width = 0.4
textsize = 0.04
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"]:
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!'
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 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 plotPostFitValues(channel,var,DM,year,*parameters,**kwargs):
"""Draw post-fit values for parameter using MultiDimFit and FitDiagnostics output."""
if DM=='DM0' and 'm_2' in var: return
print green("\n>>> plotPostFitValues %s, %s"%(DM, var))
if len(parameters)==1 and isinstance(parameters[0],list): parameters = parameters[0]
parameters = [p.replace('$CAT',DM).replace('$CHANNEL',channel) for p in list(parameters)]
title = kwargs.get('title', "" )
name = kwargs.get('name', "" )
indir = kwargs.get('indir', "output_%d"%year )
outdir = kwargs.get('outdir', "postfit_%d"%year )
tag = kwargs.get('tag', "" )
plotlabel = kwargs.get('plotlabel', "" )
compareFD = kwargs.get('compareFD', False ) and N==1
era = "%d-13TeV"%year
isBBB = any("_bin_" in p for p in parameters)
filename = '%s/higgsCombine.%s_%s-%s%s-%s.MultiDimFit.mH90.root'%(indir,channel,var,DM,tag,era)
filenamesFD = '%s/fitDiagnostics.%s_%s-%s%s-%s_TES*p*.root'%(indir,channel,var,DM,tag,era)
ensureDirectory(outdir)
if not name:
name = formatParameter(parameters[0]).replace('_'+DM,'')
if len(parameters)>1:
name = "comparison_%s"%(name) #re.sub(r"bin_\d+","bin",name)
canvasname = "%s/postfit-%s_%s_%s%s%s"%(outdir,name,var,DM,tag,plotlabel)
print '>>> file "%s"'%(filename)
graphs = [ ]
graphsFD = [ ]
tvals = [ ]
pvals = [ -2.2, +2.2 ]
tes = measureTES(filename)
for parameter in parameters[:]:
graph = getTGraphOfParameter(filename,'tes',parameter,xvals=tvals,yvals=pvals)
if graph:
graphs.append(graph)
else:
parameters.remove(parameter)
if compareFD:
graphFD = getTGraphOfParameter_FD(filenamesFD,parameter,xvals=tvals,yvals=pvals)
if graphFD: graphsFD.append(graphFD)
if len(parameters)!=len(graphs):
warning("plotPostFitValues: len(parameters) = %d != %d = len(graphs)"%(len(parameters),len(graphs)))
exit(1)
N = len(parameters)
compareFD = compareFD and len(graphsFD)>0
parameters = [formatParameter(p).replace('_'+DM,'') for p in parameters]
graphsleg = columnize(graphs,3) if N>6 else columnize(graphs,2) if N>3 else graphs # reordered for two columns
paramsleg = columnize(parameters,3) if N>6 else columnize(parameters,2) if N>3 else parameters # reordered for two columns
xtitle = 'tau energy scale'
ytitle = "%s post-fit value"%(parameters[0] if N==1 else "MultiDimFit")
xmin, xmax = min(tvals), max(tvals)
ymin, ymax = min(pvals), max(pvals)
colors = [ kBlack, kBlue, kRed, kGreen, kMagenta, kOrange, kTeal, kAzure+2, kYellow-3 ]
canvas = TCanvas("canvas","canvas",100,100,800,650)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetTopMargin( 0.07 ); canvas.SetBottomMargin( 0.13 )
canvas.SetLeftMargin( 0.11 ); canvas.SetRightMargin( 0.05 )
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
canvas.cd()
maxmargin = 0.18*abs(ymax-ymin)
minmargin = 0.20*abs(ymax-ymin) #(0.20 if N<5 else 0.10*ceil(N/2))
ymin = 0.0 if ymin>=0 else ymin-minmargin
ymax = ymax + minmargin
textsize = 0.045 if N==1 else 0.036
lineheight = 0.055 if N==1 else 0.045
x1, width = 0.42, 0.25
y1, height = 0.15, lineheight*(ceil(N/3.) if N>6 else ceil(N/2.) if N>3 else N)
if title: height += lineheight
if compareFD: height += lineheight
if N>6:
if isBBB: width = 0.62; x1 = 0.25
else: width = 0.70; x1 = 0.20
elif N>3: width = 0.52; x1 = 0.36
legend = TLegend(x1,y1,x1+width,y1+height)
legend.SetTextSize(textsize)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
if title:
legend.SetTextFont(62)
legend.SetHeader(title)
legend.SetTextFont(42)
if N>6:
legend.SetNColumns(3)
legend.SetColumnSeparation(0.02)
elif N>3:
legend.SetNColumns(2)
legend.SetColumnSeparation(0.03)
frame = canvas.DrawFrame(xmin,ymin,xmax,ymax)
frame.GetYaxis().SetTitleSize(0.060)
frame.GetXaxis().SetTitleSize(0.060)
frame.GetXaxis().SetLabelSize(0.050)
frame.GetYaxis().SetLabelSize(0.050)
frame.GetXaxis().SetLabelOffset(0.01)
frame.GetYaxis().SetLabelOffset(0.01)
frame.GetXaxis().SetTitleOffset(0.98)
frame.GetYaxis().SetTitleOffset(0.84)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetTitle(xtitle)
for i, (parameter,graph) in enumerate(zip(parameters,graphs)):
graph.SetLineColor(colors[i%len(colors)])
graph.SetLineWidth(2)
graph.SetLineStyle(1)
graph.Draw('LSAME')
for parameter,graph in zip(paramsleg,graphsleg):
if N==1:
legend.AddEntry(graph, "MultiDimFit", 'l')
else:
legend.AddEntry(graph, parameter, 'l')
line = TLine(tes, ymin, tes, ymax)
#line.SetLineWidth(1)
line.SetLineStyle(7)
line.Draw('SAME')
latex = TLatex()
latex.SetTextSize(0.045)
latex.SetTextAlign(13)
latex.SetTextFont(42)
latex.DrawLatex(tes+0.02*(xmax-xmin),ymax-0.04*(ymax-ymin),"tes = %.3f"%tes)
if compareFD:
graphFD.SetLineColor(kBlue)
graphFD.SetLineWidth(2)
graphFD.SetLineStyle(2)
graphFD.Draw('LSAME')
legend.AddEntry(graphFD, "FitDiagnostics", 'l')
legend.Draw()
CMS_lumi.relPosX = 0.12
CMS_lumi.CMS_lumi(canvas,13,0)
gPad.SetTicks(1,1)
gPad.Modified()
frame.Draw('SAMEAXIS')
canvas.SaveAs(canvasname+".png")
if args.pdf: canvas.SaveAs(canvasname+".pdf")
canvas.Close()
