full names of utils functions & isort and black formatting

NNPDF · Mar 25, 2024 · d686a39 · d686a39
1 parent 2f9159b
commit d686a39
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Showing 21 changed files with 3,168 additions and 1,218 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
@@ -1,13 +1,31 @@
-import yaml
 from math import sqrt
-def se(delta_plus, delta_minus):
-
-    semi_diff = (delta_plus + delta_minus)/2
-    average = (delta_plus - delta_minus)/2
+
+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)
+    se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff)
     return se_delta, se_sigma
 
+
 def processData():
     with open('metadata.yaml', 'r') as file:
         metadata = yaml.safe_load(file)
@@ -22,7 +40,7 @@ def processData():
     kin_altcorr1 = []
     error_altcorr1 = []
 
-# jet data
+    # jet data
 
     for i in tables:
         if i == 1:
@@ -44,7 +62,7 @@ def processData():
             y_min = 2.5
             y_max = 3
         y_central = None
-        hepdata_tables="rawdata/atlas_inclusive_jet2015_r04_eta"+str(i)+".yaml"
+        hepdata_tables = "rawdata/atlas_inclusive_jet2015_r04_eta" + str(i) + ".yaml"
         with open(hepdata_tables, 'r') as file:
             input = yaml.safe_load(file)
 
@@ -57,21 +75,32 @@ def processData():
             value_delta = 0
             error_value = {}
             for k in range(len(values[j]['errors'])):
-                se_delta, se_sigma = se(values[j]['errors'][k]['asymerror']['plus'], values[j]['errors'][k]['asymerror']['minus'])
+                se_delta, se_sigma = symmetrize_errors(
+                    values[j]['errors'][k]['asymerror']['plus'],
+                    values[j]['errors'][k]['asymerror']['minus'],
+                )
                 value_delta = value_delta + se_delta
                 error_label = str(values[j]['errors'][k]['label'])
                 error_value[error_label] = se_sigma
             data_central_value = values[j]['value'] + value_delta
             data_central.append(data_central_value)
             error.append(error_value)
-            kin_value = {'sqrts': {'min': None, 'mid': sqrts, 'max': None}, 'pT': {'min': pT_min, 'mid': None, 'max': pT_max}, 'y': {'min': y_min, 'mid': y_central, 'max': y_max}}
+            kin_value = {
+                'sqrts': {'min': None, 'mid': sqrts, 'max': None},
+                'pT': {'min': pT_min, 'mid': None, 'max': pT_max},
+                'y': {'min': y_min, 'mid': y_central, 'max': y_max},
+            }
             kin.append(kin_value)
 
-    hepdata_tables="rawdata/atlas_inclusive_jet2015_r04_eta1.yaml"
+    hepdata_tables = "rawdata/atlas_inclusive_jet2015_r04_eta1.yaml"
     with open(hepdata_tables, 'r') as file:
         input = yaml.safe_load(file)
     error_definition = {}
-    error_definition['stat'] = {'description': 'total statistical uncertainty', 'treatment': 'ADD', 'type': 'UNCORR'}
+    error_definition['stat'] = {
+        'description': 'total statistical uncertainty',
+        'treatment': 'ADD',
+        'type': 'UNCORR',
+    }
     for i in range(1, len(input['dependent_variables'][0]['values'][0]['errors'])):
         error_name = input['dependent_variables'][0]['values'][0]['errors'][i]['label']
         error_definition[error_name] = {'description': '', 'treatment': 'MULT', 'type': 'CORR'}
@@ -81,15 +110,15 @@ def processData():
     uncertainties_yaml = {'definitions': error_definition, 'bins': error}
 
     with open('data.yaml', 'w') as file:
-         yaml.dump(data_central_yaml, file, sort_keys=False)
+        yaml.dump(data_central_yaml, file, sort_keys=False)
 
     with open('kinematics.yaml', 'w') as file:
-         yaml.dump(kinematics_yaml, file, sort_keys=False)
+        yaml.dump(kinematics_yaml, file, sort_keys=False)
 
     with open('uncertainties.yaml', 'w') as file:
         yaml.dump(uncertainties_yaml, file, sort_keys=False)
 
-# jet altcorr1 data
+    # jet altcorr1 data
 
     for i in tables_altcorr1:
         if i == 1:
@@ -111,7 +140,7 @@ def processData():
             y_min = 2.5
             y_max = 3
         y_central = None
-        hepdata_tables="rawdata/atlas_inclusive_jet2015_r04_altcorr1_eta"+str(i)+".yaml"
+        hepdata_tables = "rawdata/atlas_inclusive_jet2015_r04_altcorr1_eta" + str(i) + ".yaml"
         with open(hepdata_tables, 'r') as file:
             input = yaml.safe_load(file)
 
@@ -124,36 +153,52 @@ def processData():
             value_delta = 0
             error_value = {}
             for k in range(len(values[j]['errors'])):
-                se_delta, se_sigma = se(values[j]['errors'][k]['asymerror']['plus'], values[j]['errors'][k]['asymerror']['minus'])
+                se_delta, se_sigma = symmetrize_errors(
+                    values[j]['errors'][k]['asymerror']['plus'],
+                    values[j]['errors'][k]['asymerror']['minus'],
+                )
                 value_delta = value_delta + se_delta
                 error_label = str(values[j]['errors'][k]['label'])
                 error_value[error_label] = se_sigma
             data_central_value = values[j]['value'] + value_delta
             data_central_altcorr1.append(data_central_value)
             error_altcorr1.append(error_value)
-            kin_value = {'sqrts': {'min': None, 'mid': sqrts, 'max': None}, 'pT': {'min': pT_min, 'mid': None, 'max': pT_max}, 'y': {'min': y_min, 'mid': y_central, 'max': y_max}}
+            kin_value = {
+                'sqrts': {'min': None, 'mid': sqrts, 'max': None},
+                'pT': {'min': pT_min, 'mid': None, 'max': pT_max},
+                'y': {'min': y_min, 'mid': y_central, 'max': y_max},
+            }
             kin_altcorr1.append(kin_value)
 
-    hepdata_tables="rawdata/atlas_inclusive_jet2015_r04_altcorr1_eta1.yaml"
+    hepdata_tables = "rawdata/atlas_inclusive_jet2015_r04_altcorr1_eta1.yaml"
     with open(hepdata_tables, 'r') as file:
         input = yaml.safe_load(file)
     error_definition_altcorr1 = {}
-    error_definition_altcorr1['stat'] = {'description': 'total statistical uncertainty', 'treatment': 'ADD', 'type': 'UNCORR'}
+    error_definition_altcorr1['stat'] = {
+        'description': 'total statistical uncertainty',
+        'treatment': 'ADD',
+        'type': 'UNCORR',
+    }
     for i in range(1, len(input['dependent_variables'][0]['values'][0]['errors'])):
         error_name = input['dependent_variables'][0]['values'][0]['errors'][i]['label']
-        error_definition_altcorr1[error_name] = {'description': '', 'treatment': 'MULT', 'type': 'CORR'}
+        error_definition_altcorr1[error_name] = {
+            'description': '',
+            'treatment': 'MULT',
+            'type': 'CORR',
+        }
 
     data_central_altcorr1_yaml = {'data_central': data_central_altcorr1}
     kinematics_altcorr1_yaml = {'bins': kin_altcorr1}
     uncertainties_altcorr1_yaml = {'definitions': error_definition_altcorr1, 'bins': error_altcorr1}
 
     with open('data_altcorr1.yaml', 'w') as file:
-         yaml.dump(data_central_altcorr1_yaml, file, sort_keys=False)
+        yaml.dump(data_central_altcorr1_yaml, file, sort_keys=False)
 
     with open('kinematics_altcorr1.yaml', 'w') as file:
-         yaml.dump(kinematics_altcorr1_yaml, file, sort_keys=False)
+        yaml.dump(kinematics_altcorr1_yaml, file, sort_keys=False)
 
     with open('uncertainties_altcorr1.yaml', 'w') as file:
         yaml.dump(uncertainties_altcorr1_yaml, file, sort_keys=False)
 
+
 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
@@ -1,14 +1,31 @@
-import yaml
 from math import sqrt
 
-def se(delta_plus, delta_minus):
-
-    semi_diff = (delta_plus + delta_minus)/2
-    average = (delta_plus - delta_minus)/2
+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)
+    se_sigma = sqrt(average * average + 2 * semi_diff * semi_diff)
     return se_delta, se_sigma
 
+
 def processData():
     with open('metadata.yaml', 'r') as file:
         metadata = yaml.safe_load(file)
@@ -39,7 +56,7 @@ def processData():
             y_min = 2.5
             y_max = 3
         y_central = None
-        hepdata_tables="rawdata/atlas_mjj_jet2015_r04_ystar"+str(i)+".yaml"
+        hepdata_tables = "rawdata/atlas_mjj_jet2015_r04_ystar" + str(i) + ".yaml"
         with open(hepdata_tables, 'r') as file:
             input = yaml.safe_load(file)
 
@@ -52,21 +69,32 @@ def processData():
             value_delta = 0
             error_value = {}
             for k in range(len(values[j]['errors'])):
-                se_delta, se_sigma = se(values[j]['errors'][k]['asymerror']['plus'], values[j]['errors'][k]['asymerror']['minus'])
+                se_delta, se_sigma = symmetrize_errors(
+                    values[j]['errors'][k]['asymerror']['plus'],
+                    values[j]['errors'][k]['asymerror']['minus'],
+                )
                 value_delta = value_delta + se_delta
                 error_label = str(values[j]['errors'][k]['label'])
                 error_value[error_label] = se_sigma
             data_central_value = values[j]['value'] + value_delta
             data_central.append(data_central_value)
             error.append(error_value)
-            kin_value = {'sqrts': {'min': None, 'mid': sqrts, 'max': None}, 'm_jj': {'min': m_jj_min, 'mid': None, 'max': m_jj_max}, 'ystar': {'min': y_min, 'mid': y_central, 'max': y_max}}
+            kin_value = {
+                'sqrts': {'min': None, 'mid': sqrts, 'max': None},
+                'm_jj': {'min': m_jj_min, 'mid': None, 'max': m_jj_max},
+                'ystar': {'min': y_min, 'mid': y_central, 'max': y_max},
+            }
             kin.append(kin_value)
 
-    hepdata_tables="rawdata/atlas_mjj_jet2015_r04_ystar1.yaml"
+    hepdata_tables = "rawdata/atlas_mjj_jet2015_r04_ystar1.yaml"
     with open(hepdata_tables, 'r') as file:
         input = yaml.safe_load(file)
     error_definition = {}
-    error_definition['stat'] = {'description': 'total statistical uncertainty', 'treatment': 'ADD', 'type': 'UNCORR'}
+    error_definition['stat'] = {
+        'description': 'total statistical uncertainty',
+        'treatment': 'ADD',
+        'type': 'UNCORR',
+    }
     for i in range(1, len(input['dependent_variables'][0]['values'][0]['errors'])):
         error_name = input['dependent_variables'][0]['values'][0]['errors'][i]['label']
         error_definition[error_name] = {'description': '', 'treatment': 'MULT', 'type': 'CORR'}
@@ -76,12 +104,13 @@ def processData():
     uncertainties_yaml = {'definitions': error_definition, 'bins': error}
 
     with open('data.yaml', 'w') as file:
-         yaml.dump(data_central_yaml, file, sort_keys=False)
+        yaml.dump(data_central_yaml, file, sort_keys=False)
 
     with open('kinematics.yaml', 'w') as file:
-         yaml.dump(kinematics_yaml, file, sort_keys=False)
+        yaml.dump(kinematics_yaml, file, sort_keys=False)
 
     with open('uncertainties.yaml', 'w') as file:
         yaml.dump(uncertainties_yaml, file, sort_keys=False)
 
+
 processData()