Ejemplo n.º 1
0
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")
Ejemplo n.º 2
0
def MakeOneDHist(pathToDir, distribution):

    numFittingSamples = 0

    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"
    elif arguments.normalizeToData:
        NormText = "MC scaled to data"
        NormLabel.SetLabel(NormText)

    YieldsLabel = TPaveText(0.39, 0.7, 0.59, 0.9, "NDC")
    YieldsLabel.SetBorderSize(0)
    YieldsLabel.SetFillColor(0)
    YieldsLabel.SetFillStyle(0)
    YieldsLabel.SetTextAlign(12)

    RatiosLabel = TPaveText()
    RatiosLabel.SetDrawOption("NDC")
    RatiosLabel.SetBorderSize(0)
    RatiosLabel.SetFillColor(0)
    RatiosLabel.SetFillStyle(0)
    RatiosLabel.SetTextAlign(32)

    Legend = TLegend()
    Legend.SetBorderSize(0)
    Legend.SetFillColor(0)
    Legend.SetFillStyle(0)

    fittingIntegral = 0
    scaleFactor = 1

    HistogramsToFit = []
    TargetDataset = distribution['target_dataset']

    FittingLegendEntries = []
    DataLegendEntries = []

    FittingHistogramDatasets = []

    Stack_list = []
    Stack_list.append(THStack("stack_before", distribution['name']))
    Stack_list.append(THStack("stack_after", distribution['name']))

    fileName = condor_dir + "/" + distribution['target_dataset'] + ".root"
    if not os.path.exists(fileName):
        return
    inputFile = TFile(fileName)
    if inputFile.IsZombie() or not inputFile.GetNkeys():
        return

    Target = inputFile.Get("OSUAnalysis/" + distribution['channel'] + "/" +
                           distribution['name']).Clone()
    Target.SetDirectory(0)
    inputFile.Close()

    Target.SetMarkerStyle(20)
    Target.SetMarkerSize(0.8)
    Target.SetFillStyle(0)
    Target.SetLineColor(colors[TargetDataset])
    Target.SetLineStyle(1)
    Target.SetLineWidth(2)
    targetIntegral = Target.Integral()
    if (arguments.normalizeToUnitArea and Target.Integral() > 0):
        Target.Scale(1. / Target.Integral())
    if arguments.rebinFactor:
        RebinFactor = int(arguments.rebinFactor)
        #don't rebin histograms which will have less than 5 bins or any gen-matching histograms
        if Target.GetNbinsX() >= RebinFactor * 5 and Target.GetName().find(
                "GenMatch") is -1:
            Target.Rebin(RebinFactor)

    ### formatting target histogram and adding to legend
    legendIndex = 0
    Legend.AddEntry(Target, labels[TargetDataset], "LEP")
    legendIndex = legendIndex + 1

    if not outputFile.Get("OSUAnalysis"):
        outputFile.mkdir("OSUAnalysis")
    if not outputFile.Get("OSUAnalysis/" + distribution['channel']):
        outputFile.Get("OSUAnalysis").mkdir(distribution['channel'])

    for sample in distribution[
            'datasets']:  # loop over different samples requested to be fit

        dataset_file = "%s/%s.root" % (condor_dir, sample)
        inputFile = TFile(dataset_file)
        HistogramObj = inputFile.Get(pathToDir + "/" +
                                     distribution['channel'] + "/" +
                                     distribution['name'])
        if not HistogramObj:
            print "WARNING:  Could not find histogram " + pathToDir + "/" + distribution[
                'channel'] + "/" + distribution[
                    'name'] + " in file " + dataset_file + ".  Will skip it and continue."
            continue
        Histogram = HistogramObj.Clone()
        Histogram.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.GetName(
            ).find("GenMatch") is -1:
                Histogram.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 = "Entries / " + str(Histogram.GetXaxis().GetBinWidth(
                1)) + " " + xAxisLabel[unitBeginIndex + 1:unitEndIndex]
        else:
            yAxisLabel = "Entries per bin (" + str(
                Histogram.GetXaxis().GetBinWidth(1)) + " width)"

        if not arguments.makeFancy:
            histoTitle = Histogram.GetTitle()
        else:
            histoTitle = ""

        legLabel = labels[sample]
        if (arguments.printYields):
            yieldHist = Histogram.Integral()
            legLabel = legLabel + " (%.1f)" % yieldHist
        FittingLegendEntries.append(legLabel)

        if (types[sample] == "bgMC"):

            numFittingSamples += 1
            fittingIntegral += Histogram.Integral()

            Histogram.SetLineStyle(1)
            if (arguments.noStack):
                Histogram.SetFillStyle(0)
                Histogram.SetLineColor(colors[sample])
                Histogram.SetLineWidth(2)
            else:
                Histogram.SetFillStyle(1001)
                Histogram.SetFillColor(colors[sample])
                Histogram.SetLineColor(1)
                Histogram.SetLineWidth(1)

        elif (types[sample] == "signalMC"):

            numFittingSamples += 1

            Histogram.SetFillStyle(0)
            Histogram.SetLineColor(colors[sample])
            Histogram.SetLineStyle(1)
            Histogram.SetLineWidth(2)
        if (arguments.normalizeToUnitArea and Histogram.Integral() > 0):
            Histogram.Scale(1. / Histogram.Integral())

        HistogramsToFit.append(Histogram)
        FittingHistogramDatasets.append(sample)

    #scaling histograms as per user's specifications
    if targetIntegral > 0 and fittingIntegral > 0:
        scaleFactor = targetIntegral / fittingIntegral
    for fittingHist in HistogramsToFit:
        if arguments.normalizeToData:
            fittingHist.Scale(scaleFactor)

        if arguments.normalizeToUnitArea and not arguments.noStack and fittingIntegral > 0:
            fittingHist.Scale(1. / fittingIntegral)
        elif arguments.normalizeToUnitArea and arguments.noStack and fittingHist.Integral(
        ) > 0:
            fittingHist.Scale(1. / fittingHist.Integral())

    def fitf(x, par):
        xBin = HistogramsToFit[0].FindBin(x[0])
        value = 0.0

        for i in range(0, len(HistogramsToFit)):
            value += par[i] * HistogramsToFit[i].GetBinContent(xBin) + par[
                i +
                len(HistogramsToFit)] * HistogramsToFit[i].GetBinError(xBin)

        return value

    lowerLimit = Target.GetBinLowEdge(1)
    upperLimit = Target.GetBinLowEdge(Target.GetNbinsX()) + Target.GetBinWidth(
        Target.GetNbinsX())
    if 'lowerLimit' in distribution:
        lowerLimit = distribution['lowerLimit']
    if 'upperLimit' in distribution:
        upperLimit = distribution['upperLimit']
    func = TF1("fit", fitf, lowerLimit, upperLimit, 2 * len(HistogramsToFit))

    for i in range(0, len(HistogramsToFit)):
        if 'fixed_datasets' in distribution and distribution['datasets'][
                i] in distribution['fixed_datasets']:
            func.FixParameter(i, 1.0)
        else:
            func.SetParameter(i, 1.0)
#            func.SetParLimits (i, 0.0, 1.0e2) # comment this out so we don't have to pre-normalize the QCD input sample
        func.SetParName(i, labels[FittingHistogramDatasets[i]])

    shiftedScaleFactors = []
    if arguments.parametricErrors:
        # loop over all input histograms and shift them +- 1 sigma
        for i in range(0, len(HistogramsToFit)):
            sfs = []

            # -1 => -1 sigma, +1 => +1 sigma
            for j in [-1, 1]:
                # loop over the parameters holding the errors for each dataset, fixing all to 0
                for k in range(len(HistogramsToFit), 2 * len(HistogramsToFit)):
                    func.FixParameter(k, 0)
                # fix the error of the dataset of interest to +-1
                func.FixParameter(i + len(HistogramsToFit), j)

                # perform new fit
                for k in range(0, distribution['iterations'] - 1):
                    if j == -1:
                        print "Scale down " + labels[FittingHistogramDatasets[
                            i]] + " iteration " + str(k + 1) + "..."
                    if j == 1:
                        print "Scale up " + labels[FittingHistogramDatasets[
                            i]] + " iteration " + str(k + 1) + "..."
                    Target.Fit("fit", "QEMR0")
                Target.Fit("fit", "VEMR0")

                # save the new scale factors for each dataset
                for k in range(0, len(HistogramsToFit)):
                    sfs.append(func.GetParameter(k))

            shiftedScaleFactors.append(sfs)

    # reset the parameters with the errors of each dataset to 0
    for i in range(len(HistogramsToFit), 2 * len(HistogramsToFit)):
        func.FixParameter(i, 0)
    # do the fit to get the central values
    for i in range(0, distribution['iterations'] - 1):
        print "Iteration " + str(i + 1) + "..."
        Target.Fit("fit", "QEMR0")
    Target.Fit("fit", "VEMR0")

    if arguments.parametricErrors:
        # make a list of the largest errors on each contribution by shifting any other contribution
        parErrors = []
        # loop over all the datasets
        for i in range(0, len(HistogramsToFit)):
            centralValue = func.GetParameter(i)
            maxError = 0
            # find the maximum deviation from the central value and save that
            for shiftedScaleFactor in shiftedScaleFactors[i]:
                currentError = abs(shiftedScaleFactor - centralValue)
                if currentError > maxError:
                    maxError = currentError

            parErrors.append(maxError)

    finalMax = 0
    if not arguments.noStack:
        for fittingHist in HistogramsToFit:
            finalMax += fittingHist.GetMaximum()
        else:
            for fittingHist in HistogramsToFit:
                if (fittingHist.GetMaximum() > finalMax):
                    finalMax = fittingHist.GetMaximum()
    if (Target.GetMaximum() > finalMax):
        finalMax = Target.GetMaximum()

    Target.SetMaximum(1.1 * finalMax)
    Target.SetMinimum(0.0001)

    Canvas = TCanvas(distribution['name'] + "_FitFunction")
    Canvas.cd(1)
    Target.Draw()
    func.Draw("same")

    outputFile.cd("OSUAnalysis/" + distribution['channel'])
    Canvas.Write()
    if arguments.savePDFs:
        if histogram == input_histograms[0]:
            Canvas.Print(pdfFileName + "(", "pdf")
        else:
            Canvas.Print(pdfFileName, "pdf")
    Target.SetStats(0)

    ### formatting bgMC histograms and adding to legend
    legendIndex = numFittingSamples - 1
    for Histogram in reversed(HistogramsToFit):
        if (arguments.noStack):
            Legend.AddEntry(Histogram, FittingLegendEntries[legendIndex], "L")
        else:
            Legend.AddEntry(Histogram, FittingLegendEntries[legendIndex], "F")
        legendIndex = legendIndex - 1

    ### Drawing histograms to canvas

    makeRatioPlots = arguments.makeRatioPlots
    makeDiffPlots = arguments.makeDiffPlots

    yAxisMin = 0.0001
    if arguments.setYMin:
        yAxisMin = float(arguments.setYMin)

    ### Draw everything to the canvases !!!!

    for i in range(0, 2):  # 0 => before, 1 => after

        integrals = []
        ratios = []
        errors = []

        if i == 1:
            # loop over each dataset, saving it's yield and the errors on it
            for j in range(0, len(HistogramsToFit)):

                integrals.append(HistogramsToFit[j].Integral())
                HistogramsToFit[j].Scale(func.GetParameter(j))
                ratios.append(func.GetParameter(j))
                errors.append(func.GetParError(j))

        for fittingHist in HistogramsToFit:
            if not arguments.noStack:
                Stack_list[i].Add(fittingHist)

        #creating the histogram to represent the statistical errors on the stack
        if not arguments.noStack:
            ErrorHisto = HistogramsToFit[0].Clone("errors")
            ErrorHisto.SetFillStyle(3001)
            ErrorHisto.SetFillColor(13)
            ErrorHisto.SetLineWidth(0)
            if i == 1:
                Legend.AddEntry(ErrorHisto, "Stat. Errors", "F")
            for Histogram in HistogramsToFit:
                if Histogram is not HistogramsToFit[0]:
                    ErrorHisto.Add(Histogram)

        if i == 0:
            Canvas = TCanvas(distribution['name'] + "_Before")
        if i == 1:
            Canvas = TCanvas(distribution['name'] + "_After")

        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)

        ### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
        finalMax = 0
        if numFittingSamples is not 0 and not arguments.noStack:
            finalMax = ErrorHisto.GetMaximum() + ErrorHisto.GetBinError(
                ErrorHisto.GetMaximumBin())
        else:
            for bgMCHist in HistogramsToFit:
                if (bgMCHist.GetMaximum() > finalMax):
                    finalMax = bgMCHist.GetMaximum()
        if (Target.GetMaximum() > finalMax):
            finalMax = Target.GetMaximum() + Target.GetBinError(
                Target.GetMaximumBin())
        finalMax = 1.15 * finalMax
        if arguments.setYMax:
            finalMax = float(arguments.setYMax)

        if not arguments.noStack:  # draw stacked background samples
            Stack_list[i].SetTitle(histoTitle)
            Stack_list[i].Draw("HIST")
            Stack_list[i].GetXaxis().SetTitle(xAxisLabel)
            Stack_list[i].GetYaxis().SetTitle(yAxisLabel)
            Stack_list[i].SetMaximum(finalMax)
            Stack_list[i].SetMinimum(yAxisMin)
            if makeRatioPlots or makeDiffPlots:
                Stack_list[i].GetHistogram().GetXaxis().SetLabelSize(0)
            #draw shaded error bands
            ErrorHisto.Draw("A E2 SAME")

        else:  #draw the unstacked backgrounds
            HistogramsToFit[0].SetTitle(histoTitle)
            HistogramsToFit[0].Draw("HIST")
            HistogramsToFit[0].GetXaxis().SetTitle(xAxisLabel)
            HistogramsToFit[0].GetYaxis().SetTitle(yAxisLabel)
            HistogramsToFit[0].SetMaximum(finalMax)
            HistogramsToFit[0].SetMinimum(yAxisMin)
            for bgMCHist in HistogramsToFit:
                bgMCHist.Draw("A HIST SAME")

        Target.Draw("A E X0 SAME")

        #legend coordinates, empirically determined :-)
        x_left = 0.6761745
        x_right = 0.9328859
        x_width = x_right - x_left
        y_max = 0.9
        entry_height = 0.05

        if (numFittingSamples is not 0):  #then draw the data & bgMC legend

            numExtraEntries = 2  # count the target and (lack of) title
            Legend.SetX1NDC(x_left)
            numExtraEntries = numExtraEntries + 1  # count the stat. errors entry

            Legend.SetY1NDC(y_max - entry_height *
                            (numExtraEntries + numFittingSamples))
            Legend.SetX2NDC(x_right)
            Legend.SetY2NDC(y_max)
            Legend.Draw()

            RatiosLabel.SetX1NDC(x_left - 0.1)
            RatiosLabel.SetX2NDC(x_right)
            RatiosLabel.SetY2NDC(Legend.GetY1NDC() - 0.1)
            RatiosLabel.SetY1NDC(RatiosLabel.GetY2NDC() - entry_height *
                                 (numFittingSamples))

            # Deciding which text labels to draw and drawing them
            drawLumiLabel = False
            drawNormLabel = False
            offsetNormLabel = False
            drawHeaderLabel = False

            if not arguments.normalizeToUnitArea:  #don't draw the lumi label if there's no data and it's scaled to unit area
                drawLumiLabel = True
                # move the normalization label down before drawing if we drew the lumi. label
                offsetNormLabel = True
            if arguments.normalizeToUnitArea or arguments.normalizeToData:
                drawNormLabel = True
            if arguments.makeFancy:
                drawHeaderLabel = True
                drawLumiLabel = False

            # now that flags are set, draw the appropriate labels

            if drawLumiLabel:
                LumiLabel.Draw()

            if drawNormLabel:
                if offsetNormLabel:
                    NormLabel.SetY1NDC(topLeft_y_bottom - topLeft_y_offset)
                    NormLabel.SetY2NDC(topLeft_y_top - topLeft_y_offset)
                else:
                    NormLabel.SetY1NDC(topLeft_y_bottom)
                    NormLabel.SetY2NDC(topLeft_y_top)
                NormLabel.Draw()

            if drawHeaderLabel:
                HeaderLabel.Draw()

            YieldsLabel.Clear()
            mcYield = Stack_list[i].GetStack().Last().Integral()
            dataYield = Target.Integral()
            if i == 0:
                YieldsLabel.AddText("Before Fit to Data")
            if i == 1:
                YieldsLabel.AddText("After Fit to Data")
            YieldsLabel.AddText("data yield: " + '%.1f' % dataYield)
            YieldsLabel.AddText("bkgd yield: " + '%.1f' % mcYield)
            YieldsLabel.AddText("data/bkgd: " + '%.2f' % (dataYield / mcYield))
            if i == 1:
                for j in range(0, len(FittingLegendEntries)):
                    if abs(ratios[j] - 1) < 0.001 and abs(
                            errors[j]
                    ) < 0.001:  #then it probably was held fixed
                        continue
                    if arguments.showFittedYields:
                        yield_ = ratios[j] * integrals[j]
                        yielderror_ = errors[j] * yield_
                        text = FittingLegendEntries[
                            j] + " yield: " + '%.0f' % yield_ + ' #pm %.0f' % yielderror_
                    else:
                        text = FittingLegendEntries[
                            j] + " ratio: " + '%.2f' % ratios[
                                j] + ' #pm %.2f' % errors[j]
                    text = text + " (fit)"
                    if arguments.parametricErrors:
                        yield_ = ratios[j] * integrals[j]
                        yieldParError_ = parErrors[j] * yield_
                        if arguments.showFittedYields:
                            text += ' #pm %.2f' % yieldParError_
                        else:
                            text += ' #pm %.2f' % parErrors[j]
                        text = text + " (sys)"
                    RatiosLabel.AddText(text)
            YieldsLabel.Draw()
            RatiosLabel.Draw()

        # drawing the ratio or difference plot if requested
        if (makeRatioPlots or makeDiffPlots):
            Canvas.cd(2)
            BgSum = Stack_list[i].GetStack().Last()
            if makeRatioPlots:
                if arguments.ratioRelErrMax:
                    Comparison = ratioHistogram(Target, BgSum,
                                                arguments.ratioRelErrMax)
                else:
                    Comparison = ratioHistogram(Target, BgSum)
            elif makeDiffPlots:
                Comparison = Target.Clone("diff")
                Comparison.Add(BgSum, -1)
                Comparison.SetTitle("")
                Comparison.GetYaxis().SetTitle("Data-Bkgd")
            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")

        if i == 0:
            Canvas.Write(distribution['name'] + "_Before")
            if arguments.savePDFs:
                pathToDirString = plainTextString(pathToDir)
                Canvas.SaveAs(condor_dir + "/fitting_histogram_pdfs/" +
                              pathToDirString + "/" + distribution['name'] +
                              "_Before.pdf")

        if i == 1:
            Canvas.Write(distribution['name'] + "_After")
            if arguments.savePDFs:
                pathToDirString = plainTextString(pathToDir)
                Canvas.SaveAs(condor_dir + "/fitting_histogram_pdfs/" +
                              pathToDirString + "/" + distribution['name'] +
                              "_After.pdf")
Ejemplo n.º 3
0
def MakeOneDHist(histogramName,integrateDir): 

    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)

    canvasName = histogramName
    if integrateDir is "left":
        canvasName += "_CumulativeLeft"
    elif integrateDir is "right":
        canvasName += "_CumulativeRight"
    Canvas = TCanvas(canvasName)
    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)
        if arguments.generic:
            HistogramObj = inputFile.Get(source['channel'] + "/" +histogramName)  
        else: 
            HistogramObj = inputFile.Get("OSUAnalysis/" + source['channel'] + "/" +histogramName)
        if not HistogramObj:
            print "WARNING:  Could not find histogram " + source['channel'] + "/" + histogramName + " in file " + dataset_file + ".  Will skip it and continue."  
            return 
        Histogram = HistogramObj.Clone()
        Histogram.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:
                Histogram.Rebin(RebinFactor)

        xAxisLabel = Histogram.GetXaxis().GetTitle()
        unitBeginIndex = xAxisLabel.find("[")
        unitEndIndex = xAxisLabel.find("]")
        xAxisLabelVar = xAxisLabel
        
        if unitBeginIndex is not -1 and unitEndIndex is not -1: #x axis has a unit
            yAxisLabel = "Entries / " + str(Histogram.GetXaxis().GetBinWidth(1)) + " " + xAxisLabel[unitBeginIndex+1:unitEndIndex]
            xAxisLabelVar = xAxisLabel[0:unitBeginIndex]
        else:
            yAxisLabel = "Entries per bin (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " width)"
        if arguments.normalizeToUnitArea:
            yAxisLabel = yAxisLabel + " (Unit Area Norm.)"

        if arguments.normalizeToUnitArea and arguments.makeSignificancePlots:
            unit = "Efficiency"
        else:
            unit = "Yield"
        if integrateDir is "left":
            yAxisLabel = unit + ", " + xAxisLabelVar + "< x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
        if integrateDir is "right":
            yAxisLabel = unit + ", " + xAxisLabelVar + "> x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
                                                        
        
        if not arguments.makeFancy and not arguments.generic:  
            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)

        if arguments.normalizeToUnitArea and Histogram.Integral() > 0:
            Histogram.Scale(1./Histogram.Integral())

        Histogram = MakeIntegralHist(Histogram, integrateDir)
            
        LegendEntries.append(source['legend_entry']) 
        Histograms.append(Histogram)

            
    ### 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
    for histogram in Histograms:
        currentMax = histogram.GetMaximum() + histogram.GetBinError(histogram.GetMaximumBin())
        if(currentMax > finalMax):
            finalMax = currentMax
    finalMax = 1.5*finalMax
    if arguments.setYMax:  
        finalMax = float(arguments.setYMax)

    ### Drawing histograms to canvas

    makeRatioPlots = arguments.makeRatioPlots
    makeDiffPlots = arguments.makeDiffPlots
    #makeSignifPlots = arguments.makeSignificancePlots
    
    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.generic:
        plotting_options = "p,e" 
    if arguments.plot_hist:
        plotting_options = "HIST"

    for histogram in Histograms:
        histogram.SetTitle(histoTitle)
        if arguments.verbose:
            print "Debug:  drawing hist " + histogram.GetName() + ", with plotting_options = " + plotting_options + ", with mean = " + str(histogram.GetMean()) + ", with color = " + str(histogram.GetLineColor())    
        histogram.Draw(plotting_options)
        histogram.GetXaxis().SetTitle(xAxisLabel)
        histogram.GetYaxis().SetTitle(yAxisLabel)
        histogram.SetMaximum(finalMax)
        histogram.SetMinimum(yAxisMin)
        if makeRatioPlots or makeDiffPlots:
            histogram.GetXaxis().SetLabelSize(0)
        if histCounter is 0:
            plotting_options = plotting_options + " SAME"
        histCounter = histCounter + 1

    #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()


    # Deciding which text labels to draw and drawing them
    drawHeaderLabel = False

    if arguments.makeFancy:
        drawHeaderLabel = True

    #now that flags are set, draw the appropriate labels

    if drawHeaderLabel:
        HeaderLabel.Draw()




    #drawing the ratio or difference plot if requested

    if makeRatioPlots or makeDiffPlots:
        Canvas.cd(2)
        if makeRatioPlots:
            if arguments.ratioRelErrMax:
                Comparison = ratioHistogram(Histograms[0],Histograms[1],float(arguments.ratioRelErrMax))
            else:
                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("comparison_histograms_pdfs/"+histogramName+".pdf")