def DrawSplotHistograms(DataFileName,
DataTreeName,
SFileName,
STreeName,
noStack=True):
fData = TFile(DataFileName)
tData = fData.Get(DataTreeName)
tData.AddFriend(STreeName, SFileName)
histoListe = setupHistograms()
HistDic = {}
for i, h in enumerate(histoListe):
legende = TLegend(0.75, 0.83, 0.97, 0.97)
CanvasName = "c" + str(i)
CanvasName = TCanvas(CanvasName, 'Defining histogram size')
g = THStack("", "")
#tMC.Draw(histoListe[i][3],CutMC)
#hist_MC = tMC.GetHistogram().Clone("hist_MC")
#hist_MC.SetLineColor(6)
#hist_MC.SetLineWidth(1)
##hist_MC.SetMarkerStyle(21)
#legende.AddEntry(hist_MC, "MC", "lp")
#hist_MC.GetXaxis().SetTitle(h[1])
#hist_MC.GetYaxis().SetTitle(h[2])
#hist_MC.Scale(1/hist_MC.Integral())
#MaxMC = hist_MC.GetMaximum()
#g.Add(hist_MC)
tData.Draw(histoListe[i][3], "B_M>5300")
hist_data = tData.GetHistogram().Clone("hist_data")
hist_data.SetLineColor(5)
hist_data.SetLineWidth(1)
#hist_data.SetMarkerStyle(21)
legende.AddEntry(hist_data, "Data", "lp")
hist_data.GetXaxis().SetTitle(h[1])
hist_data.GetYaxis().SetTitle(h[2])
MaxData = hist_data.GetMaximum()
g.Add(hist_data)
tData.Draw(histoListe[i][3], "nsig_sw")
hist_sw = tData.GetHistogram().Clone("hist_sw")
hist_sw.SetLineColor(4)
hist_sw.SetLineWidth(1)
##hist_RS.SetMarkerStyle(21)
legende.AddEntry(hist_sw, "sweighted Data", "lp")
MaxSW = hist_sw.GetMaximum()
g.Add(hist_sw)
if noStack:
if (MaxSW > MaxData):
g.SetMaximum(MaxSW * 1.2)
else:
g.SetMaximum(MaxData * 1.2)
g.Draw("nostackhist")
else:
g.SetMaximum(g.GetMaximum() * 1.2)
g.Draw("hist")
legende.Draw()
g.GetXaxis().SetTitle(h[1])
g.GetYaxis().SetTitle(h[2])
g.GetYaxis().SetTitleOffset(1.4)
g.GetXaxis().SetTitleOffset(1.1)
my_Latex = TLatex()
my_Latex.SetTextSize(0.04)
my_Latex.DrawLatexNDC(0.13, 0.85, "LHCb Data 2012")
CanvasName.Update()
outDir = '/sps/lhcb/volle/FitBMass/v1_Min5120'
if not os.path.isdir(outDir):
os.makedirs(outDir)
CanvasName.SaveAs("{}/{}_both.pdf".format(outDir,
histoListe[i][0])) #_both
CanvasName.SaveAs("{}/{}_both.png".format(outDir,
histoListe[i][0])) #_both
print 'Corrected chi2'
#chi2 = ndf*1.0
chi2 = theFitter.computeChi2(ndf)
print 'Raw chi2'
#chi2Raw = ndf2*1.0
chi2Raw = theFitter.computeChi2(ndf2, False)
mf = theFitter.stackedPlot()
mf.SetName("Mjj_Stacked")
## sf = theFitter.residualPlot(mf, "h_background", "dibosonPdf", False)
# pf = theFitter.residualPlot(mf, "h_total", "", True)
pf = pulls.createPull(mf.getHist('theData'), mf.getCurve('h_total'))
pf.SetName("Mjj_Pull")
## lf = theFitter.stackedPlot(True)
l = TLatex()
l.SetNDC()
l.SetTextSize(0.035)
l.SetTextFont(42)
cs = TCanvas("cs", "stacked")
mf.Draw()
# l.DrawLatex(0.66, 0.55,
# '#chi^{{2}}/dof = {0:0.3f}/{1}'.format(chi2, ndf)
# )
pyroot_logon.cmsPrelim(cs, fitterPars.intLumi/1000)
cs.Print('H{2}_Mjj_{0}_{1}jets_Stacked.pdf'.format(modeString, opts.Nj, opts.mH))
cs.Print('H{2}_Mjj_{0}_{1}jets_Stacked.png'.format(modeString, opts.Nj, opts.mH))
# if (fr.covQual() != 3):
# print "Fit did not converge with a good error matrix. Bailing out."
def PlotHisto(hist, fitName, plotType):
if debug:
print "Fitting", fitName, "function"
#get fitting params
height = hist.GetMaximum()
mean = hist.GetMean()
rms = hist.GetRMS()
#define fit range variables
xmin = mean - 3 * rms
xmax = mean + 3 * rms
#make the required fit
if fitName == "Gauss":
fitfunc = TF1('Gauss', Gauss(), xmin, xmax, 3)
fitfunc.SetParameters(height, mean, rms)
elif fitName == "Bukin":
fitfunc = TF1('Bukin', Bukin(), xmin, xmax, 6)
fitfunc.SetParameters(height, mean, rms, -0.4, 0.01, 0.005)
#create and draw legend and canvas
c = TCanvas(histname, histname, 800, 400)
legend = TLegend(0.13, 0.7, 0.45, 0.85)
#histoStyle()
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
#fit and plot according to requirements
if plotType == "hist":
hist.Fit(fitfunc, "0")
legend.AddEntry(hist, "Higgs Mass histo", "l")
hist.Draw()
elif plotType == "overlay":
hist.Fit(fitfunc)
legend.AddEntry(hist, "Higgs Mass histo", "l")
legend.AddEntry(fitfunc, "Fitted function", "l")
hist.Draw()
elif plotType == "fit":
hist.Fit(fitfunc)
func = hist.GetFunction(fitName)
legend.AddEntry(func, "Fitted function", "l")
hist.Draw("FUNC")
func = hist.GetFunction(fitName)
fitresults = (func.GetParameter(0), func.GetParameter(1),
func.GetParameter(2), func.GetParameter(3),
func.GetParameter(4), func.GetParameter(5))
hist.SetXTitle("mbb [GeV]")
hist.SetYTitle("Number of events")
legend.AddEntry(None, "#bf{mean[GeV] / sigma[GeV] / ratio}", "")
legend_text = "#bf{%-.3f/%-.3f/%-.3f}" % (
fitresults[1], fitresults[2], ratio(fitresults[2], fitresults[1]))
legend.AddEntry(None, legend_text, "")
legend.SetBorderSize(0)
legend.SetTextFont(42)
legend.SetTextSize(0.03)
legend.Draw("same")
t = TLatex()
t.SetNDC()
t.SetTextSize(10)
t.SetTextFont(43)
t.SetTextAlign(13)
t.DrawLatex(0.65, 0.85, "#it{#bf{SUPAROOT} lab2 }")
t.Draw("same")
c.Print(outputfileName)
return
def OverlayHistograms(fitName, plotType, histograms, outputfileName):
if debug:
print "Fitting", fit, "function"
print "PlotType:", plotType
#create and draw legend and canvas
c = TCanvas("canvas", "canvas", 1600, 800)
legend = TLegend(0.12, 0.47, 0.40, 0.87)
legend.AddEntry(None, "#bf{mean[GeV] / sigma[GeV] / ratio}", "")
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetTextSize(0.03)
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
#make a template histo so that y axis has correct height
#find max height
for hist in histograms:
heights = []
height = hist.GetMaximum()
heights.append(height)
maxheight = max(heights) + 100
template = histograms[0].Clone()
template.SetMaximum(maxheight)
template.Reset()
template.Draw()
template.SetXTitle("mbb [GeV]")
template.SetYTitle("Number of events")
col = 2
#loop over histos to overlay
for hist in histograms:
#get fitting params
height = hist.GetMaximum()
mean = hist.GetMean()
rms = hist.GetRMS()
#set line color
hist.SetLineColor(col)
#define fit range variables
xmin = mean - 3 * rms
xmax = mean + 3 * rms
#make the required fit
if fitName == "Gauss":
fitfunc = TF1('Gauss', Gauss(), xmin, xmax, 3)
fitfunc.SetParameters(height, mean, rms)
elif fitName == "Bukin":
fitfunc = TF1('Bukin', Bukin(), xmin, xmax, 6)
fitfunc.SetParameters(height, mean, rms, -0.4, 0.01, 0.005)
#fit and plot according to requirements
if plotType == "hist":
hist.Fit(fitfunc, "0")
legend.AddEntry(hist, hist.GetName(), "l")
hist.Draw("same")
elif plotType == "overlay":
hist.Fit(fitfunc, "0")
func = hist.GetFunction(fitName)
legend.AddEntry(hist, hist.GetName(), "l")
hist.Draw("same")
func.SetLineColor(col)
func.Draw("SAME")
elif plotType == "fit":
hist.Fit(fitfunc, "0")
func = hist.GetFunction(fitName)
legend.AddEntry(hist, hist.GetName(), "l")
func.Draw("SAME")
func.SetLineColor(col)
#show fit results in the legend
func = hist.GetFunction(fitName)
fitresults = (func.GetParameter(0), func.GetParameter(1),
func.GetParameter(2), func.GetParameter(3),
func.GetParameter(4), func.GetParameter(5))
legend_text = "#bf{%-.3f/%-.3f/%-.3f}" % (
fitresults[1], fitresults[2], ratio(fitresults[2], fitresults[1]))
legend.AddEntry(None, legend_text, "")
col += 1
#end for loop
legend.Draw("same")
#plot text
t = TLatex()
t.SetNDC()
t.SetTextSize(14)
t.SetTextFont(43)
t.SetTextAlign(13)
t.DrawLatex(0.8, 0.85, "#it{#bf{SUPAROOT} lab2 }")
t.Draw("same")
c.Print(outputfileName)
return
def __init__(self):
self.dataFiles = None
self.bins = (50, 0, 1)
self.Info = None
self.lt = TLatex()
def FitRegion(REGION='SignalRegion'):
gROOT.SetBatch(True)
# cavn0=TCanvas('test','test',600,600)
# SD_REGION='Signal'
# REGION='SignalRegion'
# REGION='SidebandRegion'
#filename='/nfs/dust/cms/user/albrechs/CMSSW_8_1_0/src/DijetCombineLimitCode/input/ZZ_S0_16p00.root'
# filename='/nfs/dust/cms/user/albrechs/UHH2_Output/'+REGION+'/backup/uhh2.AnalysisModuleRunner.Data.DATA.root'
if ('Signal' in REGION):
filename = '/nfs/dust/cms/user/albrechs/UHH2_Output/' + REGION + '/uhh2.AnalysisModuleRunner.MC.MC_QCD.root'
else:
filename = '/nfs/dust/cms/user/albrechs/UHH2_Output/' + REGION + '/uhh2.AnalysisModuleRunner.Data.DATA.root'
# filename='/nfs/dust/cms/user/albrechs/UHH2_Output/'+REGION+'/uhh2.AnalysisModuleRunner.MC.MC_QCD.root'
File = TFile(filename)
# VVHist_1GeV= File.Get('qcd_invMass')
# VBFHist_1GeV= File.Get('qcd_invMass_afterVBFsel')
VVHist_1GeV = File.Get('VVRegion/M_jj_AK8_highbin')
VBFHist_1GeV = File.Get('invMAk4sel_1p0/M_jj_AK8_highbin')
# VVHist_1GeV.Draw('PE1')
# raw_input('press enter to continue')
VVHist_1GeV.Scale(1. / VVHist_1GeV.Integral(), 'width')
VBFHist_1GeV.Scale(1. / VBFHist_1GeV.Integral(), 'width')
# VVHist_1GeV.Draw('PE1')
# raw_input('press enter to continue')
equidistant = False
fitbinning = array('d')
if (equidistant):
binwidth = 400
yTitle = 'Normalized # Events / (%.1f GeV)' % binwidth
#NBins=(14000/binwidth) - ( (1040/binwidth) + 1 )
NBins = (14000 / binwidth) - ((1040 / binwidth) + 1)
NBins = int(NBins)
for i in range(NBins + 1):
fitbinning.append(1050 + i * binwidth)
# # print(fitbinning)
else:
yTitle = 'Normalized # Events'
#not plotting bin before Mjj>1050GeV Cut
nonequidistant_binning = [
1058, 1118, 1181, 1246, 1313, 1383, 1455, 1530, 1607, 1687, 1770,
1856, 1945, 2037, 2132, 2231, 2332, 2438, 2546, 2659, 2775, 2895,
3019, 3147, 3279, 3416, 3558, 3704, 3854, 4010, 4171, 4337, 4509,
4686, 4869, 5058, 5253, 5455, 5663, 5877, 6099, 6328, 6564, 6808,
7060, 7320, 7589, 7866, 8152, 8447, 8752, 9067, 9391, 9726, 10072,
10430, 10798, 11179, 11571, 11977, 12395, 12827, 13272, 13732,
14000
]
# nonequidistant_binning=[1, 3, 6, 10, 16, 23, 31, 40, 50, 61, 74, 88, 103, 119, 137, 156, 176, 197, 220, 244, 270, 296, 325, 354, 386, 419, 453, 489, 526, 565, 606, 649, 693, 740, 788, 838, 890, 944, 1000, 1058, 1118, 1181, 1246, 1313, 1383, 1455, 1530, 1607, 1687, 1770, 1856, 1945, 2037, 2132, 2231, 2332, 2438, 2546, 2659, 2775, 2895, 3019, 3147, 3279, 3416, 3558, 3704, 3854, 4010, 4171, 4337, 4509, 4686, 4869, 5058, 5253, 5455, 5663, 5877, 6099, 6328, 6564, 6808, 7060, 7320, 7589, 7866, 8152, 8447, 8752, 9067, 9391, 9726, 10072, 10430, 10798, 11179, 11571, 11977, 12395, 12827, 13272, 13732, 14000]
NBins = len(nonequidistant_binning) - 1
for b in nonequidistant_binning:
fitbinning.append(b)
VVHist_100GeV = VVHist_1GeV.Rebin(NBins, "fit parameter", fitbinning)
VBFHist_100GeV = VBFHist_1GeV.Rebin(NBins, "fit parameter", fitbinning)
# VVHist_100GeV.Scale(1./VVHist_100GeV.Integral(),'width')
# VBFHist_100GeV.Scale(1./VBFHist_100GeV.Integral(),'width')
# VVHist_100GeV.Draw('PE1')
# raw_input('press enter to continue')
gStyle.SetOptStat(0)
gStyle.SetOptFit(0000)
# gStyle.SetOptFit(1100)
gStyle.SetOptTitle(0)
RooFit.SumW2Error(kTRUE)
VV_MAXIMUM = 0
for i in range(VVHist_100GeV.GetNbinsX()):
if (VVHist_100GeV.GetBinContent(i) > 0):
VV_MAXIMUM = VVHist_100GeV.GetBinCenter(i)
VBF_MAXIMUM = 0
for i in range(VBFHist_100GeV.GetNbinsX()):
if (VBFHist_100GeV.GetBinContent(i) > 0):
VBF_MAXIMUM = VBFHist_100GeV.GetBinCenter(i)
VVcanv = TCanvas('VV', 'VV', 700, 700)
VVcanv.SetLogy()
VVcanv.SetLeftMargin(0.20)
VVcanv.cd()
# fitOptions='R'
# fitOptions='R'
fitOptions = 'RSWLM'
twopar = '[0]/TMath::Power(x/13000,[1])'
threeparlog = '[0]/TMath::Power(x/13000,[1])+([2]*TMath::Log10(x/13000))'
threepar = '[0]*TMath::Power((1-(x/13000)),[2])/TMath::Power(x/13000,[1])'
# threepar='[0]*TMath::Power((1-x)/13000,[1])+(x/13000)*[2]'
fourpar = '[0]*TMath::Power((1-(x/13000),[1])/TMath::Power(x/13000,[2]+[3]*TMath::Log10(x/13000))'
if ('Signal' in REGION):
NPar = 2
else:
NPar = 3
if (NPar == 2):
fitfunc = twopar
functionTeX = 'p_{0}/(x/#sqrt{s})^{p_{1}}'
elif (NPar == 3):
# functionTeX='#frac{p_{0}}{(x/#sqrt{s})^{p_{1}}}+p_{2}*log_{10}(x/#sqrt{s})'
# fitfunc=threeparlog
functionTeX = '#frac{p_{0}*((1-(x/#sqrt{s}))^{p_{2}}}{(x/#sqrt{s})^{p_{1}}}'
fitfunc = threepar
elif (NPar == 4):
fitfunc = fourpar
functionTeX = '#frac{p_{0}*((1-x)/#sqrt{s})^{p_{1}}}{(x/#sqrt{s})^{p_{2}+p_{3}*log_{10}(x/#sqrt{s})}}'
# for i in range(VVHist_100GeV.GetNbinsX()):
# print i,':',VVHist_100GeV.GetBinCenter(i),'-',VVHist_100GeV.GetBinContent(i)
# VVHist_100GeV.SetBinContent(19,0)
# VVHist_100GeV.SetBinError(19,0)
VVTF1 = TF1('VVTF1', fitfunc, 1058, VV_MAXIMUM)
# VVTF1.SetParLimits(0,-10**(-6),10**(-6))
# VVTF1.SetParLimits(1,0,8)
# VVTF1.SetParLimits(2,-100,0)
# VVTF1.SetParameter(0,1.70473**(-7))
VVTF1.SetParameter(0, 1.70473 * 10**(-7))
VVTF1.SetParameter(1, 5.76351)
# VVTF1.SetParameter(2,0)
VVHist_100GeV.SetMarkerStyle(8)
VVHist_100GeV.SetLineColor(1)
VVHist_100GeV.GetYaxis().SetRangeUser(10**(-6), 10)
VVHist_100GeV.GetXaxis().SetTitle('M_{jj-AK8} [GeV/c^{2}]')
VVHist_100GeV.GetYaxis().SetTitle(yTitle)
VVHist_100GeV.GetYaxis().SetTitleOffset(2)
VVHist_100GeV.Draw('PE1')
VVHist_100GeV.GetXaxis().SetRangeUser(1058, VV_MAXIMUM + 1000)
VVHist_100GeV.Draw('PE1SAME')
#raw_input('press enter to continue')
VVHist_100GeV.Sumw2()
VVHist_100GeV.Fit('VVTF1', fitOptions)
# VVHist_100GeV.Fit('VVTF1','R')
VVTF1.Draw('SAME')
# VVTF1UP=TF1('VVTF1UP',fitfunc,1050,VV_MAXIMUM)
# VVTF1UP.SetParameter(0,VVTF1.GetParameter(0)+VVTF1.GetParError(0))
# VVTF1UP.SetParameter(1,VVTF1.GetParameter(1)+VVTF1.GetParError(1))
# VVTF1UP.SetLineStyle(rt.kDashed)
# VVTF1DOWN=TF1('VVTF1DOWN',fitfunc,1050,VV_MAXIMUM)
# VVTF1DOWN.SetParameter(0,VVTF1.GetParameter(0)-VVTF1.GetParError(0))
# VVTF1DOWN.SetParameter(1,VVTF1.GetParameter(1)-VVTF1.GetParError(1))
# VVTF1DOWN.SetLineStyle(rt.kDashed)
# VVTF1UP.Draw('SAME')
# VVTF1DOWN.Draw('SAME')
print('chi2/ndf:', VVTF1.GetChisquare(), '/', VVTF1.GetNDF())
latex = TLatex()
latex.SetNDC(kTRUE)
latex.SetTextSize(0.03)
# latex.DrawLatex(0.52,0.953,"%.2f fb^{-1} (13 TeV)"%36.1)
latex.DrawLatex(
0.45, 0.65, "#chi^{2}/ndof=%.2f/%.2f=%.2f" %
(VVTF1.GetChisquare(), VVTF1.GetNDF(),
VVTF1.GetChisquare() / VVTF1.GetNDF()))
latex.Draw("SAME")
VVleg = TLegend(0.45, 0.7, 0.9, 0.9)
VVleg.SetBorderSize(0)
VVleg.SetFillStyle(0)
if ('Data' in filename):
VVleg.AddEntry(VVHist_100GeV, 'Data-!VBF', 'p')
VVleg.AddEntry(VVTF1, 'Data-!VBF Fit %s' % functionTeX, 'l')
else:
VVleg.AddEntry(VVHist_100GeV, 'QCD-!VBF', 'p')
VVleg.AddEntry(VVTF1, 'QCD-!VBF Fit %s' % functionTeX, 'l')
VVleg.SetTextSize(0.03)
VVleg.Draw('SAME')
VVcanv.Print(REGION + '_VVRegion.eps')
VBFcanv = TCanvas('VBF', 'VBF', 700, 700)
VBFcanv.SetLogy()
VBFcanv.SetLeftMargin(0.20)
VBFcanv.cd()
VBFTF1 = TF1('VBFTF1', fitfunc, 1058, VBF_MAXIMUM)
if (NPar > 2):
VBFTF1.SetParameter(0, 2.85852 * 10**(-8))
VBFTF1.SetParameter(1, 6.49129)
VBFTF1.SetParameter(2, -1)
VBFTF1.SetLineColor(rt.kBlue)
VBFTF1.SetLineWidth(2)
# VBFTF1.SetLineStyle(2)
VBFHist_100GeV.SetMarkerStyle(8)
VBFHist_100GeV.SetLineColor(1)
VBFHist_100GeV.GetYaxis().SetRangeUser(10**(-6), 10)
VBFHist_100GeV.GetXaxis().SetTitle('M_{jj-AK8} [GeV/c^{2}]')
VBFHist_100GeV.GetYaxis().SetTitle(yTitle)
VBFHist_100GeV.GetYaxis().SetTitleOffset(2)
VBFHist_100GeV.Draw('PE1')
VBFHist_100GeV.GetXaxis().SetRangeUser(1058, VV_MAXIMUM + 1000)
VBFHist_100GeV.Draw('PE1SAME')
# raw_input('press enter to continue')
# VBFHist_100GeV.Sumw2()
VBFHist_100GeV.Fit('VBFTF1', fitOptions)
VBFTF1.Draw('SAME')
# VVTF1.SetLineStyle(2)
VVTF1.Draw('SAME')
# VVTF1UP.Draw('SAME')
# VVTF1DOWN.Draw('SAME')
# VBFTF1UP=TF1('VBFTF1UP',fitfunc,1050,VBF_MAXIMUM)
# VBFTF1UP.SetParameter(0,VBFTF1.GetParameter(0)+VBFTF1.GetParError(0))
# VBFTF1UP.SetParameter(1,VBFTF1.GetParameter(1)+VBFTF1.GetParError(1))
# VBFTF1UP.SetLineColor(rt.kBlue)
# VBFTF1UP.SetLineStyle(rt.kDashed)
# VBFTF1DOWN=TF1('VBFTF1DOWN',fitfunc,1050,VBF_MAXIMUM)
# VBFTF1DOWN.SetParameter(0,VBFTF1.GetParameter(0)-VBFTF1.GetParError(0))
# VBFTF1DOWN.SetParameter(1,VBFTF1.GetParameter(1)-VBFTF1.GetParError(1))
# VBFTF1DOWN.SetLineColor(rt.kBlue)
# VBFTF1DOWN.SetLineStyle(rt.kDashed)
# VBFTF1UP.Draw('SAME')
# VBFTF1DOWN.Draw('SAME')
print('chi2/ndf:', VBFTF1.GetChisquare(), '/', VBFTF1.GetNDF())
latexvbf = TLatex()
latexvbf.SetNDC(kTRUE)
latexvbf.SetTextSize(0.03)
latexvbf.DrawLatex(
0.45, 0.65, "#chi^{2}/ndof=%.2f/%.2f=%.2f" %
(VBFTF1.GetChisquare(), VBFTF1.GetNDF(),
VBFTF1.GetChisquare() / VBFTF1.GetNDF()))
VBFleg = TLegend(0.45, 0.7, 0.9, 0.9)
VBFleg.SetBorderSize(0)
VBFleg.SetFillStyle(0)
if ('Data' in filename):
VBFleg.AddEntry(VBFHist_100GeV, 'Data-VBF', 'p')
VBFleg.AddEntry(VBFTF1, 'Data-VBF Fit %s' % functionTeX, 'l')
VBFleg.AddEntry(TH1F(), '', '')
VBFleg.AddEntry(VVTF1, 'Data-!VBF Fit %s' % functionTeX, 'l')
else:
VBFleg.AddEntry(VBFHist_100GeV, 'QCD-VBF', 'p')
VBFleg.AddEntry(VBFTF1, 'QCD-VBF Fit %s' % functionTeX, 'l')
if (NPar == 3):
VBFleg.AddEntry(TH1F(), '', '')
VBFleg.AddEntry(VVTF1, 'QCD-!VBF Fit %s' % functionTeX, 'l')
VBFleg.SetTextSize(0.03)
VBFleg.Draw('SAME')
VBFcanv.Print(REGION + '_VBFRegion.eps')
def SAME3VsLumi(g1, g2, g3, title, ptype, lineMC1, lineDATA1, lineMC2, lineDATA2, lineMC3, lineDATA3, DoInclusive, dataPeriod):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
graph2=copy.deepcopy(g2)
graph3=copy.deepcopy(g3)
graph2.SetMarkerColor(kBlue)#electrons
graph3.SetMarkerColor(kRed)#muons
multigraph = TMultiGraph()
if(DoInclusive):
graph1=copy.deepcopy(g1)
multigraph.Add(graph1,"AP")
multigraph.Add(graph2,"AP")
multigraph.Add(graph3,"AP")
multigraph.Draw("AP")
TGaxis.SetMaxDigits(2)
TGaxis.SetExponentOffset(-0.05, 0.02, "y")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetYaxis().SetTitleOffset(1.4)
if(ptype == "Zmass"):
multigraph.GetYaxis().SetTitle("M_{Z} [GeV]")
# multigraph.GetYaxis().SetTitle("M_{l^{+}l^{-}} [GeV]")
multigraph.SetMaximum(max(multigraph.GetHistogram().GetMaximum(),91.4))
multigraph.SetMinimum(min(multigraph.GetHistogram().GetMinimum(),89.6))
elif(ptype == "Zwidth"):
multigraph.GetYaxis().SetTitle("#Gamma_{Z} [GeV]")
elif(ptype == "Zmult"):
multigraph.GetYaxis().SetTitle("#Z / fb^{-1}")
if(not DoInclusive) :
multigraph.SetMaximum(max(multigraph.GetHistogram().GetMaximum(),60000.)) # set y axis minimum at 60000.
multigraph.SetMinimum(0.) # set y axis minimum at 0.
# multigraph.SetMaximum(60000.) #second type: vs 2016 plots
# multigraph.SetMinimum(25000.)
printLumiPrelOut(canvas)
# Draw legend
legend = TLegend(0.93,0.84,0.99,0.93)
if(DoInclusive):
#legend.AddEntry(graph1,"inclusive","P")
legend.AddEntry(graph1,"BB","P")
legend.AddEntry(graph2,"BE","P")
legend.AddEntry(graph3,"EE","P")
else :
legend.AddEntry(graph2,"e^{+}e^{-}","P")
legend.AddEntry(graph3,"#mu^{+}#mu^{-}","P")
legend.SetFillColor(kWhite)
legend.SetLineColor(kBlack)
legend.SetTextFont(43)
legend.SetTextSize(20)
legend.Draw()
canvas.Update()
# Draw letters for data-taking periods
if(dataPeriod == "data2017"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "Zmass"):
textLetters.DrawLatex(2., gPad.GetUymin()+0.2,"B")
textLetters.DrawLatex(9.5, gPad.GetUymin()+0.2,"C")
textLetters.DrawLatex(16., gPad.GetUymin()+0.2,"D")
textLetters.DrawLatex(23., gPad.GetUymin()+0.2,"E")
textLetters.DrawLatex(36., gPad.GetUymin()+0.2,"F")
elif(ptype == "Zwidth"):
textLetters.DrawLatex(2., gPad.GetUymin()+0.3,"B")
textLetters.DrawLatex(9.5, gPad.GetUymin()+0.3,"C")
textLetters.DrawLatex(16., gPad.GetUymin()+0.3,"D")
textLetters.DrawLatex(23., gPad.GetUymin()+0.3,"E")
textLetters.DrawLatex(36., gPad.GetUymin()+0.3,"F")
elif(ptype == "Zmult") :
textLetters.DrawLatex(2., 260000,"B")
textLetters.DrawLatex(9.5, 260000,"C")
textLetters.DrawLatex(16., 260000,"D")
textLetters.DrawLatex(23., 260000,"E")
textLetters.DrawLatex(36., 260000,"F")
if(dataPeriod == "data2018"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "Zmass"):
textLetters.DrawLatex(6., gPad.GetUymin() + 0.6,"A")
textLetters.DrawLatex(16., gPad.GetUymin() + 0.6,"B")
textLetters.DrawLatex(23., gPad.GetUymin() + 0.6,"C")
textLetters.DrawLatex(43., gPad.GetUymin() + 0.6,"D")
elif(ptype == "Zwidth"):
textLetters.DrawLatex(6., gPad.GetUymin() +0.3,"A")
textLetters.DrawLatex(16., gPad.GetUymin() +0.3,"B")
textLetters.DrawLatex(23., gPad.GetUymin() +0.3,"C")
textLetters.DrawLatex(43., gPad.GetUymin() +0.3,"D")
elif(ptype == "Zmult") :
textLetters.DrawLatex(6., 260000,"A")
textLetters.DrawLatex(16., 260000,"B")
textLetters.DrawLatex(23., 260000,"C")
textLetters.DrawLatex(43., 260000,"D")
# ****
if(dataPeriod == "data2018"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineA = TLine(13.48, down, 13.48, up) # Run2018A up to 13.48 fb-1
lineA.SetLineColor(kBlack)
lineA.SetLineStyle(2)
lineA.Draw()
lineB = TLine(20.265, down, 20.265, up) # Run2018B up to 20.265 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(26.877, down, 26.877, up) # Run2018C up to 26.877 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
if(dataPeriod == "data2017"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(4.793, down, 4.793, up) # Run2017B up to 4.793 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(14.549, down, 14.549, up) # Run2017C up to 14.549 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(18.868, down, 18.868, up) # Run2017D up to 18.868 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(28.293, down, 28.293, up) # Run2017E up to 28.293 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
if(dataPeriod == "data2016"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.789, down, 5.789, up) # Run2016B up to 5.789 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.366, down, 8.366, up) # Run2016C up to 8.366 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.616, down, 12.616, up) # Run2016D up to 12.616 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.624, down, 16.624, up) # Run2016E up to 16.624 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.725, down, 19.725, up) # Run2016F up to 19.725 fb-1
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(27.268, down, 27.268, up) # Run2016G up to 27.268 fb-1
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
# ****
# draw orizontal lines for MC and DATA fit
if(ptype == "Zmass" or ptype == "Zwidth") :
leftEnd = gPad.GetUxmin()
rightEnd = gPad.GetUxmax()
if(DoInclusive):
line1 = TLine(leftEnd,lineMC1,rightEnd,lineMC1)
line1.SetLineColor(kBlack)
line1.SetLineStyle(1)
line1.Draw()
line2 = TLine(leftEnd,lineDATA1,rightEnd,lineDATA1)
line2.SetLineColor(kBlack)
line2.SetLineStyle(2)
line2.Draw()
# line for graph 2: color blue
line3 = TLine(leftEnd,lineMC2,rightEnd,lineMC2)
line3.SetLineColor(kBlue)
line3.SetLineStyle(1)
line3.Draw()
line4 = TLine(leftEnd,lineDATA2,rightEnd,lineDATA2)
line4.SetLineColor(kBlue)
line4.SetLineStyle(2)
line4.Draw()
# line for graph 3: color red
line5 = TLine(leftEnd,lineMC3,rightEnd,lineMC3)
line5.SetLineColor(kRed)
line5.SetLineStyle(1)
line5.Draw()
line6 = TLine(leftEnd,lineDATA3,rightEnd,lineDATA3)
line6.SetLineColor(kRed)
line6.SetLineStyle(2)
line6.Draw()
# ***
canvas.SaveAs(title + ".root")
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
lineVector = [
line1, line2, line3, line4, line5, line6, line7, line8, line9, line10,
line11, line12, line13, line14, line15, line16, line17, line18, line19,
line20, line21, line22, line23, line24, line25, line26, line27, line28,
line29, line30, line31, line32, line33, line34, line35, line36, line37,
line38, line39, line40, line41, line42, line43, line44, line45, line46,
line47, line48, line49, line50, line51, line52, line53, line54, line55,
line56, line57, line58, line59, line60, line61, line62, line63, line64
]
for line in lineVector:
line.SetLineColor(ROOT.kBlack)
line.SetLineWidth(3)
line.Draw()
leg = TLegend(.54, .78, .58, .82)
leg.SetFillStyle(0)
leg.SetLineWidth(4)
leg.Draw()
text = TLatex(.6, .78, "NA49 Coverage")
text.SetTextColor(ROOT.kBlack)
text.SetNDC()
text.SetTextSize(1.4 / 30.)
text.SetTextAlign(11)
#text.DrawLatex(.48, .55, "#Square");
text.Draw()
raw_input("Please press enter to exit.")
def GetAndDrawHistograms(DataFileName,
DataTreeName,
MCFileName,
MCTreeName,
noStack=True):
fMC = TFile(MCFileName)
tMC = fMC.Get(MCTreeName)
fData = TFile(DataFileName)
tData = fData.Get(DataTreeName)
histoListe = setupHistograms()
HistDic = {}
for i, h in enumerate(histoListe):
legende = TLegend(0.7, 0.7, 0.89, 0.89)
CanvasName = "c" + str(i)
CanvasName = TCanvas(CanvasName, 'Defining histogram size')
g = THStack("", "")
#tMC.Draw(histoListe[i][3],CutMC)
#hist_MC = tMC.GetHistogram().Clone("hist_MC")
#hist_MC.SetLineColor(6)
#hist_MC.SetLineWidth(1)
##hist_MC.SetMarkerStyle(21)
#legende.AddEntry(hist_MC, "MC", "lp")
#hist_MC.GetXaxis().SetTitle(h[1])
#hist_MC.GetYaxis().SetTitle(h[2])
#hist_MC.Scale(1/hist_MC.Integral())
#MaxMC = hist_MC.GetMaximum()
#g.Add(hist_MC)
tData.Draw(histoListe[i][3], CutData)
hist_data = tData.GetHistogram().Clone("hist_data")
hist_data.SetLineColor(9)
hist_data.SetLineWidth(1)
#hist_data.SetMarkerStyle(21)
legende.AddEntry(hist_data, "Data", "lp")
hist_data.GetXaxis().SetTitle(h[1])
hist_data.GetYaxis().SetTitle(h[2])
#hist_data.Scale(1/hist_data.Integral())
MaxData = hist_data.GetMaximum()
g.Add(hist_data)
#tData.Draw(histoListe[i][3],CutData_RS)
#hist_RS = tData.GetHistogram().Clone("hist_RS")
#hist_RS.SetLineColor(4)
#hist_RS.SetLineWidth(1)
##hist_RS.SetMarkerStyle(21)
#legende.AddEntry(hist_RS, "Data RS", "lp")
#hist_RS.Scale(1/hist_RS.Integral())
#MaxRS = hist_RS.GetMaximum()
#g.Add(hist_RS)
#if noStack:
# if (MaxMC > MaxData):
# g.SetMaximum(MaxMC*1.1)
# else:
# g.SetMaximum(MaxData*1.1)
# g.Draw("nostackhist")
#else:
# g.SetMaximum(g.GetMaximum()*1.1)
# g.Draw("hist")
g.SetMaximum(MaxData * 1.1)
g.Draw("hist")
#legende.Draw()
g.GetXaxis().SetTitle(h[1])
g.GetYaxis().SetTitle(h[2])
g.GetYaxis().SetTitleOffset(1.4)
g.GetXaxis().SetTitleOffset(1.1)
my_Latex = TLatex()
my_Latex.SetTextSize(0.04)
my_Latex.DrawLatexNDC(0.13, 0.85, "LHCb Data 2012")
CanvasName.Update()
outDir = '/sps/lhcb/volle/BMass'
if not os.path.isdir(outDir):
os.makedirs(outDir)
CanvasName.SaveAs("{}/{}_{}.pdf".format(outDir, histoListe[i][0],
comment))
CanvasName.SaveAs("{}/{}_{}.png".format(outDir, histoListe[i][0],
comment))
def MakePlots(self):
if not hasattr(self, "Numerator") or not hasattr(self, "Denominator"):
print "Either Numerator or Denominator has not been defined. Not finding hot spots..."
return
circles = []
for spots in self._hotSpotsList:
circle = TEllipse(float(spots[0]), float(spots[1]), 0.06)
circle.SetLineColor(2)
circle.SetLineWidth(1)
circle.SetFillStyle(0)
circles.append(circle)
LumiText = str.format('{0:.1f}',
self._luminosityInInvFb) + " fb^{-1} (13 TeV)"
pasLumiLatex = TLatex()
pasLumiLatex.SetNDC()
pasLumiLatex.SetTextAngle(0)
pasLumiLatex.SetTextFont(42)
pasLumiLatex.SetTextAlign(32)
pasLumiLatex.SetTextSize(0.04)
pasCMSLatex = TLatex()
pasCMSLatex.SetNDC()
pasCMSLatex.SetTextAngle(0)
pasCMSLatex.SetTextFont(62)
pasCMSLatex.SetTextAlign(12)
pasCMSLatex.SetTextSize(0.04)
pasPrelimLatex = TLatex()
pasPrelimLatex.SetNDC()
pasPrelimLatex.SetTextAngle(0)
pasPrelimLatex.SetTextFont(62)
pasPrelimLatex.SetTextAlign(12)
pasPrelimLatex.SetTextSize(0.04)
self.Denominator["histogram"].Draw('colz')
pasLumiLatex.DrawLatex(0.96, 0.93, LumiText)
pasCMSLatex.DrawLatex(0.12, 0.925, "CMS Preliminary")
self._canvas.SaveAs('fiducialMapCalc_beforeVeto_' +
self.Denominator["sample"] + '.pdf')
self.Numerator["histogram"].Draw('colz')
pasLumiLatex.DrawLatex(0.96, 0.93, LumiText)
pasCMSLatex.DrawLatex(0.12, 0.925, "CMS Preliminary")
self._canvas.SaveAs('fiducialMapCalc_afterVeto_' +
self.Numerator["sample"] + '.pdf')
self._canvas.SetLogz(False)
self.Numerator["histogram"].Divide(self.Denominator["histogram"])
self.Numerator["histogram"].Draw('colz')
if 'SingleEle' in self.Numerator["sample"]:
self.Numerator["histogram"].GetZaxis().SetRangeUser(0, 0.5)
elif 'SingleMu' in self.Numerator["sample"]:
self.Numerator["histogram"].GetZaxis().SetRangeUser(0, 0.05)
self.Numerator["histogram"].GetZaxis().SetLabelSize(0.025)
for circle in circles:
circle.Draw("same")
pasLumiLatex.DrawLatex(0.96, 0.93, LumiText)
pasCMSLatex.DrawLatex(0.12, 0.925, "CMS Preliminary")
self._canvas.SaveAs('fiducialMapCalc_efficiency_' +
self.Numerator["sample"] + '.pdf')
for xbin in range(1,
self.Numerator["histogram"].GetXaxis().GetNbins()):
for ybin in range(
1, self.Numerator["histogram"].GetYaxis().GetNbins()):
thisInefficiency = self.Numerator["histogram"].GetBinContent(
xbin, ybin)
if thisInefficiency == 0:
continue
valueInSigma = (thisInefficiency - self._meanInefficiency
) / self._stdDevInefficiency
if valueInSigma < 0:
valueInSigma = 0
self.Numerator["histogram"].SetBinContent(
xbin, ybin, valueInSigma)
self._canvas.SetLogz(False)
self.Numerator["histogram"].GetZaxis().SetLabelSize(0.04)
self.Numerator["histogram"].Draw('colz')
if 'SingleEle' in self.Numerator["sample"]:
if '2017' in self.Numerator["sample"]:
self.Numerator["histogram"].GetZaxis().SetRangeUser(0, 7)
self.Numerator["histogram"].GetZaxis().SetRangeUser(0, 12)
elif 'SingleMu' in self.Numerator["sample"]:
self.Numerator["histogram"].GetZaxis().SetRangeUser(0, 23)
self.Numerator["histogram"].GetZaxis().SetLabelSize(0.025)
for circle in circles:
circle.Draw("same")
pasLumiLatex.DrawLatex(0.96, 0.93, LumiText)
pasCMSLatex.DrawLatex(0.12, 0.925, "CMS Preliminary")
self._canvas.SaveAs('fiducialMapCalc_efficiencyInSigma_' +
self.Numerator["sample"] + '.pdf')
c4.SetBottomMargin(0.15)
c4.SetRightMargin(0.06)
#c4.SetLogy(1)
#expected95.SetMinimum(0.0001);
expected95.SetMaximum(0.0056)
expected95.Draw("a3")
expected95.GetXaxis().SetTitle("Diphoton Mass [GeV/c^{2}]")
expected95.GetYaxis().SetTitle("#sigma(G_{RS} #rightarrow #gamma #gamma)[pb]")
expected68.Draw("3same")
expected_p.Draw("csame")
observed_p.Draw("cpsame")
theory.Draw("same")
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
latex.SetTextAlign(31) # align right
latex.DrawLatex(0.45, 0.95, "CMS Preliminary")
latex2 = TLatex()
latex2.SetNDC()
latex2.SetTextSize(0.04)
latex2.SetTextAlign(31) # align right
latex2.DrawLatex(0.87, 0.95, "19.37 fb^{-1} at #sqrt{s} = 8 TeV")
latex4 = TLatex()
latex4.SetNDC()
latex4.SetTextSize(0.04)
latex4.SetTextAlign(31) # align right
def main():
output = argv[1]
rap = argv[2]
flavour = argv[3]
trackType = argv[4]
f = argv[5]
fit_min = int(argv[6])
fit_max = int(argv[7])
rebinFactor = int(argv[8])
i = int(argv[9])
if f == "CB":
DOCRYSTALBALL = True
DOCRUIJFF = False
DODOUBLECB = False
elif f == "cruijff":
DOCRUIJFF = True
DOCRYSTALBALL = False
DODOUBLECB = False
elif f == "doubleCB":
DODOUBLECB = True
DOCRYSTALBALL = False
DOCRUIJFF = False
print ("+++++++++++++++++++++++++++++++++++++++++")
print ("Fitting histogram for %d < pt_{l} <%d" %(ptbins[i],ptbins[i+1]))
print ("+++++++++++++++++++++++++++++++++++++++++\n")
wsFile = TFile("tmpWorkspace.root")
ws = wsFile.Get("tempWS")
# fit with a gaussian
if DOCRYSTALBALL:
funct = TF1("crystal","crystalball",fit_min,fit_max)
funct.SetLineColor(kRed)
if ws.data("hist").sum(False) < 1500:
nDOF = (fit_max-fit_min)*2/(rebinFactor)-3
else:
nDOF = (fit_max-fit_min)*2/rebinFactor-3
ws.factory("RooCBShape::cb(mass, mean[0.0,-1.5,1.5], sigma[2,0,10], alphaL[3,-25,25], nL[5,-25,25])")
ws.factory("BreitWigner::bw(mass,meanZ[91.187], width[2.495])")
bw = ws.pdf("bw")
cb = ws.pdf("cb")
ws.var("mass").setBins(2000,"cache")
ws.var("mass").setMin("cache",0)
ws.var("mass").setMax("cache",1000); ## need to be adjusted to be higher than limit setting
sigpdf = RooFFTConvPdf("sig","sig",ws.var("mass"),bw,cb)
getattr(ws,'import')(sigpdf,RooCmdArg())
fitResult = ws.pdf("sig").fitTo(ws.data("hist"),RooFit.Save(), RooFit.SumW2Error(kFALSE), RooFit.Minos(kFALSE))
elif DOCRUIJFF:
gSystem.Load("./RooCruijff_cxx.so")
ws.factory("RooCruijff::cb(mass, mean[0.0,-1.5,1.5], sigma[2,0,20], sigma, alphaL[1,0,25], alphaR[1,0,25])")
if ws.data("hist").sum(False) < 1500:
nDOF = (fit_max-fit_min)*2/(1)-3
elif ws.data("hist").sum(False) < 2500:
nDOF = (fit_max-fit_min)*2/(1)-3
else:
nDOF = (fit_max-fit_min)*2/rebinFactor-3
ws.factory("BreitWigner::bw(mass,meanZ[91.187], width[2.495])")
bw = ws.pdf("bw")
cb = ws.pdf("cb")
ws.var("mass").setBins(2000,"cache")
ws.var("mass").setMin("cache",0)
ws.var("mass").setMax("cache",1000); ## need to be adjusted to be higher than limit setting
sigpdf = RooFFTConvPdf("sig","sig",ws.var("mass"),bw,cb)
getattr(ws,'import')(sigpdf,RooCmdArg())
fitResult = ws.pdf("sig").fitTo(ws.data("hist"),RooFit.Save(), RooFit.SumW2Error(kFALSE), RooFit.Minos(kFALSE))
elif DODOUBLECB:
gSystem.Load("./RooDCBShape_cxx.so")
if i > 2:
ws.factory("RooDCBShape::cb(mass, mean[0.0,-1.5,1.5], sigma[2,0,20], alphaL[2,0,25] , alphaR[2,0,25], nL[2.5,0,25], nR[0])")
else:
ws.factory("RooDCBShape::cb(mass, mean[0.0,-1.5,1.5], sigma[2,0,20], alphaL[2,0,25] , alphaR[2,0,25], nL[2.5,0,25], nR[2.5,0,25])")
if i == 0:
ws.var("nL").setVal(1)
ws.var("nR").setVal(1)
ws.factory("BreitWigner::bw(mass,meanZ[91.187], width[2.495])")
bw = ws.pdf("bw")
cb = ws.pdf("cb")
ws.var("mass").setBins(2000,"cache")
ws.var("mass").setMin("cache",0)
ws.var("mass").setMax("cache",1000); ## need to be adjusted to be higher than limit setting
sigpdf = RooFFTConvPdf("sig","sig",ws.var("mass"),bw,cb)
getattr(ws,'import')(sigpdf,RooCmdArg())
fitResult = ws.pdf("sig").fitTo(ws.data("hist"),RooFit.Save(), RooFit.SumW2Error(kFALSE), RooFit.Minos(kFALSE))
chi2 = RooChi2Var("bla","blubb",ws.pdf("sig"),ws.data("hist")).getVal()
if ws.data("hist").sum(False) < 1500:
nDOF = (fit_max-fit_min)*2/(1)-5
elif ws.data("hist").sum(False) < 2500:
nDOF = (fit_max-fit_min)*2/(1)-5
else:
nDOF = (fit_max-fit_min)*2/rebinFactor-5
chi2 = RooChi2Var("bla","blubb",ws.pdf("sig"),ws.data("hist")).getVal()
mean = RooRealVar('Mean','Mean',ws.var("meanZ").getVal() )
getattr(ws,'import')(mean,RooCmdArg())
meane = RooRealVar('Meane','Meane',ws.var("meanZ").getError() )
getattr(ws,'import')(meane,RooCmdArg())
sig = RooRealVar('Sig','Sig',ws.var("sigma").getVal() )
getattr(ws,'import')(sig,RooCmdArg())
sige = RooRealVar('Sige','Sige',ws.var("sigma").getError() )
getattr(ws,'import')(sige,RooCmdArg())
c1 = TCanvas("c1","c1",700,700)
c1.cd()
plotPad = TPad("plotPad","plotPad",0,0,1,1)
style = setTDRStyle()
gStyle.SetOptStat(0)
gStyle.SetTitleXOffset(1.45)
gStyle.SetPadLeftMargin(0.2)
gStyle.SetTitleYOffset(2)
plotPad.UseCurrentStyle()
plotPad.Draw()
plotPad.cd()
if DODOUBLECB or DOCRYSTALBALL or DOCRUIJFF:
ws.var("mass").setBins(30)
frame = ws.var('mass').frame(RooFit.Title('Invariant mass of dimuon pairs'))
frame.GetXaxis().SetTitle('m_{#mu#mu} [GeV]')
frame.GetYaxis().SetTitle("Events / 2 GeV")
RooAbsData.plotOn(ws.data('hist'), frame,RooFit.Name("hist"))
ws.pdf('sig').plotOn(frame,RooFit.Name("sig"))
frame.Draw()
chi2 = frame.chiSquare("sig","hist")
else:
h.GetXaxis().SetTitle("m_{ll} [GeV]")
h.SetLineColor(kBlack)
h.GetXaxis().SetRangeUser(fit_min,fit_max)
h.SetMarkerStyle(20)
h.SetMarkerSize(0.7)
h.Draw("E")
if DOCRYSTALBALL or DOCRUIJFF or DODOUBLECB:
funct.Draw("SAME")
else:
gaus.Draw("SAME")
nDOFforWS = RooRealVar('nDOF','nDOF',nDOF )
getattr(ws,'import')(nDOFforWS,RooCmdArg())
chi2forWS = RooRealVar('chi2','chi2',chi2*nDOF )
getattr(ws,'import')(chi2forWS,RooCmdArg())
latex = TLatex()
latex.SetTextFont(42)
latex.SetTextAlign(31)
latex.SetTextSize(0.04)
latex.SetNDC(True)
latexCMS = TLatex()
latexCMS.SetTextFont(61)
latexCMS.SetTextSize(0.055)
latexCMS.SetNDC(True)
latexCMSExtra = TLatex()
latexCMSExtra.SetTextFont(52)
latexCMSExtra.SetTextSize(0.03)
latexCMSExtra.SetNDC(True)
latex.DrawLatex(0.95, 0.96, "(13 TeV)")
cmsExtra = "Preliminary"
latexCMS.DrawLatex(0.78,0.88,"CMS")
yLabelPos = 0.84
latexCMSExtra.DrawLatex(0.78,yLabelPos,"%s"%(cmsExtra))
latexFit1 = TLatex()
latexFit1.SetTextFont(42)
latexFit1.SetTextSize(0.035)
latexFit1.SetNDC(True)
latexFit1.DrawLatex(0.25, 0.84, "%d GeV < p_{T} < %d GeV" %(ptbins[i],ptbins[i+1]))
latexFit = TLatex()
latexFit.SetTextFont(42)
latexFit.SetTextSize(0.030)
latexFit.SetNDC(True)
latexFit.DrawLatex(0.25, 0.74,"%s = %5.3g #pm %5.3g GeV"%("mean bias",ws.var("mean").getVal(),ws.var("mean").getError()))
if f == "CB":
latexFit.DrawLatex(0.25, 0.7,"%s = %5.3g #pm %5.3g GeV"%("#sigma",ws.var("sigma").getVal(),ws.var("sigma").getError()))
latexFit.DrawLatex(0.25, 0.66,"%s = %5.3g #pm %5.3g"%("alphaL",ws.var("alphaL").getVal(),ws.var("alphaL").getError()))
latexFit.DrawLatex(0.25, 0.62,"%s = %5.3g #pm %5.3g"%("nL",ws.var("nL").getVal(),ws.var("nL").getError()))
elif f == "cruijff":
latexFit.DrawLatex(0.25, 0.7,"%s = %5.3g #pm %5.3g GeV"%("#sigma",ws.var("sigma").getVal(),ws.var("sigma").getError()))
latexFit.DrawLatex(0.25, 0.66,"%s = %5.3g #pm %5.3g"%("alphaL",ws.var("alphaL").getVal(),ws.var("alphaL").getError()))
latexFit.DrawLatex(0.25, 0.62,"%s = %5.3g #pm %5.3g"%("alphaR",ws.var("alphaR").getVal(),ws.var("alphaR").getError()))
elif f == "doubleCB":
latexFit.DrawLatex(0.25, 0.7,"%s = %5.3g #pm %5.3g GeV"%("#sigma",ws.var("sigma").getVal(),ws.var("sigma").getError()))
latexFit.DrawLatex(0.25, 0.66,"%s = %5.3g #pm %5.3g"%("alphaL",ws.var("alphaL").getVal(),ws.var("alphaL").getError()))
latexFit.DrawLatex(0.25, 0.62,"%s = %5.3g #pm %5.3g"%("alphaR",ws.var("alphaR").getVal(),ws.var("alphaR").getError()))
latexFit.DrawLatex(0.25, 0.58,"%s = %5.3g #pm %5.3g"%("nL",ws.var("nL").getVal(),ws.var("nL").getError()))
latexFit.DrawLatex(0.25, 0.54,"%s = %5.3g #pm %5.3g"%("nR",ws.var("nR").getVal(),ws.var("nR").getError()))
latexFit.DrawLatex(0.25, 0.5, "#chi^{2}/ndf = %5.3f / %2.0f = %4.2f" %(chi2*nDOF,nDOF,chi2))
saveas = "/MassRes_%s_%s_Pt%d_%d_%s" %(trackType,flavour,ptbins[i],ptbins[i+1],rap)
c1.SaveAs(output+saveas+".root")
c1.SaveAs(output+saveas+".C")
c1.SaveAs(output+saveas+".png")
c1.SaveAs(output+saveas+".pdf")
print ("DONE Fitting...")
ws.writeToFile("tmpWorkspaceReturn.root")
print "Max quarantined " + str(
max([e.Q for j, e in histories[i].iteritems()]))
print "Max deaths " + str(
max([e.D for j, e in histories[i].iteritems()]))
from ROOT import TH1F, TCanvas
import math
######################
# Estimation part!!! #
######################
nbins = int(0.5 * math.sqrt(n_pseudo_exp)) if n_pseudo_exp > 10 else 3
from ROOT import TLatex
latex = TLatex()
latex.SetTextSize(0.03)
latex.SetTextFont(42)
# qpeak 30000, deaths 8000, total 60000
#
# Peak of quarantined
#
qpeak = 35000
histos["q_peak"] = TH1F("q_peak", "", nbins, 0., 1e5)
for i, h in histories.iteritems():
histos["q_peak"].Fill(max([e.Q for i, e in h.iteritems()]))
canvases["q_peak"] = TCanvas("q_peak", "Peak of quarantines", 400, 400)
histos["q_peak"].SetStats(0)
histos["q_peak"].SetTitle("; Maximum of quarantined people; A.U.")
histos["q_peak"].SetLineColor(1)
def fit(histo, outdir, file=0, Ecm=0):
"""Fit the transverse profile to gat the parametrization and save in root file"""
canvas_fit = TCanvas("c_fit_{}_{}".format(histo, Ecm), "c_fit", 800, 600)
if not file:
infile = outdir + ".root"
else:
infile = file
file_ = TFile(infile, "r")
file_.cd()
g_fit = gDirectory.Get(histo)
g_fit.Draw()
par = array('d', 13 * [0.])
f1 = TF1("f1", "gaus", -4, -3.5)
g_fit.Fit(f1, "R0")
par1 = f1.GetParameters()
tail1 = TF1("tail1", "crystalball", -6, -3.5)
tail1.SetParameters(par1[0], par1[1], par1[2], 1.0, 1.6)
tail1.SetLineColor(3)
g_fit.Fit(tail1, "R0+")
par2 = tail1.GetParameters()
tail2 = TF1("tail2", "crystalball", -4, -2)
tail2.SetParameters(par1[0], par1[1], par1[2], -0.68, 1.85)
tail2.SetLineColor(4)
g_fit.Fit(tail2, "R0+")
par3 = tail2.GetParameters()
par[0], par[1], par[2] = par1[0], par1[1], par1[2]
par[3], par[4], par[5], par[6], par[7] = par2[0], par1[1], par2[2], par2[
3], par2[4]
par[8], par[9], par[10], par[11], par[12] = par3[0], par1[1], par3[
2], par3[3], par3[4]
total = TF1("total", 'gaus(0)+crystalball(3)+crystalball(8)', -6, -2.3)
total.SetParameters(par)
total.SetLineColor(1)
g_fit.Fit(total, "R+")
# gStyle.SetOptFit(1)
tot_param = total.GetParameters()
sum_sigma = sqrt(tot_param[2] * tot_param[2] +
tot_param[5] * tot_param[5] +
tot_param[10] * tot_param[10])
print sum_sigma
sum_sigma2 = sqrt(par1[2] * par1[2] + par2[2] * par2[2] +
par3[2] * par3[2])
print "Verif = ", sum_sigma2
uncertainty = TLatex()
uncertainty.DrawLatex(0, 0, "#sigma = {}".format(sum_sigma))
# write into the output file and close the file0
outFileName = "{}.root".format(outdir)
outFile = TFile(outFileName, "UPDATE")
raw_input("hit a key to exit")
canvas_fit.Write("", TObject.kOverwrite)
outFile.Write()
outFile.Close()
def do_plot(categories):
#this sets how tall the canvas is
N_cats = len(plot_categories.keys())
#sets the number of divisions on the plot
N_cuts = max(len(cuts) for cuts in plot_categories.itervalues())
canv = TCanvas('theorycomp','',500,500+200*N_cats)
main_pad_ylow = 1-(500.0/(500+200*N_cats))
rat_pad_height = main_pad_ylow/N_cats
canv.cd()
max_cs = get_max_cs(categories)
min_cs = get_min_cs(categories)
scaffold = TH1F('scaf','',N_cuts,0,N_cuts)
scaffold.GetYaxis().SetLimits(10*max_cs,min_cs/10.0)
scaffold.GetYaxis().SetRangeUser(min_cs/10.0,10*max_cs)
scaffold.SetNdivisions(100*N_cuts)
scaffold.SetStats(False)
scaffold.GetYaxis().SetTitle(y_axis_title)
unshitify(scaffold)
main_pad = TPad('main_plot','',0,main_pad_ylow,1,1,0,0,0)
main_pad.SetLogy()
main_pad.Draw()
main_pad.cd()
scaffold.Draw()
cut_labels = TLatex()
cut_labels.SetNDC()
plot_start = 0.15
column_width = (0.945 - plot_start)/N_cuts
cut_labels.SetTextSize(0.04)
cut_labels.DrawLatex(0.15,0.96,
"CMS %i, #sqrt{s} = %s"%(year,sqrts))
cut_labels.DrawLatex(0.18,0.86,luminosity)
labels_drawn = 0
ratio_pads = []
cat_meass = []
cat_preds = []
cat_meas_rats = []
cat_pred_rats = []
legend = TLegend(0.5,0.65,0.93,0.93)
legend.SetFillColor(0)
legend.SetLineColor(0)
legend.SetBorderSize(1)
for j, (cat, cuts) in enumerate(plot_categories.iteritems()):
canv.cd()
ratio_pads.append(TPad(cat,'',
0,rat_pad_height*j+0.075,
1,rat_pad_height*(j+1)+rat_pad_height/4,
0,0,0))
ratio_pads[-1].Draw()
ratio_pads[-1].cd()
rat_scaf = scaffold.DrawCopy()
rat_scaf.GetYaxis().SetLimits(-1,3)
rat_scaf.GetYaxis().SetRangeUser(0,2)
rat_scaf.GetYaxis().SetNdivisions(105)
rat_scaf.GetYaxis().SetTitle("#frac{Data}{%s}"%(prediction_name))
rat_scaf.GetYaxis().SetTitleOffset(0.6)
rat_scaf.GetYaxis().SetTitleSize(0.10)
main_pad.cd()
print j,cat
cat_meass.append([])
cat_preds.append(TGraphErrors())
cat_meas_rats.append([])
cat_pred_rats.append(TGraphErrors())
cat_preds[-1].SetName("%s (%s)"%(prediction_name,cat))
added_channels = False
for i,cut in enumerate(cuts):
cut_name = cut.keys()[0]
if len(cuts) == N_cuts and labels_drawn != len(cuts):
canv.cd()
cut_labels.DrawLatex(plot_start+column_width*(i+0.35),
0.05,
cut_name)
labels_drawn+=1
main_pad.cd()
print '\t%i : %s'%(i,cut_name)
realkeys = list(cut[cut_name].keys())
realkeys.remove('PREDICTION')
nchan = len(realkeys)
divsize = 1.0/(nchan)
if not added_channels:
cat_meass[-1] += [TGraphErrors() for l in range(nchan)]
cat_meas_rats[-1] += [TGraphErrors() for l in range(nchan)]
print cat_meass[-1]
added_channels = True
#graph entries for prediction
pcs, perr = cut[cut_name]['PREDICTION']
cat_preds[-1].SetPoint(i,i+0.5,pcs)
cat_preds[-1].SetPointError(i,0.5,perr)
cat_pred_rats[-1].SetPoint(i,i+0.5,1.0)
cat_pred_rats[-1].SetPointError(i,0.5,perr/pcs)
#graph entries for data measurement
for k, key in enumerate(realkeys):
gidx = i
print cut[cut_name][key]
cs,stat,syst = cut[cut_name][key]
err = hypot(stat,syst)
cat_meass[-1][k].SetName("%s (%s)"%(key,cat))
cat_meass[-1][k].SetPoint(gidx,
i + (k+0.5)*divsize,
cs)
cat_meass[-1][k].SetPointError(gidx,
0,
err)
cat_meas_rats[-1][k].SetPoint(gidx,
i + (k+0.5)*divsize,
cs/pcs)
cat_meas_rats[-1][k].SetPointError(gidx,
0,
err/pcs)
main_pad.cd()
cat_preds[-1].SetFillColor(fill_colors[j]-3)
cat_preds[-1].Draw('2')
legend.AddEntry(cat_preds[-1],cat_preds[-1].GetName(),'f')
for i,gr in enumerate(cat_meass[-1]):
gr.SetMarkerStyle(20+4*j+i)
gr.Draw('pe1')
legend.AddEntry(gr,gr.GetName(),'pl')
ratio_pads[-1].cd()
cat_pred_rats[-1].SetFillColor(fill_colors[j]-3)
cat_pred_rats[-1].Draw('2')
for i,gr in enumerate(cat_meas_rats[-1]):
gr.SetMarkerStyle(20+4*j+i)
gr.Draw('pe1')
main_pad.cd()
legend.Draw()
canv.cd()
cut_labels.DrawLatex(0.80,0.015,'E_{T}^{#gamma} (GeV)')
canv.Print('vgamma_theory_comparison.pdf')
canv.Print('vgamma_theory_comparison.eps')
canv.Print('vgamma_theory_comparison.png')
def make_comparison_plot(outdir, var, groupname1, groupname2, category, weight = "PU_weight*MC_weight*bTagSF_weight*leptonSF_weight*triggerSF_weight*FR_weight", dataset = "ttH"):
var_name = var[0]
n_bins = var[3]
range_low = var[4]
range_high = var[5]
histos = []
plot_name = "p" #segfault when using different names for each
#"%s_%s_%s_%s_%s_vs_%s" % (outdir, var_name, dataset, category, groupname1, groupname2)
name1 = "plot_%s_%s" % (groupname1, plot_name)
plot1 = single_plot("%s/%s" % (groups[groupname1]["inputPath"], groups[groupname1]["inputFiles"][dataset]),
name1,
"%s_%s" % (groups[groupname1]["treePrefix"], category),
var_name,
weight,
n_bins, range_low, range_high)
name2 = "plot_%s_%s" % (groupname2, plot_name)
plot2 = single_plot("%s/%s" % (groups[groupname2]["inputPath"], groups[groupname2]["inputFiles"][dataset]),
name2,
"%s_%s" % (groups[groupname2]["treePrefix"], category),
var_name,
weight,
n_bins, range_low, range_high)
histos.append(plot1)
histos.append(plot2)
leg_entry = []
leg_entry.append("%s:\t N=%d, mean=%.2f, RMS=%.2f" % (groupname1, plot1.GetEntries(), plot1.GetMean(), plot1.GetRMS()))
leg_entry.append("%s:\t N=%d, mean=%.2f, RMS=%.2f" % (groupname2, plot2.GetEntries(), plot2.GetMean(), plot2.GetRMS()))
leg=TLegend(0.45,0.74,0.85,0.89)
leg.SetHeader(get_header(category));
leg.SetBorderSize(0)
leg.SetTextSize(0.04)
leg.SetFillColor(0)
for i in range(len(histos)):
normalize_histogram(histos[i])
leg.AddEntry(histos[i], leg_entry[i])
histos[0].SetLineColor(ROOT.kOrange-2)
histos[0].SetFillColor(ROOT.kOrange-2)
histos[0].SetStats(0)
histos[0].SetTitle("")
histos[1].SetLineColor(1)
histos[1].SetLineWidth(2)
c=TCanvas("c_%s" % plot_name,"c_%s" % plot_name, 800, 600)
pad1 = TPad("pad1", "pad1", 0, 0.3, 1, 1.0)
pad1.SetLeftMargin(0.15)
pad1.SetBottomMargin(0) # Upper and lower plot are joined
pad1.Draw() # Draw the upper pad: pad1
pad1.cd() # pad1 becomes the current pad
max_val = 0.1
min_val = 0
for i in range(len(histos)):
max_val = max(histos[i].GetMaximum(), max_val)
min_val = min(histos[i].GetMinimum(), min_val)
for i in range(len(histos)):
histos[i].SetMaximum(1.4*max_val)
histos[i].SetMinimum(1.4*min_val)
histos[i].GetXaxis().SetTitle(var_name)
histos[i].GetYaxis().SetTitle("a.u.")
histos[i].GetYaxis().SetTitleOffset(1.7)
#histos[i].GetYaxis().SetTickLength(0)
#histos[i].GetYaxis().SetLabelOffset(999)
texl = TLatex(histos[0].GetBinLowEdge(1), 1.01*1.4*max_val, "CMS Preliminary, Simulation ttH #sqrt{s}=13 TeV")
texl.SetTextSize(0.04)
texl.Draw("same")
histos[0].Draw("hist")
histos[1].Draw("same")
leg.Draw("same")
texl.Draw("same")
histos[0].GetYaxis().SetLabelSize(0.)
axis = TGaxis(range_low, min_val, range_low, max_val, min_val, max_val, 510, "")
axis.SetLabelFont(43) #Absolute font size in pixel (precision 3)
axis.SetLabelSize(15)
axis.Draw()
# lower plot will be in pad
c.cd() # Go back to the main canvas before defining pad2
pad2 = TPad("pad2", "pad2", 0, 0.05, 1, 0.3)
pad2.SetLeftMargin(0.15)
pad2.SetTopMargin(0)
pad2.SetBottomMargin(0.35)
pad2.Draw()
pad2.cd()
h_ratio = make_ratio_histogram("h_ratio", histos[1], histos[0])
"""
h_ratio = h[1].Clone("h_ratio")
"""
h_ratio.SetTitle("")
h_ratio.Draw() #Draw the ratio plot
# Y axis histo_emul plot settings
histos[0].GetYaxis().SetTitleSize(20)
histos[0].GetYaxis().SetTitleFont(43)
histos[0].GetYaxis().SetTitleOffset(1.5)
# Ratio plot (h_ratio) settings
#h_ratio.SetTitle("") # Remove the ratio title
h_ratio.GetYaxis().SetLabelSize(0.)
axis2 = TGaxis( range_low, 0.01, range_low, 1.99, 0.01, 1.99, 505,"")
axis2.SetLabelFont(43) # Absolute font size in pixel (precision 3)
axis2.SetLabelSize(15)
axis2.Draw()
# Y axis ratio plot settings
h_ratio.GetYaxis().SetTitle("%s/%s" % (groupname2, groupname1))
h_ratio.GetYaxis().SetNdivisions(505)
h_ratio.GetYaxis().SetTitleSize(20)
h_ratio.GetYaxis().SetTitleFont(43)
h_ratio.GetYaxis().SetTitleOffset(1.5)
#h_ratio.GetYaxis().SetLabelFont(43) # Absolute font size in pixel (precision 3)
#h_ratio.GetYaxis().SetLabelSize(15)
# X axis ratio plot settings
h_ratio.GetXaxis().SetTitleSize(20)
h_ratio.GetXaxis().SetTitleFont(43)
h_ratio.GetXaxis().SetTitleOffset(4.)
h_ratio.GetXaxis().SetLabelFont(43) # Absolute font size in pixel (precision 3)
h_ratio.GetXaxis().SetLabelSize(15)
line = TLine(range_low, 1., range_high,1.)
line.Draw("same")
plot_file_name="%s" % (var_name)
dirname = ("%s_vs_%s/%s/%s" % (groupname1, groupname2, category, outdir)).replace(" ", "_")
for file_format in ["png", "pdf"]:
mkdir_p("plots_test/%s/%s" % (dirname, file_format))
c.SaveAs("plots_test/%s/%s/%s.%s" % (dirname, file_format, plot_file_name, file_format))
legend4.Draw("same")
#legend2=TLegend(0.17,0.8,0.5,0.85,str(minpt)+" < p_{T} < "+str(maxpt)+" GeV")
legend2 = TLegend(0.17, 0.8, 0.5, 0.85,
"p_{T} > " + str(minpt) + " GeV, |#eta|<2.4")
legend2.SetTextSize(0.03)
legend2.SetFillStyle(0)
legend2.Draw("same")
legend2a = TLegend(0.17, 0.75, 0.5, 0.8, "massdrop < 0.4")
legend2a.SetTextSize(0.03)
legend2a.SetFillStyle(0)
#legend2a.Draw("same")
banner = TLatex(
0.27, 0.93,
" CMS L = 2.3 fb^{-1} at #sqrt{s} = 13 TeV, dijets")
banner.SetNDC()
banner.SetTextSize(0.04)
banner.Draw()
legend3 = TLegend(
0.17, 0.7, 0.5, 0.75,
str(cuts[max(0,
cuts.index(cut) - 1)]) + "<#tau_{2}/#tau_{1}<" +
str(cut))
legend3.SetTextSize(0.03)
legend3.SetFillStyle(0)
#legend3.Draw("same")
legend3 = TLegend(
# Setup basic drawer
gROOT.LoadMacro("tdrstyle.C")
gROOT.ProcessLine("setTDRStyle();")
#gROOT.SetBatch(True)
gStyle.SetPadGridX(True)
gStyle.SetPadGridY(True)
#gStyle.SetPadRightMargin(0.05)
#gStyle.SetTitleOffset(0.9, "Y")
#gStyle.SetTitleOffset(1.2, "Y")
gROOT.ForceStyle()
tline = TLine()
tline.SetLineColor(920 + 2) # kGray+2
tline.SetLineStyle(2)
tlatexCMS1 = TLatex()
tlatexCMS1.SetNDC()
tlatexCMS1.SetTextFont(61)
tlatexCMS1.SetTextSize(0.75 * 0.05)
tlatexCMS2 = TLatex()
tlatexCMS2.SetNDC()
tlatexCMS2.SetTextFont(52)
tlatexCMS2.SetTextSize(0.60 * 0.05)
tlatexCMS3 = TLatex()
tlatexCMS3.SetNDC()
tlatexCMS3.SetTextFont(42)
tlatexCMS3.SetTextSize(0.60 * 0.05)
tlatexCMS3.SetTextAlign(11)
def main():
gStyle.SetOptStat(0)
zplist = [600, 600, 1200, 1200, 2000, 2000]
a0list = [300, 400, 300, 500, 300, 600]
c1 = TCanvas('c1', 'c1', 3)
gPad.SetTickx()
gPad.SetTicky()
c1.SetLeftMargin(0.12)
h_frame = TH1F('frame', '', 60, 0, 1200)
h_frame.SetXTitle('P^{miss}_{T} (GeV)')
h_frame.SetYTitle('Arbitrary units')
h_frame.SetMaximum(0.3)
h_higgsPt = TH1F('h_higgsPt', 'h_higgsPt', 60, 0, 1200)
h_higgsPtList = []
rootfilelist = []
for i in range(6):
fName = 'rootFile/higgsPt_MZp' + str(zplist[i]) + '_MA0' + str(
a0list[i]) + '.root'
rootfile = TFile(fName)
rootfilelist.append(rootfile)
colorList = [61, 95, 65, 91, 69, 87]
for i in range(6):
hist = rootfilelist[i].Get('h_higgsPt')
hist.SetName('h_higgsPt_MZp' + str(zplist[i]) + '_MA0' +
str(a0list[i]))
h_higgsPtList.append(hist)
h_higgsPtList[i].SetLineWidth(2)
h_higgsPtList[i].SetLineColor(colorList[i])
info_bar = TLatex(0, 0.305, 'CMS')
info_bar_3 = TLatex(700, 0.15, '#font[42]{tan#beta=1.0}')
info_bar_2 = TLatex(1200, 0.305, '35.9 fb^{-1} (13 TeV)')
info_bar.SetTextSize(0.03)
info_bar_2.SetTextSize(0.03)
info_bar_3.SetTextSize(0.04)
info_bar_2.SetTextAlign(31)
leg = TLegend(0.32, 0.57, 0.87, 0.87)
leg.SetBorderSize(0)
for j in range(3):
i = 2 * j
text = 'M_{Z\'} = ' + str(zplist[i]) + ' GeV, M_{A} = ' + str(
a0list[i]) + ' GeV'
leg.AddEntry(h_higgsPtList[i], text)
for j in range(3):
i = 2 * j + 1
text = 'M_{Z\'} = ' + str(zplist[i]) + ' GeV, M_{A} = ' + str(
a0list[i]) + ' GeV'
leg.AddEntry(h_higgsPtList[i], text)
h_frame.Draw('hist')
for i in range(6):
h_higgsPtList[i].DrawNormalized('histsame')
leg.Draw()
info_bar.Draw()
info_bar_2.Draw()
info_bar_3.Draw()
c1.Print('Zp2HDM_higgsPt_new.pdf')
'''
line6 = TLine(31, 1.55, 42, 1.55)
line7 = TLine(42, 1.55, 42, 2)
line8 = TLine(42, 2, 60, 2)
line9 = TLine(60, 2, 90, 2)
line10 = TLine(90, 2, 90, 0)
line11 = TLine(90, 0, 20, 0)
lineVector = [
line1, line2, line3, line4, line5, line6, line7, line8, line9, line10,
line11
]
for line in lineVector:
line.SetLineColor(ROOT.kBlack)
line.SetLineWidth(3)
line.Draw()
leg = TLegend(.61, .55, .65, .59)
leg.SetFillStyle(0)
leg.SetLineWidth(4)
leg.Draw()
text = TLatex(.67, .55, "MIPP Coverage")
text.SetTextColor(ROOT.kBlack)
text.SetNDC()
text.SetTextSize(1.4 / 30.)
text.SetTextAlign(11)
#text.DrawLatex(.48, .55, "#Square");
text.Draw()
raw_input("Please press enter to exit.")
def SAME2VsLumi(g1, g2,title, ptype, dataPeriod):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
graph1=copy.deepcopy(g1)
graph2=copy.deepcopy(g2)
graph1.SetMarkerColor(kBlue)#electrons
graph2.SetMarkerColor(kRed)#muons
multigraph = TMultiGraph()
multigraph.Add(graph1,"AP")
multigraph.Add(graph2,"AP")
multigraph.Draw("AP")
TGaxis.SetMaxDigits(2)
TGaxis.SetExponentOffset(-0.06, 0.02, "y")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetYaxis().SetTitleOffset(1.4)
if(ptype == "ISO"):
multigraph.GetYaxis().SetTitle("Isolation")
gPad.Modified()
multigraph.SetMinimum(0.5*gPad.GetUymin())
multigraph.SetMaximum(1.5*gPad.GetUymax())
elif(ptype == "SIP"):
multigraph.GetYaxis().SetTitle("SIP")
multigraph.SetMinimum(min(multigraph.GetHistogram().GetMinimum(),1.))
multigraph.SetMaximum(max(multigraph.GetHistogram().GetMinimum(),2.2))
min(multigraph.GetHistogram().GetMinimum(),1.)
printLumiPrelOut(canvas)
# Draw legend
legend = TLegend(0.93,0.84,0.99,0.93)
legend.AddEntry(graph1,"e^{+}e^{-}","P")
legend.AddEntry(graph2,"#mu^{+}#mu^{-}","P")
legend.SetFillColor(kWhite)
legend.SetLineColor(kBlack)
legend.SetTextFont(43)
legend.SetTextSize(20)
legend.Draw()
canvas.Update()
# Draw letters for data-taking periods
if(dataPeriod == "data2017"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "ISO"):
textLetters.DrawLatex(2., 0.8*gPad.GetUymax(),"B")
textLetters.DrawLatex(9.5, 0.8*gPad.GetUymax(),"C")
textLetters.DrawLatex(16., 0.8*gPad.GetUymax(),"D")
textLetters.DrawLatex(23., 0.8*gPad.GetUymax(),"E")
textLetters.DrawLatex(36., 0.8*gPad.GetUymax(),"F")
elif(ptype == "SIP"):
textLetters.DrawLatex(2., 1.5,"B")
textLetters.DrawLatex(9.5, 1.5,"C")
textLetters.DrawLatex(16., 1.5,"D")
textLetters.DrawLatex(23., 1.5,"E")
textLetters.DrawLatex(36., 1.5,"F")
if(dataPeriod == "data2018"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "ISO"):
textLetters.DrawLatex(6., 0.8*gPad.GetUymax(), "A")
textLetters.DrawLatex(16., 0.8*gPad.GetUymax(), "B")
textLetters.DrawLatex(23., 0.8*gPad.GetUymax(), "C")
textLetters.DrawLatex(43., 0.8*gPad.GetUymax(), "D")
elif(ptype == "SIP"):
textLetters.DrawLatex(6., 1.5, "A")
textLetters.DrawLatex(16., 1.5, "B")
textLetters.DrawLatex(23., 1.5, "C")
textLetters.DrawLatex(43., 1.5, "D")
# ****
if(dataPeriod == "data2018"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineA = TLine(13.48, down, 13.48, up) # Run2018A up to 13.48 fb-1
lineA.SetLineColor(kBlack)
lineA.SetLineStyle(2)
lineA.Draw()
lineB = TLine(20.265, down, 20.265, up) # Run2018B up to 20.265 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(26.877, down, 26.877, up) # Run2018C up to 26.877 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
# ****
if(dataPeriod == "data2017"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(4.793, down, 4.793, up) # Run2017B up to 4.793 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(14.549, down, 14.549, up) # Run2017C up to 14.549 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(18.868, down, 18.868, up) # Run2017D up to 18.868 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(28.293, down, 28.293, up) # Run2017E up to 28.293 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
# ****
if(dataPeriod == "data2016"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.789, down, 5.789, up) # Run2016B up to 5.789 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.366, down, 8.366, up) # Run2016C up to 8.366 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.616, down, 12.616, up) # Run2016D up to 12.616 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.624, down, 16.624, up) # Run2016E up to 16.624 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.725, down, 19.725, up) # Run2016F up to 19.725 fb-1
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(27.268, down, 27.268, up) # Run2016G up to 27.268 fb-1
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
# ****
canvas.SaveAs(title + ".root")
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
def dijet(category):
channel = 'bb'
stype = channel
isSB = True # relict from using Alberto's more complex script
isData = not ISMC
nTupleDir = NTUPLEDIR
samples = data if isData else back
pd = []
for sample_name in samples:
if YEAR == 'run2':
pd += sample[sample_name]['files']
else:
pd += [x for x in sample[sample_name]['files'] if YEAR in x]
print "datasets:", pd
if not os.path.exists(PLOTDIR): os.makedirs(PLOTDIR)
if BIAS: print "Running in BIAS mode"
order = 0
RSS = {}
X_mass = RooRealVar("jj_mass_widejet", "m_{jj}", X_min, X_max, "GeV")
weight = RooRealVar("MANtag_weight", "", -1.e9, 1.e9)
variables = RooArgSet(X_mass)
variables.add(RooArgSet(weight))
if VARBINS:
binsXmass = RooBinning(len(abins) - 1, abins)
X_mass.setBinning(RooBinning(len(abins_narrow) - 1, abins_narrow))
plot_binning = RooBinning(
int((X_mass.getMax() - X_mass.getMin()) / 100), X_mass.getMin(),
X_mass.getMax())
else:
X_mass.setBins(int((X_mass.getMax() - X_mass.getMin()) / 10))
binsXmass = RooBinning(int((X_mass.getMax() - X_mass.getMin()) / 100),
X_mass.getMin(), X_mass.getMax())
plot_binning = binsXmass
baseCut = ""
print stype, "|", baseCut
print " - Reading from Tree"
treeBkg = TChain("tree")
for ss in pd:
if os.path.exists(nTupleDir + ss + "_" + BTAGGING + ".root"):
treeBkg.Add(nTupleDir + ss + "_" + BTAGGING + ".root")
else:
print "found no file for sample:", ss
setData = RooDataSet("setData", "Data (QCD+TTbar MC)", variables,
RooFit.Cut(baseCut), RooFit.WeightVar(weight),
RooFit.Import(treeBkg))
nevents = setData.sumEntries()
dataMin, dataMax = array('d', [0.]), array('d', [0.])
setData.getRange(X_mass, dataMin, dataMax)
xmin, xmax = dataMin[0], dataMax[0]
lastBin = X_mass.getMax()
if VARBINS:
for b in narrow_bins:
if b > xmax:
lastBin = b
break
print "Imported", (
"data" if isData else "MC"
), "RooDataSet with", nevents, "events between [%.1f, %.1f]" % (xmin, xmax)
#xmax = xmax+binsXmass.averageBinWidth() # start form next bin
# 1 parameter
print "fitting 1 parameter model"
p1_1 = RooRealVar("CMS" + YEAR + "_" + category + "_p1_1", "p1", 7.0, 0.,
2000.)
modelBkg1 = RooGenericPdf("Bkg1", "Bkg. fit (2 par.)",
"1./pow(@0/13000, @1)", RooArgList(X_mass, p1_1))
normzBkg1 = RooRealVar(
modelBkg1.GetName() + "_norm", "Number of background events", nevents,
0., 5. * nevents) #range dependent of actual number of events!
modelExt1 = RooExtendPdf(modelBkg1.GetName() + "_ext",
modelBkg1.GetTitle(), modelBkg1, normzBkg1)
fitRes1 = modelExt1.fitTo(setData, RooFit.Extended(True), RooFit.Save(1),
RooFit.SumW2Error(not isData),
RooFit.Strategy(2), RooFit.Minimizer("Minuit2"),
RooFit.PrintLevel(1 if VERBOSE else -1))
fitRes1.Print()
RSS[1] = drawFit("Bkg1", category, X_mass, modelBkg1, setData, binsXmass,
[fitRes1], normzBkg1.getVal())
# 2 parameters
print "fitting 2 parameter model"
p2_1 = RooRealVar("CMS" + YEAR + "_" + category + "_p2_1", "p1", 0., -100.,
1000.)
p2_2 = RooRealVar("CMS" + YEAR + "_" + category + "_p2_2", "p2",
p1_1.getVal(), -100., 600.)
modelBkg2 = RooGenericPdf("Bkg2", "Bkg. fit (3 par.)",
"pow(1-@0/13000, @1) / pow(@0/13000, @2)",
RooArgList(X_mass, p2_1, p2_2))
normzBkg2 = RooRealVar(modelBkg2.GetName() + "_norm",
"Number of background events", nevents, 0.,
5. * nevents)
modelExt2 = RooExtendPdf(modelBkg2.GetName() + "_ext",
modelBkg2.GetTitle(), modelBkg2, normzBkg2)
fitRes2 = modelExt2.fitTo(setData, RooFit.Extended(True), RooFit.Save(1),
RooFit.SumW2Error(not isData),
RooFit.Strategy(2), RooFit.Minimizer("Minuit2"),
RooFit.PrintLevel(1 if VERBOSE else -1))
fitRes2.Print()
RSS[2] = drawFit("Bkg2", category, X_mass, modelBkg2, setData, binsXmass,
[fitRes2], normzBkg2.getVal())
# 3 parameters
print "fitting 3 parameter model"
p3_1 = RooRealVar("CMS" + YEAR + "_" + category + "_p3_1", "p1",
p2_1.getVal(), -2000., 2000.)
p3_2 = RooRealVar("CMS" + YEAR + "_" + category + "_p3_2", "p2",
p2_2.getVal(), -400., 2000.)
p3_3 = RooRealVar("CMS" + YEAR + "_" + category + "_p3_3", "p3", -2.5,
-500., 500.)
modelBkg3 = RooGenericPdf(
"Bkg3", "Bkg. fit (4 par.)",
"pow(1-@0/13000, @1) / pow(@0/13000, @2+@3*log(@0/13000))",
RooArgList(X_mass, p3_1, p3_2, p3_3))
normzBkg3 = RooRealVar(modelBkg3.GetName() + "_norm",
"Number of background events", nevents, 0.,
5. * nevents)
modelExt3 = RooExtendPdf(modelBkg3.GetName() + "_ext",
modelBkg3.GetTitle(), modelBkg3, normzBkg3)
fitRes3 = modelExt3.fitTo(setData, RooFit.Extended(True), RooFit.Save(1),
RooFit.SumW2Error(not isData),
RooFit.Strategy(2), RooFit.Minimizer("Minuit2"),
RooFit.PrintLevel(1 if VERBOSE else -1))
fitRes3.Print()
RSS[3] = drawFit("Bkg3", category, X_mass, modelBkg3, setData, binsXmass,
[fitRes3], normzBkg3.getVal())
# 4 parameters
print "fitting 4 parameter model"
p4_1 = RooRealVar("CMS" + YEAR + "_" + category + "_p4_1", "p1",
p3_1.getVal(), -2000., 2000.)
p4_2 = RooRealVar("CMS" + YEAR + "_" + category + "_p4_2", "p2",
p3_2.getVal(), -2000., 2000.)
p4_3 = RooRealVar("CMS" + YEAR + "_" + category + "_p4_3", "p3",
p3_3.getVal(), -50., 50.)
p4_4 = RooRealVar("CMS" + YEAR + "_" + category + "_p4_4", "p4", 0.1, -50.,
50.)
modelBkg4 = RooGenericPdf(
"Bkg4", "Bkg. fit (5 par.)",
"pow(1 - @0/13000, @1) / pow(@0/13000, @2+@3*log(@0/13000)+@4*pow(log(@0/13000), 2))",
RooArgList(X_mass, p4_1, p4_2, p4_3, p4_4))
normzBkg4 = RooRealVar(modelBkg4.GetName() + "_norm",
"Number of background events", nevents, 0.,
5. * nevents)
modelExt4 = RooExtendPdf(modelBkg4.GetName() + "_ext",
modelBkg4.GetTitle(), modelBkg4, normzBkg4)
fitRes4 = modelExt4.fitTo(setData, RooFit.Extended(True), RooFit.Save(1),
RooFit.SumW2Error(not isData),
RooFit.Strategy(2), RooFit.Minimizer("Minuit2"),
RooFit.PrintLevel(1 if VERBOSE else -1))
fitRes4.Print()
RSS[4] = drawFit("Bkg4", category, X_mass, modelBkg4, setData, binsXmass,
[fitRes4], normzBkg4.getVal())
# Normalization parameters are should be set constant, but shape ones should not
# if BIAS:
# p1_1.setConstant(True)
# p2_1.setConstant(True)
# p2_2.setConstant(True)
# p3_1.setConstant(True)
# p3_2.setConstant(True)
# p3_3.setConstant(True)
# p4_1.setConstant(True)
# p4_2.setConstant(True)
# p4_3.setConstant(True)
# p4_4.setConstant(True)
normzBkg1.setConstant(True)
normzBkg2.setConstant(True)
normzBkg3.setConstant(True)
normzBkg4.setConstant(True)
#*******************************************************#
# #
# Fisher #
# #
#*******************************************************#
# Fisher test
with open(PLOTDIR + "/Fisher_" + category + ".tex", 'w') as fout:
fout.write(r"\begin{tabular}{c|c|c|c|c}")
fout.write("\n")
fout.write(r"function & $\chi^2$ & RSS & ndof & F-test \\")
fout.write("\n")
fout.write("\hline")
fout.write("\n")
CL_high = False
for o1 in range(1, 5):
o2 = min(o1 + 1, 5)
fout.write("%d par & %.2f & %.2f & %d & " %
(o1 + 1, RSS[o1]["chi2"], RSS[o1]["rss"],
RSS[o1]["nbins"] - RSS[o1]["npar"]))
if o2 > len(RSS):
fout.write(r"\\")
fout.write("\n")
continue #order==0 and
CL = fisherTest(RSS[o1]['rss'], RSS[o2]['rss'], o1 + 1., o2 + 1.,
RSS[o1]["nbins"])
fout.write("CL=%.3f " % (CL))
if CL > 0.10: # The function with less parameters is enough
if not CL_high:
order = o1
#fout.write( "%d par are sufficient " % (o1+1))
CL_high = True
else:
#fout.write( "%d par are needed " % (o2+1))
if not CL_high:
order = o2
fout.write(r"\\")
fout.write("\n")
fout.write("\hline")
fout.write("\n")
fout.write(r"\end{tabular}")
print "saved F-test table as", PLOTDIR + "/Fisher_" + category + ".tex"
#print "-"*25
#print "function & $\\chi^2$ & RSS & ndof & F-test & result \\\\"
#print "\\multicolumn{6}{c}{", "Zprime_to_bb", "} \\\\"
#print "\\hline"
#CL_high = False
#for o1 in range(1, 5):
# o2 = min(o1 + 1, 5)
# print "%d par & %.2f & %.2f & %d & " % (o1+1, RSS[o1]["chi2"], RSS[o1]["rss"], RSS[o1]["nbins"]-RSS[o1]["npar"]),
# if o2 > len(RSS):
# print "\\\\"
# continue #order==0 and
# CL = fisherTest(RSS[o1]['rss'], RSS[o2]['rss'], o1+1., o2+1., RSS[o1]["nbins"])
# print "%d par vs %d par CL=%f & " % (o1+1, o2+1, CL),
# if CL > 0.10: # The function with less parameters is enough
# if not CL_high:
# order = o1
# print "%d par are sufficient" % (o1+1),
# CL_high=True
# else:
# print "%d par are needed" % (o2+1),
# if not CL_high:
# order = o2
# print "\\\\"
#print "\\hline"
#print "-"*25
#print "@ Order is", order, "("+category+")"
#order = min(3, order)
#order = 2
if order == 1:
modelBkg = modelBkg1 #.Clone("Bkg")
modelAlt = modelBkg2 #.Clone("BkgAlt")
normzBkg = normzBkg1 #.Clone("Bkg_norm")
fitRes = fitRes1
elif order == 2:
modelBkg = modelBkg2 #.Clone("Bkg")
modelAlt = modelBkg3 #.Clone("BkgAlt")
normzBkg = normzBkg2 #.Clone("Bkg_norm")
fitRes = fitRes2
elif order == 3:
modelBkg = modelBkg3 #.Clone("Bkg")
modelAlt = modelBkg4 #.Clone("BkgAlt")
normzBkg = normzBkg3 #.Clone("Bkg_norm")
fitRes = fitRes3
elif order == 4:
modelBkg = modelBkg4 #.Clone("Bkg")
modelAlt = modelBkg3 #.Clone("BkgAlt")
normzBkg = normzBkg4 #.Clone("Bkg_norm")
fitRes = fitRes4
else:
print "Functions with", order + 1, "or more parameters are needed to fit the background"
exit()
modelBkg.SetName("Bkg_" + YEAR + "_" + category)
modelAlt.SetName("Alt_" + YEAR + "_" + category)
normzBkg.SetName("Bkg_" + YEAR + "_" + category + "_norm")
print "-" * 25
# Generate pseudo data
setToys = RooDataSet()
setToys.SetName("data_toys")
setToys.SetTitle("Data (toys)")
if not isData:
print " - Generating", nevents, "events for toy data"
setToys = modelBkg.generate(RooArgSet(X_mass), nevents)
#setToys = modelAlt.generate(RooArgSet(X_mass), nevents)
print "toy data generated"
if VERBOSE: raw_input("Press Enter to continue...")
#*******************************************************#
# #
# Plot #
# #
#*******************************************************#
print "starting to plot"
c = TCanvas("c_" + category, category, 800, 800)
c.Divide(1, 2)
setTopPad(c.GetPad(1), RATIO)
setBotPad(c.GetPad(2), RATIO)
c.cd(1)
frame = X_mass.frame()
setPadStyle(frame, 1.25, True)
if VARBINS: frame.GetXaxis().SetRangeUser(X_mass.getMin(), lastBin)
signal = getSignal(
category, stype,
2000) #replacing Alberto's getSignal by own dummy function
graphData = setData.plotOn(frame, RooFit.Binning(plot_binning),
RooFit.Scaling(False), RooFit.Invisible())
modelBkg.plotOn(frame, RooFit.VisualizeError(fitRes, 1, False),
RooFit.LineColor(602), RooFit.FillColor(590),
RooFit.FillStyle(1001), RooFit.DrawOption("FL"),
RooFit.Name("1sigma"))
modelBkg.plotOn(frame, RooFit.LineColor(602), RooFit.FillColor(590),
RooFit.FillStyle(1001), RooFit.DrawOption("L"),
RooFit.Name(modelBkg.GetName()))
modelAlt.plotOn(frame, RooFit.LineStyle(7), RooFit.LineColor(613),
RooFit.FillColor(609), RooFit.FillStyle(1001),
RooFit.DrawOption("L"), RooFit.Name(modelAlt.GetName()))
if not isSB and signal[0] is not None: # FIXME remove /(2./3.)
signal[0].plotOn(
frame,
RooFit.Normalization(signal[1] * signal[2], RooAbsReal.NumEvent),
RooFit.LineStyle(3), RooFit.LineWidth(6), RooFit.LineColor(629),
RooFit.DrawOption("L"), RooFit.Name("Signal"))
graphData = setData.plotOn(
frame, RooFit.Binning(plot_binning), RooFit.Scaling(False),
RooFit.XErrorSize(0 if not VARBINS else 1),
RooFit.DataError(RooAbsData.Poisson if isData else RooAbsData.SumW2),
RooFit.DrawOption("PE0"), RooFit.Name(setData.GetName()))
fixData(graphData.getHist(), True, True, not isData)
pulls = frame.pullHist(setData.GetName(), modelBkg.GetName(), True)
chi = frame.chiSquare(setData.GetName(), modelBkg.GetName(), True)
#setToys.plotOn(frame, RooFit.DataError(RooAbsData.Poisson), RooFit.DrawOption("PE0"), RooFit.MarkerColor(2))
frame.GetYaxis().SetTitle("Events / ( 100 GeV )")
frame.GetYaxis().SetTitleOffset(1.05)
frame.Draw()
#print "frame drawn"
# Get Chi2
# chi2[1] = frame.chiSquare(modelBkg1.GetName(), setData.GetName())
# chi2[2] = frame.chiSquare(modelBkg2.GetName(), setData.GetName())
# chi2[3] = frame.chiSquare(modelBkg3.GetName(), setData.GetName())
# chi2[4] = frame.chiSquare(modelBkg4.GetName(), setData.GetName())
frame.SetMaximum(frame.GetMaximum() * 10)
frame.SetMinimum(max(frame.GetMinimum(), 1.e-1))
c.GetPad(1).SetLogy()
drawAnalysis(category)
drawRegion(category, True)
#drawCMS(LUMI, "Simulation Preliminary")
drawCMS(LUMI, "Work in Progress", suppressCMS=True)
leg = TLegend(0.575, 0.6, 0.95, 0.9)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.AddEntry(setData.GetName(),
setData.GetTitle() + " (%d events)" % nevents, "PEL")
leg.AddEntry(modelBkg.GetName(), modelBkg.GetTitle(),
"FL") #.SetTextColor(629)
leg.AddEntry(modelAlt.GetName(), modelAlt.GetTitle(), "L")
if not isSB and signal[0] is not None:
leg.AddEntry("Signal", signal[0].GetTitle(), "L")
leg.SetY1(0.9 - leg.GetNRows() * 0.05)
leg.Draw()
latex = TLatex()
latex.SetNDC()
latex.SetTextSize(0.04)
latex.SetTextFont(42)
if not isSB:
latex.DrawLatex(leg.GetX1() * 1.16,
leg.GetY1() - 0.04, "HVT model B (g_{V}=3)")
# latex.DrawLatex(0.67, leg.GetY1()-0.045, "#sigma_{X} = 1.0 pb")
c.cd(2)
frame_res = X_mass.frame()
setPadStyle(frame_res, 1.25)
frame_res.addPlotable(pulls, "P")
setBotStyle(frame_res, RATIO, False)
if VARBINS: frame_res.GetXaxis().SetRangeUser(X_mass.getMin(), lastBin)
frame_res.GetYaxis().SetRangeUser(-5, 5)
frame_res.GetYaxis().SetTitle("pulls(#sigma)")
frame_res.GetYaxis().SetTitleOffset(0.3)
frame_res.Draw()
fixData(pulls, False, True, False)
drawChi2(RSS[order]["chi2"], RSS[order]["nbins"] - (order + 1), True)
line = drawLine(X_mass.getMin(), 0, lastBin, 0)
if VARBINS:
c.SaveAs(PLOTDIR + "/BkgSR_" + category + ".pdf")
c.SaveAs(PLOTDIR + "/BkgSR_" + category + ".png")
else:
c.SaveAs(PLOTDIR + "/BkgSR_" + category + ".pdf")
c.SaveAs(PLOTDIR + "/BkgSR_" + category + ".png")
#*******************************************************#
# #
# Generate workspace #
# #
#*******************************************************#
if BIAS:
gSystem.Load("libHiggsAnalysisCombinedLimit.so")
from ROOT import RooMultiPdf
cat = RooCategory("pdf_index", "Index of Pdf which is active")
pdfs = RooArgList(modelBkg, modelAlt)
roomultipdf = RooMultiPdf("roomultipdf", "All Pdfs", cat, pdfs)
normulti = RooRealVar("roomultipdf_norm",
"Number of background events", nevents, 0., 1.e6)
normzBkg.setConstant(
False
) ## newly put here to ensure it's freely floating in the combine fit
# create workspace
w = RooWorkspace("Zprime_" + YEAR, "workspace")
# Dataset
if isData: getattr(w, "import")(setData, RooFit.Rename("data_obs"))
else: getattr(w, "import")(setToys, RooFit.Rename("data_obs"))
#getattr(w, "import")(setData, RooFit.Rename("data_obs"))
if BIAS:
getattr(w, "import")(cat, RooFit.Rename(cat.GetName()))
getattr(w, "import")(normulti, RooFit.Rename(normulti.GetName()))
getattr(w, "import")(roomultipdf, RooFit.Rename(roomultipdf.GetName()))
getattr(w, "import")(modelBkg, RooFit.Rename(modelBkg.GetName()))
getattr(w, "import")(modelAlt, RooFit.Rename(modelAlt.GetName()))
getattr(w, "import")(normzBkg, RooFit.Rename(normzBkg.GetName()))
w.writeToFile(WORKDIR + "%s_%s.root" % (DATA_TYPE + "_" + YEAR, category),
True)
print "Workspace", WORKDIR + "%s_%s.root" % (
DATA_TYPE + "_" + YEAR, category), "saved successfully"
if VERBOSE: raw_input("Press Enter to continue...")
def createCompoundPlots(detector, plot, geometry):
"""Produce the requested plot for the specified detector.
Function that will plot the requested @plot for the specified
@detector. The specified detector could either be a real
detector or a compound one. The list of available plots are the
keys of plots dictionary (imported from plot_utils.
"""
setTDRStyle()
theDirname = 'Images'
if not checkFile_(theDirname):
os.mkdir(theDirname)
goodToGo, theDetectorFilename = paramsGood_(detector, plot, geometry)
if not goodToGo:
return
hist_X0_elements = OrderedDict()
# stack
stackTitle = "%s;%s;%s" % (detector, plots[plot].abscissa,
plots[plot].ordinate)
stack_X0 = THStack("stack_X0", stackTitle)
theLegend = TLegend(0.50, 0.70, 0.70, 0.90)
def setRanges(h):
legendSpace = 1. + 0.3 # 30%
minY = h.GetYaxis().GetXmin()
maxY = h.GetBinContent(h.GetMaximumBin()) * legendSpace
h.GetYaxis().SetRangeUser(minY, maxY)
for label, [num, color, leg] in six.iteritems(hist_label_to_num):
# We don't want the sum to be added as part of the stack
if label is 'SUM':
continue
hist_X0_elements[label] = get1DHisto_(detector,
num + plots[plot].plotNumber,
geometry)
hist_X0_elements[label].SetFillColor(color)
hist_X0_elements[label].SetLineColor(kBlack)
stack_X0.Add(hist_X0_elements[label])
if hist_X0_elements[label].Integral() > 0.:
theLegend.AddEntry(hist_X0_elements[label], leg, "f")
# canvas
canname = "MBCan_1D_%s_%s" % (detector, plot)
can = TCanvas(canname, canname, 800, 800)
can.Range(0, 0, 25, 25)
gStyle.SetOptTitle(0)
# Draw
setRanges(stack_X0.GetStack().Last())
stack_X0.Draw("HIST")
stack_X0.GetXaxis().SetLabelSize(0.035)
stack_X0.GetYaxis().SetLabelSize(0.035)
theLegend.Draw()
cmsMark = TLatex()
cmsMark.SetNDC()
cmsMark.SetTextAngle(0)
cmsMark.SetTextColor(kBlack)
cmsMark.SetTextFont(61)
cmsMark.SetTextSize(5e-2)
cmsMark.SetTextAlign(11)
cmsMark.DrawLatex(0.16, 0.86, "CMS")
simuMark = TLatex()
simuMark.SetNDC()
simuMark.SetTextAngle(0)
simuMark.SetTextColor(kBlack)
simuMark.SetTextSize(3e-2)
simuMark.SetTextAlign(11)
simuMark.DrawLatex(0.16, 0.82, "#font[52]{Simulation Internal}")
# Store
can.Update()
can.SaveAs("%s/%s_%s_%s.pdf" % (theDirname, detector, plot, geometry))
can.SaveAs("%s/%s_%s_%s.png" % (theDirname, detector, plot, geometry))
def get_text(x, y, f, s):
t = TLatex(x, y, "#font[41]{{0:d} :} {1}".format(f(), s))
t.SetTextFont(f('root'))
t.SetTextAlign(12)
t.SetTextSize(0.048)
return t
def showENC():
fname1 = '/data/repos/Mic4Test_KC705/Software/Analysis/data/ENC/ENC_Chip5Col12_scan1.dat'
tree1 = TTree()
tree1.ReadFile(
'/data/repos/Mic4Test_KC705/Software/Analysis/data/ENC/ENC_Chip5Col12_scan1.dat',
'idX/i:vL/F:vH:A:D/i:R:W')
tree1.ReadFile(
'/data/repos/Mic4Test_KC705/Software/Analysis/data/ENC/ENC_Chip5Col12_scan2_mod.dat'
)
tree1.Show(500)
p1 = TProfile('p1', 'p1;#DeltaU [V];Prob', 50, 0.12, 0.2)
tree1.Draw("D:(vH-vL)>>p1", "", "profE")
### change it to tgraph
g1 = TGraphErrors()
for i in range(p1.GetNbinsX() + 2):
N = p1.GetBinEntries(i)
if N > 0:
print i, N, p1.GetXaxis().GetBinCenter(i), p1.GetBinContent(
i), p1.GetBinError(i)
n = g1.GetN()
g1.SetPoint(n, p1.GetXaxis().GetBinCenter(i), p1.GetBinContent(i))
g1.SetPointError(n, 0, p1.GetBinError(i))
# g1.SetMarkerColor(3)
# g1.SetLineColor(3)
p1.Draw("axis")
g1.Draw('Psame')
fun1 = TF1('fun1', '0.5*(1+TMath::Erf((x-[0])/(TMath::Sqrt(2)*[1])))',
0.05, 0.3)
fun1.SetParameter(0, 0.155)
fun1.SetParameter(1, 0.005)
g1.Fit(fun1)
fun1a = g1.GetFunction('fun1')
# p1.Fit(fun1)
# fun1a = p1.GetFunction('fun1')
fun1a.SetLineColor(2)
# p1.Draw("Esame")
v0 = fun1a.GetParameter(0)
e0 = fun1a.GetParError(0)
v1 = fun1a.GetParameter(1)
e1 = fun1a.GetParError(1)
print v0, v1
fUnit = 1000.
lt = TLatex()
lt.DrawLatexNDC(
0.185, 0.89,
'#mu = {0:.1f} #pm {1:.1f} mV'.format(v0 * fUnit, e0 * fUnit))
lt.DrawLatexNDC(
0.185, 0.84,
'#sigma = {0:.1f} #pm {1:.1f} mV'.format(v1 * fUnit, e1 * fUnit))
print 'TMath::Gaus(x,{0:.5f},{1:.5f})'.format(v0, v1)
fun2 = TF1('gaus1', 'TMath::Gaus(x,{0:.5f},{1:.5f})'.format(v0, v1))
fun2.SetLineColor(4)
fun2.SetLineStyle(2)
fun2.Draw('same')
lg = TLegend(0.7, 0.4, 0.95, 0.5)
lg.SetFillStyle(0)
lg.AddEntry(p1, 'Measurement', 'p')
lg.AddEntry(fun1a, 'Fit', 'l')
lg.AddEntry(fun2, 'Gaus', 'l')
lg.Draw()
waitRootCmdX()
def write_rootgraph(vectorx, vectory, graphtitle, xtitle, ytitle,
sectorscurrents, rootdirectory):
"""Function to perform ROOT graph"""
arrayx = array('d')
arrayy = array('d')
for x in vectorx:
arrayx.append(x)
for y in vectory:
arrayy.append(y)
#How many graph points
n = len(vectorx)
MyTGraph = TGraph(n, arrayx, arrayy)
MyTGraph.SetName(graphtitle)
if ytitle == "i":
ytitle = ytitle + " (uA)"
color = 2
offset = 1.
minimum = -0.5
maximum = int(np.max(vectory) + 1.5)
lineup = TLine(float(np.min(vectorx)), 500, float(np.max(vectorx)),
500)
lineup.SetLineColor(2)
lineup.SetLineStyle(2)
linedown = TLine(float(np.min(vectorx)), 500., float(np.max(vectorx)),
500.)
linedown.SetLineColor(8)
linedown.SetLineStyle(2)
for entry in range(len(sectorscurrents)):
if vectory[entry] > 0.01:
latex = TLatex(MyTGraph.GetX()[entry],
MyTGraph.GetY()[entry], sectorscurrents[entry])
latex.SetTextSize(0.02)
MyTGraph.GetListOfFunctions().Add(latex)
else:
latex = TLatex(MyTGraph.GetX()[entry],
MyTGraph.GetY()[entry], "")
latex.SetTextSize(0.02)
MyTGraph.GetListOfFunctions().Add(latex)
if ytitle == "v":
ytitle = ytitle + " (V)"
color = 4
offset = 0.9
minimum = 400
maximum = 600
lineup = TLine(float(np.min(vectorx)), 580., float(np.max(vectorx)),
580.)
lineup.SetLineColor(2)
lineup.SetLineStyle(2)
linedown = TLine(float(np.min(vectorx)), 530., float(np.max(vectorx)),
530.)
linedown.SetLineColor(8)
linedown.SetLineStyle(2)
for entry in range(len(sectorscurrents)):
if vectory[entry] > 569.0:
latex = TLatex(MyTGraph.GetX()[entry],
MyTGraph.GetY()[entry], "")
else:
latex = TLatex(MyTGraph.GetX()[entry],
MyTGraph.GetY()[entry], sectorscurrents[entry])
latex.SetTextSize(0.02)
MyTGraph.GetListOfFunctions().Add(latex)
#Draw + DrawOptions
Style = gStyle
Style.SetPadLeftMargin(2.0)
XAxis = MyTGraph.GetXaxis() #TGraphfasthescin
#XAxis.SetTitleOffset(offset)
XAxis.SetTitle(xtitle)
MyTGraph.SetMarkerColor(color)
MyTGraph.SetMarkerStyle(1)
MyTGraph.SetMarkerSize(1)
MyTGraph.SetLineColor(color)
MyTGraph.SetTitle(graphtitle)
#XAxis.SetTitle(xtitle)
YAxis = MyTGraph.GetYaxis()
YAxis.SetTitleOffset(offset)
YAxis.SetTitle(ytitle)
MyTGraph.GetHistogram().SetMinimum(minimum)
MyTGraph.GetHistogram().SetMaximum(maximum)
rootdirectory.WriteTObject(MyTGraph)
c = TCanvas()
c.SetName(graphtitle + "_canvas")
MyTGraph.Draw("APL")
lineup.Draw("")
linedown.Draw("")
rootdirectory.WriteTObject(c)
#MyTGraph.Write(graphtitle)
MyTGraph.Draw("APL")
#gPad.SaveAs("current-"+graphtitle+".pdf")
gPad.Close()
def main(options, args):
from ROOT import gSystem, gROOT, gStyle
gROOT.SetBatch()
gSystem.Load("libRooFitCore")
if options.doWebPage:
from lip.Tools.rootutils import loadToolsLib, apply_modifs
loadToolsLib()
from ROOT import TFile, RooFit, RooArgSet, RooDataHist, RooKeysPdf, RooHistPdf, TCanvas, TLegend, TLatex, TArrow, TPaveText, RooAddPdf, RooArgList
from ROOT import kWhite, kBlue, kOpenSquare
if options.doWebPage:
from ROOT import HtmlHelper, HtmlTag, HtmlTable, HtmlPlot
rootglobestyle.setTDRStyle()
gStyle.SetMarkerSize(1.5)
gStyle.SetTitleYOffset(1.5)
gStyle.SetPadLeftMargin(0.16)
gStyle.SetPadRightMargin(0.05)
gStyle.SetPadTopMargin(0.05)
gStyle.SetPadBottomMargin(0.13)
gStyle.SetLabelFont(42, "XYZ")
gStyle.SetLabelOffset(0.007, "XYZ")
gStyle.SetLabelSize(0.05, "XYZ")
gStyle.SetTitleSize(0.06, "XYZ")
gStyle.SetTitleXOffset(0.9)
gStyle.SetTitleYOffset(1.24)
gStyle.SetTitleFont(42, "XYZ")
##
## Read files
##
options.outdir = "%s_m%1.0f" % (options.outdir, options.mH)
if options.fp:
options.outdir += "_fp"
ncat = options.ncat
cats = options.cats
if cats is "":
categories = ["_cat%d" % i for i in range(0, ncat)]
else:
categories = ["_cat%s" % i for i in cats.split(",")]
if options.mva:
clables = {
"_cat0": ("MVA > 0.89", ""),
"_cat1": ("0.74 #leq MVA", "MVA < 0.89"),
"_cat2": ("0.545 #leq MVA", "MVA < 0.74"),
"_cat3": ("0.05 #leq MVA", "MVA < 0.545"),
"_cat4": ("Di-jet", "Tagged"),
"_cat5": ("Di-jet", "Tagged"),
"_combcat": ("All Classes", "Combined")
}
else:
clables = {
"_cat0": ("max(|#eta|<1.5", "min(R_{9})>0.94"),
"_cat1": ("max(|#eta|<1.5", "min(R_{9})<0.94"),
"_cat2": ("max(|#eta|>1.5", "min(R_{9})>0.94"),
"_cat3": ("max(|#eta|>1.5", "min(R_{9})<0.94"),
"_cat4": ("Di-jet", "Tagged"),
"_cat5": ("Di-jet", "Tagged"),
"_combcat": ("All Classes", "Combined")
}
helper = Helper()
fin = TFile.Open(options.infile)
helper.files.append(fin)
ws = fin.Get("cms_hgg_workspace")
mass = ws.var("CMS_hgg_mass")
mass.SetTitle("m_{#gamma#gamma}")
mass.setUnit("GeV")
mass.setRange(100., 150.)
mass.setBins(100, "plot")
mass.setBins(5000)
print ws
aset = RooArgSet(mass)
helper.objs.append(mass)
helper.objs.append(aset)
fitopt = (RooFit.Minimizer("Minuit2", ""), RooFit.Minos(False),
RooFit.SumW2Error(False), RooFit.NumCPU(8))
if not options.binned and not options.refit:
finpdf = TFile.Open(options.infilepdf)
helper.files.append(finpdf)
wspdf = finpdf.Get("wsig")
else:
wspdf = ws
for c in categories:
processes = ["ggh", "vbf", "wzh"]
if options.fp:
processes = ["vbf", "wzh"]
### elif clables[c][0] == "Di-jet":
### processes = [ "vbf", "ggh" ]
dsname = "sig_mass_m%1.0f%s" % (options.mH, c)
print dsname
print ws
ds = ws.data("sig_%s_mass_m%1.0f%s" %
(processes[0], options.mH, c)).Clone(dsname)
for proc in processes[1:]:
ds.append(ws.data("sig_%s_mass_m%1.0f%s" % (proc, options.mH, c)))
helper.dsets.append(ds)
if options.binned:
binned_ds = RooDataHist("binned_%s" % dsname, "binned_%s" % dsname,
aset, ds)
pdf = RooKeysPdf("pdf_%s_%s" % (dsname, f), "pdf_%s" % dsname,
mass, ds)
plot_pdf = RooHistPdf("pdf_%s" % dsname, "pdf_%s" % dsname, aset,
plot_ds)
helper.add(binned_ds, binned_ds.GetName())
else:
if options.refit:
if options.refitall and clables[c][0] != "Di-jet":
rpdfs = []
for proc in processes:
for ngaus in range(1, 4):
pp = build_pdf(ws, "%s_%s" % (c, proc), ngaus,
ngaus == 3)
pp.fitTo(
ws.data("sig_%s_mass_m%1.0f%s" %
(proc, options.mH, c)),
RooFit.Strategy(0), *fitopt)
rpdfs.append(pp)
pdf = RooAddPdf("hggpdfrel%s" % c, "hggpdfrel%s" % c,
RooArgList(*tuple(rpdfs)))
else:
if options.refitall and clables[c][0] == "Di-jet":
for ngaus in range(1, 5):
pdf = build_pdf(ws, c, ngaus, ngaus == 5)
pdf.fitTo(ds, RooFit.Strategy(0), *fitopt)
else:
for ngaus in range(1, 4):
pdf = build_pdf(ws, c, ngaus, ngaus == 3)
pdf.fitTo(ds, RooFit.Strategy(0), *fitopt)
else:
pdfs = (wspdf.pdf("hggpdfrel%s_%s" % (c, p))
for p in processes)
pdf = RooAddPdf("hggpdfrel%s" % c, "hggpdfrel%s" % c,
RooArgList(*pdfs))
helper.add(pdf, pdf.GetName())
plot_pdf = pdf.Clone("pdf_%s" % dsname)
plot_ds = RooDataHist("plot_%s" % dsname, "plot_%s" % dsname, aset,
"plot")
plot_ds.add(ds)
cdf = pdf.createCdf(aset)
hmin, hmax, hm = get_FWHM(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
wmin, wmax = get_eff_sigma(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
### hmin, hmax, hm = get_FWHM( points )
helper.add(plot_ds, plot_ds.GetName())
helper.add(plot_pdf, plot_pdf.GetName())
helper.add((wmin, wmax), "eff_sigma%s" % c)
helper.add((hmin, hmax, hm), "FWHM%s" % c)
helper.add(ds.sumEntries(),
"sumEntries%s" % c) # signal model integral
# data integral for PAS tables
data = ws.data("data_mass%s" % c)
helper.add(
data.sumEntries("CMS_hgg_mass>=%1.4f && CMS_hgg_mass<=%1.4f" %
(options.mH - 10., options.mH + 10.)),
"data_sumEntries%s" % c)
del cdf
del pdf
dsname = "sig_mass_m%1.0f_combcat" % options.mH
print dsname
combined_ds = helper.dsets[0].Clone(dsname)
for d in helper.dsets[1:]:
combined_ds.append(d)
if options.binned:
binned_ds = RooDataHist("binned_%s" % dsname, "binned_%s" % dsname,
aset, combined_ds)
pdf = RooKeysPdf("pdf_%s" % (dsname), "pdf_%s" % dsname, mass,
combined_ds)
plot_pdf = RooHistPdf("pdf_%s" % dsname, "pdf_%s" % dsname, aset,
plot_ds)
helper.add(binned_ds, binned_ds.GetName())
else:
#### pdf = build_pdf(ws,"_combcat")
#### pdf.fitTo(combined_ds, RooFit.Strategy(0), *fitopt )
#### plot_pdf = pdf.Clone( "pdf_%s" % dsname )
pdf = RooAddPdf(
"pdf_%s" % dsname, "pdf_%s" % dsname,
RooArgList(*(helper.histos["hggpdfrel%s" % c]
for c in categories)))
plot_pdf = pdf
cdf = pdf.createCdf(aset)
plot_ds = RooDataHist("plot_%s" % dsname, "plot_%s" % dsname, aset, "plot")
plot_ds.add(combined_ds)
wmin, wmax = get_eff_sigma(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
hmin, hmax, hm = get_FWHM(mass, pdf, cdf, options.mH - 10.,
options.mH + 10.)
helper.add(plot_ds, plot_ds.GetName())
helper.add(plot_pdf, plot_pdf.GetName())
helper.add((wmin, wmax), "eff_sigma_combcat")
helper.add((hmin, hmax, hm), "FWHM_combcat")
helper.add(plot_ds.sumEntries(), "sumEntries_combcat")
mass.setRange("higgsrange", options.mH - 25., options.mH + 15.)
del cdf
del pdf
del helper.dsets
### label = TLatex(0.1812081,0.8618881,"#scale[0.8]{#splitline{CMS preliminary}{Simulation}}")
label = TLatex(0.7, 0.86,
"#scale[0.65]{#splitline{CMS preliminary}{Simulation}}")
label.SetNDC(1)
##
## Make web page with plots
##
if options.doWebPage:
hth = HtmlHelper(options.outdir)
hth.navbar().cell(HtmlTag("a")).firstChild().txt("..").set(
"href", "../?C=M;O=D")
hth.navbar().cell(HtmlTag("a")).firstChild().txt("home").set(
"href", "./")
tab = hth.body().add(HtmlTable())
ip = 0
for c in ["_combcat"] + categories:
### for c in categories:
if options.doWebPage and ip % 4 == 0:
row = tab.row()
ip = ip + 1
dsname = "sig_mass_m%1.0f%s" % (options.mH, c)
canv = TCanvas(dsname, dsname, 600, 600)
helper.objs.append(canv)
### leg = TLegend(0.4345638,0.6835664,0.9362416,0.9178322)
leg = TLegend(0.2, 0.96, 0.5, 0.55)
#apply_modifs( leg, [("SetLineColor",kWhite),("SetFillColor",kWhite),("SetFillStyle",0),("SetLineStyle",0)] )
hplotcompint = mass.frame(RooFit.Bins(250), RooFit.Range("higgsrange"))
helper.objs.append(hplotcompint)
helper.objs.append(leg)
plot_ds = helper.histos["plot_%s" % dsname]
plot_pdf = helper.histos["pdf_%s" % dsname]
wmin, wmax = helper.histos["eff_sigma%s" % c]
hmin, hmax, hm = helper.histos["FWHM%s" % c]
print hmin, hmax, hm
style = (RooFit.LineColor(kBlue), RooFit.LineWidth(2),
RooFit.FillStyle(0))
style_seff = (
RooFit.LineWidth(2),
RooFit.FillStyle(1001),
RooFit.VLines(),
RooFit.LineColor(15),
)
style_ds = (RooFit.MarkerStyle(kOpenSquare), )
plot_ds.plotOn(hplotcompint, RooFit.Invisible())
plot_pdf.plotOn(hplotcompint, RooFit.NormRange("higgsrange"),
RooFit.Range(wmin, wmax), RooFit.FillColor(19),
RooFit.DrawOption("F"), *style_seff)
seffleg = hplotcompint.getObject(int(hplotcompint.numItems() - 1))
plot_pdf.plotOn(hplotcompint, RooFit.NormRange("higgsrange"),
RooFit.Range(wmin, wmax), RooFit.LineColor(15),
*style_seff)
plot_pdf.plotOn(hplotcompint, RooFit.NormRange("higgsrange"),
RooFit.Range("higgsrange"), *style)
pdfleg = hplotcompint.getObject(int(hplotcompint.numItems() - 1))
plot_ds.plotOn(hplotcompint, *style_ds)
pointsleg = hplotcompint.getObject(int(hplotcompint.numItems() - 1))
iob = int(hplotcompint.numItems() - 1)
leg.AddEntry(pointsleg, "Simulation", "pe")
leg.AddEntry(pdfleg, "Parametric model", "l")
leg.AddEntry(seffleg,
"#sigma_{eff} = %1.2f GeV " % (0.5 * (wmax - wmin)), "fl")
clabel = TLatex(0.74, 0.65,
"#scale[0.65]{#splitline{%s}{%s}}" % clables[c])
clabel.SetNDC(1)
helper.objs.append(clabel)
hm = hplotcompint.GetMaximum() * 0.5 * 0.9
### hm = pdfleg.GetMaximum()*0.5
fwhmarrow = TArrow(hmin, hm, hmax, hm)
fwhmarrow.SetArrowSize(0.03)
helper.objs.append(fwhmarrow)
fwhmlabel = TPaveText(0.20, 0.58, 0.56, 0.48, "brNDC")
fwhmlabel.SetFillStyle(0)
fwhmlabel.SetLineColor(kWhite)
reducedFWHM = (hmax - hmin) / 2.3548200
fwhmlabel.AddText("FWHM/2.35 = %1.2f GeV" % reducedFWHM)
helper.objs.append(fwhmlabel)
hplotcompint.SetTitle("")
hplotcompint.GetXaxis().SetNoExponent(True)
hplotcompint.GetXaxis().SetTitle("m_{#gamma#gamma} (GeV)")
hplotcompint.GetXaxis().SetNdivisions(509)
## hplotcompint.GetYaxis().SetTitle("A.U.");
## hplotcompint.GetYaxis().SetRangeUser(0.,hplotcompint.GetMaximum()*1.4);
hplotcompint.Draw()
leg.Draw("same")
label.Draw("same")
clabel.Draw("same")
fwhmarrow.Draw("<>")
fwhmlabel.Draw("same")
plot_ds.sumEntries()
if options.doWebPage:
hpl = HtmlPlot(canv, False, "", True, True, True)
hpl.caption("<i>%s</i>" % canv.GetTitle())
row.cell(hpl)
else:
if os.path.isdir(options.outdir) is False:
os.mkdir(options.outdir)
for ext in "C", "png", "pdf":
canv.SaveAs(
os.path.join(options.outdir,
"%s.%s" % (canv.GetName(), ext)))
if "comb" in c:
ip = 0
if options.doWebPage:
print "Creating pages..."
hth.dump()
for f in helper.files:
f.Close()
gROOT.Reset()
from pprint import pprint
pprint(helper)
print 'Summary statistics per event class'
print 'Cat\tSignal\t\tData/GeV (in %3.1f+/-10)\tsigEff\tFWHM/2.35' % options.mH
sigTotal = 0.
dataTotal = 0.
for c in categories:
sigVal = helper.histos["sumEntries%s" % c]
datVal = helper.histos["data_sumEntries%s" % c]
sigTotal += sigVal
dataTotal += datVal
for c in categories:
sigVal = helper.histos["sumEntries%s" % c]
datVal = helper.histos["data_sumEntries%s" % c]
effSig = 0.5 * (helper.histos["eff_sigma%s" % c][1] -
helper.histos["eff_sigma%s" % c][0])
fwhm = (helper.histos["FWHM%s" % c][1] -
helper.histos["FWHM%s" % c][0]) / 2.3548200
print c, '\t%3.1f (%3.1f%%)\t%3.1f (%3.1f%%)\t\t\t%2.2f\t%2.2f' % (
sigVal, 100. * sigVal / sigTotal, datVal /
(10. + 10.), 100. * datVal / dataTotal, effSig, fwhm)
print "Done."
ratePlot.GetYaxis().SetTitle("Rate [Hz]")
leg.Draw()
# Plot ranges
ratePlot.GetYaxis().SetRangeUser(1e2, 1e10)
ratePlot.GetXaxis().SetRangeUser(30, 370)
# Lumi and energy info
text = TPaveText(0.2, 0.84, 0.6, 0.9, "NDC")
text.AddText("L_{inst} = 3 #times 10^{35} cm^{-2} s^{-1} #sqrt{s} = 100 TeV")
text.Draw()
# Adding a reference line at 1 MHz
mhzLine = TLine(30, mySettings.yScale, 160, mySettings.yScale)
mhzLine.SetLineColor(2)
mhzLine.SetLineStyle(2)
mhzLine.Draw()
label_1MHz = TLatex(143, 1.1 * mySettings.yScale, "1 MHz")
label_1MHz.SetTextSize(0.04)
label_1MHz.Draw()
canvas.Update()
canvas.Draw()
canvas.Print("ratePlot.png", "png")
canvas.Print("ratePlot.svg", "svg")
canvas.Print("ratePlot.pdf", "pdf")
canvas.Print("ratePlot.C", "cxx")
def main(argv):
VERBOSE = False
# Read in command line args
parser = OptionParser(usage=str(
"\n" +
"create_resource_correlation_plots.py [run period] [minversion] [version]\n"
+ "example: create_resource_correlation_plots.py 2015_03 15 20\n" +
"\n" + "Input xml file should be created with\n" +
"hdswif.py summary [workflow]"))
parser.add_option("-V", "--verbose", dest="verbose", help="verbose output")
(options, args) = parser.parse_args(argv)
if (options.verbose):
VERBOSE = True
if len(args) != 3:
print "Usage:"
print "create_resource_correlation_plots.py [run period] [minversion] [version]"
print "example: create_resource_correlation_plots.py 2015_03 15 20"
exit()
RUNPERIOD = ""
VERSION = ""
# RUNPERIOD is with underscore
RUNPERIOD = args[0]
RUNPERIOD = RUNPERIOD.replace('-', '_')
RUNPERIOD_HYPHEN = RUNPERIOD.replace('_', '-')
MINVERSION = int(args[1])
VERSION = int(args[2])
#assert MINVERSION < VERSION
# List of all valid launch vers
launchlist = []
# Only run over launches that had table created in DB
# Create MySQL connection
db_conn = MySQLdb.connect(host='hallddb',
user='******',
passwd='',
db='farming')
cursor = db_conn.cursor()
for ver in range(MINVERSION, VERSION):
formatted_vernum = "%02d" % ver
tablename = 'cross_analysis_table_' + RUNPERIOD + '_ver' + formatted_vernum
cursor.execute("SHOW TABLES LIKE '" + tablename + "'")
results = cursor.fetchall()
if len(results) == 0:
print 'table ' + tablename + ' does NOT exist, skipping...'
else:
# print 'table ' + tablename + ' exists'
launchlist.append(ver)
print 'Launch vers to compare: ' + str(launchlist)
# Dictionary between ver to be filled and TGraph
dict_cpu_sec = {}
dict_wall_sec = {}
dict_mem_kb = {}
dict_vmem_kb = {}
dict_nevents = {}
dict_input_copy_sec = {}
dict_plugin_sec = {}
# This one is a TH1F
dict_nevents_diff = {}
for ver in launchlist:
dict_cpu_sec[ver] = TGraph()
dict_wall_sec[ver] = TGraph()
dict_mem_kb[ver] = TGraph()
dict_vmem_kb[ver] = TGraph()
dict_nevents[ver] = TGraph()
dict_input_copy_sec[ver] = TGraph()
dict_plugin_sec[ver] = TGraph()
hname = 'dict_nevents_diff_' + format(ver, 2)
dict_nevents_diff[ver] = TH1F(
hname, ';#events ver' + str(VERSION) + ' - ver' + str(ver) + ';',
400, -200, 200)
# Create MySQL connection
db_conn = MySQLdb.connect(host='hallddb',
user='******',
passwd='',
db='farming')
cursor = db_conn.cursor()
# Get all runs and files for the launch of interest (ver VERSION)
formatted_mainvernum = "%02d" % VERSION
tablename = 'cross_analysis_table_' + RUNPERIOD + '_ver' + formatted_mainvernum
cursor.execute('SELECT run, file FROM ' + tablename)
results = cursor.fetchall()
# Keep the run/file combination in a set. The entries in the DB
# should be unique, but this acts as a guard.
set_run_file = Set()
for row in results:
run_file = format(row[0], 6) + '_' + format(row[1], 3)
if run_file in set_run_file:
print run_file + ' has already been accounted for, skipping'
continue
set_run_file.add(run_file)
npoints = 0
for run_file in set_run_file:
npoints += 1
if npoints % 500 == 0:
print 'processing ' + format(npoints, 4) + ' / ' + str(
len(set_run_file)) + '...'
match = re.search(r"(\d\d\d\d\d\d)_(\d\d\d)", run_file)
run_num = match.group(1)
file_num = match.group(2)
if VERBOSE:
print '-------------------------------------------------------------------'
print 'run = ' + str(run_num) + ' file = ' + str(file_num)
# Grab results from DB for each version for this file,
# fill into dicts
# Dictionaries between [version] : [resources]
cpu_sec = {}
wall_sec = {}
mem_kb = {}
vmem_kb = {}
nevents = {}
input_copy_sec = {}
plugin_sec = {}
# Iterate over VERSION and launchlist.
# Start with VERSION so that the condition for
# filling the correlation plots gets satsified
# for each of the vers in launchlist
noValue = -999
for ver in [VERSION] + launchlist:
cpu_sec[ver] = noValue
wall_sec[ver] = noValue
mem_kb[ver] = noValue
vmem_kb[ver] = noValue
nevents[ver] = noValue
input_copy_sec[ver] = noValue
plugin_sec[ver] = noValue
formatted_vernum = "%02d" % ver
tablename = 'cross_analysis_table_' + RUNPERIOD + '_ver' + formatted_vernum
cursor.execute('SELECT cpu_sec, wall_sec, mem_kb, vmem_kb, nevents, input_copy_sec, plugin_sec FROM ' \
+ tablename + ' WHERE run = ' + str(run_num) + ' AND file = ' + str(file_num))
results = cursor.fetchall()
for row in results:
cpu_sec[ver] = row[0]
wall_sec[ver] = row[1]
mem_kb[ver] = row[2]
vmem_kb[ver] = row[3]
nevents[ver] = row[4]
input_copy_sec[ver] = row[5]
plugin_sec[ver] = row[6]
if ver == VERSION:
# Nothing to fill for ver VERSION
continue
# Fill correlations plots
if cpu_sec[VERSION] != noValue and cpu_sec[ver] != noValue:
dict_cpu_sec[ver].SetPoint(dict_cpu_sec[ver].GetN(),
float(cpu_sec[VERSION]) / 60,
float(cpu_sec[ver]) / 60)
if wall_sec[VERSION] != noValue and wall_sec[ver] != noValue:
dict_wall_sec[ver].SetPoint(dict_wall_sec[ver].GetN(),
float(wall_sec[VERSION]) / 60,
float(wall_sec[ver]) / 60)
if mem_kb[VERSION] != noValue and mem_kb[ver] != noValue:
dict_mem_kb[ver].SetPoint(dict_mem_kb[ver].GetN(),
float(mem_kb[VERSION]) / 1024 / 1024,
float(mem_kb[ver]) / 1024 / 1024)
if vmem_kb[VERSION] != noValue and vmem_kb[ver] != noValue:
dict_vmem_kb[ver].SetPoint(
dict_vmem_kb[ver].GetN(),
float(vmem_kb[VERSION]) / 1024 / 1024,
float(vmem_kb[ver]) / 1024 / 1024)
if nevents[VERSION] != noValue and nevents[ver] != noValue:
dict_nevents[ver].SetPoint(dict_nevents[ver].GetN(),
float(nevents[VERSION]),
float(nevents[ver]))
dict_nevents_diff[ver].Fill(
float(nevents[VERSION]) - float(nevents[ver]))
if input_copy_sec[VERSION] != noValue and input_copy_sec[
ver] != noValue:
dict_input_copy_sec[ver].SetPoint(
dict_input_copy_sec[ver].GetN(),
float(input_copy_sec[VERSION]) / 60,
float(input_copy_sec[ver]) / 60)
if plugin_sec[VERSION] != noValue and plugin_sec[ver] != noValue:
dict_plugin_sec[ver].SetPoint(dict_plugin_sec[ver].GetN(),
float(plugin_sec[VERSION]) / 60,
float(plugin_sec[ver]) / 60)
# end of loop over vers
# end of loop over run and files
# Create html page
htmlDir = 'resource_use'
if not os.path.exists(htmlDir):
os.makedirs(htmlDir)
htmlfilename = htmlDir + '/resource_use_' + RUNPERIOD + '_ver' + format(
VERSION, 2) + '.html'
htmlfile = open(htmlfilename, 'w')
htmlfile.write('<!-- launch ver ' + format(VERSION, 2) + '-->\n')
htmlfile.write('<html>\n')
htmlfile.write('\n')
htmlfile.write('<head>\n')
htmlfile.write(
'<link rel="stylesheet" type="text/css" href="mystyle.css">\n')
htmlfile.write(
'<meta http-equiv="content-style-type" content="text/css">\n')
htmlfile.write('<title>Offline Monitoring Results 2015-03</title>\n')
htmlfile.write('\n')
htmlfile.write('<style>\n')
htmlfile.write(' #content iframe{\n')
htmlfile.write(' overflow: hidden;\n')
htmlfile.write(' width:100%;\n')
htmlfile.write(' border:none;\n')
htmlfile.write(' margin: 0;\n')
htmlfile.write(' padding: 0;\n')
htmlfile.write(' }\n')
htmlfile.write('</style>\n')
htmlfile.write('\n')
htmlfile.write('<script language="javascript" type="text/javascript">\n')
htmlfile.write(' function resizeIframe(obj) {\n')
htmlfile.write(
" obj.style.height = obj.contentWindow.document.body.scrollHeight + 'px';\n"
)
htmlfile.write(' }\n')
htmlfile.write('</script>\n')
htmlfile.write('\n')
htmlfile.write('</head>\n')
htmlfile.write('\n')
htmlfile.write('<body>\n')
htmlfile.write('<h2>Comparison of ver' + format(VERSION, 2) +
' and older</h2>\n')
tablewidth = (VERSION - MINVERSION) * 20
htmlfile.write('<table style="width:' + str(tablewidth) + '%">\n')
# cpu_sec
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> CPU time (min) </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 01___cpu_sec ver' + format(ver, 2) + '-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/01___cpu_sec_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/01___cpu_sec_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
# wall_sec
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> wall time (min) </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 02___wall_sec ver' + format(ver, 2) + '-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/02___wall_sec_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/02___wall_sec_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
# mem_kb
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> Memory (GB) </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 03___mem_kb ver' + format(ver, 2) + '-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/03___mem_kb_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/03___mem_kb_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
# vmem_kb
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> Virtual memory (GB) </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 04___vmem_kb ver' + format(ver, 2) + '-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/04___vmem_kb_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/04___vmem_kb_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
# nevents
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> #events </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 05___nevents ver' + format(ver, 2) + '-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/05___nevents_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/05___nevents_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
# nevents_diff
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> Δ events </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 06___nevents_diff ver' + format(ver, 2) +
'-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/06___nevents_diff_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/06___nevents_diff_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
# input_copy_sec
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> input copy time (min) </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 07___input_copy_sec ver' + format(ver, 2) +
'-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/07___input_copy_sec_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/07___input_copy_sec_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
# plugin_time
htmlfile.write(' <tr>\n')
htmlfile.write(' <td colspan="' + str(VERSION - MINVERSION) +
'"> plugin time (min) </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write(' <tr>\n')
for ver in launchlist:
htmlfile.write(' <!-- 08___plugin_time ver' + format(ver, 2) +
'-->\n')
htmlfile.write(' <td style="width:20%">\n')
htmlfile.write(' <a href="./figures/SWIF/ver' + format(VERSION,2) + '/08___plugin_time_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png">\n')
htmlfile.write(' <img src="./figures/SWIF/ver' + format(VERSION,2) + '/08___plugin_time_ver' \
+ format(VERSION,2) + '_ver' + format(ver,2) + '.png" width="100%">\n')
htmlfile.write(' </a>\n')
htmlfile.write(' </td>\n')
htmlfile.write(' </tr>\n')
htmlfile.write('</table>\n')
htmlfile.write('</body>\n')
htmlfile.write('</html>\n')
htmlfile.close()
line = TLine(0, 0, 0, 0)
latex = TLatex()
latex.SetTextColor(ROOT.kBlack)
latex.SetTextSize(0.06)
latex.SetTextAlign(12)
latex.SetNDC(1)
figureDir = htmlDir + '/figures/SWIF/ver' + format(VERSION, 2)
if not os.path.exists(figureDir):
os.makedirs(figureDir)
for ver in launchlist:
#--------------------------------------------------------------------
# cpu_sec
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.02)
c1.SetRightMargin(0.02)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_cpu_sec[ver].GetXaxis().SetTitleSize(0.06)
dict_cpu_sec[ver].GetXaxis().SetTitleOffset(0.900)
dict_cpu_sec[ver].GetXaxis().SetLabelSize(0.05)
dict_cpu_sec[ver].GetYaxis().SetTitleSize(0.06)
dict_cpu_sec[ver].GetYaxis().SetTitleOffset(1.200)
dict_cpu_sec[ver].GetYaxis().CenterTitle()
dict_cpu_sec[ver].GetYaxis().SetLabelSize(0.05)
dict_cpu_sec[ver].SetMarkerColor(ROOT.kRed)
dict_cpu_sec[ver].SetMarkerStyle(20)
dict_cpu_sec[ver].SetMarkerSize(1.2)
dict_cpu_sec[ver].SetLineColor(ROOT.kRed)
dict_cpu_sec[ver].SetLineStyle(1)
dict_cpu_sec[ver].SetLineWidth(1)
dict_cpu_sec[ver].GetXaxis().SetTitle('CPU time (min) for ver' +
format(VERSION, 2))
dict_cpu_sec[ver].GetYaxis().SetTitle('CPU time (min) for ver' +
format(ver, 2))
X = dict_cpu_sec[ver].GetXaxis().GetXmax()
Y = dict_cpu_sec[ver].GetYaxis().GetXmax()
larger = Y if X < Y else X
# don't show negative values (should not exist)
dict_cpu_sec[ver].GetXaxis().SetLimits(0, larger)
dict_cpu_sec[ver].SetMinimum(0)
dict_cpu_sec[ver].SetMaximum(larger)
dict_cpu_sec[ver].Draw('AP')
line.SetX1(0)
line.SetY1(0)
line.SetX2(larger)
line.SetY2(larger)
line.SetLineColor(ROOT.kMagenta)
line.SetLineStyle(2)
line.DrawClone("same")
text = "total: " + str(dict_cpu_sec[ver].GetN())
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/01___cpu_sec_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
#--------------------------------------------------------------------
# wall_sec
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.02)
c1.SetRightMargin(0.02)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_wall_sec[ver].GetXaxis().SetTitleSize(0.06)
dict_wall_sec[ver].GetXaxis().SetTitleOffset(0.900)
dict_wall_sec[ver].GetXaxis().SetLabelSize(0.05)
dict_wall_sec[ver].GetYaxis().SetTitleSize(0.06)
dict_wall_sec[ver].GetYaxis().SetTitleOffset(1.200)
dict_wall_sec[ver].GetYaxis().CenterTitle()
dict_wall_sec[ver].GetYaxis().SetLabelSize(0.05)
dict_wall_sec[ver].SetMarkerColor(ROOT.kRed)
dict_wall_sec[ver].SetMarkerStyle(20)
dict_wall_sec[ver].SetMarkerSize(1.2)
dict_wall_sec[ver].SetLineColor(ROOT.kRed)
dict_wall_sec[ver].SetLineStyle(1)
dict_wall_sec[ver].SetLineWidth(1)
dict_wall_sec[ver].GetXaxis().SetTitle('wall time (min) for ver' +
format(VERSION, 2))
dict_wall_sec[ver].GetYaxis().SetTitle('wall time (min) for ver' +
format(ver, 2))
X = dict_wall_sec[ver].GetXaxis().GetXmax()
Y = dict_wall_sec[ver].GetYaxis().GetXmax()
larger = Y if X < Y else X
# don't show negative values (should not exist)
dict_wall_sec[ver].GetXaxis().SetLimits(0, larger)
dict_wall_sec[ver].SetMinimum(0)
dict_wall_sec[ver].SetMaximum(larger)
dict_wall_sec[ver].Draw('AP')
line.SetX1(0)
line.SetY1(0)
line.SetX2(larger)
line.SetY2(larger)
line.SetLineColor(ROOT.kMagenta)
line.SetLineStyle(2)
line.DrawClone("same")
text = "total: " + str(dict_wall_sec[ver].GetN())
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/02___wall_sec_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
#--------------------------------------------------------------------
# mem_kb
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.02)
c1.SetRightMargin(0.02)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_mem_kb[ver].GetXaxis().SetTitleSize(0.06)
dict_mem_kb[ver].GetXaxis().SetTitleOffset(0.900)
dict_mem_kb[ver].GetXaxis().SetLabelSize(0.05)
dict_mem_kb[ver].GetYaxis().SetTitleSize(0.06)
dict_mem_kb[ver].GetYaxis().SetTitleOffset(1.200)
dict_mem_kb[ver].GetYaxis().CenterTitle()
dict_mem_kb[ver].GetYaxis().SetLabelSize(0.05)
dict_mem_kb[ver].SetMarkerColor(ROOT.kRed)
dict_mem_kb[ver].SetMarkerStyle(20)
dict_mem_kb[ver].SetMarkerSize(1.2)
dict_mem_kb[ver].SetLineColor(ROOT.kRed)
dict_mem_kb[ver].SetLineStyle(1)
dict_mem_kb[ver].SetLineWidth(1)
dict_mem_kb[ver].GetXaxis().SetTitle('mem (GB) for ver' +
format(VERSION, 2))
dict_mem_kb[ver].GetYaxis().SetTitle('mem (GB) for ver' +
format(ver, 2))
X = dict_mem_kb[ver].GetXaxis().GetXmax()
Y = dict_mem_kb[ver].GetYaxis().GetXmax()
larger = Y if X < Y else X
# don't show negative values (should not exist)
dict_mem_kb[ver].GetXaxis().SetLimits(0, larger)
dict_mem_kb[ver].SetMinimum(0)
dict_mem_kb[ver].SetMaximum(larger)
dict_mem_kb[ver].Draw('AP')
line.SetX1(0)
line.SetY1(0)
line.SetX2(larger)
line.SetY2(larger)
line.SetLineColor(ROOT.kMagenta)
line.SetLineStyle(2)
line.DrawClone("same")
text = "total: " + str(dict_mem_kb[ver].GetN())
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/03___mem_kb_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
#--------------------------------------------------------------------
# vmem_kb
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.02)
c1.SetRightMargin(0.02)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_vmem_kb[ver].GetXaxis().SetTitleSize(0.06)
dict_vmem_kb[ver].GetXaxis().SetTitleOffset(0.900)
dict_vmem_kb[ver].GetXaxis().SetLabelSize(0.05)
dict_vmem_kb[ver].GetYaxis().SetTitleSize(0.06)
dict_vmem_kb[ver].GetYaxis().SetTitleOffset(1.200)
dict_vmem_kb[ver].GetYaxis().CenterTitle()
dict_vmem_kb[ver].GetYaxis().SetLabelSize(0.05)
dict_vmem_kb[ver].SetMarkerColor(ROOT.kRed)
dict_vmem_kb[ver].SetMarkerStyle(20)
dict_vmem_kb[ver].SetMarkerSize(1.2)
dict_vmem_kb[ver].SetLineColor(ROOT.kRed)
dict_vmem_kb[ver].SetLineStyle(1)
dict_vmem_kb[ver].SetLineWidth(1)
dict_vmem_kb[ver].GetXaxis().SetTitle('vmem (GB) for ver' +
format(VERSION, 2))
dict_vmem_kb[ver].GetYaxis().SetTitle('vmem (GB) for ver' +
format(ver, 2))
X = dict_vmem_kb[ver].GetXaxis().GetXmax()
Y = dict_vmem_kb[ver].GetYaxis().GetXmax()
larger = Y if X < Y else X
# don't show negative values (should not exist)
dict_vmem_kb[ver].GetXaxis().SetLimits(0, larger)
dict_vmem_kb[ver].SetMinimum(0)
dict_vmem_kb[ver].SetMaximum(larger)
dict_vmem_kb[ver].Draw('AP')
line.SetX1(0)
line.SetY1(0)
line.SetX2(larger)
line.SetY2(larger)
line.SetLineColor(ROOT.kMagenta)
line.SetLineStyle(2)
line.DrawClone("same")
text = "total: " + str(dict_vmem_kb[ver].GetN())
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/04___vmem_kb_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
#--------------------------------------------------------------------
# nevents
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.04)
c1.SetRightMargin(0.04)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_nevents[ver].GetXaxis().SetTitleSize(0.06)
dict_nevents[ver].GetXaxis().SetTitleOffset(0.900)
dict_nevents[ver].GetXaxis().SetLabelSize(0.05)
dict_nevents[ver].GetYaxis().SetTitleSize(0.06)
dict_nevents[ver].GetYaxis().SetTitleOffset(1.200)
dict_nevents[ver].GetYaxis().CenterTitle()
dict_nevents[ver].GetYaxis().SetLabelSize(0.05)
dict_nevents[ver].SetMarkerColor(ROOT.kRed)
dict_nevents[ver].SetMarkerStyle(20)
dict_nevents[ver].SetMarkerSize(1.2)
dict_nevents[ver].SetLineColor(ROOT.kRed)
dict_nevents[ver].SetLineStyle(1)
dict_nevents[ver].SetLineWidth(1)
dict_nevents[ver].GetXaxis().SetTitle('#events for ver' +
format(VERSION, 2))
dict_nevents[ver].GetYaxis().SetTitle('#events for ver' +
format(ver, 2))
X = dict_nevents[ver].GetXaxis().GetXmax()
Y = dict_nevents[ver].GetYaxis().GetXmax()
larger = Y if X < Y else X
# don't show negative values (should not exist)
dict_nevents[ver].GetXaxis().SetLimits(0, larger)
dict_nevents[ver].SetMinimum(0)
dict_nevents[ver].SetMaximum(larger)
dict_nevents[ver].Draw('AP')
line.SetX1(0)
line.SetY1(0)
line.SetX2(larger)
line.SetY2(larger)
line.SetLineColor(ROOT.kMagenta)
line.SetLineStyle(2)
line.DrawClone("same")
text = "total: " + str(dict_nevents[ver].GetN())
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/05___nevents_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
#--------------------------------------------------------------------
# nevents_diff
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.04)
c1.SetRightMargin(0.04)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_nevents_diff[ver].GetXaxis().SetTitleSize(0.06)
dict_nevents_diff[ver].GetXaxis().SetTitleOffset(0.900)
dict_nevents_diff[ver].GetXaxis().SetLabelSize(0.05)
dict_nevents_diff[ver].GetYaxis().SetTitleSize(0.06)
dict_nevents_diff[ver].GetYaxis().SetTitleOffset(1.200)
dict_nevents_diff[ver].GetYaxis().CenterTitle()
dict_nevents_diff[ver].GetYaxis().SetLabelSize(0.05)
dict_nevents_diff[ver].SetLineColor(ROOT.kRed)
dict_nevents_diff[ver].SetLineStyle(1)
dict_nevents_diff[ver].SetLineWidth(1)
c1.SetLogy(1)
dict_nevents_diff[ver].Draw()
text = "total: " + str(int(dict_nevents_diff[ver].GetEntries()))
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/06___nevents_diff_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
#--------------------------------------------------------------------
# input_copy_sec
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.02)
c1.SetRightMargin(0.02)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_input_copy_sec[ver].GetXaxis().SetTitleSize(0.06)
dict_input_copy_sec[ver].GetXaxis().SetTitleOffset(0.900)
dict_input_copy_sec[ver].GetXaxis().SetLabelSize(0.05)
dict_input_copy_sec[ver].GetYaxis().SetTitleSize(0.06)
dict_input_copy_sec[ver].GetYaxis().SetTitleOffset(1.200)
dict_input_copy_sec[ver].GetYaxis().CenterTitle()
dict_input_copy_sec[ver].GetYaxis().SetLabelSize(0.05)
dict_input_copy_sec[ver].SetMarkerColor(ROOT.kRed)
dict_input_copy_sec[ver].SetMarkerStyle(20)
dict_input_copy_sec[ver].SetMarkerSize(1.2)
dict_input_copy_sec[ver].SetLineColor(ROOT.kRed)
dict_input_copy_sec[ver].SetLineStyle(1)
dict_input_copy_sec[ver].SetLineWidth(1)
dict_input_copy_sec[ver].GetXaxis().SetTitle(
'input copy time (min) for ver' + format(VERSION, 2))
dict_input_copy_sec[ver].GetYaxis().SetTitle(
'input copy time (min) for ver' + format(ver, 2))
X = dict_input_copy_sec[ver].GetXaxis().GetXmax()
Y = dict_input_copy_sec[ver].GetYaxis().GetXmax()
larger = Y if X < Y else X
# don't show negative values (should not exist)
dict_input_copy_sec[ver].GetXaxis().SetLimits(0, larger)
dict_input_copy_sec[ver].SetMinimum(0)
dict_input_copy_sec[ver].SetMaximum(larger)
dict_input_copy_sec[ver].Draw('AP')
line.SetX1(0)
line.SetY1(0)
line.SetX2(larger)
line.SetY2(larger)
line.SetLineColor(ROOT.kMagenta)
line.SetLineStyle(2)
line.DrawClone("same")
text = "total: " + str(dict_input_copy_sec[ver].GetN())
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/07___input_copy_sec_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
#--------------------------------------------------------------------
# plugin_sec
#--------------------------------------------------------------------
c1 = TCanvas('c1', 'canvas', 0, 0, 1600, 1200)
c1.SetTopMargin(0.02)
c1.SetRightMargin(0.02)
c1.SetLeftMargin(0.15)
c1.SetBottomMargin(0.14)
dict_plugin_sec[ver].GetXaxis().SetTitleSize(0.06)
dict_plugin_sec[ver].GetXaxis().SetTitleOffset(0.900)
dict_plugin_sec[ver].GetXaxis().SetLabelSize(0.05)
dict_plugin_sec[ver].GetYaxis().SetTitleSize(0.06)
dict_plugin_sec[ver].GetYaxis().SetTitleOffset(1.200)
dict_plugin_sec[ver].GetYaxis().CenterTitle()
dict_plugin_sec[ver].GetYaxis().SetLabelSize(0.05)
dict_plugin_sec[ver].SetMarkerColor(ROOT.kRed)
dict_plugin_sec[ver].SetMarkerStyle(20)
dict_plugin_sec[ver].SetMarkerSize(1.2)
dict_plugin_sec[ver].SetLineColor(ROOT.kRed)
dict_plugin_sec[ver].SetLineStyle(1)
dict_plugin_sec[ver].SetLineWidth(1)
dict_plugin_sec[ver].GetXaxis().SetTitle('plugin time (min) for ver' +
format(VERSION, 2))
dict_plugin_sec[ver].GetYaxis().SetTitle('plugin time (min) for ver' +
format(ver, 2))
X = dict_plugin_sec[ver].GetXaxis().GetXmax()
Y = dict_plugin_sec[ver].GetYaxis().GetXmax()
larger = Y if X < Y else X
# don't show negative values (should not exist)
dict_plugin_sec[ver].GetXaxis().SetLimits(0, larger)
dict_plugin_sec[ver].SetMinimum(0)
dict_plugin_sec[ver].SetMaximum(larger)
dict_plugin_sec[ver].Draw('AP')
line.SetX1(0)
line.SetY1(0)
line.SetX2(larger)
line.SetY2(larger)
line.SetLineColor(ROOT.kMagenta)
line.SetLineStyle(2)
line.DrawClone("same")
text = "total: " + str(dict_plugin_sec[ver].GetN())
latex.SetTextColor(ROOT.kBlue)
latex.DrawLatex(0.75, 0.92, text)
c1.SaveAs(figureDir + '/08___plugin_time_ver' + format(VERSION, 2) +
'_ver' + format(ver, 2) + '.png')
c1.Close()
# Copy all files to web-accessible directory
outDir = '/group/halld/www/halldweb/html/data_monitoring/launch_analysis/' + RUNPERIOD + '/resource_use/'
shutil.copy(htmlfilename, outDir)
outputfigureDir = outDir + '/figures/SWIF/ver' + format(VERSION, 2)
# delete directory if it already exists (necessary for shutil.copytree)
if os.path.exists(outputfigureDir):
shutil.rmtree(outputfigureDir)
shutil.copytree(figureDir, outputfigureDir + '/')
# Create link from main [RUNPERIOD].html file
# Add the newest row into the html table using the hook
# that is added at the end of each launch version.
runperiodfilename = '/group/halld/www/halldweb/html/data_monitoring/launch_analysis/' + RUNPERIOD + '/' + RUNPERIOD + '.html'
with open(runperiodfilename, 'r') as runperiodfile:
alllines = runperiodfile.readlines()
# Reverse the lines and find the first occurrence of the hook
# this is the final (most recent hook)
alllines.reverse()
nlines = 0
pos = 0
old_hook = ''
for line in alllines:
nlines += 1
if re.search(
'<!--20[1-3][0-9]_[0-1][0-9]_ver[0-9][0-9] resource_use-->',
line):
pos = nlines
old_hook = line
break
if old_hook == '':
print 'Did not find old hook, make sure that file'
print runperiodfilename
print 'has a line containing <!--[RUNPERIOD]_ver[VERSION] resource_use-->'
exit()
# position to seek is total number of lines in file minus pos + 1
pos = len(alllines) - pos + 1
# lines for link
linklines = []
linklines.append(' <li style="color:blue;">\n')
linklines.append(' <h3><a href = "resource_use/resource_use_' + RUNPERIOD + '_ver' + format(VERSION,2) + '.html">' \
+ 'ver' + format(VERSION,2) + '</a></h3> <!--' + RUNPERIOD + '_ver' \
+ format(VERSION,2) + ' resource_use-->\n')
# Reopen stats html file and insert newlines into line pos
with open(runperiodfilename, 'r+') as runperiodfile:
alllines = runperiodfile.readlines()
alllines[pos:pos] = linklines
# Write the new file
with open(runperiodfilename, 'w') as runperiodfile:
for line in alllines:
runperiodfile.write(line)
exit()
def addCMSTitle(x=0.2, y=0.93):
T1 = TLatex()
T1.SetNDC()
T1.DrawLatex(x, y, "#scale[0.9]{CMS Preliminary #sqrt{s} = 8 TeV}")
