Belle II Software  release-08-01-10
inputVariablesPlots.py
1 #!/usr/bin/env python3
2 
3 
10 
11 
23 
24 import os
25 import glob
26 import sys
27 from matplotlib.ticker import FormatStrFormatter
28 import matplotlib.pyplot as plt
29 import ROOT
30 from ROOT import Belle2
31 import basf2 as b2
32 import flavorTagger as ft
33 from defaultEvaluationParameters import categories
34 
35 import numpy as np
36 import matplotlib as mpl
37 mpl.use('Agg')
38 mpl.rcParams.update({'font.size': 22})
39 mpl.rcParams['text.usetex'] = True
40 mpl.rcParams['text.latex.preamble'] = [r"\usepackage{amsmath}"]
41 
42 ROOT.gROOT.SetBatch(True)
43 
44 if len(sys.argv) != 5:
45  sys.exit("Must provide 4 arguments: [Belle or Belle2] [BGx0 or BGx1] [training] [workingDirectory]"
46  )
47 
48 belleOrBelle2 = sys.argv[1]
49 MCtype = str(sys.argv[2])
50 decayChannelTrainedOn = str(sys.argv[3]) # Decay channel of the weight files "JPsiKs" or "nunubar"
51 workingDirectory = sys.argv[4]
52 
53 filesDirectory = workingDirectory + '/FlavorTagging/TrainedMethods'
54 
55 if decayChannelTrainedOn == 'JPsiKs':
56  decayChannelTrainedOn = 'JpsiKs_mu'
57 
58 weightFiles = 'B2' + decayChannelTrainedOn + MCtype
59 
60 
61 ROOT.TH1.SetDefaultSumw2()
62 
63 allInputVariables = []
64 
65 belleOrBelle2Flag = belleOrBelle2
66 
67 identifiersExtraInfosDict = dict()
68 identifiersExtraInfosKaonPion = []
69 
70 if belleOrBelle2 == "Belle":
71  unitImp = "cm"
72 
73 dBw = 50
74 
75 pBins = 50
76 fBins = 100
77 
78 unitImp = "mm"
79 
80 variablesPlotParamsDict = {
81  'useCMSFrame(p)': ['useCMSFrame__bop__bc', pBins, 0, 3, r'$p^*\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
82  'useCMSFrame(pt)': ['useCMSFrame__bopt__bc', pBins, 0, 3, r'$p_{\rm t}^*\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
83  'p': ['p', pBins, 0, 3, r'$p\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
84  'pt': ['pt', pBins, 0, 3, r'$p_{\rm t}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
85  'cosTheta': ['cosTheta', dBw, -1, 1.01, r'$\cos{\theta}$', ""],
86  ft.eId[ft.getBelleOrBelle2()]: [Belle2.MakeROOTCompatible.makeROOTCompatible(ft.eId[ft.getBelleOrBelle2()]),
87  dBw, 0, 1.01, r'$\mathcal{L}_{e}$', ""],
88  'eid_dEdx': ['eid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{{\rm d}E/{\rm d}x}$', ""],
89  'eid_TOP': ['eid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{\rm TOP}$', ""],
90  'eid_ARICH': ['eid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{\rm ARICH}$', ""],
91  'eid_ECL': ['eid_ECL', dBw, 0, 1.01, r'$\mathcal{L}_{e}^{\rm ECL}$', ""],
92  'BtagToWBosonVariables(recoilMassSqrd)': ['BtagToWBosonVariables__borecoilMassSqrd__bc', fBins,
93  0, 100, r'$M_{\rm rec}^2\ [{\rm GeV}^2/c^4]$', r"{\rm GeV}^2/c^4"],
94  'BtagToWBosonVariables(pMissCMS)': [
95  'BtagToWBosonVariables__bopMissCMS__bc', 60, 0, 3.6,
96  r'$p^*_{\rm miss}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
97  'BtagToWBosonVariables(cosThetaMissCMS)': ['BtagToWBosonVariables__bocosThetaMissCMS__bc',
98  dBw, -1, 1.01, r'$\cos{\theta^*_{\rm miss}}$', ""],
99  'BtagToWBosonVariables(EW90)': ['BtagToWBosonVariables__boEW90__bc',
100  dBw, 0, 4, r'$E_{90}^{W}\ [{\rm GeV}]$', r"{\rm GeV}\, "],
101  'BtagToWBosonVariables(recoilMass)': ['sqrt(abs(BtagToWBosonVariables__borecoilMassSqrd__bc))',
102  dBw, 0, 12, r'$M_{\rm rec}\ [{\rm GeV}/c^2]$', r"{\rm GeV}/c^2\, "],
103  'cosTPTO': ['cosTPTO', dBw, 0, 1.01, r'$\vert\cos{\theta^*_{\rm T}}\vert$', ""],
104  'ImpactXY': ['ImpactXY', dBw, 0, 0.5, r'$d_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
105  'z0': ['z0', dBw, 0, 1.0, r'$z_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
106  'y': ['y', dBw, -0.15, 0.15, r'$y_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
107  'OBoost': ['OBoost', dBw, -0.15, 0.15, r'$d_0^\prime\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
108  'distance': ['distance', dBw, 0, 1.5, r'$\xi_0\ [{\rm ' + unitImp + '}]$', r"{\rm " + unitImp + r"}\, "],
109  'chiProb': ['chiProb', dBw, 0, 1.01, r'$p$-${\rm value}$', ""],
110  ft.muId[ft.getBelleOrBelle2()]: [Belle2.MakeROOTCompatible.makeROOTCompatible(ft.muId[ft.getBelleOrBelle2()]),
111  dBw, 0, 1.01, r'$\mathcal{L}_{\mu}$', ""],
112  'muid_dEdx': ['muid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{{\rm d}E/{\rm d}x}$', ""],
113  'muid_TOP': ['muid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{\rm TOP}$', ""],
114  'muid_ARICH': ['muid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{\rm ARICH}$', ""],
115  'muid_KLM': ['muid_KLM', dBw, 0, 1.01, r'$\mathcal{L}_{\mu}^{\rm KLM}$', ""],
116  ft.KId[ft.getBelleOrBelle2()]: [Belle2.MakeROOTCompatible.makeROOTCompatible(ft.KId[ft.getBelleOrBelle2()]),
117  dBw, 0, 1.01, r'$\mathcal{L}_{K}$', ""],
118  'Kid_dEdx': ['Kid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{K}^{{\rm d}E/{\rm d}x}$', ""],
119  'Kid_TOP': ['Kid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{K}^{\rm TOP}$', ""],
120  'Kid_ARICH': ['Kid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{K}^{\rm ARICH}$', ""],
121  'NumberOfKShortsInRoe': ['NumberOfKShortsInRoe', dBw, 0, 12, r'$n_{K^0_S}$', ""],
122  'ptTracksRoe': ['ptTracksRoe', fBins, 0, 6, r'$\Sigma\, p_{\rm t}^2\ [{\rm GeV^2}/c^2]$',
123  r"{\rm GeV^2}/c^2"],
124  'extraInfo(isRightCategory(Kaon))': ['extraInfo__boisRightCategory__boKaon__bc__bc',
125  dBw, 0, 1.01, r"$y_{\rm Kaon}$", ""],
126  'HighestProbInCat(pi+:inRoe, isRightCategory(SlowPion))': [
127  'HighestProbInCat__bopi__pl__clinRoe__cm__spisRightCategory__boSlowPion__bc__bc',
128  dBw, 0, 1.01, r"$y_{\rm SlowPion}$", ""],
129  'KaonPionVariables(cosKaonPion)': ['KaonPionVariables__bocosKaonPion__bc',
130  dBw, -1, 1.01, r'$\cos{\theta^*_{K\pi}}$', ""],
131  'KaonPionVariables(HaveOpositeCharges)': ['KaonPionVariables__boHaveOpositeCharges__bc',
132  dBw, 0, 1.01, r'$\frac{1 - q_{K} \cdot q_\pi}{2}$', ""],
133  'pionID': ['pionID', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}$', ""],
134  'piid_dEdx': ['piid_dEdx', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}^{{\rm d}E/{\rm d}x}$', ""],
135  'piid_TOP': ['piid_TOP', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}^{\rm TOP}$', ""],
136  'piid_ARICH': ['piid_ARICH', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}^{\rm ARICH}$', ""],
137  'pi_vs_edEdxid': ['pi_vs_edEdxid', dBw, 0, 1.01, r'$\mathcal{L}_{\pi/e}^{{\rm d}E/{\rm d}x}$', ""],
138  'FSCVariables(pFastCMS)': ['FSCVariables__bopFastCMS__bc', pBins, 0, 3, r'$p^*_{\rm Fast}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
139  'FSCVariables(cosSlowFast)': ['FSCVariables__bocosSlowFast__bc', dBw, -1, 1.01, r'$\cos{\theta^*_{\rm SlowFast}}$', ''],
140  'FSCVariables(cosTPTOFast)': ['FSCVariables__bocosTPTOFast__bc', dBw, 0, 1.01, r'$\vert\cos{\theta^*_{\rm T, Fast}}\vert$', ''],
141  'FSCVariables(SlowFastHaveOpositeCharges)': ['FSCVariables__boSlowFastHaveOpositeCharges__bc',
142  dBw, 0, 1.01, r'$\frac{1 - q_{\rm Slow} \cdot q_{\rm Fast}}{2}$', ""],
143  'lambdaFlavor': ['lambdaFlavor', dBw, -1, 1.01, r'$q_{\Lambda}$', ""],
144  'M': ['M', dBw, 1.08, 1.22, r'$M_{\Lambda}\ [{\rm GeV}/c^2]$', r"{\rm MeV}/c^2\, "],
145  'cosAngleBetweenMomentumAndVertexVector': ['cosAngleBetweenMomentumAndVertexVector',
146  dBw, -1, 1.01,
147  r'$\cos{\theta_{\boldsymbol{x}_{\Lambda},\boldsymbol{p}_{\Lambda}}}$', ""],
148  'lambdaZError': ['lambdaZError', dBw, 0, 0.05, r'$\sigma_{\Lambda}^{zz}$', r"{\rm mm}\, "],
149  'daughter(0,p)': ['daughter__bo0__cmp__bc', dBw, 0, 1, r'$p_{\pi}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
150  'daughter(0,useCMSFrame(p))': ['daughter__bo0__cmuseCMSFrame__bop__bc__bc',
151  dBw, 0, 1, r'$p^*_{\pi}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
152  'daughter(1,p)': ['daughter__bo1__cmp__bc', dBw, 0, 2, r'$p_{p}\ [{\rm GeV}/c]$', r"{\rm GeV}/c"],
153  'daughter(1,useCMSFrame(p))': ['daughter__bo1__cmuseCMSFrame__bop__bc__bc',
154  dBw, 0, 2, r'$p^*_{p}\ [{\rm GeV}/c]$', r"{\rm GeV}/c\, "],
155  'daughter(1,protonID)': ['daughter__bo1__cmprotonID__bc', dBw, 0, 1.01, r'$\mathcal{L}_{p}$', ""],
156  'daughter(0,pionID)': ['daughter__bo0__cmpionID__bc', dBw, 0, 1.01, r'$\mathcal{L}_{\pi}$', ""]}
157 
158 if not b2.find_file('InputVariablesPlots', silent=True):
159  os.mkdir('./InputVariablesPlots')
160 
161 
162 def plotInputVariablesOfFlavorTagger():
163  """
164  Makes plots of the distribution of the input variables of the flavor tagger
165  for each category distinguishing between the target particles of the category (signal)
166  and all the other (bkg.)
167  """
168 
169  for (particleList, category, _) in ft.getEventLevelParticleLists(categories):
170 
171  # if category != "SlowPion":
172  # continue
173 
174  if not b2.find_file('InputVariablesPlots/' + category, silent=True):
175  os.mkdir('./InputVariablesPlots/' + category)
176 
177  if particleList not in identifiersExtraInfosDict and category != 'KaonPion':
178  identifiersExtraInfosDict[particleList] = []
179 
180  methodPrefixEventLevel = "FlavorTagger_" + belleOrBelle2Flag + "_" + weightFiles + 'EventLevel' + category + 'FBDT'
181  treeName = methodPrefixEventLevel + "_tree"
182  targetVariable = 'isRightCategory(' + category + ')'
183 
184  tree = ROOT.TChain(treeName)
185 
186  workingFiles = glob.glob(filesDirectory + '/' + methodPrefixEventLevel + 'sampled*.root')
187  # print("workingFiles = ", workingFiles)
188  # workingFiles = glob.glob(filesDirectory + '/' + methodPrefixEventLevel + 'sampled1?.root')
189 
190  for iFile in workingFiles:
191  tree.AddFile(iFile)
192 
193  categoryInputVariables = []
194  trulyUsedInputVariables = []
195  for iVariable in tree.GetListOfBranches():
196 
197  managerVariableName = str(Belle2.MakeROOTCompatible.invertMakeROOTCompatible(iVariable.GetName()))
198 
199  if managerVariableName in ft.getTrainingVariables(category) or managerVariableName == 'distance' or \
200  managerVariableName == 'z0' or managerVariableName == 'ImpactXY' or \
201  managerVariableName == 'y' or managerVariableName == 'OBoost':
202  if managerVariableName in categoryInputVariables:
203  continue
204 
205  categoryInputVariables.append(managerVariableName)
206  if managerVariableName in ft.getTrainingVariables(category):
207  allInputVariables.append((category, managerVariableName))
208  trulyUsedInputVariables.append((category, managerVariableName))
209 
210  if managerVariableName not in identifiersExtraInfosDict[particleList] and category != 'KaonPion':
211  identifiersExtraInfosDict[particleList].append(managerVariableName)
212 
213  elif category == 'KaonPion' and managerVariableName not in identifiersExtraInfosKaonPion:
214  identifiersExtraInfosKaonPion.append(managerVariableName)
215 
216  # if managerVariableName not in variablesPlotParamsDict:
217  # variablesPlotParamsDict[managerVariableName] =
218  # [iVariable.GetName(), 100, 0, 2, iVariable.GetName(), "unit"]
219 
220  print("The number of variables used in " + category + " is = ", len(trulyUsedInputVariables))
221 
222  if category != 'KaonPion' and category != 'FSC' and category != 'MaximumPstar' and \
223  category != 'FastHadron' and category != 'Lambda':
224  categoryInputVariables.append('BtagToWBosonVariables(recoilMass)')
225 
226  for inputVariable in categoryInputVariables:
227 
228  print(inputVariable)
229 
230  nBins = variablesPlotParamsDict[inputVariable][1]
231  limXmin = variablesPlotParamsDict[inputVariable][2]
232  limXmax = variablesPlotParamsDict[inputVariable][3]
233 
234  if category == "SlowPion":
235  if inputVariable == 'p' or inputVariable == 'useCMSFrame(p)' or \
236  inputVariable == 'pt' or inputVariable == 'useCMSFrame(pt)':
237  nBins = 150
238  limXmax = 1.5
239 
240  if inputVariable == 'distance':
241  nBins = 80
242  limXmax = 2.4
243 
244  if inputVariable == 'ImpactXY':
245  nBins = 80
246  limXmax = 0.8
247 
248  if category == "Lambda":
249  if inputVariable == 'distance':
250  # nBins = 25
251  limXmax = 10
252 
253  if inputVariable == 'chiProb':
254  nBins = 25
255 
256  signalHistogram = ROOT.TH1F("signal" + category + str(Belle2.MakeROOTCompatible.makeROOTCompatible(inputVariable)), "",
257  nBins,
258  limXmin,
259  limXmax)
260  backgroundHistogram = ROOT.TH1F("bkg" + category + str(Belle2.MakeROOTCompatible.makeROOTCompatible(inputVariable)), "",
261  nBins,
262  limXmin,
263  limXmax)
264 
265  factorMultiplication = ''
266 
267  if belleOrBelle2 == "Belle2" and ((category != "Lambda" and inputVariable == 'distance') or inputVariable ==
268  'z0' or inputVariable == 'ImpactXY' or inputVariable ==
269  'y' or inputVariable == 'OBoost'):
270  factorMultiplication = "*10 "
271 
272  tree.Draw(variablesPlotParamsDict[inputVariable][0] + factorMultiplication + ">> signal" + category + str(
273  Belle2.MakeROOTCompatible.makeROOTCompatible(inputVariable)),
274  Belle2.MakeROOTCompatible.makeROOTCompatible(targetVariable) + " > 0")
275 
276  tree.Draw(
277  variablesPlotParamsDict[inputVariable][0] +
278  factorMultiplication +
279  ">> bkg" +
280  category +
281  str(
282  Belle2.MakeROOTCompatible.makeROOTCompatible(inputVariable)),
283  Belle2.MakeROOTCompatible.makeROOTCompatible(targetVariable) +
284  " < 1")
285 
286  signalScalingFactor = signalHistogram.Integral()
287  backgroundScalingFactor = backgroundHistogram.Integral()
288 
289  if signalScalingFactor == 0:
290  signalScalingFactor = 1
291 
292  if backgroundScalingFactor == 0:
293  backgroundScalingFactor = 1
294 
295  signalHistogram.Scale(1 / signalScalingFactor)
296  backgroundHistogram.Scale(1 / backgroundScalingFactor)
297 
298  signalArray = np.zeros((signalHistogram.GetNbinsX(), 2))
299  backgroundArray = np.zeros((backgroundHistogram.GetNbinsX(), 2))
300 
301  for i in range(0, signalHistogram.GetNbinsX()):
302  signalArray[i] = np.array([signalHistogram.GetBinCenter(i + 1), signalHistogram.GetBinContent(i + 1)])
303  backgroundArray[i] = np.array([backgroundHistogram.GetBinCenter(i + 1), backgroundHistogram.GetBinContent(i + 1)])
304 
305  fig1 = plt.figure(1, figsize=(11, 10))
306 
307  # if inputVariable == 'Kid_dEdx' or inputVariable == 'muid_dEdx':
308  # ax1 = plt.axes([0.18, 0.17, 0.75, 0.8])
309  # if inputVariable == 'pi_vs_edEdxid':
310  # ax1 = plt.axes([0.18, 0.187, 0.75, 0.805])
311  # else:
312  ax1 = plt.axes([0.18, 0.2, 0.76, 0.705])
313 
314  # print(signalArray.shape, signalHistogram.GetNbinsX(), )
315  # print(signalArray)
316  ax1.hist(
317  signalArray[:, 0], weights=signalArray[:, 1], bins=signalHistogram.GetNbinsX(),
318  histtype='step',
319  edgecolor='r',
320  linewidth=4,
321  alpha=0.9,
322  label=r'${\rm Signal}$')
323 
324  ax1.hist(backgroundArray[:, 0], weights=backgroundArray[:, 1], bins=backgroundHistogram.GetNbinsX(),
325  histtype='step',
326  edgecolor='b', linewidth=4.5, linestyle='dashed', label=r'${\rm Background}$') # hatch='.',
327 
328  p1, = ax1.plot([], label=r'${\rm Signal}$', linewidth=5, linestyle='solid', alpha=0.9, c='r')
329  p2, = ax1.plot([], label=r'${\rm Background}$', linewidth=5.5, linestyle='dashed', c='b')
330 
331  binWidth = signalHistogram.GetBinWidth(2)
332 
333  if inputVariable == 'lambdaZError': # or inputVariable == 'ImpactXY' or\
334  # (category != "Lambda" and inputVariable == 'distance'):
335  binWidth = binWidth * 10
336 
337  if inputVariable == 'M':
338  binWidth = binWidth * 1000
339 
340  if category == "Lambda" and inputVariable == 'distance':
341  variablesPlotParamsDict[inputVariable][5] = r"{\rm cm}\, "
342 
343  binWidth = '{:8.2f}'.format(binWidth)
344 
345  xLabel = variablesPlotParamsDict[inputVariable][4]
346  legendLocation = 1
347 
348  if category == "FSC":
349  if inputVariable == 'cosTPTO':
350  xLabel = r'$\vert\cos{\theta^*_{\rm T, Slow}}\vert$'
351  if inputVariable == 'useCMSFrame(p)':
352  xLabel = r'$p^*_{\rm Slow}\ [{\rm GeV}/c]$'
353  if category == 'Lambda':
354  if inputVariable == 'useCMSFrame(p)':
355  xLabel = r'$p^*_{\Lambda}\ [{\rm GeV}/c]$'
356  if inputVariable == 'p':
357  xLabel = r'$p_{\Lambda}\ [{\rm GeV}/c]$'
358 
359  ax1.set_ylabel(r'${\rm Fraction\hspace{0.25em} of\hspace{0.25em} Events}\, /\, (\, ' + binWidth + r'\, ' +
360  variablesPlotParamsDict[inputVariable][5] + r')$', fontsize=46)
361  ax1.set_xlabel(xLabel, fontsize=65)
362  # plt.xticks([-1, -0.75, -0.5, -0.25, 0, 0.25, 0.5, 0.75, 1],
363  # [r'$-1$', r'', r'$-0.5$', r'', r'$0$', r'', r'$0.5$', r'', r'$1$'], rotation=0, size=40)
364  if inputVariable == 'extraInfo(isRightCategory(Kaon))' or \
365  inputVariable == 'HighestProbInCat(pi+:inRoe, isRightCategory(SlowPion))':
366  legendLocation = 3
367  ax1.set_yscale('log', nonposy='clip')
368  else:
369  ax1.yaxis.set_major_formatter(FormatStrFormatter(r'$%.2f$'))
370 
371  ax1.tick_params(axis='x', labelsize=50)
372  ax1.tick_params(axis='y', labelsize=40)
373 
374  if inputVariable == 'pi_vs_edEdxid':
375  ax1.xaxis.labelpad = 5
376  else:
377  ax1.xaxis.labelpad = 15
378 
379  if inputVariable.find('ARICH') != -1 or inputVariable.find('TOP') != -1 or \
380  inputVariable == 'cosTPTO' or inputVariable.find('KLM') != -1 or \
381  inputVariable == 'cosTheta' or inputVariable == 'FSCVariables(cosTPTOFast)' or \
382  inputVariable == 'KaonPionVariables(cosKaonPion)' or \
383  inputVariable == 'BtagToWBosonVariables(recoilMass)':
384  legendLocation = 2
385 
386  elif inputVariable == 'FSCVariables(SlowFastHaveOpositeCharges)' or \
387  inputVariable == 'KaonPionVariables(HaveOpositeCharges)' or inputVariable == "eid_ECL" or \
388  inputVariable.find('ID') != -1 or inputVariable.find('dEdx') != -1:
389  legendLocation = 9
390 
391  if inputVariable == 'muid_dEdx':
392  if category != 'KinLepton':
393  legendLocation = 8
394 
395  ax1.legend([p1, p2], [r'${\rm Signal}$', r'${\rm Bkgr.}$'], prop={
396  'size': 50}, loc=legendLocation, numpoints=1, handlelength=1)
397  ax1.grid(True)
398  # ax1.set_ylim(0, 1.4)
399  ax1.set_xlim(limXmin, limXmax)
400  plt.savefig('./InputVariablesPlots/' + category + '/' + category +
401  "_" + str(Belle2.MakeROOTCompatible.makeROOTCompatible(inputVariable)) + '.pdf')
402  fig1.clear()
403 
404  signalHistogram.Delete()
405  backgroundHistogram.Delete()
406 
407 
408 if __name__ == '__main__':
409 
410  plotInputVariablesOfFlavorTagger()
411 
412  totalNumberOfVariables = 0
413 
414  for category in ft.AvailableCategories:
415  totalNumberOfVariables += len(ft.getTrainingVariables(category))
416 
417  print("Total number of variables = ", totalNumberOfVariables)
418 
419  totalNumberOfCalculatedVariables = len(identifiersExtraInfosKaonPion)
420 
421  print("Calculations for Kaon-Pion Category = ", totalNumberOfCalculatedVariables)
422 
423  print("Variables per particle list:")
424  for particleList in identifiersExtraInfosDict:
425  print(particleList)
426  print(identifiersExtraInfosDict[particleList])
427  totalNumberOfCalculatedVariables += len(identifiersExtraInfosDict[particleList])
428 
429  print("Total number of calculated variables = ", totalNumberOfCalculatedVariables)
Belle2::MakeROOTCompatible::makeROOTCompatible
static std::string makeROOTCompatible(std::string str)
Remove special characters that ROOT dislikes in branch names, e.g.
Definition: MakeROOTCompatible.cc:60
Belle2::MakeROOTCompatible::invertMakeROOTCompatible
static std::string invertMakeROOTCompatible(std::string str)
Invert makeROOTCompatible operation.
Definition: MakeROOTCompatible.cc:75