Belle II Software  release-05-01-25
xgboost_default.py
1 #!/usr/bin/env python3
2 # -*- coding: utf-8 -*-
3 
4 # Thomas Keck 2017
5 
6 import numpy as np
7 import basf2_mva
8 import basf2_mva_util
9 import time
10 
11 if __name__ == "__main__":
12  from basf2 import conditions
13  # NOTE: do not use testing payloads in production! Any results obtained like this WILL NOT BE PUBLISHED
14  conditions.testing_payloads = [
15  'localdb/database.txt'
16  ]
17 
18  variables = ['M', 'p', 'pt', 'pz',
19  'daughter(0, p)', 'daughter(0, pz)', 'daughter(0, pt)',
20  'daughter(1, p)', 'daughter(1, pz)', 'daughter(1, pt)',
21  'daughter(2, p)', 'daughter(2, pz)', 'daughter(2, pt)',
22  'chiProb', 'dr', 'dz',
23  'daughter(0, dr)', 'daughter(1, dr)',
24  'daughter(0, dz)', 'daughter(1, dz)',
25  'daughter(0, chiProb)', 'daughter(1, chiProb)', 'daughter(2, chiProb)',
26  'daughter(0, kaonID)', 'daughter(0, pionID)',
27  'daughterInvariantMass(0, 1)', 'daughterInvariantMass(0, 2)', 'daughterInvariantMass(1, 2)']
28 
29  general_options = basf2_mva.GeneralOptions()
30  general_options.m_datafiles = basf2_mva.vector("train.root")
31  general_options.m_treename = "tree"
32  general_options.m_identifier = "XGBoost"
33  general_options.m_variables = basf2_mva.vector(*variables)
34  general_options.m_target_variable = "isSignal"
35 
36  specific_options = basf2_mva.PythonOptions()
37  specific_options.m_steering_file = 'mva/examples/python/xgboost_default.py'
38  specific_options.m_framework = "xgboost"
39  param = ('{"max_depth": 3, "eta": 0.1, "silent": 1, "objective": "binary:logistic",'
40  '"subsample": 0.5, "nthread": 1, "nTrees": 100}')
41  specific_options.m_config = param
42 
43  test_data = ["test.root"] * 10
44  training_start = time.time()
45  basf2_mva.teacher(general_options, specific_options)
46  training_stop = time.time()
47  training_time = training_stop - training_start
48  method = basf2_mva_util.Method(general_options.m_identifier)
49  inference_start = time.time()
50  p, t = method.apply_expert(basf2_mva.vector(*test_data), general_options.m_treename)
51  inference_stop = time.time()
52  inference_time = inference_stop - inference_start
54  print("XGBoost", training_time, inference_time, auc)
basf2_mva_util.calculate_roc_auc
def calculate_roc_auc(p, t)
Definition: basf2_mva_util.py:39
basf2_mva_util.Method
Definition: basf2_mva_util.py:81