def EMTFEta(plotter):
## variables for the plot
xTitle = "Generated muon |#eta|"
title = "%s;%s;%s" % (topTitle, xTitle, yTitle)
toPlot = "TMath::Abs(%s)" % (geneta)
h_bins = "(20,1.2,2.4)"
nBins = int(h_bins[1:-1].split(',')[0])
minBin = float(h_bins[1:-1].split(',')[1])
maxBin = float(h_bins[1:-1].split(',')[2])
c = newCanvas()
gPad.SetGridx(xGrid)
gPad.SetGridy(yGrid)
base = TH1F("base", title, nBins, minBin, maxBin)
base.SetMinimum(0)
base.SetMaximum(plotter.yMax)
base.GetXaxis().SetLabelSize(0.05)
base.GetYaxis().SetLabelSize(0.05)
base.GetXaxis().SetTitleSize(0.05)
base.GetYaxis().SetTitleSize(0.05)
base.Draw("")
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
denom_cut = AND(ok_eta(1.2, 2.4), ok_2_csc_lcts())
h1 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>20")), ok_emtf(20),
"same", kBlue)
h2 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>15")), ok_emtf(15),
"same", kRed)
h3 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>10")), ok_emtf(10),
"same", kGreen + 2)
h4 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>5")), ok_emtf(5),
"same", kOrange + 2)
h5 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>3")), ok_emtf(0),
"same", kBlack)
leg = TLegend(0.45, 0.2, .75, 0.5, "", "brNDC")
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetTextSize(0.05)
leg.SetHeader("EMTF")
leg.AddEntry(h1, "p_{T} > 20 GeV", "l")
leg.AddEntry(h2, "p_{T} > 15 GeV", "l")
leg.AddEntry(h3, "p_{T} > 10 GeV", "l")
leg.AddEntry(h4, "p_{T} > 5 GeV", "l")
leg.AddEntry(h5, "p_{T} > 0 GeV", "l")
leg.Draw("same")
c.Print("%sEff_EMTF_eta_Pt20_%s" %
(plotter.targetDir + subdirectory, plotter.ext))
del c, base, h1, leg, h2, h3, h4, h5
def drawStavePlots(detector, det):
from ROOT import TCanvas
from ROOT import TH1F
from ROOT import gPad
StavePlots = {}
if det == 1:
Lay = [0, 1, 2]
Phi = [22, 38, 52]
detname = "PIX"
if det == 2:
Lay = [0, 1, 2, 3]
Phi = [32, 40, 48, 56]
detname = "SCT"
ncanvas = 0
for lay in Lay:
for phi in range(Phi[lay]):
StavePlots[ncanvas] = TCanvas(
"Stave%sPlots_L%d_Phi%d" % (detname, lay, phi),
"Stave Plots %s L%d Phi%d" % (detname, lay, phi))
StavePlots[ncanvas].Divide(3, 2)
stavemodules = detector.ReturnModules(det, 0, lay, phi)
hStaveCorrections = {}
for i in range(6):
StavePlots[ncanvas].cd(i + 1)
name, value = detector.GetModule(0).GetDoF(i)
hname = 'Stave_%s_L%d_Phi%d_%s_corrections' % (detname, lay,
phi, name)
htitle = 'Stave %s L%d Phi%d %s Corrections' % (detname, lay,
phi, name)
hStaveCorrections[name] = TH1F(hname, htitle,
len(stavemodules), 0,
len(stavemodules))
if name is 'Tx' or name is 'Ty' or name is 'Tz' or name is 'Bx':
hStaveCorrections[name].SetYTitle("mm")
else:
hStaveCorrections[name].SetYTitle("mrad")
bin = 1
for mod in stavemodules:
hStaveCorrections[name].SetBinContent(
bin,
detector.GetModule(mod).GetDoF(i)[1])
bin = bin + 1
#hStaveCorrections[name].Draw()
XAxis = hStaveCorrections[name].GetXaxis()
XAxis.CenterLabels()
bin = 1
for mod in stavemodules:
XAxis.SetBinLabel(bin, str(detector.GetModule(mod).Eta))
bin = bin + 1
hStaveCorrections[name].SetStats(False)
hStaveCorrections[name].DrawCopy()
gPad.SetGridx()
gPad.SetGridy()
ncanvas = ncanvas + 1
return StavePlots
def setpad(left, right, top, bottom):
gPad.SetFillColor(10)
gPad.SetBorderMode(0)
gPad.SetBorderSize(0)
gPad.SetFrameFillColor(10)
gPad.SetFrameBorderMode(0)
gPad.SetFrameBorderSize(0)
gPad.SetLeftMargin(left)
gPad.SetRightMargin(right)
gPad.SetTopMargin(top)
gPad.SetBottomMargin(bottom)
gPad.SetGridx(0)
gPad.SetGridy(0)
gStyle.SetOptStat(0)
def drawSctBarrelCorrDistributions(detector):
from ROOT import TCanvas
from ROOT import TH1F
from ROOT import gPad
SctBarrelCorrDistributions = TCanvas(
"SctBarrelCorrDistributions", "SCT Barrel Corrections Distributions")
SctBarrelCorrDistributions.Divide(3, 2)
hSctBarrelCorrDistributions = {}
detname = "SCT Barrel"
Color = AutoColors(len(detector))
for d in detector:
hSctBarrelCorrDistributions[d] = {}
for i in range(6):
SctBarrelCorrDistributions.cd(i + 1)
name, value = detector[d].GetModule(0).GetDoF(i)
hname = '%s_%sCorrections_%d' % (detname, name, d)
htitle = '%s %s Corrections' % (detname, name)
if name is 'Tx':
hSctBarrelCorrDistributions[d][name] = TH1F(
hname, htitle, 50, -0.005, 0.005)
elif name is 'Ty':
hSctBarrelCorrDistributions[d][name] = TH1F(
hname, htitle, 50, -0.1, 0.1)
else:
hSctBarrelCorrDistributions[d][name] = TH1F(
hname, htitle, 50, -0.25, 0.25)
if name is 'Tx' or name is 'Ty' or name is 'Tz' or name is 'Bx':
hSctBarrelCorrDistributions[d][name].GetXaxis().SetTitle(
name + " (mm)")
else:
hSctBarrelCorrDistributions[d][name].GetXaxis().SetTitle(
name + " (mrad)")
hSctBarrelCorrDistributions[d][name].GetYaxis().SetTitle("Modules")
hSctBarrelCorrDistributions[d][name].SetLineColor(Color[d])
for module in detector[d].ReturnSctBarrelModules():
hSctBarrelCorrDistributions[d][name].Fill(module.GetDoF(i)[1])
if d == 0:
hSctBarrelCorrDistributions[d][name].Draw()
else:
hSctBarrelCorrDistributions[d][name].Draw("Same")
gPad.SetGridx()
gPad.SetGridy()
SctBarrelCorrDistributions.Update()
return SctBarrelCorrDistributions, hSctBarrelCorrDistributions
def drawCorrVsHits(detector):
from ROOT import TCanvas
from ROOT import TGraph
from array import array
from ROOT import gPad
CorrVsHits = TCanvas("CorrVsHits", "Alignment Corrections vs hits")
CorrVsHits.Divide(3, 2)
hCorrVsHits = {}
Color = AutoColors(len(detector))
for det in detector:
hCorrVsHits[det] = {}
for i in range(6):
CorrVsHits.cd(i + 1)
name, value = detector[det].GetModule(0).GetDoF(i)
hname = 'CorrVsHits_%s_corrections_%d' % (name, det)
htitle = '%s Corrections vs hits_%d' % (name, det)
xpoints = []
ypoints = []
for j in range(detector[det].nModules()):
xpoints.append(detector[det].GetModule(j).Hits)
ypoints.append(detector[det].GetModule(j).GetDoF(i)[1])
x = array("f", xpoints)
y = array("f", ypoints)
hCorrVsHits[det][name] = TGraph(detector[det].nModules(), x, y)
hCorrVsHits[det][name].SetTitle(htitle)
hCorrVsHits[det][name].GetXaxis().SetTitle("Hits per module")
hCorrVsHits[det][name].GetYaxis().SetTitle(name)
if name is 'Tx' or name is 'Ty' or name is 'Tz' or name is 'Bx':
hCorrVsHits[det][name].GetYaxis().SetTitle(name + " (mm)")
else:
hCorrVsHits[det][name].GetYaxis().SetTitle(name + " (mrad)")
hCorrVsHits[det][name].SetMarkerStyle(4)
hCorrVsHits[det][name].SetMarkerSize(0.5)
hCorrVsHits[det][name].SetMarkerColor(Color[det])
if det == 0:
hCorrVsHits[det][name].Draw("Ap")
else:
hCorrVsHits[det][name].Draw("psame")
gPad.SetGridx()
gPad.SetGridy()
gPad.SetLogx()
CorrVsHits.Update()
return CorrVsHits, hCorrVsHits
def rooFit109():
print ">>> setup model..."
x = RooRealVar("x", "x", -10, 10)
sigma = RooRealVar("sigma", "sigma", 3, 0.1, 10)
mean = RooRealVar("mean", "mean", 0, -10, 10)
gauss = RooGaussian("gauss", "gauss", x, RooConst(0),
sigma) # RooConst(0) gives segfaults
data = gauss.generate(RooArgSet(x), 100000) # RooDataSet
#sigma = 3.15 # overwrites RooRealVar with a float
sigma.setVal(3.15)
print ">>> plot data and slightly distorted model..."
frame1 = x.frame(Title("Data with distorted Gaussian pdf"),
Bins(40)) # RooPlot
data.plotOn(frame1, DataError(RooAbsData.SumW2))
gauss.plotOn(frame1)
print ">>> calculate chi^2..."
# Show the chi^2 of the curve w.r.t. the histogram
# If multiple curves or datasets live in the frame you can specify
# the name of the relevant curve and/or dataset in chiSquare()
print ">>> chi^2 = %.2f" % frame1.chiSquare()
print ">>> construct histograms with the residuals and pull of the data wrt the curve"
hresid = frame1.residHist() # RooHist
hpull = frame1.pullHist() # RooHist
frame2 = x.frame(Title("Residual Distribution")) # RooPlot
frame2.addPlotable(hresid, "P")
frame3 = x.frame(Title("Pull Distribution")) # RooPlot
frame3.addPlotable(hpull, "P")
print ">>> draw functions and toy data on canvas..."
canvas = TCanvas("canvas", "canvas", 100, 100, 2000, 400)
canvas.Divide(3)
for i, frame in enumerate([frame1, frame2, frame3], 1):
canvas.cd(i)
gPad.SetLeftMargin(0.14)
gPad.SetRightMargin(0.04)
frame.GetYaxis().SetTitleOffset(1.5)
frame.GetYaxis().SetLabelOffset(0.010)
frame.GetYaxis().SetTitleSize(0.045)
frame.GetYaxis().SetLabelSize(0.042)
frame.GetXaxis().SetTitleSize(0.045)
frame.GetXaxis().SetLabelSize(0.042)
frame.Draw()
canvas.SaveAs("rooFit109.png")
canvas.Close()
# ratio/pull/residual plot
print ">>> draw with pull plot..."
canvas = TCanvas("canvas", "canvas", 100, 100, 1000, 1000)
canvas.Divide(2)
canvas.cd(1)
gPad.SetPad("pad1", "pad1", 0, 0.33, 1, 1, 0, -1, 0)
gPad.SetTopMargin(0.10)
gPad.SetBottomMargin(0.03)
gPad.SetLeftMargin(0.14)
gPad.SetRightMargin(0.04)
gPad.SetBorderMode(0)
gStyle.SetTitleFontSize(0.062)
frame1.GetYaxis().SetTitle("Events / %.3g GeV" % frame1.getFitRangeBinW())
frame1.GetYaxis().SetTitleSize(0.059)
frame1.GetYaxis().SetTitleOffset(1.21)
#frame1.GetYaxis().SetLabelOffset(0.010)
frame1.GetXaxis().SetLabelSize(0)
frame1.GetYaxis().SetLabelSize(0.045)
frame1.Draw()
canvas.cd(2)
gPad.SetPad("pad2", "pad2", 0, 0, 1, 0.33, 0, -1, 0)
gPad.SetTopMargin(0.01)
gPad.SetBottomMargin(0.30)
gPad.SetLeftMargin(0.14)
gPad.SetRightMargin(0.04)
gPad.SetBorderMode(0)
gPad.SetGridy(kTRUE)
line1 = TLine(frame3.GetXaxis().GetXmin(), 0,
frame3.GetXaxis().GetXmax(), 0)
line2 = TLine(frame3.GetXaxis().GetXmin(), 0,
frame3.GetXaxis().GetXmax(), 0)
line1.SetLineColor(0) # white to clear dotted grid lines
line2.SetLineColor(12) # dark grey
line2.SetLineStyle(2)
frame3.SetTitle("")
frame3.GetYaxis().SetTitle("pull")
frame3.GetXaxis().SetTitle("#Deltam^{2}_{ll} [GeV]")
frame3.GetXaxis().SetTitleSize(0.13)
frame3.GetYaxis().SetTitleSize(0.12)
frame3.GetXaxis().SetTitleOffset(1.0)
frame3.GetYaxis().SetTitleOffset(0.58)
frame3.GetXaxis().SetLabelSize(0.10)
frame3.GetYaxis().SetLabelSize(0.10)
frame3.GetXaxis().SetLabelOffset(0.02)
frame3.GetYaxis().SetLabelOffset(0.01)
frame3.GetYaxis().SetRangeUser(-5, 5)
frame3.GetYaxis().CenterTitle(True)
frame3.GetYaxis().SetNdivisions(505)
frame3.Draw("")
line1.Draw("SAME")
line2.Draw("SAME")
frame3.Draw("SAME")
canvas.SaveAs("rooFit109_ratiolike.png")
canvas.Close()
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 MakeOneDHist(histogramDirectory, histogramName,integrateDir):
if arguments.verbose:
print "Creating histogram", histogramName, "in directory", histogramDirectory
HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetTextFont(42)
HeaderLabel.SetTextSize(0.697674)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
CMSLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
CMSLabel.SetTextAlign(32)
CMSLabel.SetTextFont(42)
CMSLabel.SetTextSize(0.697674)
CMSLabel.SetBorderSize(0)
CMSLabel.SetFillColor(0)
CMSLabel.SetFillStyle(0)
if makeFancy:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,"CMS Preliminary","NDC")
LumiLabel.SetTextFont(62)
LumiLabel.SetTextSize(0.7)
LumiLabel.SetTextAlign(12)
else:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
LumiLabel.SetTextAlign(32)
LumiLabel.SetTextFont(42)
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
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 = []
RefIndex = -99
LegendEntries = []
colorIndex = 0
markerStyleIndex = 0
fillIndex = 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:
if histogramDirectory == "":
histPath = histogramName
else:
histPath = histogramDirectory + "/" + histogramName
HistogramObj = inputFile.Get(histPath)
else:
HistogramObj = inputFile.Get(source['channel'] + "Plotter/" + histogramDirectory + "/" + 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()
Histogram.Sumw2()
if arguments.verbose:
print " Got histogram", Histogram.GetName(), "from file", dataset_file
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)
# correct bin contents of object multiplcity plots
if Histogram.GetName().startswith("num") and "PV" not in Histogram.GetName():
# include overflow bin
for bin in range(2,Histogram.GetNbinsX()+2):
content = Histogram.GetBinContent(bin)
Histogram.SetBinContent(bin, content/float(bin-1))
xAxisLabel = Histogram.GetXaxis().GetTitle()
unitBeginIndex = xAxisLabel.find("[")
unitEndIndex = xAxisLabel.find("]")
xAxisLabelVar = xAxisLabel
if "_pfx" in Histogram.GetName() or "_pfy" in Histogram.GetName() or "_sigma" in Histogram.GetName():
yAxisLabel = Histogram.GetYaxis().GetTitle()
else:
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)"
nbins = Histogram.GetNbinsX()
if not noOverFlow:
Histogram.SetBinContent(nbins, Histogram.GetBinContent(nbins) + Histogram.GetBinContent(nbins+1)) # Add overflow
Histogram.SetBinError(nbins, math.sqrt(math.pow(Histogram.GetBinError(nbins),2) + math.pow(Histogram.GetBinError(nbins+1),2))) # Set the errors to be the sum in quadrature
if not noUnderFlow:
Histogram.SetBinContent(1, Histogram.GetBinContent(1) + Histogram.GetBinContent(0)) # Add underflow
Histogram.SetBinError(1, math.sqrt(math.pow(Histogram.GetBinError(1), 2) + math.pow(Histogram.GetBinError(0), 2))) # Set the errors to be the sum in quadrature
if not arguments.makeFancy and not arguments.generic:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
if len(splitTitle) > 1:
histoTitle = splitTitle[1].lstrip(" ")
else:
histoTitle = splitTitle[0]
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
markerStyleIndex = markerStyleIndex + 1
if markerStyleIndex is len(markerStyleList):
markerStyleIndex = 0
fillIndex = fillIndex + 1
if 'scale' in source:
Histogram.Scale(source['scale'])
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
else:
markerStyle = markers[markerStyleList[markerStyleIndex]]
fillStyle = 0
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
else:
markerStyle = markerStyle + fills[fillList[fillIndex]]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetMarkerSize(0.5)
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)
if 'reference' in source:
if source['reference']:
RefIndex = len(Histograms)-1
### formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
# Legend.AddEntry(histogram,LegendEntries[legendIndex],"P")
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
addOneToRatio = -1
if arguments.addOneToRatio:
addOneToRatio = arguments.addOneToRatio
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 " 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)
if "_pfx" not in Histogram.GetName() and "_pfy" not in Histogram.GetName() and "_sigma" not in Histogram.GetName():
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
if arguments.makeFancy:
HeaderLabel.Draw()
LumiLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Comparisons = []
Canvas.cd(2)
if RefIndex == -99:
Reference = Histograms[0]
else:
Reference = Histograms[RefIndex]
for Histogram in Histograms:
if Histogram is Reference:
continue
if makeRatioPlots:
makeRatio = functools.partial (ratioHistogram,Histogram, Reference)
if arguments.ratioRelErrMax is not -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, relErrMax = float(arguments.ratioRelErrMax))
if addOneToRatio != -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, addOne = bool (addOneToRatio))
Comparison = makeRatio()
elif makeDiffPlots:
Comparison = Reference.Clone("diff")
Comparison.Add(Histograms[1],-1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("X-ref")
Comparison.SetLineColor(Histogram.GetLineColor())
Comparison.SetFillColor(Histogram.GetFillColor())
Comparison.SetFillStyle(Histogram.GetFillStyle())
Comparison.SetMarkerColor(Histogram.GetMarkerColor())
Comparison.SetMarkerStyle(Histogram.GetMarkerStyle())
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)
if addOneToRatio == -1: # it gets initialized to this dummy value of -1
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange, RatioYRange)
else:
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange + 1.0, RatioYRange + 1.0)
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)
Comparisons.append(Comparison)
option = "E0"
for index,Comparison in enumerate(Comparisons):
if index == 0:
option += " SAME"
Comparison.Draw(option)
outputFile.cd(histogramDirectory)
Canvas.Write()
if arguments.verbose:
print " Finished writing canvas: ", Canvas.GetName()
if arguments.savePDFs:
Canvas.SaveAs("comparison_histograms_pdfs/"+histogramName+".pdf")
def MakeOneHist(dirName, histogramName):
HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetTextFont(42)
HeaderLabel.SetTextSize(0.697674)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
CMSLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
CMSLabel.SetTextAlign(32)
CMSLabel.SetTextFont(42)
CMSLabel.SetTextSize(0.697674)
CMSLabel.SetBorderSize(0)
CMSLabel.SetFillColor(0)
CMSLabel.SetFillStyle(0)
if makeFancy:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,"CMS Preliminary","NDC")
LumiLabel.SetTextFont(62)
LumiLabel.SetTextSize(0.7)
LumiLabel.SetTextAlign(12)
else:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
LumiLabel.SetTextAlign(32)
LumiLabel.SetTextFont(42)
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
#legend coordinates, empirically determined :-)
x_left = 0.4
x_right = 0.7
y_min = 0.15
y_max = 0.3
Legend = TLegend(x_left,y_min,x_right,y_max)
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas(histogramName)
Histograms = []
HistogramClones = []
NBins = []
MaxXValues = []
MinXValues = []
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(source['num_channel'] + "Plotter/" + dirName + "/" + 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(source['den_channel'] + "Plotter/" + dirName + "/" + histogramName)
else: # Default is to use the same condor directory
DenHistogramObj = inputFile.Get(source['den_channel'] + "Plotter/" + dirName + "/" + histogramName)
if not NumHistogramObj:
print "WARNING: Could not find histogram " + source['num_channel'] + "Plotter/" + dirName + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
if not DenHistogramObj:
print "WARNING: Could not find histogram " + source['den_channel'] + "Plotter/" + dirName + "/" + 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()
nbinsN = Histogram.GetNbinsX()
nbinsD = DenHistogram.GetNbinsX()
if not noOverFlow:
# Add overflow
Histogram.SetBinContent( nbinsN, Histogram.GetBinContent(nbinsN) + Histogram.GetBinContent(nbinsN+1))
DenHistogram.SetBinContent(nbinsD, DenHistogram.GetBinContent(nbinsD) + DenHistogram.GetBinContent(nbinsD+1))
# Set the errors to be the sum in quadrature
Histogram.SetBinError( nbinsN, math.sqrt(math.pow(Histogram.GetBinError(nbinsN),2) + math.pow(Histogram.GetBinError(nbinsN+1),2)))
DenHistogram.SetBinError(nbinsD, math.sqrt(math.pow(DenHistogram.GetBinError(nbinsD),2) + math.pow(DenHistogram.GetBinError(nbinsD+1),2)))
if not noUnderFlow:
# Add underflow
Histogram.SetBinContent( 1, Histogram.GetBinContent(1) + Histogram.GetBinContent(0))
DenHistogram.SetBinContent(1, DenHistogram.GetBinContent(1) + DenHistogram.GetBinContent(0))
# Set the errors to be the sum in quadrature
Histogram.SetBinError( 1, math.sqrt(math.pow(Histogram.GetBinError(1), 2) + math.pow(Histogram.GetBinError(0), 2)))
DenHistogram.SetBinError(1, math.sqrt(math.pow(DenHistogram.GetBinError(1), 2) + math.pow(DenHistogram.GetBinError(0), 2)))
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.)"
#check if bin content is consistent
TEfficiency.CheckConsistency(Histogram,DenHistogram)
for i in range(1,Histogram.GetNbinsX()+1):
if Histogram.GetBinContent(i) > DenHistogram.GetBinContent(i):
DenHistogram.SetBinContent(i,Histogram.GetBinContent(i))
#HistogramClone and HistogramClones only used for ratio plot
HistogramClone = Histogram.Clone()
HistogramClone.SetDirectory(0)
HistogramClone.Divide(DenHistogram)
Nbins = HistogramClone.GetNbinsX()
MaxXValue = HistogramClone.GetXaxis().GetBinLowEdge(Nbins+1)
MinXValue = HistogramClone.GetXaxis().GetBinLowEdge(1)
#this Histogram becomes the main TEfficiency
if Histogram.Class().InheritsFrom("TH2"):
Histogram.Divide(DenHistogram)
else:
#using default methods (which give correct uncertainties)
#see https://root.cern.ch/doc/master/classTEfficiency.html (c.f. section IV)
Histogram = TEfficiency(Histogram,DenHistogram)
if not arguments.makeFancy:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
# print splitTitle
if len(splitTitle) > 1:
histoTitle = splitTitle[1].lstrip(" ")
else:
histoTitle = splitTitle[0]
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)
HistogramClones.append(HistogramClone)
NBins.append(Nbins)
MaxXValues.append(MaxXValue)
MinXValues.append(MinXValue)
### 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 = 1.1
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
addOneToRatio = -1
if arguments.addOneToRatio:
addOneToRatio = arguments.addOneToRatio
dontRebinRatio = -1
if arguments.dontRebinRatio:
dontRebinRatio = arguments.dontRebinRatio
ratioRelErrMax = -1
if arguments.ratioRelErrMax:
ratioRelErrMax = arguments.ratioRelErrMax
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"
h = TH2F("h1","",NBins[0],MinXValues[0],MaxXValues[0],110,0.,finalMax)
h.SetTitle(";"+xAxisLabel+";"+yAxisLabel)
h.Draw()
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()
else:
if histogram.InheritsFrom("TEfficiency") and histCounter==0:
plotting_options = "P SAME"
histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TEfficiency"):
plotting_options = "P" + " SAME"
histCounter = histCounter + 1
if histogram.Class().InheritsFrom("TH2"):
return
Legend.Draw()
if arguments.makeFancy:
HeaderLabel.Draw()
LumiLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
makeRatio = functools.partial (ratioHistogram,HistogramClones[0],HistogramClones[1])
if addOneToRatio != -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, addOne = bool (addOneToRatio))
if ratioRelErrMax is not -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, relErrMax = float (ratioRelErrMax))
if dontRebinRatio is True:
makeRatio = functools.partial (makeRatio, dontRebinRatio)
Comparison = makeRatio ()
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)
if addOneToRatio == -1: # it gets initialized to this dummy value of -1
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange, RatioYRange)
else:
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange + 1.0, RatioYRange + 1.0)
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(dirName)
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/"+histogramName+".pdf")
def OLD_drawCorrEvolution(detector,
labelList,
drawErrors=False,
drawLine=True,
whichdof=-1):
from ROOT import TCanvas
from ROOT import TH1F
from ROOT import gPad
from ROOT import TLegend
doDebug = True
showErrors = True
drawAllDofs = True
nUsedDofs = 6
if (whichdof != -1):
drawAllDofs = False
if (whichdof > 5):
nUsedDofs = 7 # 7/oct/2015 with the BowX we may have up to 7 dofs. Unless stated draw the ordinary 6.
lowerDof = 0
upperDof = 5
if (not drawAllDofs):
lowerDof = whichdof
upperDof = whichdof
# a canvas for all dofs
ThisCanvas = TCanvas("AlignmentCorrectionsEvol",
"Evolution of alignment corrections (All)")
if (drawAllDofs): ThisCanvas.Divide(3, 2)
hCorrectionsEvol = {}
hCorrectionsEvolStruct = {}
yrange = [0.002, 0.002, 0.002, 0.01, 0.01, 0.01,
0.002] # minimum is 0.001 (mm or mrad)
# here detector = num of iterations
numOfIterations = len(detector)
if (doDebug): print " numOfIterations=", numOfIterations
numOfAlignableStruct = detector[0].nModules()
if (doDebug): print " numOfAlignableStructe=", numOfAlignableStruct
EvolColor = AutoColors(numOfAlignableStruct)
# find out range
#for i in range(lowerDof, upperDof):
for i in range(nUsedDofs):
for iter in range(numOfIterations):
for bin in range(detector[iter].nModules()):
thisValue = abs(detector[iter].GetModule(bin).GetDoF(
i)[1]) + detector[iter].GetModule(bin).GetDoFError(i)[1]
if abs(thisValue) > yrange[i]:
yrange[i] = thisValue
yrange[i] *= 1.025
if (doDebug): print " dof=", i, " --> range: ", yrange[i]
# maximum range
maxTransRange = 0.100
if (yrange[0] > maxTransRange): yrange[0] = maxTransRange
if (yrange[1] > maxTransRange): yrange[1] = maxTransRange
if (yrange[2] > maxTransRange): yrange[2] = maxTransRange
#yrange[0] = 0.04
#yrange[1] = 0.04
# Tx and Ty should have the same range
if (yrange[0] > yrange[1]):
yrange[1] = yrange[0]
else:
yrange[0] = yrange[1]
# Tz range should be as minimum as Tx and Ty
if (yrange[2] < yrange[0]): yrange[2] = yrange[0]
# Rx and Ry should have the same range
if (yrange[3] > yrange[4]):
yrange[4] = yrange[3]
else:
yrange[3] = yrange[4]
# Rz range should be as minimum as Rx and Ry
#if (yrange[5] < yrange[3]): yrange[5] = yrange[3]
# prepare the legend
myLegend = TLegend(0.65, 0.65, 0.92, 0.92)
# loop dof by dof (Tx, Ty...) and fill a polyline with teh corrections for each iteration
if (doDebug):
print " ** drawCorrEvolution ** lowerDof=", lowerDof, " upperDof = ", upperDof
#for dof in range(nUsedDofs):
for dof in range(lowerDof, upperDof + 1):
if (doDebug):
print " ** drawCorrEvolution ** going to draw dof=", dof
ThisCanvas.cd()
if (drawAllDofs):
ThisCanvas.cd(dof + 1)
name = detector[0].GetModule(0).GetDoF(dof)[0]
hname = 'Dof_%s_corrections_Evol' % (name)
htitle = 'Corrections evolution for %s' % (name)
if (doDebug):
print " ** drawCorrEvolution ** dof=", dof, " hname = ", hname
print " htitle = ", htitle
# this histogram is the main frame
hCorrectionsEvol[dof] = TH1F(hname, htitle, numOfIterations - 1, -0.5,
numOfIterations * 1. - 1.5)
# set the x axis labels
if (numOfIterations > 12):
hCorrectionsEvol[dof].GetXaxis().SetLabelSize(0.03)
hCorrectionsEvol[dof].GetXaxis().SetBit(18)
for iter in range(numOfIterations -
1): # -1 do not include the total sum in the plot
hCorrectionsEvol[dof].GetXaxis().SetBinLabel(
iter + 1, 'Iter_%d' % (iter))
if (len(labelList) > iter): # use label given by user
hCorrectionsEvol[dof].GetXaxis().SetBinLabel(
iter + 1, labelList[iter])
# label Y axis
if name is 'Tx' or name is 'Ty' or name is 'Tz' or name is 'Bx':
hCorrectionsEvol[dof].SetYTitle("mm")
else:
hCorrectionsEvol[dof].SetYTitle("mrad")
hCorrectionsEvol[dof].GetYaxis().SetRangeUser(-yrange[dof],
yrange[dof])
hCorrectionsEvol[dof].SetStats(False)
hCorrectionsEvol[dof].DrawCopy()
gPad.SetGridx()
gPad.SetGridy()
#once the frame is plotted, loop on every structure and fill a histogram and draw it
print " .. dealing with", name, "corrections .. with range for this dof: (", dof, ") range: +-", yrange[
dof]
print " ** ==> numOfAlignableStruct = ", numOfAlignableStruct
for struct in range(numOfAlignableStruct):
#for struct in range(0,2):
if (doDebug): print " >> looping on struct:", struct
hCorrectionsEvolStruct[dof] = {}
hname = 'Dof_%s_corrections_Evol_struct_%d' % (name, struct)
htitle = 'Corrections evolution for structure %s (struct %d)' % (
name, struct)
hCorrectionsEvolStruct[dof][struct] = TH1F(
hname, htitle, numOfIterations, -0.5,
numOfIterations * 1. - 0.5)
hCorrectionsEvolStruct[dof][struct].SetLineColor(EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].SetStats(False)
# once the histogram is created, fill it with the corrections of each iteration
accumvalue = 0
for iter in range(numOfIterations -
1): # -1 to account for the overall integration
value = detector[iter].GetModule(struct).GetDoF(dof)[1]
accumvalue = accumvalue + value
# if (doDebug): print " dof:",dof, " struct:",struct," iter:",iter," delta=",value
hCorrectionsEvolStruct[dof][struct].SetBinContent(
iter + 1, value)
# if (doDebug): print "hCorrectionsEvolStruct[",dof,"][",struct,"].SetBinContent(",iter+1,",", value,")"
if (drawErrors):
hCorrectionsEvolStruct[dof][struct].SetBinError(
iter + 1,
detector[iter].GetModule(struct).GetDoFError(dof)[1])
# now draw the corrections for this structure
if (doDebug): print "Accumulated", hname, ":", accumvalue
# store the accumulated
if (dof == 0):
detector[numOfIterations -
1].GetModule(struct).setTx(accumvalue)
if (dof == 1):
detector[numOfIterations -
1].GetModule(struct).setTy(accumvalue)
if (dof == 2):
detector[numOfIterations -
1].GetModule(struct).setTz(accumvalue)
if (dof == 3):
detector[numOfIterations -
1].GetModule(struct).setRx(accumvalue)
if (dof == 4):
detector[numOfIterations -
1].GetModule(struct).setRy(accumvalue)
if (dof == 5):
detector[numOfIterations -
1].GetModule(struct).setRz(accumvalue)
if (dof == 6):
detector[numOfIterations -
1].GetModule(struct).setBx(accumvalue)
if (drawErrors):
hCorrectionsEvolStruct[dof][struct].SetFillColor(
EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].SetFillStyle(3354)
# hCorrectionsEvolStruct[dof][struct].DrawCopy('same e3')
# --> original hCorrectionsEvolStruct[dof][struct].DrawCopy('same e3')
hCorrectionsEvolStruct[dof][struct].SetMarkerStyle(20)
hCorrectionsEvolStruct[dof][struct].SetMarkerSize(0.5)
hCorrectionsEvolStruct[dof][struct].SetMarkerColor(
EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].DrawCopy('same p e3 x0')
for iter in range(numOfIterations - 1):
hCorrectionsEvolStruct[dof][struct].SetBinError(
iter + 1, 0)
hCorrectionsEvolStruct[dof][struct].SetFillStyle(0)
hCorrectionsEvolStruct[dof][struct].DrawCopy('same l')
else:
myOption = "same"
if (drawLine):
myOption += " l"
else:
myOption += " p"
hCorrectionsEvolStruct[dof][struct].SetMarkerStyle(20)
hCorrectionsEvolStruct[dof][struct].SetMarkerColor(
EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].DrawCopy(myOption)
gPad.Update()
if (dof == nUsedDofs - 1 and False):
myLegend.AddEntry(hCorrectionsEvolStruct[dof][struct],
detector[0].GetModule(struct).GetName(), "l")
myLegend.Draw()
gPad.Update()
return ThisCanvas
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")
def MakeOneHist(varXaxis, varConst, xvalues, constval):
if len(xvalues)<=1:
return # Do not make plot if there is only 1 xvalue
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas("sigEff_"+varConst+str(constval)+"_vs_"+varXaxis)
Histograms = []
LegendEntries = []
colorIndex = 0
for source in input_sources: # loop over different input sources in config file
# print "Debug: running over input_source from: ", source['condor_dir'], " for varXaxis=", varXaxis, ", varConst=", varConst
# Create histogram of efficiencies with appropriate binning
xAxisBins = array('d')
xBinWidth = xvalues[1] - xvalues[0]
for xval in xvalues:
xAxisBins.append(xval - xBinWidth/2.0)
xAxisBins.append(xvalues[-1] + xBinWidth/2.0) # add an extra bin boundary for the last bin.
Histogram = TH1F("Histogram", ";x title;signal efficiency", len(xvalues), xAxisBins)
Histogram.SetDirectory(0)
# Now fill the histogram of efficiencies:
for xval in xvalues:
if varXaxis=="mass" and varConst=="lifetime":
mass = xval
lifetime = constval
elif varXaxis=="lifetime" and varConst=="mass":
lifetime = xval
mass = constval
else:
print "Unrecognized value of varXaxis=", varXaxis
return
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],dataset)
dataset_file = dataset_file.replace("MASS", str(mass))
dataset_file = dataset_file.replace("LIFETIME", str(lifetime))
inputFile = TFile(dataset_file)
HistCutflow = inputFile.Get("OSUAnalysis/" + source['channel'] + "CutFlow")
if not HistCutflow:
print "WARNING: Could not find histogram OSUAnalysis/" + source['channel'] + "CutFlow in file " + dataset_file + ". Will skip it and continue."
return
# calculate efficiency
nbinsCutflow = HistCutflow.GetNbinsX()
if arguments.xsecFile:
xsec = float(signal_cross_sections[str(mass)]['value'])
denom = xsec * intLumi
else:
denom = HistCutflow.GetBinContent(1) # denominator is the first entry in the cutflow histogram
eff = HistCutflow.GetBinContent(nbinsCutflow) / denom
effErr = HistCutflow.GetBinError (nbinsCutflow) / denom
ibin = Histogram.FindBin(xval)
Histogram.SetBinContent(ibin, eff)
Histogram.SetBinError (ibin, effErr)
print "Setting bin content for varConst = ", varConst, " = ", constval, " in ibin=", ibin, ", xval=", xval, ", eff=", eff, " +- ", effErr, ", fractional error =", effErr/eff, " numerator = ", HistCutflow.GetBinContent(nbinsCutflow), " denom = ", denom, " from file: ", dataset_file
inputFile.Close()
if varXaxis=="mass":
xAxisLabel = "chargino mass [GeV]"
elif varXaxis=="lifetime":
xAxisLabel = "chargino c#tau [cm]"
else:
print "Unrecognized value of varXaxis=", varXaxis
return
yAxisLabel = "efficiency"
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.SetMarkerSize(1)
# Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
# Finish loop over input_sources
# formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
# print "Adding entry to legend: ", LegendEntries[legendIndex]
# Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
Legend.AddEntry(histogram,LegendEntries[legendIndex],"P")
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())
currentMax = histogram.GetMaximum()
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 = 0.0
## 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 = "pe, x0" # x0 suppresses the error bar along x
## if arguments.plot_hist:
## plotting_options = "HIST"
for histogram in Histograms:
# 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
x_left = 0.15
x_right = 0.55
y_min = 0.6
y_max = 0.8
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
customText = "chargino " + varConst + " " + str(constval)
if varConst == "mass":
customText += " GeV"
elif varConst == "lifetime":
customText += " cm"
customText = customText.replace("lifetime", "c#tau")
CustomLabel = TPaveLabel(x_left, 0.8, x_right, 0.9, customText, "NDC")
CustomLabel.SetBorderSize(0)
CustomLabel.SetFillColor(0)
CustomLabel.SetFillStyle(0)
CustomLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
# Comparison = ratioHistogram(Histograms[0],Histograms[1], 1000)
Comparison = Histograms[0].Clone()
Comparison.Divide(Histograms[1])
Comparison.GetYaxis().SetTitle("ratio")
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(0.7, 1.3)
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")
Comparison.Draw("PE, X0") # X0 suppresses error bar in x direction
outputFile.cd()
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/"+histogramName+".pdf")
def drawAllCorr(detector):
from ROOT import TCanvas
from ROOT import TH1F
from ROOT import gPad
debug = False
if (debug): print " -- drawAllCorr -- starting for detector = ", detector
showErrors = True
Alldetector = TCanvas("AlignmentCorrections(All)",
"Alignment Corrections (All)")
Alldetector.Divide(3, 2)
AllCorrections = {}
yrange = [0, 0, 0, 0, 0, 0]
if (debug): print " -- drawAllCorr -- finding out histogram ranges... "
for i in range(6):
if (debug): print " -- drawAllCorr -- extracting range for dof:", i
for det in detector:
for bin in range(detector[det].nModules()):
#print " ** drawutils ** drawAllCorr ** det:",det," nModules = ",detector[det].nModules()
if abs(detector[det].GetModule(bin).GetDoF(i)[1]) > yrange[i]:
yrange[i] = abs(detector[det].GetModule(bin).GetDoF(i)[1])
yrange[i] *= 1.1
if (debug): print " -- drawAllCorr -- finding out colors ..."
Color = AutoColors(len(detector))
for det in detector:
for i in range(6):
Alldetector.cd(i + 1)
AllCorrections[det] = {}
name, value = detector[det].GetModule(0).GetDoF(i)
hname = 'All_%s_corrections_%d' % (name, det)
htitle = 'All %s Corrections_%d' % (name, det)
AllCorrections[det][name] = TH1F(hname, htitle,
detector[det].nModules(), 0,
detector[det].nModules())
if name is 'Tx' or name is 'Ty' or name is 'Tz' or name is 'Bx':
AllCorrections[det][name].SetYTitle("mm")
else:
AllCorrections[det][name].SetYTitle("mrad")
for bin in range(detector[det].nModules()):
AllCorrections[det][name].SetBinContent(
bin + 1, detector[det].GetModule(bin).GetDoF(i)[1])
if showErrors:
AllCorrections[det][name].SetBinError(
bin + 1,
detector[det].GetModule(bin).GetDoFError(i)[1])
if detector[det].nModules() < 35:
AllCorrections[det][name].GetXaxis().SetBinLabel(
bin + 1, detector[det].GetModule(bin).GetName())
#AllCorrections[det][name].SetMarkerStyle(20)
AllCorrections[det][name].SetMarkerColor(Color[det])
AllCorrections[det][name].SetLineColor(Color[det])
AllCorrections[det][name].SetFillColor(Color[det])
AllCorrections[det][name].SetFillStyle(1001)
AllCorrections[det][name].SetStats(False)
if det == 0:
AllCorrections[det][name].GetYaxis().SetRangeUser(
-yrange[i], yrange[i])
AllCorrections[det][name].DrawCopy()
else:
AllCorrections[det][name].DrawCopy('same')
gPad.SetGridx()
gPad.SetGridy()
gPad.Update()
return Alldetector
def drawL3CorrVsHits(detector, det, bec):
from ROOT import TCanvas
from ROOT import TGraph
from array import array
from ROOT import gPad
if det == 1:
if bec == None:
detname = "PIX"
elif bec == 0:
detname = "PIXBarrel"
elif bec == -1:
detname = "PIXECC"
elif bec == 1:
detname = "PIXECA"
elif det == 2:
if bec == None:
detname = "SCT"
elif bec == 0:
detname = "SCTBarrel"
elif bec == -1:
detname = "SCTECC"
elif bec == 1:
detname = "SCTECA"
L3CorrVsHits = TCanvas(detname + "CorrVsHits",
detname + " Alignment Corrections vs hits")
L3CorrVsHits.Divide(3, 2)
hCorrVsHits = {}
Color = AutoColors(len(detector))
for d in detector:
hCorrVsHits[d] = {}
for i in range(6):
L3CorrVsHits.cd(i + 1)
name, value = detector[d].GetModule(0).GetDoF(i)
hname = '%s_CorrVsHits_%s_corrections' % (detname, name)
htitle = '%s %s Corrections vs hits' % (detname, name)
xpoints = []
ypoints = []
for j in detector[d].ReturnModules(det, bec):
xpoints.append(detector[d].GetModule(j).Hits)
ypoints.append(detector[d].GetModule(j).GetDoF(i)[1])
x = array("f", xpoints)
y = array("f", ypoints)
hCorrVsHits[d][name] = TGraph(len(x), x, y)
hCorrVsHits[d][name].SetTitle(htitle)
hCorrVsHits[d][name].GetXaxis().SetTitle("Hits per module")
hCorrVsHits[d][name].GetYaxis().SetTitle(name)
if name is 'Tx' or name is 'Ty' or name is 'Tz' or name is 'Bx':
hCorrVsHits[d][name].GetYaxis().SetTitle(name + " (mm)")
else:
hCorrVsHits[d][name].GetYaxis().SetTitle(name + " (mrad)")
hCorrVsHits[d][name].SetMarkerStyle(4)
hCorrVsHits[d][name].SetMarkerSize(0.5)
hCorrVsHits[d][name].SetMarkerColor(Color[d])
if d == 0:
hCorrVsHits[d][name].Draw("Ap")
else:
hCorrVsHits[d][name].Draw("Ap")
gPad.SetGridx()
gPad.SetGridy()
L3CorrVsHits.Update()
return L3CorrVsHits, hCorrVsHits
def drawCorrEvolution(detector,
labelList,
drawErrors=False,
drawLine=True,
whichdof=-1,
outputFormat=1):
from ROOT import TCanvas
from ROOT import TH1F
from ROOT import gPad
from ROOT import TLegend
from ROOT import TLine
import time
import os
#check with environment variable if server runs as local test
runLocalTest = False
try:
runLocalTest = os.getenv('RUNLOCALTEST', False)
except:
runLocalTest = False
doDebug = True
showErrors = True
drawAllDofs = True
nUsedDofs = 7
if (whichdof != -1):
drawAllDofs = False
if (whichdof > 5):
nUsedDofs = 7 # 7/oct/2015 with the BowX we may have up to 7 dofs. Unless stated draw the ordinary 6.
lowerDof = 0
upperDof = 6
if (not drawAllDofs):
lowerDof = whichdof
upperDof = whichdof
# output formats
ALLINONE = 1
ONEBYONE = 2
SPLITBYSTRUCT = 3
Alldetector = {} # list of canvas
finalName = ["", "", "", "", "", "", ""] #name of the output files
gridALLENTRIES = 1
gridNEWRUN = 2
xGridType = gridNEWRUN
#
pathfiles = "."
if (runLocalTest):
pathfiles = "/Users/martis/projectes/atlas/alineament/webmonitoringtest/InDetAlignmentWebMonitor/trunk/WebPage/constant/"
plotfile = {}
rootSetup()
# -- start the body of the code --
if (doDebug):
print "\n -- drawCorrEvolution -- START -- \n"
print " runLocalTest= ", runLocalTest
print " pathfiles= ", pathfiles
print " outputFormat= ", outputFormat
# list of the histograms
hCorrectionsEvol = {}
hCorrectionsEvolStruct = {}
# min axis range for each dof
# Tx Ty Tz Rx Ry Rz Bx
yrange = [0.002, 0.002, 0.002, 0.01, 0.01, 0.01,
0.002] # minimum is 0.001 (mm or mrad)
# here detector = num of iterations
numberOfSamples = len(detector)
if (doDebug):
print " -- drawCorrEvolution -- numberOfSamples=", numberOfSamples
numOfAlignableStruct = detector[0].nModules()
if (doDebug): print " numOfAlignableStructe=", numOfAlignableStruct
EvolColor = AutoColors(numOfAlignableStruct)
# a canvas for all dofs
ThisCanvas = TCanvas("AlignmentCorrectionsEvol",
"Evolution of alignment corrections (All)", 920, 600)
if (drawAllDofs and outputFormat == ALLINONE): ThisCanvas.Divide(3, 2)
# find out range
#for i in range(lowerDof, upperDof):
for i in range(nUsedDofs):
for iter in range(numberOfSamples):
for bin in range(detector[iter].nModules()):
thisValue = abs(detector[iter].GetModule(bin).GetDoF(
i)[1]) + detector[iter].GetModule(bin).GetDoFError(i)[1]
if abs(thisValue) > yrange[i]:
yrange[i] = thisValue
yrange[i] *= 1.025
if (doDebug): print " dof=", i, " --> range: ", yrange[i]
#
# --- Y range of the plots --- cap the drawing range
# maximum range
maxTransRange = 0.100
if (yrange[0] > maxTransRange): yrange[0] = maxTransRange
if (yrange[1] > maxTransRange): yrange[1] = maxTransRange
if (yrange[2] > maxTransRange): yrange[2] = maxTransRange
if (yrange[6] > maxTransRange): yrange[6] = maxTransRange #Bx
# Tx and Ty should have the same range
if (yrange[0] > yrange[1]):
yrange[1] = yrange[0]
else:
yrange[0] = yrange[1]
# Tz range should be as minimum as Tx and Ty
if (yrange[2] < yrange[0]): yrange[2] = yrange[0]
#Bx range --> keep it independent
# Rx and Ry should have the same range
if (yrange[3] > yrange[4]):
yrange[4] = yrange[3]
else:
yrange[3] = yrange[4]
# Rz keep it independent
#yrange[0] = 0.004
yrange[1] = 0.0065
#yrange[2] = 0.040
#yrange[3] = 0.04
#yrange[4] = 0.04
#yrange[5] = 0.06
yrange[6] = 0.0025
#
# prepare the legend
#
myLegend = TLegend(0.80, 0.85, 0.99, 0.99)
myLegend.SetFillColor(0) # white
# and a line to split the runs if xGridType = gridNEWRUN
myGridLine = TLine()
myGridLine.SetLineStyle(3)
# loop dof by dof (Tx, Ty...) and fill a polyline with teh corrections for each iteration
if (doDebug):
print " -- drawCorrEvolution -- going to draw form lowerDof=", lowerDof, " to upperDof = ", upperDof
#for dof in range(nUsedDofs):
for dof in range(lowerDof, upperDof + 1):
#for dof in range(lowerDof, 6):
# extract dof name
name = detector[0].GetModule(0).GetDoF(dof)[0]
if (doDebug):
print "\n -- drawCorrEvolution -- going to draw dof= %d (%s)" % (
dof, name)
#dealing with canvases
if (outputFormat == ALLINONE):
ThisCanvas.cd()
if (drawAllDofs):
ThisCanvas.cd(dof + 1)
if (outputFormat == ONEBYONE):
Alldetector[dof] = {}
Alldetector[dof] = TCanvas(
"AlignCorrectionsEvol_%s" % (name),
"Alignment_corrections_evolution_%s" % (name), 920, 600)
print " -- drawCorrEvolution -- new canvas declared %s" % Alldetector[
dof].GetName()
if (outputFormat == SPLITBYSTRUCT):
Alldetector[dof] = {}
Alldetector[dof] = TCanvas(
"AlignCorrectionsEvol_%s_byDOF" % (name),
"Alignment_corrections_evolution_%s_byDOF" % (name), 920, 600)
if (numOfAlignableStruct >= 15):
Alldetector[dof].Divide(5, 3)
print " -- drawCorrEvolution -- Divide (5x3)"
print " -- drawCorrEvolution -- new canvas declared %s for %d structures" % (
Alldetector[dof].GetName(), numOfAlignableStruct)
# prepare the histogram that will store the corrections
hname = 'Dof_%s_corrections_Evol' % (name)
htitle = 'Evolution of %s corrections' % (name)
htitle = 'Evolution of d%s/dLB corrections' % (name)
if (doDebug):
print " -- drawCorrEvolution -- dof= %d hname= %s" % (dof, hname)
print " htitle= ", htitle
# build the histogram that is the main frame to plot the corrections for this dof (evolution of dof for each sample)
hCorrectionsEvol[dof] = TH1F(
hname, htitle, numberOfSamples - 1, -0.5,
numberOfSamples * 1. - 1.5) # the last sample is the accumulation
# set the x axis labels
hCorrectionsEvol[dof].GetXaxis().SetLabelSize(0.05)
if (numberOfSamples > 8): # this is in case there are too many
hCorrectionsEvol[dof].GetXaxis().SetLabelSize(0.04)
hCorrectionsEvol[dof].GetXaxis().SetBit(18)
if (numberOfSamples > 16): # reduce further the size
hCorrectionsEvol[dof].GetXaxis().SetLabelSize(0.03)
if (numberOfSamples > 24): # reduce further the size
hCorrectionsEvol[dof].GetXaxis().SetLabelSize(0.02)
hCorrectionsEvol[dof].GetXaxis().SetLabelSize(0.05)
hCorrectionsEvol[dof].GetYaxis().SetLabelSize(0.05)
for iter in range(numberOfSamples):
hCorrectionsEvol[dof].GetXaxis().SetBinLabel(
iter + 1, 'Iter_%d' % (iter))
if (len(labelList) > iter): # use label given by user
hCorrectionsEvol[dof].GetXaxis().SetBinLabel(
iter + 1, labelList[iter])
# label of the Y axis
if name is 'Tx' or name is 'Ty' or name is 'Tz' or name is 'Bx':
hCorrectionsEvol[dof].SetYTitle("mm")
hCorrectionsEvol[dof].SetYTitle("dTy/dLB [mm/25LB]")
else:
hCorrectionsEvol[dof].SetYTitle("mrad")
# set the range
hCorrectionsEvol[dof].GetYaxis().SetRangeUser(-yrange[dof],
yrange[dof])
hCorrectionsEvol[dof].SetStats(False)
# going to draw the frame
# -be ware, in case of drawing by structure need to change to the right pad
if (outputFormat == ALLINONE or outputFormat == ONEBYONE):
hCorrectionsEvol[dof].DrawCopy()
gPad.SetGridy()
if (xGridType == gridALLENTRIES): gridPad.SetGridx()
# draw the frame
#hCorrectionsEvol[dof].DrawCopy()
#gPad.SetGridx()
#gPad.SetGridy()
#
# once the frame is plotted, loop on every structure and fill a histogram and draw it
#
if (doDebug):
print " -- drawCorrEvolution -- dealing with", name, "corrections. Y range for this dof: (", dof, ") range: +-", yrange[
dof]
print " reminder: numOfAlignableStruct = ", numOfAlignableStruct
#for struct in range(numOfAlignableStruct):
for struct in range(2):
if (doDebug and False): print " >> looping on struct:", struct
if (outputFormat == SPLITBYSTRUCT):
Alldetector[dof].cd(struct + 1)
# then draw frame
hCorrectionsEvol[dof].DrawCopy()
gPad.SetGridy()
if (xGridType == gridALLENTRIES): gridPad.SetGridx()
hCorrectionsEvolStruct[dof] = {}
hname = 'Dof_%s_corrections_Evol_struct_%d' % (name, struct)
htitle = 'Corrections evolution for structure %s (struct %d)' % (
name, struct)
hCorrectionsEvolStruct[dof][struct] = TH1F(
hname, htitle, numberOfSamples - 1, -0.5,
numberOfSamples * 1. -
1.5) # last point is for the accumulation --> do not show
#print " -- drawCorrEvolution -- hCorrectionsEvolStruct has ",hCorrectionsEvolStruct[dof][struct].GetNbinsX(), ' bins in X'
hCorrectionsEvolStruct[dof][struct].SetLineColor(EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].SetStats(False)
# once the histogram is created, fill it with the corrections of each iteration
currentLabel = "000000" # dummy value
for iterval in range(numberOfSamples):
value = detector[iterval].GetModule(struct).GetDoF(dof)[1]
# derivatives
if (iterval == 0): value = 0
if (iterval > 0):
value = (
detector[iterval].GetModule(struct).GetDoF(dof)[1] -
detector[iterval - 1].GetModule(struct).GetDoF(dof)[1])
print " iterval ", iterval, " dx=", value, " +-", detector[
iterval].GetModule(struct).GetDoFError(dof)[1]
hCorrectionsEvolStruct[dof][struct].SetBinContent(
iterval + 1, value)
if (drawErrors):
hCorrectionsEvolStruct[dof][struct].SetBinError(
iterval + 1, detector[iterval].GetModule(
struct).GetDoFError(dof)[1])
# check the label in case it needs to be marked
if (xGridType == gridNEWRUN and len(labelList) > 0
and iterval < len(labelList)):
thisLabel = labelList[iterval]
if (thisLabel != currentLabel and "LB" in thisLabel):
# new run found
currentLabel = thisLabel
#print " thisLabel = ", thisLabel," iterval = ",iterval
myGridLine.DrawLine(iterval, -yrange[dof], iterval,
yrange[dof])
# now draw the corrections for this structure
if (drawErrors):
hCorrectionsEvolStruct[dof][struct].SetFillColor(
EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].SetFillStyle(3354)
# hCorrectionsEvolStruct[dof][struct].DrawCopy('same e3')
# --> original hCorrectionsEvolStruct[dof][struct].DrawCopy('same e3')
hCorrectionsEvolStruct[dof][struct].SetMarkerStyle(20)
hCorrectionsEvolStruct[dof][struct].SetMarkerSize(0.5)
hCorrectionsEvolStruct[dof][struct].SetMarkerColor(
EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].DrawCopy('same p e3 x0')
for iterval in range(numberOfSamples):
hCorrectionsEvolStruct[dof][struct].SetBinError(
iterval + 1, 0)
hCorrectionsEvolStruct[dof][struct].SetFillStyle(0)
hCorrectionsEvolStruct[dof][struct].DrawCopy('l x0 e3 same')
else:
myOption = "same"
if (drawLine):
myOption += " l"
else:
myOption += " p"
hCorrectionsEvolStruct[dof][struct].SetMarkerStyle(20)
hCorrectionsEvolStruct[dof][struct].SetMarkerColor(
EvolColor[struct])
hCorrectionsEvolStruct[dof][struct].DrawCopy(myOption)
gPad.Update()
#if (dof == 0 and True):
if (True):
if (dof == 0):
myLegend.AddEntry(hCorrectionsEvolStruct[dof][struct],
detector[0].GetModule(struct).GetName(),
"l")
myLegend.Draw()
gPad.Update()
t = time.time()
finalName[dof] = "%f_evolution_%s" % (t, name)
gPad.Update()
if (outputFormat == ONEBYONE or outputFormat == SPLITBYSTRUCT):
#print " -- drawCorrEvol -- saving plots from ONEBYONE "
Alldetector[dof].SaveAs(pathfiles + finalName[dof] + ".png", "png")
Alldetector[dof].SaveAs(pathfiles + finalName[dof] + ".pdf", "pdf")
#Alldetector[dof].SaveAs(pathfiles + finalName[dof] + ".root", "root")
#Alldetector[dof].SaveAs(pathfiles + finalName[dof] + ".C", "C")
if (outputFormat == ALLINONE):
#print " -- drawCorrEvol -- saving plots from ALLINONE "
t = time.time()
myFinalName = "%f_evolution_dofs" % (t)
ThisCanvas.SaveAs(pathfiles + myFinalName + ".png", "png")
ThisCanvas.SaveAs(pathfiles + myFinalName + ".pdf", "pdf")
plotfile['png'] = {0: myFinalName + ".png"}
plotfile['pdf'] = {0: myFinalName + ".pdf"}
if (outputFormat == ONEBYONE or outputFormat == SPLITBYSTRUCT):
plotfile['png'] = {
0: finalName[0] + ".png",
1: finalName[1] + ".png",
2: finalName[2] + ".png",
3: finalName[3] + ".png",
4: finalName[4] + ".png",
5: finalName[5] + ".png",
6: finalName[6] + ".png"
}
plotfile['pdf'] = {
0: finalName[0] + ".pdf",
1: finalName[1] + ".pdf",
2: finalName[2] + ".pdf",
3: finalName[3] + ".pdf",
4: finalName[4] + ".pdf",
5: finalName[5] + ".pdf",
6: finalName[6] + ".pdf"
}
#return plotfile
return ThisCanvas
nc.cd()
print colorlist[j]
g.SetLineColor(colorlist[j])
g.SetMarkerColor(colorlist[j])
g.SetMarkerStyle(8)
g.SetMarkerSize(0.8)
g.SetTitle('')
g.GetXaxis().SetTitle(ix[3])
g.GetYaxis().SetTitle(var[1])
g.GetYaxis().SetRangeUser(var[5][0], var[5][1])
graphs.append(g)
nc.cd()
for j, jgraph in enumerate(graphs):
jgraph.Draw('AP' * (j == 0) + 'P same' * (j != 0))
if options.leg:
l.AddEntry(jgraph, options.leg.split(',')[j], "pel")
nc.Update()
nc.Modified()
if options.leg:
l.Draw()
gPad.SetGridx(True)
gPad.SetGridy(True)
nc.SaveAs('pull_resolution_plots/' + var[6] + 'vs' + ix[0] +
'_Run278820_RelVal.pdf')
def mistagSFtopEMu(year_, ana_):
if year_ == 2017:
dir = "monohbb.v06.00.05.2017_NCU/withSingleTop/" + ana_ + "/"
if year_ == 2018:
dir = "monohbb.v06.00.05.2018_NCU/withSingleTop/" + ana_ + "/"
print "Top Electron Region"
print " "
openfile1 = TFile(dir + "TopE.root") #
topmatchTopE = openfile1.Get("h_TopMatch")
WmatchTopE = openfile1.Get("h_Wmatch")
unmatchTopE = openfile1.Get("h_unmatch")
wjetsTopE = openfile1.Get("h_sumWJets")
dibosonTopE = openfile1.Get("h_sumDiboson")
unsubtractedDataTopE = openfile1.Get("h_Data")
failMCsubtractTopE = openfile1.Get("h_ttFailed")
passMCsubtractTopE = openfile1.Get("h_ttPassed")
subtractedDataTopE = openfile1.Get("SubtractedData")
datafailTopE = openfile1.Get("SubtractedDataFailed")
datapassTopE = openfile1.Get("SubtractedDataPassed") #
totaldataTopE = openfile1.Get("h_totaldata")
totalMCtopE = openfile1.Get("h_tt")
passedTopEdataBfrSubtract = openfile1.Get("h_Data_Passed")
wjetsTopEpassed = openfile1.Get("h_sumWJetsPassed")
dibosonTopEpassed = openfile1.Get("h_sumDibosonPassed")
failedTopEdataBfrSubtract = openfile1.Get("h_Data_Failed")
wjetsTopEfailed = openfile1.Get("h_sumWJetsFailed")
dibosonTopEfailed = openfile1.Get("h_sumDibosonFailed")
stTopE = openfile1.Get("h_sumST")
stTopEpassed = openfile1.Get("h_sumSTPassed")
stTopEfailed = openfile1.Get("h_sumSTFailed")
print "Top Muon Region"
print " "
openfile2 = TFile(dir + "TopMu.root") #
topmatchTopMu = openfile2.Get("h_TopMatch")
WmatchTopMu = openfile2.Get("h_Wmatch")
unmatchTopMu = openfile2.Get("h_unmatch")
wjetsTopMu = openfile2.Get("h_sumWJets")
dibosonTopMu = openfile2.Get("h_sumDiboson")
unsubtractedDataTopMu = openfile2.Get("h_Data")
failMCsubtractTopMu = openfile2.Get("h_ttFailed")
passMCsubtractTopMu = openfile2.Get("h_ttPassed")
subtractedDataTopMu = openfile2.Get("SubtractedData")
datafailTopMu = openfile2.Get("SubtractedDataFailed")
datapassTopMu = openfile2.Get("SubtractedDataPassed") #
totaldataTopMu = openfile2.Get("h_totaldata")
totalMCtopMu = openfile2.Get("h_tt")
passedTopMudataBfrSubtract = openfile2.Get("h_Data_Passed")
wjetsTopMupassed = openfile2.Get("h_sumWJetsPassed")
dibosonTopMupassed = openfile2.Get("h_sumDibosonPassed")
failedTopMudataBfrSubtract = openfile2.Get("h_Data_Failed")
wjetsTopMufailed = openfile2.Get("h_sumWJetsFailed")
dibosonTopMufailed = openfile2.Get("h_sumDibosonFailed")
stTopMu = openfile2.Get("h_sumST")
stTopMupassed = openfile2.Get("h_sumSTPassed")
stTopMufailed = openfile2.Get("h_sumSTFailed")
print "get histograms from root files: done"
print " "
SubtractedDataPassedTopE = datapassTopE.Clone("SubtractedDataPassedTopE")
SubtractedDataPassedTopMu = datapassTopMu.Clone(
"SubtractedDataPassedTopMu")
#merge histogram"
print "merge histograms"
print " "
topmatchMerge = topmatchTopE + topmatchTopMu
WmatchMerge = WmatchTopE + WmatchTopMu
unmatchMerge = unmatchTopE + unmatchTopMu
wjetsMerge = wjetsTopE + wjetsTopMu
stMerge = stTopE + stTopMu
dibosonMerge = dibosonTopE + dibosonTopMu
unsubtractedDataMerge = unsubtractedDataTopE + unsubtractedDataTopMu
failMCsubtractMerge = failMCsubtractTopE.Clone("failMCsubtractMerge")
failMCsubtractMerge = failMCsubtractMerge + failMCsubtractTopMu
passMCsubtractMerge = passMCsubtractTopE.Clone("passMCsubtractMerge")
passMCsubtractMerge = passMCsubtractMerge + passMCsubtractTopMu
subtractedDataMerge = subtractedDataTopE + subtractedDataTopMu
ttData_fraction = arr.array('d')
ttData_error = arr.array('d')
totaldataMerge = totaldataTopE + totaldataTopMu
totaldata = totaldataMerge.Integral()
totaldataMerge.Rebin(14)
datafailMerge = datafailTopE + datafailTopMu
faildata = datafailMerge.Integral()
datafailMerge.Rebin(14)
datafailMerge.Sumw2()
datafailMerge.Divide(totaldataMerge)
frac_ttData_fail = datafailMerge.Integral()
ttData_fraction.append(frac_ttData_fail)
ttData_error.append(datafailMerge.GetBinError(1))
datapassMerge = datapassTopE + datapassTopMu
passdata = datapassMerge.Integral()
datapassMerge.Rebin(14)
datapassMerge.Sumw2()
datapassMerge.Divide(totaldataMerge)
frac_ttData_pass = datapassMerge.Integral()
ttData_fraction.append(frac_ttData_pass)
ttData_error.append(datapassMerge.GetBinError(1))
ttMC_fraction = arr.array('d')
ttMC_error = arr.array('d')
totalMCmerge = totalMCtopE + totalMCtopMu
totalMCmerge.Rebin(14)
MCfailTopE = failMCsubtractTopE.Clone("MCfailTopE")
MCfailTopMu = failMCsubtractTopMu.Clone("MCfailTopMu")
MCfailMerge = MCfailTopE + MCfailTopMu
MCfailMerge.Rebin(14)
MCfailMerge.Sumw2()
MCfailMerge.Divide(totalMCmerge)
frac_Failed_fin = MCfailMerge.Integral()
ttMC_fraction.append(frac_Failed_fin)
ttMC_error.append(MCfailMerge.GetBinError(1))
MCpassTopE = passMCsubtractTopE.Clone("MCpassTopE")
MCpassTopMu = passMCsubtractTopMu.Clone("MCpassTopMu")
MCpassMerge = MCpassTopE + MCpassTopMu
MCpassMerge.Rebin(14)
MCpassMerge.Sumw2()
MCpassMerge.Divide(totalMCmerge)
frac_Passed_fin = MCpassMerge.Integral()
ttMC_fraction.append(frac_Passed_fin)
ttMC_error.append(MCpassMerge.GetBinError(1))
#print "\nttMC_fraction:", ttMC_fraction
#print "ttMC_error:", ttMC_error
sfMerge = datapassMerge.Clone("sfMerge")
sfMerge.Sumw2()
sfMerge.Divide(MCpassMerge)
stacklist = []
stacklist.append(dibosonMerge)
stacklist.append(stMerge)
stacklist.append(wjetsMerge)
stacklist.append(unmatchMerge)
stacklist.append(WmatchMerge)
stacklist.append(topmatchMerge)
print "merge histograms: done"
print " "
print "draw histograms"
print " "
#----------------------- canvas 1 -----------------------#
c1 = TCanvas("c1", "", 800, 900) #width-height
c1.SetTopMargin(0.4)
c1.SetBottomMargin(0.05)
c1.SetRightMargin(0.1)
c1.SetLeftMargin(0.15)
gStyle.SetOptStat(0)
binvalues1 = []
for i in range(14):
binvalue = unsubtractedDataMerge.GetBinContent(i)
binvalues1.append(binvalue)
totalmax = max(binvalues1) + 100
padMain = TPad("padMain", "", 0.0, 0.25, 1.0, 0.97)
padMain.SetTopMargin(0.4)
padMain.SetRightMargin(0.05)
padMain.SetLeftMargin(0.17)
padMain.SetBottomMargin(0.03)
padMain.SetTopMargin(0.1)
padRatio = TPad("padRatio", "", 0.0, 0.0, 1.0, 0.25)
padRatio.SetRightMargin(0.05)
padRatio.SetLeftMargin(0.17)
padRatio.SetTopMargin(0.05)
padRatio.SetBottomMargin(0.3)
padMain.Draw()
padRatio.Draw()
padMain.cd()
gPad.GetUymax()
leg1 = myLegend(coordinate=[0.45, 0.57, 0.65, 0.6])
unsubtractedDataMerge.SetMaximum(totalmax)
unsubtractedDataMerge.SetLineColor(1)
unsubtractedDataMerge.SetMarkerStyle(20)
unsubtractedDataMerge.SetMarkerSize(1.5)
unsubtractedDataMerge.GetXaxis().SetLabelSize(0)
unsubtractedDataMerge.GetXaxis().SetTitleSize(0)
unsubtractedDataMerge.GetXaxis().SetTitle("DDB")
unsubtractedDataMerge.GetYaxis().SetTitle("Events/Bin")
leg1.AddEntry(unsubtractedDataMerge, "Data", "lep")
unsubtractedDataMerge.Draw("e1")
stackhisto = myStack(colorlist_=[627, 800, 854, 813, 822, 821],
backgroundlist_=stacklist,
legendname_=[
"Diboson", "Single Top", "W+Jets",
"Top (unmtch.)", "Top (W-mtch.)", "Top (mtch.)"
])
stackhisto[0].Draw("histsame")
unsubtractedDataMerge.Draw("e1same")
stackhisto[1].Draw()
leg1.Draw()
lt = TLatex()
lt.DrawLatexNDC(0.23, 0.85,
"#scale[0.8]{CMS} #scale[0.65]{#bf{#it{Internal}}}")
if ana_ == "Inclusive":
lt.DrawLatexNDC(0.17, 0.92, "#scale[0.7]{#bf{" + ana_ + "}}")
if ana_ == "PT-200-350" or ana_ == "PT-350-500" or ana_ == "PT-500-2000":
words = ana_.split("-")
if words[2] == "2000":
lt.DrawLatexNDC(0.17, 0.92,
"#scale[0.7]{#bf{p_{T} " + words[1] + "-Inf GeV}}")
else:
lt.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-" +
words[2] + " GeV}}")
else:
words = ana_.split("-")
lt.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{" + words[0] + " " + words[1] + "-" +
words[2] + " GeV}}")
lt.DrawLatexNDC(0.23, 0.8, "#scale[0.7]{#bf{t#bar{t} CR (e+#mu)}}")
lt.DrawLatexNDC(0.23, 0.75, "#scale[0.5]{#bf{2-prong (bq) enriched}}")
if year_ == 2017:
lt.DrawLatexNDC(0.71, 0.92, "#scale[0.7]{#bf{41.5 fb^{-1} (13 TeV)}}")
if year_ == 2018:
lt.DrawLatexNDC(0.71, 0.92,
"#scale[0.7]{#bf{58.827 fb^{-1} (13 TeV)}}")
padRatio.cd()
gPad.GetUymax()
h_totalBkg = topmatchMerge.Clone("h_totalBkg")
h_totalBkg = h_totalBkg + WmatchMerge + unmatchMerge + wjetsMerge + dibosonMerge
ratio = dataPredRatio(data_=unsubtractedDataMerge, totalBkg_=h_totalBkg)
ratio.SetLineColor(1)
ratio.SetLineWidth(3)
ratio.SetMarkerSize(1.5)
ratio.GetXaxis().SetLabelSize(0.13)
ratio.GetXaxis().SetTitleOffset(1)
ratio.GetXaxis().SetTitleSize(0.13)
ratio.GetXaxis().SetTickLength(0.1)
ratio.GetYaxis().SetLabelSize(0.12)
ratio.GetYaxis().SetTitleOffset(0.5)
ratio.GetYaxis().SetTitleSize(0.13)
ratio.GetYaxis().SetNdivisions(405)
ratio.GetYaxis().SetTitle("#frac{Data-Pred}{Pred}")
ratio.GetXaxis().SetTitle("DDB")
ratio.Draw("e1")
c1.SaveAs(dir + "Merge_all.pdf") #
#----------------------- canvas 2 -----------------------#
c2 = myCanvas(c="c2")
gPad.GetUymax()
leg2 = myLegend()
binvalues2 = []
for i in range(14):
binvalue = subtractedDataMerge.GetBinContent(i)
binvalues2.append(binvalue)
ttmax = max(binvalues2) + 50
failMCsubtractMerge.SetMaximum(ttmax)
failMCsubtractMerge.SetFillColor(821)
failMCsubtractMerge.SetLineColor(821) #922
failMCsubtractMerge.GetXaxis().SetTitle("DDB")
failMCsubtractMerge.GetYaxis().SetTitle("Events/Bin")
leg2.AddEntry(failMCsubtractMerge, "t#bar{t}", "f")
passMCsubtractMerge.SetFillColor(622)
passMCsubtractMerge.SetLineColor(622)
#passMCsubtractMerge.GetXaxis().SetTitle("DDB")
#passMCsubtractMerge.GetYaxis().SetTitle("Events/Bin")
leg2.AddEntry(passMCsubtractMerge, "t#bar{t} mistag", "f")
subtractedDataMerge.SetLineColor(1)
subtractedDataMerge.SetMarkerStyle(20)
subtractedDataMerge.SetMarkerSize(1.5)
#subtractedDataMerge.GetXaxis().SetTitle("DDB")
#subtractedDataMerge.GetYaxis().SetTitle("Events/Bin")
leg2.AddEntry(subtractedDataMerge, "Subtracted Data", "lep")
failMCsubtractMerge.Draw("hist")
passMCsubtractMerge.Draw("histsame")
subtractedDataMerge.Draw("e1same")
leg2.Draw()
lt2 = TLatex()
if ana_ == "Inclusive":
lt2.DrawLatexNDC(0.17, 0.92, "#scale[0.7]{#bf{" + ana_ + "}}")
if ana_ == "PT-200-350" or ana_ == "PT-350-500" or ana_ == "PT-500-2000":
words = ana_.split("-")
if words[2] == "2000":
lt2.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-Inf GeV}}")
else:
lt2.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-" +
words[2] + " GeV}}")
else:
words = ana_.split("-")
lt2.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{" + words[0] + " " + words[1] + "-" +
words[2] + " GeV}}")
lt2.DrawLatexNDC(0.23, 0.85,
"#scale[0.8]{CMS} #scale[0.65]{#bf{#it{Internal}}}")
lt2.DrawLatexNDC(0.23, 0.8, "#scale[0.7]{#bf{t#bar{t} CR (e+#mu)}}")
lt2.DrawLatexNDC(0.23, 0.75, "#scale[0.5]{#bf{2-prong (bq) enriched}}")
if year_ == 2017:
lt2.DrawLatexNDC(0.71, 0.92, "#scale[0.7]{#bf{41.5 fb^{-1} (13 TeV)}}")
if year_ == 2018:
lt2.DrawLatexNDC(0.71, 0.92,
"#scale[0.7]{#bf{58.827 fb^{-1} (13 TeV)}}")
c2.SaveAs(dir + "Merged_subtrac.pdf") #
#----------------------- canvas 3 -----------------------#
c3 = myCanvas(c="c3", size=[700, 900])
pad1 = TPad("pad1", "", 0.01, 0.25, 0.93, 1.0)
pad1.SetTopMargin(0.1)
pad1.SetRightMargin(0.05)
pad1.SetLeftMargin(0.17)
pad1.SetBottomMargin(0.05)
pad2 = TPad("pad2", "", 0.0, 0.0, 0.375, 0.24)
pad2.SetTopMargin(0.0)
pad2.SetRightMargin(0.0)
pad2.SetLeftMargin(0.0)
pad2.SetBottomMargin(0.0)
pad3 = TPad("pad3", "", 0.38, 0.025, 0.94, 0.25)
pad2.SetTopMargin(0.05)
pad2.SetRightMargin(0.0)
pad2.SetLeftMargin(0.45)
pad2.SetBottomMargin(0.2)
pad1.Draw()
pad2.Draw()
pad3.Draw()
#* Pad 1 *#
pad1.cd()
leg3 = myLegend(coordinate=[0.65, 0.4, 0.75, 0.5])
xaxisname = arr.array('d', [1, 2])
zero1 = np.zeros(2)
gPad.Modified()
gPad.SetGridy()
gr1 = TGraphErrors(2, xaxisname, ttMC_fraction, zero1, ttMC_error)
gr1.SetTitle("t#bar{t}")
gr1.SetLineColor(870)
gr1.SetLineWidth(3)
gr1.SetMarkerStyle(20)
gr1.SetMarkerColor(870)
leg3.AddEntry(gr1, "t#bar{t}", "lep")
gr2 = TGraphErrors(2, xaxisname, ttData_fraction, zero1, ttData_error)
gr2.SetTitle("t#bar{t} Data")
gr2.SetLineColor(1)
gr2.SetLineWidth(2)
gr2.SetMarkerStyle(20)
gr2.SetMarkerColor(1)
leg3.AddEntry(gr2, "t#bar{t} Data", "lep")
mg = TMultiGraph("mg", "")
mg.Add(gr1)
mg.Add(gr2)
mg.GetHistogram().SetMaximum(1.5)
mg.GetHistogram().SetMinimum(0)
mg.GetYaxis().SetTitle("Fraction")
mg.GetXaxis().SetLimits(0, 3)
mg.GetXaxis().SetTickLength(0.03)
mg.GetXaxis().SetNdivisions(103)
mg.GetXaxis().ChangeLabel(2, -1, -1, -1, -1, -1, "Fail")
mg.GetXaxis().ChangeLabel(1, -1, 0)
mg.GetXaxis().ChangeLabel(-1, -1, 0)
mg.GetXaxis().ChangeLabel(3, -1, -1, -1, -1, -1, "Pass")
mg.Draw("AP")
leg3.Draw()
lt3 = TLatex()
if ana_ == "Inclusive":
lt3.DrawLatexNDC(0.17, 0.92, "#scale[0.7]{#bf{" + ana_ + "}}")
if ana_ == "PT-200-350" or ana_ == "PT-350-500" or ana_ == "PT-500-2000":
words = ana_.split("-")
if words[2] == "2000":
lt3.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-Inf GeV}}")
else:
lt3.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-" +
words[2] + " GeV}}")
else:
words = ana_.split("-")
lt3.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{" + words[0] + " " + words[1] + "-" +
words[2] + " GeV}}")
lt3.DrawLatexNDC(0.19, 0.855,
"#scale[0.8]{CMS} #scale[0.65]{#bf{#it{Internal}}}")
lt3.DrawLatexNDC(0.19, 0.805, "#scale[0.7]{#bf{t#bar{t} CR (e+#mu)}}")
lt3.DrawLatexNDC(0.19, 0.755, "#scale[0.5]{#bf{2-prong (bq) enriched}}")
if year_ == 2017:
lt3.DrawLatexNDC(0.71, 0.92, "#scale[0.7]{#bf{41.5 fb^{-1} (13 TeV)}}")
if year_ == 2018:
lt3.DrawLatexNDC(0.71, 0.92,
"#scale[0.7]{#bf{58.827 fb^{-1} (13 TeV)}}")
lt3.Draw()
pad1.Update()
#* Pad 2 *#
pad2.cd()
MCpassMerge.SetFillColor(0)
MCpassMerge.SetLineColor(870)
MCpassMerge.SetLineWidth(3)
MCpassMerge.SetMarkerColor(870)
MCpassMerge.SetMarkerStyle(20)
MCpassMerge.GetYaxis().SetTitle("Fraction")
MCpassMerge.GetYaxis().SetTitleSize(0.09)
MCpassMerge.GetYaxis().SetLabelSize(0.1)
MCpassMerge.GetYaxis().SetNdivisions(404)
MCpassMerge.SetMaximum(0.3)
MCpassMerge.SetMinimum(0.0)
MCpassMerge.GetXaxis().SetTitle("")
MCpassMerge.GetXaxis().SetLabelOffset(0.02)
MCpassMerge.GetXaxis().SetLabelSize(0.09)
MCpassMerge.GetXaxis().SetNdivisions(104)
MCpassMerge.GetXaxis().ChangeLabel(2, -1, -1, -1, -1, -1, "Pass")
MCpassMerge.GetXaxis().ChangeLabel(1, -1, 0)
MCpassMerge.GetXaxis().ChangeLabel(-1, -1, 0)
datapassMerge.SetFillColor(0)
datapassMerge.SetLineColor(1)
datapassMerge.SetLineWidth(2)
datapassMerge.SetMarkerColor(1)
datapassMerge.SetMarkerStyle(20)
MCpassMerge.Draw("e1")
datapassMerge.Draw("e1histsame")
#* Pad 3 *#
pad3.cd()
SF = sfMerge.Integral()
print "******"
print "mistag SF:", SF
SFfinal = round(SF, 3)
SFtext = "SF = " + str(SFfinal)
mistagSFmax = SF + 0.2
mistagSFmin = SF - 0.2
sfMerge.SetLineColor(797)
sfMerge.SetMarkerColor(797)
sfMerge.SetLineWidth(3)
sfMerge.SetMaximum(mistagSFmax)
sfMerge.SetMinimum(mistagSFmin)
sfMerge.GetXaxis().SetTitle(" ")
sfMerge.GetXaxis().SetLabelOffset(999)
sfMerge.GetXaxis().SetLabelSize(0)
sfMerge.GetXaxis().SetTickLength(0)
sfMerge.GetYaxis().SetLabelSize(0.1)
sfMerge.GetYaxis().SetNdivisions(404)
sfMerge.GetYaxis().SetTitle(" ")
sfMerge.Draw("e1hist")
pt = TPaveText(0.21, 0.72, 0.31, 0.8, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.1)
pt.AddText(SFtext)
pt.Draw()
c3.SaveAs(dir + "Merge_SF.pdf") #
passedBfrSubtactDataMerge = (passedTopEdataBfrSubtract +
passedTopMudataBfrSubtract).Integral()
failedBfrSubtractDataMerge = (failedTopEdataBfrSubtract +
failedTopMudataBfrSubtract).Integral()
passbackground = (wjetsTopEpassed + wjetsTopMupassed + dibosonTopEpassed +
dibosonTopMupassed + stTopEpassed +
stTopMupassed).Integral()
failbackground = (wjetsTopEfailed + wjetsTopMufailed + dibosonTopEfailed +
dibosonTopMufailed + stTopEfailed +
stTopMufailed).Integral()
totalbackground = (wjetsMerge + dibosonMerge + stMerge).Integral()
#get the statistical uncertainty#
dx = ttData_error[1]
print "data efficiency error", dx
dy = ttMC_error[1]
print "MC efficiency error", dy
x = datapassMerge.Integral()
y = MCpassMerge.Integral()
statUnc = TMath.Sqrt(((dx**2) / (y**2)) + ((x**2) * (dy**2) / (y**4)))
#print "statistical Uncertainty in Top (e+muon) CR", statUnc
#print " "
print "relative statistical Uncertainty in Top (e+muon) CR", statUnc / SF * 100, " %"
print " "
print "DDB Mistag SF and stat: ", round(SF, 3), " +- ", round(statUnc,
3), " (stat)"
#print "theoretical statistical uncertainty of data efficiency", TMath.Sqrt((x*(1-x))/(subtractedDataMerge.Integral()))
#print "theoretical statistical uncertainty of MC efficiency", TMath.Sqrt((y*(1-y))/(totalMCmerge.Integral()))
#print " "
header = ["Process", "Number of Events", "Top (e+muon)"]
row1 = [
" ", "DDB mistag SF",
str(SFfinal) + " +- " + str(round(statUnc, 3)) + " (stat)"
]
row2 = ["tt MC", "Pass (not normalized)", ""]
row3 = [
" ", "Pass (normalized)",
str(round(passMCsubtractMerge.Integral(), 2))
]
row4 = [" ", "Fail (not normalized)", ""]
row5 = [
" ", "Fail (normalized)",
str(round(failMCsubtractMerge.Integral(), 2))
]
row6 = [" ", "Total (not normalized)", ""]
row7 = [" ", "Total (normalized)", str(round(totalMCmerge.Integral(), 2))]
inforMC = [row2, row3, row4, row5, row6, row7]
row8 = [
"tt DATA", "Pass (before subtraction)",
str(round(passedBfrSubtactDataMerge, 2))
]
row9 = [" ", "Pass (after subtraction)", str(round(passdata, 2))]
row10 = [
" ", "Fail (before subtraction)",
str(round(failedBfrSubtractDataMerge, 2))
]
row11 = [" ", "Fail (after subtraction)", str(round(faildata, 2))]
row12 = [
" ", "Total (before subtraction)",
str(round(unsubtractedDataMerge.Integral(), 2))
]
row13 = [" ", "Total (after subtraction)", str(round(totaldata, 2))]
inforDATA = [row8, row9, row10, row11, row12, row13]
row14 = ["Background", "Pass (normalized)", str(round(passbackground, 2))]
row15 = [" ", "Fail (normalized)", str(round(failbackground, 2))]
row16 = [" ", "Total (normalized)", str(round(totalbackground, 2))]
inforBKG = [row14, row15, row16]
DDB_mistagSF.makeTable(header, row1, inforMC, inforDATA, inforBKG)
c = TCanvas('f2r_test', 'f2r Test', 600, 400)
gStyle.SetPalette(1)
gStyle.SetOptStat(0)
gStyle.SetOptFit(0)
# make a test plot and store plots in file
for plot in plots:
if plot.get_type() == '1DPLOT':
if PLOT1D:
plot.get_histo().Draw('P')
plot.get_histo().Write()
if plot.get_type() == '2DPLOT':
if PLOT2D:
gPad.SetLogz()
gPad.SetGridx()
gPad.SetGridy()
plot.get_histo().Draw('COLZ')
plot.get_histo().Write()
if plot.get_type() == '3DPLOT':
if PLOT3D:
gPad.SetLogz()
gPad.SetGridx()
gPad.SetGridy()
hist = plot.get_histo()
for i in range(4):
hist[i].Draw()
raw_input('Close the window and press enter')
hist[i].Write()
file.Close()
defVeto_type = "%s_%s" % (iDefVeto, iSuffix)
if (defVeto_type in h1Run_diffTwoYT.keys() and
h1Run_diffTwoYT[defVeto_type].GetEntries() != 0):
leg_diffTwoYT[defOrVeto_type].AddEntry(
h1_diffTwoYT[defVeto_type],
"#splitline{%s: %d runs}{Underflow: %d Overflow: %d}"
%
(defectVeto["description"][iDefVeto],
h1_diffTwoYT[defVeto_type].GetEntries(),
h1_diffTwoYT[defVeto_type].GetBinContent(0),
h1_diffTwoYT[defVeto_type].GetBinContent(
h1_diffTwoYT[defVeto_type].GetNbinsX() + 1)),
"P")
if (first):
gPad.SetGridy(1)
h1Run_diffTwoYT[defVeto_type].SetMinimum(
-1.2 * maxAbsLumiDiff[defOrVeto_type])
h1Run_diffTwoYT[defVeto_type].SetMaximum(
1.2 * maxAbsLumiDiff[defOrVeto_type])
h1Run_diffTwoYT[defVeto_type].Draw("L")
c_diffTwoYT[defOrVeto_type].cd(2)
gPad.SetGrid(1)
h1_diffTwoYT[defVeto_type].Draw("L")
first = False
else:
h1Run_diffTwoYT[defVeto_type].Draw("L SAME")
c_diffTwoYT[defOrVeto_type].cd(2)
h1_diffTwoYT[defVeto_type].Draw("L SAME")
c_diffTwoYT[defOrVeto_type].cd(2)
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")
