392631, + 0.013233038480393422, + 1.7842459385852827e-05, + 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"validphys": "4.0.9.post909.dev0+d8a530032" } } 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, -0.10418701171875, -0.10375979542732239, 0.0, 0.0, 0.0, 0.0] -- [0.0, 0.0, 0.0, -0.096921905875206, -0.09737326204776764, -0.09737326204776764, - -0.6048541069030762, -0.09737326204776764, -0.09737326204776764, -0.096921905875206, +- [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, 0.0] -- [0.0, 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-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..4252d4f68e 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": 17.964065313339233, "start": 0.0, - "replica_set": 0.249741792678833, - "replica_fitted": 18.62974452972412, - "replica_set_to_replica_fitted": 18.380002737045288 + "replica_set": 0.23597407341003418, + "replica_fitted": 17.963902473449707, + "replica_set_to_replica_fitted": 17.727928400039673 }, "cputime": { - "Total": 19.099821179000003, + "Total": 18.071885989000002, "start": 0.0, - "replica_set": 0.24700718099999985, - "replica_fitted": 19.099551677, - "replica_set_to_replica_fitted": 18.852544496 + "replica_set": 0.2340430049999993, + "replica_fitted": 18.071721742999998, + "replica_set_to_replica_fitted": 17.837678738 } }, "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.post909.dev0+d8a530032", + "validphys": "4.0.9.post909.dev0+d8a530032" } } diff --git a/extra_tests/regression_fits/single_dense_316.json b/extra_tests/regression_fits/single_dense_316.json index 97bad55b75..073e96f113 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": 32.28785991668701, "start": 0.0, - "replica_set": 0.25393104553222656, - "replica_fitted": 34.448877811431885, - "replica_set_to_replica_fitted": 34.19494676589966 + "replica_set": 0.23024249076843262, + "replica_fitted": 32.287729263305664, + "replica_set_to_replica_fitted": 32.05748677253723 }, "cputime": { - "Total": 35.914583166, + "Total": 31.545657242, "start": 0.0, - "replica_set": 0.24511515099999936, - "replica_fitted": 35.914323130999996, - "replica_set_to_replica_fitted": 35.669207979999996 + "replica_set": 0.2285582650000002, + "replica_fitted": 31.545524994999997, + "replica_set_to_replica_fitted": 31.316966729999997 } }, "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.post909.dev0+d8a530032", + "validphys": "4.0.9.post909.dev0+d8a530032" } } diff --git a/extra_tests/regression_fits/trainable_prepro_61.json b/extra_tests/regression_fits/trainable_prepro_61.json index 5c426e7b05..c0e8af0fa9 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": 32.61800265312195, "start": 0.0, - "replica_set": 0.24268245697021484, - "replica_fitted": 34.79669666290283, - "replica_set_to_replica_fitted": 34.55401420593262 + "replica_set": 0.23979687690734863, + "replica_fitted": 32.61782908439636, + "replica_set_to_replica_fitted": 32.378032207489014 }, "cputime": { - "Total": 36.326103099, + "Total": 33.684330003, "start": 0.0, - "replica_set": 0.24133399599999983, - "replica_fitted": 36.325896654, - "replica_set_to_replica_fitted": 36.084562657999996 + "replica_set": 0.23799519599999996, + "replica_fitted": 33.684154264, + "replica_set_to_replica_fitted": 33.446159068 } }, "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.post909.dev0+d8a530032", + "validphys": "4.0.9.post909.dev0+d8a530032" } } From 4d5360ba99fb270ded88f1e33a08b867e8ff2687 Mon Sep 17 00:00:00 2001 From: Redo regressions bot Date: Fri, 7 Jun 2024 20:11:10 +0000 Subject: [PATCH 5/5] Automatically regenerated regressions from PR 2107, branch separate_multiplicative_to_false. --- extra_tests/regression_fits/central_16.json | 20 +++++++++---------- extra_tests/regression_fits/diagonal_45.json | 20 +++++++++---------- .../regression_fits/feature_scaling_81.json | 20 +++++++++---------- extra_tests/regression_fits/flavour_29.json | 20 +++++++++---------- extra_tests/regression_fits/no_csr_613.json | 20 +++++++++---------- .../regression_fits/no_lagrange_27.json | 20 +++++++++---------- extra_tests/regression_fits/no_msr_92.json | 20 +++++++++---------- .../regression_fits/no_sumrules_18.json | 20 +++++++++---------- extra_tests/regression_fits/no_vsr_54.json | 20 +++++++++---------- .../regression_fits/normal_fit_72.json | 20 +++++++++---------- .../regression_fits/polarized_evol_34.json | 20 +++++++++---------- .../regression_fits/single_dense_316.json | 20 +++++++++---------- .../regression_fits/trainable_prepro_61.json | 20 +++++++++---------- 13 files changed, 130 insertions(+), 130 deletions(-) diff --git a/extra_tests/regression_fits/central_16.json b/extra_tests/regression_fits/central_16.json index d607d3b395..6f2b9a68d7 100644 --- a/extra_tests/regression_fits/central_16.json +++ b/extra_tests/regression_fits/central_16.json @@ -71,25 +71,25 @@ ], "timing": { "walltime": { - "Total": 33.35334396362305, + "Total": 30.10047173500061, "start": 0.0, - "replica_set": 0.23613405227661133, - "replica_fitted": 33.3531174659729, - "replica_set_to_replica_fitted": 33.11698341369629 + "replica_set": 0.23421192169189453, + "replica_fitted": 30.100268602371216, + "replica_set_to_replica_fitted": 29.86605668067932 }, "cputime": { - "Total": 34.918751412, + "Total": 31.299373692000003, "start": 0.0, - "replica_set": 0.23205279599999962, - "replica_fitted": 34.918523647, - "replica_set_to_replica_fitted": 34.686470850999996 + "replica_set": 0.23228165799999978, + "replica_fitted": 31.299169341000002, + "replica_set_to_replica_fitted": 31.066887683000004 } }, "version": { "keras": "3.3.3", "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post909.dev0+d8a530032", - "validphys": "4.0.9.post909.dev0+d8a530032" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/diagonal_45.json b/extra_tests/regression_fits/diagonal_45.json index 6c24b69486..520c9561bf 100644 --- a/extra_tests/regression_fits/diagonal_45.json +++ b/extra_tests/regression_fits/diagonal_45.json @@ -71,25 +71,25 @@ ], "timing": { "walltime": { - "Total": 31.73482918739319, + "Total": 29.147084712982178, "start": 0.0, - "replica_set": 0.2278597354888916, - "replica_fitted": 31.734679460525513, - "replica_set_to_replica_fitted": 31.50681972503662 + "replica_set": 0.2392897605895996, + "replica_fitted": 29.146868228912354, + "replica_set_to_replica_fitted": 28.907578468322754 }, "cputime": { - "Total": 32.994349703000005, + "Total": 30.027262939000003, "start": 0.0, - "replica_set": 0.22653086100000053, - "replica_fitted": 32.994198551000004, - "replica_set_to_replica_fitted": 32.76766769 + "replica_set": 0.2373946069999997, + "replica_fitted": 30.027044852000003, + "replica_set_to_replica_fitted": 29.789650245 } }, "version": { "keras": "3.3.3", "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post909.dev0+d8a530032", - "validphys": "4.0.9.post909.dev0+d8a530032" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/feature_scaling_81.json b/extra_tests/regression_fits/feature_scaling_81.json index f2c5ffca35..efa458289e 100644 --- a/extra_tests/regression_fits/feature_scaling_81.json +++ b/extra_tests/regression_fits/feature_scaling_81.json @@ -71,25 +71,25 @@ ], "timing": { "walltime": { - "Total": 33.433435916900635, + "Total": 31.037630796432495, "start": 0.0, - "replica_set": 0.24986958503723145, - "replica_fitted": 33.43318152427673, - "replica_set_to_replica_fitted": 33.1833119392395 + "replica_set": 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"walltime": { - "Total": 8.88758897781372, + "Total": 8.016386985778809, "start": 0.0, - "replica_set": 0.24344515800476074, - "replica_fitted": 8.887479782104492, - "replica_set_to_replica_fitted": 8.644034624099731 + "replica_set": 0.22813057899475098, + "replica_fitted": 8.016170024871826, + "replica_set_to_replica_fitted": 7.788039445877075 }, "cputime": { - "Total": 8.904189728, + "Total": 8.175631554, "start": 0.0, - "replica_set": 0.24074732199999982, - "replica_fitted": 8.904077878999999, - "replica_set_to_replica_fitted": 8.663330556999998 + "replica_set": 0.22713051000000029, + "replica_fitted": 8.175411814, + "replica_set_to_replica_fitted": 7.948281304 } }, "version": { "keras": "3.3.3", "tensorflow": "2.16.1, mkl=False", "numpy": "1.26.4", - "nnpdf": "4.0.9.post909.dev0+d8a530032", - "validphys": "4.0.9.post909.dev0+d8a530032" + "nnpdf": "4.0.9.post910.dev0+670d39e81", + "validphys": "4.0.9.post910.dev0+670d39e81" } } diff --git a/extra_tests/regression_fits/no_csr_613.json b/extra_tests/regression_fits/no_csr_613.json index 22bad86cbe..2fc2d91e09 100644 --- a/extra_tests/regression_fits/no_csr_613.json +++ b/extra_tests/regression_fits/no_csr_613.json @@ -77,25 +77,25 @@ ], "timing": { "walltime": { - "Total": 26.523786067962646, + "Total": 26.624579191207886, "start": 0.0, - "replica_set": 0.23438024520874023, - "replica_fitted": 26.52363872528076, - "replica_set_to_replica_fitted": 26.28925848007202 + "replica_set": 0.23645830154418945, + "replica_fitted": 26.624445915222168, + "replica_set_to_replica_fitted": 26.38798761367798 }, "cputime": { - "Total": 27.565364704000004, + "Total": 27.446348086999997, "start": 0.0, - "replica_set": 0.2324746950000005, - "replica_fitted": 27.565215195, - "replica_set_to_replica_fitted": 27.3327405 + "replica_set": 0.23441415199999938, + "replica_fitted": 27.446212664999997, + "replica_set_to_replica_fitted": 27.211798512999998 } }, "version": { "keras": "3.3.3", 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