Belle II Software  release-06-02-00
inputVariablesPlots.py
1 #!/usr/bin/env python3
2 # -*- coding: utf-8 -*-
3 
4 
11 
12 
24 
25 import os
26 import glob
27 import sys
28 from matplotlib.ticker import FormatStrFormatter
29 import matplotlib.pyplot as plt
30 import ROOT
31 from ROOT import Belle2
32 import basf2 as b2
33 import flavorTagger as ft
34 from defaultEvaluationParameters import categories
35 
36 import numpy as np
37 import matplotlib as mpl
38 mpl.use('Agg')
39 mpl.rcParams.update({'font.size': 22})
40 mpl.rcParams['text.usetex'] = True
41 mpl.rcParams['text.latex.preamble'] = [r"\usepackage{amsmath}"]
42 
43 ROOT.gROOT.SetBatch(True)
44 
45 if len(sys.argv) != 5:
46  sys.exit("Must provide 4 arguments: [Belle or Belle2] [BGx0 or BGx1] [training] [workingDirectory]"
47  )
48 
49 belleOrBelle2 = sys.argv[1]
50 MCtype = str(sys.argv[2])
51 decayChannelTrainedOn = str(sys.argv[3]) # Decay channel of the weight files "JPsiKs" or "nunubar"
52 workingDirectory = sys.argv[4]
53 
54 filesDirectory = workingDirectory + '/FlavorTagging/TrainedMethods'
55 
56 if decayChannelTrainedOn == 'JPsiKs':
57  decayChannelTrainedOn = 'JpsiKs_mu'
58 
59 weightFiles = 'B2' + decayChannelTrainedOn + MCtype
60 
61 
62 ROOT.TH1.SetDefaultSumw2()
63 
64 allInputVariables = []
65 
66 
67 ft.WhichCategories(categories)
68 ft.setVariables()
69 
70 belleOrBelle2Flag = belleOrBelle2
71 
72 identifiersExtraInfosDict = dict()
73 identifiersExtraInfosKaonPion = []
74 
75 if belleOrBelle2 == "Belle":
76  unitImp = "cm"
77 
78 dBw = 50
79 
80 pBins = 50
81 fBins = 100
82 
83 unitImp = "mm"
84 
85 variablesPlotParamsDict = {
86  'useCMSFrame(p)': ['useCMSFrame__bop__bc', pBins, 0, 3, r'$p^*\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
87  'useCMSFrame(pt)': ['useCMSFrame__bopt__bc', pBins, 0, 3, r'$p_{\rm t}^*\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
88  'p': ['p', pBins, 0, 3, r'$p\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
89  'pt': ['pt', pBins, 0, 3, r'$p_{\rm t}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
90  'cosTheta': ['cosTheta', dBw, -1, 1.01, r'$\cos{\theta}$', ""],
91  ft.eId[ft.getBelleOrBelle2()]: [Belle2.makeROOTCompatible(ft.eId[ft.getBelleOrBelle2()]),
92  dBw, 0, 1.01, r'$\mathcal{L}_{e}$', ""],
93  'eid_dEdx': ['eid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{{\rm d}E/{\rm d}x}$', ""],
94  'eid_TOP': ['eid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{\rm TOP}$', ""],
95  'eid_ARICH': ['eid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{\rm ARICH}$', ""],
96  'eid_ECL': ['eid_ECL', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{\rm ECL}$', ""],
97  'BtagToWBosonVariables(recoilMassSqrd)': ['BtagToWBosonVariables__borecoilMassSqrd__bc', fBins,
98  0, 100, r'$M_{\rm rec}^2\ [{\rm GeV}^2/c^4]$', r"{\rm GeV}^2/c^4"],
99  'BtagToWBosonVariables(pMissCMS)': [
100  'BtagToWBosonVariables__bopMissCMS__bc', 60, 0, 3.6,
101  r'$p^*_{\rm miss}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
102  'BtagToWBosonVariables(cosThetaMissCMS)': ['BtagToWBosonVariables__bocosThetaMissCMS__bc',
103  dBw, -1, 1.01, r'$\cos{\theta^*_{\rm miss}}$', ""],
104  'BtagToWBosonVariables(EW90)': ['BtagToWBosonVariables__boEW90__bc',
105  dBw, 0, 4, r'$E_{90}^{W}\ [{\rm GeV}]$', r"{\rm GeV}\, "],
106  'BtagToWBosonVariables(recoilMass)': ['sqrt(abs(BtagToWBosonVariables__borecoilMassSqrd__bc))',
107  dBw, 0, 12, r'$M_{\rm rec}\ [{\rm GeV}/c^2]$', r"{\rm GeV}/c^2\, "],
108  'cosTPTO': ['cosTPTO', dBw, 0, 1.01, r'$\vert\cos{\theta^*_{\rm T}}\vert$', ""],
109  'ImpactXY': ['ImpactXY', dBw, 0, 0.5, r'$d_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
110  'z0': ['z0', dBw, 0, 1.0, r'$z_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
111  'y': ['y', dBw, -0.15, 0.15, r'$y_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
112  'OBoost': ['OBoost', dBw, -0.15, 0.15, r'$d_0^\prime\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
113  'distance': ['distance', dBw, 0, 1.5, r'$\xi_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
114  'chiProb': ['chiProb', dBw, 0, 1.01, r'$p$-${\rm value}$', ""],
115  ft.muId[ft.getBelleOrBelle2()]: [Belle2.makeROOTCompatible(ft.muId[ft.getBelleOrBelle2()]),
116  dBw, 0, 1.01, r'$\mathcal{L}_{\mu}$', ""],
117  'muid_dEdx': ['muid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{{\rm d}E/{\rm d}x}$', ""],
118  'muid_TOP': ['muid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{\rm TOP}$', ""],
119  'muid_ARICH': ['muid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{\rm ARICH}$', ""],
120  'muid_KLM': ['muid_KLM', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{\rm KLM}$', ""],
121  ft.KId[ft.getBelleOrBelle2()]: [Belle2.makeROOTCompatible(ft.KId[ft.getBelleOrBelle2()]),
122  dBw, 0, 1.01, r'$\mathcal{L}_{K}$', ""],
123  'Kid_dEdx': ['Kid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{K}^{{\rm d}E/{\rm d}x}$', ""],
124  'Kid_TOP': ['Kid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{K}^{\rm TOP}$', ""],
125  'Kid_ARICH': ['Kid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{K}^{\rm ARICH}$', ""],
126  'NumberOfKShortsInRoe': ['NumberOfKShortsInRoe', dBw, 0, 12, r'$n_{K^0_S}$', ""],
127  'ptTracksRoe': ['ptTracksRoe', fBins, 0, 6, r'$\Sigma\, p_{\rm t}^2\ [{\rm GeV^2}/c^2]$',
128  r"{\rm GeV^2}/c^2"],
129  'extraInfo(isRightCategory(Kaon))': ['extraInfo__boisRightCategory__boKaon__bc__bc',
130  dBw, 0, 1.01, r"$y_{\rm Kaon}$", ""],
131  'HighestProbInCat(pi+:inRoe, isRightCategory(SlowPion))': [
132  'HighestProbInCat__bopi__pl__clinRoe__cm__spisRightCategory__boSlowPion__bc__bc',
133  dBw, 0, 1.01, r"$y_{\rm SlowPion}$", ""],
134  'KaonPionVariables(cosKaonPion)': ['KaonPionVariables__bocosKaonPion__bc',
135  dBw, -1, 1.01, r'$\cos{\theta^*_{K\pi}}$', ""],
136  'KaonPionVariables(HaveOpositeCharges)': ['KaonPionVariables__boHaveOpositeCharges__bc',
137  dBw, 0, 1.01, r'$\frac{1 - q_{K} \cdot q_\pi}{2}$', ""],
138  'pionID': ['pionID', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}$', ""],
139  'piid_dEdx': ['piid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}^{{\rm d}E/{\rm d}x}$', ""],
140  'piid_TOP': ['piid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}^{\rm TOP}$', ""],
141  'piid_ARICH': ['piid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}^{\rm ARICH}$', ""],
142  'pi_vs_edEdxid': ['pi_vs_edEdxid', dBw, 0, 1.01, r'$\mathcal{L}_{\pi/e}^{{\rm d}E/{\rm d}x}$', ""],
143  'FSCVariables(pFastCMS)': ['FSCVariables__bopFastCMS__bc', pBins, 0, 3, r'$p^*_{\rm Fast}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
144  'FSCVariables(cosSlowFast)': ['FSCVariables__bocosSlowFast__bc', dBw, -1, 1.01, r'$\cos{\theta^*_{\rm SlowFast}}$', ''],
145  'FSCVariables(cosTPTOFast)': ['FSCVariables__bocosTPTOFast__bc', dBw, 0, 1.01, r'$\vert\cos{\theta^*_{\rm T, Fast}}\vert$', ''],
146  'FSCVariables(SlowFastHaveOpositeCharges)': ['FSCVariables__boSlowFastHaveOpositeCharges__bc',
147  dBw, 0, 1.01, r'$\frac{1 - q_{\rm Slow} \cdot q_{\rm Fast}}{2}$', ""],
148  'lambdaFlavor': ['lambdaFlavor', dBw, -1, 1.01, r'$q_{\Lambda}$', ""],
149  'M': ['M', dBw, 1.08, 1.22, r'$M_{\Lambda}\ [{\rm GeV}/c^2]$', r"{\rm MeV}/c^2\, "],
150  'cosAngleBetweenMomentumAndVertexVector': ['cosAngleBetweenMomentumAndVertexVector',
151  dBw, -1, 1.01,
152  r'$\cos{\theta_{\boldsymbol{x}_{\Lambda},\boldsymbol{p}_{\Lambda}}}$', ""],
153  'lambdaZError': ['lambdaZError', dBw, 0, 0.05, r'$\sigma_{\Lambda}^{zz}$', r"{\rm mm}\, "],
154  'daughter(0,p)': ['daughter__bo0__cmp__bc', dBw, 0, 1, r'$p_{\pi}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
155  'daughter(0,useCMSFrame(p))': ['daughter__bo0__cmuseCMSFrame__bop__bc__bc',
156  dBw, 0, 1, r'$p^*_{\pi}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
157  'daughter(1,p)': ['daughter__bo1__cmp__bc', dBw, 0, 2, r'$p_{p}\ [{\rm GeV}/c]$', r"{\rm GeV}/c"],
158  'daughter(1,useCMSFrame(p))': ['daughter__bo1__cmuseCMSFrame__bop__bc__bc',
159  dBw, 0, 2, r'$p^*_{p}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
160  'daughter(1,protonID)': ['daughter__bo1__cmprotonID__bc', dBw, 0, 1.01, r'$\mathcal{L}_{p}$', ""],
161  'daughter(0,pionID)': ['daughter__bo0__cmpionID__bc', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}$', ""]}
162 
163 if not b2.find_file('InputVariablesPlots', silent=True):
164  os.mkdir('./InputVariablesPlots')
165 
166 
167 def plotInputVariablesOfFlavorTagger():
168  """
169  Makes plots of the distribution of the input variables of the flavor tagger
170  for each category distinguishing between the target particles of the category (signal)
171  and all the other (bkg.)
172  """
173 
174  for (particleList, category, combinerVariable) in ft.eventLevelParticleLists:
175 
176  # if category != "SlowPion":
177  # continue
178 
179  if not b2.find_file('InputVariablesPlots/' + category, silent=True):
180  os.mkdir('./InputVariablesPlots/' + category)
181 
182  if particleList not in identifiersExtraInfosDict and category != 'KaonPion':
183  identifiersExtraInfosDict[particleList] = []
184 
185  methodPrefixEventLevel = "FlavorTagger_" + belleOrBelle2Flag + "_" + weightFiles + 'EventLevel' + category + 'FBDT'
186  treeName = methodPrefixEventLevel + "_tree"
187  targetVariable = 'isRightCategory(' + category + ')'
188 
189  tree = ROOT.TChain(treeName)
190 
191  workingFiles = glob.glob(filesDirectory + '/' + methodPrefixEventLevel + 'sampled*.root')
192  # print("workingFiles = ", workingFiles)
193  # workingFiles = glob.glob(filesDirectory + '/' + methodPrefixEventLevel + 'sampled1?.root')
194 
195  for iFile in workingFiles:
196  tree.AddFile(iFile)
197 
198  categoryInputVariables = []
199  trulyUsedInputVariables = []
200  for iVariable in tree.GetListOfBranches():
201 
202  managerVariableName = str(Belle2.invertMakeROOTCompatible(iVariable.GetName()))
203 
204  if managerVariableName in ft.variables[category] or managerVariableName == 'distance' or \
205  managerVariableName == 'z0' or managerVariableName == 'ImpactXY' or \
206  managerVariableName == 'y' or managerVariableName == 'OBoost':
207  if managerVariableName in categoryInputVariables:
208  continue
209 
210  categoryInputVariables.append(managerVariableName)
211  if managerVariableName in ft.variables[category]:
212  allInputVariables.append((category, managerVariableName))
213  trulyUsedInputVariables.append((category, managerVariableName))
214 
215  if managerVariableName not in identifiersExtraInfosDict[particleList] and category != 'KaonPion':
216  identifiersExtraInfosDict[particleList].append(managerVariableName)
217 
218  elif category == 'KaonPion' and managerVariableName not in identifiersExtraInfosKaonPion:
219  identifiersExtraInfosKaonPion.append(managerVariableName)
220 
221  # if managerVariableName not in variablesPlotParamsDict:
222  # variablesPlotParamsDict[managerVariableName] =
223  # [iVariable.GetName(), 100, 0, 2, iVariable.GetName(), "unit"]
224 
225  print("The number of variables used in " + category + " is = ", len(trulyUsedInputVariables))
226 
227  if category != 'KaonPion' and category != 'FSC' and category != 'MaximumPstar' and \
228  category != 'FastHadron' and category != 'Lambda':
229  categoryInputVariables.append('BtagToWBosonVariables(recoilMass)')
230 
231  for inputVariable in categoryInputVariables:
232 
233  print(inputVariable)
234 
235  nBins = variablesPlotParamsDict[inputVariable][1]
236  limXmin = variablesPlotParamsDict[inputVariable][2]
237  limXmax = variablesPlotParamsDict[inputVariable][3]
238 
239  if category == "SlowPion":
240  if inputVariable == 'p' or inputVariable == 'useCMSFrame(p)' or \
241  inputVariable == 'pt' or inputVariable == 'useCMSFrame(pt)':
242  nBins = 150
243  limXmax = 1.5
244 
245  if inputVariable == 'distance':
246  nBins = 80
247  limXmax = 2.4
248 
249  if inputVariable == 'ImpactXY':
250  nBins = 80
251  limXmax = 0.8
252 
253  if category == "Lambda":
254  if inputVariable == 'distance':
255  # nBins = 25
256  limXmax = 10
257 
258  if inputVariable == 'chiProb':
259  nBins = 25
260 
261  signalHistogram = ROOT.TH1F("signal" + category + str(Belle2.makeROOTCompatible(inputVariable)), "",
262  nBins,
263  limXmin,
264  limXmax)
265  backgroundHistogram = ROOT.TH1F("bkg" + category + str(Belle2.makeROOTCompatible(inputVariable)), "",
266  nBins,
267  limXmin,
268  limXmax)
269 
270  factorMultiplication = str()
271 
272  if belleOrBelle2 == "Belle2" and ((category != "Lambda" and inputVariable == 'distance') or inputVariable ==
273  'z0' or inputVariable == 'ImpactXY' or inputVariable ==
274  'y' or inputVariable == 'OBoost'):
275  factorMultiplication = "*10 "
276 
277  tree.Draw(variablesPlotParamsDict[inputVariable][0] + factorMultiplication + ">> signal" + category +
278  str(Belle2.makeROOTCompatible(inputVariable)), Belle2.makeROOTCompatible(targetVariable) + " > 0")
279 
280  tree.Draw(variablesPlotParamsDict[inputVariable][0] + factorMultiplication + ">> bkg" + category +
281  str(Belle2.makeROOTCompatible(inputVariable)), Belle2.makeROOTCompatible(targetVariable) + " < 1")
282 
283  signalScalingFactor = signalHistogram.Integral()
284  backgroundScalingFactor = backgroundHistogram.Integral()
285 
286  if signalScalingFactor == 0:
287  signalScalingFactor = 1
288 
289  if backgroundScalingFactor == 0:
290  backgroundScalingFactor = 1
291 
292  signalHistogram.Scale(1 / signalScalingFactor)
293  backgroundHistogram.Scale(1 / backgroundScalingFactor)
294 
295  signalArray = np.zeros((signalHistogram.GetNbinsX(), 2))
296  backgroundArray = np.zeros((backgroundHistogram.GetNbinsX(), 2))
297 
298  for i in range(0, signalHistogram.GetNbinsX()):
299  signalArray[i] = np.array([signalHistogram.GetBinCenter(i + 1), signalHistogram.GetBinContent(i + 1)])
300  backgroundArray[i] = np.array([backgroundHistogram.GetBinCenter(i + 1), backgroundHistogram.GetBinContent(i + 1)])
301 
302  fig1 = plt.figure(1, figsize=(11, 10))
303 
304  # if inputVariable == 'Kid_dEdx' or inputVariable == 'muid_dEdx':
305  # ax1 = plt.axes([0.18, 0.17, 0.75, 0.8])
306  # if inputVariable == 'pi_vs_edEdxid':
307  # ax1 = plt.axes([0.18, 0.187, 0.75, 0.805])
308  # else:
309  ax1 = plt.axes([0.18, 0.2, 0.76, 0.705])
310 
311  # print(signalArray.shape, signalHistogram.GetNbinsX(), )
312  # print(signalArray)
313  ax1.hist(
314  signalArray[:, 0], weights=signalArray[:, 1], bins=signalHistogram.GetNbinsX(),
315  histtype='step',
316  edgecolor='r',
317  linewidth=4,
318  alpha=0.9,
319  label=r'${\rm Signal}$')
320 
321  ax1.hist(backgroundArray[:, 0], weights=backgroundArray[:, 1], bins=backgroundHistogram.GetNbinsX(),
322  histtype='step',
323  edgecolor='b', linewidth=4.5, linestyle='dashed', label=r'${\rm Background}$') # hatch='.',
324 
325  p1, = ax1.plot([], label=r'${\rm Signal}$', linewidth=5, linestyle='solid', alpha=0.9, c='r')
326  p2, = ax1.plot([], label=r'${\rm Background}$', linewidth=5.5, linestyle='dashed', c='b')
327 
328  binWidth = signalHistogram.GetBinWidth(2)
329 
330  if inputVariable == 'lambdaZError': # or inputVariable == 'ImpactXY' or\
331  # (category != "Lambda" and inputVariable == 'distance'):
332  binWidth = binWidth * 10
333 
334  if inputVariable == 'M':
335  binWidth = binWidth * 1000
336 
337  if category == "Lambda" and inputVariable == 'distance':
338  variablesPlotParamsDict[inputVariable][5] = r"{\rm cm}\, "
339 
340  binWidth = '{:8.2f}'.format(binWidth)
341 
342  xLabel = variablesPlotParamsDict[inputVariable][4]
343  legendLocation = 1
344 
345  if category == "FSC":
346  if inputVariable == 'cosTPTO':
347  xLabel = r'$\vert\cos{\theta^*_{\rm T, Slow}}\vert$'
348  if inputVariable == 'useCMSFrame(p)':
349  xLabel = r'$p^*_{\rm Slow}\ [{\rm GeV}/c]$'
350  if category == 'Lambda':
351  if inputVariable == 'useCMSFrame(p)':
352  xLabel = r'$p^*_{\Lambda}\ [{\rm GeV}/c]$'
353  if inputVariable == 'p':
354  xLabel = r'$p_{\Lambda}\ [{\rm GeV}/c]$'
355 
356  ax1.set_ylabel(r'${\rm Fraction\hspace{0.25em} of\hspace{0.25em} Events}\, /\, (\, ' + binWidth + r'\, ' +
357  variablesPlotParamsDict[inputVariable][5] + r')$', fontsize=46)
358  ax1.set_xlabel(xLabel, fontsize=65)
359  # plt.xticks([-1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1],
360  # [r'$-1$', r'', r'$-0.5$', r'', r'$0$', r'', r'$0.5$', r'', r'$1$'], rotation=0, size=40)
361  if inputVariable == 'extraInfo(isRightCategory(Kaon))' or \
362  inputVariable == 'HighestProbInCat(pi+:inRoe, isRightCategory(SlowPion))':
363  legendLocation = 3
364  ax1.set_yscale('log', nonposy='clip')
365  else:
366  ax1.yaxis.set_major_formatter(FormatStrFormatter(r'$%.2f$'))
367 
368  ax1.tick_params(axis='x', labelsize=50)
369  ax1.tick_params(axis='y', labelsize=40)
370 
371  if inputVariable == 'pi_vs_edEdxid':
372  ax1.xaxis.labelpad = 5
373  else:
374  ax1.xaxis.labelpad = 15
375 
376  if inputVariable.find('ARICH') != -1 or inputVariable.find('TOP') != -1 or \
377  inputVariable == 'cosTPTO' or inputVariable.find('KLM') != -1 or \
378  inputVariable == 'cosTheta' or inputVariable == 'FSCVariables(cosTPTOFast)' or \
379  inputVariable == 'KaonPionVariables(cosKaonPion)' or \
380  inputVariable == 'BtagToWBosonVariables(recoilMass)':
381  legendLocation = 2
382 
383  elif inputVariable == 'FSCVariables(SlowFastHaveOpositeCharges)' or \
384  inputVariable == 'KaonPionVariables(HaveOpositeCharges)' or inputVariable == "eid_ECL" or \
385  inputVariable.find('ID') != -1 or inputVariable.find('dEdx') != -1:
386  legendLocation = 9
387 
388  if inputVariable == 'muid_dEdx':
389  if category != 'KinLepton':
390  legendLocation = 8
391 
392  ax1.legend([p1, p2], [r'${\rm Signal}$', r'${\rm Bkgr.}$'], prop={
393  'size': 50}, loc=legendLocation, numpoints=1, handlelength=1)
394  ax1.grid(True)
395  # ax1.set_ylim(0, 1.4)
396  ax1.set_xlim(limXmin, limXmax)
397  plt.savefig('./InputVariablesPlots/' + category + '/' + category +
398  "_" + str(Belle2.makeROOTCompatible(inputVariable)) + '.pdf')
399  fig1.clear()
400 
401  signalHistogram.Delete()
402  backgroundHistogram.Delete()
403 
404 
405 if __name__ == '__main__':
406 
407  plotInputVariablesOfFlavorTagger()
408 
409  totalNumberOfVariables = 0
410 
411  for category in ft.variables:
412  totalNumberOfVariables += len(ft.variables[category])
413 
414  print("Total number of variables = ", totalNumberOfVariables)
415 
416  totalNumberOfCalculatedVariables = len(identifiersExtraInfosKaonPion)
417 
418  print("Calculations for Kaon-Pion Category = ", totalNumberOfCalculatedVariables)
419 
420  print("Variables per particle list:")
421  for particleList in identifiersExtraInfosDict:
422  print(particleList)
423  print(identifiersExtraInfosDict[particleList])
424  totalNumberOfCalculatedVariables += len(identifiersExtraInfosDict[particleList])
425 
426  print("Total number of calculated variables = ", totalNumberOfCalculatedVariables)
Belle2::makeROOTCompatible
std::string makeROOTCompatible(std::string str)
Remove special characters that ROOT dislikes in branch names, e.g.
Definition: MakeROOTCompatible.cc:64
Belle2::invertMakeROOTCompatible
std::string invertMakeROOTCompatible(std::string str)
Invert makeROOTCompatible operation.
Definition: MakeROOTCompatible.cc:79