def Create_Legend(x1,
y1,
x2,
y2,
font=42,
text_size=0.045,
fill=0,
border_size=1,
entry_sep=0,
margin=0.3,
show_stats=False,
ncols=1):
leg = TLegend(x1, y1, x2, y2)
leg.SetTextFont(font)
leg.SetTextSize(text_size)
leg.SetFillColor(fill)
leg.SetBorderSize(border_size)
leg.SetEntrySeparation(entry_sep)
leg.SetMargin(margin)
leg.SetNColumns(ncols)
if show_stats:
leg.SetNColumns(2)
## Creating headers for the legend
leg.AddEntry(0, "", "")
# leg.AddEntry( 0, "#bf{Mean}", "")
leg.AddEntry(0, "#bf{RMSE}", "")
return leg
def phicomparison(rbef,raft,wheel,station,name,title):
hb = barrelSectorAvg( rbef, wheel, station, name+"_bef", title )
ha = barrelSectorAvg( raft, wheel, station, name+"_aft", title )
hsettings(ha); ha.SetLineColor(kBlue); ha.SetLineWidth(3)
hsettings(hb); hb.SetLineColor(kRed); hb.SetLineWidth(3)
acan = TCanvas("can","",1200,700)
leg = TLegend(0.645,0.68,0.845,0.88)
leg.SetFillStyle( 0 )
leg.SetBorderSize(0)
leg.SetMargin( 0.1 )
maxx = hb.GetMaximum()
if maxx < ha.GetMaximum():
maxx = ha.GetMaximum()
ha.SetMaximum(1.1*maxx)
hb.SetMaximum(1.1*maxx)
leg.AddEntry(ha, "after TS2", "l")
leg.AddEntry(hb, "before TS2", "l")
ha.Draw("same hist")
hb.Draw("same hist")
leg.Draw("same")
acan.SaveAs(name+".png")
acan.Clear()
return {"before":hb,"after":ha}
def plotHists(hists,xtitle,plotname,header,ctexts=[ ],otext="",logy=False,y1=0.70):
colors = [ kBlue, kRed, kGreen+2, kOrange, kMagenta+1 ]
canvas = TCanvas('canvas','canvas',100,100,800,700)
canvas.SetMargin(0.12,0.03,0.14,0.06 if otext else 0.03)
textsize = 0.040
height = 1.28*(len(hists)+1)*textsize
y1
legend = TLegend(0.65,y1,0.88,y1-height)
legend.SetTextSize(textsize)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetTextFont(62)
legend.SetHeader(header)
legend.SetTextFont(42)
legend.SetMargin(0.2)
latex = TLatex()
latex.SetTextAlign(13)
latex.SetTextFont(42)
latex.SetNDC(True)
frame = hists[0]
frame.GetXaxis().SetTitle(xtitle)
frame.GetYaxis().SetTitle("Fraction [%]")
frame.GetXaxis().SetLabelSize(0.074)
frame.GetYaxis().SetLabelSize(0.046)
frame.GetXaxis().SetTitleSize(0.048)
frame.GetYaxis().SetTitleSize(0.052)
frame.GetXaxis().SetTitleOffset(1.38)
frame.GetYaxis().SetTitleOffset(1.12)
frame.GetXaxis().SetLabelOffset(0.009)
frame.SetMaximum(1.25*max(h.GetMaximum() for h in hists))
if logy:
canvas.SetLogy()
frame.SetMinimum(1e-3)
else:
frame.SetMinimum(0)
for i, hist in enumerate(hists):
hist.Draw('HISTE0E1SAME')
hist.SetLineWidth(2)
hist.SetLineColor(colors[i%len(colors)])
legend.AddEntry(hist,hist.GetTitle(),'le')
legend.Draw()
for i, text in enumerate(ctexts):
textsize = 0.024 #if i>0 else 0.044
latex.SetTextSize(textsize)
latex.DrawLatex(0.14,0.98-canvas.GetTopMargin()-1.7*i*textsize,text)
if otext:
latex.SetTextSize(0.05)
latex.SetTextAlign(31)
latex.DrawLatex(1.-canvas.GetRightMargin(),1.-0.84*canvas.GetTopMargin(),otext)
canvas.SaveAs(plotname+".png")
canvas.SaveAs(plotname+".pdf")
canvas.Close()
for hist in hists:
gDirectory.Delete(hist.GetName())
def getLegend():
legend = TLegend(0.55010112, 0.7183362, 0.70202143, 0.919833)
legend.SetTextSize(0.032)
legend.SetLineColor(0)
legend.SetShadowColor(0)
legend.SetLineStyle(1)
legend.SetLineWidth(1)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetMargin(0.35)
return legend
def getLegend(x1=0.70010112,y1=0.123362,x2=0.90202143,y2=0.279833): legend = TLegend(x1,y1,x2,y2) legend.SetTextSize(0.032) legend.SetLineColor(0) legend.SetShadowColor(0) legend.SetLineStyle(1) legend.SetLineWidth(1) legend.SetFillColor(0) legend.SetFillStyle(0) legend.SetMargin(0.35) return legend
def setup_canvas(hist_name):
canvas = TCanvas(hist_name, hist_name, 0, 0, 800, 800)
canvas.SetMargin(0.13, 0.05, 0.12, 0.05)
canvas.SetTicks(1, 1)
leg = TLegend(0.3, 0.15, 0.75, 0.4)
leg.SetNColumns(3)
leg.SetBorderSize(0)
leg.SetTextSize(0.03)
leg.SetTextFont(42)
leg.SetMargin(0.2)
leg.SetHeader("Train setup: #it{N}_{ev}^{training}, #it{n}_{#it{#varphi}}" +\
" #times #it{n}_{#it{r}} #times #it{n}_{#it{z}}", "C")
return canvas, leg
def make_legend(x1=.65,
y2=.88,
nentries=2,
scale=1,
name='l',
y1=None,
margin=.25,
x2=None):
x2 = .95 if x2 is None else x2
y1 = y2 - nentries * .05 * scale if y1 is None else y1
l = TLegend(x1, y1, x2, y2)
l.SetName(name)
l.SetTextFont(42)
l.SetTextSize(0.03 * scale)
l.SetMargin(margin)
return l
def checklegend(samples,tag=""):
"""Check legend entries: colors, titles, ..."""
# https://root.cern.ch/doc/master/classTLegend.html
LOG.header("checklegend"+tag.replace(' ',''))
output = ensuredir('plots')
fname = "%s/testStyle_legend%s"%(output,tag)
#height = 0.05*(len(samples))
xdim = 550
ydim = 50*(len(samples)+2)
#width = 0.4
#x1, y1 = 0.1, 0.9
print ">>> Canvas: %sx%s (nsamples=%d)"%(xdim,ydim,len(samples))
canvas = TCanvas('canvas','canvas',xdim,ydim)
#legend = TLegend(x1,y1,x1+width,y1-height)
legend = TLegend(0,0,1,1)
legend.SetBorderSize(0)
legend.SetMargin(0.12)
#legend.SetTextSize(tsize)
#legend.SetNColumns(ncols)
#legend.SetColumnSeparation(colsep)
#legend.SetHeader("HTT style",'C')
legend.SetTextFont(42) # bold for title
hists = [ ]
for sample in samples:
color = STYLE.getcolor(sample,verb=2)
title = STYLE.gettitle(sample,latex=True,verb=2)
style = 'ep' if 'Data' in sample else 'f'
hist = TH1F(sample,title,1,0,1)
hist.SetFillColor(color)
#hist.SetLineColor(kBlack)
hist.SetLineWidth(2)
hist.SetMarkerColor(kBlack)
#hist.SetMarkerStyle(1)
legend.AddEntry(hist,title,style)
if 'Data' in sample: hist.Draw('E1')
hists.append(hist)
legend.Draw()
canvas.SaveAs(fname+".png")
canvas.SaveAs(fname+".pdf")
canvas.Close()
def DrawText(can,text='text',x1=None,y1=None,x2=None,y2=None,angle=0,align='',textsize=18,totalentries=1) :
if x1 == None : x1 = 0.2
if x2 == None : x2 = 0.5
if can.GetPrimitive('pad_top') :
if y1 == None : y1 = 0.73
if y2 == None : y2 = 0.93
else :
if y1 == None : y1 = 0.78
if y2 == None : y2 = 0.94
can.cd()
if can.GetPrimitive('pad_top') :
can.GetPrimitive('pad_top').cd()
from ROOT import TLegend
leg = TLegend(x1,y1,x2,y2)
leg.SetMargin(0)
leg.SetName(can.GetName()+'_text')
tobject_collector.append(leg)
leg.SetTextSize(textsize)
leg.SetTextFont(43)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
if type(text) == type('') :
text = [text]
total = 0
for i in text :
leg.AddEntry(0,i,'')
total += 1
while (total < totalentries) :
leg.AddEntry(0,'','')
total += 1
leg.Draw()
can.Modified()
#can.Update()
return
if (i > 0):
binwidths.append(bins[i] - bins[i - 1])
else:
binwidths.append(30.0)
#print binwidths
normCMS = normalizeGraph(unnormCMS, binwidths)
normCMS.SetMarkerStyle(kFullCircle)
normCMS.SetMarkerSize(1.4)
normCMS.SetMarkerColor(kBlue + 2)
normCMS.SetLineColor(kBlue + 2)
normCMS.Draw('apz')
normCMS.SetMaximum(0.3)
leg = TLegend(0.4, 1. - gPad.GetTopMargin() - 0.03 - 0.18,
1. - gPad.GetRightMargin() - 0.02,
1. - gPad.GetTopMargin() - 0.03, '', 'NDC')
leg.SetMargin(0.15)
#leg.Dump()
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.AddEntry(normCMS, 'CMS, |y|<2, #sqrt{s}=7 TeV', 'pe')
if (D0):
D0.Draw('pz')
leg.AddEntry(D0, 'D#oslash, |y|<1.8, #sqrt{s}=1.96 TeV', 'pe')
else:
leg.SetY1(1. - gPad.GetTopMargin() - 0.03 - 0.12)
if (CDF):
CDF.Draw('pz')
leg.AddEntry(CDF, 'CDF, |y|<0.4, #sqrt{s}=1.8 TeV', 'pe')
#leg.Dump()
leg.Draw('same')
l.DrawLatex(1.0 - gPad.GetRightMargin() - 0.04,
def main():
rpcrateB = RPCRates('316111',"m")
rpcrateA = RPCRates('323726',"m")
rpcrateA.rates_ = load_json("ratesAt1p5After.json")
rpcrateB.rates_ = load_json("ratesAt1p5before.json")
hREP4A = rollavg( rpcrateA.rates_, "hREP4A", "RE+4/R3", "RE+4_R3_" )
hREM4A = rollavg( rpcrateA.rates_, "hREM4A", "RE-4/R3", "RE-4_R3_" )
hREP4B = rollavg( rpcrateB.rates_, "hREP4B", "RE+4/R3", "RE+4_R3_" )
hREM4B = rollavg( rpcrateB.rates_, "hREM4B", "RE-4/R3", "RE-4_R3_" )
hsettings(hREP4A); hREP4A.SetLineColor(kBlue)
hsettings(hREM4A); hREM4A.SetLineColor(kBlue)
hsettings(hREP4B); hREP4B.SetLineColor(kRed)
hsettings(hREM4B); hREM4B.SetLineColor(kRed)
acan = TCanvas("can","",1200,700)
leg = TLegend(0.645,0.68,0.845,0.88)
leg.SetFillStyle( 0 )
leg.SetBorderSize(0)
leg.SetMargin( 0.1 )
#leg.AddEntry(hREP4B, "before TS2", "l")
#leg.AddEntry(hREP4A, "after TS2", "l")
#hREP4B.Draw("same hist")
#hREP4A.Draw("same hist")
#leg.Draw("same")
#acan.SaveAs("compREP4.png")
#acan.Clear()
#return
#leg.AddEntry(hREM4B, "before TS2", "l")
#leg.AddEntry(hREM4A, "after TS2", "l")
#hREM4B.Draw("same hist")
#hREM4A.Draw("same hist")
#leg.Draw("same")
#acan.Update()
#acan.SaveAs("compREM4.png")
#acan.Clear()
#return
hREP4A.Divide(hREP4B)
hREM4A.Divide(hREM4B)
hREP4A.SetLineColor(kBlue); hREP4A.SetLineWidth(3)
hREM4A.SetLineColor(kRed); hREM4A.SetLineWidth(3)
hREP4A.GetYaxis().SetTitle("rate ratio")
hREM4A.GetYaxis().SetTitle("rate ratio")
hREP4A.SetMaximum(1.5)
hREM4A.SetMaximum(1.5)
#leg.AddEntry(hREP4A, "RE+4", "l")
#leg.AddEntry(hREM4A, "RE-4", "l")
#hREP4A.Draw("same hist")
#hREM4A.Draw("same hist")
#leg.Draw("same")
#acan.SaveAs("ratiosRE4.png")
#acan.Clear()
#return
mapcreator = RPCMapCreator()
histsB = mapcreator.create2Dhistograms( rpcrateB.rates_, 'RPC', "run316111")
histsA = mapcreator.create2Dhistograms( rpcrateA.rates_, 'RPC', "run323726")
#prep4_b = histsB["RE+4"].ProjectionX ("rep4b_pfx"); prep4_a = histsA["RE+4"].ProjectionX ("rep4a_pfx")
#prem4_b = histsB["RE-4"].ProjectionX ("rem4b_pfx"); prem4_a = histsA["RE-4"].ProjectionX ("rem4a_pfx")
#prep4_b = histsB["RE+4"].ProfileX ("rep4b_pfx"); prep4_a = histsA["RE+4"].ProfileX ("rep4a_pfx")
#prem4_b = histsB["RE-4"].ProfileX ("rem4b_pfx"); prem4_a = histsA["RE-4"].ProfileX ("rem4a_pfx")
rep4B = histsB["RE+4"]; rep4A = histsA["RE+4"]
rem4B = histsB["RE-4"]; rem4A = histsA["RE-4"]
#prep4_b.SetLineColor(kBlue)
#prep4_a.SetLineColor(kRed)
#prem4_b.SetLineColor(kBlue)
#prem4_a.SetLineColor(kRed)
#acan.cd()
rep4A.Divide(rep4B)
rep4A.SetMaximum(1.1)
rep4A.SetMinimum(0.9)
rep4A.Draw("text89 colz")
acan.SaveAs("ratios2DREP4.png")
def savePlots(title,
saveName,
listFromats,
plot,
Histos,
keyHisto,
listLegend,
options,
ratios=None,
legendName=""):
#create canvas
c = {}
pads = {}
if options.doRatio:
c[keyHisto] = TCanvas(saveName, keyHisto + plot.title, 700,
700 + 24 * len(listFlavors))
pads["hist"] = TPad("hist", saveName + plot.title, 0,
0.11 * len(listFlavors), 1.0, 1.0)
else:
c[keyHisto] = TCanvas(keyHisto, saveName + plot.title, 700, 700)
pads["hist"] = TPad("hist", saveName + plot.title, 0, 0., 1.0, 1.0)
pads["hist"].Draw()
if ratios:
for r in range(0, len(ratios)):
pads["ratio_" + str(r)] = TPad("ratio_" + str(r),
saveName + plot.title + str(r), 0,
0.11 * r, 1.0, 0.11 * (r + 1))
pads["ratio_" + str(r)].Draw()
pads["hist"].cd()
#canvas style
if plot.logY: pads["hist"].SetLogy()
if plot.grid: pads["hist"].SetGrid()
#legend
leg = TLegend(0.6, 0.4, 0.8, 0.6)
leg.SetMargin(0.12)
leg.SetTextSize(0.035)
leg.SetFillColor(10)
leg.SetBorderSize(0)
#draw histos
first = True
option = drawOption
optionSame = drawOption + "same"
if plot.doPerformance:
option = "AP"
optionSame = "sameP"
for i in range(0, len(Histos)):
if Histos[i] is None: continue
if first:
if not plot.doPerformance:
Histos[i].GetPainter().PaintStat(ROOT.gStyle.GetOptStat(), 0)
Histos[i].SetTitle(title)
Histos[i].Draw(option)
first = False
else:
Histos[i].Draw(optionSame)
#Fill legend
if plot.legend and len(Histos) % len(listLegend) == 0:
r = len(Histos) / len(listLegend)
index = i - r * len(listLegend)
while (index < 0):
index += len(listLegend)
legName = legendName.replace("KEY", listLegend[index])
if i < len(listLegend):
legName = legName.replace("isVAL", options.ValRel)
else:
legName = legName.replace("isVAL", options.RefRel)
if drawOption == "HIST":
leg.AddEntry(Histos[i], legName, "L")
else:
leg.AddEntry(Histos[i], legName, "P")
#Draw legend
if plot.legend and options.drawLegend: leg.Draw("same")
tex = None
if options.printBanner:
print(type(options.printBanner))
tex = TLatex(0.55, 0.75, options.Banner)
tex.SetNDC()
tex.SetTextSize(0.05)
tex.Draw()
#save canvas
if ratios:
for r in range(0, len(ratios)):
pads["ratio_" + str(r)].cd()
if ratios[r] is None: continue
pads["ratio_" + str(r)].SetGrid()
ratios[r].GetYaxis().SetTitle(listLegend[r] + "-jets")
ratios[r].GetYaxis().SetTitleSize(0.15)
ratios[r].GetYaxis().SetTitleOffset(0.2)
ratios[r].GetYaxis().SetNdivisions(3, 3, 2)
ratios[r].Draw("")
unity.Draw("same")
for format in listFromats:
save = saveName + "." + format
c[keyHisto].Print(save)
return [c, leg, tex, pads]
class DataMCPlot(object):
'''Handles a Data vs MC plot.
Features a list of histograms (some of them being stacked),
and several Drawing functions.
'''
_f_keeper = {}
_t_keeper = {}
def __init__(self, name):
self.histosDict = {}
self.histos = []
self.supportHist = None
self.name = name
self.stack = None
self.legendOn = True
self.legend = None
# self.legendBorders = 0.20, 0.46, 0.44, 0.89
# self.legendPos = 'left'
self.legendBorders = 0.20, 0.78, 0.80, 0.88
self.legendPos = 'top'
# self.lastDraw = None
# self.lastDrawArgs = None
self.nostack = None
self.blindminx = None
self.blindmaxx = None
self.groups = {}
self.axisWasSet = False
self.histPref = histPref
def __contains__(self, name):
return name in self.histosDict
def __getitem__(self, name):
return self.histosDict[name]
def readTree(self,
file_name,
tree_name='tree',
verbose=False,
friend_func=None):
'''Cache files/trees'''
if file_name in self.__class__._t_keeper:
ttree = self.__class__._t_keeper[file_name]
if verbose:
print 'got cached tree', ttree
else:
tfile = self.__class__._f_keeper[file_name] = TFile.Open(file_name)
ttree = self.__class__._t_keeper[file_name] = tfile.Get(tree_name)
if verbose:
print 'read tree', ttree, 'from file', file_name
if friend_func:
file_name = friend_func(file_name)
friend_tree = self.readTree(file_name, tree_name, verbose)
ttree.AddFriend(friend_tree)
gROOT.cd()
return ttree
def Blind(self, minx, maxx, blindStack):
self.blindminx = minx
self.blindmaxx = maxx
if self.stack and blindStack:
self.stack.Blind(minx, maxx)
if self.nostack:
for hist in self.nostack:
if hist.style.drawAsData:
hist.Blind(minx, maxx)
def AddHistogram(self, name, histo, layer=0, legendLine=None, stack=True):
'''Add a ROOT histogram, with a given name.
Histograms will be drawn by increasing layer.'''
tmp = Histogram(name, histo, layer, legendLine, stack=stack)
self.histos.append(tmp)
self.histosDict[name] = tmp
return tmp
def Group(self,
groupName,
namesToGroup,
layer=None,
style=None,
silent=False):
'''Group all histos with names in namesToGroup into a single
histo with name groupName. All histogram properties are taken
from the first histogram in namesToGroup.
See UnGroup as well
'''
groupHist = None
realNames = []
actualNamesInGroup = []
for name in namesToGroup:
hist = self.histosDict.get(name, None)
if hist is None:
if not silent:
print 'warning, no histo with name', name
continue
if groupHist is None:
groupHist = hist.Clone(groupName)
self.histos.append(groupHist)
self.histosDict[groupName] = groupHist
else:
groupHist.Add(hist)
actualNamesInGroup.append(name)
realNames.append(hist.realName)
hist.on = False
if groupHist:
self.groups[groupName] = actualNamesInGroup
groupHist.realName = ','.join(realNames)
if style is not None:
groupHist.SetStyle(style)
self._ApplyPrefs()
def UnGroup(self, groupName):
'''Ungroup groupName, recover the histograms in the group'''
group = self.groups.get(groupName, None)
if group is None:
print groupName, 'is not a group in this plot.'
return
for name in group:
self.histosDict[name].on = True
self.histosDict[groupName].on = False
def Replace(self, name, pyhist):
'''Not very elegant... should have a clone function in Histogram...'''
oldh = self.histosDict.get(name, None)
if oldh is None:
print 'histogram', name, 'does not exist, cannot replace it.'
return
pythist = copy.deepcopy(pyhist)
pythist.layer = oldh.layer
pythist.stack = oldh.stack
pythist.name = oldh.name
pythist.legendLine = oldh.legendLine
pythist.SetStyle(oldh.style)
pythist.weighted.SetFillStyle(oldh.weighted.GetFillStyle())
index = self.histos.index(oldh)
self.histosDict[name] = pythist
self.histos[index] = pythist
def _SortedHistograms(self, reverse=False):
'''Returns the histogram dictionary, sorted by increasing layer,
excluding histograms which are not "on".
This function is used in all the Draw functions.'''
byLayer = sorted(self.histos, key=attrgetter('layer'))
byLayerOn = [hist for hist in byLayer if (hist.on is True)]
if reverse:
byLayerOn.reverse()
return byLayerOn
def Hist(self, histName):
'''Returns a histogram.
Print the DataMCPlot object to see which histograms are available.'''
return self.histosDict[histName]
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()
# self.lastDraw = 'DrawNormalized'
# self.lastDrawArgs = [ opt ]
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'
# set_trace()
yaxis = self.supportHist.GetYaxis()
yaxis.SetRangeUser(0.01, 1.5 * ymax(self._SortedHistograms()))
self.DrawLegend()
if TPad.Pad():
TPad.Pad().Update()
# self.lastDraw = 'Draw'
# self.lastDrawArgs = [ opt ]
def CreateLegend(self, ratio=False, print_norm=False):
if self.legend is None:
self.legend = TLegend(*self.legendBorders)
self.legend.SetFillColor(0)
self.legend.SetFillStyle(0)
self.legend.SetLineColor(0)
self.legend.SetLineWidth(1)
self.legend.SetNColumns(5) # number of comps / 2 (or 3) + 1
self.legend.SetEntrySeparation(0.2)
self.legend.SetColumnSeparation(0.2)
self.legend.SetBorderSize(0)
self.legend.SetMargin(0.25)
else:
self.legend.Clear()
hists = self._SortedHistograms(reverse=True)
if ratio:
hists = hists[:-1] # removing the last histo.
for index, hist in enumerate(hists):
if print_norm:
if not hist.legendLine:
hist.legendLine = hist.name
hist.legendLine += ' ({norm:.1f})'.format(norm=hist.Yield())
hist.AddEntry(self.legend)
def DrawLegend(self, ratio=False, print_norm=False):
'''Draw the legend.'''
if self.legendOn:
self.CreateLegend(ratio=ratio, print_norm=print_norm)
self.legend.Draw('same')
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 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 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, 0.2, 1)
if TPad.Pad():
TPad.Pad().Update()
# self.lastDraw = 'DrawNormalizedRatioStack'
# self.lastDrawArgs = [ opt ]
def DrawRatioLines(self, hist, frac=0.2, y0=1.):
'''Draw a line at y = 1, at 1+frac, and at 1-frac.
hist is used to get the x axis range.'''
xmin = hist.obj.GetXaxis().GetXmin()
xmax = hist.obj.GetXaxis().GetXmax()
line = TLine()
line.DrawLine(xmin, y0, xmax, y0)
line.SetLineStyle(2)
line.DrawLine(xmin, y0 + frac, xmax, y0 + frac)
line.DrawLine(xmin, y0 - frac, xmax, y0 - frac)
def GetStack(self):
'''Returns stack; builds stack if not there yet'''
if not self.stack:
self._BuildStack(self._SortedHistograms(), ytitle='Events')
return self.stack
def BGHist(self):
return self.GetStack().totalHist
def SignalHists(self):
return [h for h in self.nostack if not h.style.drawAsData]
def DrawStack(self,
opt='',
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 * 2
centrality = self.supportHist.weighted.GetRMS() / (
self.supportHist.weighted.GetXaxis().GetXmax() -
self.supportHist.weighted.GetXaxis().GetXmin())
if centrality > 0.15:
ymax = mx * 2.2
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.legendBorders = 0.20, 0.78, 0.80, 0.88
# self.legendPos = 'right'
self.legendPos = 'top'
self.DrawLegend(print_norm=print_norm)
if TPad.Pad():
TPad.Pad().Update()
# set_trace()
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()
# self.lastDraw = 'DrawNormalizedStack'
# self.lastDrawArgs = [ opt ]
def Rebin(self, factor):
'''Rebin, and redraw.'''
# the dispatching technique is not too pretty,
# but keeping a self.lastDraw function initialized to one of the Draw functions
# when calling it creates a problem in deepcopy.
for hist in self.histos:
hist.Rebin(factor)
self.axisWasSet = False
def NormalizeToBinWidth(self):
'''Normalize each Histograms bin to the bin width.'''
for hist in self.histos:
hist.NormalizeToBinWidth()
def WriteDataCard(self,
filename=None,
verbose=True,
mode='RECREATE',
dir=None,
postfix=''):
'''Export current plot to datacard'''
if not filename:
filename = self.name + '.root'
outf = TFile(filename, mode)
if dir and outf.Get(dir):
print 'Directory', dir, 'already present in output file'
if any(
outf.Get(dir + '/' + hist.name + postfix)
for hist in self._SortedHistograms()):
print 'Recreating file because histograms already present'
outf = TFile(filename, 'RECREATE')
if dir:
outf_dir = outf.Get(dir)
if not outf_dir:
outf_dir = outf.mkdir(dir)
outf_dir.cd()
for hist in self._SortedHistograms():
'Writing', hist, 'as', hist.name
hist.weighted.Write(hist.name + postfix)
outf.Write()
def _BuildStack(self, hists, ytitle=None):
'''build a stack from a list of Histograms.
The histograms for which Histogram.stack is False are put in self.nostack'''
self.stack = None
self.stack = Stack(self.name + '_stack', ytitle=ytitle)
self.nostack = []
for hist in hists:
if hist.stack:
self.stack.Add(hist)
else:
self.nostack.append(hist)
def _GetHistPref(self, name):
'''Return the preference dictionary for a given component'''
thePref = None
for prefpat, pref in self.histPref.iteritems():
if fnmatch.fnmatch(name, prefpat):
if thePref is not None:
print 'several matching preferences for', name
thePref = pref
if thePref is None:
print 'cannot find preference for hist', name
thePref = {'style': Style(), 'layer': 999, 'legend': name}
return thePref
def _ApplyPrefs(self):
for hist in self.histos:
pref = self._GetHistPref(hist.name)
hist.layer = pref['layer']
hist.SetStyle(pref['style'])
hist.legendLine = pref['legend']
def __str__(self):
if self.stack is None:
self._BuildStack(self._SortedHistograms(), ytitle='Events')
tmp = [' '.join(['DataMCPlot: ', self.name])]
tmp.append('Histograms:')
for hist in self._SortedHistograms(reverse=True):
tmp.append(' '.join(['\t', str(hist)]))
tmp.append(
'Stack yield = {integ:7.1f}'.format(integ=self.stack.integral))
return '\n'.join(tmp)
def make_time_rod_evo(error_dict, rod_dict, results, doLock):
c2 = TCanvas( 'c2', 'c2', 1000, 600)
leg = TLegend(0.18,0.85,0.45,0.55)
leg.SetLineColor(0)
leg.SetFillStyle(0)
leg.SetShadowColor(0)
leg.SetBorderSize(0)
leg.SetNColumns(2)
R15 = TLine(431,0,431,60)
R15.SetLineColorAlpha(kPink+10,0.4)
R15.SetLineWidth(4)
R16 = TLine(1820,0,1820,60)
R16.SetLineColorAlpha(kMagenta+10,0.4)
R16.SetLineWidth(4)
R17 = TLine(3376,0,3376,60)
R17.SetLineColorAlpha(kGreen-3,0.4)
R17.SetLineWidth(4)
TS1 = TLine(431,0,432,60)
TS1.SetLineColorAlpha(kPink+10,0.5)
TS1.SetLineWidth(5)
TS2 = TLine(1415,0,1415,60)
TS2.SetLineColorAlpha(kMagenta+3,0.5)
TS2.SetLineWidth(5)
leg2 = TLegend(0.18,0.45,0.35,0.55)
leg2.SetLineColor(0)
leg2.SetFillStyle(0)
leg2.SetShadowColor(0)
leg2.SetBorderSize(0)
gStyle.SetLegendTextSize(0.030)
leg2.AddEntry(R15, "End of 2015", 'lf')
leg2.AddEntry(R16, "End of 2016", 'lf')
leg2.AddEntry(R17, "End of 2017", 'lf')
#leg2.AddEntry(TS2, "TS2", 'lf')
for key,val in rod_dict.items():
TS1.SetY2(val*0.5)
TS2.SetY2(val+1)
R15.SetY2(val*0.3)
R16.SetY2(val*0.5)
R17.SetY2(val*0.8)
times = {}
times.clear()
for e in error_bits:
times['0x'+e] = [0]
for error in results:
pos_rod = error.text.find("ROD") + 4
pos_lock = error.text.find("Lock") + 15
pos_buff = error.text.find("buffer") + 17
if error.msgID == 'TRT::ROD05Module':
rod = '0x'+str(error.text[pos_rod:pos_rod+6])
else:
rod = str(error.text[pos_rod:pos_rod+8])
lock = str(error.text[pos_lock:pos_lock+3])
buff = str(error.text[pos_buff:pos_buff+3])
if key == rod and doLock and lock != '0xf':
times[lock].append(error.sb_total_time)
leg.Clear()
mg = TMultiGraph()
for e in error_bits:
errs = []
for i,x in enumerate(times['0x'+e]):
errs.append(i+0.0)
errs.append(errs[-1])
#times['0x'+e].append(1800.0)
times['0x'+e].append(results[-1].sb_total_time)
gr = TGraph(len(times['0x'+e]), array(times['0x'+e]), array(errs))
gr.SetMarkerSize(0.7)
if bin(int('0x'+e, 16))[2:].zfill(4) == '0111':
leg.AddEntry(gr,'GOL 3',"lp");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1011':
leg.AddEntry(gr,'GOL 2',"lp");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1101':
leg.AddEntry(gr,'GOL 1',"lp");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1110':
leg.AddEntry(gr,'GOL 0',"lp");
else:
leg.AddEntry(gr,bin(int('0x'+e, 16))[2:].zfill(4),"lp");
mg.Add(gr,"pl");
mg.SetTitle("; Hours of stable beams; # of rocketio io lock errors");
mg.Draw("PMC PLC a");
R15.Draw()
R16.Draw()
R17.Draw()
#TS1.Draw()
#TS2.Draw()
AtlasStyle.ATLAS_LABEL(0.19,.88, 1, "Internal")
leg.Draw()
leg2.Draw()
AtlasStyle.myText(0.4, 0.88, kBlack, "ROD: " + key)
leg.SetMargin(0.5)
gPad.Modified()
mg.GetXaxis().SetLimits(0,results[-1].sb_total_time)
mg.SetMinimum(0.)
mg.SetMaximum(val+1)
c2.Update()
c2.Print("plots/time_"+key+".pdf")
c2.Clear()
label = ROOT.TLatex()
label.SetNDC()
label.SetTextSize(0.04)
label.SetTextFont(42)
#label.DrawLatex(0.575, 0.645, "#sqrt{s} = 13 TeV, 70fb^{-1}")
label.DrawLatex(text_x, 0.785, "#sqrt{s} = 13 TeV, %sfb^{-1}" % str(fb))
label = ROOT.TLatex()
label.SetNDC()
label.SetTextSize(0.04)
label.SetTextFont(42)
#label.DrawLatex(0.575, 0.645, "#sqrt{s} = 13 TeV, 70fb^{-1}")
label.DrawLatex(text_x, 0.73, "|y*| < %s" % str(rapidity))
legend = TLegend(0.125, 0.125, 0.6, 0.3)
legend.SetMargin(0.15)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.AddEntry(theory_line, particle_symbol, "l")
legend.AddEntry(data_line, "Observed 95% CL upper limit", "lp")
legend.AddEntry(brazil_line, "Expected 95% CL upper limit", "l")
legend.AddEntry(brazil_yellow, "Expected #pm1#sigma and #pm2#sigma")
legend.Draw()
canvas.SaveAs(op.join(args.output_dir, "brazil-{0}.png".format(job_id)))
canvas.SaveAs(op.join(args.output_dir, "brazil-{0}.pdf".format(job_id)))
with open(op.join(args.output_dir, "limits.txt"), "w") as limit_file:
limit_file.write("Observed mass limit: {0} GeV\n".format(x_intersect))
limit_file.write(
"Observed cross section limit: {0} pb\n".format(y_intersect))
projectBin = -1 #all
if thesuper[ikey].projection == "x": projectAxis = "x"
if thesuper[ikey].projection == "y": projectAxis = "y"
if thesuper[ikey].bin != None: projectBin = thesuper[ikey].bin
profileAxis = "no"
if thesuper[ikey].profile == "x": profileAxis = "x"
if thesuper[ikey].profile == "y": profileAxis = "y"
doFill = False
if thesuper[ikey].Fill == "true": doFill = True
if verbose : print("fill option:"+ doFill)
#create canvas
cv[thesuper[ikey].name] = TCanvas(thesuper[ikey].name,thesuper[ikey].title,700,700)
#legend
aleg = TLegend(0.6,0.4,0.8,0.6)
SetOwnership( aleg, 0 )
aleg.SetMargin(0.12)
aleg.SetTextSize(0.035)
aleg.SetFillColor(10)
aleg.SetBorderSize(0)
isFirst = 1
ii = 0
stacklist[thesuper[ikey].name] = THStack("astack"+thesuper[ikey].name,thesuper[ikey].title)
astack = stacklist[thesuper[ikey].name]
for ihname in listname:
for jkey in thedata:
tmpkeys = thedata[jkey].histos.keys()
for tmpname in tmpkeys:
def MakeLegend(can,
x1=.8,
y1=.8,
x2=.9,
y2=.9,
textsize=18,
ncolumns=1,
totalentries=0,
option='f',
skip=[]):
from ROOT import TLegend, TH1, gStyle, TGraph
if can.GetPrimitive('pad_top'):
MakeLegend(can.GetPrimitive('pad_top'),
x1,
y1,
x2,
y2,
textsize,
ncolumns,
totalentries,
skip=skip)
return
if CanvasEmpty(can):
print 'Error: trying to make legend from canvas with 0 plots. Will do nothing.'
return
#
# if a previous version exists from this function, delete it
#
if can.GetPrimitive('legend'):
can.GetPrimitive('legend').Delete()
leg = TLegend(x1, y1, x2, y2)
leg.SetName('legend')
tobject_collector.append(leg)
leg.SetTextFont(43)
leg.SetTextSize(textsize)
leg.SetTextFont(43)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetNColumns(ncolumns)
#
# Add by TH1 GetTitle()
#
the_primitives = can.GetListOfPrimitives()
if can.GetPrimitive('pad_top'):
the_primitives = can.GetPrimitive('pad_top').GetListOfPrimitives()
if can.GetPrimitive('stack'):
the_stack = list(reversed(list(can.GetPrimitive('stack').GetHists())))
the_primitives = the_stack + list(the_primitives)
if type(option) == type(''):
option = [option] * 100
total = 0
for i in the_primitives:
if i.GetName() == 'stack': continue
drawopt = i.GetDrawOption()
if issubclass(type(i), TH1) or issubclass(type(i), TGraph):
if i.GetTitle() in skip:
continue
leg.AddEntry(i, i.GetTitle(), option[total]) # plef
total += 1
#
# Add empty entries to ensure a standard layout
#
for i in range(100):
if totalentries == 0: break
if total >= totalentries: break
leg.AddEntry(None, '', '')
total += 1
# recipe for making roughly square boxes
h = leg.GetY2() - leg.GetY1()
w = leg.GetX2() - leg.GetX1()
leg.SetMargin(leg.GetNColumns() * h / float(leg.GetNRows() * w))
can.cd()
if can.GetPrimitive('pad_top'):
can.GetPrimitive('pad_top').cd()
leg.Draw()
can.Modified()
can.Update()
return
def binFile(rerror, filename, xtitle, backgrounds):
warnings.simplefilter("ignore")
file = TFile(filename)
keys = file.GetListOfKeys()
print 'input file:', filename
print 'background:', backgrounds
h_bkg = {}
h_data = {}
resultfile = filename.split('.')[0] + '_rebinned.root'
# load all the background and data histograms
for key in keys:
key = key.GetName()
info = hinfo(key)
if not info.systematic:
if info.process in backgrounds:
if info.channel in h_bkg:
print 'merging', info.channel
h_bkg[info.channel] = merge(h_bkg[info.channel],
file.Get(key).Clone())
else:
print 'adding', info.channel
h_bkg[info.channel] = file.Get(key).Clone()
elif info.process == 'data' or info.process == 'DATA':
if info.channel in h_data:
h_data[info.channel] = merge(h_data[info.channel],
file.Get(key).Clone())
else:
h_data[info.channel] = file.Get(key).Clone()
canvas = TCanvas()
canvas.SetLogy()
#keys = file.GetListOfKeys()
output = TFile(resultfile, 'RECREATE')
#print h_bkg[1]
# print all the histograms for all the channels
for key in h_bkg:
binning = array.array('d', computeBinning(h_bkg[key], rerror))
#print binning
h_bkg[key] = h_bkg[key].Rebin(
len(binning) - 1, h_bkg[key].GetName(), binning)
h_bkg[key].SetLineColor(ROOT.kGray + 1)
h_bkg[key].SetFillColor(ROOT.kGray + 1)
maxs = h_bkg[key].GetMaximum()
if len(h_data) > 0:
h_data[key] = h_data[key].Rebin(
len(binning) - 1, h_data[key].GetName(), binning)
h_data[key].SetLineColor(ROOT.kBlack)
h_data[key].SetMarkerStyle(20)
maxs = [h_data[key].GetMaximum(), h_bkg[key].GetMaximum()]
pad = canvas.cd(1)
pad.SetLeftMargin(0.15)
pad.SetBottomMargin(0.15)
min = h_bkg[key].GetBinContent(h_bkg[key].GetMinimumBin())
if len(h_data) > 0:
h_data[key].GetYaxis().SetRangeUser(0.5 * min, max(maxs) * 1.8)
h_data[key].GetYaxis().SetLabelSize(0.05)
h_data[key].GetYaxis().SetTitleSize(0.05)
h_data[key].GetYaxis().SetTitle('event yield')
h_data[key].GetXaxis().SetLabelSize(0.05)
h_data[key].GetXaxis().SetTitleSize(0.05)
h_data[key].GetXaxis().SetTitle(xtitle)
h_data[key].Draw('e')
h_bkg[key].Draw('samehist')
if len(h_data) > 0:
h_data[key].Draw('samee')
legend = TLegend(.67, .78, .89, .88)
legend.SetMargin(0.12)
legend.SetTextSize(0.03)
legend.SetFillColor(10)
legend.SetBorderSize(0)
legend.AddEntry(h_bkg[key], "Background", "f")
if len(h_data) > 0: legend.AddEntry(h_data[key], "CMS Data 2016", "lp")
legend.Draw()
labelcms = TLegend(.15, .91, 1, .96)
labelcms.SetTextSize(0.04)
labelcms.SetMargin(0.12)
labelcms.SetFillColor(10)
labelcms.SetBorderSize(0)
labelcms.SetHeader('CMS Preliminary #sqrt{s} = 13 TeV')
labelcms.Draw()
labellumi = TLegend(.73, .91, 1, .96)
labellumi.SetTextSize(0.04)
labellumi.SetMargin(0.12)
labellumi.SetFillColor(10)
labellumi.SetBorderSize(0)
labellumi.SetHeader('L = 35.8 fb^{-1}')
labellumi.Draw()
labellumi2 = TLegend(.67, .70, .89, .75)
labellumi2.SetTextSize(0.03)
labellumi2.SetMargin(0.12)
labellumi2.SetFillColor(10)
labellumi2.SetBorderSize(0)
labellumi2.SetHeader(key)
labellumi2.Draw()
canvas.SaveAs('h_' + filename.split('.')[0] + '_' + key + '.pdf')
for hkey in keys:
hkey = hkey.GetName()
info = hinfo(hkey)
if info.channel == key:
#print hkey
#print info.channel,key
#print hkey
histogram = file.Get(hkey).Clone()
# Hack to fix the data lowercase names
#if info.systematic == 'pdf':
# continue
#if (info.systematic == 'scale' or info.systematic == 'matching') and 'light' in info.process and '1btag' in info.channel:
# print "Excluding : ", info.systematic, info.process, info.channel
# continue
if 'data' in info.process:
histogram.SetName(histogram.GetName().replace(
'data', 'DATA'))
if info.systematic:
if ('ttjets' in info.process.lower()
or 'ttbar' in info.process.lower()
) and 'scale' in info.systematic:
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace(
'scaleWeight', 'scale_ttbar'))
if debug:
print "Renaming: %s to %s" % (orig,
histogram.GetName())
elif ('wjets' in info.process.lower()
or 'zjets' in info.process.lower()
) and 'scale' in info.systematic:
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace(
'scaleWeight', 'scale_vjets'))
if debug:
print "Renaming: %s to %s" % (orig,
histogram.GetName())
elif 'singlet' in info.process.lower(
) and 'scale' in info.systematic:
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace(
'scaleWeight', 'scale_singletop'))
if debug:
print "Renaming: %s to %s" % (orig,
histogram.GetName())
elif ('bpb' in info.process.lower()
or 'bpt' in info.process.lower()
) and 'scale' in info.systematic:
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace(
'scaleWeight', 'scale_bp'))
if debug:
print "Renaming: %s to %s" % (orig,
histogram.GetName())
elif 'qcd' in info.process.lower(
) and 'scale' in info.systematic:
if debug: print "ignoring QCD scale uncertainties"
continue
#following not used at the moment!
if ('wlight' in info.process or 'zlight'
in info.process) and info.systematic == 'matching':
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace(
'matching', 'matching_vjets'))
print "Renaming: %s to %s" % (orig, histogram.GetName())
if 'mcregion' in hkey:
print key
channel = info.channel.replace('Mu', '')
channel = channel.replace('Ele', '')
histogram.SetName(histogram.GetName().replace(
'mcregion', 'mcregion_' + channel))
#Rename the hists to make it easier for theta to find the mass
if 'X53' in info.process:
histogram.SetName(histogram.GetName().replace('X53', 'X'))
#norm signal, just pure shape
if ('Bprime' in info.process
or 'X53' in info.process) and info.systematic:
for h_hkey in keys:
h_hkey = h_hkey.GetName()
h_info = hinfo(h_hkey)
if not h_info.systematic and info.process == h_info.process and h_info.channel == info.channel:
h_norm = file.Get(hkey).Clone()
events_unc = 0
events_nom = 0
for i in xrange(1, histogram.GetNbinsX() + 1):
events_nom += h_norm.GetBinContent(i)
events_unc += histogram.GetBinContent(i)
#print 'Going to normalize to the same value', h_info.process,h_info.channel,info.systematic,'factor',events_nom/events_unc
#histogram.Scale(events_nom/events_unc)
#print 'rebinning',hkey
histogram = histogram.Rebin(
len(binning) - 1, histogram.GetName(), binning)
for i in xrange(1, histogram.GetNbinsX() + 1):
if histogram.GetBinContent(i) <= 0.:
histogram.SetBinContent(i, 0.0001)
output.cd()
histogram.Sumw2()
histogram.Write()
return resultfile
def plotMatches(tree, basebranch, trigger, WPs, plotname, header, ctexts):
gStyle.SetOptTitle(True)
hists = []
for i, wp in enumerate(WPs, 1):
###canvas = TCanvas('canvas','canvas',100,100,800,600)
branch = basebranch + ("" if 'all' in wp else '_' + wp)
histname = "%s_%s" % (trigger, branch)
histtitle = "all (slimmed)" if wp == 'all' else wp #"%s, %s"%(trigger,wp)
hist = TH1F(histname, histtitle, 8, -2, 6)
hist.GetXaxis().SetTitle(branch)
hist.GetYaxis().SetTitle("Fraction")
for ibin in xrange(1, hist.GetXaxis().GetNbins() + 1):
xbin = hist.GetBinLowEdge(ibin)
if xbin == -2:
hist.GetXaxis().SetBinLabel(ibin, "HLT not fired")
elif xbin == -1:
hist.GetXaxis().SetBinLabel(ibin, "No trig. obj.")
elif xbin == 0:
hist.GetXaxis().SetBinLabel(ibin, "No match")
elif xbin == 1:
hist.GetXaxis().SetBinLabel(ibin, "1 match")
else:
hist.GetXaxis().SetBinLabel(ibin, "%d matches" % xbin)
hist.GetXaxis().SetLabelSize(0.074)
hist.GetYaxis().SetLabelSize(0.046)
hist.GetXaxis().SetTitleSize(0.046)
hist.GetYaxis().SetTitleSize(0.052)
hist.GetXaxis().SetTitleOffset(2.14)
hist.GetYaxis().SetTitleOffset(0.98)
hist.GetXaxis().SetLabelOffset(0.009)
if len(branch) > 60:
hist.GetXaxis().CenterTitle(True)
hist.GetXaxis().SetTitleOffset(2.65)
hist.GetXaxis().SetTitleSize(0.038)
elif len(branch) > 40:
hist.GetXaxis().CenterTitle(True)
hist.GetXaxis().SetTitleOffset(2.16)
hist.GetXaxis().SetTitleSize(0.044)
hist.SetLineWidth(2)
hist.SetLineColor(i)
out = tree.Draw("%s >> %s" % (branch, histname),
"trigger_%s" % trigger, 'gOff')
if hist.Integral() > 0:
hist.Scale(1. / hist.Integral())
else:
print "Warning! Histogram '%s' is empty!" % hist.GetName()
###hist.Draw('HISTE')
###canvas.SaveAs(histname+".png")
###canvas.SaveAs(histname+".pdf")
###canvas.Close()
hists.append(hist)
gStyle.SetOptTitle(False)
canvas = TCanvas('canvas', 'canvas', 100, 100, 800, 600)
canvas.SetMargin(0.10, 0.09, 0.18, 0.03)
textsize = 0.040
height = 1.28 * (len(hists) + 1) * textsize
legend = TLegend(0.63, 0.70, 0.88, 0.70 - height)
legend.SetTextSize(textsize)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetTextFont(62)
legend.SetHeader(header)
legend.SetTextFont(42)
legend.SetMargin(0.2)
latex = TLatex()
latex.SetTextAlign(13)
latex.SetTextFont(42)
latex.SetNDC(True)
hists[0].SetMaximum(1.25 * max(h.GetMaximum() for h in hists))
for hist in hists:
hist.Draw('HISTSAME')
legend.AddEntry(hist, hist.GetTitle().capitalize(), 'l')
legend.Draw()
for i, text in enumerate(ctexts):
textsize = 0.031 if i > 0 else 0.044
latex.SetTextSize(textsize)
latex.DrawLatex(0.14, 0.95 - 1.7 * i * textsize, text)
canvas.SaveAs(plotname + ".png")
canvas.SaveAs(plotname + ".pdf")
canvas.Close()
for hist in hists:
gDirectory.Delete(hist.GetName())
graph_exclusion_exp_.Draw("AL")
graph_exclusion_exp_pm1sig_.Draw("Fsame")
graph_exclusion_exp_p1sig_.Draw("Lsame")
graph_exclusion_exp_m1sig_.Draw("Lsame")
if drawObs:
graph_exclusion_obs_.Draw("Lsames")
graph_exclusion_atlas_8TeV_2g.Draw("Lsames")
graph_exclusion_cms_7TeV_1g.Draw("Lsames")
#graph_exclusion_cms_8TeV_1g.Draw("Fsames")
#graph_exclusion_cms_8TeV_2g.Draw("Fsames")
####legend
leg_2d_exclusion_ = TLegend(0.21, 0.70, 0.6, 0.92)
leg_2d_exclusion_.SetMargin(0.5)
leg_2d_exclusion_.SetBorderSize(0)
leg_2d_exclusion_.SetTextSize(0.03)
leg_2d_exclusion_.SetTextFont(42)
#leg_2d_exclusion_.SetLineColor(1)
#leg_2d_exclusion_.SetLineStyle(1)
#leg_2d_exclusion_.SetLineWidth(1)
leg_2d_exclusion_.SetFillColor(0)
leg_2d_exclusion_.SetFillStyle(1001)
leg_2d_exclusion_.SetHeader(" GMSB SPS8")
leg_2d_exclusion_.AddEntry(
graph_exclusion_exp_,
"CMS expected (#pm 1 #sigma) " + label_this_withoutY, "LF")
if drawObs:
leg_2d_exclusion_.AddEntry(graph_exclusion_obs_,
def make_plot_all_rods(error_dict, rod_dict, name):
leg = TLegend(0,0,0,0)
if 'lock' in name:
leg = TLegend(0.18,0.85,0.50,0.55)
else:
leg = TLegend(0.18,0.85,0.40,0.55)
leg.SetLineColor(0)
leg.SetFillStyle(0)
leg.SetShadowColor(0)
leg.SetBorderSize(0)
leg.SetNColumns(3)
gStyle.SetLegendTextSize(0.045)
v_hists = []
#for e,c in zip(error_bits, error_colors):
for e in error_bits:
h = TH1F('h'+e,'h'+e, len(rod_dict), 0, len(rod_dict))
h.SetFillStyle(1001)
h.SetLineWidth(0)
v_hists.append(h)
v_hists[-1].SetDirectory(0)
if bin(int('0x'+e, 16))[2:].zfill(4) == '0111':
leg.AddEntry(v_hists[-1],'GOL 3',"f");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1011':
leg.AddEntry(v_hists[-1],'GOL 2',"f");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1101':
leg.AddEntry(v_hists[-1],'GOL 1',"f");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1110':
leg.AddEntry(v_hists[-1],'GOL 0',"f");
else:
leg.AddEntry(v_hists[-1],bin(int('0x'+e, 16))[2:].zfill(4),"f");
h = leg.GetY2()-leg.GetY1();
w = leg.GetX2()-leg.GetX1()*.6;
leg.SetMargin(leg.GetNColumns()*h/(leg.GetNRows()*w))
for key,val in error_dict.items():
idx_rod = 0
for i, key2 in enumerate(rod_dict):
if key2 == key[:8]:
idx_rod = i
v_hists[int(key[11:12], 16)].Fill(idx_rod, val)
stack = THStack("stack","stack")
for hist in v_hists:
stack.Add(hist)
if 'buff' in name:
c1 = TCanvas( 'c1', 'c1', 2000, 500)
else:
c1 = TCanvas( 'c1', 'c1', 1000, 500)
h1 = TH1F('h_1','h_1', len(rod_dict), 0, len(rod_dict))
for i, key in enumerate(rod_dict):
h1.GetXaxis().SetBinLabel(i+1,key)
h1.SetBinContent(i+1,rod_dict[key])
h1.GetXaxis().LabelsOption("v")
h1.GetXaxis().SetTitle("ROD")
h1.GetXaxis().SetTitleOffset(2.2)
h1.GetYaxis().SetTitle("# of rocketio errors")
h1.SetLineColor(kRed)
h1.SetLineWidth(1)
leg.AddEntry(h1,'total',"l");
c1.SetBottomMargin(0.23)
h1.GetXaxis().SetTitle("ROD")
h1.Draw("HIST")
stack.Draw("PFC PLC SAME HIST")
h1.Draw("SAMEHIST")
AtlasStyle.ATLAS_LABEL(0.19,.88, 1, "Internal")
leg.Draw()
c1.Update()
c1.Print("plots/"+name +".pdf")
c1.Clear()
def main():
ratesA_ = load_json("ratesAt1p5after.json")
ratesB_ = load_json("ratesAt1p5before.json")
wp2 = phicomparison(ratesB_,ratesA_,"W+2","RB4","compWP2RB4","W+2/RB4")
wp1 = phicomparison(ratesB_,ratesA_,"W+1","RB4","compWP1RB4","W+1/RB4")
wp0 = phicomparison(ratesB_,ratesA_,"W+0","RB4","compWP0RB4","W+0/RB4")
wm1 = phicomparison(ratesB_,ratesA_,"W-1","RB4","compWM1RB4","W-1/RB4")
wm2 = phicomparison(ratesB_,ratesA_,"W-2","RB4","compWM2RB4","W-2/RB4")
rem4 = diskphicomparison(ratesB_,ratesA_,"RE-4","R3","compREM4R3","RE-4/R3")
rem3 = diskphicomparison(ratesB_,ratesA_,"RE-3","R3","compREM3R3","RE-3/R3")
rem2 = diskphicomparison(ratesB_,ratesA_,"RE-2","R3","compREM2R3","RE-2/R3")
rem1 = diskphicomparison(ratesB_,ratesA_,"RE-1","R3","compREM1R3","RE-1/R3")
rep1 = diskphicomparison(ratesB_,ratesA_,"RE+1","R3","compREP1R3","RE+1/R3")
rep2 = diskphicomparison(ratesB_,ratesA_,"RE+2","R3","compREP2R3","RE+2/R3")
rep3 = diskphicomparison(ratesB_,ratesA_,"RE+3","R3","compREP3R3","RE+3/R3")
rep4 = diskphicomparison(ratesB_,ratesA_,"RE+4","R3","compREP4R3","RE+4/R3")
wp2["before"].SetLineColor(kRed+2); wp2["after"].SetLineColor(kRed+2)
wp1["before"].SetLineColor(kBlue+2); wp1["after"].SetLineColor(kBlue+2)
wp0["before"].SetLineColor(kBlack); wp0["after"].SetLineColor(kBlack)
wm1["before"].SetLineColor(kGreen+2); wm1["after"].SetLineColor(kGreen+2)
wm1["before"].SetLineStyle(9); wm1["after"].SetLineStyle(9)
wm2["before"].SetLineColor(kMagenta+2); wm2["after"].SetLineColor(kMagenta+2)
wm2["before"].SetLineStyle(9); wm2["after"].SetLineStyle(9)
acan = TCanvas("can","",1200,700)
acan.Divide(2,1)
#wp2["after"].Divide(wp2["before"])
#wp1["after"].Divide(wp1["before"])
#wp0["after"].Divide(wp0["before"])
#wm1["after"].Divide(wm1["before"])
#wm2["after"].Divide(wm2["before"])
#wp2["after"].SetMaximum(2.5)
#wp1["after"].SetMaximum(2.5)
#wp0["after"].SetMaximum(2.5)
#wm1["after"].SetMaximum(2.5)
#wm2["after"].SetMaximum(2.5)
#wp2["after"].SetBarWidth(0.18); wp2["after"].SetBarOffset(0.0); wp2["after"].SetFillColor(kRed+2);
#h1 = wp2["after"].DrawCopy("bar2");
#wp1["after"].SetBarWidth(0.18); wp1["after"].SetBarOffset(0.20); wp1["after"].SetFillColor(kBlue+2);
#h2 = wp1["after"].DrawCopy("bar2 same");
#wp0["after"].SetBarWidth(0.18); wp0["after"].SetBarOffset(0.40); wp0["after"].SetFillColor(kBlack);
#h3 = wp0["after"].DrawCopy("bar2 same");
#wm1["after"].SetBarWidth(0.18); wm1["after"].SetBarOffset(0.60); wm1["after"].SetFillColor(kGreen+2);
#h4 = wm1["after"].DrawCopy("bar2 same");
#wp2["after"].SetBarWidth(0.18); wp2["after"].SetBarOffset(0.80); wp2["after"].SetFillColor(kMagenta+2);
#h5 = wp2["after"].DrawCopy("bar2 same");
acan.cd(1)
wp2["after"].SetTitle("RB4")
wp2["after"].Draw("same hist")
wp1["after"].Draw("same hist")
wp0["after"].Draw("same hist")
wm1["after"].Draw("same hist")
wm2["after"].Draw("same hist")
acan.cd(2)
wp2["before"].SetTitle("RB4")
wp2["before"].Draw("same hist")
wp1["before"].Draw("same hist")
wp0["before"].Draw("same hist")
wm1["before"].Draw("same hist")
wm2["before"].Draw("same hist")
leg = TLegend(0.345,0.68,0.845,0.88)
leg.SetFillStyle( 0 )
leg.SetBorderSize(0)
leg.SetMargin( 0.1 )
leg.AddEntry(wp2["after"], "W+2", "l")
leg.AddEntry(wp1["after"], "W+1", "l")
leg.AddEntry(wp0["after"], "W+0", "l")
leg.AddEntry(wm1["after"], "W-1", "l")
leg.AddEntry(wm2["after"], "W-2", "l")
leg.Draw("same")
acan.SaveAs("allwheels.png")
acan.Clear()
acan.Divide(2,1)
acan.cd(1)
rem4["after"].SetTitle("R3")
rem4["after"].Draw("same hist")
rem3["after"].Draw("same hist")
rem2["after"].Draw("same hist")
rem1["after"].Draw("same hist")
acan.cd(2)
rem4["before"].SetTitle("R3")
rem4["before"].Draw("same hist")
rem3["before"].Draw("same hist")
rem2["before"].Draw("same hist")
rem1["before"].Draw("same hist")
leg = TLegend(0.345,0.68,0.845,0.88)
leg.SetFillStyle( 0 )
leg.SetBorderSize(0)
leg.SetMargin( 0.1 )
leg.AddEntry(rem4["after"], "RE-4", "l")
leg.AddEntry(rem3["after"], "RE-3", "l")
leg.AddEntry(rem2["after"], "RE-2", "l")
leg.AddEntry(rem1["after"], "RE-1", "l")
leg.Draw("same")
acan.SaveAs("alldisks.png")
acan.Clear()
return
def printmultigraph(grs, sortk, plotoptions, outn, title, year, doext,
ploterror, ymax):
import CMS_lumi, tdrstyle
import array
#set the tdr style
tdrstyle.setTDRStyle()
#change the CMS_lumi variables (see CMS_lumi.py)
CMS_lumi.writeExtraText = 1
CMS_lumi.extraText = "Preliminary"
if year == 2018:
CMS_lumi.extraText2 = "2018 pp data"
if year == 2017:
CMS_lumi.extraText2 = "2017 pp data"
if year == 2016:
CMS_lumi.extraText2 = "2016 pp data"
CMS_lumi.lumi_sqrtS = "13 TeV" # used with iPeriod = 0, e.g. for simulation-only plots (default is an empty string)
CMS_lumi.writeTitle = 1
CMS_lumi.textTitle = title
iPos = 11
if (iPos == 0): CMS_lumi.relPosX = 0.12
H_ref = 600
W_ref = 800
W = W_ref
H = H_ref
iPeriod = 0
# references for T, B, L, R
T = 0.08 * H_ref
B = 0.12 * H_ref
L = 0.12 * W_ref
R = 0.04 * W_ref
c = TCanvas("c", "c", 50, 50, W, H)
#gStyle.SetOptStat(0)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
c.SetLeftMargin(L / W)
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.SetTickx(0)
c.SetTicky(0)
#canvassettings(c)
mg = TMultiGraph()
#mg = grs['main']
mg.SetTitle(title)
#gStyle.SetTitleAlign(33)
#gStyle.SetTitleX(0.99)
leg = TLegend(
0.345, 0.68, 0.645, 0.88
) #TLegend(1. - c.GetRightMargin() - 0.8, 1. - c.GetTopMargin() - 0.40,1. - c.GetRightMargin()- 0.60, 1. - c.GetTopMargin() -0.02)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetMargin(0.1)
#ymax = 0;
ratesFromFit = {}
evVal = 15000
if doext:
evVal = 50000
#f=TFile.Open(outn+".root","RECREATE")
# for name,value in plotoptions.iteritems():
for name in sortk:
if name != 'main': continue
value = plotoptions[name]
#print grs
gr = grs[name]
#print gr
gr.SetName(title)
#extrate = fitGraph(gr,evVal)
#ratesFromFit[name] = extrate
if doext:
#print name, extrate[0], extrate[1]
NN = gr.GetN()
gr.Set(NN + 1)
gr.SetPoint(NN + 1, 50000.0, extrate["rate"][0])
yErr = extrate["rate"][1]
if not ploterror:
yErr = 0.0
gr.SetPointError(NN + 1, 0.0, yErr)
gr.SetMarkerColor(value['color'])
gr.SetMarkerStyle(value['markst'])
gr.SetLineColor(value['color'])
gr.SetMarkerSize(1.15) #1.05
gr.SetMinimum(0.1)
#gr.Write()
mg.Add(gr)
text = title #name #+plotoptions[name]['leg']
leg.AddEntry(gr, text, "p")
continue
mg.SetName(outn)
mg.SetMinimum(0.1)
mg.SetMaximum(ymax) #1.6*ymax
mg.Draw("AP")
mg.GetXaxis().SetRangeUser(2000, 20000)
c.Update()
graphAxis(mg)
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
c.cd()
c.Update()
frame = c.GetFrame()
frame.Draw()
leg.Draw()
c.SaveAs(outn + ".png")
#c.SaveAs(outn+".C")
del c
return ratesFromFit
def binFile(rerror, filename, xtitle, backgrounds):
file = TFile(filename)
keys = file.GetListOfKeys()
h_bkg = {}
h_data = {}
# load all the background and data histograms
for key in keys:
key = key.GetName()
print key
info = hinfo(key)
if not info.systematic:
if info.process in backgrounds:
if info.channel in h_bkg:
h_bkg[info.channel] = merge(h_bkg[info.channel], file.Get(key).Clone())
else:
h_bkg[info.channel] = file.Get(key).Clone()
elif info.process == 'data' or info.process == 'DATA':
if info.channel in h_data:
h_data[info.channel] = merge(h_data[info.channel], file.Get(key).Clone())
else:
h_data[info.channel] = file.Get(key).Clone()
canvas = TCanvas()
canvas.SetLogy()
keys = file.GetListOfKeys()
output = TFile(filename.split('.')[0]+'_rebinned.root', 'RECREATE')
# print all the histograms for all the channels
for key in h_bkg:
binning = array.array('d', computeBinning(h_bkg[key], rerror))
h_bkg[key] = h_bkg[key].Rebin(len(binning)-1, h_bkg[key].GetName(), binning)
h_data[key] = h_data[key].Rebin(len(binning)-1, h_data[key].GetName(), binning)
h_bkg[key].SetLineColor(ROOT.kGray+1)
h_bkg[key].SetFillColor(ROOT.kGray+1)
h_data[key].SetLineColor(ROOT.kBlack)
h_data[key].SetMarkerStyle(20)
pad = canvas.cd(1)
pad.SetLeftMargin(0.15)
pad.SetBottomMargin(0.15)
maxs = [h_data[key].GetMaximum(), h_bkg[key].GetMaximum()]
min = h_bkg[key].GetBinContent(h_bkg[key].GetMinimumBin())
h_data[key].GetYaxis().SetRangeUser(0.5*min,max(maxs)*1.8)
h_data[key].GetYaxis().SetLabelSize(0.05)
h_data[key].GetYaxis().SetTitleSize(0.05)
h_data[key].GetYaxis().SetTitle('event yield')
h_data[key].GetXaxis().SetLabelSize(0.05)
h_data[key].GetXaxis().SetTitleSize(0.05)
h_data[key].GetXaxis().SetTitle(xtitle)
h_data[key].Draw('e')
h_bkg[key].Draw('samehist')
h_data[key].Draw('samee')
legend = TLegend(.67, .78, .89, .88)
legend.SetMargin(0.12);
legend.SetTextSize(0.03);
legend.SetFillColor(10);
legend.SetBorderSize(0);
legend.AddEntry(h_bkg[key], "Background", "f")
legend.AddEntry(h_data[key], "CMS Data 2015", "lp")
legend.Draw()
labelcms = TLegend(.15, .91, 1, .96)
labelcms.SetTextSize(0.04)
labelcms.SetMargin(0.12);
labelcms.SetFillColor(10);
labelcms.SetBorderSize(0);
labelcms.SetHeader('CMS Preliminary #sqrt{s} = 13 TeV')
labelcms.Draw()
labellumi = TLegend(.73, .91, 1, .96)
labellumi.SetTextSize(0.04)
labellumi.SetMargin(0.12);
labellumi.SetFillColor(10);
labellumi.SetBorderSize(0);
labellumi.SetHeader('L = 2.4 fb^{-1}')
labellumi.Draw()
labellumi2 = TLegend(.67, .70, .89, .75)
labellumi2.SetTextSize(0.03)
labellumi2.SetMargin(0.12);
labellumi2.SetFillColor(10);
labellumi2.SetBorderSize(0);
labellumi2.SetHeader(key)
labellumi2.Draw()
canvas.SaveAs('h_'+filename.split('.')[0]+'_'+key+'.pdf')
for hkey in keys:
hkey = hkey.GetName()
info = hinfo(hkey)
if info.channel == key:
histogram = file.Get(hkey).Clone()
# Hack to fix the data lowercase names
#if info.systematic == 'pdf':
# continue
if (info.systematic == 'scale' or info.systematic == 'matching') and 'light' in info.process and '1btag' in info.channel:
print "Excluding : ", info.systematic, info.process, info.channel
continue
if 'data' in info.process:
histogram.SetName(histogram.GetName().replace('data','DATA'))
if 'ttbar' in info.process and info.systematic == 'scale':
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace('scale','scale_ttbar'))
print "Renaming: %s to %s" % (orig, histogram.GetName())
if ('wlight' in info.process or 'zlight' in info.process) and info.systematic == 'scale':
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace('scale','scale_vjets'))
print "Renaming: %s to %s" % (orig, histogram.GetName())
if ('wlight' in info.process or 'zlight' in info.process) and info.systematic == 'matching':
orig = histogram.GetName()
histogram.SetName(histogram.GetName().replace('matching','matching_vjets'))
print "Renaming: %s to %s" % (orig, histogram.GetName())
if info.process.startswith('zp') or info.process.startswith('rsg'):
print "Scaling signal sample %s by x0.1" % histogram.GetName()
histogram.Scale(0.1)
histogram = histogram.Rebin(len(binning)-1, histogram.GetName(), binning)
output.cd()
histogram.Write()
def drawlegend(self, position=None, **kwargs):
"""Create and draw legend.
Legend position can be controlled in several ways
drawlegend(position)
drawlegend(position=position)
where position is a string which can contain the horizontal position, e.g.
'left', 'center', 'right', 'L', 'C', 'R', 'x=0.3', ...
where 'x' is the position (between 0 an 1) of the left side in the frame.
The position string can also contain the vertical position as e.g.
'top', 'middle', 'bottom', 'T', 'M', 'B', 'y=0.3', ...
where 'y' is the position (between 0 an 1) of the top side in the frame.
Instead of the strings, the exact legend coordinates can be controlled with
the keywords x1, x2, y1 and y2, or, x1, y1, width and height:
drawlegend(x1=0.2,width=0.4)
drawlegend(x1=0.2,width=0.4,y1=0.9,height=0.4)
drawlegend(x1=0.2,x2=0.6,y1=0.9,y2=0.4)
These floats are normalized to the axis frame, ignoring the canvas margins:
x=0 is the left, x=1 is the right, y=0 is the bottom and y=1 is the top side.
Values less than 0, or larger than 1, will put the legend outside the frame.
"""
#if not ratio:
# tsize *= 0.80
# signaltsize *= 0.80
verbosity = LOG.getverbosity(self, kwargs)
hists = self.hists
errstyle = 'lep' if gStyle.GetErrorX() else 'ep'
entries = kwargs.get('entries', [])
bands = kwargs.get('band', [self.errband]) # error bands
bands = ensurelist(bands, nonzero=True)
bandentries = kwargs.get('bandentries', [])
title = kwargs.get('header', None)
title = kwargs.get('title', title) # legend header/title
latex = kwargs.get('latex',
True) # automatically format strings as LaTeX
style = kwargs.get('style', None)
style0 = kwargs.get('style0', None) # style of first histogram
errstyle = kwargs.get('errstyle', errstyle) # style for an error point
styles = kwargs.get('styles', [])
position = kwargs.get('pos', position) # legend position
position = kwargs.get('position', position) or self.position
option = kwargs.get('option', '')
border = kwargs.get('border', False)
transparent = kwargs.get('transparent', True)
x1_user = kwargs.get('x1', None) # legend left side
x2_user = kwargs.get('x2', None) # legend right side
y1_user = kwargs.get('y1', None) # legend top side
y2_user = kwargs.get('y2', None) # legend bottom side
width = kwargs.get('width', -1) # legend width
height = kwargs.get('height', -1) # legend height
tsize = kwargs.get('tsize', _lsize) # text size
twidth = kwargs.get('twidth',
None) or 1 # scalefactor for legend width
theight = kwargs.get('theight',
None) or 1 # scalefactor for legend height
texts = kwargs.get('text', []) # extra text below legend
ncols = kwargs.get('ncols',
self.ncols) or 1 # number of legend columns
colsep = kwargs.get('colsep',
0.06) # seperation between legend columns
bold = kwargs.get('bold', True) # bold legend header
panel = kwargs.get('panel', 1) # panel (top=1, bottom=2)
texts = ensurelist(texts, nonzero=True)
entries = ensurelist(entries, nonzero=False)
bandentries = ensurelist(bandentries, nonzero=True)
headerfont = 62 if bold else 42
# CHECK
LOG.insist(self.canvas, "Canvas does not exist!")
self.canvas.cd(panel)
scale = 485. / min(gPad.GetWh() * gPad.GetHNDC(),
gPad.GetWw() * gPad.GetWNDC())
tsize *= scale # text size
# ENTRIES
#if len(bandentries)==len(bands) and len(entries)>len(hists):
# for band, bandtitle in zip(band,bandentries):
# entries.insert(hists.index(band),bandtitle)
while len(entries) < len(hists):
entries.append(hists[len(entries)].GetTitle())
while len(bandentries) < len(bands):
bandentries.append(bands[len(bandentries)].GetTitle())
hists = hists + bands
entries = entries + bandentries
if latex:
title = maketitle(title)
entries = [maketitle(e) for e in entries]
texts = [maketitle(t) for t in texts]
maxlen = estimatelen([title] + entries + texts)
# STYLES
if style0:
styles[0] = style0
while len(styles) < len(hists):
hist = hists[len(styles)]
if hist in bands:
styles.append('f')
elif style != None:
styles.append(style)
elif hasattr(hist, 'GetFillStyle') and hist.GetFillStyle() > 0:
styles.append('f')
elif 'E0' in hist.GetOption() or 'E1' in hist.GetOption():
styles.append(errstyle)
else:
styles.append('lp')
# NUMBER of LINES
nlines = sum([1 + e.count('\n') for e in entries])
#else: nlines += 0.80
if texts: nlines += sum([1 + t.count('\n') for t in texts])
if ncols > 1: nlines /= float(ncols)
if title: nlines += 1 + title.count('\n')
# DIMENSIONS
if width < 0:
width = twidth * max(0.22, min(0.60, 0.036 + 0.016 * maxlen))
if height < 0: height = theight * 1.34 * tsize * nlines
if ncols > 1: width *= ncols / (1 - colsep)
x2 = 0.90
x1 = x2 - width
y1 = 0.92
y2 = y1 - height
# POSITION
if position == None:
position = ""
position = position.replace('left', 'L').replace(
'center', 'C').replace('right', 'R').replace( #.lower()
'top', 'T').replace('middle', 'M').replace('bottom', 'B')
if not any(c in position for c in 'TMBy'): # set default vertical
position += 'T'
if not any(c in position for c in 'LCRx'): # set default horizontal
position += 'RR' if ncols > 1 else 'R' # if title else 'L'
if 'C' in position:
if 'R' in position: center = 0.57
elif 'L' in position: center = 0.43
else: center = 0.50
x1 = center - width / 2
x2 = center + width / 2
elif 'LL' in position:
x1 = 0.03
x2 = x1 + width
elif 'L' in position:
x1 = 0.08
x2 = x1 + width
elif 'RR' in position:
x2 = 0.97
x1 = x2 - width
elif 'R' in position:
x2 = 0.92
x1 = x2 - width
elif 'x=' in position:
x1 = float(re.findall(r"x=(\d\.\d+)", position)[0])
x2 = x1 + width
if 'M' in position:
if 'T' in position: middle = 0.57
elif 'B' in position: middle = 0.43
else: middle = 0.50
y1 = middle - height / 2
y2 = middle + height / 2
elif 'TT' in position:
y2 = 0.97
y1 = y2 - height
elif 'T' in position:
y2 = 0.92
y1 = y2 - height
elif 'BB' in position:
y1 = 0.03
y2 = y1 + height
elif 'B' in position:
y1 = 0.08
y2 = y1 + height
elif 'y=' in position:
y2 = float(re.findall(r"y=(\d\.\d+)", position)[0])
y1 = y2 - height
if x1_user != None:
x1 = x1_user
x2 = x1 + width if x2_user == None else x2_user
if y1_user != None:
y1 = y1_user
y2 = y1 - height if y2_user == None else y2_user
L, R = gPad.GetLeftMargin(), gPad.GetRightMargin()
T, B = gPad.GetTopMargin(), gPad.GetBottomMargin()
X1, X2 = L + (1 - L - R) * x1, L + (
1 - L - R) * x2 # convert frame to canvas coordinates
Y1, Y2 = B + (1 - T - B) * y1, B + (
1 - T - B) * y2 # convert frame to canvas coordinates
legend = TLegend(X1, Y1, X2, Y2)
LOG.verb(
"Plot.drawlegend: position=%r, height=%.3f, width=%.3f, (x1,y1,x2,y2)=(%.2f,%.2f,%.2f,%.2f), (X1,Y1,X2,Y2)=(%.2f,%.2f,%.2f,%.2f)"
% (position, height, width, x1, y1, x2, y2, X1, Y1, X2, Y2),
verbosity, 1)
# MARGIN
if ncols >= 2:
margin = 0.090 / width
else:
margin = 0.044 / width
legend.SetMargin(margin)
# STYLE
if transparent: legend.SetFillStyle(0) # 0 = transparent
else: legend.SetFillColor(0)
legend.SetBorderSize(border)
legend.SetTextSize(tsize)
legend.SetTextFont(headerfont) # bold for title
if ncols > 1:
legend.SetNColumns(ncols)
legend.SetColumnSeparation(colsep)
# HEADER
if title:
legend.SetHeader(title)
legend.SetTextFont(42) # no bold for entries
# ENTRIES
if hists:
for hist1, entry1, style1 in columnize(zip(hists, entries, styles),
ncols):
for entry in entry1.split('\n'):
legend.AddEntry(hist1, entry, style1)
hist1, style1 = 0, ''
for line in texts:
legend.AddEntry(0, line, '')
if verbosity >= 2:
print ">>> Plot.drawlegend: title=%r, texts=%s, latex=%s" % (
title, texts, latex)
print ">>> Plot.drawlegend: hists=%s" % (hists)
print ">>> Plot.drawlegend: entries=%s" % (entries)
print ">>> Plot.drawlegend: styles=%s" % (styles)
print ">>> Plot.drawlegend: nlines=%s, len(hists)=%s, len(texts)=%s, ncols=%s, margin=%s" % (
nlines, len(hists), len(texts), ncols, margin)
legend.Draw(option)
self.legends.append(legend)
return legend
def cutflow(Region='SignalRegion',
removeEvents=False,
logY=True,
normalise=True,
singlePlots=False,
drawOptions='HIST',
weightedORraw='weighted'):
# removeEvents=True
PreSelectionName = 'PreSelection'
# Region='HIGHSidebandRegion'
PlotBGStack = False
StackBG = False
# singlePlots=False
# normalise=True
# logY=True
# drawOptions='HIST TEXT90'
channel = 'ZZ'
channelTex = {
'WPWP': 'W^{+}W^{+}',
'WPWM': 'W^{+}W^{-}',
'WMWM': 'W^{-}W^{-}',
'WPZ': 'W^{+}Z',
'WMZ': 'W^{-}Z',
'ZZ': 'ZZ'
}
plotstyle = [(1, 1), (1, 2), (2, 1), (2, 2), (4, 1), (4, 2)]
PreSelectionCuts = [
('nocuts', 'All'),
('common', 'CommonModules'),
# ('corrections','JetCorrections'),
# ('cleaner','JetCleaner'),
('AK4pfidfilter', 'AK4 PFID-Filter'),
('AK8pfidfilter', 'AK8 PFID-Filter'),
('AK8N2sel', 'N_{AK8} #geq 2'),
('invMAk8sel', 'M_{jj-AK8} > 1050 GeV'),
('detaAk8sel', '|#Delta#eta_{jj-AK8}|<1.3')
]
SelectionCuts = [ #('preselection','PreSelection-check'),
('softdropAK8sel', '65 GeV <M_{SD}< 105 GeV'),
('tau21sel', '0 #leq #tau_{2}/#tau_{1}<0.35'),
('deltaR48', '#Delta R(AK4,leading AK8) > 1.3'),
# ('VVRegion','VVRegion'),
('AK4N2sel', 'N_{AK4} #geq 2'),
('OpSignsel', '#eta_{1-AK4} #eta_{2-AK4} < 0'),
('detaAk4sel', '|#Delta#eta_{jj-AK4}| > 3.0'),
('invMAk4sel_1p0', 'M_{jj-AK4} > 1.0 TeV')
]
Cuts = PreSelectionCuts + SelectionCuts
# Cuts=SelectionCuts
QCDColor = rt.kAzure + 7
WJetsColor = rt.kRed - 4
ZJetsColor = rt.kOrange - 2
path = '/nfs/dust/cms/user/albrechs/UHH2_Output/'
datasets = [ #(filename, Name for Legend, Linestyle, Color)
('MC.MC_aQGC_%sjj_hadronic.root' % channel, channelTex[channel], 1, 28
) #,
# ('MC.MC_QCD.root','QCD',1,QCDColor),
# ('MC.MC_WJetsToQQ_HT600ToInf.root','W+JetsToQQ',1,WJetsColor),
# ('MC.MC_ZJetsToQQ_HT600ToInf.root','Z+JetsToQQ',1,ZJetsColor),
# ('Data.DATA.root','Data',1,1)
]
gROOT.ProcessLine("gErrorIgnoreLevel = 2001;")
PreSelectionFiles = []
SelectionFiles = []
if removeEvents:
PreSelectionName = PreSelectionName + 'RmEvent'
Region = Region + 'RmEvent'
for dataset in datasets:
PreSelectionFiles.append(
TFile(path + PreSelectionName +
"/uhh2.AnalysisModuleRunner.%s" % dataset[0]))
# SelectionFiles.append(TFile(path+Region+'/backup/'+"/uhh2.AnalysisModuleRunner.%s"%dataset[0]))
SelectionFiles.append(
TFile(path + Region +
"/uhh2.AnalysisModuleRunner.%s" % dataset[0]))
gROOT.ProcessLine("gErrorIgnoreLevel = 0;")
yTitle = 'NEvents_%s' % weightedORraw
if (normalise):
yTitle = yTitle + '/N_%s' % Cuts[0][1]
canv = TCanvas('cutflow_canvas', 'cutflow_canvas', 1000, 500)
if (not singlePlots):
legend = TLegend(0.7, 0.7, 0.9, 0.95)
legend.SetFillStyle(0)
legend.SetTextSize(0.02)
legend.SetMargin(0.4)
NCuts = len(Cuts)
# NMETFilter=0
# if 'common' in Cuts[:][0]:
# NMETFilter=PreSelectionFiles[0].Get('cf_metfilters').GetNbinsX()
# for i in range(1,PreSelectionFiles[0].Get('cf_metfilters').GetNbinsX()):
# Cuts.insert(Cuts.index(('common','CommonModules')),(PreSelectionFiles[0].Get('cf_metfilters').GetXaxis().GetBinLabel(i),PreSelectionFiles[0].Get('cf_metfilters').GetXaxis().GetBinLabel(i)))
# NCuts=NCuts+NMETFilter
print('Plotting Cutflow of', NCuts, 'Cuts.')
# for dataset in datasets:
BGStack = THStack('MCBackground', 'MCBackground')
TotalMinimum = 10**10
NBG = 0
for l in range(len(datasets)):
print('checking', datasets[l][1])
if normalise:
if ((len(Cuts) == len(PreSelectionCuts)) or
(len(Cuts) == (len(PreSelectionCuts) + len(SelectionCuts)))):
Norm = PreSelectionFiles[l].Get(Cuts[0][0] + '/NEvents_%s' %
weightedORraw).GetBinContent(1)
else:
Norm = SelectionFiles[l].Get(Cuts[0][0] + '/NEvents_%s' %
weightedORraw).GetBinContent(1)
else:
Norm = 1
if (len(Cuts) > len(PreSelectionCuts)):
CurrentMinimum = SelectionFiles[l].Get(
SelectionCuts[-1][0] +
'/NEvents_%s' % weightedORraw).GetBinContent(1) / Norm
else:
CurrentMinimum = PreSelectionFiles[l].Get(
PreSelectionCuts[-1][0] +
'/NEvents_%s' % weightedORraw).GetBinContent(1) / Norm
print(CurrentMinimum, TotalMinimum)
if (CurrentMinimum < TotalMinimum):
print('setting ', datasets[l][1], 'as new minimum')
TotalMinimum = CurrentMinimum
if (datasets[l][1] == 'QCD' or datasets[l][1] == 'W+JetsToQQ'
or datasets[l][1] == 'Z+JetsToQQ'):
# NBG= NBG + PreSelectionFiles[l].Get(Cuts[0][0]+'/NEvents_%s'%weightedORraw).GetBinContent(1)
NBG = NBG + Norm
cutflows = []
for i in range(len(datasets)):
if (singlePlots):
legend = TLegend(0.75, 0.6, 1, 0.9)
legend.SetFillStyle(0)
legend.SetTextSize(0.02)
legend.SetMargin(0.4)
print('Drawing', datasets[i][1])
currentCutflow = TH1F(datasets[i][1], datasets[i][1], NCuts, 0, NCuts)
cutflows.append(currentCutflow)
#filling the current cutflow (with NEvents_weighted or NEvents_raw)
if (normalise):
if (StackBG and
(datasets[i][1] == 'QCD' or datasets[i][1] == 'W+JetsToQQ'
or datasets[i][1] == 'Z+JetsToQQ')):
NAll = NBG
else:
if ((len(Cuts) == len(PreSelectionCuts))
or (len(Cuts)
== (len(PreSelectionCuts) + len(SelectionCuts)))):
NAll = PreSelectionFiles[i].Get(
PreSelectionCuts[0][0] +
'/NEvents_%s' % weightedORraw).GetBinContent(1)
else:
NAll = SelectionFiles[i].Get(
SelectionCuts[0][0] +
'/NEvents_%s' % weightedORraw).GetBinContent(1)
else:
NAll = 1
for j in range(NCuts):
cut = Cuts[j]
if ((len(Cuts) == len(PreSelectionCuts)) or
(len(Cuts) == (len(PreSelectionCuts) + len(SelectionCuts)))
and j < len(PreSelectionCuts)):
NEvents = PreSelectionFiles[i].Get(
cut[0] + '/NEvents_%s' % weightedORraw).GetBinContent(1)
else:
NEvents = SelectionFiles[i].Get(cut[0] + '/NEvents_%s' %
weightedORraw).GetBinContent(1)
# NEvents=NAll
currentCutflow.GetXaxis().SetBinLabel(j + 1, cut[1])
currentCutflow.Fill(j + 0.5, NEvents / NAll)
#cosmectics for and draw current cutflow
currentCutflow.SetLineColor(datasets[i][3])
currentCutflow.SetMarkerSize(1.4)
currentCutflow.GetYaxis().SetTitle(yTitle)
HistMax = currentCutflow.GetMaximum()
if (logY):
if (singlePlots):
MAX = float(10**(magnitude(HistMax) + 3))
MIN = float(10**(magnitude(currentCutflow.GetMinimum()) - 1))
else:
MAX = float(10**(magnitude(HistMax) + 2))
MIN = float(10**(magnitude(TotalMinimum) - 1))
MIN += float(10**(magnitude(MIN)))
else:
MAX = 1.1 * HistMax
MIN = 0.
currentCutflow.GetYaxis().SetRangeUser(MIN, MAX)
print('RangeUser=(', MIN, ',', MAX, ')')
print('drawOptions:', drawOptions)
if (datasets[i][1] == 'Data'):
# legend.AddEntry(currentCutflow,datasets[i][1],'lep')
# currentCutflow.SetMarkerStyle(8)
# currentCutflow.Draw(drawOptions+'HP')
legend.AddEntry(currentCutflow, datasets[i][1], 'l')
currentCutflow.Draw(drawOptions)
if (not singlePlots and ('SAME' not in drawOptions)):
drawOptions = drawOptions + 'SAME'
elif (StackBG
and (datasets[i][1] == 'QCD' or datasets[i][1] == 'W+JetsToQQ'
or datasets[i][1] == 'Z+JetsToQQ')):
legend.AddEntry(currentCutflow, datasets[i][1], 'f')
currentCutflow.SetFillColor(datasets[i][3])
BGStack.Add(currentCutflow, drawOptions)
# currentCutflow.Draw(drawOptions)
PlotBGStack = True
else:
legend.AddEntry(currentCutflow, datasets[i][1], 'l')
currentCutflow.Draw(drawOptions)
if (not singlePlots and ('SAME' not in drawOptions)):
drawOptions = drawOptions + 'SAME'
if (singlePlots):
legend.Draw()
if (logY):
canv.SetLogy()
# canv.SetGrid()
canv.SetTicks()
gPad.RedrawAxis()
canv.Print('cutflows/' + Region + '_cutflow_%s_%s.eps' %
(datasets[i][1], weightedORraw))
if (not singlePlots):
if (PlotBGStack):
BGStack.Draw(drawOptions)
legend.Draw()
if (logY):
canv.SetLogy()
# canv.SetGrid()
canv.SetTicks()
gPad.RedrawAxis()
canv.Print('cutflows/' + Region + '_cutflow_%s.eps' % weightedORraw)
def plotter(plotdir,
plot,
xTitle,
logY,
channels=['VV'],
includeData=False,
scaleSignal=0,
UserRange=[None, None, None, None],
initPath=''):
# channelTex={'WPWP':'W^{+}W^{+}', 'WPWM':'W^{+}W^{-}','WMWM':'W^{-}W^{-}','WPZ':'W^{+}Z','WMZ':'W^{-}Z','ZZ':'ZZ'}
channelTex = {'ZZ': 'ZZ'}
# plotstyle=[(1,1),(1,2),(2,1),(2,2),(4,1),(4,2)]
plotstyle = [(1, 1)]
# 0 1 2 3 4 5 6
# Backgrounds=['QCD', 'WJetsToQQ_HT600ToInf', 'ZJetsToQQ_HT600ToInf', 'TT', 'WW', 'WZ', 'ZZ']
# BGColors= [rt.kAzure+7, rt.kRed-4, rt.kOrange-2, rt.kGreen+2, rt.kOrange+7, rt.kBlue+1, rt.kMagenta+2]
# BGTeX= ['QCD', 'W+JetsToQQ', 'Z+JetsToQQ', 'TTbar'], 'WW', 'WZ', 'ZZ']
#stackOrder= [4,5,6,2,1,3,0]
Backgrounds = [
'QCD'
] # 'WJetsToQQ_HT600ToInf', 'ZJetsToQQ_HT600ToInf', 'ZZ'] 'TT', 'WW', 'WZ', 'ZZ']
BGColors = [
rt.kAzure + 7
] #, rt.kOrange-2, rt.kGreen+2], rt.kOrange+7, rt.kBlue+1, rt.kMagenta+2]
BGTeX = ['QCD'] #
stackOrder = [0]
PreSelection = [
'nocuts', 'common', 'corrections', 'cleaner', 'softdropmassCorr',
'AK4pfidfilter', 'AK8pfidfilter', 'invMAk8sel', 'detaAk8sel',
'AK8N2sel'
]
Selection = [
'preselection', 'softdropAK8sel', 'tau21sel', 'deltaR48', 'VVRegion',
'AK4N2sel', 'OpSignsel', 'detaAk4sel', 'invMAk4sel_1p0', 'Kin_AK8'
]
cutnames = [
'cleaner', 'AK8N2sel', 'invMAk8sel', 'detaAk8sel', 'softdropAK8sel',
'tau21sel', 'AK4cleaner', 'AK4N2sel', 'OpSignsel', 'detaAk4sel',
'invMAk4sel_1p0'
]
cuts = {
'cleaner':
'#splitline{p_{T-AK8} > 200 GeV, |#eta_{AK8}| < 2.5}{p_{T-AK4} > 30 GeV, |#eta_{AK4}| < 5.0}',
'AK8N2sel': 'N_{AK8} #geq 2',
'invMAk8sel': 'M_{jj-AK8} > 1050 GeV',
'detaAk8sel': '|#Delta#eta_{jj-AK8}|<1.3',
'softdropAK8sel': '65 GeV <M_{SD}< 105 GeV',
'tau21sel': '0 #leq #tau_{2}/#tau_{1}<0.45',
# 'AK4cleaner':'p_{T-AK4} > 30 GeV, |#eta_{AK4}| < 5.0',
'AK4cleaner': '',
'AK4N2sel': 'N_{AK4} #geq 2',
'OpSignsel': '#eta_{1-AK4} #eta_{2-AK4} < 0',
'detaAk4sel': '|#Delta#eta_{jj-AK4}| > 3.0',
'invMAk4sel_1p0': 'M_{jj-AK4} > 1.0 TeV'
}
VV = ('VV' in channels)
seperate = (not VV)
if VV:
#channels=["WPWP","WPWM","WMWM","WPZ","WMZ","ZZ"]
channels = ["ZZ"]
plottitle = plotdir + '_' + plot
lumi = 36.814
xLabelSize = 18.
yLabelSize = 18.
xTitleSize = 20.
yTitleSize = 22.
xTitleOffset = 4.
yTitleOffset = 1.3
printout = False
Portrait = True
cutname = False
ratio = includeData
if ('highbin' in plot):
binning = 'dijetbinning'
else:
binning = 'default'
if (Portrait):
canvX = 600
canvY = 600
else:
canvX = 900
canvY = 675
if (plotdir in PreSelection):
region = 'PreSelection'
initPath = ''
referenceHistPath = 'detaAk8sel/N_pv'
if (PreSelection.index(plotdir) < 4 and ('softdrop' in plot)):
return 'SofdropMass not filled yet!'
else:
region = 'SignalRegion'
referenceHistPath = 'tau21sel/N_pv'
referenceHistPath = plotdir + '/' + plot
if (initPath == ''):
path = '/nfs/dust/cms/user/loemkerj/bachelor/CMSSW_10_2_16/src/UHH2/aQGCVVjjhadronic/%s' % region
else:
path = initPath
outputPath = path.replace(
'/nfs/dust/cms/user/loemkerj/bachelor/CMSSW_10_2_16/src/UHH2/aQGCVVjjhadronic/SignalRegion',
'plots/')
if (plotdir in PreSelection):
CutNumber = PreSelection.index(plotdir)
else:
CutNumber = Selection.index(plotdir)
outputPath = outputPath + '/%02i_%s' % (CutNumber, plotdir) + '/'
if (printout):
print('InputPath:', path)
print('OutputPath:', outputPath)
#check if OutputPath exists - and if not create it!
if not os.path.exists(outputPath):
os.makedirs(outputPath)
# path='/home/albrec/Master/signal/'
scaleVV = (scaleSignal != 0)
VVScale = scaleSignal
if (UserRange[2] == None or UserRange[3] == None):
YRangeUser = False
Ymin = UserRange[2]
Ymax = UserRange[3]
else:
YRangeUser = True
Ymin = UserRange[2]
Ymax = UserRange[3]
if (UserRange[0] == None or UserRange[1] == None):
XRangeUser = False
Xmin = UserRange[0]
Xmax = UserRange[1]
else:
XRangeUser = True
Xmin = UserRange[0]
Xmax = UserRange[1]
# YRangeUser=False
# Ymin=0.11
# Ymax=9*10**3
# XRangeUser=False
# Xmin=0
# Xmax=6000.
gROOT.ProcessLine("gErrorIgnoreLevel = 2001;")
SFiles = []
for i in range(len(channels)):
SFiles.append(
TFile(
path +
"/uhh2.AnalysisModuleRunner.MC.MC_aQGC_%sjj_hadronic_2016v3.root"
% channels[i]))
#uhh2.AnalysisModuleRunner.MC.MC_aQGC_ZZjj_hadronic_2016v3.root
##Open Files to get BackgroundHist:
BFiles = []
for i in range(len(Backgrounds)):
BFiles.append(
TFile(path +
"/uhh2.AnalysisModuleRunner.MC.MC_%s.root" % Backgrounds[i]))
#Open File to get DataHist:
# DataFile = TFile(path+"/uhh2.AnalysisModuleRunner.Data.DATA.root")
#gROOT.ProcessLine( "gErrorIgnoreLevel = 0;")
if (includeData == True):
#calculate QCDscale with Integrals from the following Histogram:
# referenceHistPath = 'tau21sel/N_AK4'
# referenceHistPath = 'detaAk8sel/N_pv'
# referenceHistPath = 'tau21sel/met_pt_over_sumptAK8_2'
QCDscale = float(DataFile.Get(referenceHistPath).Integral())
QCDNorm = 1
for i in range(len(BFiles)):
if ('QCD' in BFiles[i].GetName()):
QCDNorm = float(BFiles[i].Get(referenceHistPath).Integral())
else:
QCDscale -= float(BFiles[i].Get(referenceHistPath).Integral())
QCDscale /= QCDNorm
else:
QCDscale = 1.0
if (printout):
print('using QCDscale:', QCDscale)
SHists = []
for i in range(len(channels)):
SHists.append(SFiles[i].Get(plotdir + '/' + plot))
BHists = []
for i in range(len(BFiles)):
BHists.append(BFiles[i].Get(plotdir + '/' + plot))
if ('QCD' in BFiles[i].GetName()):
BHists[-1].Scale(QCDscale)
#if(includeData):
# DataHist=DataFile.Get(plotdir+'/'+plot)
if (binning == 'dijetbinning'):
fitbinning = array('d')
binwidth = 200
NBins = (14000 / binwidth) - ((1040 / binwidth) + 1)
NBins = int(NBins)
for i in range(NBins + 1):
fitbinning.append(1050 + i * binwidth)
for i in range(len(channels)):
SHists[i] = SHists[i].Rebin(NBins, "new binning", fitbinning)
for i in range(len(Backgrounds)):
BHists[i] = BHists[i].Rebin(NBins, "new binning", fitbinning)
if (includeData):
DataHist = DataHist.Rebin(NBins, "new binning", fitbinning)
canv = TCanvas(plottitle, plottitle, canvX, canvY)
yplot = 0.7
yratio = 0.3
ymax = 1.0
xmax = 1.0
xmin = 0.0
if (ratio):
plotpad = TPad("plotpad", "Plot", xmin, ymax - yplot, xmax, ymax)
ratiopad = TPad("ratiopad", "Ratio", xmin, ymax - yplot - yratio, xmax,
ymax - yplot)
else:
plotpad = TPad("plotpad", "Plot", xmin, ymax - yplot - yratio, xmax,
ymax)
plotpad.SetTopMargin(0.08)
plotpad.SetLeftMargin(0.1)
plotpad.SetRightMargin(0.05)
plotpad.SetTicks()
plotpad.Draw()
if (ratio):
plotpad.SetBottomMargin(0.016)
ratiopad.SetTopMargin(0.016)
ratiopad.SetBottomMargin(0.35)
ratiopad.SetLeftMargin(0.1)
ratiopad.SetRightMargin(0.05)
ratiopad.SetTicks()
ratiopad.Draw()
else:
plotpad.SetBottomMargin(0.1)
if (logY):
plotpad.SetLogy()
canv.SetLogy()
if ('-logX' in xTitle):
plotpad.SetLogx()
if (ratio):
ratiopad.SetLogx()
canv.SetLogx()
drawOptions = "HE"
stack = THStack(plottitle, plottitle)
BHist = THStack(plottitle, plottitle)
# for i in range(len(Backgrounds)):
for i in stackOrder:
# BHists[i].SetFillColor(BGColors[i])
BHists[i].SetLineColor(BGColors[i])
BHist.Add(BHists[i], 'Hist')
BHist.SetTitle(plottitle)
BHistErr = BHists[0].Clone()
for i in range(1, len(Backgrounds)):
BHistErr.Add(BHists[i])
BHistErr.SetFillStyle(3204)
BHistErr.SetFillColor(rt.kGray + 2)
BHistErr.SetLineColor(1)
BGMax = BHist.GetMaximum()
SIGMax = 0
#if(VV): #new
# SIGMax=VVsum.GetMaximum()
#else:
for i in range(len(channels)):
tmpmax = SHists[i].GetMaximum()
if (tmpmax > SIGMax):
SIGMax = tmpmax
if (scaleVV):
SIGMax = SIGMax * VVScale
if (logY):
MAX = 0.9 * float(10**(magnitude(max(BGMax, SIGMax)) + 1))
MIN = float(10**(magnitude(max(BGMax, SIGMax)) - 5))
MIN += float(10**(magnitude(MIN)))
legendMIN = math.log(max(BGMax, SIGMax)) / math.log(MAX)
else:
MAX = (1.0 / 0.8) * max(BGMax, SIGMax)
legendMIN = 0.7
MIN = 0.
legendMIN = (legendMIN * 0.7) + 0.3 - 0.016
legend = TLegend(0.5, 0.75, 0.85, 0.89)
legend.SetFillStyle(0)
legend.SetTextSize(0.02)
legend.SetMargin(0.4)
legend.SetNColumns(2)
legend.SetColumnSeparation(0.3)
if (includeData):
DataHist.SetMarkerStyle(8)
DataHist.SetLineColor(1)
DataHist.SetTitle(plottitle)
if VV:
for i in range(len(channels)):
if (i == 0):
VVsum = SHists[i].Clone()
else:
VVsum.Add(SHists[i])
legentry = 'VVjj'
if (scaleVV):
VVsum.Scale(VVScale)
legentry += ' *%0.f' % VVScale
VVsum.SetLineColor(1)
VVsum.SetLineStyle(plotstyle[0][1])
VVsum.SetLineWidth(2)
legend.AddEntry(VVsum, legentry)
else:
for i in range(len(channels)):
SHists[i].SetLineColor(plotstyle[i][0])
SHists[i].SetLineStyle(plotstyle[i][1])
SHists[i].SetLineWidth(2)
legentry = "%sjj" % channelTex[channels[i]]
if (scaleVV):
SHists[i].Scale(VVScale)
legentry += ' *%.2E' % VVScale
legend.AddEntry(SHists[i], legentry)
for i in stackOrder:
legend.AddEntry(BHists[i], BGTeX[i], "f")
legend.AddEntry(BHistErr, "stat. Uncertainty", "f")
if (includeData):
legend.AddEntry(DataHist, "Data", "lep")
canv.SetTitle(plottitle)
BHistErr.GetYaxis().SetTitle('Events')
BHistErr.GetYaxis().SetRangeUser(MIN, MAX)
BHistErr.GetYaxis().SetTitleFont(43)
BHistErr.GetYaxis().SetTitleSize(yTitleSize)
BHistErr.GetYaxis().SetTitleOffset(yTitleOffset)
BHistErr.GetYaxis().SetLabelFont(43)
BHistErr.GetYaxis().SetLabelSize(yLabelSize)
if (ratio):
BHistErr.GetXaxis().SetTitleSize(0.0)
BHistErr.GetXaxis().SetLabelSize(0.0)
else:
BHistErr.GetXaxis().SetTitle(xTitle)
BHistErr.GetXaxis().SetTitleFont(43)
BHistErr.GetXaxis().SetTitleSize(xTitleSize)
# BHistErr.GetXaxis().SetTitleOffset(xTitleOffset)
BHistErr.GetXaxis().SetTitleOffset(1.2)
BHistErr.GetXaxis().SetLabelFont(43)
BHistErr.GetXaxis().SetLabelSize(xLabelSize)
# BHistErr.GetXaxis().SetTickLength(0.08)
# BHistErr.GetXaxis().SetNdivisions(506)
if (YRangeUser):
BHistErr.GetYaxis().SetRangeUser(Ymin, Ymax)
if (XRangeUser):
BHistErr.GetXaxis().SetRangeUser(Xmin, Xmax)
plotpad.cd()
BHistErr.Draw("E2")
BHist.Draw("HistSAME")
BHistErr.Draw("E2SAME")
if (VV):
VVsum.Draw("SAME" + drawOptions)
elif ('-noSig' not in xTitle):
for i in range(len(channels)):
SHists[i].Draw("SAME" + drawOptions)
if (includeData):
DataHist.Draw("APE1SAME")
plotpad.RedrawAxis()
if (ratio):
ratiopad.cd()
if (includeData):
ratioHist = DataHist.Clone()
else:
ratioHist = BHistErr.Clone()
ratioHist.SetLineColor(rt.kBlack)
# ratioHist.Sumw2()
ratioHist.SetStats(0)
ratioHist.Divide(BHistErr)
ratioHist.SetMarkerStyle(21)
ratioHist.SetMarkerSize(0.7)
#Yaxis
ratioHist.GetYaxis().SetRangeUser(0.3, 1.7)
ratioHist.GetYaxis().SetTitle("Data/BG")
ratioHist.GetYaxis().CenterTitle()
ratioHist.GetYaxis().SetTitleFont(43)
ratioHist.GetYaxis().SetTitleSize(yTitleSize)
ratioHist.GetYaxis().SetTitleOffset(yTitleOffset)
ratioHist.GetYaxis().SetLabelFont(43)
ratioHist.GetYaxis().SetLabelSize(yLabelSize)
ratioHist.GetYaxis().SetNdivisions(506)
#Xaxis
ratioHist.GetXaxis().SetTitle(xTitle)
ratioHist.GetXaxis().SetTitleFont(43)
ratioHist.GetXaxis().SetTitleSize(xTitleSize)
ratioHist.GetXaxis().SetTitleOffset(xTitleOffset)
ratioHist.GetXaxis().SetLabelFont(43)
ratioHist.GetXaxis().SetLabelSize(xLabelSize)
ratioHist.GetXaxis().SetTickLength(0.08)
ratioHist.GetXaxis().SetNdivisions(506)
# if(YRangeUser):
# ratioHist.GetYaxis().SetRangeUser(Ymin,Ymax)
if (XRangeUser):
ratioHist.GetXaxis().SetRangeUser(Xmin, Xmax)
ratioXMin = Xmin
ratioXMax = Xmax
else:
ratioXMin = ratioHist.GetXaxis().GetXmin()
ratioXMax = ratioHist.GetXaxis().GetXmax()
ratioHist.Draw("ep")
zeropercent = TLine(ratioXMin, 1, ratioXMax, 1)
zeropercent.Draw()
plus10percent = TLine(ratioXMin, 1.1, ratioXMax, 1.1)
plus10percent.SetLineStyle(rt.kDashed)
plus10percent.Draw()
minus10percent = TLine(ratioXMin, 0.9, ratioXMax, 0.9)
minus10percent.SetLineStyle(rt.kDashed)
minus10percent.Draw()
canv.cd()
gPad.RedrawAxis()
legend.Draw()
latex = TLatex()
latex.SetNDC(kTRUE)
latex.SetTextSize(20)
latex.DrawLatex(0.69, 0.953, "%.2f fb^{-1} (13 TeV)" % lumi)
latex.DrawLatex(0.1, 0.953, "private work")
lastcut = 'nocuts'
for cut in cutnames:
if cut in plotdir:
lastcut = cut
if (not (lastcut == 'nocuts') and cutname):
# latex.SetTextSize(0.03)
latex.SetTextSize(15)
for l in range(cutnames.index(lastcut) + 1):
latex.DrawLatex(0.12, 0.8 - l * 0.04, cuts[cutnames[l]])
canv.Update()
canv.Print(outputPath + '/%s_%s.pdf' % (plotdir, plot))
#prevents memory leak in Canvas Creation/Deletion
#see: https://root.cern.ch/root/roottalk/roottalk04/2484.html
gSystem.ProcessEvents()
if (ratio):
del ratiopad
del plotpad, canv
# gc.collect()
return 'done!'
def drawHistsWithRatio(hists, name, **kwargs):
"""Draw histograms with ratios."""
title = kwargs.get('title', "")
xtitle = kwargs.get('xtitle', "")
ytitle = kwargs.get('ytitle', "")
rtitle = kwargs.get('rtitle', "Ratio")
xmin = kwargs.get('xmin', hists[0].GetXaxis().GetXmin())
xmax = kwargs.get('xmax', hists[0].GetXaxis().GetXmax())
ymin = kwargs.get('ymin', None)
ymax = kwargs.get('ymax', None)
rmin = kwargs.get('rmin', 0.45)
rmax = kwargs.get('rmax', 1.55)
logx = kwargs.get('logx', False)
logy = kwargs.get('logy', False)
denom = kwargs.get('denom', 1) - 1 # denominator for ratio
textsize = kwargs.get('textsize', 0.045)
texts = kwargs.get('text', [])
#textheight = kwargs.get('textheight', 1.09 )
#ctext = kwargs.get('ctext', [ ] ) # corner text
#cposition = kwargs.get('cposition', 'topleft' ).lower() # cornertext
#ctextsize = kwargs.get('ctextsize', 1.4*legendtextsize )
colors = kwargs.get('colors', linecolors)
if not isinstance(texts, list) or isinstance(texts, tuple):
texts = [texts]
if ymax == None:
ymax = 1.12 * max(h.GetMaximum() for h in hists)
# MAIN plot
canvas = TCanvas('canvas', 'canvas', 100, 100, 800, 800)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameBorderMode(0)
canvas.Divide(2)
canvas.SetMargin(0.0, 0.0, 0.0, 0.0)
canvas.cd(1)
gPad.SetPad('pad1', 'pad1', 0, 0.33, 1, 1)
gPad.SetMargin(0.12, 0.04, 0.02, 0.08)
gPad.SetFillColor(0)
gPad.SetBorderMode(0)
gPad.SetTickx(0)
gPad.SetTicky(0)
gPad.SetGrid()
gPad.Draw()
canvas.cd(2)
gPad.SetPad('pad2', 'pad2', 0, 0, 1, 0.33)
gPad.SetMargin(0.12, 0.04, 0.30, 0.03)
gPad.SetFillColor(0)
gPad.SetFillStyle(4000)
gPad.SetFrameFillStyle(0)
gPad.SetBorderMode(0)
gPad.Draw()
# MAIN plot
canvas.cd(1)
for i, hist in enumerate(hists):
color = colors[i % len(colors)]
hist.SetLineColor(color)
hist.SetLineWidth(2)
hist.Draw('HIST SAME')
frame = hists[0]
frame.GetYaxis().SetTitleSize(0.060)
frame.GetXaxis().SetTitleSize(0)
frame.GetXaxis().SetLabelSize(0)
frame.GetYaxis().SetLabelSize(0.052)
frame.GetXaxis().SetLabelOffset(0.010)
frame.GetXaxis().SetTitleOffset(0.98)
frame.GetYaxis().SetTitleOffset(1.05)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetTitle(xtitle)
if logx:
gPad.Update()
gPad.SetLogx()
if logy:
gPad.Update()
gPad.SetLogy()
if ymin: frame.SetMinimum(ymin)
if ymax: frame.SetMaximum(ymax)
width = 0.25
height = 1.1 * textsize * len([l for l in texts + hists if l])
x1, y1 = 0.65, 0.88
x2, y2 = x1 + width, y1 - height
legend = TLegend(x1, y1, x2, y2)
legend.SetTextSize(textsize)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetMargin(0.05 / width)
if title:
legend.SetTextFont(62)
legend.SetHeader(title)
legend.SetTextFont(42)
for hist in hists:
legend.AddEntry(hist, hist.GetTitle(), 'l')
for text in texts:
legend.AddEntry(0, text, '')
legend.Draw()
gPad.SetTicks(1, 1)
gPad.Modified()
frame.Draw('AXIS SAME')
CMS_style.CMS_lumi(gPad, 13, 0)
# RATIO plot
canvas.cd(2)
ratios = []
for i, hist in enumerate(hists):
if i == denom: continue
ratio = hist.Clone(hist.GetName() + "_ratio")
ratio.Divide(hists[denom])
ratio.Draw('HIST SAME')
ratios.append(ratio)
frame_ratio = ratios[0]
frame_ratio.GetYaxis().SetRangeUser(rmin, rmax)
frame_ratio.GetYaxis().CenterTitle()
frame_ratio.GetYaxis().SetTitleSize(0.13)
frame_ratio.GetXaxis().SetTitleSize(0.13)
frame_ratio.GetXaxis().SetLabelSize(0.12)
frame_ratio.GetYaxis().SetLabelSize(0.11)
frame_ratio.GetXaxis().SetLabelOffset(0.012)
frame_ratio.GetXaxis().SetTitleOffset(1.02)
frame_ratio.GetYaxis().SetTitleOffset(0.48)
frame_ratio.GetXaxis().SetNdivisions(508)
frame_ratio.GetYaxis().CenterTitle(True)
frame_ratio.GetYaxis().SetTitle(rtitle)
frame_ratio.GetXaxis().SetTitle(xtitle)
frame_ratio.GetYaxis().SetNdivisions(505)
if logx:
gPad.Update()
gPad.SetLogx()
line = TLine(xmin, 1., xmax, 1.)
line.SetLineColor(hists[denom].GetLineColor())
line.SetLineWidth(hists[denom].GetLineWidth())
line.SetLineStyle(1)
line.Draw('SAME')
gPad.SetTicks(1, 1)
gPad.Update()
gPad.SetGrid()
gPad.Modified()
frame_ratio.Draw('SAME AXIS')
canvas.SaveAs(name + ".png")
canvas.SaveAs(name + ".pdf")
canvas.Close()
xstart = 0.4
ystart = 0.75
latex = TLatex()
latex.SetNDC()
latex.SetTextAlign(12)
latex.SetTextSize(textsize)
latex.DrawLatex(xstart, 0.85, "CMS Preliminary")
latex.DrawLatex(xstart, 0.80, "4.96 fb^{-1}, #sqrt{s}=7TeV")
legend = TLegend(xstart, ystart - 7.7 * textsize, xstart + width, ystart)
legend.SetFillColor(0)
legend.SetTextSize(textsize)
legend.SetColumnSeparation(0.0)
legend.SetEntrySeparation(0.1)
legend.SetMargin(0.2)
# Add data to legend
if nj == "2":
legend.AddEntry(rooplot.findObject("h_dataset"), "2-jet Data", "p")
elif nj == "3":
legend.AddEntry(rooplot.findObject("h_dataset"), "3-jet Data", "p")
elif nj == "4":
legend.AddEntry(rooplot.findObject("h_dataset"), "#geq4-jet Data", "p")
elif nj == "23":
legend.AddEntry(rooplot.findObject("h_dataset"), "2+3-jet Data", "p")
# Add functions to legend
for func in ["f1", "f2", "f3"]:
legend.AddEntry(pdfs[func, "obj"], fitFuncs[func, "name"], "l")
def hvt(benchmark=['B3', 'A1']):
hxs = {}
hw = {}
gxs = {}
gw = {}
mg = TMultiGraph()
for m in massPoints:
hxs[m] = TH2F("hxs_M%d" % m, ";;", 50, -0.04, 3.96, 100, 0., 2.)
hw[m] = TH2F("hw_M%d" % m, ";;", 50, -0.04, 3.96, 50, 0., 2.)
for m in massPoints:
file = TFile.Open("HVT/scanHVT_M%s.root" % m, "READ")
tree = file.Get("tree")
for entry in range(
tree.GetEntries()): # Fill mass points only if NOT excluded
tree.GetEntry(entry)
gH, gF = tree.gv * tree.ch, tree.g * tree.g * tree.cq / tree.gv
XsBr = tree.CX0 * tree.BRbb * 1000. # in fb
if XsBr < observed[m]: hxs[m].Fill(gH, gF)
if tree.total_widthV0 / float(m) < width: hw[m].Fill(gH, gF)
for b in range(hxs[m].GetNbinsX() * hxs[m].GetNbinsY()):
hxs[m].SetBinContent(b, 1. if hxs[m].GetBinContent(b) > 0. else 0.)
hw[m].SetBinContent(b, 1. if hw[m].GetBinContent(b) > 0. else 0.)
#hxs[m].Smooth(20)
#hw[m].Smooth(20)
gxs[m] = getCurve(hxs[m])
for i, g in enumerate(gxs[m]):
g.SetLineColor(massColors[m])
g.SetFillColor(massColors[m])
g.SetFillStyle(massFill[m]) #(3345 if i>1 else 3354)
g.SetLineWidth(503 * (1 if i < 2 else -1))
mg.Add(g)
#if m==3000:
if m == massPoints[-1]:
gw[m] = getCurve(hw[m])
for i, g in enumerate(gw[m]):
g.SetPoint(0, 0., g.GetY()[0])
g.SetLineWidth(501 * (1 if i < 2 else -1))
g.SetLineColor(920 + 2)
g.SetFillColor(920 + 1)
g.SetFillStyle(3003)
mg.Add(g)
if options.root:
outFile = TFile("plotsLimit/Model.root", "RECREATE")
outFile.cd()
for m in massPoints:
mg[m].Write("X_M%d" % m)
mgW.Write("width")
outFile.Close()
print "Saved histogram in file plotsLimit/Model.root, exiting..."
exit()
### plot ###
c1 = TCanvas("c1", "HVT Exclusion Limits", 800, 600)
c1.cd()
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetTicks(1, 1)
mg.Draw("AC")
#mg.GetXaxis().SetTitle("g_{V} c_{H}")
mg.GetXaxis().SetTitle("Higgs and vector boson coupling g_{H}")
mg.GetXaxis().SetRangeUser(-3., 3.)
mg.GetXaxis().SetLabelSize(0.045)
mg.GetXaxis().SetTitleSize(0.045)
mg.GetXaxis().SetTitleOffset(1.)
#mg.GetYaxis().SetTitle("g^{2} c_{F} / g_{V}")
mg.GetYaxis().SetTitle("Fermion coupling g_{F}")
mg.GetYaxis().SetLabelSize(0.045)
mg.GetYaxis().SetTitleSize(0.045)
mg.GetYaxis().SetTitleOffset(1.)
mg.GetYaxis().SetRangeUser(-1.2, 1.2)
mg.GetYaxis().SetNdivisions(505)
# hxs[3500].Draw("CONTZ")
drawCMS(LUMI, "Preliminary", False)
# drawAnalysis("XVH"+category, False)
# latex = TLatex()
# latex.SetNDC()
# latex.SetTextFont(62)
# latex.SetTextSize(0.06)
# latex.DrawLatex(0.10, 0.925, "CMS")
# model B
g_model = {}
for i, b in enumerate(benchmark):
g_model[i] = TGraph(1)
g_model[i].SetTitle(models_name[b])
g_model[i].SetPoint(0, models_point[b][0], models_point[b][1])
g_model[i].SetMarkerStyle(models_style[b])
g_model[i].SetMarkerColor(models_color[b])
g_model[i].SetMarkerSize(1.5)
g_model[i].Draw("PSAME")
# text
latex = TLatex()
latex.SetTextSize(0.045)
latex.SetTextFont(42)
latex.SetTextColor(630)
# for b in benchmark: latex.DrawLatex(models_point[b][0]+0.02, models_point[b][1]+0.02, models_name[b])
latex.SetTextColor(920 + 2)
latex.DrawLatex(-2.8, -0.875,
"#frac{#Gamma_{Z'}}{m_{Z'}} > %.0f%%" % (width * 100, ))
#leg = TLegend(0.68, 0.60, 0.95, 0.94)
leg = TLegend(0.68, 0.34, 0.95, 0.66)
leg.SetBorderSize(1)
leg.SetFillStyle(1001)
leg.SetFillColor(0)
for m in massPoints:
leg.AddEntry(gxs[m][0], "m_{Z'} = %.1f TeV" % (m / 1000.), "fl")
for i, b in enumerate(benchmark):
leg.AddEntry(g_model[i], g_model[i].GetTitle(), "P")
leg.SetY1(leg.GetY2() - leg.GetNRows() * 0.050)
leg.SetMargin(0.35)
leg.Draw()
gxs_ = gxs[massPoints[0]][0].Clone("gxs_")
gxs_.SetLineColor(1)
# gxs_.SetFillColor(1)
latex.SetNDC()
latex.SetTextColor(1)
latex.SetTextSize(0.04)
latex.SetTextFont(52)
latex.DrawLatex(0.15, 0.95, "q#bar{q} #rightarrow Z' #rightarrow b#bar{b}")
c1.Print("plots/model/HVT.png")
c1.Print("plots/model/HVT.pdf")
c1.Print("plots/model/HVT.root")
c1.Print("plots/model/HVT.C")
#g = 0.646879, cH = 0.976246, cF = 1.02433
print "model B = [", 3 * 0.976246, ",", 0.646879 * 0.646879 * 1.02433 / 3, "]"
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
