12 variables = [
'M',
'p',
'pt',
'pz',
13 'daughter(0, p)',
'daughter(0, pz)',
'daughter(0, pt)',
14 'daughter(1, p)',
'daughter(1, pz)',
'daughter(1, pt)',
15 'daughter(2, p)',
'daughter(2, pz)',
'daughter(2, pt)',
16 'chiProb',
'dr',
'dz',
17 'daughter(0, dr)',
'daughter(1, dr)',
18 'daughter(0, dz)',
'daughter(1, dz)',
19 'daughter(0, chiProb)',
'daughter(1, chiProb)',
'daughter(2, chiProb)',
20 'daughter(0, kaonID)',
'daughter(0, pionID)',
21 'daughterInvariantMass(0, 1)',
'daughterInvariantMass(0, 2)',
'daughterInvariantMass(1, 2)']
24 def feature_importance(state):
26 Return a list containing the feature importances
28 print(
"Called overwritten feature importance")
36 print(
"Called overwritten load")
41 print(
"Executed python script")
43 if __name__ ==
"__main__":
46 if not (os.path.isfile(
'train.root')
and os.path.isfile(
'test.root')):
47 print(
"TEST SKIPPED: Not runnable on build bot", file=sys.stderr)
50 general_options = basf2_mva.GeneralOptions()
51 general_options.m_datafiles = basf2_mva.vector(
"train.root")
52 general_options.m_treename =
"tree"
53 general_options.m_variables = basf2_mva.vector(*variables)
54 general_options.m_target_variable =
"isSignal"
55 general_options.m_identifier =
"Python.xml"
57 specific_options = basf2_mva.PythonOptions()
58 specific_options.m_training_fraction = 0.9
59 specific_options.m_nIterations = 2
60 specific_options.m_mini_batch_size = 10000
61 specific_options.m_framework =
'test'
64 with tempfile.TemporaryDirectory()
as tempdir:
65 os.symlink(os.path.abspath(
'train.root'), tempdir +
'/' + os.path.basename(
'train.root'))
66 os.symlink(os.path.abspath(
'test.root'), tempdir +
'/' + os.path.basename(
'test.root'))
69 basf2_mva.teacher(general_options, specific_options)
71 basf2_mva.expert(basf2_mva.vector(
"Python.xml"),
72 basf2_mva.vector(
'train.root'),
'tree',
'expert.root')
74 specific_options.m_steering_file =
'mva/tests/python.py'
75 basf2_mva.teacher(general_options, specific_options)
77 basf2_mva.expert(basf2_mva.vector(
"Python.xml"),
78 basf2_mva.vector(
'train.root'),
'tree',
'expert.root')