def makeOverlaidPlot():
REFLIST = (('2Mu2J', (1000, 20, 2)), ('2Mu2J', (200, 50, 200)))
key = 'Dim_deltaPhi_Matched'
h = {
REFLIST[0]: HISTS[REFLIST[0]][key].Clone(),
REFLIST[1]: HISTS[REFLIST[1]][key].Clone(),
}
p = {}
for ref in h:
RT.addFlows(h[ref])
if h[ref].GetNbinsX() > 100: h[ref].Rebin(10)
p[ref] = Plotter.Plot(h[ref], '2#mu2j ({}, {}, {})'.format(*ref[1]),
'l', 'hist')
fname = 'pdfs/{}{}_Overlaid.pdf'.format(key, CUTSTRING)
canvas = Plotter.Canvas()
canvas.addMainPlot(p[REFLIST[1]])
canvas.addMainPlot(p[REFLIST[0]])
canvas.makeLegend(lWidth=.25, pos='tl')
#canvas.legend.moveLegend(Y=-.3)
canvas.legend.resizeHeight()
p[REFLIST[1]].SetLineColor(R.kBlue)
p[REFLIST[0]].SetLineColor(R.kRed)
RT.addBinWidth(canvas.firstPlot)
pave1 = canvas.makeStatsBox(p[REFLIST[1]], color=R.kBlue)
pave2 = canvas.makeStatsBox(p[REFLIST[0]], color=R.kRed)
Plotter.MOVE_OBJECT(pave2, Y=-.22, NDC=False)
canvas.cleanup(fname)
def makeSignalPlot(hkey):
HISTS = HG.getAddedSignalHistograms(FILES['2Mu2J'], '2Mu2J', hkey)
h = HISTS[hkey]
p = Plotter.Plot(h, '', '', 'hist')
canvas = Plotter.Canvas(lumi='Signal: H#rightarrow2X#rightarrow2#mu + *',
logy=True if hkey != 'nDTHits' else False)
canvas.addMainPlot(p)
p.SetLineColor(R.kBlue)
canvas.firstPlot.SetMinimum(0.9)
pave = canvas.makeStatsBox(p, color=R.kBlue)
if hkey in ('nHits', 'LxySig'):
Plotter.MOVE_OBJECT(pave, Y=-.3)
canvas.mainPad.Update()
if canvas.logy:
line = R.TLine(
CONFIG[hkey]['val'], canvas.firstPlot.GetMinimum(),
CONFIG[hkey]['val'],
10.**(R.TMath.Log10(canvas.firstPlot.GetMaximum()) * 1.06))
else:
line = R.TLine(CONFIG[hkey]['val'], canvas.firstPlot.GetMinimum(),
CONFIG[hkey]['val'],
canvas.firstPlot.GetMaximum() * 1.05)
line.Draw()
line.SetLineStyle(2)
print '\033[31m{:6s} {:8s} {:5.0f} {:5.0f} {:7.2%}\033[m'.format(
'Signal', hkey, *fractionCut(hkey, canvas.firstPlot.plot))
RT.addBinWidth(canvas.firstPlot)
canvas.cleanup('pdfs/NM1D_{}_2Mu2J.pdf'.format(hkey))
def makeBinnedResPlot(MUON, fs, sp, quantity, q2):
h = HistogramGetter.getHistogram(f, (fs, sp), '{M}_{Q}ResVS{Q2}'.format(M=MUON, Q=quantity, Q2=q2)).Clone()
fname = 'pdfs/SRR_{}_{}_{}-Binned_{}HTo2XTo{}_{}.pdf'.format(MUON, quantity+'Res', q2, 'Trig-' if TRIGGER else '', fs, SPStr(sp))
pretty, binranges, values, colors, colors2, legName = getBinningValues(q2)
projections = {key:h.ProjectionY('_'+str(i), key[0], key[1]) for i,key in enumerate(binranges)}
plots = {key:Plotter.Plot(projections[key], legName.format(Q2=pretty, V1=values[key][0], V2=values[key][1]), 'l', 'hist') for key in binranges}
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, *sp))
for key in binranges:
RT.addFlows(plots[key])
plots[key].Rebin(10)
if plots[key].Integral() != 0:
plots[key].Scale(1./plots[key].Integral())
canvas.addMainPlot(plots[key])
canvas.makeLegend(lWidth=.25, pos='tr')
canvas.legend.moveLegend(X=-.08)
canvas.legend.resizeHeight()
canvas.setMaximum(recompute=True)
for i, key in enumerate(binranges):
plots[key].SetLineColor(colors[key])
plots[key].setTitles(X=plots[key].GetXaxis().GetTitle(), Y='Normalized Counts')
canvas.drawText('#color[{}]{{'.format(colors2[key]) + 'RMS = {:.4f}'.format(plots[key].GetStdDev()) + '}',
(canvas.legend.GetX1NDC()+.01, canvas.legend.GetY1NDC()-(i*0.04)-.04)
)
RT.addBinWidth(canvas.firstPlot)
canvas.cleanup(fname)
def makeRepEffectPlots(hkey):
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'], hkey)
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
canvas = Plotter.Canvas(lumi='MC, {} replacement'.format(
hkey.replace('LxySig-', '').replace('Lxy-', '')),
logy=True)
for key in HG.BGORDER:
PLOTS[key].setColor(HG.PLOTCONFIG[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
canvas.firstPlot.setTitles(X='', copy=PLOTS[HG.BGORDER[0]])
canvas.firstPlot.setTitles(Y='Normalized Counts')
canvas.makeLegend(lWidth=.27, pos='tr', autoOrder=False, fontscale=0.8)
for ref in reversed(HG.BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
canvas.firstPlot.SetMaximum(10.**7.)
canvas.firstPlot.SetMinimum(10.**0.)
canvas.cleanup('RepEffect_MC_{}.pdf'.format(hkey))
def makeTestPlot():
hkey = 'DSA-deltaPhi'
HISTS = HG.getAddedSignalHistograms(FILES['2Mu2J'], '2Mu2J',
('deltaPhi', ))
DATAHISTS, DataPConfig = HG.getDataHistograms(FILES['Data'], hkey)
HISTS[hkey] = HISTS['deltaPhi']
pS = Plotter.Plot(HISTS[hkey], 'H#rightarrow2X#rightarrow2#mu signal', 'l',
'hist')
pD = Plotter.Plot(DATAHISTS[hkey]['data'], *DataPConfig[hkey]['data'])
canvas = Plotter.Canvas(lumi='2#mu signal + 10% of 2016 data', logy=True)
canvas.addMainPlot(pS)
canvas.addMainPlot(pD)
pS.setColor(R.kBlue, which='L')
canvas.makeLegend(lWidth=.25)
canvas.legend.resizeHeight()
canvas.legend.moveLegend(X=-.1)
canvas.firstPlot.SetMinimum(0.5)
canvas.firstPlot.SetMaximum(50000.)
canvas.firstPlot.setTitles(Y='Long-Lived Candidates')
line = R.TLine(R.TMath.Pi() / 2., 0.5, R.TMath.Pi() / 2., 50000.)
line.Draw()
line.SetLineStyle(2)
RT.addBinWidth(canvas.firstPlot)
canvas.cleanup('deltaPhi.pdf')
def makeMCPlots():
f = R.TFile.Open('roots/PATMuonStudyPlots_Combined_BS8_MC.root')
#f = R.TFile.Open('roots/PATMuonStudyPlots_Combined_BS8_MC_OldPATMatch.root')
BGORDER = ('WJets', 'WW', 'WZ', 'ZZ', 'tW', 'tbarW', 'ttbar', 'QCD20toInf-ME', 'DY10to50', 'DY50toInf')
PC = HG.PLOTCONFIG
for hkey in ('PAT-LxySig', 'DSA-LxySig', 'PAT-vtxChi2', 'DSA-vtxChi2'):
HISTS = {}
HISTS['stack'] = R.THStack('hStack', '')
PConfig = {'stack':('', '', 'hist')}
for ref in BGORDER:
HISTS[ref] = HG.getHistogram(f, ref, hkey).Clone()
#RT.addFlows(HISTS[ref])
HISTS[ref].Scale(PC[ref]['WEIGHT'])
HISTS[ref].Rebin(10)
HISTS['stack'].Add(HISTS[ref])
PConfig[ref] = (PC[ref]['LATEX'], 'f', 'hist')
PLOTS = {}
for key in BGORDER + ('stack',):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
canvas = Plotter.Canvas(logy=True)
for key in BGORDER:
PLOTS[key].setColor(PC[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
# this has to be here because it has to be drawn first
if 'LxySig' in hkey:
canvas.firstPlot.GetXaxis().SetRangeUser(0., 1000.)
pass
if 'vtxChi2' in hkey:
#canvas.firstPlot.GetXaxis().SetRangeUser(0., 200.)
pass
canvas.firstPlot.setTitles(X='', copy=PLOTS[BGORDER[0]])
canvas.firstPlot.setTitles(Y='Normalized Counts')
canvas.makeLegend(lWidth=.27, pos='tr', autoOrder=False, fontscale=0.8)
for ref in reversed(BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
HISTS['sum'] = HISTS['stack'].GetStack().Last()
nBins = HISTS['sum'].GetNbinsX()
if 'LxySig' in hkey:
val = 100.
if 'vtxChi2' in hkey:
val = 50.
print '{} Mean : {}'.format(hkey, HISTS['sum'].GetMean())
print '{} Overflow % : {}'.format(hkey, HISTS['sum'].GetBinContent( nBins+1)/HISTS['sum'].Integral(0, nBins+1)*100.)
print '{} > {:<8.0f} % : {}'.format(hkey, val, HISTS['sum'].Integral (HISTS['sum'].FindBin(val), nBins+1)/HISTS['sum'].Integral(0, nBins+1)*100.)
if hkey == 'PAT-LxySig':
h = HG.getHistogram(f, 'DY50toInf', hkey).Clone()
print '{} DY50toInf : {}'.format(hkey, h.Integral(h.FindBin(100.), h.GetNbinsX()+1))
canvas.firstPlot.SetMaximum(HISTS['sum'].GetMaximum()*1.05)
canvas.firstPlot.SetMinimum(1.)
canvas.cleanup('pdfs/MC_'+hkey+'.pdf')
def makeLessMorePlot(fs, sp, quantity):
h = {
'Less':
HG.getHistogram(FILES[fs], (fs, sp),
'{}-Less'.format(quantity)).Clone(),
'More':
HG.getHistogram(FILES[fs], (fs, sp),
'{}-More'.format(quantity)).Clone(),
}
for key in h:
try:
h[key].Scale(1. / h[key].Integral())
except:
return
pretty = {
'Less': {
'leg': 'L_{xy} < 320 cm',
'col': R.kBlue
},
'More': {
'leg': 'L_{xy} > 320 cm',
'col': R.kRed
},
}
p = {
key: Plotter.Plot(h[key], pretty[key]['leg'], 'l', 'hist')
for key in h
}
prettyFS = '2#mu' if '2Mu' in fs else '4#mu'
c = Plotter.Canvas(
lumi='H#rightarrow2X#rightarrow{} ({} GeV, {} GeV, {} mm)'.format(
prettyFS, *sp),
cWidth=600 if ARGS.SQUARE else 800)
for key in p:
c.addMainPlot(p[key])
p[key].setColor(pretty[key]['col'], which='LM')
RT.addBinWidth(c.firstPlot)
c.makeLegend(lWidth=0.125, pos='tr')
c.legend.resizeHeight()
c.legend.moveLegend(X=-.4)
c.setMaximum()
if ARGS.SQUARE:
c.firstPlot.scaleTitleOffsets(1.1, 'X')
c.cleanup('pdfs/LESSMORE_{}_{}_{}_{}_{}.pdf'.format(quantity, fs, *sp),
mode='LUMI')
def makePerSignalPlots(fs):
for sp in SIGNALPOINTS:
for key in HISTS[(fs, sp)]:
h = HISTS[(fs, sp)][key]
RT.addFlows(h)
p = Plotter.Plot(h, '', 'p', 'hist')
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, *sp))
canvas.addMainPlot(p)
p.SetLineColor(R.kBlue)
RT.addBinWidth(p)
pave = canvas.makeStatsBox(p, color=R.kBlue)
canvas.cleanup('pdfs/Gen_{}_{}HTo2XTo{}_{}.pdf'.format(
key, 'Trig-' if TRIGGER else '', fs, SPStr(sp)))
def makeGenRecoPlots():
for ref in HISTS:
if not type(ref) == tuple: continue
if ref[0] == '4Mu':
name = 'HTo2XTo4Mu_'
latexFS = '4#mu'
elif ref[0] == '2Mu2J':
name = 'HTo2XTo2Mu2J_'
latexFS = '2#mu2j'
if TRIGGER:
name = 'Trig-' + name
name += SPStr(ref[1])
lumi = SPLumiStr(ref[0], *ref[1])
colors = {'Matched': R.kRed, 'Closest': R.kBlue}
KEYS = ('Matched', 'Closest')
for MUON in ('DSA', 'REF'):
h, p = {}, {}
for key in KEYS:
h[key] = HISTS[ref]['{}_{}_{}'.format(MUON, 'deltaRGR',
key)].Clone()
RT.addFlows(h[key])
if h[key].GetNbinsX() > 100: h.Rebin(10)
p[key] = Plotter.Plot(h[key], key, 'l', 'hist')
fname = 'pdfs/{}{}_{}_{}_{}.pdf'.format(MUON, CUTSTRING,
'deltaRGR', 'Matched',
name)
canvas = Plotter.Canvas(lumi=lumi)
for key in KEYS:
canvas.addMainPlot(p[key])
p[key].SetLineColor(colors[key])
canvas.makeLegend(lWidth=.25, pos='tr')
canvas.legend.resizeHeight()
canvas.setMaximum()
RT.addBinWidth(canvas.firstPlot)
LPOS = (canvas.legend.GetX1NDC() + .01,
canvas.legend.GetY1NDC() - .04)
for i, key in enumerate(KEYS):
canvas.drawText(text='#color[{}]{{n = {:d}}}'.format(
colors[key], int(p[key].GetEntries())),
pos=(LPOS[0], LPOS[1] - i * 0.04))
canvas.cleanup(fname)
def makeEffPlots(quantity, fs, SP=None):
HKeys = {
'Eff': '{}Eff',
'Den': '{}Den',
}
for key in HKeys:
HKeys[key] = HKeys[key].format(quantity)
h = {}
p = {}
g = {}
if SP is None:
for i, sp in enumerate(SIGNALPOINTS):
if i == 0:
for key in HKeys:
h[key] = HISTS[(fs, sp)][HKeys[key]].Clone()
h[key].SetDirectory(0)
else:
for key in HKeys:
h[key].Add(HISTS[(fs, sp)][HKeys[key]])
else:
sp = SP
for key in HKeys:
h[key] = HISTS[(fs, sp)][HKeys[key]].Clone()
h[key].SetDirectory(0)
for key in HKeys:
RT.addFlows(h[key])
h[key].Rebin(10)
g['Eff'] = R.TGraphAsymmErrors(h['Eff'], h['Den'], 'cp')
g['Eff'].SetNameTitle(
'g_Eff',
';' + h['Eff'].GetXaxis().GetTitle() + ';Vertex Fit Efficiency')
p['Eff'] = Plotter.Plot(g['Eff'], '', 'elp', 'pe')
canvas = Plotter.Canvas(lumi=fs if SP is None else SPLumiStr(fs, *SP))
canvas.addMainPlot(p['Eff'])
p['Eff'].setColor(R.kBlue)
RT.addBinWidth(canvas.firstPlot)
canvas.firstPlot.SetMinimum(0.)
canvas.firstPlot.SetMaximum(1.)
canvas.cleanup('pdfs/SVFE_{}Eff{}_{}HTo2XTo{}_{}.pdf'.format(
quantity, CUTSTRING, 'Trig-' if TRIGGER else '', fs,
'Global' if SP is None else SPStr(SP)))
def makeResPlot(fs, sp):
if sp is None:
h = HG.getAddedSignalHistograms(FILES[fs], fs,
['pTRes-' + MUON for MUON in MUONS])
prettyFS = '2#mu' if '2Mu' in fs else '4#mu'
lumi = 'H#rightarrow2X#rightarrow{}, all samples combined{}'.format(
prettyFS, ' + trigger' if ARGS.TRIGGER else '')
else:
h = {}
for MUON in MUONS:
h['pTRes-' + MUON] = HG.getHistogram(FILES[fs], (fs, sp),
'pTRes-' + MUON).Clone()
prettyFS = '2#mu' if '2Mu' in fs else '4#mu'
lumi = 'H#rightarrow2X#rightarrow{} ({} GeV, {} GeV, {} mm){}'.format(
prettyFS, sp[0], sp[1], sp[2],
' + trigger' if ARGS.TRIGGER else '')
c = Plotter.Canvas(lumi=lumi, cWidth=600 if ARGS.SQUARE else 800)
pretty = {'DSA': {'col': R.kBlue}, 'RSA': {'col': R.kRed}}
p = {}
for MUON in MUONS:
h['pTRes-' + MUON].Scale(
1. /
h['pTRes-' + MUON].Integral(0, h['pTRes-' + MUON].GetNbinsX() + 1))
#h['pTRes-'+MUON].Rebin(10)
p[MUON] = Plotter.Plot(h['pTRes-' + MUON], MUON, 'l', 'hist')
c.addMainPlot(p[MUON])
p[MUON].setColor(pretty[MUON]['col'], which='LM')
c.makeLegend(lWidth=0.125, pos='tr')
c.legend.resizeHeight()
c.setMaximum()
c.firstPlot.setTitles(X='', Y='', copy=h['pTRes-DSA'])
RT.addBinWidth(c.firstPlot)
if ARGS.SQUARE:
c.firstPlot.scaleTitleOffsets(1.1, 'X')
c.firstPlot.scaleTitleOffsets(1.3, 'Y')
c.cleanup('pdfs/PTRES{}_{}_{}.pdf'.format(
'_Trig' if ARGS.TRIGGER else '', fs,
'Global' if sp is None else SPStr(sp)),
mode='LUMI')
def makePerSamplePlots():
for ref in HISTS:
if not type(ref) == tuple: continue
for key in HISTS[ref]:
if 'deltaRGR' in key: continue
if 'VS' in key: continue
if type(ref) == tuple:
if ref[0] == '4Mu':
name = 'HTo2XTo4Mu_'
latexFS = '4#mu'
elif ref[0] == '2Mu2J':
name = 'HTo2XTo2Mu2J_'
latexFS = '2#mu2j'
if TRIGGER:
name = 'Trig-' + name
name += SPStr(ref[1])
lumi = SPLumiStr(ref[0], *ref[1])
legName = HistogramGetter.PLOTCONFIG['HTo2XTo' +
ref[0]]['LATEX']
else:
if '_Matched' in key: continue
name = ref
lumi = HistogramGetter.PLOTCONFIG[ref]['LATEX']
legName = HistogramGetter.PLOTCONFIG[ref]['LATEX']
h = HISTS[ref][key].Clone()
RT.addFlows(h)
if h.GetNbinsX() > 100: h.Rebin(10)
p = Plotter.Plot(h, legName, 'l', 'hist')
fname = 'pdfs/{}{}_{}.pdf'.format(key, CUTSTRING, name)
canvas = Plotter.Canvas(lumi=lumi)
canvas.addMainPlot(p)
canvas.makeLegend(lWidth=.25, pos='tr')
canvas.legend.moveLegend(Y=-.3)
canvas.legend.resizeHeight()
p.SetLineColor(R.kBlue)
RT.addBinWidth(p)
pave = canvas.makeStatsBox(p, color=R.kBlue)
canvas.cleanup(fname)
def makePerSamplePlots():
for ref in HISTS:
for key in HISTS[ref]:
if type(ref) == tuple:
if ref[0] == '4Mu': name = 'HTo2XTo4Mu_'
elif ref[0] == '2Mu2J': name = 'HTo2XTo2Mu2J_'
name += SPStr(ref[1])
if TRIGGER:
name = 'Trig-' + name
lumi = SPLumiStr(ref[0], *ref[1])
legName = HistogramGetter.PLOTCONFIG['HTo2XTo' +
ref[0]]['LATEX']
else:
name = ref
lumi = HistogramGetter.PLOTCONFIG[ref]['LATEX']
legName = HistogramGetter.PLOTCONFIG[ref]['LATEX']
h = HISTS[ref][key].Clone()
RT.addFlows(h)
p = Plotter.Plot(h, legName, 'l', 'hist')
fname = 'pdfs/NM1_{}_{}.pdf'.format(key, name)
canvas = Plotter.Canvas(lumi=lumi)
canvas.lumi += ' : |#Delta#Phi| ' + ('<' if '_Less' in key else
'>') + ' #pi/2'
canvas.addMainPlot(p)
canvas.makeLegend(lWidth=.25, pos='tr')
canvas.legend.moveLegend(Y=-.3)
canvas.legend.resizeHeight()
p.SetLineColor(R.kBlue)
RT.addBinWidth(p)
cutKey = key.replace('_Less', '').replace('_More', '')
cutVal = Selections.CUTS[cutKey].val
l = R.TLine(cutVal, p.GetMinimum(), cutVal, p.GetMaximum() * 1.05)
l.SetLineStyle(2)
l.SetLineWidth(2)
l.Draw()
canvas.cleanup(fname)
def makeBinnedResPlotBinwise(MUONS, outputTag, quantity, q2, fs, sp):
defaultColorOrder = (R.kRed, R.kBlue, R.kGreen, R.kMagenta)
h = {}
for MUON in MUONS:
h[MUON] = HistogramGetter.getHistogram(f, (fs, sp), '{M}_{Q}ResVS{Q2}'.format(M=MUON, Q=quantity, Q2=q2)).Clone()
# leaving space for the bin number
fname = 'pdfs/SRR_{}_{}_{}-Binned-Bin-{{}}_{}HTo2XTo{}_{}.pdf'.format(outputTag, quantity+'Res', q2, 'Trig-' if TRIGGER else '', fs, SPStr(sp))
pretty, binranges, values, colors, colors2, legName = getBinningValues(q2)
for i, key in enumerate(binranges):
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, *sp))
projections, plots = {}, {}
for j, MUON in enumerate(MUONS):
projections[MUON] = h[MUON].ProjectionY('_'+str(i)+'_'+str(j), key[0], key[1])
plots[MUON] = Plotter.Plot(projections[MUON], MUON, 'l', 'hist')
RT.addFlows(plots[MUON])
plots[MUON].Rebin(10)
if plots[MUON].Integral() != 0:
plots[MUON].Scale(1./plots[MUON].Integral())
plots[MUON].SetLineColor(defaultColorOrder[j])
canvas.addMainPlot(plots[MUON])
canvas.makeLegend(lWidth=.25, pos='tr')
canvas.legend.resizeHeight()
canvas.setMaximum(recompute=True)
canvas.drawText(legName.format(Q2=pretty, V1=values[key][0], V2=values[key][1]), (canvas.legend.GetX1NDC()+.01, canvas.legend.GetY1NDC()-.04))
for j, MUON in enumerate(MUONS):
plots[MUON].SetLineColor(defaultColorOrder[j])
plots[MUON].setTitles(X=plots[MUON].GetXaxis().GetTitle(), Y='Normalized Counts')
canvas.drawText('#color[{}]{{'.format(defaultColorOrder[j]) + 'RMS = {:.4f}'.format(plots[MUON].GetStdDev()) + '}',
(canvas.legend.GetX1NDC()+.01, canvas.legend.GetY1NDC()-(j*0.04)-.08)
)
RT.addBinWidth(canvas.firstPlot)
canvas.cleanup(fname.format(i+1))
def makeRatioPlots(quantity, LxyRange):
legDict = {'Less': '< #pi/4', 'More': '> 3#pi/4'}
hkeys = {
key: 'h{}{}{}'.format(key, quantity, LxyRange)
for key in ('Less', 'More')
}
a = HISTS[hkeys['Less']]['stack'].GetStack().Last().Clone()
den = HISTS[hkeys['More']]['stack'].GetStack().Last().Clone()
a.Rebin(2), den.Rebin(2)
a.Divide(den)
d = DHists[hkeys['Less']].Clone()
den = DHists[hkeys['More']].Clone()
d.Rebin(2), den.Rebin(2)
d.Divide(den)
PLOTS = {'': Plotter.Plot(a, ' MC SR/CR', 'lp', 'hist p')}
DPLOTS = {'': Plotter.Plot(d, 'Data SR/CR', 'lp', 'hist p')}
canvas = Plotter.Canvas(lumi='36.3 fb^{-1} (13 TeV)', logy=False)
colors = {'': R.kBlue}
canvas.addMainPlot(PLOTS[''])
canvas.addMainPlot(DPLOTS[''])
PLOTS[''].setColor(R.kBlue)
DPLOTS[''].setColor(R.kBlack)
canvas.firstPlot.setTitles(X='', copy=DHists[hkeys['Less']])
canvas.firstPlot.setTitles(Y='Event Yield')
canvas.makeLegend(lWidth=.3, pos='tr')
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
canvas.firstPlot.SetMaximum(2.)
canvas.firstPlot.SetMinimum(-1.)
canvas.cleanup('pdfs/Ratio_{}_{}.pdf'.format(
keyList[hkeys['Less']], 'Lin' if not canvas.logy else 'Log'))
def makeRepEffectPlots(hkey):
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'], hkey)
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
canvas = Plotter.Canvas(
lumi='MC Background, {} PAT association (36.3 fb^{{-1}})'.format(
hkey.replace('LxySig-', '').replace('Lxy-', '')),
logy=True,
cWidth=600 if ARGS.SQUARE else 800)
for key in HG.BGORDER:
PLOTS[key].setColor(HG.PLOTCONFIG[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
canvas.firstPlot.setTitles(X='', copy=PLOTS[HG.BGORDER[0]])
canvas.firstPlot.setTitles(Y='Event Yield')
canvas.makeLegend(lWidth=.3, pos='tr', autoOrder=False, fontscale=0.8)
for ref in reversed(HG.BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
canvas.firstPlot.SetMaximum(10.**7.)
canvas.firstPlot.SetMinimum(10.**0.)
if ARGS.SQUARE:
canvas.firstPlot.scaleTitleOffsets(1.1, 'X')
z = PLOTS['stack'].plot.GetStack().Last()
print 'MC', hkey, z.Integral(0, z.GetNbinsX() + 1)
canvas.cleanup('pdfs/REPEFF_MC_{}.pdf'.format(hkey), mode='LUMI')
def makeStackPlots(DataMC=False, logy=False):
BGORDER = ('WJets', 'WW', 'WZ', 'ZZ', 'tW', 'tbarW', 'ttbar',
'QCD20toInf-ME', 'DY10to50', 'DY50toInf')
for hkey in HISTS['DY50toInf']:
if 'Matched' in hkey: continue
if 'VS' in hkey: continue
h = {}
if not MCONLY:
h['Data'] = HISTS['DoubleMuonRun2016B-07Aug17-v2'][hkey].Clone()
if True:
# h ['Signal'] = HISTS[('4Mu', (125, 20, 13)) ][hkey].Clone()
h['BG'] = R.THStack('hBG', '')
PConfig = {}
if not MCONLY:
PConfig['Data'] = ('DoubleMuon2016', 'pe', 'pe')
if True:
# PConfig['Signal'] = ('H#rightarrow2X#rightarrow4#mu', 'l' , 'hist')
PConfig['BG'] = ('', '', 'hist')
PC = HistogramGetter.PLOTCONFIG
for key in BGORDER:
h[key] = HISTS[key][hkey].Clone()
RT.addFlows(h[key])
if h[key].GetNbinsX() > 100: h[key].Rebin(10)
h[key].Scale(PC[key]['WEIGHT'])
PConfig[key] = (PC[key]['LATEX'], 'f', 'hist')
h['BG'].Add(h[key])
if not MCONLY:
for era in ('C', 'D', 'E', 'F', 'G', 'H'):
h['Data'].Add(
HISTS['DoubleMuonRun2016{}-07Aug17'.format(era)][hkey])
RT.addFlows(h['Data'])
if h['Data'].GetNbinsX() > 100: h['Data'].Rebin(10)
p = {}
for key in h:
p[key] = Plotter.Plot(h[key], *PConfig[key])
fname = 'pdfs/{}{}_Stack{}{}{}.pdf'.format(hkey, CUTSTRING,
'MC' if MCONLY else '',
'-Log' if logy else '',
'-Rat' if DataMC else '')
for key in BGORDER:
p[key].setColor(PC[key]['COLOR'], which='LF')
canvas = Plotter.Canvas(ratioFactor=0. if not DataMC else 1. / 3.,
logy=logy,
fontscale=1. if not DataMC else 1. + 1. / 3.)
if True:
canvas.addMainPlot(p['BG'])
if not MCONLY:
canvas.addMainPlot(p['Data'])
# canvas.addMainPlot(p['Signal'])
canvas.makeLegend(lWidth=.27,
pos='tr',
autoOrder=False,
fontscale=0.8 if not DataMC else 1.)
if not MCONLY:
canvas.addLegendEntry(p['Data'])
for key in reversed(BGORDER):
canvas.addLegendEntry(p[key])
# canvas.addLegendEntry(p['Signal'])
canvas.legend.resizeHeight()
p['BG'].setTitles(X=p['WJets'].GetXaxis().GetTitle(),
Y='Normalized Counts')
RT.addBinWidth(p['BG'])
canvas.firstPlot.SetMaximum(h['BG'].GetStack().Last().GetMaximum() *
1.05)
#canvas.firstPlot.SetMaximum(1.e-4)
if logy:
canvas.firstPlot.SetMinimum(1.)
if DataMC:
canvas.makeRatioPlot(p['Data'].plot,
p['BG'].plot.GetStack().Last())
canvas.firstPlot.scaleTitleOffsets(0.8, axes='Y')
canvas.rat.scaleTitleOffsets(0.8, axes='Y')
# p['Signal' ].SetLineStyle(2)
# p['Signal' ].SetLineColor(R.kRed)
canvas.finishCanvas(extrascale=1. if not DataMC else 1. + 1. / 3.)
canvas.save(fname)
canvas.deleteCanvas()
def makeEffPlots(quantity, fs, SP=None):
HKeys = {
'DSA_Num': 'DSADim_Num_{}',
'DSA_Den': 'DSADim_Den_{}',
}
for key in HKeys:
HKeys[key] = HKeys[key].format(quantity, 'HTo2XTo' + fs)
h = {}
pg = {}
pnum = {}
pden = {}
prn = {}
prd = {}
g = {}
rn = {}
rd = {}
if SP is None:
for i, sp in enumerate(SIGNALPOINTS):
if i == 0:
for key in HKeys:
h[key] = HISTS[(fs, sp)][HKeys[key]].Clone()
h[key].SetDirectory(0)
else:
for key in HKeys:
h[key].Add(HISTS[(fs, sp)][HKeys[key]])
displacement_str = None
displacement_color = None
else:
sp = SP
if isinstance(sp, tuple):
for key in HKeys:
h[key] = HISTS[(fs, sp)][HKeys[key]].Clone()
h[key].SetDirectory(0)
h[key].GetXaxis().SetLimits(limit_low, limit_high)
h[key].GetXaxis().SetRangeUser(limit_low, limit_high)
RT.addFlows(h[key])
h[key].Rebin(10)
h[key].Sumw2()
elif isinstance(sp, list):
h[key] = {}
for key in HKeys:
for spl in sp:
h[key][spl] = HISTS[(fs, spl)][HKeys[key]].Clone()
h[key][spl].SetDirectory(0)
h[key][spl].GetXaxis().SetLimits(limit_low, limit_high)
RT.addFlows(h[key][spl])
h[key][spl].Rebin(10)
h[key][spl].Sumw2()
dxy_fraction = round(FRACTIONS[fs]['{}_{}_{}'.format(*SP)][1], 1)
for key in DISPLACEMENT_CATEGORIES:
if key[0] <= dxy_fraction < key[1]:
displacement_str = DISPLACEMENT_CATEGORIES[key]['label']
displacement_color = DISPLACEMENT_CATEGORIES[key]['color']
break
else:
# we must have dxy_fractions == 100.0
key = DISPLACEMENT_CATEGORIES.keys()[-1]
displacement_str = DISPLACEMENT_CATEGORIES[key]['label']
displacement_color = DISPLACEMENT_CATEGORIES[key]['color']
# for key in HKeys:
# RT.addFlows(h[key])
# h[key].Rebin(10)
# # area = h[key].Integral()
# h[key].Sumw2()
# # if area != 0: h[key].Scale(1./area)
NumDens = (
('DSA_Num', 'DSA_Den', 'GEN', R.kBlue),
('DSA_Num', 'DSA_Den', ('untriggered', 'triggered'), (R.kBlue,
R.kRed)),
)
num, den, leg, col = NumDens[0]
g[num] = R.TGraphAsymmErrors(h[num], h[den], 'cp')
g[num].GetXaxis().SetLimits(limit_low, limit_high)
g[num].SetNameTitle(
'g_' + num,
';' + h[num].GetXaxis().GetTitle() + '; Trigger Efficiency')
pg[num] = Plotter.Plot(g[num], leg, 'elp', 'pe')
num, den, leg, col = NumDens[1]
pnum[num] = Plotter.Plot(deepcopy(h[num]), leg[1], 'elp', 'pe')
pden[num] = Plotter.Plot(deepcopy(h[den]), leg[0], 'elp', 'pe')
pnum[num].SetNameTitle('pnum_' + num,
';' + h[num].GetXaxis().GetTitle() + '; yield')
rn[num] = deepcopy(h[num])
rn[num].Scale(1. / (h[num].Integral()))
rn[num].SetNameTitle('rn_' + num,
';' + h[num].GetXaxis().GetTitle() + '; norm. yield')
# rn[num].GetXaxis().SetRangeUser(0, 100)
prn[num] = Plotter.Plot(rn[num], leg[1], 'elp', 'pe')
rd[num] = deepcopy(h[den])
rd[num].Scale(1. / (h[den].Integral()))
rd[num].SetNameTitle('rd_' + num,
';' + h[num].GetXaxis().GetTitle() + '; norm. yield')
prd[num] = Plotter.Plot(rd[num], leg[0], 'elp', 'pe')
FIRST = (0, 1)
SECOND = (1, 2)
fraction_str = '' if SP is None else '[{}%, #color[{}]{{{}%}}]'.format(
round(FRACTIONS[fs]['{}_{}_{}'.format(*SP)][0], 1), displacement_color,
round(FRACTIONS[fs]['{}_{}_{}'.format(*SP)][1], 1))
accepted_error_max = 0.1
accepted_error_halfmax = 0.2
for SECTION in (FIRST, ):
canvas_eff = Plotter.Canvas(
lumi=fs if SP is None else
'{} ({} GeV, {} GeV, {} mm) #scale[0.7]{{{fraction_str}}}'.
format(fs, *SP, fraction_str=fraction_str))
for i in range(SECTION[0], SECTION[1]):
key = NumDens[i][0]
col = NumDens[i][3]
# pg[key].GetXaxis().SetLimits(0., 3.5)
canvas_eff.addMainPlot(pg[key])
pg[key].SetMarkerColor(col)
pg[key].SetLineColor(col)
ymax = -1.
ymaxErrorYlow = 0.
ymaxErrorYhigh = 0.
ymax_pos = None
for b in range(pg[key].GetN(), 0, -1):
xtemp = R.Double(-1.)
ytemp = R.Double(-1.)
pg[key].GetPoint(b, xtemp, ytemp)
ytempErrorYlow = pg[key].GetErrorYlow(b)
ytempErrorYhigh = pg[key].GetErrorYhigh(b)
# if ytemp > ymax and max(pg[key].GetErrorYlow(b),
# pg[key].GetErrorYhigh(b)) < accepted_error_max:
# ymax = ytemp
# ymax_pos = xtemp
# if point has a lower value than the one one the right, but it
# is compatible with the fluctuations of the plot on the right
# (i.e., its errors are contained in the errors of the other
# plot), then call the (left) point the new maximum nevertheless
if ytemp < ymax and max(ytempErrorYlow,
ytempErrorYhigh) < accepted_error_max and \
ytemp-ytempErrorYlow > ymax-ymaxErrorYlow and \
ytemp+ytempErrorYhigh < ymax+ymaxErrorYhigh:
ymax = ytemp
ymaxErrorYlow = ytempErrorYlow
ymaxErrorYhigh = ytempErrorYhigh
ymax_pos = xtemp
elif ytemp > ymax and max(
ytempErrorYlow, ytempErrorYhigh) < accepted_error_max:
ymax = ytemp
ymaxErrorYlow = ytempErrorYlow
ymaxErrorYhigh = ytempErrorYhigh
ymax_pos = xtemp
if ymax_pos is not None:
maxarrow = R.TArrow(ymax_pos, -0.065, ymax_pos, 0.)
R.SetOwnership(maxarrow, 0)
maxarrow.SetLineColor(col)
maxarrow.SetLineWidth(3)
maxarrow.SetArrowSize(0.02)
maxarrow.Draw()
else:
print('WARNING: No maximum found. Maybe the accepted errors '
'are too small?')
ymax_pos = None
yhalfmax_pos = None
if ymax_pos is not None:
yhalfmax = 0.5 * ymax
yhalfmax_pos = None
for b in range(pg[key].GetN()):
xtemp = R.Double(-1.)
ytemp = R.Double(-1.)
pg[key].GetPoint(b, xtemp, ytemp)
if ytemp > yhalfmax and max(
pg[key].GetErrorYlow(b),
pg[key].GetErrorYhigh(b)) < accepted_error_halfmax:
x2 = xtemp
y2 = ytemp
xtemp_prev = R.Double(0.)
ytemp_prev = R.Double(0.)
for bprev in range(1, b + 1):
if b - bprev >= 0 and max(
pg[key].GetErrorYlow(b - bprev),
pg[key].GetErrorYhigh(
b - bprev)) < accepted_error_halfmax:
pg[key].GetPoint(b - bprev, xtemp_prev,
ytemp_prev)
x1 = xtemp_prev
y1 = ytemp_prev
# linear interpolation:
yhalfmax_pos = (yhalfmax * (x1 - x2) +
(y1 * x2 - y2 * x1)) / (y1 -
y2)
break
else:
yhalfmax_pos = x2 * 0.5
halfmaxarrow = R.TArrow(yhalfmax_pos, -0.06,
yhalfmax_pos, 0.)
R.SetOwnership(halfmaxarrow, 0)
halfmaxarrow.SetLineColor(col)
halfmaxarrow.SetLineWidth(2)
halfmaxarrow.SetArrowSize(0.02)
halfmaxarrow.Draw()
break
if ymax_pos is not None and yhalfmax_pos is not None:
pg[key].legName = pg[key].legName + \
' #scale[0.7]{{(#Delta R_{{max}} = {}, #Delta R_{{max/2}} = {}, #frac{{#Delta R_{{max/2}}}}{{#Delta R_{{max}}}} = {})}}'.format(
round(ymax_pos,3), round(yhalfmax_pos,3),
round(yhalfmax_pos/ymax_pos, 3))
run1_line = R.TLine(0.2, 0., 0.2, 1.)
R.SetOwnership(run1_line, 0)
run1_line.SetLineColor(R.kGray)
run1_line.Draw()
canvas_eff.makeLegend(lWidth=0.65, pos='tr')
# canvas_eff.legend.moveLegend(X=0.08)
canvas_eff.legend.resizeHeight()
# canvas_eff.firstPlot.GetXaxis().SetLimits(0., 3.5)
canvas_eff.firstPlot.SetMinimum(0.)
canvas_eff.firstPlot.SetMaximum(1.)
RT.addBinWidth(canvas_eff.firstPlot)
canvas_eff.cleanup('pdfs/DimSTE_{}{}Eff_HTo2XTo{}_{}_{}.pdf'.format(
output_tag, quantity, fs, 'Global' if SP is None else SPStr(SP),
(displacement_str if displacement_str is not None else '')))
for SECTION in (SECOND, ):
canvas_ratioplot = Plotter.Canvas(
ratioFactor=1 / 3.,
lumi=fs if SP is None else
'{} ({} GeV, {} GeV, {} mm) #scale[0.7]{{{fraction_str}}}'.format(
fs, *SP, fraction_str=fraction_str))
for i in range(SECTION[0], SECTION[1]):
key = NumDens[i][0]
col = NumDens[i][3]
# prn[key].GetXaxis().SetLimits(0., 3.5)
# prd[key].GetXaxis().SetLimits(0., 3.5)
canvas_ratioplot.makeLegend(lWidth=.35, pos='tr')
canvas_ratioplot.addLegendEntry(prn[key])
canvas_ratioplot.addLegendEntry(prd[key])
canvas_ratioplot.legend.resizeHeight()
canvas_ratioplot.addMainPlot(prn[key])
canvas_ratioplot.addMainPlot(prd[key])
canvas_ratioplot.makeRatioPlot(prn[key],
prd[key],
ytit='triggered / untriggered')
canvas_ratioplot.firstPlot.scaleTitleOffsets(0.8, axes='Y')
canvas_ratioplot.rat.scaleTitleOffsets(0.8, axes='Y')
vline = R.TLine(2.5, 0.5, 2.5, 1.5)
R.SetOwnership(vline, 0)
vline.SetLineColor(15)
vline.Draw()
prn[key].SetMarkerColor(col[0])
prn[key].SetLineColor(col[0])
prd[key].SetMarkerColor(col[1])
prd[key].SetLineColor(col[1])
# canvas_ratioplot.makeLegend(pos='tr')
# canvas_ratioplot.legend.moveLegend(X=0.08)
# canvas_ratioplot.legend.resizeHeight()
# canvas_ratioplot.firstPlot.SetMinimum(0.)
# canvas_ratioplot.firstPlot.SetMaximum(1.)
# vline = R.TLine(0., 1., 5., 1.)
# R.SetOwnership(vline, 0)
# vline.SetLineColor(15)
# vline.Draw()
# RT.addBinWidth(canvas_ratioplot.firstPlot)
# canvas_ratioplot.finishCanvas(extrascale=1.+1/3.)
canvas_ratioplot.cleanup(
'pdfs/DimSTE_{}{}NormRatio_HTo2XTo{}_{}_{}.pdf'.format(
output_tag, quantity, fs,
'Global' if SP is None else SPStr(SP),
(displacement_str if displacement_str is not None else '')))
canvas_overlay = Plotter.Canvas(
lumi=fs if SP is None else
'{} ({} GeV, {} GeV, {} mm) #scale[0.7]{{{fraction_str}}}'.
format(fs, *SP, fraction_str=fraction_str))
for i in range(SECTION[0], SECTION[1]):
key = NumDens[i][0]
col = NumDens[i][3]
canvas_overlay.addMainPlot(pden[num])
canvas_overlay.addMainPlot(pnum[num])
canvas_overlay.makeLegend(pos='tr', lWidth=.2)
canvas_overlay.legend.resizeHeight()
# canvas_overlay.firstPlot.GetXaxis().SetLimits(0., 3.5)
pnum[num].SetMarkerColor(col[0])
pden[num].SetMarkerColor(col[1])
pnum[num].SetLineColor(col[0])
pden[num].SetLineColor(col[1])
canvas_overlay.cleanup('pdfs/DimSTE_{}Overlay{}_{}_{}.pdf'.format(
quantity, fs, 'Global' if SP is None else SPStr(SP),
(displacement_str if displacement_str is not None else '')))
def makeOverlaidResPlot(MUONS, fs, sp, quantity, outputTag=None):
# whether the plot is dif or res makes a difference wrt binning, fit range, and stats box positions
# only pT is a res type; the others are all dif types
ISDIF = quantity != 'pT'
# what to name the plot. if MUONS is length 1, no sense to pass it twice, so get it automatically
if outputTag is None:
outputTag = MUONS[0]
# colors, in order of MUONS, and also hashed
defaultColorOrder = (R.kBlue, R.kRed, R.kGreen)
colorDict = dict(zip(MUONS, defaultColorOrder))
# get histograms and define plots
h = {}
for MUON in MUONS:
h[MUON] = HistogramGetter.getHistogram(f, (fs, sp), MUON+'_'+quantity+'Res').Clone()
p = {}
for MUON in MUONS:
RT.addFlows(h[MUON])
if not ISDIF:
h[MUON].Rebin(5)
else:
h[MUON].Rebin(10)
p[MUON] = Plotter.Plot(h[MUON], 'Signal MC ({})'.format(MUON[:3]), 'l', 'hist')
# define and fit gaussians to everything. Set FITRANGE to be something useful.
funcs = {}
fplots = {}
for MUON in MUONS:
if quantity == 'pT':
FITRANGE = (-0.4, 0.3)
elif quantity == 'eta':
FITRANGE = (-0.1, 0.1)
else:
FITRANGE = (-20., 20.)
funcs[MUON] = R.TF1('f'+MUON, 'gaus', *FITRANGE)
h[MUON].Fit('f'+MUON, 'R')
fplots[MUON] = Plotter.Plot(funcs[MUON], 'Gaussian fit ({})'.format(MUON[:3]), 'l', '')
# define canvas, add plots. addS is so that statsbox will be drawn later.
# these all should be pretty obvious until...
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, *sp))
for i, MUON in enumerate(MUONS):
canvas.addMainPlot(p[MUON], addS=True if i!=0 else False)
canvas.addMainPlot(fplots[MUON])
if len(MUONS) > 1:
canvas.firstPlot.setTitles(X=canvas.firstPlot.GetXaxis().GetTitle().replace(MUONS[0],'Reco'))
canvas.makeLegend(lWidth=.25, pos='tl')
canvas.legend.resizeHeight()
for MUON in MUONS:
p [MUON].SetLineColor(colorDict[MUON] )
fplots[MUON].SetLineColor(colorDict[MUON]+1)
RT.addBinWidth(canvas.firstPlot)
# dif type: fit boxes go down the left side
# res type: fit boxes go down the middle
# stats boxes are on the right
paves = []
for i, MUON in enumerate(MUONS):
paves.append(canvas.makeStatsBox(p[MUON], color=colorDict[MUON]))
Plotter.MOVE_OBJECT(paves[-1], Y=-.2*i)
if not ISDIF:
canvas.setFitBoxStyle(h[MUON], lWidth=0.275, pos='tr')
else:
canvas.setFitBoxStyle(h[MUON], lWidth=0.275, pos='tl')
sbox = p[MUON].FindObject('stats')
sbox.SetTextColor(colorDict[MUON]+1)
if not ISDIF:
Plotter.MOVE_OBJECT(sbox, Y=-.15*i, X=-.18, NDC=True)
else:
Plotter.MOVE_OBJECT(sbox, Y=-.15*i-0.04*4.1, NDC=True)
fname = 'pdfs/SRR_{}_{}_{}HTo2XTo{}_{}.pdf'.format(outputTag, quantity+'Res', 'Trig-' if TRIGGER else '', fs, SPStr(sp))
canvas.cleanup(fname)
def makeKinkDistPlot(quantity, masses):
points = sorted(
[sp for sp in SignalInfo if sp[0] == masses[0] and sp[1] == masses[1]],
key=lambda x: x[2])
s = {
points[0]:
HG.getHistogram(FILES['Signal'], (fs, points[0]),
'{}_1'.format(quantity)).Clone(),
points[1]:
HG.getHistogram(FILES['Signal'], (fs, points[1]),
'{}_10'.format(quantity)).Clone(),
}
s[points[0]].Scale(1. /
s[points[0]].Integral(0, s[points[0]].GetNbinsX() + 1))
s[points[1]].Scale(1. /
s[points[1]].Integral(0, s[points[1]].GetNbinsX() + 1))
#RT.addFlows(s[points[0]])
#RT.addFlows(s[points[1]])
s[points[0]].Rebin(2)
s[points[1]].Rebin(2)
pl = {
points[0]:
Plotter.Plot(s[points[0]],
'c#tau = {} mm, nominal'.format(points[0][2]), 'l',
'hist'),
points[1]:
Plotter.Plot(s[points[1]],
'c#tau = {} mm, reweighted'.format(points[0][2]), 'l',
'hist'),
}
colors = {
points[0]: R.kBlue,
points[1]: R.kRed,
}
c = Plotter.Canvas(lumi='({} GeV, {} GeV)'.format(*masses))
c.addMainPlot(pl[points[0]])
c.addMainPlot(pl[points[1]])
for p in points:
pl[p].setColor(colors[p], which='LM')
c.makeLegend(lWidth=0.3, pos='tr')
c.legend.SetMargin(0.1)
c.legend.resizeHeight()
c.drawText(text='lol',
pos=(c.legend.GetX1(), c.legend.GetY1() + .4),
NDC=False)
c.setMaximum()
RT.addBinWidth(c.firstPlot)
c.cleanup('pdfs/KINK_Dist_{}_{}_{}_{}.pdf'.format(quantity, masses[0],
masses[1],
FIGURE_OF_MERIT))
def makeSignalPlot(key):
h = HG.getAddedSignalHistograms(FILES['2Mu2J'], '2Mu2J', key)
h = h[key]
p = Plotter.Plot(h, '', '', 'hist')
RT.addBinWidth(p)
c = Plotter.Canvas(lumi='H#rightarrow2X#rightarrow2#mu, {}'.format(
CUTS[key]['lumi']),
cWidth=600 if key != 'deltaPhi' else 800,
logy=CUTS[key]['logy'])
c.addMainPlot(p)
c.firstPlot.setColor(R.kBlue)
c.firstPlot.scaleTitleOffsets(1.1, 'Y')
if key == 'deltaPhi':
axis = c.firstPlot.GetXaxis()
labeldict = {
1: '0',
25: '#pi/4',
50: '#pi/2',
75: '3#pi/4',
100: '#pi'
}
for i in xrange(1, 101):
val = labeldict.get(i)
if val is None: val = ''
axis.SetBinLabel(i, val)
axis.SetNdivisions(216, False)
axis.SetLabelSize(.06)
axis.SetTickLength(0.03)
axis.SetTickSize(0.03)
axis.LabelsOption('h')
c.mainPad.Update()
ymin = c.mainPad.GetUymin()
ymax = c.mainPad.GetUymax()
if c.logy:
ymax = 10.**ymax
xB = R.TGaxis(0., ymin,
R.TMath.Pi() - .07, ymin, 0., R.TMath.Pi(), 216, "+B",
.03)
xB.SetLabelSize(0)
xB.Draw('same')
xT = R.TGaxis(0., ymax,
R.TMath.Pi() - .07, ymax, 0., R.TMath.Pi(), 216, "-B",
.03)
xT.SetLabelSize(0)
xT.Draw('same')
if key == 'pT':
c.firstPlot.GetXaxis().SetRangeUser(0., 600.)
eff = getEff(p, key)
c.drawText('{:.1%} efficient'.format(eff),
align='tr',
pos=(1. - c.margins['r'] - .03, 1. - c.margins['t'] - .03))
c.mainPad.Update()
ymax = c.mainPad.GetUymax()
line = R.TLine(CUTS[key]['val'], 0., CUTS[key]['val'],
ymax if not c.logy else 10.**ymax)
line.SetLineStyle(2)
line.Draw()
if key == 'trkChi2': c.firstPlot.GetXaxis().SetTitle('trk. #chi^{2}/dof')
c.cleanup('pdfs/NM1_2Mu2J_{}.pdf'.format(key), mode='LUMI')
def makeSimplePlots(PLOT_SPECS,
DISTRIBUTION_SPECS,
output_filename,
output_folder="pdfs/",
logy=False,
normalize=False,
make_legend=True):
importHistograms(DISTRIBUTION_SPECS)
canvas = Plotter.Canvas(logy=logy, lumi=PLOT_SPECS["lumi_str"])
Xrange_min = None
Xrange_max = None
Yrange_min = None
Yrange_max = None
for el in DISTRIBUTION_SPECS:
hist = el.getAttribute("histogram")
leg = el.getAttribute("legend")
if leg is None: leg = ''
if normalize: leg += ' (normalized)'
linecolor = el.getAttribute("linecolor")
linestyle = el.getAttribute("linestyle")
markercolor = el.getAttribute("markercolor")
markerstyle = el.getAttribute("markerstyle")
Xrange = el.getAttribute("Xrange")
Yrange = el.getAttribute("Yrange")
rebin = el.getAttribute("rebin")
if Xrange is not None:
# find the most inclusive x-axis ranges
if Xrange_min is not None:
Xrange_min = Xrange[0] if Xrange[0] < Xrange_min else Xrange_min
else:
Xrange_min = Xrange[0]
if Xrange_max is not None:
Xrange_max = Xrange[1] if Xrange[1] > Xrange_max else Xrange_max
else:
Xrange_max = Xrange[1]
if Yrange is not None:
# find the most inclusive y-axis ranges
if Yrange_min is not None:
Yrange_min = Yrange[0] if Yrange[0] < Yrange_min else Yrange_min
else:
Yrange_min = Yrange[0]
if Yrange_max is not None:
Yrange_max = Yrange[1] if Yrange[1] > Yrange_max else Yrange_max
else:
Yrange_max = Yrange[1]
# rebin histograms, if applicable
if rebin: hist.Rebin(rebin)
# normalize histograms, if applicable
if normalize and hist.Integral() != 0:
hist.Scale(1. / hist.Integral())
plot = Plotter.Plot(hist, leg, "l", "hist")
canvas.addMainPlot(plot)
if linecolor: plot.SetLineColor(linecolor)
if linestyle: plot.SetLineStyle(linestyle)
if markercolor: plot.SetMarkerColor(markercolor)
if markerstyle: plot.SetMarkerStyle(markerstyle)
RT.addBinWidth(plot)
# set custom axis ranges if specified in DISTRIBUTION_SPECS
if logy and Yrange_min <= 0.0: Yrange_min = 1e-3
if Xrange:
print('setting x ranges: {}, {}'.format(Xrange_min, Xrange_max))
canvas.firstPlot.GetXaxis().SetRangeUser(Xrange_min, Xrange_max)
if Yrange: canvas.firstPlot.GetYaxis().SetRangeUser(Yrange_min, Yrange_max)
if make_legend:
canvas.makeLegend(pos="tl", fontscale=0.77)
canvas.legend.resizeHeight()
fname = output_folder + "/" + output_filename
if logy: fname += "_logy"
if normalize: fname += "_norm"
canvas.finishCanvas()
canvas.save(fname, extList=[".pdf", ".root"])
canvas.deleteCanvas()
def compareFOMPlot(quantity, sp, sigmaBMode='GLOBAL'):
keys = FACTORS
for FACTOR in FACTORS:
s = HG.getHistogram(FILES['Signal'], (fs, sp),
'{}_{}'.format(quantity, FACTOR)).Clone()
if sigmaBMode == 'GLOBAL':
s.Scale(ScaleFactor(sp, 1, 1.e-2))
extra = 'GLOBAL'
DHists, DPConfig = HG.getDataHistograms(FILES['Data'],
'{}_1'.format(quantity),
addFlows=False)
b = DHists['{}_1'.format(quantity)]['data']
# get cumulatives
bCum = b.GetCumulative(CONFIG[quantity]['forward'])
sCum = s.GetCumulative(CONFIG[quantity]['forward'])
fom = {z: sCum.Clone() for z in ('ZBi', 'ZPL')}
nBins = sCum.GetNbinsX()
xAxis = sCum.GetXaxis()
# dictionaries instead of numbers because we have 2 sets of ZBi curves
fom_max = {z: 0. for z in ('ZBi', 'ZPL')}
opt_cut = {z: 0. for z in ('ZBi', 'ZPL')}
opt_s = {z: 0. for z in ('ZBi', 'ZPL')}
opt_b = {z: 0. for z in ('ZBi', 'ZPL')}
for ibin in range(1, nBins + 1):
S, B, cutVal, FOMs = calculateFOM(s, b, sCum, bCum, nBins, ibin,
xAxis,
CONFIG[quantity]['forward'])
for z in ('ZBi', 'ZPL'):
if FOMs[z] > fom_max[z]:
fom_max[z] = FOMs[z]
opt_cut[z] = cutVal
opt_s[z] = S
opt_b[z] = B
fom[z].SetBinContent(ibin, FOMs[z])
p = {
z: Plotter.Plot(fom[z], PRETTY_LEG[z], 'l', 'hist p')
for z in fom
}
colors = {'ZBi': R.kRed, 'ZPL': R.kBlue}
c = Plotter.Canvas(lumi='({} GeV, {} GeV, {} mm){}'.format(
sp[0], sp[1], sp[2], '' if FACTOR ==
1 else ' #rightarrow {} mm'.format(sp[2] / FACTOR)))
for z in fom:
c.addMainPlot(p[z])
p[z].setColor(colors[z], which='LM')
c.makeLegend(lWidth=0.1, pos='tr')
#c.legend.SetMargin(0.1)
c.legend.resizeHeight()
lines = {
z: R.TLine(opt_cut[z], 0., opt_cut[z],
max(fom_max.values()) * 1.1)
for z in fom
}
for z in fom:
lines[z].SetLineStyle(2)
lines[z].SetLineColor(colors[z])
lines[z].Draw()
for i, z in enumerate(fom.keys()):
c.drawText(text='#color[{:d}]{{opt = {:.1f}}}'.format(
colors[z], opt_cut[z]),
pos=(c.legend.GetX2(),
c.legend.GetY1() - .04 - i * .04),
align='br')
c.firstPlot.SetMinimum(0.)
c.firstPlot.SetMaximum(max(fom_max.values()) * 1.1)
c.firstPlot.setTitles(Y='Figure of Merit')
RT.addBinWidth(c.firstPlot)
c.cleanup('pdfs/COMPARE_FOM-{}_{}_{}_{}_{}_{}.pdf'.format(
extra, quantity, sp[0], sp[1], sp[2], FACTOR))
def makePerSamplePlots(selection=None):
rebinning_exceptions = ("pTdiff", "nCSCDTHits")
h = {}
p = {}
for dataset in HISTS:
if selection is not None:
selected_hists_names = getHistNames(dataset, *selection)
else:
selected_hists_names = HISTS[dataset]
for key in selected_hists_names:
# do not plot empty histograms in the interest of plotting time
if HISTS[dataset][key].GetEntries() == 0:
continue
if key not in h:
h[key] = HISTS[dataset][key].Clone()
else:
h[key].Add(HISTS[dataset][key])
for key in h:
RT.addFlows(h[key])
if h[key].GetNbinsX() >= 1000:
if any(["__" + var + "VAR" in key for var in rebinning_exceptions]):
print ("Do not rebin {}".format(key))
pass
else:
if "__L1pTresVAR" in key or "__L2pTresVAR" in key:
h[key].Rebin(2)
else:
h[key].Rebin(15)
elif h[key].GetNbinsX() >= 100:
if any(["__" + var + "VAR" in key for var in rebinning_exceptions]):
print ("Do not rebin {}".format(key))
pass
else:
h[key].Rebin(5)
else:
pass
if "lowerHemisphere" in key:
hs_req = "lower hemisphere"
elif "upperHemisphere" in key:
hs_req = "upper hemisphere"
else:
hs_req = None
if "oppositeCharges" in key:
pair_charge_req = "oppositely charged pairs"
elif "equalCharges" in key:
pair_charge_req = "equally charged pairs"
else:
pair_charge_req = None
if "posCharge" in key:
charge_req = "positive muon tracks"
elif "negCharge" in key:
charge_req = "negative muon tracks"
else:
charge_req = None
legName = ""
for req in (hs_req, pair_charge_req, charge_req):
if req is not None:
if legName != "":
legName += ", "
legName += req
p = Plotter.Plot(h[key], legName, "l", "hist")
for is_logy in (True, False):
fname = "pdfs/{}{}{}.pdf".format(
key, dataset_fname, ("_logy" if is_logy else "")
)
canvas = Plotter.Canvas(logy=is_logy, lumi=lumi)
canvas.addMainPlot(p)
if legName != "":
canvas.makeLegend(lWidth=0.25, pos="tl", fontscale=0.65)
canvas.legend.resizeHeight()
for var in RANGES:
if "__{}VAR".format(var) in key:
canvas.firstPlot.GetXaxis().SetRangeUser(
RANGES[var][0], RANGES[var][1]
)
p.SetLineColor(R.kBlue)
RT.addBinWidth(p)
# Gauss fit for L2 resolution plots
if any(
["__{}VAR".format(var) in key for var in L1RESOLUTIONVARIABLES]
) or any(["__{}VAR".format(var) in key for var in L2RESOLUTIONVARIABLES]):
# Trigger information for canvas
pave_triggerinfo = R.TPaveText(0.56, 0.38, 0.88, 0.51, "NDCNB")
pave_triggerinfo.SetTextAlign(13)
pave_triggerinfo.SetTextFont(42)
# pave_triggerinfo.SetTextSize(self.fontsize*.9)
pave_triggerinfo.SetMargin(0)
pave_triggerinfo.SetFillStyle(0)
pave_triggerinfo.SetFillColor(0)
pave_triggerinfo.SetLineStyle(0)
pave_triggerinfo.SetLineColor(0)
pave_triggerinfo.SetBorderSize(0)
pave_triggerinfo.AddText(0.0, 1.0, HLT_info)
pave_triggerinfo.AddText(0.0, 0.5, L1T_info)
pave_triggerinfo.Draw()
fit_xmin, fit_xmax = findFitRange(h[key])
func = R.TF1("f" + key, "gaus", fit_xmin, fit_xmax)
func.SetParameters(10.0, -0.1, 0.5)
func.SetLineStyle(2)
func.SetLineColor(R.kBlue + 2)
R.SetOwnership(func, 0)
h[key].Fit("f" + key, "RQN")
func.Draw("same")
pave_gaus = R.TPaveText(0.56, 0.63, 0.88, 0.83, "NDCNB")
pave_gaus.SetTextAlign(13)
pave_gaus.SetTextFont(42)
# pave_gaus.SetTextSize(self.fontsize*.9)
pave_gaus.SetMargin(0)
pave_gaus.SetFillStyle(0)
pave_gaus.SetFillColor(0)
pave_gaus.SetLineStyle(0)
pave_gaus.SetLineColor(0)
pave_gaus.SetBorderSize(0)
pave_gaus.AddText(0.0, 1.0, "Gaussian fit around maximum:")
pave_gaus.AddText(
0.06, 0.65, "Mean = {:2.3f}".format(func.GetParameter(1))
)
pave_gaus.AddText(
0.06, 0.45, "Sigma = {:2.3f}".format(func.GetParameter(2))
)
pave_gaus.AddText(
0.06, 0.25, "#chi^{{2}} = {:2.3f}".format(func.GetChisquare())
)
# count the histogram contents to the right of the upper
# fit limit (to get an estimate for the content in the tail)
h_content = 0
h_content_tail = 0
fit_xmax_bin = h[key].FindBin(fit_xmax)
for b in range(1, h[key].GetNbinsX() + 1):
h_content += h[key].GetBinContent(b)
if b > fit_xmax_bin:
h_content_tail += h[key].GetBinContent(b)
pave_gaus.AddText(
0.06,
0.05,
"Entries above {:2.2f} (max. fit range): {:2.1f}%".format(
fit_xmax, 100.0 * h_content_tail / h_content
),
)
pave_gaus.Draw()
try:
canvas.legend.moveLegend(X=0.393, Y=-0.01)
except:
# continue if there is no legend
pass
else:
# Trigger information for canvas
pave_triggerinfo = R.TPaveText(0.4, 0.75, 0.72, 0.88, "NDCNB")
pave_triggerinfo.SetTextAlign(13)
pave_triggerinfo.SetTextFont(42)
# pave_triggerinfo.SetTextSize(self.fontsize*.9)
pave_triggerinfo.SetMargin(0)
pave_triggerinfo.SetFillStyle(0)
pave_triggerinfo.SetFillColor(0)
pave_triggerinfo.SetLineStyle(0)
pave_triggerinfo.SetLineColor(0)
pave_triggerinfo.SetBorderSize(0)
pave_triggerinfo.AddText(0.0, 1.0, HLT_info)
pave_triggerinfo.AddText(0.0, 0.5, L1T_info)
pave_triggerinfo.Draw()
pave = canvas.makeStatsBox(p, color=R.kBlue)
pave_triggerinfo.Draw()
# find the corresponding d0 distribution in the given d0 bin
# and display its mean
try:
current_var = re.findall(r"__(.+)VAR", key)
if len(current_var) == 1:
current_var = current_var[0].split("_")[-1]
if current_var != "d0" and all(
[c in key for c in ("__d0GT", "__d0LT")]
):
d0_hist = key.replace("__{}VAR".format(current_var), "__d0VAR")
for idataset, dataset in enumerate(HISTS):
if idataset == 0:
h_d0 = HISTS[dataset][d0_hist].Clone()
else:
h_d0.Add(HISTS[dataset][d0_hist])
d0_mean = h_d0.GetMean()
# d0_mean = HISTS[dataset][d0_hist].GetMean()
d0_min = re.findall(r"__d0GT(\d+)p(\d+)", d0_hist)
if len(d0_min) > 0:
d0_min = float("{}.{}".format(d0_min[0][0], d0_min[0][1]))
else:
d0_min = float(re.findall(r"__d0GT(\d+)", d0_hist)[0])
d0_max = re.findall(r"__d0LT(\d+)p(\d+)", d0_hist)
if len(d0_max) > 0:
d0_max = float("{}.{}".format(d0_max[0][0], d0_max[0][1]))
else:
d0_max = float(re.findall(r"__d0LT(\d+)", d0_hist)[0])
pave_d0info = R.TPaveText(0.56, 0.53, 0.88, 0.61, "NDCNB")
pave_d0info.SetTextAlign(13)
pave_d0info.SetTextFont(42)
pave_d0info.SetMargin(0)
pave_d0info.SetFillStyle(0)
pave_d0info.SetFillColor(0)
pave_d0info.SetLineStyle(0)
pave_d0info.SetLineColor(0)
pave_d0info.SetBorderSize(0)
pave_d0info.AddText(
0.0, 1.0, "{} cm < d_{{0}} < {} cm".format(d0_min, d0_max)
)
pave_d0info.AddText(
0.0, 0.0, "#LTd_{{0}}#GT = {:4.3f} cm".format(d0_mean)
)
pave_d0info.Draw()
except KeyError:
# not all of the histograms have d0 equivalents (e.g.,
# 'oppositeCharges' pair histos,...)
print (
"[PLOTTER WARNING] Error processing d0 information "
"for {}; will not be printed on canvas".format(key)
)
canvas.cleanup(fname)
return
def makeKinkFOMPlot(quantity, masses, sigmaBMode='DEFAULT'):
points = sorted(
[sp for sp in SignalInfo if sp[0] == masses[0] and sp[1] == masses[1]],
key=lambda x: x[2])
s = {
points[0]:
HG.getHistogram(FILES['Signal'], (fs, points[0]),
'{}_1'.format(quantity)).Clone(),
points[1]:
HG.getHistogram(FILES['Signal'], (fs, points[1]),
'{}_10'.format(quantity)).Clone(),
}
if sigmaBMode == 'DEFAULT':
s[points[0]].Scale(ScaleFactor(points[0], 1))
s[points[1]].Scale(ScaleFactor(points[1], 10))
extra = ''
elif sigmaBMode == 'SAME':
s[points[0]].Scale(ScaleFactor(points[0], 1))
s[points[1]].Scale(ScaleFactor(points[0], 1))
extra = '_SAME'
elif sigmaBMode == 'GLOBAL':
s[points[0]].Scale(ScaleFactor(points[0], 1, 1.e-2))
s[points[1]].Scale(ScaleFactor(points[1], 1, 1.e-2))
extra = '_GLOBAL'
DHists, DPConfig = HG.getDataHistograms(FILES['Data'],
'{}_1'.format(quantity),
addFlows=False)
b = DHists['{}_1'.format(quantity)]['data']
# get cumulatives
bCum = b.GetCumulative(CONFIG[quantity]['forward'])
sCum = {p: s[p].GetCumulative(CONFIG[quantity]['forward']) for p in points}
fom = {p: sCum[p].Clone() for p in points}
nBins = sCum[points[0]].GetNbinsX()
xAxis = sCum[points[0]].GetXaxis()
# dictionaries instead of numbers because we have 2 sets of ZBi curves
fom_max = {p: 0. for p in points}
opt_cut = {p: 0. for p in points}
opt_s = {p: 0. for p in points}
opt_b = {p: 0. for p in points}
for ibin in range(1, nBins + 1):
for p in points:
S, B, cutVal, FOMs = calculateFOM(s[p], b, sCum[p], bCum, nBins,
ibin, xAxis,
CONFIG[quantity]['forward'])
if FOMs[FIGURE_OF_MERIT] > fom_max[p]:
fom_max[p] = FOMs[FIGURE_OF_MERIT]
opt_cut[p] = cutVal
opt_s[p] = S
opt_b[p] = B
fom[p].SetBinContent(ibin, FOMs[FIGURE_OF_MERIT])
pl = {
points[0]:
Plotter.Plot(fom[points[0]],
'c#tau = {} mm, nominal'.format(points[0][2]), 'l',
'hist p'),
points[1]:
Plotter.Plot(fom[points[1]],
'c#tau = {} mm, reweighted'.format(points[0][2]), 'l',
'hist p'),
}
colors = {
points[0]: R.kBlue,
points[1]: R.kRed,
}
c = Plotter.Canvas(lumi='({} GeV, {} GeV)'.format(*masses))
c.addMainPlot(pl[points[0]])
c.addMainPlot(pl[points[1]])
for p in points:
pl[p].setColor(colors[p], which='LM')
c.makeLegend(lWidth=0.3, pos='tr')
c.legend.SetMargin(0.1)
c.legend.resizeHeight()
lines = {
p: R.TLine(opt_cut[p], 0., opt_cut[p],
max(fom_max.values()) * 1.1)
for p in points
}
for p in points:
lines[p].SetLineStyle(2)
lines[p].SetLineColor(colors[p])
lines[p].Draw()
for i, p in enumerate(points):
c.drawText(text='#color[{:d}]{{opt = {:.1f}}}'.format(
colors[p], opt_cut[p]),
pos=(c.legend.GetX2(), c.legend.GetY1() - .04 - i * .04),
align='br')
c.firstPlot.SetMinimum(0.)
c.firstPlot.SetMaximum(max(fom_max.values()) * 1.1)
c.firstPlot.setTitles(Y=PRETTY_LEG)
RT.addBinWidth(c.firstPlot)
c.cleanup('pdfs/KINK_FOM{}_{}_{}_{}_{}.pdf'.format(extra, quantity,
masses[0], masses[1],
FIGURE_OF_MERIT))
def makeResPlots(metric, quantity, sp=None):
PRETTY = {
'pTRes_hits_less': {
'mnice': 'p_{T} res.',
'qnice': 'N(hits)',
'leg': 'N(hits) #leq 12',
'col': R.kRed
},
'pTRes_hits_more': {
'mnice': 'p_{T} res.',
'qnice': 'N(hits)',
'leg': 'N(hits) > 12',
'col': R.kBlue
},
'pTRes_fpte_less': {
'mnice': 'p_{T} res.',
'qnice': '#sigma_{p_{T}}/p_{T}',
'leg': '#sigma_{p_{T}}/p_{T} < 1',
'col': R.kBlue
},
'pTRes_fpte_more': {
'mnice': 'p_{T} res.',
'qnice': '#sigma_{p_{T}}/p_{T}',
'leg': '#sigma_{p_{T}}/p_{T} #geq 1',
'col': R.kRed
},
'qdiff_hits_less': {
'mnice': 'charge diff.',
'qnice': 'N(hits)',
'leg': 'N(hits) #leq 12',
'col': R.kRed
},
'qdiff_hits_more': {
'mnice': 'charge diff.',
'qnice': 'N(hits)',
'leg': 'N(hits) > 12',
'col': R.kBlue
},
'qdiff_fpte_less': {
'mnice': 'charge diff.',
'qnice': '#sigma_{p_{T}}/p_{T}',
'leg': '#sigma_{p_{T}}/p_{T} < 1',
'col': R.kBlue
},
'qdiff_fpte_more': {
'mnice': 'charge diff.',
'qnice': '#sigma_{p_{T}}/p_{T}',
'leg': '#sigma_{p_{T}}/p_{T} #geq 1',
'col': R.kRed
},
}
witches = ('less', 'more') if quantity == 'fpte' else ('more', 'less')
hkeys = ['{}_{}_{}'.format(metric, quantity, which) for which in witches]
if sp is None:
HISTS = HG.getAddedSignalHistograms(FILES['Signal'], '2Mu2J', hkeys)
else:
HISTS = {}
for key in hkeys:
HISTS[key] = HG.getHistogram(FILES['Signal'], ('2Mu2J', sp),
key).Clone()
PLOTS = {}
for key in hkeys:
HISTS[key].Scale(1. /
HISTS[key].Integral(0, HISTS[key].GetNbinsX() + 1))
#RT.addFlows(HISTS[key])
PLOTS[key] = Plotter.Plot(HISTS[key], PRETTY[key]['leg'], 'l', 'hist')
#canvas = Plotter.Canvas(lumi='{} by {}'.format(PRETTY[hkeys[0]]['mnice'], PRETTY[hkeys[0]]['qnice']))
lumi = 'H#rightarrow2X#rightarrow2#mu'
if sp is None:
lumi += ', all samples combined'
else:
lumi += ' ({} GeV, {} GeV, {} mm)'.format(*sp)
canvas = Plotter.Canvas(lumi=lumi, cWidth=600 if ARGS.SQUARE else 800)
for key in hkeys:
canvas.addMainPlot(PLOTS[key])
PLOTS[key].setColor(PRETTY[key]['col'], which='L')
canvas.firstPlot.SetMinimum(0.)
canvas.setMaximum()
if metric == 'qdiff':
canvas.firstPlot.SetMaximum(1.)
canvas.firstPlot.setTitles(Y='Density')
if 'qdiff' in hkeys[0]:
canvas.firstPlot.SetNdivisions(3)
canvas.makeLegend(lWidth=0.27, pos='tr')
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
if ARGS.SQUARE:
canvas.firstPlot.scaleTitleOffsets(1.1, 'X')
if metric == 'pTRes':
canvas.firstPlot.scaleTitleOffsets(1.3, 'Y')
canvas.cleanup('pdfs/QCUTRES_Sig_{}_{}_{}.pdf'.format(
metric, quantity, 'Global' if sp is None else SPStr(sp)),
mode='LUMI')
def makeEffPlots(quantity, fs, SP=None):
range_limits = {
'pT': [0., 300.],
'eta': None,
'phi': None,
'd0': None,
'Lxy': [0., (500. if SP is None else \
SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['xmax'])],
'deltaR': None,
'mass': None,
'cosAlpha': None,
'dimuonPTOverM': [0, 10],
'XBeta': None,
}
HKeys = {
'GEN_Eff' : 'GEN_{}Num' ,
'GEN_Den' : 'GEN_{}Den' ,
'DSA_Eff' : 'DSA_{}Num' ,
'DSA_Den' : 'DSA_{}Den' ,
'RSA_Eff' : 'RSA_{}Num' ,
'RSA_Den' : 'RSA_{}Den' ,
}
for key in HKeys:
HKeys[key] = HKeys[key].format(quantity, 'HTo2XTo'+fs)
h = {}
p = {}
g = {}
hm = {}
if SP is None:
for i, sp in enumerate(SIGNALPOINTS):
if i == 0:
for key in HKeys:
h[key] = HISTS[(fs, sp)][HKeys[key]].Clone()
h[key].SetDirectory(0)
else:
for key in HKeys:
h[key].Add(HISTS[(fs, sp)][HKeys[key]])
else:
sp = SP
for key in HKeys:
h[key] = HISTS[(fs, sp)][HKeys[key]].Clone()
h[key].SetDirectory(0)
for key in HKeys:
RT.addFlows(h[key])
nConcatBins = 20 if SP is None else \
SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['rebin']
h[key].Rebin(nConcatBins)
# h[key].Rebin(30)
NumDens = (
('GEN_Eff' , 'GEN_Den' , 'GEN' , R.kGreen ),
('DSA_Eff' , 'DSA_Den' , 'DSA' , R.kBlue ),
('RSA_Eff' , 'RSA_Den' , 'RSA' , R.kRed ),
)
for num, den, leg, col in NumDens:
g[num] = R.TGraphAsymmErrors(h[num], h[den], 'cp')
g[num].SetNameTitle('g_'+num, ';'+h[num].GetXaxis().GetTitle()+'; Trigger Efficiency')
# g[num].GetXaxis().SetRangeUser(0., 30.)
if range_limits[quantity] is not None:
g[num].GetXaxis().SetLimits(
range_limits[quantity][0],
range_limits[quantity][1])
p[num] = Plotter.Plot(g[num], leg, 'elp', 'pe')
h[num].Sumw2()
h[den].Sumw2()
ratio_hist = R.TEfficiency(h[num], h[den])
eff_sum_num = 0
eff_sum_den = 0
for binx in range(1,h[num].GetXaxis().GetNbins()+2):
# if h[num].GetBinLowEdge(binx) > 250: continue
glob_bin = ratio_hist.GetGlobalBin(binx)
efferror = max(ratio_hist.GetEfficiencyErrorLow(glob_bin),
ratio_hist.GetEfficiencyErrorUp(glob_bin))
if efferror != 0:
eff_sum_num += ratio_hist.GetEfficiency(glob_bin) / \
(efferror*efferror)
if ratio_hist.GetEfficiency(glob_bin) != 0:
eff_sum_den += 1/(efferror*efferror)
if eff_sum_den != 0:
hm[num] = eff_sum_num / eff_sum_den
FIRST = (0, 3)
# SECOND = (3, 5)
CHARGE = ''
for SECTION in (FIRST,):
fraction_str = '' if SP is None else '[{}%, {}%]'.format(
round(SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['fractions'][0], 1),
round(SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['fractions'][1], 1))
canvas = Plotter.Canvas(lumi = fs if SP is None else \
'{} ({} GeV, {} GeV, {} mm) ' \
'#scale[0.7]{{{fraction_str}}}'.format(
fs, *SP, fraction_str=fraction_str))
for i in range(SECTION[0], SECTION[1]):
key = NumDens[i][0]
col = NumDens[i][3]
canvas.addMainPlot(p[key])
p[key].SetMarkerColor(col)
p[key].SetLineColor(col)
# if quantity in ['Lxy','pT']:
# axis_min = p[key].GetXaxis().GetBinLowEdge(1)
# axis_max = p[key].GetXaxis().GetBinLowEdge(p[key].GetXaxis().GetNbins()+1)
# hline = R.TLine(axis_min, hm[key], range_limits[quantity][1], hm[key])
# R.SetOwnership(hline, 0)
# hline.SetLineColor(col)
# hline.Draw()
canvas.makeLegend(pos='tr')
canvas.legend.moveLegend(X=-0.18)
canvas.legend.resizeHeight()
canvas.firstPlot.SetMinimum(0.)
canvas.firstPlot.SetMaximum(1.)
RT.addBinWidth(canvas.firstPlot)
if quantity == 'pT':
vline = R.TLine(28.,0.,28.,1.) # draw vertical line at 28 GeV
R.SetOwnership(vline, 0)
vline.SetLineColor(15)
vline.Draw()
canvas.cleanup(OUTPUT_PATH + FILENAME_OUT.format('STE', LXYMIN, LXYMAX, quantity, fs, 'Global' if SP is None else SPStr(SP)))
def makeCombinedPlots(categories, selection=None, exclude=None, logic="and"):
rebinning_exceptions = ("nCSCDTHits",)
h = {}
p = {}
# import all relevant histograms
for dataset in HISTS:
if selection and exclude:
selected_hists_names = getHistNames(
dataset, *selection, exclude=exclude, logic=logic
)
elif selection and not exclude:
selected_hists_names = getHistNames(dataset, *selection, logic=logic)
elif not selection and exclude:
selected_hists_names = getHistNames(
dataset, "", exclude=exclude, logic=logic
)
else:
selected_hists_names = HISTS[dataset]
for key in selected_hists_names:
if not any([cat in key for cat, __ in categories]):
continue
search_res = re.search(r"__(.+)VAR", key)
if search_res:
variable = search_res.group(1)
else:
print ("Skipping {} (unidentifiable variable)...".format(key))
continue
if variable not in h.keys():
h[variable] = {}
for category, __ in categories:
if not category in key:
continue
if category in h[variable]:
h[variable][category].Add(HISTS[dataset][key])
else:
h[variable][category] = HISTS[dataset][key].Clone()
# prepare the histograms
for variable in h:
for category in h[variable]:
RT.addFlows(h[variable][category])
if h[variable][category].GetNbinsX() >= 1000:
if variable in rebinning_exceptions:
print ("Do not rebin for variable {}".format(variable))
pass
else:
h[variable][category].Rebin(15)
elif h[variable][category].GetNbinsX() >= 100:
if variable in rebinning_exceptions:
print ("Do not rebin for variable {}".format(variable))
pass
else:
h[variable][category].Rebin(5)
else:
pass
# start creating plots
for variable in h:
p[variable] = {}
# find the best vertical axes ranges
realmin = float("inf")
realmax = -float("inf")
for category, category_name in categories:
p[variable][category] = Plotter.Plot(
h[variable][category], category_name, "l", "hist"
)
key_fname = h[variable][category].GetName()
key_fname = key_fname.replace(category, "")
if len(HISTS.keys()) > 1:
search_res = re.search(r"(_*?NoBPTXRun\d+[A-Z][_-]07Aug17)", key_fname)
if search_res:
key_fname = key_fname.replace(search_res.group(0), "")
else:
print (
"Could not identify datset. Dataset name will not be "
"stripped from the output file names"
)
if p[variable][category].GetMaximum() > realmax:
realmax = p[variable][category].GetMaximum()
if p[variable][category].GetMaximum() < realmin:
realmin = p[variable][category].GetMinimum()
for is_logy in (True, False):
palette = Plotter.ColorPalette([867, 417, 600, 600, 801, 632])
fname = "pdfs/comb_{}{}.pdf".format(key_fname, ("_logy" if is_logy else ""))
canvas = Plotter.Canvas(logy=is_logy, lumi="NoBPTXRun2016[D+E]-07Aug17")
for category, category_name in categories:
canvas.addMainPlot(p[variable][category])
p[variable][category].SetLineColor(palette.getNextColor())
if "goodQuality" in category:
p[variable][category].SetLineStyle(2)
RT.addBinWidth(p[variable][category])
if variable in RANGES:
canvas.firstPlot.GetXaxis().SetRangeUser(
RANGES[variable][0], RANGES[variable][1]
)
canvas.makeLegend(lWidth=0.3, pos="tr", fontscale=0.65)
canvas.legend.resizeHeight()
canvas.legend.moveLegend(X=-0.2, Y=-0.13)
# trigger information for canvas
pave_triggerinfo = R.TPaveText(0.4, 0.75, 0.72, 0.88, "NDCNB")
pave_triggerinfo.SetTextAlign(13)
pave_triggerinfo.SetTextFont(42)
# pave_triggerinfo.SetTextSize(self.fontsize*.9)
pave_triggerinfo.SetMargin(0)
pave_triggerinfo.SetFillStyle(0)
pave_triggerinfo.SetFillColor(0)
pave_triggerinfo.SetLineStyle(0)
pave_triggerinfo.SetLineColor(0)
pave_triggerinfo.SetBorderSize(0)
pave_triggerinfo.AddText(0.0, 1.0, HLT_info)
pave_triggerinfo.AddText(0.0, 0.5, L1T_info)
pave_triggerinfo.Draw()
if is_logy and realmin == 0:
realmin = 0.5
canvas.firstPlot.GetYaxis().SetRangeUser(realmin * 0.8, realmax * 1.2)
# canvas.cleanup(fname.replace('.pdf','.root'))
canvas.cleanup(fname)
def makeStackPlots(DataMC=False, logy=False):
BGORDER = ('WJets', 'WW', 'WZ', 'ZZ', 'tW', 'tbarW', 'ttbar', 'DY10to50',
'DY50toInf')
for hkey in HISTS['DY50toInf']:
h = {
# 'Data' : HISTS['DoubleMuonRun2016D-07Aug17'][hkey].Clone(),
# 'Signal' : HISTS[('4Mu', (125, 20, 13)) ][hkey].Clone(),
'BG': R.THStack('hBG', '')
}
PConfig = {
# 'Data' : ('DoubleMuon2016D' , 'pe', 'pe' ),
# 'Signal' : ('H#rightarrow2X#rightarrow4#mu', 'l' , 'hist'),
'BG': ('', '', 'hist'),
}
PC = HistogramGetter.PLOTCONFIG
for key in BGORDER:
h[key] = HISTS[key][hkey].Clone()
RT.addFlows(h[key])
if h[key].GetNbinsX() > 100: h[key].Rebin(10)
h[key].Scale(PC[key]['WEIGHT'])
PConfig[key] = (PC[key]['LATEX'], 'f', 'hist')
h['BG'].Add(h[key])
p = {}
for key in h:
p[key] = Plotter.Plot(h[key], *PConfig[key])
fname = 'pdfs/NM1_{}_Stack{}.pdf'.format(hkey, '-Log' if logy else '')
for key in BGORDER:
p[key].setColor(PC[key]['COLOR'], which='LF')
canvas = Plotter.Canvas(ratioFactor=0. if not DataMC else 1. / 3.,
cHeight=600 if not DataMC else 800,
logy=logy)
canvas.addMainPlot(p['BG'])
# canvas.addMainPlot(p['Data'])
# canvas.addMainPlot(p['Signal'])
canvas.lumi += ' : |#Delta#Phi| ' + ('<' if '_Less' in key else
'>') + ' #pi/2'
canvas.makeLegend(lWidth=.27, pos='tr', autoOrder=False, fontscale=0.8)
# canvas.addLegendEntry(p['Data' ])
for key in reversed(BGORDER):
canvas.addLegendEntry(p[key])
# canvas.addLegendEntry(p['Signal'])
canvas.legend.resizeHeight()
p['BG'].setTitles(X=p['WJets'].GetXaxis().GetTitle(),
Y='Normalized Counts')
RT.addBinWidth(p['BG'])
canvas.firstPlot.SetMaximum(h['BG'].GetStack().Last().GetMaximum() *
1.05)
#canvas.firstPlot.SetMaximum(1.e-4)
# if DataMC:
# canvas.makeRatioPlot(p['Data'].plot, p['BG'].plot.GetStack().Last())
# p['Signal' ].SetLineStyle(2)
# p['Signal' ].SetLineColor(R.kRed)
canvas.cleanup(fname)
def makeSimplePlots(quantity, fs, SP=None, normalize=False):
range_limits = {
'pT': [0., 300.],
'eta': None,
'phi': None,
'd0': None,
'Lxy': [0., (500. if SP is None else \
SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['xmax'])],
'deltaR': None,
'mass': None,
'cosAlpha': None,
'dimuonPTOverM': [0, 10],
'XBeta': None,
}
HKeys = {
'GEN_Den' : 'GEN_{}Den',
'DSA_Den' : 'DSA_{}Den',
'RSA_Den' : 'RSA_{}Den',
}
for key in HKeys:
HKeys[key] = HKeys[key].format(quantity, 'HTo2XTo'+fs)
h = {}
p = {}
if SP is None:
for i, sp in enumerate(SIGNALPOINTS):
if i == 0:
for key in HKeys:
h[key] = HISTS[(fs, sp)][HKeys[key]].Clone()
h[key].Sumw2()
h[key].SetDirectory(0)
else:
for key in HKeys:
h[key].Sumw2()
h[key].Add(HISTS[(fs, sp)][HKeys[key]])
else:
for key in HKeys:
h[key] = HISTS[(fs, SP)][HKeys[key]].Clone()
h[key].Sumw2()
if normalize is True and h[key].Integral() != 0:
h[key].Scale(1/h[key].Integral())
h[key].SetDirectory(0)
for key in HKeys:
RT.addFlows(h[key])
nConcatBins = 20 if SP is None else \
SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['rebin']
h[key].Rebin(nConcatBins)
if quantity == 'deltaR':
ratio_cut = 0.5
hist_ratios = {}
for key in HKeys:
num_before_cut = 0
num_after_cut = 0
for i in range(h[key].GetNbinsX()+1):
if h[key].GetXaxis().GetBinCenter(i) < ratio_cut:
num_before_cut += h[key].GetBinContent(i)
else:
num_after_cut += h[key].GetBinContent(i)
if num_before_cut+num_after_cut != 0:
hist_ratios[key] = 1.0*num_before_cut/(num_before_cut+num_after_cut)
else:
hist_ratios[key] = -1
HistSpecs = (
('GEN_Den', 'GEN', R.kGreen, 'Yield [a.u.]'),
('DSA_Den', 'DSA', R.kBlue, 'Yield [a.u.]'),
('RSA_Den', 'RSA', R.kRed, 'Yield [a.u.]'),
)
for key, leg, col, yTitle in HistSpecs:
if range_limits[quantity] is not None:
h[key].GetXaxis().SetRangeUser(
range_limits[quantity][0],
range_limits[quantity][1])
h[key].SetNameTitle('h_'+key,
';'+h[key].GetXaxis().GetTitle() + '; ' + \
('Normalized ' if normalize is True else '') + yTitle)
# leg += (': yield(#Delta R<0.5) #times 100 / (total yield) = {}'.format(
# round(hist_ratios[key]*100,2)) if quantity == 'deltaR' else '')
p[key] = Plotter.Plot(h[key], leg, '', 'hist e1 x0')
FIRST = (0, 3)
CHARGE = ''
for SECTION in (FIRST,):
fraction_str = '' if SP is None else '[{}%, {}%]'.format(
round(SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['fractions'][0], 1),
round(SAMPLE_SPECS[fs]['{}_{}_{}'.format(*SP)]['fractions'][1], 1))
canvas = Plotter.Canvas(lumi = fs if SP is None else \
'{} ({} GeV, {} GeV, {} mm) ' \
'#scale[0.7]{{{fraction_str}}}'.format(
fs, *SP, fraction_str=fraction_str))
for i in range(SECTION[0], SECTION[1]):
key = HistSpecs[i][0]
col = HistSpecs[i][2]
yTitle = HistSpecs[i][3]
canvas.addMainPlot(p[key])
p[key].SetMarkerColor(col)
p[key].SetLineColor(col)
# p[key].firstPlot.SetYTitle(yTitle)
canvas.makeLegend(pos='tl')
canvas.legend.moveLegend(X=0.15)
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
canvas.cleanup(OUTPUT_PATH + FILENAME_OUT.format('STD', LXYMIN, LXYMAX, quantity, fs, 'Global' if SP is None else SPStr(SP)))