def getGraph(self):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(
self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match" % (
len(self.__x), len(self.__y), len(
self.__yErrLow), len(self.__yErrHigh))
result = TMultiGraph()
legendPosition = [
float(i) for i in self.__getStyleOption("legendPosition").split()
]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
result.SetTitle("%s;%s;%s" %
(self.__title, self.__xTitle, self.__yTitle))
#(refArrays, refLabel) = self.__getRefernceGraphArrays()
#refGraph = TGraphAsymmErrors(*refArrays)
#refGraph.SetLineWidth(2)
#refGraph.SetLineColor(int(self.__config.get("reference","lineColor")))
#refGraph.SetFillColor(int(self.__config.get("reference","fillColor")))
#result.Add(refGraph,"L3")
#legend.AddEntry(refGraph,self.__config.get("reference","name"))
xErr = array("d", [0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr,
self.__yErrLow, self.__yErrHigh)
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
sysGraph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr,
self.__ySysErrLow, self.__ySysErrHigh)
sysGraph.SetLineWidth(1)
sysGraph.SetFillColor(0)
sysGraph.SetLineColor(int(self.__getStyleOption("lineColor")))
sysGraph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
sysGraph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
sysGraph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
result.Add(sysGraph, "[]")
result.Add(graph, "P")
# result.SetName("MultiPlots")
# result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
result.SetName("MG_%s" % (self.__title))
legend.AddEntry(graph, self.__getStyleOption("name"))
#for (x,y,yErr) in zip(self.__x, self.__y, zip(self.__yErrLow,self.__yErrHigh)):
# self.__addAnnotaion("hallo",x,y,yErr)
return (result, legend)
def getGraphSimple(self):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match"%(len(self.__x), len(self.__y), len(self.__yErrLow), len(self.__yErrHigh))
legendPosition = [float(i) for i in self.__getStyleOption("legendPosition").split()]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
xErr = array("d",[0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__yErrLow,self.__yErrHigh)
graph.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
graph.SetDrawOption("AP")
return (graph, legend)
def convertToPoisson(h):
graph = TGraphAsymmErrors()
q = (1-0.6827)/2.
for i in range(1,h.GetNbinsX()+1):
x=h.GetXaxis().GetBinCenter(i)
xLow =h.GetXaxis().GetBinLowEdge(i)
xHigh =h.GetXaxis().GetBinUpEdge(i)
y=h.GetBinContent(i)
yLow=0
yHigh=0
if y !=0.0:
yLow = y-Math.chisquared_quantile_c(1-q,2*y)/2.
yHigh = Math.chisquared_quantile_c(q,2*(y+1))/2.-y
graph.SetPoint(i-1,x,y)
graph.SetPointEYlow(i-1,yLow)
graph.SetPointEYhigh(i-1,yHigh)
graph.SetPointEXlow(i-1,0.0)
graph.SetPointEXhigh(i-1,0.0)
graph.SetMarkerStyle(20)
graph.SetLineWidth(2)
graph.SetMarkerSize(1.)
graph.SetMarkerColor(kBlack)
return graph
def makeResidHist(data, bkg):
pulls = TGraphAsymmErrors(data.GetN())
pulls.SetName("Pulls")
pulls.SetLineWidth(data.GetLineWidth())
pulls.SetLineStyle(data.GetLineStyle())
pulls.SetLineColor(data.GetLineColor())
pulls.SetMarkerSize(data.GetMarkerSize())
pulls.SetMarkerStyle(data.GetMarkerStyle())
pulls.SetMarkerColor(data.GetMarkerColor())
pulls.SetFillStyle(data.GetFillStyle())
pulls.SetFillColor(data.GetFillColor())
# Add histograms, calculate Poisson confidence interval on sum value
for i in range(data.GetN()):
x = data.GetX()[i]
dyl = data.GetErrorYlow(i)
dyh = data.GetErrorYhigh(i)
yy = data.GetY()[i] - bkg.Interpolate(x) #bkg.GetBinContent(i+1)
norm = dyl if yy > 0. else dyh
if norm == 0.:
yy, dyh, dyl = 0., 0., 0.
else:
yy /= norm
dyh /= norm
dyl /= norm
pulls.SetPoint(i, x, yy)
pulls.SetPointEYhigh(i, dyh)
pulls.SetPointEYlow(i, dyl)
return pulls
def convertHistToGraph(hist, useGarwood=False):
alpha = 1 - 0.6827
graph = TGraphAsymmErrors(hist.GetNbinsX())
if useGarwood:
lastEvent = False
for i in reversed(range(hist.GetNbinsX())):
N = hist.GetBinContent(i + 1)
if not lastEvent and N > 0: lastEvent = True
if lastEvent and N <= 0.: N = 1.e-6
L = 0 if N == 0 else ROOT.Math.gamma_quantile(alpha / 2, N, 1.)
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i + 1),
N if not N == 0 else -1.e99)
graph.SetPointError(i, 0., 0., N - L, U - N)
else:
for i in range(hist.GetNbinsX()):
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i + 1),
hist.GetBinContent(i + 1))
graph.SetPointError(i,
hist.GetXaxis().GetBinWidth(i + 1) / 2.,
hist.GetXaxis().GetBinWidth(i + 1) / 2.,
hist.GetBinError(i + 1),
hist.GetBinError(i + 1))
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetFillStyle(hist.GetFillStyle())
graph.SetFillColor(hist.GetFillColor())
return graph
def getDataPoissonErrors(hist,
kPoisson=False,
drawZeroBins=False,
drawXbars=False,
centerBin=True):
'''Make data poisson errors for a histogram with two different methods:
- TH1.kPoisson
- chi-squared quantile
'''
# https://github.com/DESY-CMS-SUS/cmgtools-lite/blob/8_0_25/TTHAnalysis/python/plotter/mcPlots.py#L70-L102
# https://github.com/DESY-CMS-SUS/cmgtools-lite/blob/8_0_25/TTHAnalysis/python/plotter/susy-1lep/RcsDevel/plotDataPredictWithSyst.py#L12-L21
if kPoisson: hist.SetBinErrorOption(TH1D.kPoisson)
Nbins = hist.GetNbinsX()
xaxis = hist.GetXaxis()
alpha = (1 - 0.6827) / 2.
graph = TGraphAsymmErrors(Nbins)
graph.SetName(hist.GetName() + "_graph")
graph.SetTitle(hist.GetTitle())
for i in xrange(1, Nbins + 1):
N = hist.GetBinContent(i)
if N <= 0 and not drawZeroBins: continue
dN = hist.GetBinError(i)
yscale = 1
if centerBin:
x = xaxis.GetBinCenter(i)
else:
x = xaxis.GetBinLowEdge(i)
if N > 0 and dN > 0 and abs(dN**2 / N -
1) > 1e-4: # check is error is Poisson
yscale = (dN**2 / N)
N = (N / dN)**2
if kPoisson:
EYlow = hist.GetBinErrorLow(i)
EYup = hist.GetBinErrorUp(i)
else:
EYlow = (N - Math.chisquared_quantile_c(1 - alpha, 2 * N) /
2.) if N > 0 else 0
EYup = Math.chisquared_quantile_c(alpha, 2 * (N + 1)) / 2. - N
y = yscale * N
EXup = xaxis.GetBinUpEdge(i) - x if drawXbars else 0
EXlow = x - xaxis.GetBinLowEdge(i) if drawXbars else 0
graph.SetPoint(i - 1, x, y)
graph.SetPointError(i - 1, EXlow, EXup, EYlow, EYup)
#print ">>> getDataPoissonErrors - bin %2d: (x,y) = ( %3.1f - %4.2f + %4.2f, %4.2f - %4.2f + %4.2f )"%(i,x,EXlow,EXup,y,EYlow,EYup)
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineColor(hist.GetLineColor())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetMarkerStyle(hist.GetMarkerStyle())
return graph
def makeEffPlotsVars(tree,
varx,
vary,
sel,
nbinx,
xmin,
xmax,
nbiny,
ymin,
ymax,
xtitle,
ytitle,
leglabel=None,
header='',
addon='',
option='pt',
marker=20,
col=1):
binning = [20, 200] if args.onebin else [
20, 30, 40, 50, 60, 70, 80, 100, 150, 200
]
if option == 'pt':
_hist_ = TH1F('h_effp_' + addon, 'h_effp' + addon,
len(binning) - 1, array('d', binning))
_ahist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon,
len(binning) - 1, array('d', binning))
elif option == 'eta':
_hist_ = TH1F('h_effp_' + addon, 'h_effp' + addon, nbinx, xmin, xmax)
_ahist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon, nbinx, xmin,
xmax)
tree.Draw(varx + ' >> ' + _hist_.GetName(), sel)
tree.Draw(varx + ' >> ' + _ahist_.GetName(), sel + ' && ' + vary)
g_efficiency = TGraphAsymmErrors()
g_efficiency.Divide(_ahist_, _hist_, "cl=0.683 b(1,1) mode")
g_efficiency.GetXaxis().SetTitle(xtitle)
g_efficiency.GetYaxis().SetTitle('efficiency')
g_efficiency.GetYaxis().SetNdivisions(507)
g_efficiency.SetLineWidth(3)
g_efficiency.SetName(header)
g_efficiency.SetMinimum(0.)
g_efficiency.GetYaxis().SetTitleOffset(1.3)
g_efficiency.SetMarkerStyle(marker)
g_efficiency.SetMarkerSize(1)
g_efficiency.SetMarkerColor(col)
g_efficiency.SetLineColor(col)
g_efficiency.Draw('ap')
# save(c, 'plots/' + addon)
return g_efficiency
def fixData(hist, useGarwood=True, cutGrass=False, maxPoisson=False):
if hist == None: return
varBins = False
data = TGraphAsymmErrors()
alpha = 1 - 0.6827
for i in list(reversed(range(0, hist.GetNbinsX()))):
#print "bin", i, "x:", hist.GetX()[i], "y:", hist.GetY()[i]
# X error bars to 0 - do not move this, otherwise the first bin will disappear, thanks Wouter and Rene!
N = max(hist.GetBinContent(i + 1), 0.) # Avoid unphysical bins
data.SetPoint(i, hist.GetXaxis().GetBinCenter(i + 1), N)
if not varBins:
data.SetPointEXlow(i, 0)
data.SetPointEXhigh(i, 0)
# Garwood confidence intervals
if (useGarwood):
L = ROOT.Math.gamma_quantile(alpha / 2, N, 1.) if N > 0 else 0.
U = ROOT.Math.gamma_quantile_c(alpha / 2, N + 1, 1)
# maximum between Poisson and Sumw2 error bars
EL = N - L if not maxPoisson else max(N -
L, hist.GetBinErrorLow(i))
EU = U - N if not maxPoisson else max(U -
N, hist.GetBinErrorHigh(i))
data.SetPointEYlow(i, EL)
data.SetPointEYhigh(i, EU)
else:
data.SetPointEYlow(i, math.sqrt(N))
data.SetPointEYhigh(i, math.sqrt(N))
# Cut grass
if cutGrass and data.GetY()[i] > 0.: cutGrass = False
# Treatment for 0 bins
# if abs(hist.GetY()[i])<=1.e-6:
# if cutGrass: hist.SetPointError(i, hist.GetErrorXlow(i), hist.GetErrorXhigh(i), 1.e-6, 1.e-6, )
# if (hist.GetX()[i]>65 and hist.GetX()[i]<135 and hist.GetY()[i]==0): hist.SetPointError(i, hist.GetErrorXlow(i), hist.GetErrorXhigh(i), 1.e-6, 1.e-6, )
# hist.SetPoint(i, hist.GetX()[i], -1.e-4)
# X error bars
#if hist.GetErrorXlow(i)<1.e-4:
# binwidth = hist.GetX()[1]-hist.GetX()[0]
# hist.SetPointEXlow(i, binwidth/2.)
# hist.SetPointEXhigh(i, binwidth/2.)
data.SetMarkerColor(hist.GetMarkerColor())
data.SetMarkerStyle(hist.GetMarkerStyle())
data.SetMarkerSize(hist.GetMarkerSize())
#data.SetLineSize(hist.GetLineSize())
return data
def convertHistToGraph(hist):
graph = TGraphAsymmErrors(hist.GetNbinsX())
for i in range(hist.GetNbinsX()):
graph.SetPoint(i,
hist.GetXaxis().GetBinCenter(i), hist.GetBinContent(i))
graph.SetPointError(i,
hist.GetXaxis().GetBinWidth(i) / 2.,
hist.GetXaxis().GetBinWidth(i) / 2.,
hist.GetBinError(i), hist.GetBinError(i))
graph.SetLineWidth(hist.GetLineWidth())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetFillStyle(hist.GetFillStyle())
graph.SetFillColor(hist.GetFillColor())
return graph
def histToGraph(hist, name='', keepErrors=True, poissonErrors=True):
## Helper method to convert a histogram to a corresponding graph
# @hist TH1 object
# @name name of the graph (default is name of histogram)
# @keepErrors decide if the y-errors should be propagated to the graph
# @poissonErrors decide if the y-errors should be calculated as Poisson errors
# @return graph
if not name:
name = 'g%s' % (hist.GetName())
from ROOT import TGraphAsymmErrors
nBins = hist.GetNbinsX()
graph = TGraphAsymmErrors(nBins)
graph.SetNameTitle(name, hist.GetTitle())
xAxis = hist.GetXaxis()
for i in xrange(nBins):
xVal = xAxis.GetBinCenter(i + 1)
yVal = hist.GetBinContent(i + 1)
graph.SetPoint(i, xVal, yVal)
graph.SetPointEXlow(i, abs(xVal - xAxis.GetBinLowEdge(i + 1)))
graph.SetPointEXhigh(i, abs(xVal - xAxis.GetBinUpEdge(i + 1)))
if keepErrors:
if poissonErrors:
lo, hi = calculatePoissonErrors(yVal)
graph.SetPointEYlow(i, lo)
graph.SetPointEYhigh(i, hi)
else:
graph.SetPointEYlow(i, hist.GetBinErrorLow(i + 1))
graph.SetPointEYhigh(i, hist.GetBinErrorUp(i + 1))
# copy the style
graph.SetMarkerStyle(hist.GetMarkerStyle())
graph.SetMarkerColor(hist.GetMarkerColor())
graph.SetMarkerSize(hist.GetMarkerSize())
graph.SetLineStyle(hist.GetLineStyle())
graph.SetLineColor(hist.GetLineColor())
graph.SetLineWidth(hist.GetLineWidth())
graph.SetFillColor(hist.GetFillColor())
graph.SetFillStyle(hist.GetFillStyle())
return graph
def fixPlots_withErrors(middleGraph):
thisBandsGraph = TGraphAsymmErrors()
thisBandsGraph.SetName(middleGraph.GetName())
thisBandsGraph.SetMarkerStyle(middleGraph.GetMarkerStyle())
thisBandsGraph.SetMarkerSize(middleGraph.GetMarkerSize())
thisBandsGraph.SetMarkerColor(middleGraph.GetMarkerColor())
thisBandsGraph.SetLineColor(middleGraph.GetLineColor())
for iPoint in xrange(0, middleGraph.GetN()):
# Retrieve middle graph for (x,y) coordinates
dataPointX = Double(0)
dataPointY = Double(0)
dataErrorX = Double(0)
middleGraph.GetPoint(iPoint, dataPointX, dataPointY)
dataErrorX = middleGraph.GetErrorX(iPoint)
dataErrorY = middleGraph.GetErrorY(iPoint)
dataPointY = fabs(dataPointY - 1)
if (iPoint < middleGraph.GetN()):
#if(dataPointY != 0 and iPoint < middleGraph.GetN()):
print "fixPlots:", dataPointX
thisBandsGraph.SetPoint(iPoint, dataPointX, dataPointY)
thisBandsGraph.SetPointError(iPoint, dataErrorX, dataErrorX,
dataErrorY, dataErrorY)
#if (dataPointY == 0) :
#thisBandsGraph.SetPoint(iPoint, dataPointX, dataPointY)
#thisBandsGraph.SetPointError(iPoint, dataErrorX, dataErrorX, dataErrorY, dataErrorY)
return thisBandsGraph
def makeEffPlotsVars(tree,
varx,
numeratorAddSelection,
baseSelection,
binning,
xtitle='',
header='',
addon='',
marker=20,
col=1):
_denomHist_ = TH1F('h_effp_' + addon, 'h_effp' + addon,
len(binning) - 1, binning)
_nominatorHist_ = TH1F('ah_effp_' + addon, 'ah_effp' + addon,
len(binning) - 1, binning)
tree.Draw(varx + ' >> ' + _denomHist_.GetName(), baseSelection)
tree.Draw(varx + ' >> ' + _nominatorHist_.GetName(),
baseSelection + ' && ' + numeratorAddSelection)
g_eff = TGraphAsymmErrors()
g_eff.Divide(_nominatorHist_, _denomHist_, "cl=0.683 b(1,1) mode")
g_eff.GetXaxis().SetTitle(xtitle)
g_eff.GetYaxis().SetTitle('efficiency')
g_eff.GetYaxis().SetNdivisions(507)
g_eff.SetLineWidth(3)
g_eff.SetName(header)
g_eff.SetMinimum(0.)
g_eff.GetYaxis().SetTitleOffset(1.3)
g_eff.SetMarkerStyle(marker)
g_eff.SetMarkerSize(1)
g_eff.SetMarkerColor(col)
g_eff.SetLineColor(col)
g_eff.Draw('ap')
return g_eff
def MakeOneHist(histogramName):
HeaderLabel = TPaveLabel(header_x_left, header_y_bottom, header_x_right,
header_y_top, HeaderText, "NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
LumiLabel = TPaveLabel(topLeft_x_left, topLeft_y_bottom, topLeft_x_right,
topLeft_y_top, LumiText, "NDC")
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
NormLabel = TPaveLabel()
NormLabel.SetDrawOption("NDC")
NormLabel.SetX1NDC(topLeft_x_left)
NormLabel.SetX2NDC(topLeft_x_right)
NormLabel.SetBorderSize(0)
NormLabel.SetFillColor(0)
NormLabel.SetFillStyle(0)
NormText = ""
if arguments.normalizeToUnitArea:
NormText = "Scaled to unit area"
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas(histogramName)
Histograms = []
LegendEntries = []
colorIndex = 0
for source in input_sources: # loop over different input sources in config file
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],
source['dataset'])
inputFile = TFile(dataset_file)
NumHistogramObj = inputFile.Get("OSUAnalysis/" +
source['num_channel'] + "/" +
histogramName)
if 'condor_dir_den' in source: # If specified, take the denominator histogram from a different condor directory.
dataset_fileDen = "condor/%s/%s.root" % (source['condor_dir_den'],
source['dataset'])
inputFileDen = TFile(dataset_fileDen)
DenHistogramObj = inputFileDen.Get("OSUAnalysis/" +
source['den_channel'] + "/" +
histogramName)
else: # Default is to use the same condor directory
DenHistogramObj = inputFile.Get("OSUAnalysis/" +
source['den_channel'] + "/" +
histogramName)
if not NumHistogramObj:
print "WARNING: Could not find histogram " + source[
'num_channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
if not DenHistogramObj:
print "WARNING: Could not find histogram " + source[
'den_channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
Histogram = NumHistogramObj.Clone()
if Histogram.Class().InheritsFrom("TH2"):
Histogram.SetName(Histogram.GetName() + "__" + source['dataset'])
Histogram.SetDirectory(0)
DenHistogram = DenHistogramObj.Clone()
DenHistogram.SetDirectory(0)
inputFile.Close()
if arguments.rebinFactor:
RebinFactor = int(arguments.rebinFactor)
#don't rebin histograms which will have less than 5 bins or any gen-matching histograms
if Histogram.GetNbinsX() >= RebinFactor * 5 and Histogram.GetTitle(
).find("GenMatch") is -1 and not Histogram.Class().InheritsFrom(
"TH2"):
Histogram.Rebin(RebinFactor)
DenHistogram.Rebin(RebinFactor)
xAxisLabel = Histogram.GetXaxis().GetTitle()
unitBeginIndex = xAxisLabel.find("[")
unitEndIndex = xAxisLabel.find("]")
if unitBeginIndex is not -1 and unitEndIndex is not -1: #x axis has a unit
yAxisLabel = "#epsilon_{ " + cutName + "} (" + str(
Histogram.GetXaxis().GetBinWidth(1)
) + " " + xAxisLabel[unitBeginIndex + 1:unitEndIndex] + " width)"
else:
yAxisLabel = "#epsilon_{ " + cutName + "} (" + str(
Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if arguments.normalizeToUnitArea:
yAxisLabel = yAxisLabel + " (Unit Area Norm.)"
#Histogram = ROOT.TGraphAsymmErrors(NumHistogramObj,DenHistogramObj)
if arguments.noTGraph or Histogram.Class().InheritsFrom("TH2"):
Histogram.Divide(DenHistogram)
else:
Histogram = TGraphAsymmErrors(Histogram, DenHistogram)
if not arguments.makeFancy:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
# print splitTitle
histoTitle = splitTitle[1].lstrip(" ")
else:
histoTitle = ""
if 'color' in source:
Histogram.SetMarkerColor(colors[source['color']])
Histogram.SetLineColor(colors[source['color']])
else:
Histogram.SetMarkerColor(colors[colorList[colorIndex]])
Histogram.SetLineColor(colors[colorList[colorIndex]])
colorIndex = colorIndex + 1
if colorIndex is len(colorList):
colorIndex = 0
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
### scaling histograms as per user's specifications
for histogram in Histograms:
if arguments.normalizeToUnitArea and histogram.Integral() > 0:
histogram.Scale(1. / histogram.Integral())
### formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
Legend.AddEntry(histogram, LegendEntries[legendIndex], "LEP")
legendIndex = legendIndex + 1
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
if arguments.noTGraph:
for histogram in Histograms:
currentMax = histogram.GetMaximum() + histogram.GetBinError(
histogram.GetMaximumBin())
if (currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5 * finalMax
if finalMax is 0:
finalMax = 1
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
yAxisMin = 0.0001
if arguments.setYMin:
yAxisMin = float(arguments.setYMin)
if makeRatioPlots or makeDiffPlots:
Canvas.SetFillStyle(0)
Canvas.Divide(1, 2)
Canvas.cd(1)
gPad.SetPad(0, 0.25, 1, 1)
gPad.SetMargin(0.15, 0.05, 0.01, 0.07)
gPad.SetFillStyle(0)
gPad.Update()
gPad.Draw()
if arguments.setLogY:
gPad.SetLogy()
Canvas.cd(2)
gPad.SetPad(0, 0, 1, 0.25)
#format: gPad.SetMargin(l,r,b,t)
gPad.SetMargin(0.15, 0.05, 0.4, 0.01)
gPad.SetFillStyle(0)
gPad.SetGridy(1)
gPad.Update()
gPad.Draw()
Canvas.cd(1)
histCounter = 0
plotting_options = ""
if arguments.plot_hist:
plotting_options = "HIST"
for histogram in Histograms:
if histogram.Class().InheritsFrom("TH2"):
histogram.SetTitle(histoTitle)
histogram.Draw("colz")
DatasetName = histogram.GetName()
DatasetName = DatasetName[
DatasetName.rfind('__') +
2:] # substring starting with the last underscore
DatasetLabel = TPaveLabel(topLeft_x_left, topLeft_y_bottom,
topLeft_x_right, topLeft_y_top,
DatasetName, "NDC")
DatasetLabel.SetBorderSize(0)
DatasetLabel.SetFillColor(0)
DatasetLabel.SetFillStyle(0)
DatasetLabel.Draw()
outputFile.cd()
Canvas.SetName(histogram.GetName())
Canvas.Write()
if arguments.makeFancy:
HeaderLabel.Draw()
else:
if histogram.InheritsFrom("TGraph") and histCounter == 0:
plotting_options = "AP"
histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TGraph"):
plotting_options = "P"
histCounter = histCounter + 1
if histogram.Class().InheritsFrom("TH2"):
return
#legend coordinates, empirically determined :-)
x_left = 0.1677852
x_right = 0.9647651
y_min = 0.6765734
y_max = 0.9
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
if arguments.makeFancy:
HeaderLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
Comparison = ratioHistogram(Histograms[0], Histograms[1])
elif makeDiffPlots:
Comparison = Histograms[0].Clone("diff")
Comparison.Add(Histograms[1], -1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("hist1-hist2")
Comparison.GetXaxis().SetTitle(xAxisLabel)
Comparison.GetYaxis().CenterTitle()
Comparison.GetYaxis().SetTitleSize(0.1)
Comparison.GetYaxis().SetTitleOffset(0.5)
Comparison.GetXaxis().SetTitleSize(0.15)
Comparison.GetYaxis().SetLabelSize(0.1)
Comparison.GetXaxis().SetLabelSize(0.15)
if makeRatioPlots:
RatioYRange = 1.15
if arguments.ratioYRange:
RatioYRange = float(arguments.ratioYRange)
Comparison.GetYaxis().SetRangeUser(-1 * RatioYRange, RatioYRange)
elif makeDiffPlots:
YMax = Comparison.GetMaximum()
YMin = Comparison.GetMinimum()
if YMax <= 0 and YMin <= 0:
Comparison.GetYaxis().SetRangeUser(-1.2 * YMin, 0)
elif YMax >= 0 and YMin >= 0:
Comparison.GetYaxis().SetRangeUser(0, 1.2 * YMax)
else: #axis crosses y=0
if abs(YMax) > abs(YMin):
Comparison.GetYaxis().SetRangeUser(-1.2 * YMax, 1.2 * YMax)
else:
Comparison.GetYaxis().SetRangeUser(-1.2 * YMin, 1.2 * YMin)
Comparison.GetYaxis().SetNdivisions(205)
Comparison.Draw("E0")
outputFile.cd()
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/" + histogramName + ".pdf")
def significanceSB(cutlist, labellist):
basecut = labellist[0]
dim = len(cutlist)
significance = [0] * (dim + 1)
file = {}
tree = {}
effs = {}
hist = {}
GrAsym = {}
yErrorUp = {}
yErrorDown = {}
totEve = 0
GrAsym = TGraphAsymmErrors()
cuts = ""
for j, c in enumerate(cutlist):
s = 0.
b = 0.
cuts += cutlist[0] if j == 0 else " && " + cutlist[j]
print "cuts = ", cuts
for num1, v in enumerate(signals):
#print "Signal = ", v
for num2, filename in enumerate(samples[v]['files']):
#print "Signal rootfile read = ", filename
file[filename] = TFile(NTUPLESIG + filename + ".root",
"READ") # Read TFile
tree[filename] = file[filename].Get("Events") # Read TTree
nevents = float(sample[filename]['nevents'])
xs = float(sample[filename]['xsec']) * float(
sample[filename]['kfactor'])
LumiMC = nevents / xs
Weight = float(LUMI) / float(LumiMC)
sig_entries = tree[filename].GetEntries(cuts)
#print "s = ", float(sig_entries) * float(Weight)
s += float(sig_entries) * float(Weight)
print "TOT SIG = ", s
for num1, k in enumerate(back):
#print "backgrounds = ", k
for num2, filename in enumerate(samples[k]['files']):
#print "backgrounds rootfile read = ", filename
file[filename] = TFile(NTUPLEDIR + filename + ".root",
"READ") # Read TFile
tree[filename] = file[filename].Get("Events") # Read TTree
nevents = float(sample[filename]['nevents'])
xs = float(sample[filename]['xsec']) * float(
sample[filename]['kfactor'])
LumiMC = nevents / xs
Weight = float(LUMI) / float(LumiMC)
bkg_entries = tree[filename].GetEntries(cuts)
#print "b = ", float(bkg_entries) * float(Weight)
b += float(bkg_entries) * float(Weight)
print "TOT BKG = ", b
##End of cutlist
#COMPUTE
#print "s = ", s
#print "b = ", b
#print "sqrt(b) = ", math.sqrt(b)
#print "significance = ", float(s/math.sqrt(b))
significance[j] = float(s / math.sqrt(b))
yErrorUp[j] = float(
TEfficiency.ClopperPearson(math.sqrt(b), s, 0.68, True) -
significance[j])
yErrorDown[j] = float(
significance[j] -
TEfficiency.ClopperPearson(math.sqrt(b), s, 0.68, False))
GrAsym.SetPoint(j, j + 0.5, significance[j])
GrAsym.SetPointError(j, 0, 0, yErrorUp[j], yErrorDown[j])
for k, cs in enumerate(labellist):
GrAsym.GetHistogram().GetXaxis().Set(dim, 0, dim)
GrAsym.GetHistogram().GetXaxis().SetBinLabel(k + 1,
"%s" % labellist[k])
GrAsym.SetLineColor(2)
GrAsym.SetLineWidth(3)
GrAsym.SetMarkerStyle(8)
GrAsym.SetMarkerColor(2)
c1 = TCanvas("c1", "Signals Acceptance", 800, 600)
c1.cd()
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetTicks(1, 1)
gStyle.SetOptStat(0)
#GrAsym.SetMaximum(1.3)
#GrAsym.SetMinimum(0.)
GrAsym.GetHistogram().GetXaxis().SetTitle("")
GrAsym.GetHistogram().GetYaxis().SetTitle("Significance (S/#sqrt{B})")
GrAsym.Draw("pa")
drawCMS(LUMI, "Work In Progress")
drawRegion(basecut)
if not os.path.exists('plots/Signal/Significance/'):
os.system('mkdir -p plots/Signal/Significance/')
c1.Print("plots/Signal/Significance/Sigf_SB_" + basecut + ".png")
c1.Print("plots/Signal/Significance/Sigf_SB_" + basecut + ".pdf")
#if not options.runBash: raw_input("Press Enter to continue...")
pass
def makeBand(middleGraph, lowerGraph, upperGraph, noorder):
bandsGraph = TGraphAsymmErrors()
bandsGraph.SetName(middleGraph.GetName())
bandsGraph.SetMarkerStyle(middleGraph.GetMarkerStyle())
bandsGraph.SetMarkerColor(middleGraph.GetMarkerColor())
bandsGraph.SetLineColor(middleGraph.GetLineColor())
x1 = Double(0)
x2 = Double(0)
x3 = Double(0)
y = []
y.append(Double(0))
y.append(Double(0))
y.append(Double(0))
tmp = Double(0)
if lowerGraph.GetN() != upperGraph.GetN() or lowerGraph.GetN(
) != middleGraph.GetN():
print "Plots don't have the same number of points!"
print "Lower: ", lowerGraph.GetN()
print "Upper: ", upperGraph.GetN()
print "Middle: ", middleGraph.GetN()
return 0
#again a hack to forget about the 1st point
for iPoint in xrange(1, lowerGraph.GetN()):
middleGraph.GetPoint(iPoint, x1, y[0])
lowerGraph.GetPoint(iPoint, x1, y[1])
upperGraph.GetPoint(iPoint, x1, y[2])
if (iPoint == lowerGraph.GetN() - 1): x2 = x1
else: upperGraph.GetPoint(iPoint + 1, x2, buf)
if (iPoint == 0): x3 = x1
else: upperGraph.GetPoint(iPoint - 1, x3, buf)
tmp = Double(0)
yup = Double(0)
yce = Double(0)
ydn = Double(0)
if noorder == 0:
yce = y[0]
ydn = y[1]
yup = y[2]
elif noorder == 1:
tmp = y[2]
if y[1] < y[2]:
y[2] = y[1]
y[1] = tmp
yce = y[0]
ydn = y[1]
yup = y[2]
else:
for p in [0, 1, 2]:
for q in [0, 1, 2]:
if y[q] > y[q + 1]:
tmp = y[q + 1]
y[q + 1] = y[q]
y[q] = tmp
ydn = y[0]
yce = y[1]
yup = y[2]
bandsGraph.SetPoint(iPoint, x1, yce)
ex0 = Double(lowerGraph.GetErrorX(iPoint))
binwl = Double(0)
binwh = Double(0)
if (ex0 == 0):
binwl = (x1 - x3) / 2.
binwh = (x2 - x1) / 2.
if binwl == 0.: binwl = binwh
if binwh == 0.: binwh = binwl
else:
binwl = ex0
binwh = ex0
dxl = Double(yce - ydn)
dxh = Double(yup - yce)
if noorder == 0:
if dxl < 0:
tmp = -dxl
dxl = dxh
dxh = tmp
bandsGraph.SetPointError(iPoint, binwl, binwh, dxl, dxh)
return bandsGraph
def trigger_efficiency(year, separate=False):
from root_numpy import root2array, fill_hist
from aliases import triggers, triggers_PFHT, triggers_Jet, triggers_BTag
import numpy as np
#spec_triggers = {"PFHT": triggers_PFHT, "Jet": triggers_Jet, "BTag": triggers_BTag}
spec_triggers = {
"HT/Jet": "(" + triggers_PFHT + " || " + triggers_Jet + ")",
"BTag": triggers_BTag
}
spec_triggers_colors = {
"PFHT": 418,
"Jet": 4,
"BTag": 6,
"HT/Jet": 4,
"total": 2
}
hist_pass = TH1F("pass", "pass", 100, 0., 10000.)
if separate:
hist_pass_spec = {}
for trig in spec_triggers.keys():
hist_pass_spec[trig] = TH1F("pass_" + trig, "pass_" + trig, 100,
0., 10000.)
hist_all = TH1F("all", "all", 100, 0., 10000.)
file_list = []
data_2016_letters = ["B", "C", "D", "E", "F", "G", "H"]
data_2017_letters = ["B", "C", "D", "E", "F"]
data_2018_letters = ["A", "B", "C", "D"]
sample_names = []
if year == '2016':
letters = data_2016_letters
elif year == '2017':
letters = data_2017_letters
elif year == '2018':
letters = data_2018_letters
else:
print "unknown year"
sys.exit()
for letter in letters:
#dir_content = os.listdir(TRIGGERDIR+"/SingleMuon_{}_{}/".format(year, letter)) ## intended to run directly on ntuples
#for entry in dir_content:
# if "_flatTuple" in entry: file_list.append(TRIGGERDIR+"/SingleMuon_{}_{}/".format(year, letter)+entry)
file_list.append(TRIGGERDIR +
"/SingleMuon_{}_{}.root".format(year, letter))
print "appending:", TRIGGERDIR + "/SingleMuon_{}_{}.root".format(
year, letter)
for file_name in file_list:
temp_array = root2array(file_name,
treename='tree',
branches='jj_mass_widejet',
selection="jj_deltaEta_widejet<1.1")
fill_hist(hist_all, temp_array)
temp_array = root2array(file_name,
treename='tree',
branches='jj_mass_widejet',
selection="jj_deltaEta_widejet<1.1 && " +
triggers)
fill_hist(hist_pass, temp_array)
if separate:
for trig in spec_triggers.keys():
temp_array = root2array(
file_name,
treename='tree',
branches='jj_mass_widejet',
selection="jj_deltaEta_widejet<1.1 && " +
spec_triggers[trig])
fill_hist(hist_pass_spec[trig], temp_array)
temp_array = None
import array
from aliases import dijet_bins
binning = []
for num in dijet_bins:
if num <= 10000: binning.append(num)
#binning = range(0,1500,100)+range(1500,2000,100)+range(2000,3100,150)+range(3100,10000,300)
binning_ = array.array('d', binning)
hist_pass2 = hist_pass.Rebin(
len(binning_) - 1, "hist_pass_rebinned", binning_)
hist_all2 = hist_all.Rebin(
len(binning_) - 1, "hist_all_rebinned", binning_)
if separate:
hist_pass_spec2 = {}
for trig in spec_triggers.keys():
hist_pass_spec2[trig] = hist_pass_spec[trig].Rebin(
len(binning_) - 1, "hist_pass_" + trig + "_rebinned", binning_)
hist_pass2.Sumw2()
hist_all2.Sumw2()
eff = TGraphAsymmErrors()
eff.Divide(hist_pass2, hist_all2)
eff.SetMarkerColor(spec_triggers_colors["total"])
if separate:
eff.SetMarkerStyle(5)
else:
eff.SetMarkerStyle(1)
eff.SetLineColor(spec_triggers_colors["total"])
eff.SetLineWidth(2)
if separate:
eff_spec = {}
for trig in spec_triggers.keys():
hist_pass_spec2[trig].Sumw2()
eff_spec[trig] = TGraphAsymmErrors()
eff_spec[trig].Divide(hist_pass_spec2[trig], hist_all2)
eff_spec[trig].SetMarkerColor(spec_triggers_colors[trig])
eff_spec[trig].SetMarkerStyle(1)
eff_spec[trig].SetLineColor(spec_triggers_colors[trig])
eff_spec[trig].SetLineWidth(2)
one_line = TGraph()
one_line.SetPoint(0, 0., 1.)
one_line.SetPoint(1, 10000., 1.)
one_line.SetLineStyle(2)
c1 = TCanvas("c1", "Trigger Efficiency", 800, 800)
c1.cd(1)
eff.Draw("AP")
one_line.Draw("L")
eff.SetTitle(";m_{jj} (GeV);trigger efficiency")
eff.SetMinimum(0.)
eff.SetMaximum(1.4) #0.65
## new
dijet_bin_centers = []
for b, lthr in enumerate(dijet_bins[:-1]):
if lthr < 1200 or lthr > 2500: continue
dijet_bin_centers.append(0.5 * (dijet_bins[b] + dijet_bins[b + 1]))
print "total trigger efficiency:"
for cval in dijet_bin_centers:
print cval, ":", eff.Eval(cval)
## end new
if separate:
leg = TLegend(0.65, 0.75, 0.9, 0.95)
leg.AddEntry(eff, "total")
for trig in spec_triggers.keys():
leg.AddEntry(eff_spec[trig], trig + "-based")
eff_spec[trig].Draw("P SAME")
## new
print trig, "trigger efficiency"
for cval in dijet_bin_centers:
print cval, ":", eff_spec[trig].Eval(cval)
## end new
leg.Draw()
eff.GetXaxis().SetTitleSize(0.045)
eff.GetYaxis().SetTitleSize(0.045)
eff.GetYaxis().SetTitleOffset(1.1)
eff.GetXaxis().SetTitleOffset(1.05)
eff.GetXaxis().SetLimits(700., 5000.)
c1.SetTopMargin(0.05)
#drawCMS(-1, "Preliminary", year=year) #Preliminary
#drawCMS(-1, "Work in Progress", year=year, suppressCMS=True)
drawCMS(-1, "", year=year, suppressCMS=True)
drawAnalysis("")
suffix = ""
if separate: suffix = "_sep"
c1.Print("plots/Efficiency/trigger_" + year + suffix + ".pdf")
c1.Print("plots/Efficiency/trigger_" + year + suffix + ".png")
def getGraph(self,dset):
from array import array
from ROOT import TMultiGraph, TLegend, TGraphAsymmErrors
n = len(self.__x)
if n != len(self.__y) or n != len(self.__yErrLow) or n != len(self.__yErrHigh):
raise StandardError, "The length of the x(%s), y(%s) and y error(%s,%s) lists does not match"%(len(self.__x), len(self.__y), len(self.__yErrLow), len(self.__yErrHigh))
result = TMultiGraph()
legendPosition = [float(i) for i in self.__getStyleOption("legendPosition").split()]
legend = TLegend(*legendPosition)
legend.SetFillColor(0)
result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
#(refArrays, refLabel) = self.__getRefernceGraphArrays()
#refGraph = TGraphAsymmErrors(*refArrays)
#refGraph.SetLineWidth(2)
#refGraph.SetLineColor(int(self.__config.get("reference","lineColor")))
#refGraph.SetFillColor(int(self.__config.get("reference","fillColor")))
#result.Add(refGraph,"L3")
#legend.AddEntry(refGraph,self.__config.get("reference","name"))
xErr = array("d",[0 for i in range(n)])
print "__x = ", self.__x
print "__y = ", self.__y
lst = []
for inc in range (0,n):
d={}
d['run']=self.__runs[inc]
d['x']=self.__x[inc]
d['y']=self.__y[inc]
d['yErr']=self.__yErrLow[inc]
d['yTitle']=self.__yTitle
if self.__config.has_option(self.__section,"yMin") and self.__config.has_option(self.__section,"yMax") :
d['ymin']=float(self.__config.get(self.__section,"yMin"))
d['ymax']=float(self.__config.get(self.__section,"yMax"))
else:
d['ymin']=0
d['ymax']=0
lst.append(d)
obj ={}
obj[self.__title]=lst
#finalObj[self.__title]=lst
#finalList.append(finalObj)
# save_path = './JSON_A/'
#completeName = os.path.join(save_path, self.__title+".json")
if not os.path.exists("JSON_RECO"):
os.makedirs("JSON_RECO")
if not os.path.exists("JSON_RECO/"+dset):
os.makedirs("JSON_RECO/"+dset)
with open("./JSON_RECO/"+dset+"/"+self.__title+".json", 'w') as outfile:
json.dump(obj, outfile,indent=4)
print json.dumps(obj,indent=2)
graph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__yErrLow,self.__yErrHigh)
graph.SetLineWidth(2)
graph.SetFillColor(0)
graph.SetLineColor(int(self.__getStyleOption("lineColor")))
graph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
graph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
graph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
sysGraph = TGraphAsymmErrors(n, self.__x, self.__y, xErr, xErr, self.__ySysErrLow,self.__ySysErrHigh)
sysGraph.SetLineWidth(1)
sysGraph.SetFillColor(0)
sysGraph.SetLineColor(int(self.__getStyleOption("lineColor")))
sysGraph.SetMarkerColor(int(self.__getStyleOption("markerColor")))
sysGraph.SetMarkerStyle(int(self.__getStyleOption("markerStyle")))
sysGraph.SetMarkerSize(float(self.__getStyleOption("markerSize")))
#TOMAS removed sys error from the plot
#result.Add(sysGraph,"[]")
result.Add(graph,"P")
# result.SetName("MultiPlots")
# result.SetTitle("%s;%s;%s"%(self.__title,self.__xTitle,self.__yTitle))
result.SetName("MG_%s"%(self.__title))
legend.AddEntry(graph, self.__getStyleOption("name"))
#for (x,y,yErr) in zip(self.__x, self.__y, zip(self.__yErrLow,self.__yErrHigh)):
# self.__addAnnotaion("hallo",x,y,yErr)
return (result, legend)
def doit():
frame = h.ProfileX(hname + "_frame", 1, -1, "s")
gr1 = TGraphAsymmErrors(h.GetNbinsX())
gr2 = TGraphAsymmErrors(h.GetNbinsX())
gr1_aspt = TGraphAsymmErrors(h.GetNbinsX())
gr2_aspt = TGraphAsymmErrors(h.GetNbinsX())
# Apply gaussian fits
for i in xrange(h.GetNbinsX()):
h_py = h.ProjectionY("_py", i + 1, i + 1)
if 50 <= i <= 60: # high pT, not enough entries (300 bins -> 150)
h_py.Rebin(2)
elif i >= 78: # low pT, resolution affected by finite bin width
h_py = h.ProjectionY("_py", i + 1,
i + 2) # merge i & (i+1) entries
if i == 82: # even lower pT, resolution affected by finite bin width
h_py = h.ProjectionY("_py", i + 1,
i + 4) # merge i & (i+4) entries
elif i >= 82:
continue
if h_py.Integral() < 20: continue
r = h_py.Fit("gaus", "SNQ", "", -1, 1.2)
#r = h_py.Fit("gaus", "SNQ", "", h_py.GetMean() - 0.04*5, h_py.GetMean() + 0.04*5)
mean, sigma, meanErr, sigmaErr = r.Parameter(1), r.Parameter(
2), r.ParError(1), r.ParError(2)
gr1.SetPoint(i, h.GetXaxis().GetBinCenter(i + 1), mean)
gr1.SetPointError(i, 0, 0, sigma, sigma)
gr2.SetPoint(i, h.GetXaxis().GetBinCenter(i + 1), sigma)
gr2.SetPointError(i, 0, 0, sigmaErr, sigmaErr)
gr1_aspt.SetPoint(i, 1.0 / h.GetXaxis().GetBinCenter(i + 1), mean)
gr1_aspt.SetPointError(i, 0, 0, sigma, sigma)
gr2_aspt.SetPoint(i, 1.0 / h.GetXaxis().GetBinCenter(i + 1), sigma)
gr2_aspt.SetPointError(i, 0, 0, sigmaErr, sigmaErr)
# Draw
h.Draw("COLZ")
gPad.SetLogx(0)
#draw_cms_lumi()
#gPad.Print("figures_perf/" + hname + "_omtf" + ".png")
#gPad.Print("figures_perf/" + hname + "_omtf" + ".pdf")
#
frame.Reset()
frame.SetBins(50, 0, 50)
frame.GetXaxis().SetTitle("gen p_{T} [GeV]")
frame.GetYaxis().SetTitle("#Delta(p_{T})/p_{T} bias")
frame.SetMaximum(0.5)
frame.SetMinimum(-0.5)
frame.SetStats(0)
frame.Draw()
gr1_aspt.SetLineColor(col)
gr1_aspt.SetMarkerColor(col)
gr1_aspt.Draw("p")
gPad.SetLogx()
draw_cms_lumi()
gPad.Print("figures_perf/" + hname + "_bias" + "_omtf" + ".png")
gPad.Print("figures_perf/" + hname + "_bias" + "_omtf" + ".pdf")
#
frame.GetXaxis().SetTitle("gen p_{T} [GeV]")
frame.GetYaxis().SetTitle("#Delta(p_{T})/p_{T} resolution")
frame.SetMaximum(0.6)
frame.SetMinimum(0.0)
frame.SetStats(0)
frame.Draw()
gr2_aspt.SetLineColor(col)
gr2_aspt.SetMarkerColor(col)
gr2_aspt.Draw("p")
#gr2_aspt.Fit("pol1", "", "", 10, 40)
gPad.SetLogx()
draw_cms_lumi()
gPad.Print("figures_perf/" + hname + "_res" + "_omtf" + ".png")
gPad.Print("figures_perf/" + hname + "_res" + "_omtf" + ".pdf")
#
h.cache = [frame, gr1, gr2, gr1_aspt, gr2_aspt]
def plotDataOverMCEff(hist_mc_tight,
hist_mc_loose,
hist_data_tight,
hist_data_loose,
plot_name='fakerate.pdf'):
g = TGraphAsymmErrors(hist_mc_tight)
g.Divide(hist_mc_tight, hist_mc_loose)
g.GetYaxis().SetTitle('Fake rate')
g.GetXaxis().SetTitle(hist_mc_tight.GetXaxis().GetTitle())
g.GetYaxis().SetTitleOffset(1.2)
g.GetYaxis().SetTitleOffset(1.3)
g.SetLineColor(2)
g.SetMarkerColor(2)
g_data = TGraphAsymmErrors(hist_data_tight)
g_data.Divide(hist_data_tight, hist_data_loose)
g_data.GetYaxis().SetTitle('Fake rate')
g_data.GetXaxis().SetTitle(hist_data_tight.GetXaxis().GetTitle())
g_data.GetYaxis().SetTitleOffset(1.2)
g_data.GetYaxis().SetTitleOffset(1.3)
g_data.SetMarkerColor(1)
g_vals = g.GetY()
g_data_vals = g_data.GetY()
g_ratio = g_data.Clone('ratio')
for i in xrange(g_data.GetN()):
ratio = g_data_vals[i] / g_vals[i] if g_vals[i] else 0.
g_ratio.SetPoint(i, g.GetX()[i], ratio)
rel_y_low = math.sqrt((g_data.GetErrorYlow(i) / g_data_vals[i])**2 + (
g.GetErrorYlow(i) /
g_vals[i])**2) if g_data_vals[i] > 0. and g_vals[i] > 0. else 0.
g_ratio.SetPointEYlow(i, rel_y_low * ratio)
rel_y_high = math.sqrt(
(g_data.GetErrorYhigh(i) / g_data_vals[i])**2 +
(g.GetErrorYhigh(i) /
g_vals[i])**2) if g_data_vals[i] > 0. and g_vals[i] > 0. else 0.
g_ratio.SetPointEYhigh(i, rel_y_high * ratio)
# Gymnastics to get same label sizes etc in ratio and main plot
ytp_ratio = 2.
xtp_ratio = 2.
# hr.GetYaxis().SetNdivisions(4)
g_ratio.GetYaxis().SetTitleSize(g.GetYaxis().GetTitleSize() * xtp_ratio)
g_ratio.GetXaxis().SetTitleSize(g.GetXaxis().GetTitleSize() * ytp_ratio)
g_ratio.GetYaxis().SetTitleOffset(g.GetYaxis().GetTitleOffset() /
xtp_ratio)
g_ratio.GetXaxis().SetTitleOffset(
g.GetXaxis().GetTitleOffset()) # / ytp_ratio)
g_ratio.GetYaxis().SetLabelSize(g.GetYaxis().GetLabelSize() * xtp_ratio)
g_ratio.GetXaxis().SetLabelSize(g.GetXaxis().GetLabelSize() * ytp_ratio)
g_data.GetXaxis().SetLabelColor(0)
g_data.GetXaxis().SetLabelSize(0)
g.GetXaxis().SetLabelColor(0)
g.GetXaxis().SetLabelSize(0)
g_ratio.GetXaxis().SetTitle(g.GetXaxis().GetTitle())
# maxy = 1.1 * min(g.GetMaximum(), g_data.GetMaximum(), 0.2)
g.GetYaxis().SetRangeUser(0.001, 0.2)
cv, pad, padr = HistDrawer.buildCanvas()
pad.cd()
g.Draw('AP')
g_data.Draw('P')
legend = TLegend(0.23, 0.73, 0.43, 0.91)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetLineColor(0)
legend.SetLineWidth(0)
legend.AddEntry(g.GetName(), 'MC', 'lep')
legend.AddEntry(g_data.GetName(), 'Observed', 'lep')
legend.Draw()
padr.cd()
g_ratio.GetYaxis().SetRangeUser(0.51, 1.49)
g_ratio.GetYaxis().SetTitle('Obs/MC')
g_ratio.Draw('AP')
drawRatioLines(g_ratio)
cv.Print(plot_name)
ey_hi_ele = grEle.GetErrorYhigh(i)
if y_mu < 1.e-9 or y_ele < 1.e-9:
ey_hi_ratio = 0.0
else:
ey_hi_ratio = y_ratio * math.hypot(ey_hi_mu / y_mu, ey_hi_ele / y_ele)
grRatio.SetPoint(i, x, y_ratio)
grRatio.SetPointEXlow(i, ex_lo)
grRatio.SetPointEXhigh(i, ex_hi)
grRatio.SetPointEYlow(i, ey_lo_ratio)
grRatio.SetPointEYhigh(i, ey_hi_ratio)
if True:
grRatio.SetMarkerStyle(20)
grRatio.SetMarkerSize(1.5)
grRatio.SetMarkerColor(1)
grRatio.SetLineStyle(1)
grRatio.SetLineColor(1)
grRatio.SetLineWidth(1)
grRatio.GetXaxis().SetLabelSize(0.04)
grRatio.GetXaxis().SetTitleSize(0.04)
grRatio.GetXaxis().SetTitleOffset(1.25)
grRatio.GetYaxis().SetLabelSize(0.04)
grRatio.GetYaxis().SetTitleSize(0.04)
grRatio.GetYaxis().SetTitleOffset(1.5)
# grRatio.GetYaxis().SetRangeUser(ylo, yhi)
grRatio.Draw("ALP")
print rates
gr_denom = TGraphAsymmErrors(len(rates))
gr_numer = TGraphAsymmErrors(len(rates))
for i, x in enumerate(rates):
pu, emtf_rate, emtf_rate_err, emtf2026_rate, emtf2026_rate_err = x
gr_denom.SetPoint(i, pu, emtf_rate)
gr_denom.SetPointError(i, 0, 0, emtf_rate_err, emtf_rate_err)
gr_numer.SetPoint(i, pu, emtf2026_rate)
gr_numer.SetPointError(i, 0, 0, emtf2026_rate_err, emtf2026_rate_err)
gr_denom.SetMarkerStyle(20)
gr_denom.SetMarkerSize(1.4)
gr_denom.SetMarkerColor(632) # kRed
gr_denom.SetLineWidth(2)
gr_denom.SetLineColor(632) # kRed
gr_numer.SetMarkerStyle(20)
gr_numer.SetMarkerSize(1.4)
gr_numer.SetMarkerColor(600) # kBlue
gr_numer.SetLineWidth(2)
gr_numer.SetLineColor(600) # kBlue
frame = TH1F("frame", "; PU; Trigger rate [kHz]", 100, 0, 350)
frame.SetMinimum(0)
frame.SetMaximum(25)
frame.Draw()
#gr_denom.Draw("P")
def pullsVertical_noBonly(fileName):
content = filterPullFile(fileName)
nbins, off = len(content), 0.10
# Graphs
h_pulls = TH2F("pulls", "", 6, -3., 3., nbins, 0, nbins)
S_pulls = TGraphAsymmErrors(nbins)
boxes = []
canvas = TCanvas("canvas", "Pulls", 720, 300 + nbins * 18) #nbins*20)
canvas.cd()
canvas.SetGrid(0, 1)
canvas.SetTopMargin(0.01)
canvas.SetRightMargin(0.01)
canvas.SetBottomMargin(0.10)
canvas.SetLeftMargin(0.40)
canvas.SetTicks(1, 1)
for i, s in enumerate(content):
l = s.split()
h_pulls.GetYaxis().SetBinLabel(i + 1, l[0])
S_pulls.SetPoint(i, float(l[3]), float(i + 1) - 0.5)
S_pulls.SetPointError(i, float(l[4]), float(l[4]), 0., 0.)
h_pulls.GetXaxis().SetTitle("(#hat{#theta} - #theta_{0}) / #Delta#theta")
h_pulls.GetXaxis().SetLabelOffset(0.0)
h_pulls.GetXaxis().SetTitleOffset(0.8)
h_pulls.GetXaxis().SetLabelSize(0.045)
h_pulls.GetXaxis().SetTitleSize(0.050)
h_pulls.GetYaxis().SetLabelSize(0.046)
h_pulls.GetYaxis().SetNdivisions(nbins, 0, 0)
S_pulls.SetFillColor(kBlack)
S_pulls.SetLineColor(kBlack)
S_pulls.SetMarkerColor(kBlack)
S_pulls.SetLineWidth(2)
S_pulls.SetMarkerStyle(20)
S_pulls.SetMarkerSize(1)
box1 = TBox(-1., 0., 1., nbins)
#box1.SetFillStyle(3001) # 3001 checkered
#box1.SetFillStyle(0)
box1.SetFillColor(kGreen + 1) # 417
box1.SetLineWidth(2)
box1.SetLineStyle(2)
box1.SetLineColor(kGreen + 1) # 417
box2 = TBox(-2., 0., 2., nbins)
#box2.SetFillStyle(3001) # 3001 checkered
#box2.SetFillStyle(0)
box2.SetFillColor(kOrange) # 800
box2.SetLineWidth(2)
box2.SetLineStyle(2)
box2.SetLineColor(kOrange) # 800
leg = TLegend(0.01, 0.01, 0.3, 0.15)
leg.SetTextSize(0.05)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetFillColor(0)
#leg.SetNColumns(2)
leg.AddEntry(S_pulls, "S+B fit", "lp")
if text: leg.AddEntry(0, text, "")
h_pulls.Draw("")
box2.Draw()
box1.Draw()
S_pulls.Draw("P6SAME")
leg.Draw()
canvas.RedrawAxis()
canvas.Print(outName + ".png")
canvas.Print(outName + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
def draw_geff(target_dir,
c_title,
ext,
t,
title,
h_name,
h_bins,
to_draw,
denom_cut,
extra_num_cut,
opt,
color,
marker_st=1,
marker_sz=1):
c = TCanvas("c", "c", 600, 600)
c.Clear()
gPad.SetGrid(1)
gStyle.SetStatStyle(0)
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
t.Draw(to_draw + ">>num_" + h_name + h_bins, extra_num_cut + denom_cut,
"goff")
num = TH1F(gDirectory.Get("num_" + h_name))
if not num:
sys.exit('num does not exist')
num = TH1F(num.Clone("eff_" + h_name))
t.Draw(to_draw + ">>denom_" + h_name + h_bins, denom_cut, "goff")
den = TH1F(gDirectory.Get("denom_" + h_name).Clone("denom_" + h_name))
eff = TGraphAsymmErrors(num, den)
if not "same" in opt:
num.Reset()
num.GetYaxis().SetRangeUser(0., 1.05)
num.SetStats(0)
num.SetTitle(title)
num.Draw()
eff.SetLineWidth(2)
eff.SetLineColor(color)
eff.SetMarkerStyle(marker_st)
eff.SetMarkerColor(color)
eff.SetMarkerSize(marker_sz)
eff.Draw(opt + " same")
## Do fit in the flat region
if "eta" in c_title:
xmin = eta_min
xmax = eta_max
else:
xmin = -999.
xmax = 999.
f1 = TF1("fit1", "pol0", xmin, xmax)
r = eff.Fit("fit1", "RQS")
ptstats = TPaveStats(0.25, 0.35, 0.75, 0.55, "brNDC")
ptstats.SetName("stats")
ptstats.SetBorderSize(0)
ptstats.SetLineWidth(0)
ptstats.SetFillColor(0)
ptstats.SetTextAlign(11)
ptstats.SetTextFont(42)
ptstats.SetTextSize(.05)
ptstats.SetTextColor(kRed)
ptstats.SetOptStat(0)
ptstats.SetOptFit(1111)
chi2 = int(r.Chi2())
ndf = int(r.Ndf())
## prob = r.Prob()
round(2.675, 2)
p0 = f1.GetParameter(0)
p0e = f1.GetParError(0)
ptstats.AddText("#chi^{2} / ndf: %d/%d" % (chi2, ndf))
## ptstats.AddText("Fit probability: %f %" %(prob))
ptstats.AddText("Efficiency: %f #pm %f %%" % (p0, p0e))
ptstats.Draw("same")
pt = TPaveText(0.09899329, 0.9178322, 0.8993289, 0.9737762, "blNDC")
pt.SetName("title")
pt.SetBorderSize(1)
pt.SetFillColor(0)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.AddText(eff.GetTitle())
pt.Draw("same")
c.Modified()
c.SaveAs(target_dir + c_title + ext)
##Prepare the canvas to plot the scan for SL1_L1
can_scan_SL1_L1 = TCanvas("can_scan_SL1_L1","can_scan_SL1_L1", 1000, 800)
can_scan_SL1_L1.SetGrid()
can_scan_SL1_L1.cd()
##Prepare summary TGraph
graph = TGraphAsymmErrors()
n=0
for a in sorted(threshold_scan):
#for a in sorted(run_parameters):
##Fill the TGraph with threshold (x-axis) and rate (y-axis)
#######graph.SetPoint(n,int(run_parameters[a]['VTHR']),float(run_parameters[a]['RATE_SL1_L1']))
graph.SetPoint(n,int(a),float(threshold_scan[a]))
n = n+1
graph.SetMarkerSize(1.)
graph.SetMarkerStyle(21)
graph.SetMarkerColor(862)
graph.SetFillColor(868)
graph.SetFillStyle(3844)
graph.SetLineColor(868)
graph.SetLineWidth(2)
graph.SetLineStyle(2)
graph.GetXaxis().SetTitle("threshold [mV]")
graph.GetYaxis().SetTitleOffset(1.2)
graph.GetYaxis().SetTitle("rate [kHz]")
graph.Draw("APL")
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
latex.SetTextColor(1)
latex.SetTextFont(42)
latex.SetTextAlign(33)
def limit(channel, signal):
multF = 1. # in fb
filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt"
if (options.mediator == 'SC'):
filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_scalar" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt"
elif (options.mediator == 'PS'):
filename = "./limitOutput_" + options.name + "/" + signal + "_MChi1_MPhi%d_pseudo" + options.bjets + "_" + channel + "_AsymptoticLimits_grepOutput.txt"
else:
print 'WRONG mediator type'
mass, val = fillValues(filename)
Obs0s = TGraph()
Exp0s = TGraph()
Exp1s = TGraphAsymmErrors()
Exp2s = TGraphAsymmErrors()
Sign = TGraph()
pVal = TGraph()
Best = TGraphAsymmErrors()
for i, m in enumerate(mass):
if not m in val:
print "Key Error:", m, "not in value map"
continue
n = Exp0s.GetN()
Obs0s.SetPoint(n, m, val[m][0] * multF)
Exp0s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPoint(n, m, val[m][3] * multF)
Exp1s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][2] * multF,
val[m][4] * multF - val[m][3] * multF)
Exp2s.SetPoint(n, m, val[m][3] * multF)
Exp2s.SetPointError(n, 0., 0., val[m][3] * multF - val[m][1] * multF,
val[m][5] * multF - val[m][3] * multF)
#Sign.SetPoint(n, m, val[m][6])
#pVal.SetPoint(n, m, val[m][7])
#Best.SetPoint(n, m, val[m][8])
#Best.SetPointError(m, 0., 0., abs(val[m][9]), abs(val[m][10]))
Exp2s.SetLineWidth(2)
Exp2s.SetLineStyle(1)
Obs0s.SetLineWidth(3)
Obs0s.SetMarkerStyle(0)
Obs0s.SetLineColor(1)
Exp0s.SetLineStyle(2)
Exp0s.SetLineWidth(3)
Exp1s.SetFillColor(417) #kGreen+1
Exp1s.SetLineColor(417) #kGreen+1
Exp2s.SetFillColor(800) #kOrange
Exp2s.SetLineColor(800) #kOrange
Exp2s.GetXaxis().SetTitle("m_{#phi} (GeV)")
Exp2s.GetXaxis().SetTitleSize(Exp2s.GetXaxis().GetTitleSize() * 1.25)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetTitle("#sigma/#sigma_{th}")
Exp2s.GetYaxis().SetTitleOffset(1.5)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetMoreLogLabels()
Sign.SetLineWidth(2)
Sign.SetLineColor(629)
Sign.GetXaxis().SetTitle("m_{#phi} (GeV)")
Sign.GetXaxis().SetTitleSize(Sign.GetXaxis().GetTitleSize() * 1.1)
Sign.GetYaxis().SetTitle("Significance")
pVal.SetLineWidth(2)
pVal.SetLineColor(629)
pVal.GetXaxis().SetTitle("m_{#phi} (GeV)")
pVal.GetXaxis().SetTitleSize(pVal.GetXaxis().GetTitleSize() * 1.1)
pVal.GetYaxis().SetTitle("local p-Value")
Best.SetLineWidth(2)
Best.SetLineColor(629)
Best.SetFillColor(629)
Best.SetFillStyle(3003)
Best.GetXaxis().SetTitle("m_{#phi} (GeV)")
Best.GetXaxis().SetTitleSize(Best.GetXaxis().GetTitleSize() * 1.1)
Best.GetYaxis().SetTitle("Best Fit (pb)")
c1 = TCanvas("c1", "Exclusion Limits", 800, 600)
c1.cd()
#SetPad(c1.GetPad(0))
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetTicks(1, 1)
#c1.GetPad(0).SetGridx()
#c1.GetPad(0).SetGridy()
c1.GetPad(0).SetLogx()
c1.GetPad(0).SetLogy()
Exp2s.Draw("A3")
Exp1s.Draw("SAME, 3")
Exp0s.Draw("SAME, L")
if not options.blind: Obs0s.Draw("SAME, L")
#Theory[0].Draw("SAME, L")
#Theory[1].Draw("SAME, L")
#setHistStyle(Exp2s)
Exp2s.GetXaxis().SetTitleSize(0.045)
Exp2s.GetXaxis().SetMoreLogLabels(True)
Exp2s.GetXaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetTitleSize(0.04)
Exp2s.GetXaxis().SetLabelSize(0.04)
Exp2s.GetYaxis().SetLabelSize(0.04)
Exp2s.GetXaxis().SetTitleOffset(1)
Exp2s.GetYaxis().SetTitleOffset(1.25)
Exp2s.GetYaxis().SetMoreLogLabels(True)
Exp2s.GetYaxis().SetNoExponent(True)
Exp2s.GetYaxis().SetRangeUser(0.1, 1000.)
#else: Exp2s.GetYaxis().SetRangeUser(0.1, 1.e2)
Exp2s.GetXaxis().SetRangeUser(mass[0], mass[-1])
drawAnalysis("tDM")
drawRegion(channel, True)
drawCMS(LUMI, "Preliminary")
if True:
if (options.mediator == 'SC'):
massT, valT = fillValues("./limitOutput_" + options.name + "/" +
signal.replace('tttDM', 'tDM') +
"_MChi1_MPhi%d_scalar" + options.bjets +
"_" + channel +
"_AsymptoticLimits_grepOutput.txt")
elif (options.mediator == 'PS'):
massT, valT = fillValues("./limitOutput_" + options.name + "/" +
signal.replace('tttDM', 'tDM') +
"_MChi1_MPhi%d_pseudo" + options.bjets +
"_" + channel +
"_AsymptoticLimits_grepOutput.txt")
ExpT, ObsT = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(massT):
if not m in val: continue
ExpT.SetPoint(ExpT.GetN(), m, valT[m][3] * multF)
ObsT.SetPoint(ObsT.GetN(), m, valT[m][0] * multF)
ExpT.SetLineWidth(3)
ExpT.SetLineColor(602) #602
ExpT.SetLineStyle(5)
ObsT.SetLineWidth(3)
ObsT.SetLineColor(602)
ExpT.SetMarkerStyle(21)
ObsT.SetMarkerStyle(22)
ExpT.SetMarkerColor(602)
ObsT.SetMarkerColor(602)
ExpT.Draw("SAME, PC")
#if not options.blind: ObsT.Draw("SAME, P")
if (options.mediator == 'SC'):
massTTT, valTTT = fillValues("./limitOutput_" + options.name +
"/" +
signal.replace('tttDM', 'ttDM') +
"_MChi1_MPhi%d_scalar" +
options.bjets + "_" + channel +
"_AsymptoticLimits_grepOutput.txt")
elif (options.mediator == 'PS'):
massTTT, valTTT = fillValues("./limitOutput_" + options.name +
"/" +
signal.replace('tttDM', 'ttDM') +
"_MChi1_MPhi%d_pseudo" +
options.bjets + "_" + channel +
"_AsymptoticLimits_grepOutput.txt")
ExpTTT, ObsTTT = TGraphAsymmErrors(), TGraphAsymmErrors()
for i, m in enumerate(massTTT):
if not m in val: continue
ExpTTT.SetPoint(ExpTTT.GetN(), m, valTTT[m][3] * multF)
ObsTTT.SetPoint(ObsTTT.GetN(), m, valTTT[m][0] * multF)
ExpTTT.SetLineWidth(3)
ExpTTT.SetLineColor(634) #602
ExpTTT.SetLineStyle(5)
ObsTTT.SetLineWidth(3)
ObsTTT.SetLineColor(634)
ExpTTT.SetMarkerStyle(21)
ObsTTT.SetMarkerStyle(22)
ExpTTT.SetMarkerColor(634)
ObsTTT.SetMarkerColor(634)
ExpTTT.Draw("SAME, PC")
#if not options.blind: ObsTTT.Draw("SAME, P")
# legend
top = 0.9
nitems = 4 + 2
leg = TLegend(0.55, top - nitems * 0.3 / 5., 0.95, top)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL limits")
leg.AddEntry(Obs0s, "Observed", "l")
leg.AddEntry(Exp0s, "Expected (t+DM, tt+DM)", "l")
leg.AddEntry(Exp1s, "#pm 1 s. d.", "f")
leg.AddEntry(Exp2s, "#pm 2 s. d.", "f")
if True:
leg.AddEntry(ExpT, "Expected (t+DM)", "p")
leg.AddEntry(ExpTTT, "Expected (tt+DM)", "p")
leg.Draw()
c1.GetPad(0).RedrawAxis()
c1.GetPad(0).Update()
if gROOT.IsBatch():
c1.Print("plotsLimit_" + options.name + "/Exclusion_" + channel + "_" +
options.mediator + "_" + options.bjets + ".png")
c1.Print("plotsLimit_" + options.name + "/Exclusion_" + channel + "_" +
options.mediator + "_" + options.bjets + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
# print "p1s[",
# for i in range(Exp0s.GetN()):
# print Exp0s.GetY()[i]+Exp1s.GetErrorYhigh(i), ",",
# print "],"
# print "m1s[",
# for i in range(Exp0s.GetN()):
# print Exp0s.GetY()[i]-Exp1s.GetErrorYlow(i), ",",
# print "],"
# print "[",
# for i in range(Exp0s.GetN()):
# print Exp0s.GetY()[i], ",",
# print "]"
return
# ---------- Significance ----------
c2 = TCanvas("c2", "Significance", 800, 600)
c2.cd()
c2.GetPad(0).SetTopMargin(0.06)
c2.GetPad(0).SetRightMargin(0.05)
c2.GetPad(0).SetTicks(1, 1)
c2.GetPad(0).SetGridx()
c2.GetPad(0).SetGridy()
Sign.GetYaxis().SetRangeUser(0., 5.)
Sign.Draw("AL3")
drawCMS(LUMI, "Preliminary")
drawAnalysis(channel[1:3])
if gROOT.IsBatch():
c2.Print("plotsLimit_" + options.name + "/Significance/" + channel +
"_" + options.mediator + "_" + options.bjets + ".png")
c2.Print("plotsLimit_" + options.name + "/Significance/" + channel +
"_" + options.mediator + "_" + options.bjets + ".pdf")
# c2.Print("plotsLimit/Significance/"+channel+suffix+".root")
# c2.Print("plotsLimit/Significance/"+channel+suffix+".C")
# ---------- p-Value ----------
c3 = TCanvas("c3", "p-Value", 800, 600)
c3.cd()
c3.GetPad(0).SetTopMargin(0.06)
c3.GetPad(0).SetRightMargin(0.05)
c3.GetPad(0).SetTicks(1, 1)
c3.GetPad(0).SetGridx()
c3.GetPad(0).SetGridy()
c3.GetPad(0).SetLogy()
pVal.Draw("AL3")
pVal.GetYaxis().SetRangeUser(2.e-7, 0.5)
ci = [
1., 0.317310508, 0.045500264, 0.002699796, 0.00006334, 0.000000573303,
0.000000001973
]
line = TLine()
line.SetLineColor(922)
line.SetLineStyle(7)
text = TLatex()
text.SetTextColor(922)
text.SetTextSize(0.025)
text.SetTextAlign(12)
for i in range(1, len(ci) - 1):
line.DrawLine(pVal.GetXaxis().GetXmin(), ci[i] / 2,
pVal.GetXaxis().GetXmax(), ci[i] / 2)
text.DrawLatex(pVal.GetXaxis().GetXmax() * 1.01, ci[i] / 2,
"%d #sigma" % i)
drawCMS(LUMI, "Preliminary")
drawAnalysis(channel[1:3])
if gROOT.IsBatch():
c3.Print("plotsLimit_" + options.name + "/pValue/" + channel + suffix +
"_" + options.mediator + "_" + options.bjets + ".png")
c3.Print("plotsLimit_" + options.name + "/pValue/" + channel + suffix +
"_" + options.mediator + "_" + options.bjets + ".pdf")
# c3.Print("plotsLimit/pValue/"+channel+suffix+".root")
# c3.Print("plotsLimit/pValue/"+channel+suffix+".C")
# --------- Best Fit ----------
c4 = TCanvas("c4", "Best Fit", 800, 600)
c4.cd()
c4.GetPad(0).SetTopMargin(0.06)
c4.GetPad(0).SetRightMargin(0.05)
c4.GetPad(0).SetTicks(1, 1)
c4.GetPad(0).SetGridx()
c4.GetPad(0).SetGridy()
Best.Draw("AL3")
drawCMS(LUMI, "Preliminary")
drawAnalysis(channel[1:3])
if gROOT.IsBatch():
c4.Print("plotsLimit_" + options.name + "/BestFit/" + channel +
suffix + "_" + options.mediator + "_" + options.bjets +
".png")
c4.Print("plotsLimit_" + options.name + "/BestFit/" + channel +
suffix + "_" + options.mediator + "_" + options.bjets +
".pdf")
# c4.Print("plotsLimit/BestFit/"+channel+suffix+".root")
# c4.Print("plotsLimit/BestFit/"+channel+suffix+".C")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
can_HV_scan_SL1_L1 = TCanvas("can_HV_scan_SL1_L1", "can_HV_scan_SL1_L1", 1000,
800)
can_HV_scan_SL1_L1.SetGrid()
can_HV_scan_SL1_L1.cd()
##Prepare summary TGraph
graph_HV_L1 = TGraphAsymmErrors()
n = 0
for a in sorted(HV_scan_L1):
#for a in sorted(run_parameters):
##Fill the TGraph with threshold (x-axis) and rate (y-axis)
#######graph.SetPoint(n,int(run_parameters[a]['VTHR']),float(run_parameters[a]['RATE_SL1_L1']))
graph_HV_L1.SetPoint(n, int(a), float(HV_scan_L1[a]))
n = n + 1
graph_HV_L1.SetMarkerSize(1.)
graph_HV_L1.SetMarkerStyle(21)
graph_HV_L1.SetMarkerColor(418)
graph_HV_L1.SetFillColor(868)
graph_HV_L1.SetFillStyle(3844)
graph_HV_L1.SetLineColor(418 - 1)
graph_HV_L1.SetLineWidth(2)
graph_HV_L1.SetLineStyle(2)
graph_HV_L1.GetXaxis().SetTitle("HV [V]")
graph_HV_L1.GetYaxis().SetTitleOffset(1.2)
graph_HV_L1.GetYaxis().SetTitle("efficiency")
graph_HV_L1.GetYaxis().SetRangeUser(0, 1.01)
graph_HV_L1.Draw("APL")
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
latex.SetTextColor(1)
latex.SetTextFont(42)
def pullsVertical(fileName):
content = filterPullFile(fileName)
nbins, off = len(content), 0.10
b_pulls = TH1F("b_pulls", ";;Pulls", nbins, 0. - off, nbins - off)
s_pulls = TH1F("s_pulls", ";;Pulls", nbins, 0. + off, nbins + off) #
for i, s in enumerate(content):
l = s.split()
b_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
s_pulls.GetXaxis().SetBinLabel(i + 1, l[0])
b_pulls.SetBinContent(i + 1, float(l[1]))
b_pulls.SetBinError(i + 1, float(l[2]))
s_pulls.SetBinContent(i + 1, float(l[3]))
s_pulls.SetBinError(i + 1, float(l[4]))
b_pulls.SetFillStyle(3005)
b_pulls.SetFillColor(923)
b_pulls.SetLineColor(923)
b_pulls.SetLineWidth(1)
b_pulls.SetMarkerStyle(20)
b_pulls.SetMarkerSize(1.25)
s_pulls.SetLineColor(602)
s_pulls.SetMarkerColor(602)
s_pulls.SetMarkerStyle(24) #24
s_pulls.SetLineWidth(1)
b_pulls.GetYaxis().SetRangeUser(-2.5, 2.5)
# Graphs
h_pulls = TH2F("pulls", "", 6, -3., 3., nbins, 0, nbins)
B_pulls = TGraphAsymmErrors(nbins)
S_pulls = TGraphAsymmErrors(nbins)
boxes = []
canvas = TCanvas("canvas", "Pulls", 600, 150 + nbins * 10) #nbins*20)
canvas.cd()
canvas.SetGrid(0, 1)
canvas.GetPad(0).SetTopMargin(0.01)
canvas.GetPad(0).SetRightMargin(0.01)
canvas.GetPad(0).SetBottomMargin(0.05)
canvas.GetPad(0).SetLeftMargin(0.25) #(0.25)#(0.065)
canvas.GetPad(0).SetTicks(1, 1)
for i, s in enumerate(content):
l = s.split()
if "1034h" in l[0]: l[0] = "CMS_PDF_13TeV"
h_pulls.GetYaxis().SetBinLabel(i + 1, l[0].replace('CMS2016_', '')) #C
#y1 = gStyle.GetPadBottomMargin()
#y2 = 1. - gStyle.GetPadTopMargin()
#h = (y2 - y1) / float(nbins)
#y1 = y1 + float(i) * h
#y2 = y1 + h
#box = TPaveText(0, y1, 1, y2, 'NDC')
#box.SetFillColor(0)
#box.SetTextSize(0.02)
#box.SetBorderSize(0)
#box.SetTextAlign(12)
#box.SetMargin(0.005)
#if i % 2 == 0:
# box.SetFillColor(18)
#box.Draw()
#boxes.append(box)
B_pulls.SetPoint(i + 1, float(l[1]), float(i + 1) - 0.3) #C
B_pulls.SetPointError(i + 1, float(l[2]), float(l[2]), 0., 0.) #C
for i, s in enumerate(content):
l = s.split()
S_pulls.SetPoint(i + 1, float(l[3]), float(i + 1) - 0.7) #C
S_pulls.SetPointError(i + 1, float(l[4]), float(l[4]), 0., 0.) #C
h_pulls.GetXaxis().SetTitle("(#hat{#theta} - #theta_{0}) / #Delta#theta")
h_pulls.GetXaxis().SetLabelOffset(-0.01)
h_pulls.GetXaxis().SetTitleOffset(.6)
h_pulls.GetYaxis().SetNdivisions(nbins, 0, 0)
B_pulls.SetFillColor(1)
B_pulls.SetLineColor(1)
B_pulls.SetLineStyle(1)
B_pulls.SetLineWidth(2)
B_pulls.SetMarkerColor(1)
B_pulls.SetMarkerStyle(20)
B_pulls.SetMarkerSize(1) #(0.75)
S_pulls.SetFillColor(629)
S_pulls.SetLineColor(629)
S_pulls.SetMarkerColor(629)
S_pulls.SetLineWidth(2)
S_pulls.SetMarkerStyle(20)
S_pulls.SetMarkerSize(1)
box1 = TBox(-1., 0., 1., nbins)
box1.SetFillStyle(3001)
#box1.SetFillStyle(0)
box1.SetFillColor(417)
box1.SetLineWidth(2)
box1.SetLineStyle(2)
box1.SetLineColor(417)
box2 = TBox(-2., 0., 2., nbins)
box2.SetFillStyle(3001)
#box2.SetFillStyle(0)
box2.SetFillColor(800)
box2.SetLineWidth(2)
box2.SetLineStyle(2)
box2.SetLineColor(800)
leg = TLegend(0.1, -0.05, 0.7, 0.08)
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetFillColor(0)
leg.SetNColumns(2)
leg.AddEntry(B_pulls, "B-only fit", "lp")
leg.AddEntry(S_pulls, "S+B fit", "lp")
if text: leg.AddEntry(0, text, "")
h_pulls.Draw("")
box2.Draw()
box1.Draw()
B_pulls.Draw("P6SAME")
S_pulls.Draw("P6SAME")
leg.Draw()
# drawCMS(35867, "Preliminary")
# drawAnalysis("VH")
# drawRegion(outName)
canvas.Print(outName + ".png")
canvas.Print(outName + ".pdf")
if not gROOT.IsBatch(): raw_input("Press Enter to continue...")
for layer in range(1, 35):
print 'producing trend plot for layer ' + str(layer)
graphs.append(TGraphAsymmErrors())
eff_vs_lumi = graphs[-1]
xlabels = add_points(eff_vs_lumi, hiteffdir + "/" + era, layer, usePU)
eff_vs_lumi.SetTitle(get_layer_name(layer))
eff_vs_lumi.GetYaxis().SetTitle("hit efficiency")
if usePU == 0: eff_vs_lumi.GetXaxis().SetTitle("inst. lumi [x10^{30}]")
else: eff_vs_lumi.GetXaxis().SetTitle("PU")
eff_vs_lumi.SetMarkerStyle(20)
eff_vs_lumi.SetMarkerSize(.8)
eff_vs_lumi.Draw("AP")
eff_vs_lumi_lastpt = TGraphAsymmErrors()
npt = eff_vs_lumi.GetN()
x, y = ROOT.Double(0), ROOT.Double(0)
eff_vs_lumi.GetPoint(npt - 1, x, y)
eff_vs_lumi_lastpt.SetPoint(0, x, y)
eff_vs_lumi_lastpt.SetMarkerStyle(24)
eff_vs_lumi_lastpt.SetMarkerColor(2)
eff_vs_lumi_lastpt.Draw("P")
if usePU == 0:
c1.Print("SiStripHitEffTrendPlotVsLumi_layer" + str(layer) + ".png")
else:
c1.Print("SiStripHitEffTrendPlotVsPU_layer" + str(layer) + ".png")
def ratioplot():
# create required parts
leg = getLegend()
latex = getLatex()
c = SetCanvas()
#c.SetLogy()
#c = TCanvas()
#c.SetLogy()
h1 = f.Get('h_num_calo_') #'calo',pf
h1 = setHistStyle(h1, bins)
h2 = f.Get('h_den_calo_')
h2 = setHistStyle(h2, bins)
h11 = f2.Get('h_num_calo_')
h11 = setHistStyle(h11, bins)
h21 = f2.Get('h_den_calo_')
h21 = setHistStyle(h21, bins)
gr = TGraphAsymmErrors(30)
#gr.Divide(h1,h2)
gr = TGraphAsymmErrors(h1, h2)
gr2 = TGraphAsymmErrors(h11, h21)
gr2.SetMarkerStyle(20)
gr2.GetXaxis().SetRangeUser(0, 1000)
gr2.SetMarkerSize(1.5)
gr2.SetLineColor(2)
gr2.SetLineWidth(1)
gr2.SetMarkerColor(2)
gr.GetXaxis().SetRangeUser(0, 1000)
# gr.GetYaxis().SetRangeUser(0.0001,1.2)
gr.SetMarkerStyle(20)
gr.SetMarkerSize(1.5)
gr.SetLineColor(1)
gr.SetLineWidth(1)
gr.SetMarkerColor(1)
gr.GetYaxis().SetTitle("Trigger Efficiency")
gr.GetXaxis().SetTitle("MET [GeV]")
gr.SetTitle("")
#base histogram
histogram_base = TH1F("histogram_base", "", 1000, 0, 1000.)
histogram_base.SetTitle("")
histogram_base.SetStats(0)
histogram_base.SetMarkerSize(2)
#histogram_base.SetMinimum(0.0)
histogram_base.SetMaximum(1.2)
histogram_base.GetXaxis().SetTitle("Online E_{T}^{miss} (GeV)")
histogram_base.GetYaxis().SetTitle("Efficiency")
histogram_base = setHistStyle(histogram_base, bins)
histogram_base.Draw("HIST")
# c.SaveAs()
gr.Draw('P same')
gr2.Draw('P same')
latex.DrawLatex(0.49, 0.93, " EGamma Run2018C, 13 TeV")
xmin = 0.0
line = TLine(max(xmin, gr.GetXaxis().GetXmin()), 1, 1000, 1)
line.SetLineColor(1)
line.SetLineWidth(1)
line.SetLineStyle(7)
line.Draw()
leg.AddEntry(gr, 'With HBHENoise filter', 'P')
leg.AddEntry(gr2, 'Without HBHENoise filter', 'P')
leg.Draw()
txt = 'Path: HLT_PFMETTypeOne200_HBHE_BeamHaloCleaned'
texcms = AddText(txt)
texcms.Draw("same")
c.SaveAs('testTurnOn_EGamma.png')
def makeplot_single(
h1_sig=None,
h1_bkg=None,
h1_data=None,
sig_legends_=None,
bkg_legends_=None,
sig_colors_=None,
bkg_colors_=None,
hist_name_=None,
sig_scale_=1.0,
dir_name_="plots",
output_name_=None,
extraoptions=None
):
if h1_sig == None or h1_bkg == None:
print("nothing to plot...")
return
os.system("mkdir -p "+dir_name_)
os.system("cp index.php "+dir_name_)
s_color = [632, 617, 839, 800, 1]
b_color = [920, 2007, 2005, 2003, 2001, 2011]
if sig_colors_:
s_color = sig_colors_
if bkg_colors_:
b_color = bkg_colors_
for idx in range(len(h1_sig)):
h1_sig[idx].SetLineWidth(3)
h1_sig[idx].SetLineColor(s_color[idx])
for idx in range(len(h1_bkg)):
h1_bkg[idx].SetLineWidth(2)
h1_bkg[idx].SetLineColor(b_color[idx])
h1_bkg[idx].SetFillColorAlpha(b_color[idx], 1)
if h1_data:
h1_data.SetBinErrorOption(1)
h1_data.SetLineColor(1)
h1_data.SetLineWidth(2)
h1_data.SetMarkerColor(1)
h1_data.SetMarkerStyle(20)
myC = r.TCanvas("myC","myC", 600, 600)
myC.SetTicky(1)
pad1 = r.TPad("pad1","pad1", 0.05, 0.33,0.95, 0.97)
pad1.SetBottomMargin(0.027)
pad1.SetRightMargin( rightMargin )
pad1.SetLeftMargin( leftMargin )
pad2 = r.TPad("pad2","pad2", 0.05, 0.04, 0.95, 0.31)
pad2.SetBottomMargin(0.4)
pad2.SetTopMargin(0.05)
pad2.SetRightMargin( rightMargin )
pad2.SetLeftMargin( leftMargin )
pad2.Draw()
pad1.Draw()
pad1.cd()
for idx in range(len(h1_sig)):
print("before signal scaling",h1_sig[idx].Integral())
h1_sig[idx].Scale(sig_scale_)
print("after signal scaling",h1_sig[idx].Integral())
stack = r.THStack("stack", "stack")
nS = np.zeros(h1_bkg[0].GetNbinsX())
eS = np.zeros(h1_bkg[0].GetNbinsX())
#hist_all is used to make the data/mc ratio. remove signal for the moment due to signal is scaled right now
hist_all = h1_sig[0].Clone("hist_all")
hist_all.Scale(0.0)
hist_s = h1_sig[0].Clone("hist_s")
hist_b = h1_bkg[0].Clone("hist_b")
for idx in range(len(h1_bkg)):
stack.Add(h1_bkg[idx])
for ib in range(h1_bkg[0].GetNbinsX()):
nS[ib] += h1_bkg[idx].GetBinContent(ib+1)
eS[ib] = math.sqrt(eS[ib]*eS[ib] + h1_bkg[idx].GetBinError(ib+1)*h1_bkg[idx].GetBinError(ib+1))
hist_all.Add(h1_bkg[idx])
if idx > 0:
hist_b.Add(h1_bkg[idx])
for idx in range(len(h1_sig)):
print("ggH signal yield: ", hist_s.Integral())
if idx > 0:
hist_temp = h1_sig[idx].Clone(h1_sig[idx].GetName()+"_temp")
#hist_all.Add(hist_temp)
hist_s.Add(h1_sig[idx])
print("all signal yield: ", hist_s.Integral())
stack.SetTitle("")
maxY = 0.0
if "stack_signal" in extraoptions and extraoptions["stack_signal"]:
for idx in range(len(h1_sig)):
h1_sig[idx].SetFillColorAlpha(s_color[idx], 1)
stack.Add(h1_sig[idx])
for ib in range(h1_bkg[0].GetNbinsX()):
nS[ib] += h1_sig[idx].GetBinContent(ib+1)
eS[ib] = math.sqrt(eS[ib]*eS[ib] + h1_sig[idx].GetBinError(ib+1)*h1_sig[idx].GetBinError(ib+1))
if stack.GetMaximum() > maxY:
maxY = stack.GetMaximum()
#if "SR" in h.GetTitle():
stack.Draw("hist")
else:
stack.Draw("hist")
if stack.GetMaximum() > maxY:
maxY = stack.GetMaximum()
for idx in range(len(h1_sig)):
if h1_sig[idx].GetMaximum() > maxY:
maxY = h1_sig[idx].GetMaximum()
if "SR" in h1_bkg[0].GetTitle():
#h1_sig[idx].Draw("samehist")
hist_s.Draw("samehist")
##draw stack total unc on top of total histogram
box = r.TBox(0,0,1,1,)
box.SetFillStyle(3002)
box.SetLineWidth(0)
box.SetFillColor(r.kBlack)
for idx in range(h1_bkg[0].GetNbinsX()):
box.DrawBox(h1_bkg[0].GetBinCenter(idx+1)-0.5*h1_bkg[0].GetBinWidth(idx+1), nS[idx]-eS[idx], h1_bkg[0].GetBinCenter(idx+1)+0.5*h1_bkg[0].GetBinWidth(idx+1), nS[idx]+eS[idx])
if h1_data:
if h1_data.GetMaximum() > maxY:
maxY = h1_data.GetMaximum()+np.sqrt(h1_data.GetMaximum())
#if not "SR" in h1_data.GetTitle() or "fail" in h1_data.GetTitle():
if True:
#print("debug h1_data.GetName()",h1_data.GetName(), h1_data.GetTitle())
TGraph_data = TGraphAsymmErrors(h1_data)
for i in range(TGraph_data.GetN()):
#data point
var_x, var_y = Double(0.), Double(0.)
TGraph_data.GetPoint(i,var_x,var_y)
if np.fabs(var_y) < 1e-5:
TGraph_data.SetPoint(i,var_x,-1.0)
TGraph_data.SetPointEYlow(i,-1)
TGraph_data.SetPointEYhigh(i,-1)
#print("zero bins in the data TGraph: bin",i+1)
else:
TGraph_data.SetPoint(i,var_x,var_y)
err_low = var_y - (0.5*TMath.ChisquareQuantile(0.1586555,2.*var_y))
TGraph_data.SetPointEYlow(i, var_y - (0.5*TMath.ChisquareQuantile(0.1586555,2.*var_y)))
TGraph_data.SetPointEYhigh(i, (0.5*TMath.ChisquareQuantile(1.-0.1586555,2.*(var_y+1))) - var_y)
TGraph_data.SetMarkerColor(1)
TGraph_data.SetMarkerSize(1)
TGraph_data.SetMarkerStyle(20)
TGraph_data.Draw("same P")
stack.GetYaxis().SetTitle("Events")
stack.GetYaxis().SetTitleOffset(1.05)
stack.GetYaxis().SetTitleSize(0.08)
stack.GetYaxis().SetLabelSize(0.06)
#stack.GetYaxis().CenterTitle()
stack.GetXaxis().SetLabelSize(0.)
#stack.GetXaxis().SetLabelOffset(0.013)
#if "xaxis_range" in extraoptions:
# stack.GetXaxis().SetRangeUser(float(extraoptions["xaxis_range"][0]),float(extraoptions["xaxis_range"][1]))
leg = r.TLegend(0.2, 0.60, 0.9, 0.88)
leg.SetNColumns(3)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.SetTextSize(0.05)
for idx in range(len(h1_bkg)):
leg.AddEntry(h1_bkg[idx], bkg_legends_[idx], "F")
if "SR" in hist_s.GetTitle():
leg.AddEntry(hist_s, 'HH #times {:1.2}'.format(sig_scale_), "L")
leg.AddEntry(box, "Total unc", "F")
if h1_data:
leg.AddEntry(h1_data, "Data", "ep")
leg.Draw()
pad2.cd()
pad2.SetGridy(1)
ratio = None
ratio_Low = 0.0
ratio_High = 4
if h1_data:
ratio = TGraphAsymmErrors(h1_data)
for i in range(ratio.GetN()):
#bkg prediction
imc = Double(hist_all.GetBinContent(i+1))
#data point
var_x, var_y = Double(0.), Double(0.)
if not ("SR" in h1_data.GetTitle() and (i>5 and i<9)):
ratio.GetPoint(i,var_x,var_y)
if var_y == 0.:
ratio.SetPoint(i,var_x,-1.0)
ratio.SetPointEYlow(i,-1)
ratio.SetPointEYhigh(i,-1)
continue
ratio.SetPoint(i,var_x,var_y/imc)
err_low = (var_y - (0.5*TMath.ChisquareQuantile(0.1586555,2.*var_y)))/imc
err_high = ((0.5*TMath.ChisquareQuantile(1.-0.1586555,2.*(var_y+1))) - var_y)/imc
ratio.SetPointEYlow(i, err_low)
ratio.SetPointEYhigh(i, err_high)
ratio.SetMarkerColor(1)
ratio.SetMarkerSize(1)
ratio.SetMarkerStyle(20)
ratio.GetXaxis().SetTitle("j_{2} regressed mass [GeV]")
#myC.Update()
if "ratio_range" in extraoptions:
ratio_Low = extraoptions["ratio_range"][0]
ratio_High = extraoptions["ratio_range"][1]
ratio.GetYaxis().SetTitle("data/mc")
ratio.GetYaxis().SetRangeUser(ratio_Low, ratio_High)
ratio.GetXaxis().SetRangeUser(50, 220)
ratio.SetTitle("")
ratio.Draw("same AP")
pad2.Update()
print(ratio.GetTitle(),ratio.GetName(),"debug")
else:
ratio = h1_sig[0].Clone("ratio")
ratio_High = 0.0
for ibin in range(1,ratio.GetNbinsX()+1):
s = hist_s.GetBinContent(ibin)
b = hist_b.GetBinContent(ibin)
L = 0.0
if b > 0.0:
L = s/math.sqrt(b)
if L > ratio_High:
ratio_High = L
ratio.SetBinContent(ibin, L)
if ratio_High > 1.0:
ratio_High = 1.0
ratio.GetYaxis().SetRangeUser(ratio_Low, ratio_High*1.2)
ratio.GetYaxis().SetTitle("S/#sqrt{B}")
ratio.Draw("samehist")
ratio.SetLineColor(1)
ratio.SetLineWidth(2)
ratio.SetMarkerStyle(20)
ratio.SetMarkerColor(1)
ratio.SetFillColorAlpha(1, 0)
ratio.GetXaxis().SetTitleOffset(0.94)
ratio.GetXaxis().SetTitleSize(0.18)
ratio.GetXaxis().SetLabelSize(0.12)
ratio.GetXaxis().SetLabelOffset(0.013)
ratio.GetYaxis().SetTitleOffset(0.40)
ratio.GetYaxis().SetTitleSize(0.17)
ratio.GetYaxis().SetLabelSize(0.13)
ratio.GetYaxis().SetTickLength(0.01)
ratio.GetYaxis().SetNdivisions(505)
#if "xaxis_range" in extraoptions:
# ratio.GetXaxis().SetRangeUser(float(extraoptions["xaxis_range"][0]),float(extraoptions["xaxis_range"][1]))
#draw stack total unc on the ratio plot to present the background uncertainty
box_ratio = r.TBox(0,0,1,1,)
box_ratio.SetFillStyle(3002)
box_ratio.SetLineWidth(0)
box_ratio.SetFillColor(r.kBlack)
for idx in range(h1_bkg[0].GetNbinsX()):
if np.fabs(nS[idx])> 1e-06:
box_ratio.DrawBox(h1_bkg[0].GetBinCenter(idx+1)-0.5*h1_bkg[0].GetBinWidth(idx+1), (nS[idx]-eS[idx])/nS[idx], h1_bkg[0].GetBinCenter(idx+1)+0.5*h1_bkg[0].GetBinWidth(idx+1), (nS[idx]+eS[idx])/nS[idx])
else:
print("blinded Higgs peak region")
if "xaxis_label" in extraoptions and extraoptions["xaxis_label"] != None:
x_title = extraoptions["xaxis_label"]
ratio.GetXaxis().SetTitle(x_title)
ratio.GetYaxis().CenterTitle()
##########draw CMS preliminary
pad1.cd()
tex1 = r.TLatex(leftMargin, 0.91, "CMS")
tex1.SetNDC()
tex1.SetTextFont(61)
tex1.SetTextSize(0.070)
tex1.SetLineWidth(2)
tex1.Draw()
tex2 = r.TLatex(leftMargin+0.12,0.912,"Internal")
tex2.SetNDC()
tex2.SetTextFont(52)
tex2.SetTextSize(0.055)
tex2.SetLineWidth(2)
tex2.Draw()
lumi_value = 137
if "lumi_value" in extraoptions:
lumi_value = extraoptions["lumi_value"]
tex3 = r.TLatex(0.72,0.912,"%d"%lumi_value+" fb^{-1} (13 TeV)")
tex3.SetNDC()
tex3.SetTextFont(42)
tex3.SetTextSize(0.055)
tex3.SetLineWidth(2)
tex3.Draw()
outFile = dir_name_
if output_name_:
outFile = outFile + "/" +output_name_
else:
outFile = outFile + "/" + hist_name_
#print("maxY = "+str(maxY))
stack.SetMaximum(maxY*1.7)
#print everything into txt file
text_file = open(outFile+"_linY.txt", "w")
text_file.write("bin | x ")
for idx in range(len(h1_bkg)):
text_file.write(" | %21s"%bkg_legends_[idx])
text_file.write(" | %21s"%("total B"))
for idx in range(len(sig_legends_)):
text_file.write(" | %25s"%sig_legends_[idx])
if h1_data:
text_file.write(" | data | data/mc")
text_file.write("\n-------------")
for idx in range(24*(len(h1_bkg) + 1)+ 29*len(sig_legends_)):
text_file.write("-")
if h1_data:
text_file.write("-------")
text_file.write("\n")
for ibin in range(0,h1_sig[0].GetNbinsX()+1):
text_file.write("%3d"%ibin+" ")
text_file.write(" | %6.3f"%h1_data.GetBinCenter(ibin)+" ")
for idx in range(len(h1_bkg)):
text_file.write(" | %7.3f "%h1_bkg[idx].GetBinContent(ibin)+"$\\pm$"+ " %7.3f"%h1_bkg[idx].GetBinError(ibin))
text_file.write(" | %7.3f "%hist_b.GetBinContent(ibin)+"$\\pm$"+ " %7.3f"%hist_b.GetBinError(ibin))
for idx in range(len(sig_legends_)):
text_file.write(" | %9.3f "%h1_sig[idx].GetBinContent(ibin)+"$\\pm$"+ " %9.3f"%h1_sig[idx].GetBinError(ibin))
if h1_data:
text_file.write(" | %d"%h1_data.GetBinContent(ibin) + " | %7.3f "%h1_data.GetBinContent(ibin) +"$\\pm$"+ " %7.3f"%h1_data.GetBinError(ibin))
text_file.write("\n\n")
#print yield table for AN
text_file.write("print yield table for AN\n")
bkg_all = 0
bkg_all_errsq = 0
for idx in range(len(h1_bkg)):
bkg_tmp = h1_bkg[idx].GetBinContent(7)+h1_bkg[idx].GetBinContent(8)+h1_bkg[idx].GetBinContent(9)
bkg_errsq_tmp = h1_bkg[idx].GetBinError(7)*h1_bkg[idx].GetBinError(7)+h1_bkg[idx].GetBinError(8)*h1_bkg[idx].GetBinError(8)+h1_bkg[idx].GetBinError(9)*h1_bkg[idx].GetBinError(9)
bkg_all += bkg_tmp
bkg_all_errsq += bkg_errsq_tmp
text_file.write("%s"%(bkg_legends_[idx])+"& %7.2f"%(bkg_tmp)+"$\\pm$"+ "%7.2f"%np.sqrt(bkg_errsq_tmp)+"\n")
text_file.write("total background & %7.2f"%(bkg_all)+"$\\pm$"+ "%7.2f"%np.sqrt(bkg_all_errsq)+"\n")
text_file.write("\ggHH SM ($\kapl=1$) & %7.2f"%((h1_sig[0].GetBinContent(7)+h1_sig[0].GetBinContent(8)+h1_sig[0].GetBinContent(9))/sig_scale_)+"$\\pm$"+ "%7.1f"%(sig_scale_*np.sqrt(h1_sig[0].GetBinError(7)*h1_sig[0].GetBinError(7)+h1_sig[0].GetBinError(8)*h1_sig[0].GetBinError(8)+h1_sig[0].GetBinError(9)*h1_sig[0].GetBinError(9)))+"\n")
text_file.write("\VBFHH SM ($\kapl=1$) & %7.2f"%((h1_sig[1].GetBinContent(7)+h1_sig[1].GetBinContent(8)+h1_sig[1].GetBinContent(9))/sig_scale_)+"$\\pm$"+ "%7.1f"%(sig_scale_*np.sqrt(h1_sig[1].GetBinError(7)*h1_sig[1].GetBinError(7)+h1_sig[1].GetBinError(8)*h1_sig[1].GetBinError(8)+h1_sig[1].GetBinError(9)*h1_sig[1].GetBinError(9)))+"\n")
text_file.write("HH bin 8 value %s"%h1_sig[0].GetBinContent(8)+"\n")
text_file.write("HH bin 9 value %s"%h1_sig[0].GetBinContent(9)+"\n")
text_file.write("HH bin 7 value %s"%h1_sig[0].GetBinContent(7)+"\n")
text_file.write("HH bin 8 error %s"%h1_sig[0].GetBinError(8)+"\n")
text_file.write("HH bin 9 error %s"%h1_sig[0].GetBinError(9)+"\n")
text_file.write("HH bin 7 error %s"%h1_sig[0].GetBinError(7)+"\n")
text_file.write("total & %7.2f"%(bkg_all+(h1_sig[0].GetBinContent(7)+h1_sig[0].GetBinContent(8)+h1_sig[0].GetBinContent(9)+h1_sig[1].GetBinContent(7)+h1_sig[1].GetBinContent(8)+h1_sig[1].GetBinContent(9))/sig_scale_)+"$\\pm$"+ "%7.2f"%(np.sqrt((h1_sig[0].GetBinError(7)*h1_sig[0].GetBinError(7)+h1_sig[0].GetBinError(8)*h1_sig[0].GetBinError(8)+h1_sig[0].GetBinError(9)*h1_sig[0].GetBinError(9))/(sig_scale_*sig_scale_)+(h1_sig[1].GetBinError(7)*h1_sig[1].GetBinError(7)+h1_sig[1].GetBinError(8)*h1_sig[1].GetBinError(8)+h1_sig[1].GetBinError(9)*h1_sig[1].GetBinError(9))/(sig_scale_*sig_scale_)+bkg_all_errsq))+"\n")
text_file.close()
os.system("cp "+outFile+"_linY.txt "+outFile+"_logY.txt")
pad1.RedrawAxis()
myC.SaveAs(outFile+"_linY.png")
myC.SaveAs(outFile+"_linY.pdf")
myC.SaveAs(outFile+"_linY.C")
pad1.cd()
stack.SetMaximum(maxY*100.0)
stack.SetMinimum(0.5)
pad1.SetLogy()
pad1.RedrawAxis()
myC.SaveAs(outFile+"_logY.png")
myC.SaveAs(outFile+"_logY.pdf")
myC.SaveAs(outFile+"_logY.C")
#save histogram and ratio to root file
outFile_root = r.TFile(outFile+".root", "recreate")
outFile_root.cd()
for idx in range(len(h1_bkg)):
h1_bkg[idx].Write()
for idx in range(len(sig_legends_)):
h1_sig[idx].Write()
if h1_data:
h1_data.Write()
ratio.Write()
#outFile_root.Write()
outFile_root.Close()
