Belle II Software  release-05-01-25
caf_boostvector.py
1 # -*- coding: utf-8 -*-
2 
3 """
4 Airflow script to perform BoostVector calibration.
5 """
6 
7 from prompt import CalibrationSettings
8 from prompt.calibrations.caf_beamspot import settings as beamspot
9 
10 
11 settings = CalibrationSettings(
12  name="BoostVector Calibrations",
13  expert_username="zlebcr",
14  description=__doc__,
15  input_data_formats=["cdst"],
16  input_data_names=["mumutight_calib"],
17  expert_config={
18  "outerLoss": "pow(rawTime - 8.0, 2) + 10 * pow(maxGap, 2)",
19  "innerLoss": "pow(rawTime - 8.0, 2) + 10 * pow(maxGap, 2)"},
20  depends_on=[beamspot])
21 
22 
23 
24 
25 def get_calibrations(input_data, **kwargs):
26  """
27  Parameters:
28  input_data (dict): Should contain every name from the 'input_data_names' variable as a key.
29  Each value is a dictionary with {"/path/to/file_e1_r5.root": IoV(1,5,1,5), ...}. Useful for
30  assigning to calibration.files_to_iov
31 
32  **kwargs: Configuration options to be sent in. Since this may change we use kwargs as a way to help prevent
33  backwards compatibility problems. But you could use the correct arguments in b2caf-prompt-run for this
34  release explicitly if you want to.
35 
36  Currently only kwargs["output_iov"] is used. This is the output IoV range that your payloads should
37  correspond to. Generally your highest ExpRun payload should be open ended e.g. IoV(3,4,-1,-1)
38 
39  Returns:
40  list(caf.framework.Calibration): All of the calibration objects we want to assign to the CAF process
41  """
42  import basf2
43  # Set up config options
44 
45  # In this script we want to use one sources of input data.
46  # Get the input files from the input_data variable
47  file_to_iov_physics = input_data["mumutight_calib"]
48 
49  # We might have requested an enormous amount of data across a run range.
50  # There's a LOT more files than runs!
51  # Lets set some limits because this calibration doesn't need that much to run.
52  max_files_per_run = 1000000
53 
54  # We filter out any more than 100 files per run. The input data files are sorted alphabetically by b2caf-prompt-run
55  # already. This procedure respects that ordering
56  from prompt.utils import filter_by_max_files_per_run
57 
58  reduced_file_to_iov_physics = filter_by_max_files_per_run(file_to_iov_physics, max_files_per_run)
59  input_files_physics = list(reduced_file_to_iov_physics.keys())
60  basf2.B2INFO(f"Total number of files actually used as input = {len(input_files_physics)}")
61 
62  # Get the overall IoV we our process should cover. Includes the end values that we may want to ignore since our output
63  # IoV should be open ended. We could also use this as part of the input data selection in some way.
64  requested_iov = kwargs.get("requested_iov", None)
65 
66  from caf.utils import IoV
67  # The actual value our output IoV payload should have. Notice that we've set it open ended.
68  output_iov = IoV(requested_iov.exp_low, requested_iov.run_low, -1, -1)
69 
70 
72 
73  from ROOT.Belle2 import BoostVectorAlgorithm
74  from basf2 import create_path, register_module
75  import modularAnalysis as ana
76  import vertex
77 
78 
80 
81  from caf.framework import Calibration
82  from caf.strategies import SingleIOV
83  from reconstruction import prepare_cdst_analysis
84 
85  # module to be run prior the collector
86  rec_path_1 = create_path()
87  prepare_cdst_analysis(path=rec_path_1, components=['CDC', 'ECL', 'KLM'])
88 
89  muSelection = '[p>1.0]'
90  muSelection += ' and abs(dz)<2.0 and abs(dr)<0.5'
91  muSelection += ' and nPXDHits >=1 and nSVDHits >= 8 and nCDCHits >= 20'
92  ana.fillParticleList('mu+:BV', muSelection, path=rec_path_1)
93  ana.reconstructDecay('Upsilon(4S):BV -> mu+:BV mu-:BV', '9.5<M<11.5', path=rec_path_1)
94  vertex.treeFit('Upsilon(4S):BV', updateAllDaughters=True, ipConstraint=True, path=rec_path_1)
95 
96  collector_bv = register_module('BoostVectorCollector', Y4SPListName='Upsilon(4S):BV')
97  algorithm_bv = BoostVectorAlgorithm()
98  algorithm_bv.setOuterLoss(kwargs['expert_config']['outerLoss'])
99  algorithm_bv.setInnerLoss(kwargs['expert_config']['innerLoss'])
100 
101  calibration_bv = Calibration('BoostVector',
102  collector=collector_bv,
103  algorithms=algorithm_bv,
104  input_files=input_files_physics,
105  pre_collector_path=rec_path_1)
106 
107  calibration_bv.strategies = SingleIOV
108 
109  # Do this for the default AlgorithmStrategy to force the output payload IoV
110  # It may be different if you are using another strategy like SequentialRunByRun
111  for algorithm in calibration_bv.algorithms:
112  algorithm.params = {"iov_coverage": output_iov}
113 
114  # Most other options like database chain and backend args will be overwritten by b2caf-prompt-run.
115  # So we don't bother setting them.
116 
117  # You must return all calibrations you want to run in the prompt process, even if it's only one
118  return [calibration_bv]
119 
120 
prompt.utils
Definition: utils.py:1
vertex.treeFit
def treeFit(list_name, conf_level=0.001, massConstraint=[], ipConstraint=False, updateAllDaughters=False, customOriginConstraint=False, customOriginVertex=[0.001, 0, 0.0116], customOriginCovariance=[0.0048, 0, 0, 0, 0.003567, 0, 0, 0, 0.0400], path=None)
Definition: vertex.py:191
Calibration
Definition: Calibration.py:1