Clean code + remove unused code

nnpdf_data/nnpdf_data/commondata/CMS_WCHARM_13TEV/filter.py

@@ -5,12 +5,9 @@
 import logging
 
 from filter_utils import Extractor
-import numpy as np
-import yaml
 
 logging.basicConfig(level=logging.INFO, format='[%(levelname)s] %(message)s')
 
-
 if __name__ == "__main__":
     CMS_WCHARM = Extractor("./metadata.yaml", "WPWM-TOT-UNNORM", mult_factor=1000)
-    _, _, _ = CMS_WCHARM.generate_data(variant='default', save_to_yaml=True)
+    CMS_WCHARM.generate_data()

nnpdf_data/nnpdf_data/commondata/CMS_WCHARM_13TEV/filter_utils.py

@@ -1,30 +1,19 @@
 import logging
-import os
 
 import numpy as np
-import pandas as pd
 from sys_uncertainties import SYS_DEFINITIONS, SYS_UNC_BY_BIN
 import yaml
 
 from nnpdf_data.filter_utils.utils import prettify_float, symmetrize_errors
 
 yaml.add_representer(float, prettify_float)
 
-SQRTS = 8000
 MW2 = 80.385**2
 CMSLUMI13 = 2.5  # %
 
-# List of systematic uncertainties that shuold
-# be considered uncorrelated
-UNCORR_SYS_UNC = ['UnfoldMCstat', 'UnfoldOtherGen', 'UnfoldReweight']
-ART_LABEL = 'art_corr_unc'
 STAT_LABEL = 'stat_uncorr_unc'
 TABLE = ''
 
-# From Table 1 of the paper
-SYS_UNC_by_bin = [{}]
-
-
 class Extractor:
     """
     Extracts kinematics, central data, and uncertainties for a given dataset
@@ -61,11 +50,6 @@ def __init__(self, metadata_file, observable, mult_factor=1):
         self.kin_labels = self.metadata['kinematic_coverage']
         self.ndata = self.metadata['ndata']
 
-        # Collect diagonal absoulute uncertainties
-        # self.diag_unc = self.__collect_diag_unc()
-        # self.unc_labels = list(self.diag_unc[0].keys())
-        # self.unc_labels.pop(0)
-
     def __retrieve_table(self, table_id):
         """
         Implementation of the lazy loading for the tables. If the table
@@ -109,8 +93,6 @@ def __extract_kinematics(self, table: dict):
         ----------
         table: dict
           Dictionary containing the bins in the transverse momentum
-        tab_number: int
-          Index to select the range of the second kinematic variable
 
         Return
         ------
@@ -209,7 +191,7 @@ def symmetrized_sys_unc(self):
             symmetrized_uncs.append(unc_dict)
         return symmetrized_uncs
 
-    def __build_unc_definitions(self, variant='default'):
+    def __build_unc_definitions(self):
         unc_definitions = {}
 
         # Statistical uncertainty
@@ -229,18 +211,19 @@ def __build_unc_definitions(self, variant='default'):
         # Add systematic uncertainty
         unc_definitions = unc_definitions | SYS_DEFINITIONS
 
-        if variant != 'default':
-            raise ValueError(f'The variant {variant} is not implemented yet.')
-
         return unc_definitions
 
-    def generate_data(self, variant='default', save_to_yaml=False, path='./'):
+    def generate_data(self):
+        '''
+        Collect central data, kinematics, and uncertainties ans save them
+        into yaml files.
+        '''
         # Get central data and kinematics
         central_data, stat_unc, _ = self.generate_data_and_unc(self.mult_factor)
         kinematics = self.generate_kinematics()
 
         # Uncertainty definitions
-        unc_definitions = self.__build_unc_definitions(variant=variant)
+        unc_definitions = self.__build_unc_definitions()
 
         sys_artificial = []  # Initialize vector of artificial uncertainties
 
@@ -268,37 +251,30 @@ def generate_data(self, variant='default', save_to_yaml=False, path='./'):
             unc_dict = unc_dict | tmp
 
             sys_artificial.append(unc_dict)
-
-        if save_to_yaml:
-            # Save kinematics into file
-            logging.info("Dumping kinematics to file...")
-            kinematics_yaml = {'bins': kinematics}
-            with open(path + self.metadata['kinematics']['file'], 'w') as kin_out_file:
-                yaml.dump(kinematics_yaml, kin_out_file, sort_keys=False)
-            logging.info("Done!")
-
-            # Save central data into file
-            logging.info("Dumping kinematics to file...")
-            dat_central_yaml = {'data_central': central_data}
-            file_name = self.metadata['data_central']
-            with open(path + file_name, 'w') as dat_out_file:
-                yaml.dump(dat_central_yaml, dat_out_file, sort_keys=False)
-            logging.info("Done!")
-
-            # Save unertainties
-            logging.info("Dumping kinematics to file...")
-            uncertainties_yaml = {'definitions': unc_definitions, 'bins': sys_artificial}
-            file_name = (
-                self.metadata['data_uncertainties'][0]
-                if variant == 'default'
-                else self.metadata['variants'][variant]['data_uncertainties'][0]
-            )
-            with open(path + file_name, 'w') as dat_out_file:
-                yaml.dump(uncertainties_yaml, dat_out_file, sort_keys=False)
-            logging.info("Done!")
-            return kinematics, central_data, sys_artificial
-        else:
-            return kinematics, central_data, sys_artificial
-
-    def get_table(self, table_id):
-        return self.__retrieve_table(table_id)
+
+        # Local path for yaml files
+        path = './'
+
+        # Save kinematics into file
+        logging.info("Dumping kinematics to file...")
+        kinematics_yaml = {'bins': kinematics}
+        with open(path + self.metadata['kinematics']['file'], 'w') as kin_out_file:
+            yaml.dump(kinematics_yaml, kin_out_file, sort_keys=False)
+        logging.info("Done!")
+
+        # Save central data into file
+        logging.info("Dumping kinematics to file...")
+        dat_central_yaml = {'data_central': central_data}
+        file_name = self.metadata['data_central']
+        with open(path + file_name, 'w') as dat_out_file:
+            yaml.dump(dat_central_yaml, dat_out_file, sort_keys=False)
+        logging.info("Done!")
+
+        # Save unertainties
+        logging.info("Dumping kinematics to file...")
+        uncertainties_yaml = {'definitions': unc_definitions, 'bins': sys_artificial}
+        file_name = self.metadata['data_uncertainties'][0]
+        with open(path + file_name, 'w') as dat_out_file:
+            yaml.dump(uncertainties_yaml, dat_out_file, sort_keys=False)
+        logging.info("Done!")
+        return kinematics, central_data, sys_artificial