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trackingPlots.py
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1 from __future__ import absolute_import
2 from builtins import range
3 import os
4 import copy
5 import collections
6 
7 import ROOT
8 ROOT.gROOT.SetBatch(True)
9 ROOT.PyConfig.IgnoreCommandLineOptions = True
10 
11 from .plotting import Subtract, FakeDuplicate, CutEfficiency, Transform, AggregateBins, ROC, Plot, PlotEmpty, PlotGroup, PlotOnSideGroup, PlotFolder, Plotter
12 from .html import PlotPurpose
13 from . import plotting
14 from . import validation
15 from . import html
16 
17 
22 
23 _maxEff = [0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 0.8, 1.025, 1.2, 1.5, 2]
24 _maxFake = [0.01, 0.02, 0.05, 0.1, 0.2, 0.5, 0.8, 1.025]
25 
26 #_minMaxResol = [1e-5, 2e-5, 5e-5, 1e-4, 2e-4, 5e-4, 1e-3, 2e-3, 5e-3, 1e-2, 2e-2, 5e-2, 0.1, 0.2, 0.5, 1]
27 _minMaxResol = [1e-5, 4e-5, 1e-4, 4e-4, 1e-3, 4e-3, 1e-2, 4e-2, 0.1, 0.4, 1]
28 _minMaxN = [5e-1, 5, 5e1, 5e2, 5e3, 5e4, 5e5, 5e6, 5e7, 5e8, 5e9]
29 
30 _minHits = [0, 5, 10]
31 _maxHits = [5, 10, 20, 40, 60, 80]
32 _minLayers = [0, 5, 10]
33 _maxLayers = [5, 10, 25]
34 _maxPixelLayers = 8
35 _min3DLayers = [0, 5, 10]
36 _max3DLayers = [5, 10, 20]
37 _minZ = [-60, -40, -20, -10, -5]
38 _maxZ = [5, 10, 20, 40, 60]
39 _minPU = [0, 10, 20, 50, 100, 150]
40 _maxPU = [20, 50, 65, 80, 100, 150, 200, 250]
41 _minMaxTracks = [0, 200, 500, 1000, 1500, 2000]
42 _minMaxMVA = [-1.025, -0.5, 0, 0.5, 1.025]
43 _maxDRJ = 0.1
44 
45 def _minMaxResidual(ma):
46  return ([-x for x in ma], ma)
47 
48 (_minResidualPhi, _maxResidualPhi) = _minMaxResidual([1e-4, 2e-4]) # rad
49 (_minResidualCotTheta, _maxResidualCotTheta) = _minMaxResidual([1e-4, 2e-4])
50 (_minResidualDxy, _maxResidualDxy) = _minMaxResidual([10, 20, 50, 100]) # um
51 (_minResidualDz, _maxResidualDz) = (_minResidualDxy, _maxResidualDxy)
52 (_minResidualPt, _maxResidualPt) = _minMaxResidual([1, 1.5, 2, 5]) # %
53 
54 
55 _legendDy_1row = 0.46
56 _legendDy_2rows = -0.025
57 _legendDy_2rows_3cols = -0.17
58 _legendDy_4rows = 0.09
59 
60 # Ok, because of the way the "reference release" histograms are
61 # stored, this histogram is not accessible for the summary plots. To
62 # be fixed later with (large) reorganization of how things work.
63 #_trackingNumberOfEventsHistogram = "DQMData/Run 1/Tracking/Run summary/Track/general_trackingParticleRecoAsssociation/tracks"
64 
65 _trackingIterationOrderHistogram = "DQMData/Run 1/Tracking/Run summary/TrackBuilding/num_reco_coll"
66 
67 def _makeEffFakeDupPlots(postfix, quantity, unit="", common={}, effopts={}, fakeopts={}):
68  p = postfix
69  q = quantity
70  xq = q
71  if unit != "":
72  xq += " (" + unit + ")"
73 
74  effargs = dict(xtitle="TP "+xq , ytitle="efficiency vs "+q , ymax=_maxEff)
75  fakeargs = dict(xtitle="track "+xq, ytitle="fake+duplicates rate vs "+q, ymax=_maxFake)
76  effargs.update(common)
77  fakeargs.update(common)
78  effargs.update(effopts)
79  fakeargs.update(fakeopts)
80 
81  return [
82  Plot("effic_vs_"+p, **effargs),
83  Plot(FakeDuplicate("fakeduprate_vs_"+p, assoc="num_assoc(recoToSim)_"+p, dup="num_duplicate_"+p, reco="num_reco_"+p, title="fake+duplicates vs "+q), **fakeargs)
84  ]
85 
86 def _makeFakeDupPileupPlots(postfix, quantity, unit="", xquantity="", xtitle=None, common={}):
87  p = postfix
88  q = quantity
89  if xtitle is None:
90  if xquantity != "":
91  xq = xquantity
92  else:
93  xq = q
94  if unit != "":
95  xq += " (" + unit + ")"
96  xtitle="track "+xq
97 
98  return [
99  Plot("fakerate_vs_"+p , xtitle=xtitle, ytitle="fakerate vs "+q , ymax=_maxFake, **common),
100  Plot("duplicatesRate_"+p, xtitle=xtitle, ytitle="duplicates rate vs "+q, ymax=_maxFake, **common),
101  Plot("pileuprate_"+p , xtitle=xtitle, ytitle="pileup rate vs "+q , ymax=_maxFake, **common),
102  ]
103 
104 def _makeFakeDist(postfix):
105  return Subtract("num_fake_"+postfix, "num_reco_"+postfix, "num_assoc(recoToSim)_"+postfix)
106 
107 def _makeDistPlots(postfix, quantity, common={}):
108  p = postfix
109  q = quantity
110 
111  args = dict(xtitle="track "+q, ylog=True, ymin=_minMaxN, ymax=_minMaxN)
112  args.update(common)
113 
114  return [
115  Plot("num_reco_"+p , ytitle="tracks", **args),
116  Plot("num_assoc(recoToSim)_"+p, ytitle="true tracks", **args),
117  Plot(_makeFakeDist(p), ytitle="fake tracks", **args),
118  Plot("num_duplicate_"+p , ytitle="duplicate tracks", **args),
119  ]
120 
121 def _makeDistSimPlots(postfix, quantity, common={}):
122  p = postfix
123  q = quantity
124 
125  args = dict(xtitle="TP "+q, ylog=True, ymin=_minMaxN, ymax=_minMaxN)
126  args.update(common)
127 
128  return [
129  Plot("num_simul_"+p , ytitle="TrackingParticles", **args),
130  Plot("num_assoc(simToReco)_"+p, ytitle="Reconstructed TPs", **args),
131  ]
132 
133 def _makeMVAPlots(num, hp=False):
134  pfix = "_hp" if hp else ""
135  pfix2 = "Hp" if hp else ""
136 
137  xtitle = "MVA%d output"%num
138  xtitlecut = "Cut on MVA%d output"%num
139  args = dict(xtitle=xtitle, ylog=True, ymin=_minMaxN, ymax=_minMaxN)
140 
141  argsroc = dict(
142  xtitle="Efficiency (excl. trk eff)", ytitle="Fake rate",
143  xmax=_maxEff, ymax=_maxFake,
144  drawStyle="EP",
145  )
146  argsroc2 = dict(
147  ztitle="Cut on MVA%d"%num,
148  xtitleoffset=5, ytitleoffset=6.5, ztitleoffset=4,
149  adjustMarginRight=0.12
150  )
151  argsroc2.update(argsroc)
152  argsroc2["drawStyle"] = "pcolz"
153 
154  argsprofile = dict(ymin=_minMaxMVA, ymax=_minMaxMVA)
155 
156  true_cuteff = CutEfficiency("trueeff_vs_mva%dcut%s"%(num,pfix), "num_assoc(recoToSim)_mva%dcut%s"%(num,pfix))
157  fake_cuteff = CutEfficiency("fakeeff_vs_mva%dcut%s"%(num,pfix), Subtract("num_fake_mva%dcut%s"%(num,pfix), "num_reco_mva%dcut%s"%(num,pfix), "num_assoc(recoToSim)_mva%dcut%s"%(num,pfix)))
158 
159  return [
160  PlotGroup("mva%d%s"%(num,pfix2), [
161  Plot("num_assoc(recoToSim)_mva%d%s"%(num,pfix), ytitle="true tracks", **args),
162  Plot(Subtract("num_fake_mva%d%s"%(num,pfix), "num_reco_mva%d%s"%(num,pfix), "num_assoc(recoToSim)_mva%d%s"%(num,pfix)), ytitle="fake tracks", **args),
163  Plot("effic_vs_mva%dcut%s"%(num,pfix), xtitle=xtitlecut, ytitle="Efficiency (excl. trk eff)", ymax=_maxEff),
164  #
165  Plot("fakerate_vs_mva%dcut%s"%(num,pfix), xtitle=xtitlecut, ytitle="Fake rate", ymax=_maxFake),
166  Plot(ROC("effic_vs_fake_mva%d%s"%(num,pfix), "effic_vs_mva%dcut%s"%(num,pfix), "fakerate_vs_mva%dcut%s"%(num,pfix)), **argsroc),
167  Plot(ROC("effic_vs_fake_mva%d%s"%(num,pfix), "effic_vs_mva%dcut%s"%(num,pfix), "fakerate_vs_mva%dcut%s"%(num,pfix), zaxis=True), **argsroc2),
168  # Same signal efficiency, background efficiency, and ROC definitions as in TMVA
169  Plot(true_cuteff, xtitle=xtitlecut, ytitle="True track selection efficiency", ymax=_maxEff),
170  Plot(fake_cuteff, xtitle=xtitlecut, ytitle="Fake track selection efficiency", ymax=_maxEff),
171  Plot(ROC("true_eff_vs_fake_rej_mva%d%s"%(num,pfix), true_cuteff, Transform("fake_rej_mva%d%s"%(num,pfix), fake_cuteff, lambda x: 1-x)), xtitle="True track selection efficiency", ytitle="Fake track rejection", xmax=_maxEff, ymax=_maxEff),
172  ], ncols=3, legendDy=_legendDy_1row),
173  PlotGroup("mva%d%sPtEta"%(num,pfix2), [
174  Plot("mva_assoc(recoToSim)_mva%d%s_pT"%(num,pfix), xtitle="Track p_{T} (GeV)", ytitle=xtitle+" for true tracks", xlog=True, **argsprofile),
175  Plot("mva_fake_mva%d%s_pT"%(num,pfix), xtitle="Track p_{T} (GeV)", ytitle=xtitle+" for fake tracks", xlog=True, **argsprofile),
176  Plot("mva_assoc(recoToSim)_mva%d%s_eta"%(num,pfix), xtitle="Track #eta", ytitle=xtitle+" for true tracks", **argsprofile),
177  Plot("mva_fake_mva%d%s_eta"%(num,pfix), xtitle="Track #eta", ytitle=xtitle+" for fake tracks", **argsprofile),
178  ], legendDy=_legendDy_2rows)
179  ]
180 
181 _effandfakePtEtaPhi = PlotGroup("effandfakePtEtaPhi", [
182  Plot("efficPt", title="Efficiency vs p_{T}", xtitle="TP p_{T} (GeV)", ytitle="efficiency vs p_{T}", xlog=True, ymax=_maxEff),
183  Plot(FakeDuplicate("fakeduprate_vs_pT", assoc="num_assoc(recoToSim)_pT", dup="num_duplicate_pT", reco="num_reco_pT", title="fake+duplicates vs p_{T}"),
184  xtitle="track p_{T} (GeV)", ytitle="fake+duplicates rate vs p_{T}", ymax=_maxFake, xlog=True),
185  Plot("effic", xtitle="TP #eta", ytitle="efficiency vs #eta", title="", ymax=_maxEff),
186  Plot(FakeDuplicate("fakeduprate_vs_eta", assoc="num_assoc(recoToSim)_eta", dup="num_duplicate_eta", reco="num_reco_eta", title=""),
187  xtitle="track #eta", ytitle="fake+duplicates rate vs #eta", ymax=_maxFake),
188 ] +
189  _makeEffFakeDupPlots("phi", "#phi")
190 )
191 
192 _effandfakeDxyDzBS = PlotGroup("effandfakeDxyDzBS",
193  _makeEffFakeDupPlots("dxy" , "dxy" , "cm") +
194  _makeEffFakeDupPlots("dz" , "dz" , "cm"),
195  legendDy=_legendDy_2rows
196 )
197 _effandfakeDxyDzPV = PlotGroup("effandfakeDxyDzPV",
198  _makeEffFakeDupPlots("dxypv" , "dxy(PV)", "cm") +
199  _makeEffFakeDupPlots("dxypv_zoomed", "dxy(PV)", "cm") +
200  _makeEffFakeDupPlots("dzpv" , "dz(PV)" , "cm") +
201  _makeEffFakeDupPlots("dzpv_zoomed" , "dz(PV)" , "cm"),
202  legendDy=_legendDy_4rows
203 )
204 _effandfakeHitsLayers = PlotGroup("effandfakeHitsLayers",
205  _makeEffFakeDupPlots("hit" , "hits" , common=dict(xmin=_minHits , xmax=_maxHits)) +
206  _makeEffFakeDupPlots("layer" , "layers" , common=dict(xmin=_minLayers , xmax=_maxLayers)) +
207  _makeEffFakeDupPlots("pixellayer", "pixel layers", common=dict( xmax=_maxPixelLayers)) +
208  _makeEffFakeDupPlots("3Dlayer" , "3D layers" , common=dict(xmin=_min3DLayers, xmax=_max3DLayers)),
209  legendDy=_legendDy_4rows
210 )
211 _common = {"ymin": 0, "ymax": _maxEff}
212 _effandfakePos = PlotGroup("effandfakePos",
213  _makeEffFakeDupPlots("vertpos", "vert r", "cm", fakeopts=dict(xtitle="track ref. point r (cm)", ytitle="fake+duplicates vs. r"), common=dict(xlog=True)) +
214  _makeEffFakeDupPlots("zpos" , "vert z", "cm", fakeopts=dict(xtitle="track ref. point z (cm)", ytitle="fake+duplicates vs. z")) +
215  _makeEffFakeDupPlots("simpvz" , "Sim. PV z", "cm", common=dict(xtitle="Sim. PV z (cm)", xmin=_minZ, xmax=_maxZ))
216 )
217 _effandfakeDeltaRPU = PlotGroup("effandfakeDeltaRPU",
218  _makeEffFakeDupPlots("dr" , "#DeltaR", effopts=dict(xtitle="TP min #DeltaR"), fakeopts=dict(xtitle="track min #DeltaR"), common=dict(xlog=True)) +
219  _makeEffFakeDupPlots("drj" , "#DeltaR(track, jet)", effopts=dict(xtitle="#DeltaR(TP, jet)", ytitle="efficiency vs #DeltaR(TP, jet"), fakeopts=dict(xtitle="#DeltaR(track, jet)"), common=dict(xlog=True, xmax=_maxDRJ))+
220  _makeEffFakeDupPlots("pu" , "PU" , common=dict(xtitle="Pileup", xmin=_minPU, xmax=_maxPU)),
221  legendDy=_legendDy_4rows
222 )
223 
224 
225 _algos_common = dict(removeEmptyBins=True, xbinlabelsize=10, xbinlabeloption="d")
226 _duplicateAlgo = PlotOnSideGroup("duplicateAlgo", Plot("duplicates_oriAlgo_vs_oriAlgo", drawStyle="COLZ", adjustMarginLeft=0.1, adjustMarginRight=0.1, **_algos_common))
227 
228 _dupandfakePtEtaPhi = PlotGroup("dupandfakePtEtaPhi", [
229  Plot("fakeratePt", xtitle="track p_{T} (GeV)", ytitle="fakerate vs p_{T}", xlog=True, ymax=_maxFake),
230  Plot("duplicatesRate_Pt", xtitle="track p_{T} (GeV)", ytitle="duplicates rate vs p_{T}", ymax=_maxFake, xlog=True),
231  Plot("pileuprate_Pt", xtitle="track p_{T} (GeV)", ytitle="pileup rate vs p_{T}", ymax=_maxFake, xlog=True),
232  Plot("fakerate", xtitle="track #eta", ytitle="fakerate vs #eta", title="", ymax=_maxFake),
233  Plot("duplicatesRate", xtitle="track #eta", ytitle="duplicates rate vs #eta", title="", ymax=_maxFake),
234  Plot("pileuprate", xtitle="track #eta", ytitle="pileup rate vs #eta", title="", ymax=_maxFake),
235 ] + _makeFakeDupPileupPlots("phi", "#phi"),
236  ncols=3
237 )
238 _dupandfakeDxyDzBS = PlotGroup("dupandfakeDxyDzBS",
239  _makeFakeDupPileupPlots("dxy" , "dxy" , "cm") +
240  _makeFakeDupPileupPlots("dz" , "dz" , "cm"),
241  ncols=3, legendDy=_legendDy_2rows_3cols
242 )
243 _dupandfakeDxyDzPV = PlotGroup("dupandfakeDxyDzPV",
244  _makeFakeDupPileupPlots("dxypv" , "dxy(PV)", "cm") +
245  _makeFakeDupPileupPlots("dxypv_zoomed", "dxy(PV)", "cm") +
246  _makeFakeDupPileupPlots("dzpv" , "dz(PV)" , "cm") +
247  _makeFakeDupPileupPlots("dzpv_zoomed" , "dz(PV)" , "cm"),
248  ncols=3, legendDy=_legendDy_4rows
249 )
250 _dupandfakeHitsLayers = PlotGroup("dupandfakeHitsLayers",
251  _makeFakeDupPileupPlots("hit" , "hits" , common=dict(xmin=_minHits , xmax=_maxHits)) +
252  _makeFakeDupPileupPlots("layer" , "layers" , common=dict(xmin=_minLayers , xmax=_maxLayers)) +
253  _makeFakeDupPileupPlots("pixellayer", "pixel layers", common=dict( xmax=_maxPixelLayers)) +
254  _makeFakeDupPileupPlots("3Dlayer" , "3D layers" , common=dict(xmin=_min3DLayers, xmax=_max3DLayers)),
255  ncols=3, legendDy=_legendDy_4rows
256 )
257 _dupandfakePos = PlotGroup("dupandfakePos",
258  _makeFakeDupPileupPlots("vertpos", "r", "cm", xquantity="ref. point r (cm)", common=dict(xlog=True)) +
259  _makeFakeDupPileupPlots("zpos" , "z", "cm", xquantity="ref. point z (cm)") +
260  _makeFakeDupPileupPlots("simpvz" , "Sim. PV z", xtitle="Sim. PV z (cm)", common=dict(xmin=_minZ, xmax=_maxZ)),
261  ncols=3,
262 )
263 _dupandfakeDeltaRPU = PlotGroup("dupandfakeDeltaRPU",
264  _makeFakeDupPileupPlots("dr" , "#DeltaR", xquantity="min #DeltaR", common=dict(xlog=True)) +
265  _makeFakeDupPileupPlots("drj" , "#DeltaR(track, jet)", xtitle="#DeltaR(track, jet)", common=dict(xlog=True, xmax=_maxDRJ)) +
266  _makeFakeDupPileupPlots("pu" , "PU" , xtitle="Pileup", common=dict(xmin=_minPU, xmax=_maxPU)),
267  ncols=3
268 )
269 _seedingLayerSet_common = dict(removeEmptyBins=True, xbinlabelsize=8, xbinlabeloption="d", adjustMarginRight=0.1)
270 _dupandfakeSeedingPlots = _makeFakeDupPileupPlots("seedingLayerSet", "seeding layers", xtitle="", common=_seedingLayerSet_common)
271 _dupandfakeChi2Seeding = PlotGroup("dupandfakeChi2Seeding",
272  _makeFakeDupPileupPlots("chi2", "#chi^{2}") +
273  _dupandfakeSeedingPlots,
274  ncols=3, legendDy=_legendDy_2rows_3cols
275 )
276 
277 _common = {
278  "ytitle": "Fake+pileup rate",
279  "ymax": _maxFake,
280  "drawStyle": "EP",
281 }
282 _common2 = {}
283 _common2.update(_common)
284 _common2["drawStyle"] = "pcolz"
285 _common2["ztitleoffset"] = 1.5
286 _common2["xtitleoffset"] = 7
287 _common2["ytitleoffset"] = 10
288 _common2["ztitleoffset"] = 6
289 _pvassociation1 = PlotGroup("pvassociation1", [
290  Plot(ROC("effic_vs_fakepileup_dzpvcut", "effic_vs_dzpvcut", FakeDuplicate("fakepileup_vs_dzpvcut", assoc="num_assoc(recoToSim)_dzpvcut", reco="num_reco_dzpvcut", dup="num_pileup_dzpvcut")),
291  xtitle="Efficiency vs. cut on dz(PV)", **_common),
292  Plot(ROC("effic_vs_fakepileup2_dzpvcut", "effic_vs_dzpvcut", FakeDuplicate("fakepileup_vs_dzpvcut", assoc="num_assoc(recoToSim)_dzpvcut", reco="num_reco_dzpvcut", dup="num_pileup_dzpvcut"), zaxis=True),
293  xtitle="Efficiency", ztitle="Cut on dz(PV)", **_common2),
294  #
295  Plot(ROC("effic_vs_fakepileup_dzpvsigcut", "effic_vs_dzpvsigcut", FakeDuplicate("fakepileup_vs_dzpvsigcut", assoc="num_assoc(recoToSim)_dzpvsigcut", reco="num_reco_dzpvsigcut", dup="num_pileup_dzpvsigcut")),
296  xtitle="Efficiency vs. cut on dz(PV)/dzError", **_common),
297  Plot(ROC("effic_vs_fakepileup2_dzpvsigcut", "effic_vs_dzpvsigcut", FakeDuplicate("fakepileup_vs_dzpvsigcut", assoc="num_assoc(recoToSim)_dzpvsigcut", reco="num_reco_dzpvsigcut", dup="num_pileup_dzpvsigcut"), zaxis=True),
298  xtitle="Efficiency", ztitle="Cut on dz(PV)/dzError", **_common2),
299 ], onlyForPileup=True,
300  legendDy=_legendDy_4rows
301 )
302 _pvassociation2 = PlotGroup("pvassociation2", [
303  Plot("effic_vs_dzpvcut", xtitle="Cut on dz(PV) (cm)", ytitle="Efficiency vs. cut on dz(PV)", ymax=_maxEff),
304  Plot("effic_vs_dzpvcut2", xtitle="Cut on dz(PV) (cm)", ytitle="Efficiency (excl. trk eff)", ymax=_maxEff),
305  Plot("fakerate_vs_dzpvcut", xtitle="Cut on dz(PV) (cm)", ytitle="Fake rate vs. cut on dz(PV)", ymax=_maxFake),
306  Plot("pileuprate_dzpvcut", xtitle="Cut on dz(PV) (cm)", ytitle="Pileup rate vs. cut on dz(PV)", ymax=_maxFake),
307  #
308  Plot("effic_vs_dzpvsigcut", xtitle="Cut on dz(PV)/dzError", ytitle="Efficiency vs. cut on dz(PV)/dzError", ymax=_maxEff),
309  Plot("effic_vs_dzpvsigcut2", xtitle="Cut on dz(PV)/dzError", ytitle="Efficiency (excl. trk eff)", ymax=_maxEff),
310  Plot("fakerate_vs_dzpvsigcut", xtitle="Cut on dz(PV)/dzError", ytitle="Fake rate vs. cut on dz(PV)/dzError", ymax=_maxFake),
311  Plot("pileuprate_dzpvsigcut", xtitle="Cut on dz(PV)/dzError", ytitle="Pileup rate vs. cut on dz(PV)/dzError", ymax=_maxFake),
312 ], onlyForPileup=True,
313  legendDy=_legendDy_4rows
314 )
315 
316 
317 # These don't exist in FastSim
318 _common = {"normalizeToUnitArea": True, "stat": True, "drawStyle": "hist"}
319 _dedx = PlotGroup("dedx", [
320  Plot("h_dedx_estim1", xtitle="dE/dx, harm2", **_common),
321  Plot("h_dedx_estim2", xtitle="dE/dx, trunc40", **_common),
322  Plot("h_dedx_nom1", xtitle="dE/dx number of measurements", title="", **_common),
323  Plot("h_dedx_sat1", xtitle="dE/dx number of measurements with saturation", title="", **_common),
324  ],
325  legendDy=_legendDy_2rows
326 )
327 
328 _chargemisid = PlotGroup("chargemisid", [
329  Plot("chargeMisIdRate", xtitle="#eta", ytitle="charge mis-id rate vs #eta", ymax=0.05),
330  Plot("chargeMisIdRate_Pt", xtitle="p_{T}", ytitle="charge mis-id rate vs p_{T}", xmax=300, ymax=0.1, xlog=True),
331  Plot("chargeMisIdRate_hit", xtitle="hits", ytitle="charge mis-id rate vs hits", title=""),
332  Plot("chargeMisIdRate_phi", xtitle="#phi", ytitle="charge mis-id rate vs #phi", title="", ymax=0.01),
333  Plot("chargeMisIdRate_dxy", xtitle="dxy", ytitle="charge mis-id rate vs dxy", ymax=0.1),
334  Plot("chargeMisIdRate_dz", xtitle="dz", ytitle="charge mis-id rate vs dz", ymax=0.1)
335 ])
336 _common = {"stat": True, "normalizeToUnitArea": True, "ylog": True, "ymin": 1e-6, "drawStyle": "hist"}
337 _hitsAndPt = PlotGroup("hitsAndPt", [
338  Plot("missing_inner_layers", xmin=_minLayers, xmax=_maxLayers, ymax=1, **_common),
339  Plot("missing_outer_layers", xmin=_minLayers, xmax=_maxLayers, ymax=1, **_common),
340  Plot("hits_eta", xtitle="track #eta", ytitle="<hits> vs #eta", ymin=_minHits, ymax=_maxHits, statyadjust=[0,0,-0.15],
341  fallback={"name": "nhits_vs_eta", "profileX": True}),
342  Plot("hits", stat=True, xtitle="track hits", xmin=_minHits, xmax=_maxHits, ylog=True, ymin=[5e-1, 5, 5e1, 5e2, 5e3], drawStyle="hist"),
343  Plot("num_simul_pT", xtitle="TP p_{T}", xlog=True, ymax=[1e-1, 2e-1, 5e-1, 1], **_common),
344  Plot("num_reco_pT", xtitle="track p_{T}", xlog=True, ymax=[1e-1, 2e-1, 5e-1, 1], **_common)
345 ])
346 _tuning = PlotGroup("tuning", [
347  Plot("chi2", stat=True, normalizeToUnitArea=True, ylog=True, ymin=1e-6, ymax=[0.1, 0.2, 0.5, 1.0001], drawStyle="hist", xtitle="#chi^{2}", ratioUncertainty=False),
348  Plot("chi2_prob", stat=True, normalizeToUnitArea=True, drawStyle="hist", xtitle="Prob(#chi^{2})"),
349  Plot("chi2mean", title="", xtitle="#eta", ytitle="< #chi^{2} / ndf >", ymin=[0, 0.5], ymax=[2, 2.5, 3, 5],
350  fallback={"name": "chi2_vs_eta", "profileX": True}),
351  Plot("ptres_vs_eta_Mean", scale=100, title="", xtitle="TP #eta (PCA to beamline)", ytitle="< #delta p_{T} / p_{T} > (%)", ymin=_minResidualPt, ymax=_maxResidualPt),
352  Plot("chi2mean_vs_pt", title="", xtitle="p_{T}", ytitle="< #chi^{2} / ndf >", ymin=[0, 0.5], ymax=[2, 2.5, 3, 5], xlog=True, fallback={"name": "chi2_vs_pt", "profileX": True}),
353  Plot("chi2mean_vs_drj", title="", xtitle="#DeltaR(track, jet)", ytitle="< #chi^{2} / ndf >", ymin=[0, 0.5], ymax=[2, 2.5, 3, 5], xlog=True, xmax=_maxDRJ, fallback={"name": "chi2_vs_drj", "profileX": True}),
354  Plot("ptres_vs_pt_Mean", title="", xtitle="p_{T}", ytitle="< #delta p_{T}/p_{T} > (%)", scale=100, ymin=_minResidualPt, ymax=_maxResidualPt,xlog=True)
355 ],
356  legendDy=_legendDy_4rows
357 )
358 _common = {"stat": True, "fit": True, "normalizeToUnitArea": True, "drawStyle": "hist", "drawCommand": "", "xmin": -10, "xmax": 10, "ylog": True, "ymin": 5e-5, "ymax": [0.01, 0.05, 0.1, 0.2, 0.5, 0.8, 1.025], "ratioUncertainty": False}
359 _pulls = PlotGroup("pulls", [
360  Plot("pullPt", **_common),
361  Plot("pullQoverp", **_common),
362  Plot("pullPhi", **_common),
363  Plot("pullTheta", **_common),
364  Plot("pullDxy", **_common),
365  Plot("pullDz", **_common),
366 ],
367  legendDx=0.1, legendDw=-0.1, legendDh=-0.015
368 )
369 _common = {"title": "", "ylog": True, "xtitle": "TP #eta (PCA to beamline)", "ymin": _minMaxResol, "ymax": _minMaxResol}
370 _resolutionsEta = PlotGroup("resolutionsEta", [
371  Plot("phires_vs_eta_Sigma", ytitle="#sigma(#delta #phi) (rad)", **_common),
372  Plot("cotThetares_vs_eta_Sigma", ytitle="#sigma(#delta cot(#theta))", **_common),
373  Plot("dxyres_vs_eta_Sigma", ytitle="#sigma(#delta d_{xy}) (cm)", **_common),
374  Plot("dzres_vs_eta_Sigma", ytitle="#sigma(#delta d_{z}) (cm)", **_common),
375  Plot("ptres_vs_eta_Sigma", ytitle="#sigma(#delta p_{T}/p_{T})", **_common),
376 ])
377 _common = {"title": "", "ylog": True, "xlog": True, "xtitle": "TP p_{T} (PCA to beamline)", "xmin": 0.1, "xmax": 1000, "ymin": _minMaxResol, "ymax": _minMaxResol}
378 _resolutionsPt = PlotGroup("resolutionsPt", [
379  Plot("phires_vs_pt_Sigma", ytitle="#sigma(#delta #phi) (rad)", **_common),
380  Plot("cotThetares_vs_pt_Sigma", ytitle="#sigma(#delta cot(#theta))", **_common),
381  Plot("dxyres_vs_pt_Sigma", ytitle="#sigma(#delta d_{xy}) (cm)", **_common),
382  Plot("dzres_vs_pt_Sigma", ytitle="#sigma(#delta d_{z}) (cm)", **_common),
383  Plot("ptres_vs_pt_Sigma", ytitle="#sigma(#delta p_{T}/p_{T})", **_common),
384 ])
385 _common = {"title": "", "ylog": True, "xtitle": "TP #Phi (PCA to beamline)", "ymin": _minMaxResol, "ymax": _minMaxResol}
386 _resolutionsPhi = PlotGroup("resolutionsPhi", [
387  Plot("dxyres_vs_phi_Sigma", ytitle="#sigma(#delta d_{xy}) (cm)", **_common),
388  Plot("dzres_vs_phi_Sigma", ytitle="#sigma(#delta d_{z}) (cm)", **_common),
389  Plot("phires_vs_phi_Sigma", ytitle="#sigma(#delta #phi) (rad)", **_common),
390  Plot("ptres_vs_phi_Sigma", ytitle="#sigma(#delta p_{T}/p_{T})", **_common),
391 ])
392 
393 
394 _extDistPtEtaPhi = PlotGroup("distPtEtaPhi",
395  _makeDistPlots("pT", "p_{T} (GeV)", common=dict(xlog=True)) +
396  _makeDistPlots("eta", "#eta") +
397  _makeDistPlots("phi", "#phi"),
398  ncols=4)
399 _extDistDxyDzBS = PlotGroup("distDxyDzBS",
400  _makeDistPlots("dxy" , "dxy (cm)") +
401  _makeDistPlots("dz" , "dz (cm)"),
402  ncols=4, legendDy=_legendDy_2rows)
403 _extDistDxyDzPV = PlotGroup("distDxyDzPV",
404  _makeDistPlots("dxypv" , "dxy(PV) (cm)") +
405  _makeDistPlots("dxypv_zoomed", "dxy(PV) (cm)") +
406  _makeDistPlots("dzpv" , "dz(PV) (cm)") +
407  _makeDistPlots("dzpv_zoomed" , "dz(PV) (cm)"),
408  ncols=4, legendDy=_legendDy_4rows)
409 _extDistHitsLayers = PlotGroup("distHitsLayers",
410  _makeDistPlots("hit" , "hits" , common=dict(xmin=_minHits , xmax=_maxHits)) +
411  _makeDistPlots("layer" , "layers" , common=dict(xmin=_minLayers , xmax=_maxLayers)) +
412  _makeDistPlots("pixellayer", "pixel layers", common=dict( xmax=_maxPixelLayers)) +
413  _makeDistPlots("3Dlayer" , "3D layers" , common=dict(xmin=_min3DLayers, xmax=_max3DLayers)),
414  ncols=4, legendDy=_legendDy_4rows,
415 )
416 _extDistPos = PlotGroup("distPos",
417  _makeDistPlots("vertpos", "ref. point r (cm)", common=dict(xlog=True)) +
418  _makeDistPlots("zpos" , "ref. point z (cm)") +
419  _makeDistPlots("simpvz" , "Sim. PV z (cm)", common=dict(xmin=_minZ, xmax=_maxZ)),
420  ncols=3,
421 )
422 _extDistDeltaR = PlotGroup("distDeltaR",
423  _makeDistPlots("dr" , "min #DeltaR", common=dict(xlog=True)) +
424  _makeDistPlots("drj" , "#DeltaR(track, jet)", common=dict(xlog=True, xmax=_maxDRJ)),
425  ncols=2, legendDy=_legendDy_2rows,
426 )
427 _extDistSeedingPlots = _makeDistPlots("seedingLayerSet", "seeding layers", common=dict(xtitle="", **_seedingLayerSet_common))
428 _extDistChi2Seeding = PlotGroup("distChi2Seeding",
429  _makeDistPlots("chi2", "#chi^{2}") +
430  _extDistSeedingPlots,
431  ncols=4, legendDy=_legendDy_2rows_3cols
432 )
433 _common = dict(title="", xtitle="TP #eta (PCA to beamline)")
434 _extResidualEta = PlotGroup("residualEta", [
435  Plot("phires_vs_eta_Mean", ytitle="< #delta #phi > (rad)", ymin=_minResidualPhi, ymax=_maxResidualPhi, **_common),
436  Plot("cotThetares_vs_eta_Mean", ytitle="< #delta cot(#theta) >", ymin=_minResidualCotTheta, ymax=_maxResidualCotTheta, **_common),
437  Plot("dxyres_vs_eta_Mean", ytitle="< #delta d_{xy} > (#mum)", scale=10000, ymin=_minResidualDxy, ymax=_maxResidualDxy, **_common),
438  Plot("dzres_vs_eta_Mean", ytitle="< #delta d_{z} > (#mum)", scale=10000, ymin=_minResidualDz, ymax=_maxResidualDz, **_common),
439  Plot("ptres_vs_eta_Mean", ytitle="< #delta p_{T}/p_{T} > (%)", scale=100, ymin=_minResidualPt, ymax=_maxResidualPt, **_common), # same as in tuning, but to be complete
440 ])
441 _common = dict(title="", xlog=True, xtitle="TP p_{T} (PCA to beamline)", xmin=0.1, xmax=1000)
442 _extResidualPt = PlotGroup("residualPt", [
443  Plot("phires_vs_pt_Mean", ytitle="< #delta #phi > (rad)", ymin=_minResidualPhi, ymax=_maxResidualPhi, **_common),
444  Plot("cotThetares_vs_pt_Mean", ytitle="< #delta cot(#theta > )", ymin=_minResidualCotTheta, ymax=_maxResidualCotTheta, **_common),
445  Plot("dxyres_vs_pt_Mean", ytitle="< #delta d_{xy} > (#mum)", scale=10000, ymin=_minResidualDxy, ymax=_maxResidualDxy, **_common),
446  Plot("dzres_vs_pt_Mean", ytitle="< #delta d_{z} > (#mum)", scale=10000, ymin=_minResidualDz, ymax=_maxResidualDz, **_common),
447  Plot("ptres_vs_pt_Mean", ytitle="< #delta p_{T}/p_{T} > (%)", scale=100, ymin=_minResidualPt, ymax=_maxResidualPt, **_common), # same as in tuning, but to be complete
448 ])
449 _common = dict(title="", ytitle="Selected tracks/TrackingParticles", ymax=_maxEff)
450 _extNrecVsNsim = PlotGroup("nrecVsNsim", [
451  Plot("nrec_vs_nsim", title="", xtitle="TrackingParticles", ytitle="Tracks", profileX=True, xmin=_minMaxTracks, xmax=_minMaxTracks, ymin=_minMaxTracks, ymax=_minMaxTracks),
452  Plot("nrecPerNsim_vs_pu", xtitle="Pileup", xmin=_minPU, xmax=_maxPU, **_common),
453  Plot("nrecPerNsimPt", xtitle="p_{T} (GeV)", xlog=True, **_common),
454  Plot("nrecPerNsim", xtitle="#eta", **_common)
455 ], legendDy=_legendDy_2rows)
456 _extHitsLayers = PlotGroup("hitsLayers", [
457  Plot("PXLhits_vs_eta", xtitle="#eta", ytitle="<pixel hits>"),
458  Plot("PXLlayersWithMeas_vs_eta", xtitle="#eta", ytitle="<pixel layers>"),
459  Plot("STRIPhits_vs_eta", xtitle="#eta", ytitle="<strip hits>"),
460  Plot("STRIPlayersWithMeas_vs_eta", xtitle="#eta", ytitle="<strip layers>"),
461 ], legendDy=_legendDy_2rows)
462 
463 
464 
465 _extDistSimPtEtaPhi = PlotGroup("distsimPtEtaPhi",
466  _makeDistSimPlots("pT", "p_{T} (GeV)", common=dict(xlog=True)) +
467  _makeDistSimPlots("eta", "#eta") +
468  _makeDistSimPlots("phi", "#phi"),
469  ncols=2)
470 _extDistSimDxyDzBS = PlotGroup("distsimDxyDzBS",
471  _makeDistSimPlots("dxy" , "dxy (cm)") +
472  _makeDistSimPlots("dz" , "dz (cm)"),
473  ncols=2, legendDy=_legendDy_2rows)
474 _extDistSimDxyDzPV = PlotGroup("distsimDxyDzPV",
475  _makeDistSimPlots("dxypv" , "dxy(PV) (cm)") +
476  _makeDistSimPlots("dxypv_zoomed", "dxy(PV) (cm)") +
477  _makeDistSimPlots("dzpv" , "dz(PV) (cm)") +
478  _makeDistSimPlots("dzpv_zoomed" , "dz(PV) (cm)"),
479  ncols=2, legendDy=_legendDy_4rows)
480 _extDistSimHitsLayers = PlotGroup("distsimHitsLayers",
481  _makeDistSimPlots("hit" , "hits" , common=dict(xmin=_minHits , xmax=_maxHits)) +
482  _makeDistSimPlots("layer" , "layers" , common=dict(xmin=_minLayers , xmax=_maxLayers)) +
483  _makeDistSimPlots("pixellayer", "pixel layers", common=dict( xmax=_maxPixelLayers)) +
484  _makeDistSimPlots("3Dlayer" , "3D layers" , common=dict(xmin=_min3DLayers, xmax=_max3DLayers)),
485  ncols=2, legendDy=_legendDy_4rows,
486 )
487 _extDistSimPos = PlotGroup("distsimPos",
488  _makeDistSimPlots("vertpos", "vert r (cm)", common=dict(xlog=True)) +
489  _makeDistSimPlots("zpos" , "vert z (cm)") +
490  _makeDistSimPlots("simpvz" , "Sim. PV z (cm)", common=dict(xmin=_minZ, xmax=_maxZ)),
491  ncols=3,
492 )
493 _extDistSimDeltaR = PlotGroup("distsimDeltaR",
494  _makeDistSimPlots("dr" , "min #DeltaR", common=dict(xlog=True)) +
495  _makeDistSimPlots("drj" , "#DeltaR(TP, jet)", common=dict(xlog=True, xmax=_maxDRJ)),
496  ncols=2, legendDy=_legendDy_2rows,
497 )
498 
499 
504 
505 _possibleTrackingNonIterationColls = [
506  'ak4PFJets',
507  'btvLike',
508 ]
509 _possibleTrackingColls = [
510  'initialStepPreSplitting',
511  'initialStep',
512  'highPtTripletStep', # phase1
513  'detachedQuadStep', # phase1
514  'detachedTripletStep',
515  'lowPtQuadStep', # phase1
516  'lowPtTripletStep',
517  'pixelPairStepA', # seeds
518  'pixelPairStepB', # seeds
519  'pixelPairStepC', # seeds
520  'pixelPairStep',
521  'mixedTripletStepA', # seeds
522  'mixedTripletStepB', # seeds
523  'mixedTripletStep',
524  'pixelLessStep',
525  'tobTecStepPair', # seeds
526  'tobTecStepTripl', # seeds
527  'tobTecStep',
528  'displacedGeneralStep',
529  'jetCoreRegionalStep',
530  'muonSeededStepInOut',
531  'muonSeededStepOutIn',
532  'displacedRegionalStepPair', # seeds
533  'displacedRegionalStepTripl', # seeds
534  'displacedRegionalStep',
535  'duplicateMerge',
536 ] + _possibleTrackingNonIterationColls
537 _possibleTrackingCollsOld = {
538  "Zero" : "iter0",
539  "First" : "iter1",
540  "Second": "iter2",
541  "Third" : "iter3",
542  "Fourth": "iter4",
543  "Fifth" : "iter5",
544  "Sixth" : "iter6",
545  "Seventh": "iter7",
546  "Ninth" : "iter9",
547  "Tenth" : "iter10",
548 }
549 
550 def _trackingSubFoldersFallbackSLHC_Phase1PU140(subfolder):
551  ret = subfolder.replace("trackingParticleRecoAsssociation", "AssociatorByHitsRecoDenom")
552  for (old, new) in [("InitialStep", "Zero"),
553  ("HighPtTripletStep", "First"),
554  ("LowPtQuadStep", "Second"),
555  ("LowPtTripletStep", "Third"),
556  ("DetachedQuadStep", "Fourth"),
557  ("PixelPairStep", "Fifth"),
558  ("MuonSeededStepInOut", "Ninth"),
559  ("MuonSeededStepOutIn", "Tenth")]:
560  ret = ret.replace(old, new)
561  if ret == subfolder:
562  return None
563  return ret
564 def _trackingRefFileFallbackSLHC_Phase1PU140(path):
565  for (old, new) in [("initialStep", "iter0"),
566  ("highPtTripletStep", "iter1"),
567  ("lowPtQuadStep", "iter2"),
568  ("lowPtTripletStep", "iter3"),
569  ("detachedQuadStep", "iter4"),
570  ("pixelPairStep", "iter5"),
571  ("muonSeededStepInOut", "iter9"),
572  ("muonSeededStepOutIn", "iter10")]:
573  path = path.replace(old, new)
574  return path
575 
576 def _trackingSubFoldersFallbackFromPV(subfolder):
577  return subfolder.replace("trackingParticleRecoAsssociation", "trackingParticleRecoAsssociationSignal")
578 def _trackingSubFoldersFallbackConversion(subfolder):
579  return subfolder.replace("quickAssociatorByHits", "quickAssociatorByHitsConversion")
580 def _trackingSubFoldersFallbackPreSplitting(subfolder):
581  return subfolder.replace("quickAssociatorByHits", "quickAssociatorByHitsPreSplitting")
582 
583 # Additional "quality" flags than highPurity. In a separate list to
584 # allow customization.
585 _additionalTrackQualities = [
586  "Pt09",
587  "ByOriginalAlgo",
588  "ByAlgoMask"
589 ]
590 def _mapCollectionToAlgoQuality(collName):
591  if "Hp" in collName:
592  quality = "highPurity"
593  else:
594  quality = ""
595  collNameNoQuality = collName.replace("Hp", "")
596  for qual in _additionalTrackQualities:
597  if qual in collName:
598  quality += qual
599  collNameNoQuality = collNameNoQuality.replace(qual, "")
600 
601  collNameNoQuality = collNameNoQuality.replace("Tracks", "", 1) # make summary naming consistent with iteration folders
602  collNameLow = collNameNoQuality.lower().replace("frompv2", "").replace("frompv", "").replace("frompvalltp", "").replace("alltp", "")
603 
604  if collNameLow.find("seed") == 0:
605  collNameLow = collNameLow[4:]
606  if collNameLow == "initialstepseedspresplitting":
607  collNameLow = "initialsteppresplittingseeds"
608  elif collNameLow == "muonseededseedsinout":
609  collNameLow = "muonseededstepinoutseeds"
610  elif collNameLow == "muonseededseedsoutin":
611  collNameLow = "muonseededstepoutinseeds"
612 
613  i_seeds = collNameLow.index("seeds")
614  quality = collNameLow[i_seeds:]+quality
615 
616  collNameLow = collNameLow[:i_seeds]
617 
618  algo = None
619  prefixes = ["cutsreco", "cutsrecofrompv", "cutsrecofrompv2", "cutsrecofrompvalltp", "cutsrecoetagreater2p7"]
620  if collNameLow in ["general", "generalfrompv", "generaletagreater2p7"]+prefixes:
621  algo = "ootb"
622  elif collNameLow in ["pixel", "pixelfrompv", "pixelfrompvalltp"]:
623  algo = "pixel"
624  else:
625  def testColl(coll):
626  for pfx in prefixes:
627  if coll == collNameLow.replace(pfx, ""):
628  return True
629  return False
630 
631  for coll in _possibleTrackingColls:
632  if testColl(coll.lower()):
633  algo = coll
634  break
635  # next try "old style"
636  if algo is None:
637  for coll, name in _possibleTrackingCollsOld.items():
638  if testColl(coll.lower()):
639  algo = name
640  break
641 
642  # fallback
643  if algo is None:
644  algo = collNameNoQuality
645 
646  # fix for track collection naming convention
647  if algo == "muonSeededInOut":
648  algo = "muonSeededStepInOut"
649  if algo == "muonSeededOutIn":
650  algo = "muonSeededStepOutIn"
651 
652  return (algo, quality)
653 
654 def _collhelper(name):
655  return (name, [name])
656 _collLabelMap = collections.OrderedDict(map(_collhelper, ["generalTracks"]+_possibleTrackingColls))
657 _collLabelMapHp = collections.OrderedDict(map(_collhelper, ["generalTracks"]+[n for n in _possibleTrackingColls if "Step" in n]))
658 def _summaryBinRename(binLabel, highPurity, byOriginalAlgo, byAlgoMask, ptCut, seeds):
659  (algo, quality) = _mapCollectionToAlgoQuality(binLabel)
660  if algo == "ootb":
661  algo = "generalTracks"
662  ret = None
663 
664  if byOriginalAlgo:
665  if algo != "generalTracks" and "ByOriginalAlgo" not in quality: # keep generalTracks bin as well
666  return None
667  quality = quality.replace("ByOriginalAlgo", "")
668  if byAlgoMask:
669  if algo != "generalTracks" and "ByAlgoMask" not in quality: # keep generalTracks bin as well
670  return None
671  quality = quality.replace("ByAlgoMask", "")
672  if ptCut:
673  if "Pt09" not in quality:
674  return None
675  quality = quality.replace("Pt09", "")
676 
677  if highPurity:
678  if quality == "highPurity":
679  ret = algo
680  elif seeds:
681  i_seeds = quality.find("seeds")
682  if i_seeds == 0:
683  ret = algo
684  seedSubColl = quality[i_seeds+5:]
685  if seedSubColl != "":
686  ret += seedSubColl[0].upper() + seedSubColl[1:]
687  else:
688  if quality == "":
689  ret = algo
690 
691  return ret
692 
693 def _constructSummary(mapping=None, highPurity=False, byOriginalAlgo=False, byAlgoMask=False, ptCut=False, seeds=False, midfix=""):
694  _common = {"drawStyle": "EP", "xbinlabelsize": 10, "xbinlabeloption": "d"}
695  _commonN = dict(ylog=True, ymin=_minMaxN, ymax=_minMaxN,
696  normalizeToNumberOfEvents=True,
697  )
698  _commonN.update(_common)
699  _commonAB = dict(mapping=mapping,
700  renameBin=lambda bl: _summaryBinRename(bl, highPurity, byOriginalAlgo, byAlgoMask, ptCut, seeds),
701  ignoreMissingBins=True,
702  originalOrder=True,
703  )
704  if byOriginalAlgo or byAlgoMask:
705  _commonAB["minExistingBins"] = 2
706  prefix = "summary"+midfix
707 
708  h_eff = "effic_vs_coll"
709  h_fakerate = "fakerate_vs_coll"
710  h_duplicaterate = "duplicatesRate_coll"
711  h_pileuprate = "pileuprate_coll"
712 
713  h_reco = "num_reco_coll"
714  h_true = "num_assoc(recoToSim)_coll"
715  h_fake = Subtract("num_fake_coll_orig", "num_reco_coll", "num_assoc(recoToSim)_coll")
716  h_duplicate = "num_duplicate_coll"
717  h_pileup = "num_pileup_coll"
718  if mapping is not None:
719  h_eff = AggregateBins("efficiency", h_eff, **_commonAB)
720  h_fakerate = AggregateBins("fakerate", h_fakerate, **_commonAB)
721  h_duplicaterate = AggregateBins("duplicatesRate", h_duplicaterate, **_commonAB)
722  h_pileuprate = AggregateBins("pileuprate", h_pileuprate, **_commonAB)
723 
724  h_reco = AggregateBins("num_reco_coll", h_reco, **_commonAB)
725  h_true = AggregateBins("num_true_coll", h_true, **_commonAB)
726  h_fake = AggregateBins("num_fake_coll", h_fake, **_commonAB)
727  h_duplicate = AggregateBins("num_duplicate_coll", h_duplicate, **_commonAB)
728  h_pileup = AggregateBins("num_pileup_coll", h_pileup, **_commonAB)
729 
730  summary = PlotGroup(prefix, [
731  Plot(h_eff, title="Efficiency vs collection", ytitle="Efficiency", ymin=1e-3, ymax=1, ylog=True, **_common),
732  Plot(h_fakerate, title="Fakerate vs collection", ytitle="Fake rate", ymax=_maxFake, **_common),
733  #
734  Plot(h_duplicaterate, title="Duplicates rate vs collection", ytitle="Duplicates rate", ymax=_maxFake, **_common),
735  Plot(h_pileuprate, title="Pileup rate vs collection", ytitle="Pileup rate", ymax=_maxFake, **_common),
736  ],
737  legendDy=_legendDy_2rows
738  )
739  summaryN = PlotGroup(prefix+"_ntracks", [
740  # FIXME
741  #Plot(h_reco, ytitle="Tracks/event", title="Number of tracks/event vs collection", **_commonN),
742  #Plot(h_true, ytitle="True tracks/event", title="Number of true tracks/event vs collection", **_commonN),
743  #Plot(h_fake, ytitle="Fake tracks/event", title="Number of fake tracks/event vs collection", **_commonN),
744  #Plot(h_duplicate, ytitle="Duplicate tracks/event", title="Number of duplicate tracks/event vs collection", **_commonN),
745  #Plot(h_pileup, ytitle="Pileup tracks/event", title="Number of pileup tracks/event vs collection", **_commonN),
746  Plot(h_reco, ytitle="Tracks", title="Number of tracks vs collection", **_commonN),
747  Plot(h_true, ytitle="True tracks", title="Number of true tracks vs collection", **_commonN),
748  Plot(h_fake, ytitle="Fake tracks", title="Number of fake tracks vs collection", **_commonN),
749  Plot(h_duplicate, ytitle="Duplicate tracks", title="Number of duplicate tracks vs collection", **_commonN),
750  Plot(h_pileup, ytitle="Pileup tracks", title="Number of pileup tracks vs collection", **_commonN),
751  ])
752 
753  return (summary, summaryN)
754 
755 (_summaryRaw, _summaryRawN) = _constructSummary(midfix="Raw")
756 (_summary, _summaryN) = _constructSummary(_collLabelMap)
757 (_summaryHp, _summaryNHp) = _constructSummary(_collLabelMapHp, highPurity=True)
758 (_summaryByOriginalAlgo, _summaryByOriginalAlgoN) = _constructSummary(_collLabelMapHp, byOriginalAlgo=True, midfix="ByOriginalAlgo")
759 (_summaryByOriginalAlgoHp, _summaryByOriginalAlgoNHp) = _constructSummary(_collLabelMapHp, byOriginalAlgo=True, midfix="ByOriginalAlgo", highPurity=True)
760 (_summaryByAlgoMask, _summaryByAlgoMaskN) = _constructSummary(_collLabelMapHp, byAlgoMask=True, midfix="ByAlgoMask")
761 (_summaryByAlgoMaskHp, _summaryByAlgoMaskNHp) = _constructSummary(_collLabelMapHp, byAlgoMask=True, midfix="ByAlgoMask", highPurity=True)
762 (_summaryPt09, _summaryPt09N) = _constructSummary(_collLabelMap, ptCut=True, midfix="Pt09")
763 (_summaryPt09Hp, _summaryPt09NHp) = _constructSummary(_collLabelMap, ptCut=True, midfix="Pt09", highPurity=True)
764 (_summarySeeds, _summarySeedsN) = _constructSummary(_collLabelMapHp, seeds=True)
765 
766 
771 
772 _common = {"normalizeToUnitArea": True, "ylog": True, "ymin": [1e-7, 1e-6, 1e-5, 1e-4, 1e-3, 1e-2], "ymax": [1e-2, 1e-1, 1.1]}
773 _commonStatus = {}
774 _commonStatus.update(_common)
775 _commonStatus.update({"xbinlabelsize": 10, "xbinlabeloption": "d", "drawStyle": "hist", "adjustMarginRight": 0.08})
776 _commonLabelSize = {}
777 _commonLabelSize.update(_common)
778 _commonLabelSize.update({"xlabelsize": 17})
779 
780 _packedCandidateFlow = PlotGroup("flow", [
781  Plot("selectionFlow", xbinlabelsize=10, xbinlabeloption="d", adjustMarginRight=0.1, drawStyle="hist", ylog=True, ymin=[0.9, 9, 9e1, 9e2, 9e3, 9e4, 9e5, 9e6, 9e7]),
782  Plot("diffCharge", xtitle="Charge", **_common),
783  Plot("diffIsHighPurity", xtitle="High purity status", **_common),
784  Plot("diffNdof", xtitle="ndof", **_common),
785  Plot("diffNormalizedChi2", xtitle="#chi^{2}/ndof", **_common),
786 ])
787 
788 _packedCandidateHitsHitPattern = PlotGroup("hitsHitPattern", [
789  Plot("diffHitPatternNumberOfValidHits", xtitle="Valid hits (via HitPattern)", **_common),
790  Plot("diffHitPatternNumberOfValidPixelHits", xtitle="Valid pixel hits (via HitPattern)", **_common),
791  Plot("diffHitPatternHasValidHitInFirstPixelBarrel", xtitle="Has valid hit in BPix1 layer (via HitPattern)", **_common),
792  Plot("diffHitPatternNumberOfLostPixelHits", xtitle="Lost pixel hits (via HitPattern)", **_common),
793 ],
794  legendDy=_legendDy_2rows
795 )
796 _packedCandidateHits = PlotGroup("hits", [
797  Plot("diffNumberOfHits", xtitle="Hits", **_common),
798  Plot("diffNumberOfPixelHits", xtitle="Pixel hits", **_common),
799  Plot("diffLostInnerHits", xtitle="Lost inner hits", **_common),
800  Plot("numberHitsOverMax", xtitle="Number of overflown hits", **_common),
801  Plot("numberPixelHitsOverMax", xtitle="Number of overflown pixel hits", **_common),
802  Plot("numberStripHitsOverMax", xtitle="Number of overflown strip hits", **_common),
803 ],
804  ncols=3, legendDy=_legendDy_2rows_3cols
805 )
806 
807 _packedCandidateLayers = PlotGroup("layers", [
808  PlotEmpty(),
809  Plot("diffNumberOfPixelLayers", xtitle="Pixel layers", **_common),
810  Plot("diffNumberOfStripLayers", xtitle="Strip layers", **_common),
811  #
812  Plot("diffHitPatternTrackerLayersWithMeasurement", xtitle="Layers (via HitPattern)", **_common),
813  Plot("diffHitPatternPixelLayersWithMeasurement", xtitle="Pixel layers (via HitPattern)", **_common),
814  Plot("diffHitPatternStripLayersWithMeasurement", xtitle="Strip layers (via HitPattern)", **_common),
815  #
816  Plot("numberLayersOverMax", xtitle="Number of overflown layers", **_common),
817  Plot("numberPixelLayersOverMax", xtitle="Number of overflown pixel layers", **_common),
818  Plot("numberStripLayersOverMax", xtitle="Number of overflown strip layers", **_common),
819 ],
820  ncols=3
821 )
822 
823 
824 _packedCandidateImpactParameter1 = PlotGroup("impactParameter1", [
825  Plot("diffDxyAssocPV", xtitle="dxy(assocPV)", adjustMarginRight=0.02, **_commonLabelSize),
826  Plot("diffDxyAssocPVStatus", **_commonStatus),
827  Plot("diffDxyAssocPVUnderOverFlowSign", xtitle="dxy(assocPV)", **_common),
828  Plot("diffDzAssocPV", xtitle="dz(assocPV)", adjustMarginRight=0.02, **_commonLabelSize),
829  Plot("diffDzAssocPVStatus", **_commonStatus),
830  Plot("diffDzAssocPVUnderOverFlowSign", xtitle="dz(assocPV)", **_common),
831  Plot("diffDxyError", xtitle="dxyError()", adjustMarginRight=0.02, **_commonLabelSize),
832  Plot("diffDszError", xtitle="dszError()", adjustMarginRight=0.02, **_commonLabelSize),
833  Plot("diffDzError", xtitle="dzError()", adjustMarginRight=0.02, **_commonLabelSize),
834 
835 ],
836  ncols=3
837 )
838 
839 _packedCandidateImpactParameter2 = PlotGroup("impactParameter2", [
840  Plot("diffDxyPV", xtitle="dxy(PV) via PC", **_commonLabelSize),
841  Plot("diffDzPV", xtitle="dz(PV) via PC", **_commonLabelSize),
842  Plot("diffTrackDxyAssocPV", xtitle="dxy(PV) via PC::bestTrack()", **_commonLabelSize),
843  Plot("diffTrackDzAssocPV", xtitle="dz(PV) via PC::bestTrack()", **_commonLabelSize),
844  Plot("diffTrackDxyError", xtitle="dxyError() via PC::bestTrack()", adjustMarginRight=0.02, **_commonLabelSize),
845  Plot("diffTrackDzError", xtitle="dzError() via PC::bestTrack()", **_commonLabelSize),
846 ])
847 
848 _packedCandidateCovarianceMatrix1 = PlotGroup("covarianceMatrix1", [
849  Plot("diffCovQoverpQoverp", xtitle="cov(qoverp, qoverp)", **_commonLabelSize),
850  Plot("diffCovQoverpQoverpStatus", **_commonStatus),
851  Plot("diffCovQoverpQoverpUnderOverFlowSign", xtitle="cov(qoverp, qoverp)", **_common),
852  Plot("diffCovLambdaLambda", xtitle="cov(lambda, lambda)", **_commonLabelSize),
853  Plot("diffCovLambdaLambdaStatus", **_commonStatus),
854  Plot("diffCovLambdaLambdaUnderOverFlowSign", xtitle="cov(lambda, lambda)", **_common),
855  Plot("diffCovLambdaDsz", xtitle="cov(lambda, dsz)", **_commonLabelSize),
856  Plot("diffCovLambdaDszStatus", **_commonStatus),
857  Plot("diffCovLambdaDszUnderOverFlowSign", xtitle="cov(lambda, dsz)", **_common),
858  Plot("diffCovPhiPhi", xtitle="cov(phi, phi)", **_commonLabelSize),
859  Plot("diffCovPhiPhiStatus", **_commonStatus),
860  Plot("diffCovPhiPhiUnderOverFlowSign", xtitle="cov(phi, phi)", **_common),
861 ],
862  ncols=3, legendDy=_legendDy_4rows
863 )
864 _packedCandidateCovarianceMatrix2 = PlotGroup("covarianceMatrix2", [
865  Plot("diffCovPhiDxy", xtitle="cov(phi, dxy)", **_commonLabelSize),
866  Plot("diffCovPhiDxyStatus", **_commonStatus),
867  Plot("diffCovPhiDxyUnderOverFlowSign", xtitle="cov(phi, dxy)", **_common),
868  Plot("diffCovDxyDxy", xtitle="cov(dxy, dxy)", adjustMarginRight=0.02, **_commonLabelSize),
869  Plot("diffCovDxyDxyStatus", **_commonStatus),
870  Plot("diffCovDxyDxyUnderOverFlowSign", xtitle="cov(dxy, dxy)", **_common),
871  Plot("diffCovDxyDsz", xtitle="cov(dxy, dsz)", adjustMarginRight=0.02, **_commonLabelSize),
872  Plot("diffCovDxyDszStatus", **_commonStatus),
873  Plot("diffCovDxyDszUnderOverFlowSign", xtitle="cov(dxy, dsz)", **_common),
874  Plot("diffCovDszDsz", xtitle="cov(dsz, dsz)", adjustMarginRight=0.02, **_commonLabelSize),
875  Plot("diffCovDszDszStatus", **_commonStatus),
876  Plot("diffCovDszDszUnderOverFlowSign", xtitle="cov(dsz, dsz)", **_common),
877 ],
878  ncols=3, legendDy=_legendDy_4rows
879 )
880 
881 _common["xlabelsize"] = 16
882 _packedCandidateVertex = PlotGroup("vertex", [
883  Plot("diffVx", xtitle="Reference point x", **_common),
884  Plot("diffVy", xtitle="Reference point y", **_common),
885  Plot("diffVz", xtitle="Reference point z", **_common),
886 ],
887  legendDy=_legendDy_2rows
888 )
889 
890 _common["adjustMarginRight"] = 0.05
891 _packedCandidateKinematics = PlotGroup("kinematics", [
892  Plot("diffPt", xtitle="p_{T}", **_common),
893  Plot("diffPtError", xtitle="p_{T} error", **_common),
894  Plot("diffEta", xtitle="#eta", **_common),
895  Plot("diffEtaError", xtitle="#eta error", **_common),
896  Plot("diffPhi", xtitle="#phi", **_common),
897 ])
898 
899 class TrackingPlotFolder(PlotFolder):
900  def __init__(self, *args, **kwargs):
901  self._fallbackRefFiles = kwargs.pop("fallbackRefFiles", [])
902  PlotFolder.__init__(self, *args, **kwargs)
903 
904  def translateSubFolder(self, dqmSubFolderName):
905  spl = dqmSubFolderName.split("_")
906  if len(spl) != 2:
907  return None
908  collName = spl[0]
909  return _mapCollectionToAlgoQuality(collName)
910 
911  def iterSelectionName(self, plotFolderName, translatedDqmSubFolder):
912  (algoOrig, quality) = translatedDqmSubFolder
913 
914  for fallback in [lambda n: n]+self._fallbackRefFiles:
915  algo = fallback(algoOrig)
916 
917  ret = ""
918  if plotFolderName != "":
919  ret += "_"+plotFolderName
920  if quality != "":
921  ret += "_"+quality
922  if not (algo == "ootb" and quality != ""):
923  ret += "_"+algo
924  yield ret
925 
926  def limitSubFolder(self, limitOnlyTo, translatedDqmSubFolder):
927  """Return True if this subfolder should be processed
928 
929  Arguments:
930  limitOnlyTo -- Function '(algo, quality) -> bool'
931  translatedDqmSubFolder -- Return value of translateSubFolder
932  """
933  (algo, quality) = translatedDqmSubFolder
934  return limitOnlyTo(algo, quality)
935 
936  # track-specific hack
937  def isAlgoIterative(self, algo):
938  return algo not in _possibleTrackingNonIterationColls
939 
940 class TrackingSummaryTable:
941  class GeneralTracks: pass
942  class GeneralTracksPt09: pass
943  class HighPurity: pass
944  class HighPurityPt09: pass
945  class BTVLike: pass
946  class AK4PFJets: pass
947  class Pixel: pass
948  class PixelPt09: pass
949 
950  def __init__(self, section, collection=GeneralTracks):
951  self._collection = collection
952  self._purpose = PlotPurpose.TrackingSummary
953  self._page = "summary"
954  self._section = section
955 
956  def getPurpose(self):
957  return self._purpose
958 
959  def getPage(self):
960  return self._page
961 
962  def getSection(self, dqmSubFolder):
963  return self._section
964 
965  def create(self, tdirectory):
966  def _getAlgoQuality(data, algo, quality):
967  for label, value in data.items():
968  (a, q) = _mapCollectionToAlgoQuality(label)
969  if a == algo and q == quality:
970  return value[0] # value is (value, uncertainty) tuple
971  return None
972  def _getN(hname):
973  h = tdirectory.Get(hname)
974  if not h:
975  return None
976  data = plotting._th1ToOrderedDict(h)
977  if self._collection == TrackingSummaryTable.GeneralTracks:
978  return _getAlgoQuality(data, "ootb", "")
979  elif self._collection == TrackingSummaryTable.GeneralTracksPt09:
980  return _getAlgoQuality(data, "ootb", "Pt09")
981  elif self._collection == TrackingSummaryTable.HighPurity:
982  return _getAlgoQuality(data, "ootb", "highPurity")
983  elif self._collection == TrackingSummaryTable.HighPurityPt09:
984  return _getAlgoQuality(data, "ootb", "highPurityPt09")
985  elif self._collection == TrackingSummaryTable.BTVLike:
986  return _getAlgoQuality(data, "btvLike", "")
987  elif self._collection == TrackingSummaryTable.AK4PFJets:
988  return _getAlgoQuality(data, "ak4PFJets", "")
989  elif self._collection == TrackingSummaryTable.Pixel:
990  return _getAlgoQuality(data, "pixel", "")
991  elif self._collection == TrackingSummaryTable.PixelPt09:
992  return _getAlgoQuality(data, "pixel", "Pt09")
993  else:
994  raise Exception("Collection not recognized, %s" % str(self._collection))
995  def _formatOrNone(num, func):
996  if num is None:
997  return None
998  return func(num)
999 
1000  n_tps = _formatOrNone(_getN("num_simul_coll"), int)
1001  n_m_tps = _formatOrNone(_getN("num_assoc(simToReco)_coll"), int)
1002 
1003  n_tracks = _formatOrNone(_getN("num_reco_coll"), int)
1004  n_true = _formatOrNone(_getN("num_assoc(recoToSim)_coll"), int)
1005  if n_tracks is not None and n_true is not None:
1006  n_fake = n_tracks-n_true
1007  else:
1008  n_fake = None
1009  n_pileup = _formatOrNone(_getN("num_pileup_coll"), int)
1010  n_duplicate = _formatOrNone(_getN("num_duplicate_coll"), int)
1011 
1012  eff = _formatOrNone(_getN("effic_vs_coll"), lambda n: "%.4f" % n)
1013  eff_nopt = _formatOrNone(_getN("effic_vs_coll_allPt"), lambda n: "%.4f" % n)
1014  fake = _formatOrNone(_getN("fakerate_vs_coll"), lambda n: "%.4f" % n)
1015  duplicate = _formatOrNone(_getN("duplicatesRate_coll"), lambda n: "%.4f" % n)
1016 
1017  ret = [eff, n_tps, n_m_tps,
1018  eff_nopt, fake, duplicate,
1019  n_tracks, n_true, n_fake, n_pileup, n_duplicate]
1020  if ret.count(None) == len(ret):
1021  return None
1022  return ret
1023 
1024  def headers(self):
1025  return [
1026  "Efficiency",
1027  "Number of TrackingParticles (after cuts)",
1028  "Number of matched TrackingParticles",
1029  "Efficiency (w/o pT cut)",
1030  "Fake rate",
1031  "Duplicate rate",
1032  "Number of tracks",
1033  "Number of true tracks",
1034  "Number of fake tracks",
1035  "Number of pileup tracks",
1036  "Number of duplicate tracks"
1037  ]
1038 
1039 # Provide a "PlotGroup" interface, but provide a html page
1040 class TrackingSeedingLayerTable:
1041  def __init__(self, fileName, plots, titles, isRate, **kwargs):
1042  self._plots = plots
1043  self._titles = titles
1044  self._fileName = fileName
1045  self._format = "%.4g" if isRate else "%d"
1046 
1047  if len(plots) != len(titles):
1048  raise Exception("Number of plots (%d) has to be the same as number of titles (%d)" % (len(plots), len(titles)))
1049 
1050  def _set(attr, default):
1051  setattr(self, "_"+attr, kwargs.get(attr, default))
1052 
1053  _set("onlyForPileup", False)
1054 
1055  def onlyForPileup(self):
1056  """Return True if the PlotGroup is intended only for pileup samples"""
1057  return self._onlyForPileup
1058 
1059  def create(self, tdirectoryNEvents, requireAllHistograms=False):
1060  # [plot][histo]
1061  for plot in self._plots:
1062  plot.create(tdirectoryNEvents, requireAllHistograms)
1063 
1064  def draw(self, legendLabels, prefix=None, directory="", *args, **kwargs):
1065  # Do not make the table if it would be empty
1066  onlyEmptyPlots = True
1067  for plot in self._plots:
1068  if not plot.isEmpty():
1069  onlyEmptyPlots = False
1070  break
1071  if onlyEmptyPlots:
1072  return []
1073 
1074  haveShortLabels = False
1075  legendLabels = legendLabels[:]
1076  if max(map(len, legendLabels)) > 20:
1077  haveShortLabels = True
1078  labels_short = [str(chr(ord('A')+i)) for i in range(len(legendLabels))]
1079  for i, ls in enumerate(labels_short):
1080  legendLabels[i] = "%s: %s" % (ls, legendLabels[i])
1081  else:
1082  labels_short = legendLabels
1083 
1084  content = [
1085  '<html>',
1086  ' <body>',
1087  ' <table border="1">',
1088  ' <tr>',
1089  ]
1090 
1091 
1092  histos_linear = []
1093  histos_index = []
1094  labels = []
1095  for plot, title in zip(self._plots, self._titles):
1096  h_tmp = []
1097  l_tmp = []
1098  for h, l in zip(plot._histograms, labels_short):
1099  if h is not None:
1100  h_tmp.append(len(histos_linear))
1101  histos_linear.append(h)
1102  l_tmp.append(l)
1103 
1104  if len(h_tmp) > 0:
1105  histos_index.append(h_tmp)
1106  labels.append(l_tmp)
1107  content.extend([
1108  ' <td></td>',
1109  ' <td colspan="%d">%s</td>' % (len(h_tmp), title),
1110  ])
1111 
1112  if len(histos_linear) == 0:
1113  return []
1114 
1115  content.extend([
1116  ' </tr>',
1117  ' <tr>',
1118  ])
1119 
1120  xbinlabels = plotting._mergeBinLabelsX(histos_linear)
1121  histos_linear = plotting._th1IncludeOnlyBins(histos_linear, xbinlabels)
1122  if len(histos_linear) == 0:
1123  return []
1124  (histos_linear_new, xbinlabels) = plotting._th1RemoveEmptyBins(histos_linear, xbinlabels)
1125  # in practice either all histograms are returned, or none, but let's add a check anyway
1126  if len(histos_linear_new) > 0 and len(histos_linear_new) != len(histos_linear):
1127  raise Exception("This should never happen. len(histos_linear_new) %d != len(histos_linear) %d" % (len(histos_linear_new), len(histos_linear)))
1128  histos_linear = histos_linear_new
1129  if len(histos_linear) == 0:
1130  return []
1131 
1132  data = [ [h.GetBinContent(i) for i in range(1, h.GetNbinsX()+1)] for h in histos_linear]
1133  table = html.Table(["dummy"]*len(histos_linear), xbinlabels, data, None, None, None)
1134  data = table.tableAsRowColumn()
1135 
1136  for labs in labels:
1137  content.append(' <td></td>')
1138  content.extend([' <td>%s</td>' % lab for lab in labs])
1139  content.extend([
1140  ' </tr>',
1141  ])
1142 
1143  for irow, row in enumerate(data):
1144  content.extend([
1145  ' <tr>',
1146  ' <td>%s</td>' % table.rowHeaders()[irow]
1147  ])
1148 
1149  for hindices in histos_index:
1150  for hindex in hindices:
1151  item = row[hindex]
1152  formatted = self._format%item if item is not None else ""
1153  content.append(' <td align="right">%s</td>' % formatted)
1154  content.append(' <td></td>')
1155  del content[-1]
1156  content.append(' </tr>')
1157 
1158  content.append(' </table>')
1159  if haveShortLabels:
1160  for lab in legendLabels:
1161  content.append(' %s<br/>' % lab)
1162 
1163  content.extend([
1164  ' </body>',
1165  '<html>'
1166  ])
1167 
1168  name = self._fileName
1169  if prefix is not None:
1170  name = prefix+name
1171  name += ".html"
1172  name = os.path.join(directory, name)
1173 
1174  with open(name, "w") as f:
1175  for line in content:
1176  f.write(line)
1177  f.write("\n")
1178  return [name]
1179 
1180 _dupandfakeSeedingTable = TrackingSeedingLayerTable("dupandfakeSeeding", [p.clone() for p in _dupandfakeSeedingPlots],
1181  ["Fake rate", "Duplicate rate", "Pileup rate"], isRate=True)
1182 _extDistSeedingTable = TrackingSeedingLayerTable("distSeeding", [p.clone() for p in _extDistSeedingPlots],
1183  ["All tracks", "True tracks", "Fake tracks", "Duplicate tracks"], isRate=False)
1184 
1185 def _trackingFolders(lastDirName="Track"):
1186  return [
1187  "DQMData/Run 1/Tracking/Run summary/"+lastDirName,
1188  "DQMData/Tracking/"+lastDirName,
1189  "DQMData/Run 1/RecoTrackV/Run summary/"+lastDirName,
1190  "DQMData/RecoTrackV/"+lastDirName,
1191  ]
1192 
1193 _simBasedPlots = [
1194  _effandfakePtEtaPhi,
1195  _effandfakeDxyDzBS,
1196  _effandfakeDxyDzPV,
1197  _effandfakeHitsLayers,
1198  _effandfakePos,
1199  _effandfakeDeltaRPU,
1200  _duplicateAlgo,
1201 ]
1202 _recoBasedPlots = [
1203  _dupandfakePtEtaPhi,
1204  _dupandfakeDxyDzBS,
1205  _dupandfakeDxyDzPV,
1206  _dupandfakeHitsLayers,
1207  _dupandfakePos,
1208  _dupandfakeDeltaRPU,
1209  _dupandfakeChi2Seeding,
1210  _dupandfakeSeedingTable,
1211  _pvassociation1,
1212  _pvassociation2,
1213  _dedx,
1214 # _chargemisid,
1215  _hitsAndPt,
1216  _pulls,
1217  _resolutionsEta,
1218  _resolutionsPhi,
1219  _resolutionsPt,
1220  _tuning,
1221 ]
1222 _seedingBuildingPlots = _simBasedPlots + [
1223  _dupandfakePtEtaPhi,
1224  _dupandfakeDxyDzBS,
1225  _dupandfakeDxyDzPV,
1226  _dupandfakeHitsLayers,
1227  _dupandfakePos,
1228  _dupandfakeDeltaRPU,
1229  _dupandfakeChi2Seeding,
1230  _dupandfakeSeedingTable,
1231  _hitsAndPt,
1232 ] + _makeMVAPlots(1) \
1233  + _makeMVAPlots(2) \
1234  + _makeMVAPlots(2, hp=True) \
1235  + _makeMVAPlots(3) \
1236  + _makeMVAPlots(3, hp=True)
1237 # add more if needed
1238 _buildingExtendedPlots = [
1239  _pulls,
1240  _resolutionsEta,
1241  _resolutionsPhi,
1242  _resolutionsPt,
1243  _tuning,
1244 ]
1245 _extendedPlots = [
1246  _extDistPtEtaPhi,
1247  _extDistDxyDzBS,
1248  _extDistDxyDzPV,
1249  _extDistHitsLayers,
1250  _extDistPos,
1251  _extDistDeltaR,
1252  _extDistChi2Seeding,
1253  _extDistSeedingTable,
1254  _extResidualEta,
1255  _extResidualPt,
1256  _extNrecVsNsim,
1257  _extHitsLayers,
1258  _extDistSimPtEtaPhi,
1259  _extDistSimDxyDzBS,
1260  _extDistSimDxyDzPV,
1261  _extDistSimHitsLayers,
1262  _extDistSimPos,
1263  _extDistSimDeltaR,
1264 ]
1265 _summaryPlots = [
1266  _summary,
1267  _summaryN,
1268  _summaryByOriginalAlgo,
1269  _summaryByOriginalAlgoN,
1270  _summaryByAlgoMask,
1271  _summaryByAlgoMaskN,
1272  _summaryPt09,
1273  _summaryPt09N,
1274 ]
1275 _summaryPlotsHp = [
1276  _summaryHp,
1277  _summaryNHp,
1278  _summaryByOriginalAlgoHp,
1279  _summaryByOriginalAlgoNHp,
1280  _summaryByAlgoMaskHp,
1281  _summaryByAlgoMaskNHp,
1282  _summaryPt09Hp,
1283  _summaryPt09NHp,
1284 ]
1285 _summaryPlotsSeeds = [
1286  _summarySeeds,
1287  _summarySeedsN,
1288 ]
1289 _packedCandidatePlots = [
1290  _packedCandidateFlow,
1291  _packedCandidateKinematics,
1292  _packedCandidateVertex,
1293  _packedCandidateImpactParameter1,
1294  _packedCandidateImpactParameter2,
1295  _packedCandidateCovarianceMatrix1,
1296  _packedCandidateCovarianceMatrix2,
1297  _packedCandidateHits,
1298  _packedCandidateHitsHitPattern,
1299  _packedCandidateLayers,
1300 ]
1301 plotter = Plotter()
1302 plotterExt = Plotter()
1303 def _appendTrackingPlots(lastDirName, name, algoPlots, onlyForPileup=False, onlyForElectron=False, onlyForConversion=False, onlyForBHadron=False, seeding=False, building=False, rawSummary=False, highPuritySummary=True):
1304  folders = _trackingFolders(lastDirName)
1305  # to keep backward compatibility, this set of plots has empty name
1306  limiters = dict(onlyForPileup=onlyForPileup, onlyForElectron=onlyForElectron, onlyForConversion=onlyForConversion, onlyForBHadron=onlyForBHadron)
1307  commonForTPF = dict(purpose=PlotPurpose.TrackingIteration, fallbackRefFiles=[
1308  _trackingRefFileFallbackSLHC_Phase1PU140
1309  ], **limiters)
1310  common = dict(fallbackDqmSubFolders=[
1311  _trackingSubFoldersFallbackSLHC_Phase1PU140,
1312  _trackingSubFoldersFallbackFromPV, _trackingSubFoldersFallbackConversion,
1313  _trackingSubFoldersFallbackPreSplitting])
1314  plotter.append(name, folders, TrackingPlotFolder(*algoPlots, **commonForTPF), **common)
1315  extendedPlots = []
1316  if building:
1317  extendedPlots.extend(_buildingExtendedPlots)
1318  extendedPlots.extend(_extendedPlots)
1319  plotterExt.append(name, folders, TrackingPlotFolder(*extendedPlots, **commonForTPF), **common)
1320 
1321  summaryName = ""
1322  if name != "":
1323  summaryName += name+"_"
1324  summaryName += "summary"
1325  summaryPlots = []
1326  if rawSummary:
1327  summaryPlots.extend([_summaryRaw, _summaryRawN])
1328  summaryPlots.extend(_summaryPlots)
1329 
1330  common = dict(loopSubFolders=False, purpose=PlotPurpose.TrackingSummary, page="summary",
1331  #numberOfEventsHistogram=_trackingNumberOfEventsHistogram, # FIXME
1332  **limiters)
1333  plotter.append(summaryName, folders,
1334  PlotFolder(*summaryPlots, section=name, **common))
1335  if highPuritySummary:
1336  plotter.append(summaryName+"_highPurity", folders,
1337  PlotFolder(*_summaryPlotsHp, section=name+"_highPurity" if name != "" else "highPurity", **common),
1338  fallbackNames=[summaryName]) # backward compatibility for release validation, the HP plots used to be in the same directory with all-track plots
1339  if seeding:
1340  plotter.append(summaryName+"_seeds", folders,
1341  PlotFolder(*_summaryPlotsSeeds, section=name+"_seeds", **common))
1342 
1343  plotter.appendTable(summaryName, folders, TrackingSummaryTable(section=name))
1344  plotter.appendTable(summaryName, folders, TrackingSummaryTable(section=name+"Pt09", collection=TrackingSummaryTable.GeneralTracksPt09))
1345  if highPuritySummary:
1346  sectionName = name+"_highPurity" if name != "" else "highPurity"
1347  plotter.appendTable(summaryName+"_highPurity", folders, TrackingSummaryTable(section=sectionName, collection=TrackingSummaryTable.HighPurity))
1348  plotter.appendTable(summaryName+"_highPurity", folders, TrackingSummaryTable(section=sectionName+"Pt09", collection=TrackingSummaryTable.HighPurityPt09))
1349  if name == "":
1350  plotter.appendTable(summaryName, folders, TrackingSummaryTable(section="btvLike", collection=TrackingSummaryTable.BTVLike))
1351  plotter.appendTable(summaryName, folders, TrackingSummaryTable(section="ak4PFJets", collection=TrackingSummaryTable.AK4PFJets))
1352 _appendTrackingPlots("Track", "", _simBasedPlots+_recoBasedPlots)
1353 _appendTrackingPlots("TrackTPPtLess09", "tpPtLess09", _simBasedPlots)
1354 _appendTrackingPlots("TrackTPEtaGreater2p7", "tpEtaGreater2p7", _simBasedPlots+_recoBasedPlots)
1355 _appendTrackingPlots("TrackAllTPEffic", "allTPEffic", _simBasedPlots, onlyForPileup=True)
1356 _appendTrackingPlots("TrackFromPV", "fromPV", _simBasedPlots+_recoBasedPlots, onlyForPileup=True)
1357 _appendTrackingPlots("TrackFromPVAllTP", "fromPVAllTP", _simBasedPlots+_recoBasedPlots, onlyForPileup=True)
1358 _appendTrackingPlots("TrackFromPVAllTP2", "fromPVAllTP2", _simBasedPlots+_recoBasedPlots, onlyForPileup=True)
1359 _appendTrackingPlots("TrackSeeding", "seeding", _seedingBuildingPlots, seeding=True)
1360 _appendTrackingPlots("TrackBuilding", "building", _seedingBuildingPlots, building=True)
1361 _appendTrackingPlots("TrackConversion", "conversion", _simBasedPlots+_recoBasedPlots, onlyForConversion=True, rawSummary=True, highPuritySummary=False)
1362 _appendTrackingPlots("TrackGsf", "gsf", _simBasedPlots+_recoBasedPlots, onlyForElectron=True, rawSummary=True, highPuritySummary=False)
1363 _appendTrackingPlots("TrackBHadron", "bhadron", _simBasedPlots+_recoBasedPlots, onlyForBHadron=True)
1364 _appendTrackingPlots("TrackDisplaced", "displaced", _simBasedPlots+_recoBasedPlots)
1365 # Pixel tracks
1366 def _appendPixelTrackingPlots(lastDirName, name):
1367  _common = dict(purpose=PlotPurpose.Pixel, page="pixel")
1368  _folders = _trackingFolders(lastDirName)
1369 
1370  plotter.append(name, _folders, TrackingPlotFolder(*(_simBasedPlots+_recoBasedPlots), **_common))
1371  plotterExt.append(name, _folders, TrackingPlotFolder(*_extendedPlots, **_common))
1372 
1373  plotter.append(name+"_summary", _folders, PlotFolder(_summaryRaw, _summaryRawN, loopSubFolders=False, purpose=PlotPurpose.TrackingSummary, page="summary", section=name))
1374  plotter.append(name+"_summary", _folders, PlotFolder(_summaryRaw, _summaryRawN, loopSubFolders=False, purpose=PlotPurpose.TrackingSummary, page="summary", section=name+"Pt09"))
1375  plotter.appendTable(name+"_summary", _folders, TrackingSummaryTable(section=name, collection=TrackingSummaryTable.Pixel))
1376  plotter.appendTable(name+"_summary", _folders, TrackingSummaryTable(section=name+"Pt09", collection=TrackingSummaryTable.PixelPt09))
1377 _appendPixelTrackingPlots("PixelTrack", "pixel")
1378 _appendPixelTrackingPlots("PixelTrackFromPV", "pixelFromPV")
1379 _appendPixelTrackingPlots("PixelTrackFromPVAllTP", "pixelFromPVAllTP")
1380 _appendPixelTrackingPlots("PixelTrackBHadron", "pixelbhadron")
1381 _appendPixelTrackingPlots("HIPixelTrack", "hiPixel")
1382 
1383 # MiniAOD
1384 plotter.append("packedCandidate", _trackingFolders("PackedCandidate"),
1385  PlotFolder(*_packedCandidatePlots, loopSubFolders=False,
1386  purpose=PlotPurpose.MiniAOD, page="miniaod", section="PackedCandidate"))
1387 plotter.append("packedCandidateLostTracks", _trackingFolders("PackedCandidate/lostTracks"),
1388  PlotFolder(*_packedCandidatePlots, loopSubFolders=False,
1389  purpose=PlotPurpose.MiniAOD, page="miniaod", section="PackedCandidate (lostTracks)"))
1390 
1391 # HLT
1392 _hltFolder = [
1393  "DQMData/Run 1/HLT/Run summary/Tracking/ValidationWRTtp",
1394 ]
1395 plotterHLT = Plotter()
1396 plotterHLTExt = Plotter()
1397 _common = dict(purpose=PlotPurpose.HLT, page="hlt")
1398 plotterHLT.append("hlt", _hltFolder, TrackingPlotFolder(*(_simBasedPlots+_recoBasedPlots), **_common))
1399 plotterHLTExt.append("hlt", _hltFolder, TrackingPlotFolder(*_extendedPlots, **_common))
1400 
1401 # Timing
1402 class Iteration:
1403  def __init__(self, name, clusterMasking=None, seeding=None, building=None, fit=None, selection=None, other=[]):
1404  self._name = name
1405 
1406  def _set(param, name, modules):
1407  if param is not None:
1408  setattr(self, name, param)
1409  else:
1410  setattr(self, name, modules)
1411 
1412  _set(clusterMasking, "_clusterMasking", [self._name+"Clusters"])
1413  # it's fine to include e.g. quadruplets here also for pair
1414  # steps, as non-existing modules are just ignored
1415  _set(seeding, "_seeding", [self._name+"SeedingLayers", self._name+"TrackingRegions", self._name+"HitDoublets", self._name+"HitTriplets", self._name+"HitQuadruplets", self._name+"Seeds"])
1416  trackCandidates = self._name+"TrackCandidates"
1417  _set(building, "_building", [trackCandidates+"MkFitSeeds", trackCandidates+"MkFit", trackCandidates])
1418  _set(fit, "_fit", [self._name+"Tracks"])
1419  _set(selection, "_selection", [self._name])
1420  self._other = other
1421 
1422  def name(self):
1423  return self._name
1424 
1425  def all(self):
1426  return self._clusterMasking+self._seeding+self._building+self._fit+self._selection+self._other
1427 
1428  def clusterMasking(self):
1429  return self._clusterMasking
1430 
1431  def seeding(self):
1432  return self._seeding
1433 
1434  def building(self):
1435  return self._building
1436 
1437  def fit(self):
1438  return self._fit
1439 
1440  def selection(self):
1441  return self._selection
1442 
1443  def other(self):
1444  return self._other
1445 
1446  def modules(self):
1447  return [("ClusterMask", self.clusterMasking()),
1448  ("Seeding", self.seeding()),
1449  ("Building", self.building()),
1450  ("Fit", self.fit()),
1451  ("Selection", self.selection()),
1452  ("Other", self.other())]
1453 
1454 
1455 _iterations = [
1456  Iteration("initialStepPreSplitting", clusterMasking=[],
1457  seeding=["initialStepSeedLayersPreSplitting",
1458  "initialStepTrackingRegionsPreSplitting",
1459  "initialStepHitDoubletsPreSplitting",
1460  "initialStepHitTripletsPreSplitting",
1461  "initialStepHitQuadrupletsPreSplitting",
1462  "initialStepSeedsPreSplitting"],
1463  building=["initialStepTrackCandidatesPreSplitting",
1464  "initialStepTrackCandidatesMkFitSeedsPreSplitting",
1465  "initialStepTrackCandidatesMkFitPreSplitting"],
1466  fit=["initialStepTracksPreSplitting"],
1467  other=["firstStepPrimaryVerticesPreSplitting",
1468  "initialStepTrackRefsForJetsPreSplitting",
1469  "caloTowerForTrkPreSplitting",
1470  "ak4CaloJetsForTrkPreSplitting",
1471  "jetsForCoreTrackingPreSplitting",
1472  "siPixelClusters",
1473  "siPixelRecHits",
1474  "MeasurementTrackerEvent",
1475  "siPixelClusterShapeCache",
1476  "mkFitSiPixelHitsPreSplitting",
1477  "mkFitSiStripHits",
1478  "mkFitEventOfHitsPreSplitting"]),
1479  Iteration("initialStep", clusterMasking=[],
1480  selection=["initialStepClassifier1",
1481  "initialStepClassifier2",
1482  "initialStepClassifier3",
1483  "initialStep",
1484  "initialStepSelector"],
1485  other=["firstStepPrimaryVerticesUnsorted",
1486  "initialStepTrackRefsForJets",
1487  "caloTowerForTrk",
1488  "ak4CaloJetsForTrk",
1489  "firstStepPrimaryVertices",
1490  "mkFitSiPixelHits",
1491  "mkFitEventOfHits"]),
1492  Iteration("highPtTripletStep",
1493  selection=["highPtTripletStepClassifier1",
1494  "highPtTripletStepClassifier2",
1495  "highPtTripletStepClassifier3",
1496  "highPtTripletStep",
1497  "highPtTripletStepSelector"]),
1498  Iteration("detachedQuadStep",
1499  selection=["detachedQuadStepClassifier1",
1500  "detachedQuadStepClassifier2",
1501  "detachedQuadStep",
1502  "detachedQuadStepSelector"]),
1503  Iteration("detachedTripletStep",
1504  selection=["detachedTripletStepClassifier1",
1505  "detachedTripletStepClassifier2",
1506  "detachedTripletStep",
1507  "detachedTripletStepSelector"]),
1508  Iteration("lowPtQuadStep",
1509  selection=["lowPtQuadStepClassifier1",
1510  "lowPtQuadStepClassifier2",
1511  "lowPtQuadStep",
1512  "lowPtQuadStepSelector"]),
1513  Iteration("lowPtTripletStep",
1514  selection=["lowPtTripletStepClassifier1",
1515  "lowPtTripletStepClassifier2",
1516  "lowPtTripletStep",
1517  "lowPtTripletStepSelector"]),
1518  Iteration("pixelPairStep",
1519  seeding=["pixelPairStepSeedLayers",
1520  "pixelPairStepSeedLayersB",
1521  "pixelPairStepSeedLayersC",
1522  "pixelPairStepTrackingRegions",
1523  "pixelPairStepTrackingRegionsB",
1524  "pixelPairStepTrackingRegionsC",
1525  "pixelPairStepTrackingRegionsSeedLayersB",
1526  "pixelPairStepHitDoublets",
1527  "pixelPairStepHitDoubletsB",
1528  "pixelPairStepHitDoubletsC",
1529  "pixelPairStepSeedsA",
1530  "pixelPairStepSeedsB",
1531  "pixelPairStepSeedsC",
1532  "pixelPairStepSeeds",],
1533  selection=["pixelPairStep",
1534  "pixelPairStepSelector"]),
1535  Iteration("mixedTripletStep",
1536  seeding=["mixedTripletStepSeedLayersA",
1537  "mixedTripletStepSeedLayersB",
1538  "mixedTripletStepTrackingRegionsA",
1539  "mixedTripletStepTrackingRegionsB",
1540  "mixedTripletStepHitDoubletsA",
1541  "mixedTripletStepHitDoubletsB",
1542  "mixedTripletStepHitTripletsA",
1543  "mixedTripletStepHitTripletsB",
1544  "mixedTripletStepSeedsA",
1545  "mixedTripletStepSeedsB",
1546  "mixedTripletStepSeeds"],
1547  selection=["mixedTripletStepClassifier1",
1548  "mixedTripletStepClassifier2",
1549  "mixedTripletStep",
1550  "mixedTripletStepSelector"]),
1551  Iteration("pixelLessStep",
1552  selection=["pixelLessStepClassifier1",
1553  "pixelLessStepClassifier2",
1554  "pixelLessStep",
1555  "pixelLessStepSelector"]),
1556  Iteration("tobTecStep",
1557  seeding=["tobTecStepSeedLayersTripl",
1558  "tobTecStepSeedLayersPair",
1559  "tobTecStepTrackingRegionsTripl",
1560  "tobTecStepTrackingRegionsPair",
1561  "tobTecStepHitDoubletsTripl",
1562  "tobTecStepHitDoubletsPair",
1563  "tobTecStepHitTripletsTripl",
1564  "tobTecStepSeedsTripl",
1565  "tobTecStepSeedsPair",
1566  "tobTecStepSeeds"],
1567  selection=["tobTecStepClassifier1",
1568  "tobTecStepClassifier2",
1569  "tobTecStep",
1570  "tobTecStepSelector"]),
1571  Iteration("displacedGeneralStep",
1572  seeding=["displacedGeneralStepSeedLayers",
1573  "displacedGeneralStepTrackingRegions",
1574  "displacedGeneralStepHitDoublets",
1575  "displacedGeneralStepHitTriplets",
1576  "displacedGeneralStepSeeds"],
1577  selection=["displacedGeneralStepClassifier1",
1578  "displacedGeneralStepClassifier2",
1579  "displacedGeneralStep",
1580  "displacedGeneralStepSelector"]),
1581  Iteration("jetCoreRegionalStep",
1582  clusterMasking=[],
1583  other=["jetsForCoreTracking",
1584  "firstStepGoodPrimaryVertices",
1585  ]),
1586  Iteration("muonSeededSteps",
1587  clusterMasking=[],
1588  seeding=["muonSeededSeedsInOut",
1589  "muonSeededSeedsOutIn"],
1590  building=["muonSeededTrackCandidatesInOut",
1591  "muonSeededTrackCandidatesOutIn"],
1592  fit=["muonSeededTracksInOut",
1593  "muonSeededTracksOutIn"],
1594  selection=["muonSeededTracksInOutClassifier",
1595  "muonSeededTracksInOutSelector",
1596  "muonSeededTracksOutIntClassifier",
1597  "muonSeededTracksOutIntSelector"],
1598 # other=["earlyMuons"]
1599  ),
1600  Iteration("displacedRegionalStep",
1601  seeding=["displacedRegionalStepSeedLayersTripl",
1602  "displacedRegionalStepSeedLayersPair",
1603  "displacedRegionalStepTrackingRegionsTripl",
1604  "displacedRegionalStepTrackingRegionsPair",
1605  "displacedRegionalStepHitDoubletsTripl",
1606  "displacedRegionalStepHitDoubletsPair",
1607  "displacedRegionalStepHitTripletsTripl",
1608  "displacedRegionalStepSeedsTripl",
1609  "displacedRegionalStepSeedsPair",
1610  "displacedRegionalStepSeeds"],
1611  selection=["displacedRegionalStepClassifier1",
1612  "displacedRegionalStepClassifier2",
1613  "displacedRegionalStep",
1614  "displacedRegionalStepSelector"]),
1615  Iteration("duplicateMerge",
1616  clusterMasking=[], seeding=[],
1617  building=["duplicateTrackCandidates"],
1618  fit=["mergedDuplicateTracks"],
1619  selection=["duplicateTrackClassifier"]),
1620  Iteration("generalTracks",
1621  clusterMasking=[], seeding=[], building=[], fit=[], selection=[],
1622  other=["preDuplicateMergingGeneralTracks",
1623  "generalTracks"]),
1624  Iteration("ConvStep",
1625  clusterMasking=["convClusters"],
1626  seeding=["convLayerPairs",
1627  "photonConvTrajSeedFromSingleLeg"],
1628  building=["convTrackCandidates"],
1629  fit=["convStepTracks"],
1630  selection=["convStepSelector"]),
1631  Iteration("Other", clusterMasking=[], seeding=[], building=[], fit=[], selection=[],
1632  other=["trackerClusterCheckPreSplitting",
1633  "trackerClusterCheck"]),
1634 ]
1635 
1636 def _iterModuleMap(includeConvStep=True, onlyConvStep=False):
1637  iterations = _iterations
1638  if not includeConvStep:
1639  iterations = [i for i in iterations if i.name() != "ConvStep"]
1640  if onlyConvStep:
1641  iterations = [i for i in iterations if i.name() == "ConvStep"]
1642  return collections.OrderedDict([(i.name(), i.all()) for i in iterations])
1643 def _stepModuleMap():
1644  def getProp(prop):
1645  ret = []
1646  for i in _iterations:
1647  if i.name() == "ConvStep":
1648  continue
1649  ret.extend(getattr(i, prop)())
1650  return ret
1651 
1652  return collections.OrderedDict([
1653  ("ClusterMask", getProp("clusterMasking")),
1654  ("Seeding", getProp("seeding")),
1655  ("Building", getProp("building")),
1656  ("Fitting", getProp("fit")),
1657  ("Selection", getProp("selection")),
1658  ("Other", getProp("other"))
1659  ])
1660 
1661 class TimePerEventPlot:
1662  def __init__(self, name, timeHisto):
1663  self._name = name
1664  self._timeHisto = timeHisto
1665  self._eventsHisto = "path time_real"
1666  self._cache = {}
1667 
1668  def __str__(self):
1669  return self._name
1670 
1671  def _create(self, tdirectory):
1672  timeTh1 = plotting._getOrCreateObject(tdirectory, self._timeHisto)
1673  if timeTh1 is None:
1674  return None
1675 
1676  eventsTh1 = plotting._getOrCreateObject(tdirectory, self._eventsHisto)
1677  if eventsTh1 is None:
1678  return None
1679  nevents = eventsTh1.GetEntries()
1680  if nevents == 0:
1681  return None
1682 
1683  ret = timeTh1.Clone(self._name)
1684  xaxis = ret.GetXaxis()
1685  for i in range(1, ret.GetNbinsX()+1):
1686  ret.SetBinContent(i, ret.GetBinContent(i)/nevents)
1687  ret.SetBinError(i, ret.GetBinError(i)/nevents)
1688  xaxis.SetBinLabel(i, xaxis.GetBinLabel(i).replace(" (unscheduled)", ""))
1689  return ret
1690 
1691  def create(self, tdirectory):
1692  path = tdirectory.GetPath()
1693  if path not in self._cache:
1694  self._cache[path] = self._create(tdirectory)
1695  return self._cache[path]
1696 
1697 class TimePerTrackPlot:
1698  def __init__(self, name, timeHisto, selectedTracks=False):
1699  self._name = name
1700  self._timeHisto = timeHisto
1701  self._selectedTracks = selectedTracks
1702 
1703  def __str__(self):
1704  return self._name
1705 
1706  def _getDirectory(self, tfile):
1707  for dirName in _trackingFolders():
1708  tdir = tfile.Get(dirName)
1709  if tdir != None:
1710  return tdir
1711  return None
1712 
1713  def create(self, tdirectory):
1714  timeTh1 = plotting._getOrCreateObject(tdirectory, self._timeHisto)
1715  if timeTh1 is None:
1716  return None
1717 
1718  # this is bit of a hack, but as long as it is needed only
1719  # here, I won't invest in better solution
1720  tfile = tdirectory.GetFile()
1721  trkDir = self._getDirectory(tfile)
1722  if trkDir is None:
1723  return None
1724 
1725  iterMap = copy.copy(_collLabelMapHp)
1726  del iterMap["generalTracks"]
1727  del iterMap["jetCoreRegionalStep"] # this is expensive per track on purpose
1728  if self._selectedTracks:
1729  renameBin = lambda bl: _summaryBinRename(bl, highPurity=True, byOriginalAlgo=False, byAlgoMask=True, ptCut=False, seeds=False)
1730  else:
1731  renameBin = lambda bl: _summaryBinRename(bl, highPurity=False, byOriginalAlgo=False, byAlgoMask=False, ptCut=False, seeds=False)
1732  recoAB = AggregateBins("tmp", "num_reco_coll", mapping=iterMap,ignoreMissingBins=True, renameBin=renameBin)
1733  h_reco_per_iter = recoAB.create(trkDir)
1734  if h_reco_per_iter is None:
1735  return None
1736  values = {}
1737  for i in range(1, h_reco_per_iter.GetNbinsX()+1):
1738  values[h_reco_per_iter.GetXaxis().GetBinLabel(i)] = h_reco_per_iter.GetBinContent(i)
1739 
1740 
1741  result = []
1742  for i in range(1, timeTh1.GetNbinsX()+1):
1743  iterName = timeTh1.GetXaxis().GetBinLabel(i)
1744  if iterName in values:
1745  ntrk = values[iterName]
1746  result.append( (iterName,
1747  timeTh1.GetBinContent(i)/ntrk if ntrk > 0 else 0,
1748  timeTh1.GetBinError(i)/ntrk if ntrk > 0 else 0) )
1749 
1750  if len(result) == 0:
1751  return None
1752 
1753  res = ROOT.TH1F(self._name, self._name, len(result), 0, len(result))
1754  for i, (label, value, error) in enumerate(result):
1755  res.GetXaxis().SetBinLabel(i+1, label)
1756  res.SetBinContent(i+1, value)
1757  res.SetBinError(i+1, error)
1758 
1759  return res
1760 
1761 class TrackingIterationOrder:
1762  def __init__(self):
1763  self._cache = {}
1764 
1765  def _findOrder(self, f):
1766  h = f.Get(_trackingIterationOrderHistogram)
1767  if not h:
1768  return None
1769  xaxis = h.GetXaxis()
1770  def _edit(s):
1771  # remove "Tracks" from the track producer name to get the iteration name
1772  # muonSeeded iterations do not have "Step" in the producer name, so add it here
1773  return s.replace("Tracks", "").replace("muonSeeded", "muonSeededStep")
1774  return [_edit(xaxis.GetBinLabel(i)) for i in range(1, h.GetNbinsX()+1)]
1775 
1776  def __call__(self, tdirectory, labels):
1777  ret = list(range(0, len(labels)))
1778  f = tdirectory.GetFile()
1779  if not f:
1780  return ret
1781 
1782  if not f.GetName() in self._cache:
1783  r = self._findOrder(f)
1784  if r is None:
1785  return ret
1786  self._cache[f.GetName()] = r
1787  order = self._cache[f.GetName()]
1788 
1789  # O(N^2) I know, but we're talking about O(10) elements...
1790  orderIndices = []
1791  for l in order:
1792  try:
1793  orderIndices.append(labels.index(l))
1794  except ValueError:
1795  pass
1796  ret = []
1797  for i, l in enumerate(labels):
1798  if l in order:
1799  try:
1800  found = orderIndices.index(i)
1801  if found == 0:
1802  ret.append(i)
1803  else:
1804  ret.append(orderIndices[0])
1805  except ValueError:
1806  ret.append(orderIndices[0])
1807  orderIndices.pop(0)
1808  else:
1809  ret.append(i)
1810  return ret
1811 
1812 _time_per_event_cpu = TimePerEventPlot("timePerEvent", "module_time_thread_total")
1813 _time_per_event_real = TimePerEventPlot("timePerEvent", "module_time_real_total")
1814 
1815 class TrackingTimingTable:
1816  def __init__(self):
1817  self._purpose = PlotPurpose.Timing
1818  self._page = "timing"
1819  self._section = "timing"
1820 
1821  def getPurpose(self):
1822  return self._purpose
1823 
1824  def getPage(self):
1825  return self._page
1826 
1827  def getSection(self, dqmSubFolder):
1828  return self._section
1829 
1830  def _getValues(self, tdirectory, histo):
1831  h = tdirectory.Get(histo._timeHisto)
1832  totalReco = None
1833  if h:
1834  totalReco = "%.1f" % h.Integral()
1835 
1836  creator = AggregateBins("iteration", histo, _iterModuleMap(includeConvStep=False), ignoreMissingBins=True)
1837  h = creator.create(tdirectory)
1838  totalTracking = None
1839  if h:
1840  totalTracking = "%.1f" % h.Integral()
1841 
1842  creator = AggregateBins("iteration", histo, _iterModuleMap(onlyConvStep=True), ignoreMissingBins=True)
1843  h = creator.create(tdirectory)
1844  totalConvStep = None
1845  if h:
1846  totalConvStep = "%.1f" % h.Integral()
1847 
1848  return [
1849  totalReco,
1850  totalTracking,
1851  totalConvStep,
1852  ]
1853 
1854  def create(self, tdirectory):
1855  cpuValues = self._getValues(tdirectory, _time_per_event_cpu)
1856  realValues = self._getValues(tdirectory, _time_per_event_real)
1857 
1858  return cpuValues + realValues
1859 
1860  def headers(self):
1861  return [
1862  "Average reco CPU time / event (ms)",
1863  "Average tracking (w/o convStep) CPU time / event (ms)",
1864  "Average convStep CPU time / event (ms)",
1865  "Average reco real time / event (ms)",
1866  "Average tracking (w/o convStep) real time / event (ms)",
1867  "Average convStep real time / event (ms)",
1868  ]
1869 
1870 _common = {
1871  "drawStyle": "P",
1872  "xbinlabelsize": 10,
1873  "xbinlabeloption": "d"
1874 }
1875 
1876 _iteration_reorder = TrackingIterationOrder()
1877 _time_per_iter_cpu = AggregateBins("iteration", _time_per_event_cpu, _iterModuleMap(), ignoreMissingBins=True, reorder=_iteration_reorder)
1878 _time_per_iter_real = AggregateBins("iteration", _time_per_event_real, _iterModuleMap(), ignoreMissingBins=True, reorder=_iteration_reorder)
1879 
1880 _timing_summaryCPU = PlotGroup("summaryCPU", [
1881  Plot(_time_per_iter_cpu,
1882  ytitle="Average CPU time (ms)", title="Average CPU time / event", legendDx=-0.4, **_common),
1883  Plot(AggregateBins("iteration_fraction", _time_per_event_cpu, _iterModuleMap(), ignoreMissingBins=True, reorder=_iteration_reorder),
1884  ytitle="Fraction", title="", normalizeToUnitArea=True, **_common),
1885  #
1886  Plot(AggregateBins("step", _time_per_event_cpu, _stepModuleMap(), ignoreMissingBins=True),
1887  ytitle="Average CPU time (ms)", title="Average CPU time / event", **_common),
1888  Plot(AggregateBins("step_fraction", _time_per_event_cpu, _stepModuleMap(), ignoreMissingBins=True),
1889  ytitle="Fraction", title="", normalizeToUnitArea=True, **_common),
1890  #
1891  Plot(TimePerTrackPlot("iteration_track", _time_per_iter_cpu, selectedTracks=False),
1892  ytitle="Average CPU time / built track (ms)", title="Average CPU time / built track", **_common),
1893  Plot(TimePerTrackPlot("iteration_trackhp", _time_per_iter_cpu, selectedTracks=True),
1894  ytitle="Average CPU time / selected track (ms)", title="Average CPU time / selected HP track by algoMask", **_common),
1895  ],
1896 )
1897 _timing_summaryReal = PlotGroup("summaryReal", [
1898  Plot(_time_per_iter_real,
1899  ytitle="Average real time (ms)", title="Average real time / event", legendDx=-0.4, **_common),
1900  Plot(AggregateBins("iteration_fraction", _time_per_event_real, _iterModuleMap(), ignoreMissingBins=True, reorder=_iteration_reorder),
1901  ytitle="Fraction", title="", normalizeToUnitArea=True, **_common),
1902  #
1903  Plot(AggregateBins("step", _time_per_event_real, _stepModuleMap(), ignoreMissingBins=True),
1904  ytitle="Average real time (ms)", title="Average real time / event", **_common),
1905  Plot(AggregateBins("step_fraction", _time_per_event_real, _stepModuleMap(), ignoreMissingBins=True),
1906  ytitle="Fraction", title="", normalizeToUnitArea=True, **_common),
1907  #
1908  Plot(TimePerTrackPlot("iteration_track", _time_per_iter_real, selectedTracks=False),
1909  ytitle="Average real time / built track (ms)", title="Average real time / built track", **_common),
1910  Plot(TimePerTrackPlot("iteration_trackhp", _time_per_iter_real, selectedTracks=True),
1911  ytitle="Average real time / selected track (ms)", title="Average real time / selected HP track by algoMask", **_common),
1912  ],
1913 )
1914 
1915 _timing_iterationsCPU = PlotGroup("iterationsCPU", [
1916  Plot(AggregateBins(i.name(), _time_per_event_cpu, collections.OrderedDict(i.modules()), ignoreMissingBins=True),
1917  ytitle="Average CPU time (ms)", title=i.name(), **_common)
1918  for i in _iterations
1919 ],
1920  ncols=4, legend=False
1921 )
1922 _timing_iterationsReal = PlotGroup("iterationsReal", [
1923  Plot(AggregateBins(i.name(), _time_per_event_real, collections.OrderedDict(i.modules()), ignoreMissingBins=True),
1924  ytitle="Average real time (ms)", title=i.name(), **_common)
1925  for i in _iterations
1926 ],
1927  ncols=4, legend=False
1928 )
1929 
1930 # TODO: to be updated to new FastTimerService format later
1931 #_pixelTiming = PlotGroup("pixelTiming", [
1932 # Plot(AggregateBins("pixel", "reconstruction_step_module_average", {"pixelTracks": ["pixelTracks"]}), ytitle="Average processing time [ms]", title="Average processing time / event", drawStyle="HIST")
1933 #])
1934 
1935 _timeFolders = [
1936 # "DQMData/Run 1/DQM/Run summary/TimerService/process RECO paths/path reconstruction_step",
1937  "DQMData/Run 1/DQM/Run summary/TimerService/process RECO paths/path prevalidation_step", # because of unscheduled, it's actually prevalidation_step that has all the tracking modules?
1938 ]
1939 timePlotter = Plotter()
1940 timePlotter.append("timing", _timeFolders, PlotFolder(
1941  _timing_summaryCPU,
1942  _timing_iterationsCPU,
1943  _timing_summaryReal,
1944  _timing_iterationsReal,
1945  # _pixelTiming,
1946  loopSubFolders=False, purpose=PlotPurpose.Timing, page="timing"
1947 ))
1948 timePlotter.appendTable("timing", _timeFolders, TrackingTimingTable())
1949 
1950 _common = {"stat": True, "normalizeToUnitArea": True, "drawStyle": "hist"}
1951 _tplifetime = PlotGroup("tplifetime", [
1952  Plot("TPlip", xtitle="TP lip", **_common),
1953  Plot("TPtip", xtitle="TP tip", **_common),
1954 ])
1955 
1956 tpPlotter = Plotter()
1957 tpPlotter.append("tp", [
1958  "DQMData/Run 1/Tracking/Run summary/TrackingMCTruth/TrackingParticle",
1959  "DQMData/Tracking/TrackingMCTruth/TrackingParticle",
1960 ], PlotFolder(
1961  _tplifetime,
1962 ))
EcalMonitorTask_cff.func
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Definition: EcalMonitorTask_cff.py:10
trackingPlots.TrackingPlotFolder.iterSelectionName
def iterSelectionName(self, plotFolderName, translatedDqmSubFolder)
Definition: trackingPlots.py:911
trackingPlots.TrackingSummaryTable.getSection
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Definition: trackingPlots.py:962
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def _makeFakeDist(postfix)
Definition: trackingPlots.py:104
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def _makeFakeDupPileupPlots(postfix, quantity, unit="", xquantity="", xtitle=None, common={})
Definition: trackingPlots.py:86
trackingPlots.TimePerEventPlot.__init__
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Definition: trackingPlots.py:1662
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def _getOrCreateObject(tdirectory, nameOrCreator)
Definition: plotting.py:57
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Definition: trackingPlots.py:1636
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Definition: root2matplotlib.py:444
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Definition: trackingPlots.py:121
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Definition: trackingPlots.py:1827
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Definition: trackingPlots.py:1691
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Definition: trackingPlots.py:658
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def _trackingSubFoldersFallbackPreSplitting(subfolder)
Definition: trackingPlots.py:580
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def translateSubFolder(self, dqmSubFolderName)
Definition: trackingPlots.py:904
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def _collhelper(name)
Definition: trackingPlots.py:654
trackingPlots._mapCollectionToAlgoQuality
def _mapCollectionToAlgoQuality(collName)
Definition: trackingPlots.py:590
trackingPlots.TrackingSummaryTable.__init__
def __init__(self, section, collection=GeneralTracks)
Definition: trackingPlots.py:950
trackingPlots.TrackingPlotFolder.__init__
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Definition: trackingPlots.py:900
trackingPlots._minMaxResidual
def _minMaxResidual(ma)
Definition: trackingPlots.py:45
ComparisonHelper::zip
OutputIterator zip(InputIterator1 first1, InputIterator1 last1, InputIterator2 first2, InputIterator2 last2, OutputIterator result, Compare comp)
Definition: L1TStage2CaloLayer1.h:41
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def create(self, tdirectoryNEvents, requireAllHistograms=False)
Definition: trackingPlots.py:1059
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def _trackingSubFoldersFallbackConversion(subfolder)
Definition: trackingPlots.py:578
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def __call__(self, tdirectory, labels)
Definition: trackingPlots.py:1776
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Definition: trackingPlots.py:1303
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def _trackingSubFoldersFallbackSLHC_Phase1PU140(subfolder)
Definition: trackingPlots.py:550
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Definition: genParticles_cff.py:11
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def limitSubFolder(self, limitOnlyTo, translatedDqmSubFolder)
Definition: trackingPlots.py:926
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Definition: trackingPlots.py:1698
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def _makeMVAPlots(num, hp=False)
Definition: trackingPlots.py:133
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def _trackingRefFileFallbackSLHC_Phase1PU140(path)
Definition: trackingPlots.py:564
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def _th1RemoveEmptyBins(histos, xbinlabels)
Definition: plotting.py:607
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Definition: FastTimerService_cff.py:34
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def _appendPixelTrackingPlots(lastDirName, name)
Definition: trackingPlots.py:1366
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def _constructSummary(mapping=None, highPurity=False, byOriginalAlgo=False, byAlgoMask=False, ptCut=False, seeds=False, midfix="")
Definition: trackingPlots.py:693
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Definition: trackingPlots.py:576
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Definition: trackingPlots.py:107
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Definition: trackingPlots.py:1041
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Definition: trackingPlots.py:1671
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Definition: trackingPlots.py:1713
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Definition: trackingPlots.py:1403
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Definition: trackingPlots.py:67
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Definition: plotting.py:100
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Definition: trackingPlots.py:1064
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def _mergeBinLabelsX(histos)
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