Added split of ZpT data sets according to different processes. Adde utils for specialised theory covmat prescriptions

Author: enocera

nnpdf_data/nnpdf_data/commondata/ATLAS_Z0J_13TEV_PT_LARGE/data.yaml

@@ -0,0 +1,42 @@
+data_central:
+- 0.0473835
+- 0.0405684
+- 0.0343165
+- 0.0291566
+- 0.0248037
+- 0.021268
+- 0.018325
+- 0.0156045
+- 0.01318
+- 0.0112073
+- 0.00955676
+- 0.00810287
+- 0.00678809
+- 0.00575628
+- 0.00487686
+- 0.00416884
+- 0.00352131
+- 0.00297507
+- 0.00254333
+- 0.00218319
+- 0.00187701
+- 0.0015932
+- 0.00135193
+- 0.0011323
+- 0.00095743
+- 0.000814977
+- 0.000653718
+- 0.000484859
+- 0.000329051
+- 0.000186048
+- 0.000104998
+- 6.12794e-05
+- 3.0584e-05
+- 1.22113e-05
+- 5.90263e-06
+- 2.77421e-06
+- 1.25134e-06
+- 5.5219e-07
+- 2.01646e-07
+- 5.11526e-08
+- 2.51767e-06

nnpdf_data/nnpdf_data/commondata/ATLAS_Z0J_13TEV_PT_LARGE/filter.py

@@ -0,0 +1,94 @@
+"""
+This file contains the piece of code needed to implement the ATLAS ZpT 
+measurement at 13 TeV. We consider the combined electron-muon measurement, for
+which a total uncorrelated and a total correlated ucnertainties are given. The 
+measurement is normalised to the fiducial cross section, therefore there is no
+luminosity ucnertainty. The first three bins in pT are cropped, because of
+the impossiblity of producing theoretical predictions.
+"""
+
+import yaml
+
+def get_tables():
+    """
+    Get the Hepdata table
+    """
+    hepdata_tables = ["rawdata/HEPData-ins1768911-v3-Table_4a.yaml"]
+
+    return hepdata_tables
+
+def get_all():
+    """
+    Returns data, kinematics and uncertainties for dumping in the .yaml files
+    """
+    data_central = []
+    kinematics = []
+    uncertainties = []
+
+    hepdata_tables = get_tables()
+    for table in hepdata_tables:
+        with open(table, 'r') as f:
+            input = yaml.safe_load(f)
+            
+        # Central values
+        data_values = input["dependent_variables"][0]["values"]
+        for data_value in data_values:
+            data_central.append(data_value["value"])
+        # Kinematic bins
+        kin_values = input["independent_variables"][0]["values"]
+        for kin_value in kin_values:
+            kin = {
+                'pT': {'min': kin_value['low'],
+                       'mid': 0.5 * (kin_value['low'] + kin_value['high']),
+                       'max': kin_value['high']},
+                'm_Z2': {'min': None, 'mid': 8317.44, 'max': None},
+                'sqrts':  {'min': None, 'mid': 13000, 'max': None}}
+               
+            kinematics.append(kin)
+        # Uncertainties
+        i = 0
+        for data_value in data_values:
+            errors = data_value["errors"]
+            uncertainty = {}
+            for error in errors:
+                uncertainty[error["label"]] = float(error["symerror"].replace('%',''))*data_central[i]/100.
+                uncertainty.update(uncertainty)
+                
+            uncertainties.append(uncertainty)
+            i = i+1
+
+    n=3
+    return (data_central[n:], kinematics[n:], uncertainties[n:])
+
+def filter_ATLAS_Z0J_13TEV_PT():
+    """
+    Dumps data, kinematics, and uncertainties on .yaml files
+    """
+    central_values, kinematics, uncertainties = get_all()
+    # Central values
+    data_central_yaml = {"data_central": central_values}
+    # Kinematics
+    kinematics_yaml = {"bins": kinematics}
+    # Uncertainties
+    treatment = {"correlated uncertainty": "ADD",
+                 "uncorrelated uncertainty": "ADD",}
+    correlation = {"correlated uncertainty": "CORR",
+                 "uncorrelated uncertainty": "UNCORR",}
+    definitions = {}
+    for key,value in uncertainties[0].items():
+        definition = {key :
+                      {"description": key,
+                       "treatment": treatment[key],
+                       "type": correlation[key]}}
+        definitions.update(definition)
+    uncertainties_yaml = {"definitions": definitions,"bins": uncertainties}
+
+    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)
+    with open("uncertainties.yaml", "w") as file:
+        yaml.dump(uncertainties_yaml, file, sort_keys=False)
+        
+if __name__ == "__main__":
+    filter_ATLAS_Z0J_13TEV_PT()