def DrawStack(self, opt='', xmin=None, xmax=None, ymin=None, ymax=None):
'''Draw all histograms, some of them in a stack.
if Histogram.stack is True, the histogram is put in the stack.'''
self._BuildStack(self._SortedHistograms(), ytitle='Events')
same = 'same'
if len(self.nostack) == 0:
same = ''
self.supportHist = None
for hist in self.nostack:
hist.Draw()
if not self.supportHist:
self.supportHist = hist
self.stack.Draw(opt + same, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)
if self.supportHist is None:
self.supportHist = self.stack.totalHist
if not self.axisWasSet:
mxsup = self.supportHist.weighted.GetBinContent(
self.supportHist.weighted.GetMaximumBin())
mxstack = self.stack.totalHist.weighted.GetBinContent(
self.stack.totalHist.weighted.GetMaximumBin())
mx = max(mxsup, mxstack)
if ymin is None: ymin = 0.01
if ymax is None: ymax = mx * 1.3
self.supportHist.GetYaxis().SetRangeUser(ymin, ymax)
self.axisWasSet = True
for hist in self.nostack:
if self.blindminx:
hist.Blind(self.blindminx, self.blindmaxx)
hist.Draw('same')
self.DrawLegend()
if TPad.Pad():
TPad.Pad().Update()
def DrawDataOverMCMinus1(self, ymin=-0.5, ymax=0.5):
stackedHists = []
dataHist = None
for hist in self._SortedHistograms():
if hist.stack is False:
dataHist = hist
continue
stackedHists.append(hist)
self._BuildStack(stackedHists, ytitle='Data/MC')
mcHist = self.BGHist()
if dataHist == None:
dataHist = mcHist # this was added to avoid crashes for SR plots (without data)
self.dataOverMCHist = copy.deepcopy(dataHist)
# self.dataOverMCHist.Add(mcHist, -1)
self.dataOverMCHist.Divide(mcHist)
self.dataOverMCHist.Draw()
yaxis = self.dataOverMCHist.GetYaxis()
yaxis.SetRangeUser(ymin + 1., ymax + 1.)
yaxis.SetTitle('Data/MC')
yaxis.SetNdivisions(5)
fraclines = 0.2
if ymax <= 0.2 or ymin >= -0.2:
fraclines = 0.1
self.DrawRatioLines(self.dataOverMCHist, fraclines, 1.)
if TPad.Pad():
TPad.Pad().Update()
def DrawRatioStack(self,
opt='',
xmin=None,
xmax=None,
ymin=None,
ymax=None):
'''Draw ratios.
The stack is considered as a single histogram.'''
denom = None
# import pdb; pdb.set_trace()
histForRatios = []
denom = None
for hist in self._SortedHistograms():
if hist.stack is False:
# if several unstacked histograms, the highest layer is used
denom = hist
continue
histForRatios.append(hist)
self._BuildStack(histForRatios, ytitle='MC/Data')
self.stack.Divide(denom.obj)
if self.blindminx and self.blindmaxx:
self.stack.Blind(self.blindminx, self.blindmaxx)
self.stack.Draw(opt, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)
self.ratios = []
for hist in self.nostack:
if hist is denom: continue
ratio = copy.deepcopy(hist)
ratio.obj.Divide(denom.obj)
ratio.obj.Draw('same')
self.ratios.append(ratio)
self.DrawLegend(ratio=True)
self.DrawRatioLines(denom, 0.2, 1)
if TPad.Pad():
TPad.Pad().Update()
def DrawStack(self, opt='',
xmin=None, xmax=None, ymin=None, ymax=None, factor=None, print_norm=False):
'''Draw all histograms, some of them in a stack.
if Histogram.stack is True, the histogram is put in the stack.'''
self._BuildStack(self._SortedHistograms(), ytitle='Events')
same = 'same'
if len(self.nostack) == 0:
same = ''
self.supportHist = None
for hist in self.nostack:
# hist.Draw()
if not self.supportHist:
self.supportHist = hist
self.stack.Draw(opt+same,
xmin=xmin, xmax=xmax,
ymin=ymin, ymax=ymax, factor=factor)
if self.supportHist is None:
self.supportHist = self.stack.totalHist
if not self.axisWasSet:
mxsup = self.supportHist.weighted.GetBinContent(
self.supportHist.weighted.GetMaximumBin()
)
mxstack = self.stack.totalHist.weighted.GetBinContent(
self.stack.totalHist.weighted.GetMaximumBin()
)
mx = max(mxsup, mxstack)
if ymin is None:
ymin = 0.01
if ymax is None:
ymax = mx*1.3
self.supportHist.GetYaxis().SetRangeUser(ymin, ymax)
self.axisWasSet = True
for hist in self.nostack:
# import pdb; pdb.set_trace()
if self.blindminx:
hist.Blind(self.blindminx, self.blindmaxx)
# hist.Draw('same')
# print 'Check', hist.name, self.signal2show
if hist.name.find('LQ')!=-1 or hist.name.find('Zprime')!=-1:
if hist.name in self.signal2show:
# print 'PASS!!!!!!!!!!!!!!!!!!!!!!!'
hist.Draw('same')
else:
hist.Draw('same')
if self.supportHist.weighted.GetMaximumBin() < self.supportHist.weighted.GetNbinsX()/2:
# self.legendBorders = 0.62, 0.46, 0.88, 0.89
self.legendPos = 'right'
self.DrawLegend(print_norm=print_norm)
if TPad.Pad():
TPad.Pad().Update()
def DrawDataMinusMCOverData(self, ymin=-0.5, ymax=0.5):
stackedHists = []
dataHist = None
for hist in self._SortedHistograms():
if hist.stack is False:
dataHist = hist
continue
stackedHists.append( hist )
self._BuildStack( stackedHists, ytitle='Data/MC')
mcHist = copy.deepcopy(self.stack.totalHist)
self.dataOverMCHist = copy.deepcopy(dataHist)
# mcHist.Scale(self.dataOverMCHist.Integral()/mcHist.Integral())
self.dataOverMCHist.Add(mcHist, -1)
self.dataOverMCHist.Divide( dataHist )
self.dataOverMCHist.Draw()
yaxis = self.dataOverMCHist.GetYaxis()
yaxis.SetRangeUser(ymin, ymax)
yaxis.SetTitle('(data-MC)/data')
yaxis.SetNdivisions(5)
fraclines= 0.2
if ymax <= 0.2 or ymin>=-0.2:
fraclines = 0.1
self.DrawRatioLines(self.dataOverMCHist, fraclines, 0.)
if TPad.Pad():
TPad.Pad().Update()
def DrawRatio(self, opt=''):
'''Draw ratios : h_i / h_0.
h_0 is the histogram with the smallest layer, and h_i, i>0 are the other histograms.
if the DataMCPlot object contains N histograms, N-1 ratio plots will be drawn.
To take another histogram as the denominator, change the layer of this histogram by doing:
dataMCPlot.Hist("histName").layer = -99 '''
same = ''
denom = None
self.ratios = []
for hist in self._SortedHistograms():
if denom == None:
denom = hist
continue
ratio = copy.deepcopy(hist)
ratio.obj.Divide(denom.obj)
ratio.obj.Draw(same)
self.ratios.append(ratio)
if same == '':
same = 'same'
self.DrawLegend(ratio=True)
if TPad.Pad():
TPad.Pad().Update()
self.lastDraw = 'DrawRatio'
self.lastDrawArgs = [opt]
def DrawStack(self, opt='hist',
xmin=None, xmax=None, ymin=None, ymax=None, print_norm=False,
scale_signal=''):
'''Draw all histograms, some of them in a stack.
if Histogram.stack is True, the histogram is put in the stack.
scale_signal: mc_int -> scale to stack integral'''
self._BuildStack(self._SortedHistograms(), ytitle='Events')
same = 'same'
if len(self.nostack) == 0:
same = ''
self.supportHist = None
for hist in self.nostack:
if hist.style.drawAsData:
hist.Draw('SAME' if self.supportHist else '')
else:
if scale_signal == 'mc_int':
hist.Scale(hist.Yield(weighted=True)/self.stack.integral)
hist.Draw('SAME HIST' if self.supportHist else 'HIST')
if not self.supportHist:
self.supportHist = hist
self.stack.Draw(opt+same,
xmin=xmin, xmax=xmax,
ymin=ymin, ymax=ymax)
if self.supportHist is None:
self.supportHist = self.BGHist()
if not self.axisWasSet:
mxsup = self.supportHist.weighted.GetBinContent(
self.supportHist.weighted.GetMaximumBin()
)
mxstack = self.BGHist().weighted.GetBinContent(
self.BGHist().weighted.GetMaximumBin()
)
mx = max(mxsup, mxstack)
if ymin is None:
ymin = 0.01
if ymax is None:
ymax = mx*1.3
# centrality = self.supportHist.weighted.GetRMS()/(self.supportHist.weighted.GetXaxis().GetXmax() - self.supportHist.weighted.GetXaxis().GetXmin())
# if centrality > 0.15:
# ymax = mx*2.0
self.supportHist.GetYaxis().SetRangeUser(ymin, ymax)
self.axisWasSet = True
for hist in self.nostack:
if self.blindminx and hist.style.drawAsData:
hist.Blind(self.blindminx, self.blindmaxx)
if hist.style.drawAsData:
hist.Draw('SAME')
else:
hist.Draw('SAME HIST')
## if self.supportHist.weighted.GetMaximumBin() < self.supportHist.weighted.GetNbinsX()/2:
## self.legendBorders = 0.62, 0.46, 0.88, 0.89
## self.legendPos = 'right'
self.DrawLegend(print_norm=print_norm)
if TPad.Pad():
TPad.Pad().Update()
def DrawNormalized(self, opt=''):
'''All histograms are drawn as PDFs, even the stacked ones'''
same = ''
for hist in self._SortedHistograms():
hist.obj.DrawNormalized(same + opt)
if same == '':
same = 'same'
self.DrawLegend()
if TPad.Pad():
TPad.Pad().Update()
def Draw(self, opt=''):
'''All histograms are drawn.'''
same = ''
self.supportHist = None
for hist in self._SortedHistograms():
if self.supportHist is None:
self.supportHist = hist
hist.Draw(same + opt)
if same == '':
same = 'same'
yaxis = self.supportHist.GetYaxis()
yaxis.SetRangeUser(0.01, ymax(self._SortedHistograms()))
self.DrawLegend()
if TPad.Pad():
TPad.Pad().Update()
def DrawNormalizedStack(self, opt='',
xmin=None, xmax=None, ymin=0.001, ymax=None):
'''Draw all histograms, some of them in a stack.
if Histogram.stack is True, the histogram is put in the stack.
all histograms out of the stack, and the stack itself, are shown as PDFs.'''
self._BuildStack(self._SortedHistograms(), ytitle='p.d.f.')
self.stack.DrawNormalized(opt,
xmin=xmin, xmax=xmax,
ymin=ymin, ymax=ymax)
for hist in self.nostack:
hist.obj.DrawNormalized('same')
self.DrawLegend()
if TPad.Pad():
TPad.Pad().Update()
def DrawDataOverMCMinus1(self, ymin=-0.5, ymax=0.5):
stackedHists = []
dataHist = None
for hist in self._SortedHistograms():
if hist.stack is False:
dataHist = hist
continue
stackedHists.append(hist)
self._BuildStack(stackedHists, ytitle='Data/MC')
mcHist = self.BGHist()
if dataHist == None: dataHist = mcHist # this was added to avoid crashes for SR plots (without data)
self.dataOverMCHist = copy.deepcopy(dataHist)
self.dataOverMCHist.Divide(mcHist)
self.mcHist_err = copy.deepcopy(mcHist)
self.mcHist_err.Divide(mcHist)
self.mcHist_err.weighted.SetFillColor(kGray)
self.mcHist_err.weighted.SetMarkerStyle(0)
self.mcHist_err.weighted.SetFillStyle(1001) #standard 3244, check out at https://root.cern.ch/root/html402/TAttFill.html
# self.mcHist_err.weighted.SetFillStyle(3544) #standard 3244, check out at https://root.cern.ch/root/html402/TAttFill.html
self.mcHist_err.Draw('e2')
self.dataOverMCHist.Draw('same')
yaxis = self.mcHist_err.GetYaxis()
yaxis.SetRangeUser(ymin + 1., ymax + 1.)
# yaxis.SetTitle('Data/Bkg')
yaxis.SetTitle('Residuals')
yaxis.SetNdivisions(5)
yaxis.SetLabelSize(0.1)
yaxis.SetTitleSize(0.1)
yaxis.SetTitleOffset(0.7)
xaxis = self.mcHist_err.GetXaxis()
xaxis.SetTitle(self.xtitle)
xaxis.SetLabelSize(0.1)
xaxis.SetTitleSize(0.1)
fraclines = 0.2
if ymax <= 0.2 or ymin >= -0.2:
fraclines = 0.1
self.DrawRatioLines(self.dataOverMCHist, fraclines, 1.)
if TPad.Pad():
TPad.Pad().Update()
def DrawNormalizedRatioStack(self,
opt='',
xmin=None,
xmax=None,
ymin=None,
ymax=None):
'''Draw ratios.
The stack is considered as a single histogram.
All histograms are normalized before computing the ratio'''
denom = None
histForRatios = []
for hist in self._SortedHistograms():
# taking the first histogram (lowest layer)
# as the denominator histogram.
if denom == None:
denom = copy.deepcopy(hist)
continue
# other histograms will be divided by the denominator
histForRatios.append(hist)
self._BuildStack(histForRatios, ytitle='MC p.d.f. / Data p.d.f.')
self.stack.Normalize()
denom.Normalize()
self.stack.Divide(denom.weighted)
self.stack.Draw(opt, xmin=xmin, xmax=xmax, ymin=ymin, ymax=ymax)
self.ratios = []
for hist in self.nostack:
# print 'nostack ', hist
ratio = copy.deepcopy(hist)
ratio.Normalize()
ratio.obj.Divide(denom.weighted)
ratio.obj.Draw('same')
self.ratios.append(ratio)
self.DrawLegend(ratio=True)
self.DrawRatioLines(denom, xmin, xmax)
if TPad.Pad():
TPad.Pad().Update()
self.lastDraw = 'DrawNormalizedRatioStack'
self.lastDrawArgs = [opt]
'higgs_rescaled_pt',
'jet1_e',
'jet2_e',
'jet1_bmatch',
'jet2_bmatch',
'jet1_b',
'jet2_b',
'misenergy_m',
'misenergy_pz',
'misenergy_pt',
]
args = {
'jet1_b': dict(nbins=2, xmin=0, xmax=2),
'jet2_b': dict(nbins=2, xmin=0, xmax=2),
'jet1_bmatch': dict(nbins=2, xmin=0, xmax=2),
'jet2_bmatch': dict(nbins=2, xmin=0, xmax=2),
}
cut = 'jet1_e>0 && jet2_e>0'
canvas = SplitCanvas(len(vars), 'canvas', 'title', 400)
cp = TreeComparator(tc, tj, 'colin', 'janik', normalize=-1)
for ivar, var in enumerate(vars):
canvas.cd(ivar + 1)
print TPad.Pad()
kwargs = args.get(var, dict())
cp.draw(var, cut=cut, **kwargs)
def DrawStack(self, opt='',
xmin=None, xmax=None, ymin=None, ymax=None, print_norm=False,
scale_signal='', dataAsPoisson=False):
'''Draw all histograms, some of them in a stack.
if Histogram.stack is True, the histogram is put in the stack.
scale_signal: mc_int -> scale to stack integral'''
self._BuildStack(self._SortedHistograms(), ytitle='Events')
same = 'same'
if len(self.nostack) == 0:
same = ''
self.supportHist = None
histg = None
for hist in self.nostack:
if hist.style.drawAsData:
hist.Draw('SAME' if self.supportHist else '')
else:
if scale_signal == 'mc_int':
print "Scale to unity"
hist.Scale(hist.Yield(weighted=True)/self.stack.integral)
hist.Draw('SAME HIST' if self.supportHist else 'HIST')
# use nostack hist only if data, since signal might peak at different position
if not self.supportHist and (hist.name.find("data") >= 0):
self.supportHist = hist
self.stack.Draw(opt+same,
xmin=xmin, xmax=xmax,
ymin=ymin, ymax=ymax)
if self.supportHist is None:
self.supportHist = self.stack.totalHist
if (self.supportHist.weighted.GetMaximumBin() < self.supportHist.weighted.GetNbinsX()/2) and (0.5*self.supportHist.weighted.GetBinContent(self.supportHist.weighted.GetMaximumBin()) > self.supportHist.weighted.GetBinContent(self.supportHist.weighted.GetMinimumBin())):
# for falling spectra, put legend on the right
self.legendBorders = 0.62, 0.46, 0.88, 0.89
self.legendPos = 'right'
if not self.axisWasSet:
mxsup = self.supportHist.weighted.GetBinContent(
self.supportHist.weighted.GetMaximumBin()
)
mxstack = self.stack.totalHist.weighted.GetBinContent(
self.stack.totalHist.weighted.GetMaximumBin()
)
mx = max(mxsup, mxstack)
if ymin is None:
ymin = 0.01
if ymax is None:
ymax = mx*1.3
if self.legendPos == 'left':
# mind that this does not depend on the number of legend entries
# print len(self._SortedHistograms())
ymax = mx*2.
self.supportHist.GetYaxis().SetRangeUser(ymin, ymax)
# self.supportHist.GetYaxis().SetTitleOffset(1.3)
self.axisWasSet = True
for hist in self.nostack:
if self.blindminx and hist.style.drawAsData:
hist.Blind(self.blindminx, self.blindmaxx)
if hist.style.drawAsData:
if dataAsPoisson:
hist.obj.SetBinErrorOption(TH1.kPoisson)
hist.Draw('E SAME')
else:
hist.Draw('SAME')
else:
hist.Draw('SAME HIST')
self.DrawLegend(print_norm=print_norm)
if TPad.Pad():
TPad.Pad().Update()
