option to save cfgs + figures for application

ML/MLApplication.py

@@ -7,6 +7,7 @@
 import sys
 import argparse
 import yaml
+import matplotlib.pyplot as plt
 
 from hipe4ml.model_handler import ModelHandler
 from hipe4ml.tree_handler import TreeHandler
@@ -22,6 +23,13 @@ def main(): #pylint: disable=too-many-statements, too-many-branches
         inputCfg = yaml.load(ymlCfgFile, yaml.FullLoader)
     print('Loading analysis configuration: Done!')
 
+    if inputCfg.get('savecfg'):
+        # Save the YAML file to the folder
+        if not os.path.isdir(os.path.expanduser(inputCfg['standalone_appl']['output_dir'])):
+            os.makedirs(os.path.expanduser(inputCfg['standalone_appl']['output_dir']))
+        with open(f'{os.path.expanduser(inputCfg["standalone_appl"]["output_dir"])}/cfg.yml', 'w') as ymlOutFile:
+            yaml.dump(inputCfg, ymlOutFile, default_flow_style=False)
+
     PtBins = [[a, b] for a, b in zip(inputCfg['pt_ranges']['min'], inputCfg['pt_ranges']['max'])]
     OutputLabels = [inputCfg['output']['out_labels']['Bkg'],
                     inputCfg['output']['out_labels']['Prompt']]
@@ -49,7 +57,7 @@ def main(): #pylint: disable=too-many-statements, too-many-branches
         else:
             DataHandler = TreeHandler(inputFile, treename)
 
-        DataHandler.slice_data_frame('pt_cand', PtBins, True)
+        DataHandler.slice_data_frame('fPt', PtBins, True)
         print(f'Loading and preparing data files {inputFile}: Done!')
 
         print('Applying ML model to dataframes: ...', end='\r')
@@ -67,10 +75,10 @@ def main(): #pylint: disable=too-many-statements, too-many-branches
             if not isinstance(ColumnsToSaveFinal, list):
                 print('\033[91mERROR: column_to_save_list must be defined!\033[0m')
                 sys.exit()
-            if 'inv_mass' not in ColumnsToSaveFinal:
-                print('\033[93mWARNING: inv_mass is not going to be saved in the output dataframe!\033[0m')
-            if 'pt_cand' not in ColumnsToSaveFinal:
-                print('\033[93mWARNING: pt_cand is not going to be saved in the output dataframe!\033[0m')
+            if 'fM' not in ColumnsToSaveFinal:
+                print('\033[93mWARNING: fM is not going to be saved in the output dataframe!\033[0m')
+            if 'fPt' not in ColumnsToSaveFinal:
+                print('\033[93mWARNING: fPt is not going to be saved in the output dataframe!\033[0m')
             if 'pt_B' in ColumnsToSaveFinal and 'pt_B' not in DataDfPtSel.columns:
                 ColumnsToSaveFinal.remove('pt_B') # only in MC
             DataDfPtSel = DataDfPtSel.loc[:, ColumnsToSaveFinal]
@@ -80,6 +88,18 @@ def main(): #pylint: disable=too-many-statements, too-many-branches
                 for Pred, Lab in enumerate(OutputLabels):
                     DataDfPtSel[f'ML_output_{Lab}'] = yPred[:, Pred]
             DataDfPtSel.to_parquet(f'{OutPutDirPt}/{outName}_pT_{PtBin[0]}_{PtBin[1]}_ModelApplied.parquet.gzip')
+
+            if inputCfg.get('savedistrs'):
+                plt.figure(figsize=(10, 6))
+                for col in DataDfPtSel.columns:
+                    if 'ML_output' in col:
+                        plt.hist(DataDfPtSel[col], bins=100, alpha=0.5, label=col, log=True)
+                plt.title(f'Distributions of ML Outputs for {outName}')
+                plt.xlabel('Score')
+                plt.ylabel('Frequency (log scale)')
+                plt.legend()
+                plt.savefig(f"{OutPutDirPt}/{outName}Distrs.pdf", format="pdf", bbox_inches="tight")
+
             del DataDfPtSel
         print('Applying ML model to dataframes: Done!')
 

ML/MLClassification.py

@@ -315,6 +315,13 @@ def main(): #pylint: disable=too-many-statements
         inputCfg = yaml.load(ymlCfgFile, yaml.FullLoader)
     print('Loading analysis configuration: Done!')
 
+    if inputCfg.get('savecfg'):
+        # Save the YAML file to the folder
+        if not os.path.isdir(os.path.expanduser(inputCfg['output']['dir'])):
+            os.makedirs(os.path.expanduser(inputCfg['output']['dir']))
+        with open(f'{os.path.expanduser(inputCfg["output"]["dir"])}/cfg.yml', 'w') as ymlOutFile:
+            yaml.dump(inputCfg, ymlOutFile, default_flow_style=False)
+
     print('Loading and preparing data files: ...', end='\r')
     PromptHandler = TreeHandler(inputCfg['input']['prompt'], inputCfg['input']['treename'])
     FDHandler = None if inputCfg['input']['FD'] is None else TreeHandler(inputCfg['input']['FD'],