TrainLambdaSelector.py

#!/usr/bin/env python3
 

 

 
import basf2 as b2
import basf2_mva
import LambdaSelector as LambdaSelector
 
# Train weight file for V0 Selection.
# name of output file is specified by the argument 'mva_identifier'.
LambdaSelector.V0Selector_Training(
    train_data=b2.find_file('LambdaSelector_train_V0Selector.root', 'examples', False),
    tree_name="tree",
    mva_identifier="MVA_LGBM_V0Selector.root",
    target_variable="isSignal",
    options={'max_events': 1000}  # number of training events manually reduced to speed up test, set to 0 for full statistics
)
 
# Train weight file for V0 Selection.
# name of output file is specified by the argument 'mva_identifier'.
LambdaSelector.KsVeto_Training(
    train_data=b2.find_file('LambdaSelector_train_KsVeto.root', 'examples', False),
    tree_name="tree",
    mva_identifier="MVA_LGBM_KsVeto.root",
    target_variable="isSignal",
    options={'max_events': 1000}  # number of training events manually reduced to speed up test, set to 0 for full statistics
)
 
# apply mva to the training data
basf2_mva.expert(basf2_mva.vector('MVA_LGBM_V0Selector.root'),
                 basf2_mva.vector(b2.find_file('LambdaSelector_train_V0Selector.root', 'examples', False)),
                 'tree', 'MVAExpert_V0Selector.root')
basf2_mva.expert(basf2_mva.vector('MVA_LGBM_KsVeto.root'),
                 basf2_mva.vector(b2.find_file('LambdaSelector_train_KsVeto.root', 'examples', False)),
                 'tree', 'MVAExpert_KsVeto.root')