def makeColorPlot(MUON, fs, quantity, sp=None, q2=None):
if q2 is None:
fstring = '{M}_{Q}VS{Q}'.format(M=MUON, Q=quantity)
else:
fstring = '{M}_{Q}ResVS{Q2}'.format(M=MUON, Q=quantity, Q2=q2)
if sp is None:
for i, SP in enumerate(SIGNALPOINTS):
if i == 0:
h = HistogramGetter.getHistogram(f, (fs, SP), fstring).Clone()
else:
h.Add(HistogramGetter.getHistogram(f, (fs, SP), fstring).Clone())
fname = 'pdfs/SRR_{}_{}HTo2XTo{}_Global.pdf'.format(fstring, 'Trig-' if TRIGGER else '', fs)
else:
h = HistogramGetter.getHistogram(f, (fs, sp), fstring).Clone()
fname = 'pdfs/SRR_{}_{}HTo2XTo{}_{}.pdf'.format(fstring, 'Trig-' if TRIGGER else '', fs, SPStr(sp))
h.Rebin2D(10, 10)
p = Plotter.Plot(h, '', '', 'colz')
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, *sp) if sp is not None else fs)
canvas.mainPad.SetLogz(True)
canvas.addMainPlot(p)
canvas.scaleMargins(1.75, edges='R')
canvas.scaleMargins(0.8, edges='L')
canvas.cleanup(fname)
def makeIndividualPlots(obj, dtype, key):
if type(key) == tuple:
fs, sp = key
lumi = SPLumiStr(fs, *sp)
fname = 'pdfs/CutTable_{}-{}_{}HTo2XTo{}_{}.pdf'.format(obj, dtype, 'Trig-' if TRIGGER else '', fs, SPStr(sp))
else:
sample = key
lumi = sample
fname = 'pdfs/CutTable_{}-{}_{}.pdf'.format(obj, dtype, sample)
p = Plotter.Plot(HISTS[obj][dtype][key], '', '', 'hist')
canvas = Plotter.Canvas(lumi=lumi)
canvas.addMainPlot(p)
canvas.firstPlot.SetMaximum(1.)
canvas.firstPlot.SetMinimum(0.)
#canvas.firstPlot.SetMarkerColor(R.kBlue)
#canvas.firstPlot.SetLineColor(R.kBlue)
canvas.firstPlot.SetLineColor(4000)
canvas.firstPlot.SetFillColor(R.kOrange)
for ibin in xrange(1, p.GetNbinsX()+1):
canvas.drawText(text='{:.2f}'.format(p.GetBinContent(ibin)), pos=(ibin-0.5, 0.1), align='cc', NDC=False)
canvas.cleanup(fname)
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 makeColorPlots(key):
for ref in HISTS:
if not type(ref) == tuple: 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])
else:
name = ref
lumi = HistogramGetter.PLOTCONFIG[ref]['LATEX']
if '_Matched' in key: continue
h = HISTS[ref][key].Clone()
h.Rebin2D(10, 10)
p = Plotter.Plot(h, '', '', 'colz')
canvas = Plotter.Canvas(lumi=lumi)
#canvas.mainPad.SetLogz(True)
canvas.addMainPlot(p)
canvas.scaleMargins(1.75, edges='R')
canvas.scaleMargins(0.8, edges='L')
fname = 'pdfs/{}{}_{}.pdf'.format(key, CUTSTRING, name)
canvas.cleanup(fname)
def makeDSASignal2DPlots():
for quantity in ('pT', 'eta', 'trkChi2'):
hkey = 'DSA-12-' + quantity
HISTS = HG.getAddedSignalHistograms(FILES[fs], fs, (hkey, ))
if 'trkChi2' not in hkey: HISTS[hkey].Rebin2D(10, 10)
for sp in SIGNALPOINTS:
HISTS[sp] = HG.getHistogram(FILES[fs], (fs, sp), hkey).Clone()
if 'trkChi2' not in hkey: HISTS[sp].Rebin2D(10, 10)
opt = 'colz'
#opt = 'scat=0.2'
PLOTS = {hkey: Plotter.Plot(HISTS[hkey], '', '', opt)}
for sp in SIGNALPOINTS:
PLOTS[sp] = Plotter.Plot(HISTS[sp], '', '', opt)
for sp in [
hkey,
] + SIGNALPOINTS:
canvas = Plotter.Canvas(lumi=fs + lumiExtra.get(CUTSTRING) if
type(sp) != tuple else SPLumiStr(fs, *sp))
canvas.addMainPlot(PLOTS[sp])
canvas.mainPad.SetLogz()
if quantity == 'trkChi2':
canvas.firstPlot.GetXaxis().SetRangeUser(0., 10.)
canvas.firstPlot.GetYaxis().SetRangeUser(0., 10.)
canvas.scaleMargins(1.75, edges='R')
canvas.scaleMargins(0.8, edges='L')
canvas.cleanup('pdfs/ZEP_2D_{}_{}_{}_{}.pdf'.format(
quantity, CUTSTRING, fs,
'Global' if type(sp) != tuple else SPStr(sp)))
def makeLxyEffPlot(key, colorAxis, fs, sp, pTCut=''):
config = {
'Correct': ('Correct', 'Matches'),
}
if colorAxis == 'nMuons':
num, den = config[key]
nums = ['Lxy' + pTCut + '_n' + num + '_' + m for m in mnames]
dens = ['Lxy' + pTCut + '_n' + den + '_' + m for m in mnames]
tags = list(set(nums + dens))
legs = {
num: m if 'All' in m else m + ' #mu'
for num, m in zip(nums, mnames)
}
cols = {num: c for num, c in zip(nums, colors)}
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
for z in h:
h[z].Rebin(10)
p = {}
graphs = {}
for num, den in zip(nums, dens):
realDen = h[den].Clone()
graphs[num] = R.TGraphAsymmErrors(h[num], realDen, 'cp')
p[num] = Plotter.Plot(graphs[num], legs[num], 'l', 'px')
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs)
for tag in nums:
canvas.addMainPlot(p[tag])
canvas.firstPlot.SetMaximum(1.01)
canvas.firstPlot.SetMinimum(0.)
canvas.firstPlot.setTitles(X=h[tags[0]].GetXaxis().GetTitle(),
Y='Efficiency')
for tag in p:
p[tag].setColor(cols[tag], which='LM')
canvas.makeLegend(lWidth=.275, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/RA_{}-Lxy{}-{}{}_HTo2XTo{}_{}.pdf'.format(
'ComboMu' if colorAxis == 'nMuons' else 'ComboEff', pTCut, key,
ARGS.CUTSTRING, fs,
SPStr(sp) if sp is not None else 'Global'))
def makeDistPlot(quantity, criteria, fs, sp=None):
# configy type stuff
legs = ('All', 'Matched', 'NotMatched')
tags = [
quantity + '_' + ('All' + ('-4' if '-4' in criteria else '')
if 'All' in leg else criteria + '_' + leg)
for leg in legs
]
cols = (R.kBlack, R.kBlue, R.kRed)
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
# make plots
p = {}
for i, tag in enumerate(tags):
p[tag] = Plotter.Plot(h[tag], legs[i], 'l', 'hist')
# canvas, plots, min max
logy = True
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs,
logy=logy)
for tag in tags:
canvas.addMainPlot(p[tag])
canvas.setMaximum()
if not logy:
canvas.firstPlot.SetMinimum(0)
else:
canvas.firstPlot.SetMinimum(1.)
if 'Lxy' in quantity:
canvas.firstPlot.GetXaxis().SetRangeUser(0., 330.)
# colors
for i, tag in enumerate(tags):
p[tag].SetLineColor(cols[i])
# legend, cleanup
canvas.makeLegend(lWidth=.2, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/LCD_{}Dist_{}{}_HTo2XTo{}_{}.pdf'.format(
quantity, criteria, ARGS.CUTSTRING, fs,
SPStr(sp) if sp is not None else 'Global'))
def makeStackPlot(key, colorAxis, fs, sp):
if colorAxis == 'nMuons':
tags = ['n' + key + '_' + m for m in mnames[1:]]
legs = {tag: m + ' #mu' for tag, m in zip(tags, mnames[1:])}
cols = {tag: R.kRed + i for i, tag in enumerate(tags)}
elif colorAxis == 'Eff':
tags = ['n' + k + '_' + key for k in hnames[1:]]
legs = {tag: k for tag, k in zip(tags, hnames[1:])}
cols = {tag: c for tag, c in zip(tags, colors[1:])}
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
h['stack'] = R.THStack('hBG' + key, '')
p = {}
for tag in tags:
if fs == '4Mu' and 'Event' in tag and colorAxis == 'Eff':
h[tag].Scale(2.)
h['stack'].Add(h[tag])
p['stack'] = Plotter.Plot(h['stack'], '', '',
'hist' if colorAxis == 'nMuons' else 'nostack')
for tag in tags:
p[tag] = Plotter.Plot(h[tag], legs[tag], 'f', 'hist')
for tag in tags:
p[tag].setColor(cols[tag], which='LMF')
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs)
for tag in ('stack', ):
canvas.addMainPlot(p[tag])
if colorAxis == 'nMuons':
canvas.setMaximum(recompute=True)
canvas.firstPlot.SetMinimum(0.)
canvas.makeLegend(lWidth=.2, pos='tr', autoOrder=False)
canvas.firstPlot.setTitles(X=h[tags[0]].GetXaxis().GetTitle(), Y='Counts')
for tag in tags:
canvas.addLegendEntry(p[tag])
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/RA_{}-{}{}_HTo2XTo{}_{}.pdf'.format(
'StackMu' if colorAxis == 'nMuons' else 'StackEff', key,
ARGS.CUTSTRING, fs, sp if sp is not None else 'Global'))
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 makePTCutPlot(fs, sp=None):
# configy type stuff
legs = ('All', 'Matched', 'Wrong', 'Right', 'Hopeless', 'Lost')
tags = ['pT_' + tag for tag in legs]
cols = (R.kBlack, R.kGreen, R.kOrange, R.kBlue, R.kRed, R.kMagenta)
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
# make plots
p = {}
for i, tag in enumerate(tags):
p[tag] = Plotter.Plot(h[tag], legs[i], 'l', 'hist')
# canvas, plots, min max
logy = True
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs,
logy=logy)
for tag in tags:
canvas.addMainPlot(p[tag])
canvas.setMaximum()
if not logy:
canvas.firstPlot.SetMinimum(0)
else:
canvas.firstPlot.SetMinimum(1.)
#canvas.firstPlot.GetXaxis().SetRangeUser(0., 200.)
canvas.firstPlot.GetXaxis().SetRangeUser(0., 30.)
# colors
for i, tag in enumerate(tags):
p[tag].SetLineColor(cols[i])
# legend, cleanup
canvas.makeLegend(lWidth=.2, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/HPD_pTDist_HTo2XTo{}_{}.pdf'.format(
fs,
SPStr(sp) if sp is not None else 'Global'))
def makePerSamplePlots():
for ref in HISTS:
for key in HISTS[ref]:
if 'DenVS' in key: continue
matches = re.match(r'(.*)EffVS(.*)', key)
cut = matches.group(1)
val = matches.group(2)
if cut in Selections.CutLists['MuonCutList'] and val == 'Lxy':
continue
if cut in Selections.CutLists['DimuonCutList'] and val in ('pT',
'eta',
'd0'):
continue
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)
d = HISTS[ref][key.replace('Eff', 'Den')].Clone()
RT.addFlows(d)
g = R.TGraphAsymmErrors(h, d, 'cp')
g.SetNameTitle(
'g_' + key,
';' + h.GetXaxis().GetTitle() + ';' + h.GetYaxis().GetTitle())
p = Plotter.Plot(g, '', 'pe', 'pe')
canvas = Plotter.Canvas(lumi=lumi)
canvas.addMainPlot(p)
p.setColor(R.kBlue)
canvas.firstPlot.SetMinimum(0.)
canvas.firstPlot.SetMaximum(1.)
fname = 'pdfs/NM1E_{}_{}.pdf'.format(key, name)
canvas.cleanup(fname)
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 makeEffPlot(quantity, den, fs, sp=None):
tags = (quantity + '_MSD', quantity + '_LCD', quantity + '_CID')
effTag = quantity + '_CID'
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
hNum = h[quantity + '_CID']
h[quantity + '_' + den].Add(h[quantity + '_CID'])
hDen = h[quantity + '_' + den]
graph = R.TGraphAsymmErrors(hNum, hDen, 'cp')
# make plots
p = Plotter.Plot(graph, '', 'l', 'px')
# canvas, plots, min max
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs)
canvas.addMainPlot(p)
canvas.setMaximum()
canvas.firstPlot.SetMinimum(0)
# set titles
canvas.firstPlot.setTitles(X=hNum.GetXaxis().GetTitle(), Y='Efficiency')
# colors
p.setColor(R.kBlue, which='M')
# legend, cleanup
#canvas.makeLegend(lWidth=.2, pos='tr')
#canvas.legend.resizeHeight()
canvas.cleanup('pdfs/3Mu_{}Eff-{}{}_HTo2XTo{}_{}.pdf'.format(
quantity, den, ARGS.CUTSTRING, fs,
SPStr(sp) if sp is not None else 'Global'))
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 makePlot(fs, sp, quantity):
# configy type stuff
tags = ('Matched', 'Junk')
legs = {'Matched': 'Matched', 'Junk': 'Incorrect Pair'}
cols = {'Matched': R.kBlue, 'Junk': R.kRed}
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(
f, (fs, SIGNALPOINTS[0]), quantity + '_' + tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(
HistogramGetter.getHistogram(f, (fs, SP),
quantity + '_' + tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), quantity + '_' +
tag).Clone()
# make plots
p = {}
for tag in tags:
p[tag] = Plotter.Plot(h[tag], legs[tag], 'l', 'hist')
# canvas, plots, min max
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs,
logy=True)
for tag in tags:
canvas.addMainPlot(p[tag])
canvas.setMaximum()
# colors
for tag in tags:
p[tag].SetLineColor(cols[tag])
# legend, cleanup
canvas.makeLegend(lWidth=.2, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/PV_{}{}_HTo2XTo{}_{}.pdf'.format(
quantity, args.CUTSTRING, fs,
SPStr(sp) if sp is not None else 'Global'))
def makeSplit4Plot(quantity, fs, sp=None):
tags = [quantity + '_' + tag for tag in ('CID', 'MSD', 'LCD', 'UMD')]
legs = dict(
zip(tags, ('correct', 'signal', 'lowest #chi^{2}/dof', 'unmatched')))
cols = dict(zip(tags, (R.kBlue, R.kGreen, R.kMagenta, R.kRed)))
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
# make plots
p = {}
for tag in tags:
p[tag] = Plotter.Plot(h[tag], legs[tag], 'l', 'hist')
# canvas, plots, min max
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs,
logy=True)
for tag in tags:
canvas.addMainPlot(p[tag])
canvas.setMaximum(scale=2.)
canvas.firstPlot.SetMinimum(1.)
# colors
for tag in tags:
p[tag].setColor(cols[tag], which='L')
# legend, cleanup
canvas.makeLegend(lWidth=.2, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/3Mu_{}Dist{}_HTo2XTo{}_{}.pdf'.format(
quantity, ARGS.CUTSTRING, fs,
SPStr(sp) if sp is not None else 'Global'))
def makePTCutPlot(fs, sp=None, PC=False, extra=''):
# configy type stuff
tags = TAGS[ARGS.FS + ('' if not PC else 'PC') + extra]
legs = [CONFIG[tag]['LEG_H'] for tag in tags]
cols = [CONFIG[tag]['COL'] for tag in tags]
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
# make plots
p = {}
for i, tag in enumerate(tags):
p[tag] = Plotter.Plot(h[tag], legs[i], 'l', 'hist')
# canvas, plots, min max
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs)
for tag in tags:
canvas.addMainPlot(p[tag])
canvas.setMaximum()
canvas.setMinimum()
# colors
for i, tag in enumerate(tags):
p[tag].SetLineColor(cols[i])
# legend, cleanup
canvas.makeLegend(lWidth=.275, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/PC_Match{}{}_HTo2XTo{}_{}.pdf'.format(
'-PC' if PC else '', extra, fs,
SPStr(sp) if sp is not None else 'Global'))
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 makeSignal2DPlots():
for quantity in ('normChi2', 'nTrkLay', 'nPxlHit', 'highPurity',
'isGlobal', 'isMedium', 'hitsBeforeVtx',
'missingHitsAfterVtx'):
if quantity == 'nTrkLay':
R.gStyle.SetPaintTextFormat('.1f')
else:
R.gStyle.SetPaintTextFormat('g')
hkey = 'PAT-12-' + quantity
HISTS = HG.getAddedSignalHistograms(FILES[fs], fs, (hkey, ))
for sp in SIGNALPOINTS:
HISTS[sp] = HG.getHistogram(FILES[fs], (fs, sp), hkey).Clone()
if quantity != 'normChi2':
opt = 'colz text'
else:
opt = 'colz'
PLOTS = {hkey: Plotter.Plot(HISTS[hkey], '', '', opt)}
for sp in SIGNALPOINTS:
PLOTS[sp] = Plotter.Plot(HISTS[sp], '', '', opt)
for sp in [
hkey,
] + SIGNALPOINTS:
canvas = Plotter.Canvas(lumi=fs + lumiExtra.get(CUTSTRING) if
type(sp) != tuple else SPLumiStr(fs, *sp))
canvas.addMainPlot(PLOTS[sp])
canvas.firstPlot.SetMarkerColor(R.kWhite)
if quantity == 'normChi2':
canvas.firstPlot.GetXaxis().SetRangeUser(0., 10.)
canvas.firstPlot.GetYaxis().SetRangeUser(0., 10.)
canvas.scaleMargins(1.75, edges='R')
canvas.scaleMargins(0.8, edges='L')
canvas.cleanup('pdfs/ZEP_2D_{}_{}_{}_{}.pdf'.format(
quantity, CUTSTRING, fs,
'Global' if type(sp) != tuple else SPStr(sp)))
def makePTCutEffPlot(fs, sp=None, PC=False, extra=''):
# configy type stuff
tags = TAGS[ARGS.FS + ('' if not PC else 'PC') + extra]
legs = [CONFIG[tag]['LEG_EFF'] for tag in tags]
cols = [CONFIG[tag]['COL'] for tag in tags]
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
# clone everything, the h is about to be overwritten
copies = {}
for tag in tags:
copies[tag] = h[tag].Clone()
# nMatch: scale to first bin (gives ~efficiency)
# others: divide by nMatch
h[tags[0]].Scale(1. / copies[tags[0]].GetBinContent(1))
for tag in tags[1:]:
h[tag] = R.TGraphAsymmErrors(copies[tag], copies[tags[0]], 'cp')
# make plots
p = {}
for i, tag in enumerate(tags):
p[tag] = Plotter.Plot(h[tag], legs[i], 'p',
'p' + ('' if i == 0 else 'x'))
# it's an efficiency so the scale is 0-1, but zoom in on the relevant part
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs)
for tag in tags:
canvas.addMainPlot(p[tag])
canvas.firstPlot.SetMaximum(1.01)
canvas.firstPlot.SetMinimum(0.90 if ARGS.FS == '2Mu2J' else 0.50)
if ARGS.FS == '2Mu2J' and extra != '':
canvas.firstPlot.SetMinimum(0.)
#canvas.setMaximum()
#canvas.setMinimum()
# set colors
for i, tag in enumerate(tags):
p[tag].setColor(cols[i])
# legend, cleanup
if extra == '':
canvas.makeLegend(lWidth=.275, pos='br')
canvas.legend.resizeHeight()
# hack for getting the legend in the right spot for 1000 and 400, as it turns out
if sp is not None and sp[0] > 399:
canvas.legend.moveLegend(X=-.35)
else:
canvas.legend.moveLegend(Y=.2)
else:
canvas.makeLegend(lWidth=.275, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/PC_MatchEff{}{}_HTo2XTo{}_{}.pdf'.format(
'-PC' if PC else '', extra, fs,
SPStr(sp) if sp is not None else 'Global'))
def makeEffPlots(quantity, fs, SP=None):
HKeys = {
'DSA_Eff': 'DSA_{}Eff',
'RSA_Eff': 'RSA_{}Eff',
'REF_Eff': 'REF_{}Eff',
'REF_Den': 'REF_{}Den',
'Den': '{}Den',
# 'Extra' : '{}Extra' ,
'DSA_ChargeEff': 'DSA_{}ChargeEff',
'RSA_ChargeEff': 'RSA_{}ChargeEff',
'REF_ChargeEff': 'REF_{}ChargeEff',
'DSA_ChargeDen': 'DSA_{}ChargeDen',
'RSA_ChargeDen': 'RSA_{}ChargeDen',
'REF_ChargeDen': 'REF_{}ChargeDen',
}
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])
if quantity != 'dR':
h[key].Rebin(10)
else:
h[key].Rebin(5)
# Extra is commented out, same with FIRST SECOND
# so they don't appear on SRE plots by default now
NumDens = (
('DSA_Eff', 'Den', 'DSA', R.kBlue),
('RSA_Eff', 'Den', 'RSA', R.kRed),
('REF_Eff', 'REF_Den', 'REF', R.kGreen),
# ('Extra' , 'Den' , 'Extra' , R.kMagenta),
('DSA_ChargeEff', 'DSA_ChargeDen', 'DSA:Charge', R.kBlue),
('RSA_ChargeEff', 'RSA_ChargeDen', 'RSA:Charge', R.kRed),
('REF_ChargeEff', 'REF_ChargeDen', 'REF:Charge', R.kGreen),
)
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() + ';Reconstruction Efficiency')
p[num] = Plotter.Plot(g[num], leg, 'elp', 'pe')
# FIRST = (0, 3)
# SECOND = (3, 5)
# FIRST = (0, 2)
# SECOND = (2, 4)
FIRST = (0, 3)
SECOND = (3, 6)
CHARGE = ''
for SECTION in (FIRST, SECOND):
canvas = Plotter.Canvas(lumi=fs if SP is None else SPLumiStr(fs, *SP))
for i in range(SECTION[0], SECTION[1]):
key = NumDens[i][0]
col = NumDens[i][3]
canvas.addMainPlot(p[key])
p[key].setColor(col)
# aesthetic change
if quantity == 'Lxy' or (quantity == 'd0' and CHARGE == ''):
canvas.makeLegend(pos='bl')
else:
canvas.makeLegend(pos='br')
canvas.legend.moveLegend(Y=0.25)
canvas.legend.moveLegend(X=-.1)
canvas.legend.resizeHeight()
canvas.firstPlot.SetMinimum(0.)
canvas.firstPlot.SetMaximum(1.)
#RT.addBinWidth(canvas.firstPlot)
# aesthetic change
if quantity == 'dR':
canvas.firstPlot.GetXaxis().SetRangeUser(0., 1.)
elif quantity == 'pT':
canvas.firstPlot.GetXaxis().SetRangeUser(0., 800.)
canvas.cleanup('pdfs/SRE_{}{}Eff_{}HTo2XTo{}_{}.pdf'.format(
quantity, CHARGE, 'Trig-' if TRIGGER else '', fs,
'Global' if SP is None else SPStr(SP)))
CHARGE = 'Charge'
def makeMultiplicityPlots(fs, sp):
if ARGS.FS == '4Mu': return
# configy type stuff
pTCuts = (0, 5, 10, 15)
splits = ('_', '_Matched_', '_NotMatched_')
prettysplits = {
'_': '',
'_Matched_': ' (Matched)',
'_NotMatched_': ' (Junk)'
}
quants = ('Muon', 'Dimuon')
for q in quants:
for split in splits:
for logy in (True, False):
tags = []
legs = []
cols = [R.kRed, R.kBlue, R.kGreen, R.kMagenta]
for pTCut in pTCuts:
tags.append('n{}{}{}'.format(q, split, pTCut))
legs.append(
'{} GeV'.format(pTCut) if pTCut > 0 else 'no cut')
# the code after this is identical to the makePTCutPlot code, except for the lumi string, min/max, and cleanup
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(
f, (fs, SIGNALPOINTS[0]), tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(
HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(
f, (fs, sp), tag).Clone()
p = {}
for i, tag in enumerate(tags):
p[tag] = Plotter.Plot(h[tag], legs[i], 'l', 'hist')
canvas = Plotter.Canvas(
lumi=(SPLumiStr(fs, sp) if sp is not None else fs) +
prettysplits[split],
logy=logy)
for tag in tags:
canvas.addMainPlot(p[tag])
if logy:
canvas.setMaximum(scale=2.)
canvas.firstPlot.SetMinimum(1.)
else:
canvas.setMaximum()
canvas.firstPlot.SetMinimum(0.)
for i, tag in enumerate(tags):
p[tag].SetLineColor(cols[i])
canvas.makeLegend(lWidth=.25, pos='tr')
canvas.legend.resizeHeight()
canvas.cleanup('pdfs/PC_{}Mult{}{}HTo2XTo{}_{}.pdf'.format(
q, split, 'Log_' if logy else '', fs,
SPStr(sp) if sp is not None else 'Global'))
def optimizeCut(fs, sp, quantity):
# get histograms
s = getHistogram(f, fs, sp, quantity, 'Matched')
b = getHistogram(f, fs, sp, quantity, 'Junk' )
# get cumulatives
sCum = s.GetCumulative()
bCum = b.GetCumulative()
fom = sCum.Clone()
# print out suppression
nBins = sCum.GetNbinsX()
if quantity == 'LxyErr':
ibin = 200
else:
ibin = 660
srej = 1.-sCum.GetBinContent(ibin)/sCum.GetBinContent(nBins)
brej = 1.-bCum.GetBinContent(ibin)/bCum.GetBinContent(nBins)
#print '{:5s} {:4d} {:3d} {:4d} :: {:6s} :: reject {:6.2%} of signal, but {:6.2%} of background'.format(
# fs,
# sp[0], sp[1], sp[2],
# quantity,
# 1.-sCum.GetBinContent(ibin)/sCum.GetBinContent(nBins),
# 1.-bCum.GetBinContent(ibin)/bCum.GetBinContent(nBins),
#)
# fill f.o.m. histogram, and keep track of max f.o.m. and cut value
nBins = sCum.GetNbinsX()
xAxis = sCum.GetXaxis()
fom_max = 0.
opt_cut = 0.
for ibin in range(1,nBins+1):
val = FOM(sCum.GetBinContent(ibin), bCum.GetBinContent(ibin))
if val > fom_max:
fom_max = val
opt_cut = xAxis.GetBinCenter(ibin)
fom.SetBinContent(ibin, val)
# make plots
p = {}
p['sig'] = Plotter.Plot(sCum, 'matched' , 'l', 'hist')
p['bg' ] = Plotter.Plot(bCum, 'other' , 'l', 'hist')
p['fom'] = Plotter.Plot(fom , 'S/#sqrt{S+B}', 'l', 'hist')
# make canvas, colors, maximum
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, *sp))
canvas.addMainPlot(p['sig'])
canvas.addMainPlot(p['bg' ])
canvas.addMainPlot(p['fom'])
p['sig'].SetLineColor(R.kBlue )
p['bg' ].SetLineColor(R.kRed )
p['fom'].SetLineColor(R.kGreen)
canvas.setMaximum()
# scale f.o.m. and make new axis
fom.Scale(canvas.firstPlot.GetMaximum()/fom_max/1.05)
axis = R.TGaxis(xAxis.GetXmax(), 0., xAxis.GetXmax(), canvas.firstPlot.GetMaximum(), 0., fom_max*1.05, 510, '+L')
for attr in ('LabelFont', 'LabelOffset', 'TitleFont', 'TitleOffset', 'TitleSize'):
getattr(axis, 'Set'+attr)(getattr(xAxis, 'Get'+attr)())
axis.SetTitle('Figure of Merit')
axis.CenterTitle()
axis.Draw()
canvas.scaleMargins(1.1, edges='R')
# make the legend after
canvas.makeLegend(lWidth=.2, pos='br')
canvas.legend.resizeHeight()
# draw optimum text and line
x, y = canvas.legend.GetX1(), canvas.legend.GetY2()
canvas.drawText(text='#color[{:d}]{{opt. cut = {:.2f}}}'.format(R.kBlack, opt_cut), pos=(x, y+0.05), align='bl')
line = R.TLine(opt_cut, 0., opt_cut, canvas.firstPlot.GetMaximum())
line.SetLineStyle(2)
line.Draw()
# save
canvas.cleanup('OPT_{}_HTo2XTo{}_{}.pdf'.format(quantity, fs, SPStr(sp)))
# save cut val
if sp not in DATA[fs]: DATA[fs][sp] = {}
if quantity not in DATA[fs][sp]: DATA[fs][sp][quantity] = {
'opt':0,
'srej':0,
'brej':0,
}
DATA[fs][sp][quantity]['opt'] = opt_cut
DATA[fs][sp][quantity]['srej'] = srej
DATA[fs][sp][quantity]['brej'] = brej
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 optimizeCut(fs, sp, quantity):
# get histograms
s = HG.getHistogram(FILES['Signal'], (fs, sp), quantity)
DHists, DPConfig = HG.getDataHistograms(FILES['Data'], quantity)
b = DHists[quantity]['data']
n = s.Integral(0, s.GetNbinsX()+1)
s.Scale(ScaleFactor(sp, sigmaB=1.e-2))
# get cumulatives
sCum = s.GetCumulative(CONFIG[quantity]['forward'])
bCum = b.GetCumulative(CONFIG[quantity]['forward'])
fom = sCum.Clone()
print '**** Data (|DeltaPhi| > Pi/2) vs. HTo2XTo{} ({} GeV, {} GeV, {} mm) (|DeltaPhi| < Pi/2)'.format(fs, *sp)
print '**** Quantity = {:s} ::: Passing (N-1) = {:.0f} ::: N_gen = {:.0f} ::: Sigma*B = {:.3f} pb ::: 2016 ILumi = 35922 /pb'.format(
CONFIG[quantity]['pretty'], n, SignalInfo[sp]['sumWeights'][1], SignalInfo[sp]['sigmaBLimit'])
print '{:>8s} {:>7s} {:>7s} {:>7s} {:>6s} {:>6s}'.format('CutVal', 'S', 'B=nOff', 'S+B=nOn', 'ZBi', 'ZPL')
# fill f.o.m. histogram, and keep track of max f.o.m. and cut value
nBins = sCum.GetNbinsX()
xAxis = sCum.GetXaxis()
fom_max = 0.
opt_cut = 0.
opt_s = 0.
opt_b = 0.
for ibin in range(1,nBins+1):
S, B, cutVal, FOMs = calculateFOM(s, b, sCum, bCum, nBins, ibin, xAxis, CONFIG[quantity]['forward'])
print '{:8.3f} {:7.3f} {:7.3f} {:7.3f} {:6.3f} {:6.3f}'.format(cutVal, S, B, S+B, FOMs['ZBi'], FOMs['ZPL'])
if FOMs[FIGURE_OF_MERIT] > fom_max:
fom_max = FOMs[FIGURE_OF_MERIT]
opt_cut = cutVal
opt_s = S
opt_b = B
fom.SetBinContent(ibin, FOMs[FIGURE_OF_MERIT])
# make plots
p = {}
p['sig'] = Plotter.Plot(sCum, 'signal' , 'l', 'hist')
p['bg' ] = Plotter.Plot(bCum, 'data' , 'l', 'hist')
p['fom'] = Plotter.Plot(fom , PRETTY_LEG , 'l', 'hist')
# make canvas, colors, maximum
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, *sp))
canvas.addMainPlot(p['sig'])
canvas.addMainPlot(p['bg' ])
canvas.addMainPlot(p['fom'])
p['sig'].SetLineColor(R.kBlue )
p['bg' ].SetLineColor(R.kRed )
p['fom'].SetLineColor(R.kGreen)
canvas.setMaximum()
canvas.firstPlot.SetMinimum(0.)
# scale f.o.m. and make new axis
fom.Scale(canvas.firstPlot.GetMaximum()/fom_max/1.05)
axis = R.TGaxis(xAxis.GetXmax(), 0., xAxis.GetXmax(), canvas.firstPlot.GetMaximum(), 0., fom_max*1.05, 510, '+L')
for attr in ('LabelFont', 'LabelOffset', 'TitleFont', 'TitleOffset', 'TitleSize'):
getattr(axis, 'Set'+attr)(getattr(xAxis, 'Get'+attr)())
axis.SetTitle('Figure of Merit')
axis.CenterTitle()
axis.Draw()
canvas.scaleMargins(1.1, edges='R')
# make the legend after
canvas.makeLegend(lWidth=.2, pos='br')
canvas.legend.resizeHeight()
canvas.legend.moveLegend(X=-.2, Y=.1)
# draw optimum text and line
x, y = canvas.legend.GetX1(), canvas.legend.GetY2()
canvas.drawText(text='#color[{:d}]{{opt. cut = {:.2f}}}'.format(R.kBlack, opt_cut), pos=(x, y+0.05), align='bl')
line = R.TLine(opt_cut, 0., opt_cut, canvas.firstPlot.GetMaximum())
line.SetLineStyle(2)
line.Draw()
# save
canvas.cleanup('pdfs/OPT_{}_{}_HTo2XTo{}_{}.pdf'.format(quantity, FIGURE_OF_MERIT, fs, SPStr(sp)))
def makeSplitDeltaPhiPlots():
for ref in HISTS:
if not type(ref) == tuple: continue
for KEY in HISTS[ref]:
if 'VSdeltaPhi' not 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])
else:
name = ref
lumi = HistogramGetter.PLOTCONFIG[ref]['LATEX']
if '_Matched' in KEY: continue
H = HISTS[ref][KEY].Clone()
nBins = H.GetNbinsX()
h = {
'Less': {
'hist': H.ProjectionY('Less', 1, nBins / 2),
'legName': '|#Delta#Phi|<#pi/2',
'color': R.kBlue
},
'More': {
'hist': H.ProjectionY('More', nBins / 2 + 1, nBins),
'legName': '|#Delta#Phi|>#pi/2',
'color': R.kRed
},
}
p = {}
for key in h:
if h[key]['hist'].Integral() != 0:
h[key]['hist'].Scale(1. / h[key]['hist'].Integral())
if nBins > 100: h[key]['hist'].Rebin(10)
p[key] = Plotter.Plot(h[key]['hist'], h[key]['legName'], 'l',
'hist')
canvas = Plotter.Canvas(lumi=lumi)
for key in h:
canvas.addMainPlot(p[key])
p[key].SetLineColor(h[key]['color'])
canvas.makeLegend(pos='tl')
canvas.legend.resizeHeight()
canvas.setMaximum(recompute=True)
canvas.firstPlot.setTitles(Y='Normalized Counts')
pave = []
for key in h:
pave.append(canvas.makeStatsBox(p[key], color=h[key]['color']))
for i, box in enumerate(pave):
if i == 0: continue
HEIGHT = pave[i - 1].GetY2NDC() - pave[i - 1].GetY1NDC()
Plotter.MOVE_OBJECT(box, Y=-HEIGHT - .05)
parse = re.match(r'Dim_(.*)VSdeltaPhi(.*)', KEY)
yAxis, other = parse.group(1), parse.group(2)
fname = 'pdfs/Dim_{}{}{}_Both_{}.pdf'.format(
yAxis, other, CUTSTRING, name)
canvas.cleanup(fname)
def makePerSamplePlots():
for ref in HISTS:
print "ref: ,", ref
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']
print "name: ", name, " lumi: ", lumi, " legName: ", legName
else:
name = ref
lumi = HistogramGetter.PLOTCONFIG[ref]['LATEX']
legName = HistogramGetter.PLOTCONFIG[ref]['LATEX']
# histo filename
fname = 'pdfs/muonQualityPlots_{}.pdf'.format(name)
# canvas
canvas = R.TCanvas('c', 'canvas', 0, 0, 800, 600)
gStyle.SetOptStat(111111)
# gStyle.SetStatW(0.25) # width of statistics box; default is 0.19
# gStyle.SetStatH(0.10) # height of statistics box; default is 0.1
# gStyle.SetStatFontSize(0.07) # size for stat. box
# delta R between nearest HLT and DSA muons
canvas.Clear()
htit = 'dR_HLT_DSA'
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(1, 2)
pad.cd(1)
HISTS[ref][htit].Draw("hist")
pad.cd(2)
HISTS[ref][htit].Draw("hist")
gPad.SetLogy(1)
canvas.Print(fname + "(", "Title:" + htit)
# delta R between nearest HLT and DSA muons for good events failing the default HLT-RECO match
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
pad.cd(1)
HISTS[ref]['dR1_HLT_DSA_GoodEvent'].Draw("hist")
pad.cd(2)
HISTS[ref]['dR1_HLT_DSA_GoodEvent'].Draw("hist")
gPad.SetLogy(1)
pad.cd(3)
HISTS[ref]['dR2_HLT_DSA_GoodEvent'].Draw("hist")
pad.cd(4)
HISTS[ref]['dR2_HLT_DSA_GoodEvent'].Draw("hist")
gPad.SetLogy(1)
canvas.Print(fname, "Title:dR_HLT_DSA, no HLT-RECO match, good events")
# delta R between nearest HLT and DSA muons for bad events failing the default HLT-RECO match
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
pad.cd(1)
HISTS[ref]['dR1_HLT_DSA_BadEvent'].Draw("hist")
pad.cd(2)
HISTS[ref]['dR1_HLT_DSA_BadEvent'].Draw("hist")
gPad.SetLogy(1)
pad.cd(3)
HISTS[ref]['dR2_HLT_DSA_BadEvent'].Draw("hist")
pad.cd(4)
HISTS[ref]['dR2_HLT_DSA_BadEvent'].Draw("hist")
gPad.SetLogy(1)
canvas.Print(fname, "Title:dR_HLT_DSA, no HLT-RECO match, bad events")
# number of unsuccessful and successful HLT-DSA matches
canvas.Clear()
htit = 'matches_HLT_DSA'
HISTS[ref][htit].Draw("hist")
HISTS[ref][htit].Draw("same text")
canvas.Print(fname, "Title:" + htit)
# some diagnostics for RECO muons matched to signal GEN muons but not matched to HLT muons
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
pad.cd(1)
HISTS[ref]['unmatched_pt_res'].Draw("hist")
pad.cd(2)
HISTS[ref]['unmatched_invm_res'].Draw("hist")
pad.cd(3)
HISTS[ref]['unmatched_pt_rec_vs_pt_gen'].Draw("")
pad.cd(4)
HISTS[ref]['unmatched_pt_rec_vs_pt_gen_zoomed'].Draw("")
canvas.Print(
fname,
"Title:RECO muons matched to signal GEN muons but not matched to HLT muons"
)
# N(CSC stations) vs N(DT stations)
canvas.Clear()
htit = 'CSC_vs_DT_Stations'
HISTS[ref][htit].Draw("text")
canvas.Print(fname, "Title:" + htit)
# Nhits
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
pad.cd(1)
HISTS[ref]['nMuonHits'].Draw("hist")
pad.cd(2)
HISTS[ref]['nDTCSCHits'].Draw("hist")
pad.cd(3)
HISTS[ref]['nDTHits'].Draw("hist")
pad.cd(4)
HISTS[ref]['nCSCHits'].Draw("hist")
# HISTS[ref]['nRPCHits'].Draw("hist")
canvas.Print(fname, "Title:total number of hits")
# Nhits for various Nstations
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nMuonHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:muon hits per station")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nRPCHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:RPC hits per station")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nCSCHits_vs_nDTHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("text")
canvas.Print(fname, "Title:CSC hits vs DT hits, per station")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nDTCSCHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:DT+CSC hits per station, lin scale")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
gStyle.SetOptLogy(1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nDTCSCHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
gStyle.SetOptLogy(0)
canvas.Print(fname, "Title:DT+CSC hits per station, log scale")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nDTHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:DT hits per station, lin scale")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
gStyle.SetOptLogy(1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nDTHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
gStyle.SetOptLogy(0)
canvas.Print(fname, "Title:DT hits per station, log scale")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nCSCHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:CSC hits per station, lin scale")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
gStyle.SetOptLogy(1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'nCSCHits_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
gStyle.SetOptLogy(0)
canvas.Print(fname, "Title:CSC hits per station, log scale")
# pT resolutions for groups of 3 DT+CSC hits
htot = 17
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'pTres_DTCSChits_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname, "Title:pT res for groups of 3 hits")
# pT res for groups of 3 hits, N(stat) > 1
htot = 8
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'pTres_DTCSChits_Stat234_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:pT res for groups of 3 hits, N(stat) > 1")
# pT res for 12-19 DTCSC hits, N(stat) > 1
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
for ihits in range(12, 20):
pad.cd(ihits - 11)
htit = 'pTres_Stat234_' + str(ihits) + 'DTCSChits'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:pT res for 12-19 DTCSC hits, N(stat) > 1")
# resolutions in barrel, endcap, and overlap
htot = 8 # hist8 and hist9 are empty
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'pTres_DThits_barrel_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:pT res for groups of 6 hits, barrel")
htot = 10
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'pTres_CSChits_endcap_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:pT res for groups of 3 hits, endcap")
htot = 8 # hist8 and hist9 are empty
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'pTres_DTCSChits_overlap_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:pT res for groups of 6 hits, overlap")
# 1/pT resolutions for groups of 3 DT+CSC hits
htot = 17
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'invpTres_DTCSChits_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname, "Title:1/pT res for groups of 3 hits")
# 1/pT resolutions for groups of 3 hits, N(stat) > 1
htot = 8
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'invpTres_DTCSChits_Stat234_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(
fname, "Title:1/pT res for groups of 3 hits, N(stat) > 1")
# charge difference for groups of 3 hits
htot = 17
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'qdif_DTCSChits_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname, "Title:q dif for groups of 3 hits")
# charge difference for groups of 3 hits, N(stat) > 1
htot = 8
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'qdif_DTCSChits_Stat234_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:q dif for groups of 3 hits, N(stat) > 1")
# charge difference for 12-19 DTCSC hits, N(stat) > 1
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
for ihits in range(12, 20):
pad.cd(ihits - 11)
htit = 'qdif_Stat234_' + str(ihits) + 'DTCSChits'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:q dif for 12-19 DTCSC hits, N(stat) > 1")
# d0 difference for groups of 3 hits
htot = 17
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'd0dif_DTCSChits_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname, "Title:d0 dif for groups of 3 hits")
# d0 difference for groups of 6 hits in barrel, endcap, and overlap
htot = 8 # hist8 and hist9 are empty
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'd0dif_DThits_barrel_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:d0 dif for groups of 6 hits, barrel")
htot = 10
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'd0dif_CSChits_endcap_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:d0 dif for groups of 3 hits, endcap")
htot = 8 # hist8 and hist9 are empty
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'd0dif_DTCSChits_overlap_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:d0 dif for groups of 6 hits, overlap")
# d0 difference for groups of 3 hits, N(stat) > 1
htot = 8
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'd0dif_DTCSChits_Stat234_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname,
"Title:d0 dif for groups of 3 hits, N(stat) > 1")
# sigma(pt)/pt vs chi2/ndof
canvas.Clear()
htit = 'dpt_over_pt_vs_chi2_over_ndof'
HISTS[ref][htit].Draw("")
canvas.Print(fname, "Title:" + htit)
# sigma(pT)/pT per station
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'dpt_over_pt_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:sigma(pT)/pT per station, lin scale")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
gStyle.SetOptLogy(1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'dpt_over_pt_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
gStyle.SetOptLogy(0)
canvas.Print(fname, "Title:sigma(pT)/pT per station, log scale")
# sigma(pT)/pT for groups of 3 hits
htot = 17
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'dpt_over_pt_DTCSChits_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname, "Title:sigma(pT)/pT for groups of 3 hits")
# sigma(pT)/pT for groups of 3 hits, N(stat) > 1
htot = 8
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'dpt_over_pt_DTCSChits_Stat234_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(
fname,
"Title:sigma(pT)/pT for groups of 3 hits, N(stat) > 1")
# pT resolution in slices of sigma(pT)/pT
htot = 10
for ihist in range(0, htot):
ipad = ihist % 10
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(5, 2)
pad.cd(ipad + 1)
htit = 'pTres_for_dpt_over_pt_hist' + str(ihist)
HISTS[ref][htit].Fit("gaus", "Q")
# HISTS[ref][htit].Draw("hist")
if ipad == 9 or ihist == htot - 1:
canvas.Print(fname, "Title:pT res in slices of sigma(pT)/pT")
# pT resolution in slices of sigma(pT)/pT, Nhits > 12
htot = 10
for ihist in range(0, htot):
ipad = ihist % 10
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(5, 2)
pad.cd(ipad + 1)
htit = 'pTres_for_dpt_over_pt_passed_hist' + str(ihist)
HISTS[ref][htit].Fit("gaus", "Q")
# HISTS[ref][htit].Draw("hist")
if ipad == 9 or ihist == htot - 1:
canvas.Print(
fname,
"Title:pT res in slices of sigma(pT)/pT, Nhits > 12")
# pT pull in slices of sigma(pT)/pT
htot = 10
for ihist in range(0, htot):
ipad = ihist % 10
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(5, 2)
pad.cd(ipad + 1)
htit = 'pTpull_for_dpt_over_pt_hist' + str(ihist)
# HISTS[ref][htit].Fit("gaus","Q")
HISTS[ref][htit].Draw("hist")
if ipad == 9 or ihist == htot - 1:
canvas.Print(fname, "Title:pT pull in slices of sigma(pT)/pT")
# refitted muons for DSA muons failing dpT/pT cut
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
pad.cd(1)
HISTS[ref]['eta_for_dpt_over_pt_gt_1'].Draw("hist")
pad.cd(2)
HISTS[ref]['pTres_ref_for_dpt_over_pt_gt_1'].Draw("hist")
pad.cd(3)
HISTS[ref]['dpt_over_pt_ref_for_dpt_over_pt_gt_1'].Draw("hist")
pad.cd(4)
HISTS[ref]['pTres_ref_for_dpt_over_pt_gt_1_ref_lt_1'].Draw("hist")
canvas.Print(fname, "Title:refitted muons, sigma(pT)/pT > 1")
# chi2/ndof per station
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'chi2_over_ndof_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
canvas.Print(fname, "Title:chi2/ndof per station, lin scale")
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
gStyle.SetOptLogy(1)
pad.Draw()
pad.Divide(2, 2)
for istat in range(1, 5):
pad.cd(istat)
htit = 'chi2_over_ndof_' + str(istat) + 'Stat'
HISTS[ref][htit].Draw("hist")
gStyle.SetOptLogy(0)
canvas.Print(fname, "Title:chi2/ndof per station, log scale")
# chi2/ndof for groups of 3 hits
htot = 17
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'chi2_over_ndof_DTCSChits_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(fname, "Title:chi2/ndof for groups of 3 hits")
# chi2/ndof for groups of 3 hits, N(stat) > 1
htot = 8
for ihist in range(0, htot):
ipad = ihist % 8
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
pad.cd(ipad + 1)
htit = 'chi2_over_ndof_DTCSChits_Stat234_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
if ipad == 7 or ihist == htot - 1:
canvas.Print(
fname, "Title:chi2/ndof for groups of 3 hits, N(stat) > 1")
# pT resolution in slices of chi2/ndof
htot = 10
for ihist in range(0, htot):
ipad = ihist % 10
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(5, 2)
pad.cd(ipad + 1)
htit = 'pTres_for_chi2_over_ndof_hist' + str(ihist)
HISTS[ref][htit].Fit("gaus", "Q")
# HISTS[ref][htit].Draw("hist")
if ipad == 9 or ihist == htot - 1:
canvas.Print(fname, "Title:pT res in slices of chi2/ndof")
# pT resolution in slices of chi2/ndof, Nhits > 12
htot = 10
for ihist in range(0, htot):
ipad = ihist % 10
if ipad == 0:
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(5, 2)
pad.cd(ipad + 1)
htit = 'pTres_for_chi2_over_ndof_passed_hist' + str(ihist)
HISTS[ref][htit].Fit("gaus", "Q")
# HISTS[ref][htit].Draw("hist")
if ipad == 9 or ihist == htot - 1:
canvas.Print(
fname, "Title:pT res in slices of chi2/ndof, Nhits > 12")
# placeholder for future histograms
canvas.Clear()
pad = R.TPad('pad', 'pad', 0, 0, 1, 1)
pad.Draw()
pad.Divide(4, 2)
for ihist in range(16, 17):
pad.cd(ihist - 15)
htit = 'pTres_DTCSChits_hist' + str(ihist)
HISTS[ref][htit].Draw("hist")
canvas.Print(fname + ")", "Title:placeholder")
def makeEffPlot(quantity, criteria, fs, sp=None):
# configy type stuff
legs = ('All', 'Matched', 'NotMatched')
tags = [
quantity + '_' + ('All' + ('-4' if '-4' in criteria else '')
if 'All' in leg else criteria + '_' + leg)
for leg in legs
]
cols = (R.kBlack, R.kBlue, R.kRed)
# get/add histograms
if sp is None:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, SIGNALPOINTS[0]),
tag).Clone()
for SP in SIGNALPOINTS[1:]:
for tag in tags:
h[tag].Add(HistogramGetter.getHistogram(f, (fs, SP), tag))
else:
h = {}
for tag in tags:
h[tag] = HistogramGetter.getHistogram(f, (fs, sp), tag).Clone()
for tag in tags:
h[tag].Rebin(5)
clones = {tag: h[tag].Clone() for tag in tags}
for tag in tags[1:]:
h[tag] = R.TGraphAsymmErrors(clones[tag], clones[tags[0]], 'cp')
# make plots
p = {}
for i, tag in enumerate(tags):
p[tag] = Plotter.Plot(h[tag], legs[i], 'l', 'px')
# canvas, plots, min max
canvas = Plotter.Canvas(lumi=SPLumiStr(fs, sp) if sp is not None else fs)
for tag in tags:
if 'All' in tag: continue
canvas.addMainPlot(p[tag])
canvas.setMaximum()
canvas.firstPlot.SetMinimum(0)
if 'Lxy' in quantity:
canvas.firstPlot.GetXaxis().SetRangeUser(0., 330.)
# set titles
canvas.firstPlot.setTitles(X=clones[tags[0]].GetXaxis().GetTitle(),
Y='Efficiency')
# colors
for i, tag in enumerate(tags):
p[tag].setColor(cols[i])
# legend, cleanup
canvas.makeLegend(lWidth=.2, pos='tr')
canvas.legend.resizeHeight()
if not (criteria in ('HPD-OC-C2S', 'HPD-C2S')
and ARGS.CUTSTRING in ('', '_5GeV')):
canvas.legend.moveLegend(Y=-.3)
canvas.cleanup('pdfs/LCD_{}Eff_{}{}_HTo2XTo{}_{}.pdf'.format(
quantity, criteria, ARGS.CUTSTRING, fs,
SPStr(sp) if sp is not None else 'Global'))