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()