def Draw(self, histos, scales, ref, irelhisto, preview=False):
from ROOT import TH1
from ROOT import TH1F
from ROOT import THStack
from ROOT import TLegend
from ROOT import TCanvas
# Creating a canvas
canvas = TCanvas("tempo", "")
# Special case : NPID, NAPID
if ref.observable.name in ['NPID', 'NAPID']:
# New collection with labels
labels = []
# Loop over histos
for ind in range(len(histos)):
nBins = histos[ind].GetNbinsX()
for b in range(1, nBins + 1):
# Get the bin label
theLabel = histos[ind].GetXaxis().GetBinLabel(b)
# Add in the collection
if theLabel not in labels:
labels.append(theLabel)
# Sorting labels (alphabetical order)
labels = sorted(labels)
# New histos
newhistos = []
for ind in range(len(histos)):
nBins = histos[ind].GetNbinsX()
# New histo
newhisto = TH1F(histos[ind].GetName()+'_'+str(ind),\
histos[ind].GetTitle(),\
len(labels),
0,
len(labels))
for ilabel in range(len(labels)):
# Set new labels
newhisto.GetXaxis().SetBinLabel(ilabel + 1, labels[ilabel])
fill = False
for bin in range(1, nBins + 1):
# Get the bin label
if histos[ind].GetXaxis().GetBinLabel(
bin) == labels[ilabel]:
tmp = histos[ind].GetBinContent(bin)
newhisto.SetBinContent(ilabel + 1, tmp)
fill = True
break
if not fill:
newhisto.SetBinContent(ilabel + 1, 0)
newhistos.append(newhisto)
# overwrite histos
histos = newhistos
# Loop over datasets and histos
for ind in range(0, len(histos)):
if ref.observable.name in ['NPID', 'NAPID']:
nBins = histos[ind].GetNbinsX()
for b in range(1, nBins + 1):
pid = int(histos[ind].GetXaxis().GetBinLabel(b))
if ref.observable.name == 'NPID':
spid = self.main.multiparticles.GetName(pid)
else:
spid = self.main.multiparticles.GetAName(-pid, pid)
if spid != "":
histos[ind].GetXaxis().SetBinLabel(b, spid)
# Scaling
histos[ind].Scale(scales[ind])
# Stacking or superimposing histos ?
stackmode = False
if ref.stack==StackingMethodType.STACK or \
( ref.stack==StackingMethodType.AUTO and \
self.main.stack==StackingMethodType.STACK ):
stackmode = True
# Setting AUTO settings
if len(histos) == 1:
histos[0].SetLineColor(9)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
elif len(histos) == 2:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
elif len(histos) == 3:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
elif len(histos) == 4:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
histos[3].SetLineColor(4)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
histos[3].SetFillColor(4)
histos[3].SetFillStyle(3007)
elif len(histos) == 5:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
histos[3].SetLineColor(4)
histos[4].SetLineColor(6)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
histos[3].SetFillColor(4)
histos[3].SetFillStyle(3007)
histos[4].SetFillColor(6)
histos[4].SetFillStyle(3013)
elif len(histos) == 6:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
histos[3].SetLineColor(4)
histos[4].SetLineColor(6)
histos[5].SetLineColor(2)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
histos[3].SetFillColor(4)
histos[3].SetFillStyle(3007)
histos[4].SetFillColor(6)
histos[4].SetFillStyle(3013)
histos[5].SetFillColor(2)
histos[5].SetFillStyle(3017)
elif len(histos) == 7:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
histos[3].SetLineColor(4)
histos[4].SetLineColor(6)
histos[5].SetLineColor(2)
histos[6].SetLineColor(7)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
histos[3].SetFillColor(4)
histos[3].SetFillStyle(3007)
histos[4].SetFillColor(6)
histos[4].SetFillStyle(3013)
histos[5].SetFillColor(2)
histos[5].SetFillStyle(3017)
histos[6].SetFillColor(7)
histos[6].SetFillStyle(3022)
elif len(histos) == 8:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
histos[3].SetLineColor(4)
histos[4].SetLineColor(6)
histos[5].SetLineColor(2)
histos[6].SetLineColor(7)
histos[7].SetLineColor(3)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
histos[3].SetFillColor(4)
histos[3].SetFillStyle(3007)
histos[4].SetFillColor(6)
histos[4].SetFillStyle(3013)
histos[5].SetFillColor(2)
histos[5].SetFillStyle(3017)
histos[6].SetFillColor(7)
histos[6].SetFillStyle(3022)
histos[7].SetFillColor(3)
histos[7].SetFillStyle(3315)
elif len(histos) == 9:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
histos[3].SetLineColor(4)
histos[4].SetLineColor(6)
histos[5].SetLineColor(2)
histos[6].SetLineColor(7)
histos[7].SetLineColor(3)
histos[8].SetLineColor(42)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
histos[3].SetFillColor(4)
histos[3].SetFillStyle(3007)
histos[4].SetFillColor(6)
histos[4].SetFillStyle(3013)
histos[5].SetFillColor(2)
histos[5].SetFillStyle(3017)
histos[6].SetFillColor(7)
histos[6].SetFillStyle(3022)
histos[7].SetFillColor(3)
histos[7].SetFillStyle(3315)
histos[8].SetFillColor(42)
histos[8].SetFillStyle(3351)
elif len(histos) == 10:
histos[0].SetLineColor(9)
histos[1].SetLineColor(46)
histos[2].SetLineColor(8)
histos[3].SetLineColor(4)
histos[4].SetLineColor(6)
histos[5].SetLineColor(2)
histos[6].SetLineColor(7)
histos[7].SetLineColor(3)
histos[8].SetLineColor(42)
histos[9].SetLineColor(48)
if stackmode:
histos[0].SetFillColor(9)
histos[0].SetFillStyle(3004)
histos[1].SetFillColor(46)
histos[1].SetFillStyle(3005)
histos[2].SetFillColor(8)
histos[2].SetFillStyle(3006)
histos[3].SetFillColor(4)
histos[3].SetFillStyle(3007)
histos[4].SetFillColor(6)
histos[4].SetFillStyle(3013)
histos[5].SetFillColor(2)
histos[5].SetFillStyle(3017)
histos[6].SetFillColor(7)
histos[6].SetFillStyle(3022)
histos[7].SetFillColor(3)
histos[7].SetFillStyle(3315)
histos[8].SetFillColor(42)
histos[8].SetFillStyle(3351)
histos[9].SetFillColor(48)
histos[9].SetFillStyle(3481)
else:
histos[ind].SetLineColor(self.color)
self.color += 1
# Setting USER color
for ind in range(0, len(histos)):
# linecolor
if self.main.datasets[ind].linecolor != ColorType.AUTO:
histos[ind].SetLineColor(ColorType.convert2root( \
self.main.datasets[ind].linecolor,\
self.main.datasets[ind].lineshade))
# lineStyle
histos[ind].SetLineStyle(LineStyleType.convert2code( \
self.main.datasets[ind].linestyle))
# linewidth
histos[ind].SetLineWidth(self.main.datasets[ind].linewidth)
# background color
if self.main.datasets[ind].backcolor != ColorType.AUTO:
histos[ind].SetFillColor(ColorType.convert2root( \
self.main.datasets[ind].backcolor,\
self.main.datasets[ind].backshade))
# background color
if self.main.datasets[ind].backstyle != BackStyleType.AUTO:
histos[ind].SetFillStyle(BackStyleType.convert2code( \
self.main.datasets[ind].backstyle))
# Creating and filling the stack; computing the total number of events
stack = THStack("mystack", "")
ntot = 0
for item in histos:
ntot += item.GetEntries()
stack.Add(item)
# Drawing
if stackmode:
stack.Draw()
else:
stack.Draw("nostack")
# Setting Y axis label
axis_titleY = ref.GetYaxis()
# Scale to one ?
scale2one = False
if ref.stack==StackingMethodType.NORMALIZE2ONE or \
(self.main.stack==StackingMethodType.NORMALIZE2ONE and \
ref.stack==StackingMethodType.AUTO):
scale2one = True
if scale2one:
axis_titleY += " ( scaled to one )"
elif self.main.normalize == NormalizeType.LUMI or \
self.main.normalize == NormalizeType.LUMI_WEIGHT:
axis_titleY += " ( L_{int} = " + str(self.main.lumi) + " fb^{-1} )"
elif self.main.normalize == NormalizeType.NONE:
axis_titleY += " (not normalized)"
if ref.titleY != "":
axis_titleY = self.NiceTitle(ref.titleY)
stack.GetYaxis().SetTitle(axis_titleY)
if (len(axis_titleY) > 35):
stack.GetYaxis().SetTitleSize(0.04)
else:
stack.GetYaxis().SetTitleSize(0.06)
stack.GetYaxis().SetTitleFont(22)
stack.GetYaxis().SetLabelSize(0.04)
# Setting X axis label
if ref.titleX == "":
axis_titleX = ref.GetXaxis()
else:
axis_titleX = self.NiceTitle(ref.titleX)
# Setting X axis label
stack.GetXaxis().SetTitle(axis_titleX)
stack.GetXaxis().SetTitleSize(0.06)
stack.GetXaxis().SetTitleFont(22)
stack.GetXaxis().SetLabelSize(0.04)
# Setting Log scale
if ref.logX and ntot != 0:
canvas.SetLogx()
if ref.logY and ntot != 0:
canvas.SetLogy()
# Displaying a legend
if len(self.main.datasets) > 1:
ymin_legend = .9 - .055 * len(histos)
if ymin_legend < 0.1:
ymin_legend = 0.1
legend = TLegend(.65, ymin_legend, .9, .9)
legend.SetTextSize(0.05)
legend.SetTextFont(22)
for ind in range(0, len(histos)):
legend.AddEntry(histos[ind],
self.NiceTitle(self.main.datasets[ind].title))
legend.SetFillColor(0)
legend.Draw()
if not preview:
# Save the canvas in the report format
canvas.SaveAs(self.output_path+"/selection_"+str(irelhisto)+"."+\
ReportFormatType.convert2filetype(self.mode))
# Save the canvas in the C format
canvas.SaveAs(self.output_path + "/selection_" + str(irelhisto) +
".C")
else:
# break
answer = raw_input("Press enter to continue : ")
h_signal_2017.Integral())
h_signal_2016.Scale(scaling_factor_2016_2018)
h_signal_2016.SetMarkerStyle(20)
h_signal_2016.SetMarkerColor(3)
h_signal_2017.Scale(scaling_factor_2017_2018)
h_signal_2017.SetMarkerStyle(20)
h_signal_2017.SetMarkerColor(2)
h_signal_2018.SetMarkerStyle(20)
h_signal_2018.SetMarkerColor(1)
h_signal_2016.GetXaxis().SetLabelOffset(999)
h_signal_2016.GetXaxis().SetTitle("#it{m}_{#pi#gamma} (GeV)")
h_signal_2016.GetYaxis().SetTitle("Events")
h_signal_2016.Draw()
h_signal_2017.Draw("SAME")
h_signal_2018.Draw("SAME")
legend_years.Draw("SAME")
pad2.cd()
pad2.SetTopMargin(0.03)
pad2.SetFillColor(0)
pad2.SetFillStyle(0)
for entry in h_ratio_list:
h_ratio_hists[entry].SetTitle("")
h_ratio_hists[entry].SetMarkerStyle(8)
h_ratio_hists[entry].SetLineColor(1)
h_ratio_hists[entry].GetYaxis().SetLabelSize(0.1)
h_ratio_hists[entry].GetYaxis().SetTitle("Ratio")
h_ratio_hists[entry].GetYaxis().SetTitleSize(0.12)
#h_ratio_hists[entry].GetYaxis().SetTitleOffset(0.98)
h_ratio_hists[entry].GetYaxis().SetTitleOffset(0.25)
def plotBlockComparison(treeBlockA,treeBlockB,variable,additionalCut,nBins,firstBin,lastBin,labelX,labelY,suffix,log=False,signal=False):
hCanvas = TCanvas("hCanvas", "Distribution", 800,800)
plotPad = ROOT.TPad("plotPad","plotPad",0,0.3,1,1)
ratioPad = ROOT.TPad("ratioPad","ratioPad",0,0.,1,0.3)
setTDRStyle()
plotPad.UseCurrentStyle()
ratioPad.UseCurrentStyle()
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
legend = TLegend(0.7, 0.55, 0.95, 0.95)
legend.SetFillStyle(0)
legend.SetBorderSize(1)
minMll = 20
ROOT.gStyle.SetOptStat(0)
Cutlabel = ROOT.TLatex()
Cutlabel.SetTextAlign(12)
Cutlabel.SetTextSize(0.03)
Labelin = ROOT.TLatex()
Labelin.SetTextAlign(12)
Labelin.SetTextSize(0.07)
Labelin.SetTextColor(ROOT.kRed+2)
Labelout = ROOT.TLatex()
Labelout.SetTextAlign(12)
Labelout.SetTextSize(0.07)
Labelout.SetTextColor(ROOT.kBlack)
EMuhistBlockA = createHistoFromTree(treeBlockA, variable, additionalCut, nBins, firstBin, lastBin, -1)
EMuhistBlockB = createHistoFromTree(treeBlockB, variable, additionalCut, nBins, firstBin, lastBin, -1)
EMuhistBlockB.Scale(9.2/10.4)
print EMuhistBlockA.Integral()
print EMuhistBlockB.Integral()
EMuhistBlockA.SetMarkerStyle(21)
EMuhistBlockB.SetMarkerStyle(22)
EMuhistBlockA.SetMarkerColor(ROOT.kGreen+3)
EMuhistBlockB.SetMarkerColor(ROOT.kBlack)
EMuhistBlockA.SetLineColor(ROOT.kGreen+3)
EMuhistBlockB.SetLineColor(ROOT.kBlack)
if log:
yMin=0.1
yMax = max(EMuhistBlockA.GetBinContent(EMuhistBlockA.GetMaximumBin()),EMuhistBlockB.GetBinContent(EMuhistBlockB.GetMaximumBin()))*10
plotPad.SetLogy()
else:
yMin=0
yMax = max(EMuhistBlockA.GetBinContent(EMuhistBlockA.GetMaximumBin()),EMuhistBlockB.GetBinContent(EMuhistBlockB.GetMaximumBin()))*1.5
hCanvas.DrawFrame(firstBin,yMin,lastBin,yMax,"; %s ; %s" %(labelX,labelY))
EMuhistBlockA.Draw("samep")
EMuhistBlockB.Draw("samep")
legend.AddEntry(EMuhistBlockA,"First 9.2 fb^{-1}","p")
legend.AddEntry(EMuhistBlockB,"Second 10.4 fb^{-1} scaled","p")
#~
latex = ROOT.TLatex()
latex.SetTextSize(0.043)
latex.SetTextFont(42)
latex.SetNDC(True)
latex.DrawLatex(0.13, 0.95, "CMS Preliminary, #sqrt{s} = 8 TeV, #scale[0.6]{#int}Ldt = 9.2-10.4 fb^{-1}")
#~
legend.Draw("same")
ratioPad.cd()
ratioGraphs = ratios.RatioGraph(EMuhistBlockA,EMuhistBlockB, firstBin, lastBin,title="Bl. A / Bl. B",yMin=0.0,yMax=2,ndivisions=10,color=ROOT.kGreen+3,adaptiveBinning=0.25)
ratioGraphs.draw(ROOT.gPad,True,False,True,chi2Pos=0.8)
if signal:
name = "OFUnblinding_SignalRegion_%s_%s.pdf"
else:
name = "OFUnblinding_Inclusive_%s_%s.pdf"
if variable == "p4.M()":
hCanvas.Print(name%(suffix,"Mll"))
else:
hCanvas.Print(name%(suffix,variable))
hCanvas.Clear()
def plotUpperLimits(labels, values):
# see CMS plot guidelines: https://ghm.web.cern.ch/ghm/plots/
N = len(labels)
yellow = TGraph(2 * N) # yellow band
green = TGraph(2 * N) # green band
median = TGraph(N) # median line
up2s = []
for i in range(N):
file_name = "higgsCombine" + labels[i] + ".AsymptoticLimits.mH125.root"
limit = getLimits(file_name)
up2s.append(limit[4])
yellow.SetPoint(i, values[i], limit[4]) # + 2 sigma
green.SetPoint(i, values[i], limit[3]) # + 1 sigma
median.SetPoint(i, values[i], limit[2]) # median
green.SetPoint(2 * N - 1 - i, values[i], limit[1]) # - 1 sigma
yellow.SetPoint(2 * N - 1 - i, values[i], limit[0]) # - 2 sigma
W = 800
H = 600
T = 0.08 * H
B = 0.12 * H
L = 0.12 * W
R = 0.04 * W
c = TCanvas("c", "c", 100, 100, W, H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
c.SetLeftMargin(L / W)
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.SetTickx(0)
c.SetTicky(0)
c.SetGrid()
c.cd()
frame = c.DrawFrame(1.4, 0.001, 4.1, 10)
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetTitleSize(0.05)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetLabelSize(0.04)
frame.GetYaxis().SetLabelSize(0.04)
frame.GetYaxis().SetTitleOffset(0.9)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
frame.GetYaxis().SetTitle("95% upper limit on #sigma / #sigma_{SM}")
# frame.GetYaxis().SetTitle("95% upper limit on #sigma #times BR / (#sigma #times BR)_{SM}")
frame.GetXaxis().SetTitle("background systematic uncertainty [%]")
frame.SetMinimum(0)
frame.SetMaximum(max(up2s) * 1.05)
frame.GetXaxis().SetLimits(min(values), max(values))
yellow.SetFillColor(ROOT.kOrange)
yellow.SetLineColor(ROOT.kOrange)
yellow.SetFillStyle(1001)
yellow.Draw("F")
green.SetFillColor(ROOT.kGreen + 1)
green.SetLineColor(ROOT.kGreen + 1)
green.SetFillStyle(1001)
green.Draw("Fsame")
median.SetLineColor(1)
median.SetLineWidth(2)
median.SetLineStyle(2)
median.Draw("Lsame")
cms_lumi.cms_lumi(c, 14, 11)
ROOT.gPad.SetTicks(1, 1)
frame.Draw("sameaxis")
x1 = 0.15
x2 = x1 + 0.24
y2 = 0.76
y1 = 0.60
legend = TLegend(x1, y1, x2, y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(42)
legend.AddEntry(median, "Asymptotic CL_{s} expected", "L")
legend.AddEntry(green, "#pm 1 std. deviation", "f")
# legend.AddEntry(green, "Asymptotic CL_{s} #pm 1 std. deviation",'f')
legend.AddEntry(yellow, "#pm 2 std. deviation", "f")
# legend.AddEntry(green, "Asymptotic CL_{s} #pm 2 std. deviation",'f')
legend.Draw()
print(" ")
c.SaveAs("UpperLimit.png")
c.Close()
def plot1(key, xsection1, xsection2, histo1, histo2, name1, name2, LogY, weight1, weight2, outputDIR):
c1=TCanvas(key, key, 800, 600)
pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
pad1.SetGridx()
pad1.SetGridy()
pad2.SetGridy()
pad1.SetFillColor(0)
pad1.SetLineColor(0)
pad2.SetFillColor(0)
pad2.SetLineColor(0)
pad1.SetBottomMargin(0.03)
pad2.SetTopMargin(0.15)
pad2.SetBottomMargin(0.3)
pad1.Draw()
pad2.Draw()
leg1 = TLegend(0.65,0.75,0.86,0.86)
histo1.Scale(xsection1/weight1)
histo1.SetMaximum(1.2*histo1.GetMaximum())
histo1.SetMinimum(0.0001)
histo1.SetLineColor(kRed)
histo1.SetLineWidth(2)
histo1.GetXaxis().SetLabelSize(0)
histo2.Scale(xsection2/weight2)
histo2.SetLineColor(kBlack)
histo2.SetLineWidth(2)
pad1.cd()
if LogY:
pad1.SetLogy()
histo_ratio=histo2.Clone()
histo_ratio.SetTitle('')
histo_ratio.Divide(histo1)
histo_ratio.SetMaximum(1.5)
histo_ratio.SetMinimum(0.5)
histo_ratio.GetYaxis().SetNdivisions(4,kFALSE)
histo_ratio.GetXaxis().SetTitle(key)
histo_ratio.GetXaxis().SetTitleSize(0.15)
histo_ratio.GetXaxis().SetTitleOffset(0.75)
histo_ratio.GetXaxis().SetLabelSize(0.13)
histo_ratio.GetYaxis().SetTitle(name1+'/'+name2)
histo_ratio.GetYaxis().SetTitleSize(0.1)
histo_ratio.GetYaxis().SetTitleOffset(0.3)
histo_ratio.GetYaxis().SetLabelSize(0.13)
histo_ratio.SetLineWidth(2)
histo1.Draw('pe')
histo2.Draw('same pe')
leg1.AddEntry(histo1, name1)
leg1.AddEntry(histo2, name2)
leg1.SetFillStyle(0)
leg1.SetBorderSize(0)
leg1.Draw()
c1.Update()
pad2.cd()
histo_ratio.Draw()
if LogY:
c1.SaveAs(outputDIR + '/' + key + '_log.png')
c1.SaveAs(outputDIR + '/' + key + '_log.pdf')
else:
c1.SaveAs(outputDIR + '/' + key + '.png')
c1.SaveAs(outputDIR + '/' + key + '.pdf')
# renew
histo1.Scale(weight1/xsection1)
histo2.Scale(weight2/xsection2)
def comp_fit_pars(do_ratio=False, meson='Ds'): #pylint: disable-msg=too-many-statements,too-many-locals
inputdir = '../../AnalysisNonPromptDpp2017/Dplus/outputs/rawyields'
input_files = ['RawYieldsDplus_pp5TeV_prompt_central.root', 'RawYieldsDplus_pp5TeV_FD_central_freesigma.root']
input_files_MC = ['RawYieldsDplusMC_pp5TeV_prompt_central.root', 'RawYieldsDplusMC_pp5TeV_FD_central.root']
colors = [kOrange+7, kAzure+2, kRed+1, kAzure+4]
markers = [kOpenCircle, kOpenSquare, kFullCircle, kFullSquare]
legendnames = ['MC - prompt enhanced', 'MC - FD enhanced', 'data - prompt enhanced', 'data - FD enhanced']
suffix = 'CompMCData'
min_pt = 2.
max_pt = 16.
SetGlobalStyle(padleftmargin=0.18, padtopmargin=0.05, padbottommargin=0.14,
titleoffsety=1.6, titlesize=0.045, labelsize=0.04)
hMean, hSigma = [], []
input_files = input_files_MC + input_files
if meson == 'Ds':
massD = TDatabasePDG.Instance().GetParticle(431).Mass()
elif meson == 'Dplus':
massD = TDatabasePDG.Instance().GetParticle(411).Mass()
lineMass = TLine(min_pt, massD, max_pt, massD)
lineMass.SetLineWidth(2)
lineMass.SetLineColor(kBlack)
lineMass.SetLineStyle(9)
legSigma = TLegend(0.2, 0.78, 0.8, 0.93)
legSigma.SetFillStyle(0)
legSigma.SetBorderSize(0)
legSigma.SetTextSize(0.04)
legMean = TLegend(0.4, 0.73, 0.7, 0.93)
legMean.SetFillStyle(0)
legMean.SetBorderSize(0)
legMean.SetTextSize(0.04)
legMean.AddEntry(lineMass, "PDG", 'l')
for file_path, color, marker, legend_name in zip(input_files, colors, markers, legendnames):
input_file = TFile(f'{inputdir}/{file_path}')
histo_mean = input_file.Get('hRawYieldsMean')
histo_sigma = input_file.Get('hRawYieldsSigma')
histo_mean.SetDirectory(0)
histo_sigma.SetDirectory(0)
SetObjectStyle(histo_mean, linecolor=color, markercolor=color, markerstyle=marker)
SetObjectStyle(histo_sigma, linecolor=color, markercolor=color, markerstyle=marker)
legMean.AddEntry(histo_mean, legend_name, 'p')
legSigma.AddEntry(histo_sigma, legend_name, 'p')
hMean.append(histo_mean)
hSigma.append(histo_sigma)
if do_ratio:
mean_num_list = list(hMean)
mean_num_list.pop(0)
mean_den_hist = hMean[0]
mean_ratio_list = []
for histo in mean_num_list:
mean_ratio_list.append(ComputeRatioDiffBins(histo, mean_den_hist))
cMeanRatio = TCanvas('cMeanRatio', '', 800, 800)
cMeanRatio.DrawFrame(min_pt, 0.99, max_pt, 1.01, ';#it{p}_{T} (GeV/#it{c}); peak mean / peak mean MC')
lineRatio = TLine(min_pt, 1., max_pt, 1.)
lineRatio.SetLineWidth(2)
lineRatio.SetLineColor(kBlack)
lineRatio.SetLineStyle(9)
legMeanRatio = TLegend(0.4, 0.73, 0.7, 0.93)
legMeanRatio.SetFillStyle(0)
legMeanRatio.SetBorderSize(0)
legMeanRatio.SetTextSize(0.04)
for hist, color, marker, legend_name in zip(mean_ratio_list, colors[1:],
markers[1:], legendnames[1:]):
SetObjectStyle(hist, linecolor=color, markercolor=color, markerstyle=marker)
hist.Draw('same')
legMeanRatio.AddEntry(hist, legend_name, 'p')
lineRatio.Draw()
legMeanRatio.Draw()
sigma_num_list = list(hSigma)
sigma_num_list.pop(0)
sigma_den_hist = hSigma[0]
sigma_ratio_list = []
for histo in sigma_num_list:
sigma_ratio_list.append(ComputeRatioDiffBins(histo, sigma_den_hist))
cSigmaRatio = TCanvas('cSigmaRatio', '', 800, 800)
hFrameSigma = cSigmaRatio.DrawFrame(min_pt, 0.6, max_pt, 1.8,
';#it{p}_{T} (GeV/#it{c}); peak width / peak width MC')
hFrameSigma.GetYaxis().SetDecimals()
legSigmaRatio = TLegend(0.4, 0.73, 0.7, 0.93)
legSigmaRatio.SetFillStyle(0)
legSigmaRatio.SetBorderSize(0)
legSigmaRatio.SetTextSize(0.04)
for hist, color, marker, legend_name in zip(sigma_ratio_list, colors[1:],
markers[1:], legendnames[1:]):
SetObjectStyle(hist, linecolor=color, markercolor=color, markerstyle=marker)
hist.Draw('same')
legSigmaRatio.AddEntry(hist, legend_name, 'p')
lineRatio.Draw()
legSigmaRatio.Draw()
cMeanRatio.SaveAs(f'{inputdir}/MeanRatio_{suffix}.pdf')
cSigmaRatio.SaveAs(f'{inputdir}/SigmaRatio_{suffix}.pdf')
cMean = TCanvas('cMean', '', 800, 800)
hFrameMean = cMean.DrawFrame(min_pt, massD*0.995, max_pt, massD*1.01,
';#it{p}_{T} (GeV/#it{c}); peak mean (GeV/#it{c}^{2})')
hFrameMean.GetYaxis().SetDecimals()
lineMass.Draw("same")
for histo_mean in hMean:
histo_mean.Draw('same')
legMean.Draw()
cSigma = TCanvas('cSigma', '', 800, 800)
cSigma.DrawFrame(min_pt, 0., max_pt, 0.025, ';#it{p}_{T} (GeV/#it{c}); peak width (GeV/#it{c}^{2})')
for histo_sigma in hSigma:
histo_sigma.Draw('same')
legSigma.Draw()
cMean.SaveAs(f'{inputdir}/Mean_{suffix}.pdf')
cSigma.SaveAs(f'{inputdir}/Sigma_{suffix}.pdf')
input('Press enter to exit')
else:
tau_frWeight = tree_t.tau_fake_prob
evtWeight = evtWeight * lep1_frWeight * lep2_frWeight * lep3_frWeight * tau_frWeight
mvaValue = reader.EvaluateMVA("testmva")
hist_bkg.Fill(mvaValue, evtWeight)
hist_signal.SetLineColor(2)
hist_bkg.SetLineColor(4)
hist_signal.SetFillColor(2)
hist_bkg.SetFillColor(4)
hist_signal.SetFillStyle(3004)
hist_bkg.SetFillStyle(3005)
leg = TLegend(0.2, 0.65, 0.5, 0.9)
leg.SetBorderSize(0)
leg.SetFillColor(10)
leg.SetLineColor(0)
leg.SetFillStyle(0)
leg.SetTextSize(0.04)
leg.SetTextFont(42)
leg.AddEntry(hist_signal, "loose selection", "l")
leg.AddEntry(hist_bkg, "tight selection", "l")
hist_signal.DrawNormalized("histsame")
hist_bkg.DrawNormalized("histsame")
leg.Draw()
c1.SaveAs("plots/bdt_score_sklearn_3l1t_8Var_wfrWt_loose_vs_tight_" + process +
".png")
if "Pt" in plotName_list[i]:
canvas.SetLogy()
# if "Chi2" in plotName_list[i] :
# canvas.SetLogx()
# gmt_list[i].Draw('EP')
kalman_list[i].Draw('EP')
kalmanAll_list[i].Draw('sameEP')
bmtfStd_list[i].Draw('sameEP')
bmtf_list[i].Draw('sameEP')
# legend
legend = TLegend(0.80, 0.74, 0.99, 0.91)
legend.AddEntry(kalman_list[i], "Kalman Cleaned", "pl")
legend.AddEntry(kalmanAll_list[i], "Kalman All", "pl")
# legend.AddEntry(gmt_list[i],"Gmt","pl")
legend.AddEntry(bmtfStd_list[i], "BmtfStd", "pl")
legend.AddEntry(bmtf_list[i], "Bmtf", "pl")
legend.SetFillColor(kWhite)
legend.SetLineColor(kBlack)
legend.SetTextFont(43)
legend.SetTextSize(14) #20
legend.Draw()
canvas.Update()
canvas.SaveAs(OutputPath + "/" + plotName_list[i] + ".pdf")
canvas.SaveAs(OutputPath + "/" + plotName_list[i] + ".png")
def sysCompare():
parser = argparse.ArgumentParser(
description='Produce Systematic Uncertainties From Varied inputs.')
parser.add_argument(
'-d',
'--directory',
required=False,
default="",
type=str,
help=
"Directory for comparison plots. If none given, plots are not saved")
parser.add_argument(
'-l',
'--list',
required=False,
type=str,
default="",
help=
"List of histograms/graphs to use. If not given, all objects are used."
)
parser.add_argument('-o',
'--output',
required=True,
type=str,
help="Output file to produce")
# parser.add_argument('-a','--all',requred=False,type=bool,help="whether to use all valid objects in the first file")
parser.add_argument('-r',
'--ratioMode',
required=False,
type=bool,
default=False,
help="Whether to produce plots of the ratios")
parser.add_argument(
'-c',
'--centerValueMode',
required=False,
default=0,
type=int,
help=
"Whether to use the first file as the central value (0) or the average (1)"
)
parser.add_argument('-t',
'--titles',
required=True,
type=str,
nargs='+',
help="Titles for each file")
parser.add_argument('-f',
'--files',
metavar='Files',
required=True,
type=str,
nargs='+',
help="Files to use")
parser.add_argument('-D',
'--DeletePoints',
required=False,
default=0,
type=int,
help="Delete the beginning N points for TGraphs")
# parser.add_argument('files',metavar='Files',type=str,nargs='+',help="Files to use")
parser.add_argument('-T',
'--OverallTitle',
required=False,
type=str,
default="",
help="Title to appear in legend headers")
parser.add_argument('-y',
'--LogY',
required=False,
type=int,
default=False,
help="Whether to force the plots to have log Y.")
args = parser.parse_args()
setStyle()
stringListOfHists = args.list
#list of hists/graphs
listOfHists = stringListOfHists.split()
# bUseAllObjs=False
# if (len(listOfHists) == 0):
# bUseAllObjs=True
bUseAllObjs = (len(listOfHists) == 0)
bRatioMode = args.ratioMode
if (bRatioMode):
print("Ratio Mode is enabled.")
#array of files
fileNames = args.files
fileTitles = args.titles
directory = args.directory
outputFileName = args.output
CenterValueMode = args.centerValueMode
LogYMode = False
LogYMode = args.LogY
numDelete = args.DeletePoints
print("List of hists/graphs to use:"),
print(listOfHists)
if (bUseAllObjs):
print("Will use all valid objects found in the first file")
else:
print("List of files to use:")
print(fileNames)
print("That is %d files" % (len(fileNames)))
print("List of titles:")
print(fileTitles)
print("That is %d titles" % (len(fileTitles)))
if (len(fileNames) != len(fileTitles)):
print("Error: mismatch in number of files vs titles")
exit(1)
print("Primary file:")
print(fileNames[0])
if (numDelete > 0):
print("Will delete the first %d points from TGraphs" % (numDelete))
# list of files
files = []
titlesToFileNames = zip(fileTitles, fileNames)
titlesToFileNames = set(titlesToFileNames)
print(titlesToFileNames)
fileNamesToTitles = zip(fileNames, fileTitles)
fileNamesToTitles = dict(fileNamesToTitles)
filesToTitles = {}
cleanTitlesToFiles = {}
filesToCleanTitles = {}
for filename in fileNames:
print("Opening File %s" % (filename))
tfile = TFile.Open(filename, "READ")
print("opened file %s" % (tfile.GetName()))
files.append(tfile)
filesToTitles[tfile] = fileNamesToTitles[filename]
# clean name that can be added to root object names
cleanedTitle = cleanName(fileNamesToTitles[filename])
filesToCleanTitles[tfile] = cleanedTitle
primaryFile = files[0]
if (directory == ""):
print("No directory given. Output plots will not be saved")
else:
print("Directory for output %s" % (directory))
# create output file here, before changing directory
outputFile = TFile.Open(outputFileName, "RECREATE")
OverallTitle = args.OverallTitle
canvas = TCanvas("canvas", "canvas", c_width, c_height)
if (directory != ""):
# check if the directory exists
if (not os.path.isdir(directory)):
os.makedirs(directory)
os.chdir(directory)
# This is where it gets easier than compare: just need to find the objects in the files
if (bUseAllObjs):
print("Building list of objects")
#primaryObj
ListOfKeys = primaryFile.GetListOfKeys()
for key in ListOfKeys:
print("Adding item %s" % (key.GetName()))
listOfHists.append(key.GetName())
for objName in listOfHists:
print("Starting the thing for object %s" % (objName))
#print(" Looking in file %s" % (primaryFile.GetName()))
primaryObj = primaryFile.Get(objName)
if (not primaryObj):
print("Could not find object %s in file %s" %
(objName, fileNames[0]))
else:
print("obj title = %s" % (primaryObj.GetTitle()))
objectTitle = primaryObj.GetTitle()
listOfObjs = []
for tfile in files:
localObj = tfile.Get(objName)
if (not localObj):
print("Could not find object %s in file %s" % (objName, tfile))
exit(1)
else:
print("obj title = %s" % (localObj.GetTitle()))
localObj.SetName("%s_%s" % (objName, filesToCleanTitles[tfile]))
print(" name set to %s" % (localObj.GetName()))
localObj.SetTitle(filesToTitles[tfile])
print(" title set to %s" % (localObj.GetTitle()))
listOfObjs.append(localObj)
legX = 0.6
legY = 0.22
legWidth = 0.2 #0.45
legHeight = 0.4 #0.225
# legend for comparison
# leg = TLegend(legX,legY,legX+legWidth,legY+legHeight)
# legend for SysUncert
# leg2 = TLegend(legX,legY,legX+legWidth,legY+legHeight)
# legend for comparison
leg = TLegend(legWidth, legHeight, legWidth, legHeight)
if (OverallTitle != ""):
leg.SetHeader(OverallTitle, "c")
# legend for SysUncert
leg2 = TLegend(legWidth, legHeight, legWidth, legHeight)
# Set Properties and include in legend
for i in range(len(listOfObjs)):
localObj = listOfObjs[i]
localTitle = fileTitles[i]
color = ROOT.kBlack
if (i != 0):
if (useCustomColor):
color = GetCustomColor(i)
else:
color = colorList[i]
if (i >= len(markerList)):
# This check code is redundant for now, in case I
# want to switch so something fancier than just looping
# marker styles
markerStyle = markerList[i % len(markerList)]
else:
markerStyle = markerList[i]
localObj.SetMarkerColor(color)
localObj.SetLineColor(color)
localObj.SetMarkerStyle(markerStyle)
localObj.SetTitle(localTitle)
localObj.SetFillColor(0)
leg.AddEntry(localObj, localTitle, "LP")
leg2.AddEntry(listOfObjs[0], fileTitles[0], "LP")
# Two key cases: TGraph or TH1
# For TGraphs we want to do a multigraph
# for th1, we have to manually track the y-limits
iObjType = GetObjType(listOfObjs[0])
# tgraph : 1
# th1 : 2
# other : 0
canvas.Clear()
canvas.cd()
if (iObjType == 0): # Not coded yet
print("Object is of a type I don't have comparison code for (yet)")
continue
if (iObjType == 1): # TGraph
# Get object name
#objName = "TestGraph"
# Reset the margins
gPad.SetTopMargin(fDefaultTopMargin)
gPad.SetLeftMargin(fDefaultLeftMargin)
gPad.SetBottomMargin(fDefaultBottomMargin)
gPad.SetRightMargin(fDefaultRightMargin)
mg = TMultiGraph()
for j in range(numDelete):
print("Deleting a point from object %s" %
(primaryObj.GetName()))
primaryObj.RemovePoint(0) # remove the first point
mg.SetTitle(primaryObj.GetTitle())
mg.GetXaxis().SetTitle(primaryObj.GetXaxis().GetTitle())
mg.GetYaxis().SetTitle(primaryObj.GetYaxis().GetTitle())
# FIXME is this going to double deleting points from the primary object
for lobj in listOfObjs:
print("Object starts with %d points" % (lobj.GetN()))
for j in range(numDelete):
print("Deleting a point from object %s" % (lobj.GetName()))
lobj.RemovePoint(0) # remove the first point
print("Object ends with %d points" % (lobj.GetN()))
mg.Add(lobj)
mg.Draw("ALP")
mg.GetXaxis().SetLabelSize(AxisLabelSizeX)
mg.GetYaxis().SetLabelSize(AxisLabelSizeY)
#leg.Draw("SAME")
legtest = gPad.BuildLegend()
legtest.Draw("SAME")
if (directory != ""):
canvas.Print("%s_Cmp.pdf" % (objName))
canvas.Print("%s_Cmp.png" % (objName))
canvas.Print("%s_Cmp.C" % (objName))
# Now produce systematic uncertainties (for TGraphErrors
(sysUncertObj,
ListOfRangeHists) = ProduceSystematicFromGraphs(listOfObjs)
sysUncertObj.SetName("%s_SysErr" % (objName))
#sysUncertObj.SetName(objName)
totalUncertObj = ProduceTotalErrorGraphs(primaryObj, sysUncertObj)
totalUncertObj.SetName(objName)
#totalUncertObj.SetName("%s_TotalErr" % (objName))
sysUncertObj.SetTitle("Systematic Uncertainty")
sysUncertObj.SetFillColor(ROOT.kBlue)
sysUncertObj.SetFillStyle(3002)
sysUncertObj.Draw("ALP[]5")
# reset the primary objects title
primaryObj.Draw("LP")
leg2.AddEntry(sysUncertObj, "Systematic Uncertainty", "F")
#mg.Draw("LP")
#leg.Draw("SAME")
leg2.Draw("SAME")
# not using the autobuild legend here. could get a good location
# from the comparison plot
#legtest2=gPad.BuildLegend()
#legtest2.Draw("SAME")
if (directory != ""):
canvas.Print("%s_SysUncert.pdf" % (objName))
canvas.Print("%s_SysUncert.png" % (objName))
outputFile.Add(sysUncertObj)
outputFile.Add(totalUncertObj)
for hist in ListOfRangeHists:
outputFile.Add(hist)
# Now plot them both in a split canvas
canvas.Clear()
canvas.Divide(1, 2, 0.01, 0.0)
canvas.cd(1)
mg.Draw("ALP X+")
gPad.SetTopMargin(0.0)
leg.Draw("SAME")
gPad.SetBottomMargin(0.0)
canvas.cd(2)
sysUncertObj.Draw("ALP[]5")
gPad.SetTopMargin(0.0)
gPad.SetBottomMargin(0.1)
primaryObj.Draw("LP")
leg2.Draw("SAME")
if (directory != ""):
canvas.Print("%s_SysUncert_Cmp.pdf" % (objName))
canvas.Print("%s_SysUncert_Cmp.png" % (objName))
canvas.Print("%s_SysUncert_Cmp.C" % (objName))
canvas.Clear()
canvas.Divide(1, 2, 0.01, 0.0)
ratioMg = TMultiGraph()
legRatio = TLegend(2 * legWidth, legHeight, 2 * legWidth,
legHeight)
#RatioArray=[]
# Make, draw ratios
if (bRatioMode):
max_ratio_y = 1.
min_ratio_y = 1.
nPointsFirst = primaryObj.GetN()
bDivisionPossible = True
for lobj in listOfObjs:
if (nPointsFirst != lobj.GetN()):
bDivisionPossible = False
if (bDivisionPossible):
numObjects = 0
for lobj in listOfObjs:
numObjects = numObjects + 1
if (lobj == primaryObj):
print("Avoided TGraph over itself using object")
continue
if (lobj.GetName() == primaryObj.GetName()):
print("Avoided TGraph over itself using name")
continue
if (numObjects == 1):
print("Avoided TGraph over itself using index")
continue
ratioName = "%s_Ratio" % (lobj.GetName())
lRatio = DivideTGraphErrors(lobj, primaryObj,
ratioName)
lRatio.SetTitle("%s / %s" %
(lobj.GetTitle(), fileTitles[0]))
ratioMg.Add(lRatio)
legRatio.AddEntry(lRatio, lRatio.GetTitle(), "LP")
# RatioArray.append(lRatio)
ratioMg.GetYaxis().SetTitle("Ratio over (%s)" %
(fileTitles[0]))
canvas.cd(1)
mg.Draw("ALP X+")
gPad.SetTopMargin(0.0)
leg.Draw("SAME")
gPad.SetBottomMargin(0.0)
canvas.cd(2)
ratioMg.Draw("ALP")
legRatio.Draw("SAME")
if (directory != ""):
canvas.Print("%s_Ratio.pdf" % (objName))
canvas.Print("%s_Ratio.png" % (objName))
canvas.Print("%s_Ratio.C" % (objName))
# for histograms, also draw a plot with each of them
# separately? Useful if the fit functions are visible
if (iObjType == 2): # TH1
primaryObj.Draw()
# if (LogYMode):
# canvas.SetLogy(1)
primaryObj.GetYaxis().UnZoom()
primaryObj.GetXaxis().SetLabelSize(AxisLabelSizeX)
primaryObj.GetYaxis().SetLabelSize(AxisLabelSizeY)
primaryObj.GetXaxis().SetTitleSize(kDefaultTitleSizeX)
primaryObj.GetYaxis().SetTitleSize(kDefaultTitleSizeY)
primaryObj.GetXaxis().SetTitleOffset(kDefaultTitleOffsetX)
primaryObj.GetYaxis().SetTitleOffset(kDefaultTitleOffsetY)
primaryObj.SetMarkerSize(kMarkerSize)
fYMin = GetMinValue(primaryObj)
fYMax = GetMaxValue(primaryObj)
for lobj in listOfObjs:
lobj.SetMarkerSize(kMarkerSize)
lobj.Draw("SAME")
fYMin = min(fYMin, GetMinValue(lobj))
fYMax = max(fYMax, GetMaxValue(lobj))
if (LogYMode != 0):
(fYMin, fYMax) = ExpandRange(fYMin, fYMax)
leg.Draw("SAME")
primaryObj.GetYaxis().SetRangeUser(fYMin, fYMax)
if (LogYMode == 1):
canvas.SetLogy(1)
primaryObj.GetYaxis().UnZoom()
# FIXME temp
# primaryObj.GetXaxis().SetRangeUser(0,25)
# Draw a title
tp = TPaveText(0.3, 0.91, 0.7, 0.99, "NDC")
if (objectTitle == ""):
tp.AddText(objName)
else:
tp.AddText(objectTitle)
tp.Draw("SAME")
if (directory != ""):
canvas.Print("%s_Cmp.pdf" % (objName))
canvas.Print("%s_Cmp.png" % (objName))
canvas.Print("%s_Cmp.C" % (objName))
sysUncertObj = ProduceSystematicFromHists(listOfObjs)
#sysUncertObj.SetName(objName) # This sets the name to be that of the original object
sysUncertObj.SetName("%s_SysErr" %
(objName)) # This adds the label SysErr
totalUncertObj = ProduceTotalErrorHists(primaryObj, sysUncertObj)
totalUncertObj.SetName(objName)
#totalUncertObj.SetName("%s_TotalErr" % (objName))
sysUncertObj.SetFillColor(ROOT.kBlue)
sysUncertObj.SetFillStyle(3002)
#sysUncertObj.Draw("E2")
sysUncertObj.Draw("E4")
primaryObj.Draw("SAME")
leg2.AddEntry(sysUncertObj, "Systematic Uncertainty", "F")
leg2.Draw("SAME")
if (directory != ""):
canvas.Print("%s_SysUncert.pdf" % (objName))
canvas.Print("%s_SysUncert.png" % (objName))
outputFile.Add(sysUncertObj)
outputFile.Add(totalUncertObj)
if (bRatioMode):
max_ratio_y = 1.
min_ratio_y = 1.
nBinsFirst = primaryObj.GetNbinsX()
bDivisionPossible = False
for hobj in listOfObjs:
if (nBinsFirst == hobj.GetNbinsX()):
bDivisionPossible = True
if (bDivisionPossible):
RatioArray = []
#canvas.Divide(1,2,canvSmall,canvSmall)
#canvas.cd(1)
#gPad.SetBottomMargin(small)
#primaryObj.Draw()
# Build the ratios.
# Draw the thing
for lobj in listOfObjs:
lRatio = lobj.Clone("%s_Ratio" % (lobj.GetName()))
if (bBinomialDivision):
lRatio.Divide(lRatio, primaryObj, 1.0, 1.0, "B")
else:
lRatio.Divide(primaryObj)
#lRatio.GetFunction(“myFunction”).SetBit(TF1::kNotDraw)
localRatioMin = lRatio.GetBinContent(
lRatio.GetMinimumBin())
localRatioMax = lRatio.GetBinContent(
lRatio.GetMaximumBin())
if (localRatioMin < min_ratio_y):
min_ratio_y = localRatioMin
if (localRatioMax > max_ratio_y):
max_ratio_y = localRatioMax
RatioArray.append(lRatio)
# magic adjustments to ratio min/max
if (min_ratio_y != 0):
if (max_ratio_y > 1. / min_ratio_y):
min_ratio_y = 1. / max_ratio_y
else:
max_ratio_y = 1. / min_ratio_y
if (max_ratio_y > 20.):
max_ratio_y = 1.3
min_ratio_y = 1.0 / 1.3
#min_ratio_y = pow(min_ratio_y,1.6)
#max_ratio_y = pow(max_ratio_y,1.6)
legRatio = TLegend(legWidth, legHeight, legWidth, legHeight)
RatioArray[0].Draw("HIST E")
RatioArray[0].GetYaxis().SetRangeUser(min_ratio_y, max_ratio_y)
for lRatio in RatioArray:
lRatio.Draw("SAME HIST E")
legRatio.AddEntry(lRatio, lRatio.GetTitle(), "LP")
legRatio.Draw("SAME")
if (directory != ""):
canvas.Print("%s_Ratio.pdf" % (objName))
canvas.Print("%s_Ratio.png" % (objName))
canvas.Print("%s_Ratio.C" % (objName))
# primaryObj.Draw()
# for lobj in listOfObjs:
# lobj.Draw("SAME")
# canvas.Print("Test.pdf")
outputFile.Write()
def MakeCombined(myfile, color, fitInfo):
info = myfile.split("_")
curFile = TFile.Open(myfile,"read")
if not myfile:
print "No File found in MakeCombined"
return
# else:
# curFile.Print()
elasticHdata = curFile.Get("G0")
elasticH = curFile.Get("G1")
inelasticHdata = curFile.Get("G2")
inelasticH = curFile.Get("G3")
canvas = TCanvas('canvas','shouldnotseethis',0,0,1280,720)
canvas.SetLogy()
legend = TLegend(.75,.75,.9,.9)
# title = "SFRESCO fit for initial parameters rC: {}, V_vol: {}, r_vol: {}, d_vol: {}, W_surf: {}, rW_surf: {}, aW_surf: {}".format(info[2],info[3],info[4],info[5],info[6],info[7],info[8][0:2])
title = "Final parameters rC: {}, V_vol: {}, r_vol: {}, d_vol: {}, W_surf: {}, rW_surf: {}, aW_surf: {}".format(fitInfo[1],fitInfo[2],fitInfo[3],fitInfo[4],fitInfo[5],fitInfo[6],fitInfo[7])
Dummy = ROOT.TH2F("Dummy","tmptitle",90,10,90,1000000,0,10000)
Dummy.SetTitle(title)
Dummy.GetXaxis().SetTitle("COM Angle in Degrees")
Dummy.GetYaxis().SetTitle("Cross Section in mb/sr")
Dummy.SetStats(ROOT.kFALSE)
Dummy.Draw()
Dummy.SetAxisRange(10,80,"X")
Dummy.SetAxisRange(.0001,1000,"Y")
graphOptions="sameP"
# elasticColor = ROOT.kRed
if elasticHdata:
# elasticHdata.SetMarkerColor(color)
# elasticHdata.SetLineColor(color)
# elasticHdata.SetFillColor(color)
elasticHdata.SetMarkerStyle(20)
elasticHdata.Draw(graphOptions)
legend.AddEntry(elasticHdata,"Elastic")
else:
print "No elasticH in Draw()"
if elasticH:
elasticH.SetMarkerColor(color)
elasticH.SetLineColor(color)
elasticH.SetFillColor(color)
# elasticH.SetMarkerStyle(20)
elasticH.SetLineWidth(5)
elasticH.Draw("sameL")
# inelasticColor = ROOT.kBlue
#
# if inelasticHdata:
# inelasticHdata.SetMarkerColor(inelasticColor)
# inelasticHdata.SetLineColor(inelasticColor)
# inelasticHdata.SetFillColor(inelasticColor)
# inelasticHdata.SetMarkerStyle(20)
# legend.AddEntry(inelasticHdata,"Inelastic")
# inelasticHdata.Draw(graphOptions)
#
# if inelasticH:
# inelasticH.SetMarkerColor(inelasticColor)
# inelasticH.SetLineColor(inelasticColor)
# inelasticH.SetFillColor(inelasticColor)
# #inelasticH.SetMarkerStyle(20)
# inelasticH.Draw("sameL")
legend.Draw()
saveName = "outputs/special_{}_{}_{}_{}_{}_{}_{}.png".format(info[2],info[3],info[4],info[5],info[6],info[7],info[8][0:2])
canvas.SaveAs(saveName)
def DrawScatRatio(graph1, graph2, ratio, name1, name2, fname): #, grid):
c = TCanvas("c", "c", 800, 800)
# Upper histogram plot is pad1
p1 = TPad("p1", "p1", 0, 0.3, 1, 1.0)
p1.SetBottomMargin(0) # joins upper and lower plot
p1.Draw()
# Lower ratio plot is pad 2
c.cd() # returns to main canvas before defining pad2
p2 = TPad("p2", "p2", 0, 0.05, 1, 0.3)
p2.SetTopMargin(0) # joins upper and lower plot
p2.SetBottomMargin(0.2)
# p2.SetGridx()
p2.Draw()
# Now draw
p1.cd()
leg = TLegend(0.69, 0.89, 0.69, 0.89)
leg.AddEntry(graph1, name1)
leg.AddEntry(graph2, name2)
leg.SetBorderSize(0)
graph1.SetTitle("")
graph1.GetXaxis().SetRangeUser(-1, 501)
graph1.GetYaxis().SetTitle("Tracks passing quality cuts")
# graph1.GetYaxis().SetTitleSize(20) # .04)
graph1.GetYaxis().SetTitleOffset(1.25)
graph1.GetYaxis().CenterTitle(1)
graph1.SetMarkerStyle(20) # Full circle
graph2.SetMarkerStyle(24) # Open circle
graph1.Draw("AP")
graph2.Draw("P SAME")
leg.Draw("same")
# to avoid clipping the bottom zero, redraw a small axis
# ratio.GetYaxis().SetLabelSize(15) # SetLabelSize(.05)
# axis = TGaxis(-5, 20, -5, 220, 20, 220, 510, "")
# axis.SetLabelFont(43)
# axis.SetLabelSize(15)
p2.cd()
# Sort out y-axis\
ratio.SetTitle("") # ;test;test")
y2 = ratio.GetYaxis()
y2.SetTitle("Ratio")
y2.CenterTitle(1)
y2.SetTitleOffset(1.75)
y2.SetTitleSize(20)
y2.SetTitleFont(43)
y2.SetLabelFont(43)
y2.SetLabelSize(15)
y2.SetNdivisions(6)
# Sort x-axis
x2 = ratio.GetXaxis()
x2.SetTitle("Lock low DCA threshold [#mum]")
x2.CenterTitle(1)
x2.SetTitleSize(20) #)
x2.SetTitleFont(43)
x2.SetRangeUser(-1, 501)
x2.SetTitleOffset(3.5)
x2.SetLabelFont(43)
x2.SetLabelSize(15)
ratio.SetLineColor(2)
ratio.SetMarkerColor(2)
ratio.SetMarkerStyle(24)
ratio.Draw("AP")
c.SaveAs(fname + ".pdf")
c.SaveAs(fname + ".C")
return
def plotDataMC(args, plot_mu, plot_el):
hCanvas = TCanvas("hCanvas", "Distribution", 800, 800)
if args.ratio:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
setTDRStyle()
plotPad.UseCurrentStyle()
ratioPad.UseCurrentStyle()
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
setTDRStyle()
plotPad.UseCurrentStyle()
plotPad.Draw()
plotPad.cd()
# Data load processes
colors = createMyColors()
if args.use2016:
data = Process(Data2016, normalized=True)
elif args.use2018:
data = Process(Data2018, normalized=True)
else:
data = Process(Data, normalized=True)
eventCounts_mu = totalNumberOfGeneratedEvents(path, plot_mu.muon)
eventCounts_el = totalNumberOfGeneratedEvents(path, plot_el.muon)
negWeights_mu = negWeightFractions(path, plot_mu.muon)
negWeights_el = negWeightFractions(path, plot_el.muon)
#print negWeights
# Background load processes
backgrounds = copy(args.backgrounds)
'''if plot_mu.useJets:
if "Wjets" in backgrounds:
backgrounds.remove("Wjets")
backgrounds.insert(0,"Jets")'''
processes_mu = []
processes_el = []
for background in backgrounds:
if args.use2016:
if background == "Jets":
processes_mu.append(
Process(getattr(Backgrounds2016, background),
eventCounts_mu,
negWeights_mu,
normalized=True))
processes_el.append(
Process(getattr(Backgrounds2016, background),
eventCounts_el,
negWeights_el,
normalized=True))
else:
processes_mu.append(
Process(getattr(Backgrounds2016, background),
eventCounts_mu, negWeights_mu))
processes_el.append(
Process(getattr(Backgrounds2016, background),
eventCounts_el, negWeights_el))
else:
if background == "Jets":
processes_mu.append(
Process(getattr(Backgrounds, background),
eventCounts_mu,
negWeights_mu,
normalized=True))
processes_el.append(
Process(getattr(Backgrounds, background),
eventCounts_el,
negWeights_el,
normalized=True))
else:
processes_mu.append(
Process(getattr(Backgrounds, background), eventCounts_mu,
negWeights_mu))
processes_el.append(
Process(getattr(Backgrounds, background), eventCounts_el,
negWeights_el))
'''# Signal load processes
signals = []
for signal in args.signals:
if args.use2016:
if args.ADD: signals.append(Process(getattr(Signals2016ADD, signal), eventCounts, negWeights))
else: signals.append(Process(getattr(Signals2016,signal),eventCounts,negWeights))
else:
if args.ADD: signals.append(Process(getattr(SignalsADD, signal), eventCounts, negWeights))
else: signals.append(Process(getattr(Signals,signal),eventCounts,negWeights))
'''
legend = TLegend(0.55, 0.75, 0.925, 0.925)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextFont(42)
'''legendEta = TLegend(0.35, 0.55, 0.9, 0.9)
legendEta.SetFillStyle(0)
legendEta.SetBorderSize(0)
legendEta.SetTextFont(42)
legendEta.SetNColumns(2)
'''
latex = ROOT.TLatex()
latex.SetTextFont(42)
latex.SetTextAlign(31)
latex.SetTextSize(0.04)
latex.SetNDC(True)
latexCMS = ROOT.TLatex()
latexCMS.SetTextFont(61)
latexCMS.SetTextSize(0.06)
latexCMS.SetNDC(True)
latexCMSExtra = ROOT.TLatex()
latexCMSExtra.SetTextFont(52)
latexCMSExtra.SetTextSize(0.045)
latexCMSExtra.SetNDC(True)
legendHists = []
# Modify legend information
legendHistData = ROOT.TH1F()
if args.data:
legend.AddEntry(legendHistData, "Data", "pe")
legendEta.AddEntry(legendHistData, "Data", "pe")
for process in reversed(processes_mu):
if not plot_mu.muon and "#mu^{+}#mu^{-}" in process.label:
process.label = process.label.replace("#mu^{+}#mu^{-}",
"e^{+}e^{-}")
process.theColor = ROOT.kBlue
process.theLineColor = ROOT.kBlue
temphist = ROOT.TH1F()
temphist.SetFillColor(process.theColor)
legendHists.append(temphist.Clone)
legend.AddEntry(temphist, process.label, "f")
#legendEta.AddEntry(temphist,process.label,"f")
for process in reversed(processes_el):
if not plot_el.muon and "#mu^{+}#mu^{-}" in process.label:
process.label = process.label.replace("#mu^{+}#mu^{-}",
"e^{+}e^{-}")
process.theColor = ROOT.kRed
process.theLineColor = ROOT.kRed
temphist = ROOT.TH1F()
temphist.SetFillColor(process.theColor)
legendHists.append(temphist.Clone)
legend.AddEntry(temphist, process.label, "f")
#legendEta.AddEntry(temphist,process.label,"f")
'''if args.signals !=0:
processesWithSignal = []
for process in processes:
processesWithSignal.append(process)
for Signal in signals:
processesWithSignal.append(Signal)
temphist = ROOT.TH1F()
temphist.SetFillColor(Signal.theColor)
temphist.SetLineColor(Signal.theLineColor)
legendHists.append(temphist.Clone)
legend.AddEntry(temphist,Signal.label,"l")
legendEta.AddEntry(temphist,Signal.label,"l")
'''
# Modify plot pad information
nEvents = -1
ROOT.gStyle.SetOptStat(0)
intlumi = ROOT.TLatex()
intlumi.SetTextAlign(12)
intlumi.SetTextSize(0.045)
intlumi.SetNDC(True)
intlumi2 = ROOT.TLatex()
intlumi2.SetTextAlign(12)
intlumi2.SetTextSize(0.07)
intlumi2.SetNDC(True)
scalelabel = ROOT.TLatex()
scalelabel.SetTextAlign(12)
scalelabel.SetTextSize(0.03)
scalelabel.SetNDC(True)
metDiffLabel = ROOT.TLatex()
metDiffLabel.SetTextAlign(12)
metDiffLabel.SetTextSize(0.03)
metDiffLabel.SetNDC(True)
chi2Label = ROOT.TLatex()
chi2Label.SetTextAlign(12)
chi2Label.SetTextSize(0.03)
chi2Label.SetNDC(True)
hCanvas.SetLogy()
# Luminosity information
plotPad.cd()
plotPad.SetLogy(0)
logScale = plot_mu.log
if logScale == True:
plotPad.SetLogy()
if args.use2016:
lumi_el = 35.9 * 1000
lumi_mu = 36.3 * 1000
elif args.use2018:
lumi_el = 59.97 * 1000
lumi_mu = 61.608 * 1000
else:
lumi_el = 41.529 * 1000
lumi_mu = 42.135 * 1000
if args.use2016:
zScaleFac_mu = zScale2016["muons"]
zScaleFac_el = zScale2016["electrons"]
elif args.use2018:
zScaleFac_mu = zScale2018["muons"]
zScaleFac_el = zScale2018["electrons"]
else:
zScaleFac_mu = zScale["muons"]
zScaleFac_el = zScale["electrons"]
# Data and background loading
'''if plot.plot2D:
datahist = data.loadHistogramProjected(plot,lumi,zScaleFac)
stack = TheStack2D(processes,lumi,plot,zScaleFac)
else:
datahist = data.loadHistogram(plot,lumi,zScaleFac)
stack = TheStack(processes,lumi,plot,zScaleFac)
'''
lumi_mu = 1.0 * 1000
lumi_el = 1.0 * 1000
datahist = data.loadHistogram(plot_mu, lumi_mu, zScaleFac_mu)
stackmu = TheStack(processes_mu, lumi_mu, plot_mu, zScaleFac_mu)
stackel = TheStack(processes_el, lumi_el, plot_el, zScaleFac_el)
# call hist in stack by: for h in stackmu.theStack.GetHists()
#muheight = stackmu.theHistogram.FindBin(90)
#print "Z height in mu: %.3f, %.3f"%(stackmu.theHistogram.GetBinContent(muheight), stackel.theHistogram.GetBinContent(muheight))
if args.znorm:
muheight = stackmu.theHistogram.FindBin(90)
print "Z height of mu: %d +- %d" % (stackmu.theHistogram.GetBinCenter(
muheight), stackmu.theHistogram.GetBinWidth(muheight))
print "Z height of mu: %d" % (
stackmu.theHistogram.GetBinContent(muheight))
elheight = stackel.theHistogram.FindBin(90)
print "Z height of el: %d +- %d" % (stackel.theHistogram.GetBinCenter(
elheight), stackel.theHistogram.GetBinWidth(elheight))
print "Z height of el: %d" % (
stackel.theHistogram.GetBinContent(elheight))
znum = stackmu.theHistogram.GetBinContent(muheight)
print znum
for h in stackmu.theStack.GetHists():
h.Scale(1. / znum)
for h in stackel.theStack.GetHists():
h.Scale(1. / znum)
stackmu.theHistogram.Scale(1. / znum)
stackel.theHistogram.Scale(1. / znum)
if args.ae:
year = 2017
if args.use2018: year = 2018
for h in stackmu.theStack.GetHists():
inverseAE(h, plot_mu, year)
for h in stackel.theStack.GetHists():
inverseAE(h, plot_el, year)
inverseAE(stackmu.theHistogram, plot_mu, year)
inverseAE(stackel.theHistogram, plot_el, year)
if args.data:
yMax = datahist.GetBinContent(datahist.GetMaximumBin())
if "Mass" in plot.fileName:
yMin = 0.00001
else:
yMin = 0.01
xMax = datahist.GetXaxis().GetXmax()
xMin = datahist.GetXaxis().GetXmin()
else:
yMax = stackmu.theHistogram.GetBinContent(datahist.GetMaximumBin())
yMin = 0.01
xMax = stackmu.theHistogram.GetXaxis().GetXmax()
xMin = stackmu.theHistogram.GetXaxis().GetXmin()
if plot_mu.yMax == None:
if logScale:
yMax = yMax * 10000
else:
yMax = yMax * 1.5
else:
yMax = plot_mu.yMax
if "Mass" in plot_mu.fileName:
yMax = 20000000
if not plot_mu.yMin == None:
yMin = plot_mu.yMin
if not plot_mu.xMin == None:
xMin = plot_mu.xMin
if not plot_mu.xMax == None:
xMax = plot_mu.xMax
#if args.ADD and args.use2016:
# xMin = 1700
# xMax = 4000
# yMax = 1.0
#if "CosThetaStarBBM1800" in plot.fileName:
# yMax = 3
#print xMin, xMax, yMin, yMax
'''xMin = 70
xMax = 4000
yMin = 0.00001
yMax = 20000000'''
yMin = 0.00001 / 40
yMax = 200000000.0 / 40
if args.ae: xMin = 200
if args.znorm:
yMin /= 300
yMax /= 300
plotPad.DrawFrame(
xMin, yMin, xMax, yMax,
"; %s ; %s" % ("m(l^{+}l^{-}) [GeV]", "d#sigma(pp#rightarrow ll)"))
drawStack_mu = stackmu
drawStack_el = stackel
#~ print datahist.Integral(datahist.FindBin(60),datahist.FindBin(120))/drawStack.theHistogram.Integral(drawStack.theHistogram.FindBin(60),drawStack.theHistogram.FindBin(120))
#~ low = 900
#~ high = 1300
#~ print datahist.Integral(datahist.FindBin(low),datahist.FindBin(high))
#~ print drawStack.theHistogram.Integral(datahist.FindBin(low),datahist.FindBin(high))
# Draw background from stack
drawStack_mu.theStack.Draw("same hist")
drawStack_el.theStack.Draw("same hist")
'''# Draw signal information
if len(args.signals) != 0:
signalhists = []
for Signal in signals:
if plot.plot2D: # plot collins-soper angle
signalhist = Signal.loadHistogramProjected(plot,lumi, zScaleFac)
signalhist.SetLineWidth(2)
signalBackgrounds = deepcopy(backgrounds)
signalBackgrounds.remove("DrellYan")
signalProcesses = []
for background in signalBackgrounds:
if background == "Jets":
signalProcesses.append(Process(getattr(Backgrounds,background),eventCounts,negWeights,normalized=True))
else:
signalProcesses.append(Process(getattr(Backgrounds,background),eventCounts,negWeights))
signalStack = TheStack2D(signalProcesses,lumi,plot, zScaleFac)
signalhist.Add(signalStack.theHistogram)
signalhist.SetMinimum(0.1)
signalhist.Draw("samehist")
signalhists.append(signalhist)
else:
signalhist = Signal.loadHistogram(plot,lumi,zScaleFac)
signalhist.SetLineWidth(2)
signalBackgrounds = deepcopy(backgrounds)
signalBackgrounds.remove("DrellYan") # signalBackgrounds = ["Jets", "Other"]
signalProcesses = []
for background in signalBackgrounds:
if background == "Jets":
signalProcesses.append(Process(getattr(Backgrounds,background),eventCounts,negWeights,normalized=True))
else:
signalProcesses.append(Process(getattr(Backgrounds,background),eventCounts,negWeights))
signalStack = TheStack(signalProcesses,lumi,plot,zScaleFac)
signalhist.Add(signalStack.theHistogram)
signalhist.SetMinimum(0.0001)
signalhist.Draw("samehist")
signalhists.append(signalhist)
'''
# Draw data
datahist.SetMinimum(0.0001)
#if args.data:
# datahist.Draw("samep")
# Draw legend
if "Eta" in plot_mu.fileName or "CosTheta" in plot_mu.fileName:
legendEta.Draw()
else:
legend.Draw()
plotPad.SetLogx(plot_mu.logX)
latex.DrawLatex(
0.95, 0.96,
"%.3f fb^{-1} (13 TeV, #mu#mu), %.3f fb^{-1} (13 TeV, ee)" %
(lumi_mu * 0.001, lumi_el * 0.001))
yLabelPos = 0.85
cmsExtra = "Private Work"
if not args.data:
cmsExtra = "#splitline{Private Work}{Simulation}"
yLabelPos = 0.82
latexCMS.DrawLatex(0.19, 0.89, "CMS")
latexCMSExtra.DrawLatex(0.19, yLabelPos, "%s" % (cmsExtra))
#~ print datahist.Integral()
if args.ratio:
try:
ratioPad.cd()
ratioPad.SetLogx(plot_mu.logX)
except AttributeError:
print("Plot fails. Look up in errs/failedPlots.txt")
outFile = open("errs/failedPlots.txt", "a")
outFile.write('%s\n' % plot_mu.filename %
("_" + run.label + "_" + dilepton))
outFile.close()
plot_mu.cuts = baseCut
return 1
#ratioGraphs = ratios.RatioGraph(drawStack_mu.theStack.GetHists()[0], drawStack_el.theStack.GetHists()[0], xMin=xMin, xMax=xMax,title="R_{#mu#mu/ee}",yMin=0.0,yMax=2,ndivisions=10,color=ROOT.kBlack,adaptiveBinning=10000)
#setRatioError(ratioGraphs, drawStack_mu.theHistogram, drawStack_el.theHistogram)
#ratioGraphs.draw(ROOT.gPad,True,False,True,chi2Pos=0.8)
hhmu = drawStack_mu.theHistogram
hhel = drawStack_el.theHistogram
ratioGraphs = ROOT.TGraphAsymmErrors(hhmu.GetSize() - 2)
chann = True if "BB" in plot_mu.fileName else False
for i in range(1, hhmu.GetSize() - 1):
xval = hhmu.GetBinCenter(i)
xerr = hhmu.GetBinWidth(i) / 2
if hhel.GetBinContent(i) == 0: continue
if hhel.GetBinContent(i) < 0 or hhmu.GetBinContent(i) < 0: continue
yval = hhmu.GetBinContent(i) * 1.0 / hhel.GetBinContent(i)
#if yval > 10: continue
yerr = yval * math.sqrt(
getMuErr(xval, chann, args.znorm)**2 +
getElErr(xval, chann, args.znorm)**2)
ratioGraphs.SetPoint(i, xval, yval)
ratioGraphs.SetPointError(i, xerr, xerr, yerr, yerr)
nBinsX = 20
nBinsY = 10
hAxis = ROOT.TH2F("hAxis", "", nBinsX, xMin, xMax, nBinsY, 0.0, 4.0)
hAxis.Draw("AXIS")
hAxis.GetYaxis().SetNdivisions(408)
hAxis.SetTitleOffset(0.4, "Y")
hAxis.SetTitleSize(0.15, "Y")
hAxis.SetYTitle("R_{#mu#mu/ee}")
hAxis.GetXaxis().SetLabelSize(0.0)
hAxis.GetYaxis().SetLabelSize(0.15)
hAxis.SetTitleSize(0.15, "Y")
#binMerging = [-1]
oneLine = ROOT.TLine(xMin, 1.0, xMax, 1.0)
oneLine.SetLineStyle(2)
oneLine.Draw()
ratioGraphs.SetFillColor(6)
ratioGraphs.SetFillStyle(3002)
#ratioGraphs.Draw("SAMEpZ4")
ratioGraphs.Draw("same p")
ratioPad.Update()
ROOT.gPad.RedrawAxis()
plotPad.RedrawAxis()
if args.ratio:
ratioPad.RedrawAxis()
if not os.path.exists("lepFlavor"):
os.makedirs("lepFlavor")
if args.use2016: year = "2016"
elif args.use2018: year = "2018"
else: year = "2017"
if args.ae: year += "_inverseAE"
if args.znorm: year += "_znorm"
hCanvas.Print("lepFlavor/%s_%s_other.pdf" % (plot_mu.fileName, year))
f_l2.SetMaximum(max_y+a)
f_l3.SetMaximum(max_y+a)
f_l4.SetMaximum(max_y+a)
f_l1.Draw("lsame")
f_l2.Draw("lsame")
f_l3.Draw("lsame")
f_l4.Draw("lsame")
lb.SetNDC(kTRUE)
lb.SetTextSize(0.025)
lb.SetTextAlign(13)
lb.DrawLatex(0.5, 0.55, "MP L1 = "+str(MP_l1)+"#pm"+str(MPe_l1))
lb.DrawLatex(0.5, 0.50, "MP L2 = "+str(MP_l2)+"#pm"+str(MPe_l2))
lb.DrawLatex(0.5, 0.45, "MP L3 = "+str(MP_l3)+"#pm"+str(MPe_l3))
lb.DrawLatex(0.5, 0.40, "MP L4 = "+str(MP_l4)+"#pm"+str(MPe_l4))
leg.Draw()
gPad.RedrawAxis()
c.SaveAs(plotdir+"barrel_summary_"+var+"_"+fill"_.pdf"))
#c.Update()
#c.Clear()
c2 = TCanvas('c2', 'c2', 800, 640)
leg2 = TLegend(0.60,0.90,0.90, 0.70)
leg2.SetBorderSize(0)
leg2.SetFillColor(10)
leg2.SetLineColor(10)
leg2.SetLineWidth(0)
if var == "norm_charge":
f_d1 = fitting(h_d1)
def plotFailedHoMatchesNoTrg():
c = TCanvas("cFailedHoMatchesNoTrg", "cFailedHoMatchesNoTrg", 1200, 1200)
c.cd().SetRightMargin(0.25)
c.cd().SetLeftMargin(0.08)
#legend
legend = TLegend(0.75, 0.8, 0.99, 0.9)
#Graph for in events not in geometric acceptance
grNotInGaNC = file.Get("hoMuonAnalyzer/graphs/NoTrgTdmiNotInGA")
grNotInGa = PlotStyle.convertToHcalCoords(grNotInGaNC)
grNotInGa.GetYaxis().SetTitle("i#phi / a.u.")
grNotInGa.GetXaxis().SetTitle("i#eta / a.u.")
grNotInGa.GetYaxis().SetTitleFont(62)
grNotInGa.GetYaxis().SetLabelFont(62)
grNotInGa.SetMarkerStyle(6)
grNotInGa.SetMarkerColor(PlotStyle.colorRwthDarkBlue)
grNotInGa.SetTitle(
"#eta #phi plot failed HO matches in no Single #mu Trg. events")
grNotInGa.Draw("AP")
#Graph of events with HO match below threshold
grHoBelowThrNC = file.Get("hoMuonAnalyzer/graphs/NoTrgTdmiBelowThr")
grHoBelowThr = PlotStyle.convertToHcalCoords(grHoBelowThrNC)
grHoBelowThr.SetMarkerStyle(20)
grHoBelowThr.SetMarkerSize(1.2)
grHoBelowThr.SetMarkerColor(PlotStyle.colorRwthGruen)
grHoBelowThr.Draw("samep")
#Graph for events where HO matching failed
grHoMatchFailNC = file.Get("hoMuonAnalyzer/graphs/NoTrgHoMatchFail")
grHoMatchFail = None
nNotMatching = 0
if not grHoMatchFailNC == None:
grHoMatchFail = PlotStyle.convertToHcalCoords(grHoMatchFailNC)
grHoMatchFail.SetMarkerStyle(21)
grHoMatchFail.SetMarkerSize(1)
grHoMatchFail.SetMarkerColor(PlotStyle.colorRwthRot)
grHoMatchFail.Draw("samep")
legend.AddEntry(grHoMatchFail, 'HO match fail', 'p')
nNotMatching = grHoMatchFail.GetN()
#Draw chimneys
chimney1Converted = PlotStyle.convertToHcalCoords(PlotStyle.chimney1)
chimney2Converted = PlotStyle.convertToHcalCoords(PlotStyle.chimney2)
chimney1Converted.SetLineColor(PlotStyle.colorRwthMagenta)
chimney2Converted.SetLineColor(PlotStyle.colorRwthMagenta)
chimney1Converted.Draw('same')
chimney2Converted.Draw('same')
#cms private label
label = TPaveText(
PlotStyle.getLabelCmsPrivateSimulation(x1ndc=0.5, x2ndc=0.75))
label.Draw()
#create extra marker for the legend
marker = TMarker(1, 1, 2)
marker.SetMarkerSize(3)
marker.SetMarkerColor(PlotStyle.colorRwthDarkBlue)
legend.AddEntry(chimney2Converted, "chimney", "l")
legend.AddEntry(marker, 'Not in GA', 'p')
legend.AddEntry(grHoBelowThr, 'HO match < 0.2 GeV', 'p')
legend.Draw()
nNotInGa = grNotInGa.GetN()
nBelowThr = grHoBelowThr.GetN()
nTotal = nNotMatching + nNotInGa + nBelowThr
print 80 * '#'
print 'Not Matching:\t%5d/%d\t=> %5.2f%% +- %f%%' % (
nNotMatching, nTotal, nNotMatching / float(nTotal) * 100,
PlotStyle.calcSigma(nNotMatching, float(nTotal)))
print 'Not in GA:\t%5d/%d\t=> %5.2f%% +- %f%%' % (
nNotInGa, nTotal, nNotInGa / float(nTotal) * 100,
PlotStyle.calcSigma(nNotInGa, float(nTotal)))
print 'Below Thr:\t%5d/%d\t=> %5.2f%% +- %f%%' % (
nBelowThr, nTotal, nBelowThr / float(nTotal) * 100,
PlotStyle.calcSigma(nBelowThr, float(nTotal)))
print 80 * '#'
c.Update()
c.SaveAs('plots/graphsEtaPhi/gNoTrgHoMatchingFailed.png')
c.SaveAs('plots/graphsEtaPhi/gNoTrgHoMatchingFailed.pdf')
return c, grNotInGa, label, chimney1Converted, chimney2Converted, legend, grHoMatchFail, grHoBelowThr
#Drawing the graphs
c2=TCanvas()
c2.Divide(2,2,.01,.01,0)
c2.cd(1)
l2=TLegend(.3,.2)
l2.AddEntry(g2,"Uncorrected","l")
l2.AddEntry(b2,"Background","l")
l2.AddEntry(cor2,"Corrected by Event","l")
g2.ProfileX().Draw()
b2.SetLineColor(2)
b2.ProfileX().Draw("same")
cor2.SetLineColor(3)
cor2.ProfileX().Draw("same")
l2.Draw("same")
c2.cd(2)
l3=TLegend(.3,.2)
l3.AddEntry(g3,"Uncorrected","l")
l3.AddEntry(b3,"Background","l")
l3.AddEntry(cor3,"Corrected by Event","l")
g3.ProfileX().Draw()
b3.SetLineColor(2)
b3.ProfileX().Draw("same")
cor3.SetLineColor(3)
cor3.ProfileX().Draw("same")
l3.Draw("same")
c2.cd(3)
l4=TLegend(.3,.2)
legEff.AddEntry(hEffPrompt[5], 'FONLL #times MC@sHQ-EPOS2', 'p')
lineatone = TLine(0., 1., 36., 1.)
lineatone.SetLineWidth(2)
lineatone.SetLineStyle(9)
lineatone.SetLineColor(kBlack)
cShapes = TCanvas('cShapes', '', 1000, 500)
cShapes.Divide(2, 1)
cShapes.cd(1).DrawFrame(0, 1.e-8, 36, 1., ';#it{p}_{T} GeV/#it{c}; d#it{N}/d#it{p}_{T} (a. u.)')
cShapes.cd(1).SetLogy()
for iShape, _ in enumerate(hPtShapes):
hPtShapes[iShape].SetLineWidth(2)
hPtShapes[iShape].SetLineColor(colors[iShape])
hPtShapes[iShape].Draw('chistsame')
leg.Draw()
cShapes.cd(2).DrawFrame(0, 1.e-3, 36, 1.e+1, ';#it{p}_{T} GeV/#it{c}; #it{p}_{T} weights')
cShapes.cd(2).SetLogy()
lineatone.Draw('same')
for iShape, _ in enumerate(hPtWeights):
hPtWeights[iShape].Draw('chistsame')
hPtWeights[iShape].SetLineWidth(2)
hPtWeights[iShape].SetLineColor(colors[iShape+1])
cShapes.SaveAs(outFilePtWeightsName)
if inFileEffNames and len(inFileEffNames) == len(PtShapes):
ptmin = hEffPrompt[0].GetBinLowEdge(1)
ptmax = hEffPrompt[0].GetBinLowEdge(hEffPrompt[0].GetNbinsX(
))+hEffPrompt[0].GetBinWidth(hEffPrompt[0].GetNbinsX())
cEff = TCanvas('cEff', '', 1000, 500)
def plot(path, leg_title, ecms, xmin, xmax, xbins):
try:
f_data = TFile(path[0])
t_data = f_data.Get('save')
entries_data = t_data.GetEntries()
logging.info('data entries :' + str(entries_data))
except:
logging.error(path[0] + 'is invalid!')
sys.exit()
try:
f_side1 = TFile(path[1])
t_side1 = f_side1.Get('save')
entries_side1 = t_side1.GetEntries()
logging.info('data(side1) entries :' + str(entries_side1))
except:
logging.error(path[1] + ' is invalid!')
sys.exit()
try:
f_side2 = TFile(path[2])
t_side2 = f_side2.Get('save')
entries_side2 = t_side2.GetEntries()
logging.info('data(side2) entries :' + str(entries_side2))
except:
logging.error(path[2] + ' is invalid!')
sys.exit()
try:
f_side3 = TFile(path[3])
t_side3 = f_side3.Get('save')
entries_side3 = t_side3.GetEntries()
logging.info('data(side3) entries :' + str(entries_side3))
except:
logging.error(path[3] + ' is invalid!')
sys.exit()
try:
f_side4 = TFile(path[4])
t_side4 = f_side4.Get('save')
entries_side4 = t_side4.GetEntries()
logging.info('data(side4) entries :' + str(entries_side4))
except:
logging.error(path[4] + ' is invalid!')
sys.exit()
mbc = TCanvas('mbc', 'mbc', 800, 600)
set_canvas_style(mbc)
content = int((xmax - xmin) / xbins * 1000)
ytitle = 'Entries/%.1f MeV' % content
xtitle = 'RM(#pi^{+}_{0}#pi^{-}_{0})(GeV)'
h_data = TH1F('data', 'data', xbins, xmin, xmax)
set_histo_style(h_data, xtitle, ytitle, 1, -1)
rm_pipi_fill(t_data, h_data)
h_side1 = TH1F('side1', 'side1', xbins, xmin, xmax)
set_histo_style(h_side1, xtitle, ytitle, 3, 3004)
rm_pipi_fill(t_side1, h_side1)
h_side2 = TH1F('side2', 'side2', xbins, xmin, xmax)
set_histo_style(h_side2, xtitle, ytitle, 3, 3004)
rm_pipi_fill(t_side2, h_side2)
h_side3 = TH1F('side3', 'side3', xbins, xmin, xmax)
set_histo_style(h_side3, xtitle, ytitle, 3, 3004)
rm_pipi_fill(t_side3, h_side3)
h_side4 = TH1F('side4', 'side4', xbins, xmin, xmax)
set_histo_style(h_side4, xtitle, ytitle, 3, 3004)
rm_pipi_fill(t_side4, h_side4)
h_side1.Add(h_side2)
h_side1.Scale(0.5)
h_side3.Add(h_side4)
h_side3.Scale(0.35)
h_side1.Add(h_side3, -1)
h_data.Draw('E1')
hs = THStack('hs', 'Stacked')
hs.Add(h_side1)
hs.Draw('same')
h_data.Draw('sameE1')
legend = TLegend(0.55, 0.65, 0.8, 0.85)
set_legend(legend, h_data, h_side1, leg_title)
legend.Draw()
if not os.path.exists('./figs/'):
os.makedirs('./figs/')
mbc.SaveAs('./figs/rm_pipi_' + str(ecms) + '.pdf')
raw_input('Enter anything to end...')
def MCSPlot(self, pname):
#print self.fname
f = TFile(self.fname)
self.RMS = {}
self.RMSErr = {}
self.Chi2 = {}
self.RMSsysdiff = {}
self.RMSsyserr = {}
# create a plot for each histvarname
for histvar in self.histvarnames:
self.RMS[histvar] = {}
self.RMSErr[histvar] = {}
self.RMSsysdiff[histvar] = {}
self.RMSsyserr[histvar] = {}
self.Chi2[histvar] = {}
names = [histvar + '_' + x for x in self.histstatenames]
print names
hists = [f.Get(histvar + '_' + x) for x in self.histstatenames]
print hists[0]
hists[0].SetTitle("")
# hists[3].Scale(norm)
# self.formatHist(hist[0], 0)
resplots = [x.Clone() for x in hists]
resplots[0].SetTitle('')
resplots[0].GetYaxis().SetTitle("Normalized Residuals")
# if histvar == 'thetaScatt':
leg = TLegend(0.55, 0.73, 0.89, 0.92)
leg.SetLineColor(10)
# else:
# leg = TLegend(0.35,0.2,0.65,0.5)
for i in range(len(self.histstatedesc)):
hists[i].Sumw2()
if histvar == 'theta2Scatt':
hists[i].Rebin(8)
resplots[i].Rebin(8)
elif histvar == 'thetaScatt':
hists[i].Rebin(1)
resplots[i].Rebin(1)
else:
hists[i].Rebin(1)
resplots[i].Rebin(1)
self.formatHists(hists[i], i)
self.formatHists(resplots[i], i)
self.addToRMS(i, hists[i], hists[0], resplots[i], histvar)
if histvar == 'theta2Scatt':
hists[i].GetYaxis().SetTitle('Probability per ' + str(
round(1000 * 1000 *
hists[i].GetXaxis().GetBinWidth(4), 2)) +
' mrad^{2}')
else:
hists[i].GetYaxis().SetTitle('Probability per ' + str(
round(1000 * hists[i].GetXaxis().GetBinWidth(4), 2)) +
' mrad')
leg.AddEntry(hists[i], self.histstatedesc[i], self.histopts[i])
#print hists[0]
self.calculateChi2(i, hists[i], hists[0], resplots[i], histvar,
pname)
c = TCanvas(self.fname[:-5] + '_' + histvar + '_c1')
if self.desc[0] == 'XePion':
t1 = TText(0.18, 0.885, "MICE ISIS cycle 2015/03")
t2 = TText(0.18, 0.85,
"Xe, " + self.desc[1][2:5] + ", MAUS v3.1.2")
else:
t1 = TText(0.18, 0.885, "MICE ISIS cycle 2015/04")
t2 = TText(0.18, 0.85,
"LiH, " + self.desc[1][2:5] + ", MAUS v3.1.2")
t1.SetNDC(1)
t1.SetTextSize(0.04)
t1.SetTextFont(42)
t2.SetNDC(1)
t2.SetTextSize(0.03)
t2.SetTextFont(42)
hists[0].GetYaxis().SetRangeUser(4e-4, 2.0)
hists[0].SetTitle(";" + hists[0].GetXaxis().GetTitle() +
" (radians);" + hists[0].GetYaxis().GetTitle())
hists[0].Draw('ep')
c.SetBottomMargin(0.15)
c.SetTopMargin(0.075)
for h in hists[1:len(self.histstatedesc)]:
h.Draw('epsame')
leg.SetTextSize(0.04)
leg.Draw('same')
t1.Draw()
t2.Draw()
c.SetLogy()
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys.eps')
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys.root')
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys_pq.jpg')
c.Clear()
c.SetLogy(0)
resplots[0].GetYaxis().SetRangeUser(-2, 2)
resplots[0].SetTitle(";" + resplots[0].GetXaxis().GetTitle() +
" (radians);" +
resplots[0].GetYaxis().GetTitle())
leg.SetX1NDC(0.5)
leg.SetX2NDC(0.89)
leg.SetY1NDC(0.2)
leg.SetY2NDC(0.4)
resplots[0].Draw("p")
for r in resplots:
r.Draw('psame')
leg.SetTextSize(0.04)
leg.Draw('same')
t1.Draw()
t2.Draw()
# pblock.Draw()
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys_res_T.eps')
c.SaveAs(pname + '_' + self.fname[:-5] + '_' + histvar +
'_sys_res_pq.jpg')
momhist = f.Get("cor_mom")
#mom = [momhist.GetMean() + 19.468, momhist.GetMeanError()]
#if self.fname.find("LiHMuon_03172") >= 0:
# mom = [momhist.GetMean()*1.107 + 1.05, momhist.GetMeanError()]
#elif self.fname.find("LiHMuon_03200") >= 0:
# mom = [momhist.GetMean()*1.104 + 1.139, momhist.GetMeanError()]
#elif self.fname.find("LiHMuon_03240") >= 0:
# mom = [momhist.GetMean()*1.17 - 9.41, momhist.GetMeanError()]
if self.fname.find("LiHMuon_03172") >= 0:
mom = [momhist.GetMean(), momhist.GetMeanError()]
elif self.fname.find("LiHMuon_03200") >= 0:
mom = [momhist.GetMean(), momhist.GetMeanError()]
elif self.fname.find("LiHMuon_03240") >= 0:
mom = [momhist.GetMean(), momhist.GetMeanError()]
rms = [momhist.GetRMS(), momhist.GetRMSError()]
summary = []
syssummary = []
def sigfig(x):
if math.fabs(x) > 1e-5:
return int(math.ceil(math.fabs(math.log(math.fabs(x), 10))))
else:
return 1
# syssummary.append("p (MeV/c) & "+self.histvarnames[0]+"&"+self.histvarnames[1]+"&"+self.histvarnames[3]+"\\\\")
if pname != "Truth":
for sys in self.sysFiles:
# if sys[3] == 'Material': stindx = 1
# else:
stindx = 0
# print sys[3], self.histstatenames[stindx]
difference0 = self.RMSsysdiff[self.histvarnames[0]][
self.histstatenames[stindx]][sys[3]]
difference1 = self.RMSsysdiff[self.histvarnames[1]][
self.histstatenames[stindx]][sys[3]]
difference3 = self.RMSsysdiff[self.histvarnames[3]][
self.histstatenames[stindx]][sys[3]]
syserr0 = self.RMSsyserr[self.histvarnames[0]][
self.histstatenames[stindx]][sys[3]]
syserr1 = self.RMSsyserr[self.histvarnames[1]][
self.histstatenames[stindx]][sys[3]]
syserr3 = self.RMSsyserr[self.histvarnames[3]][
self.histstatenames[stindx]][sys[3]]
relerr0 = syserr0 / self.RMS[self.histvarnames[0]][
self.histstatenames[0]]
relerr1 = syserr1 / self.RMS[self.histvarnames[1]][
self.histstatenames[0]]
relerr3 = syserr3 / self.RMS[self.histvarnames[3]][
self.histstatenames[0]]
syssummary.append(str(round(mom[0],sigfig(mom[1])))+"$\pm$"+str(round(mom[1],sigfig(mom[1])))+\
" & "+str(round(difference0,sigfig(difference0)))+\
" & "+str(round(syserr0,sigfig(syserr0)))+\
" & "+str(round(relerr0,sigfig(relerr0)))+\
" & "+str(round(difference1,sigfig(difference1)))+\
" & "+str(round(syserr1,sigfig(syserr1)))+\
" & "+str(round(relerr1,sigfig(relerr1)))+\
" & "+str(round(difference3,sigfig(difference3)))+\
" & "+str(round(syserr3,sigfig(syserr3)))+\
" & "+str(round(relerr3,sigfig(relerr3)))+"\\\\")
# print syssummary[-1]
syssummary.append(str(round(mom[0],2))+"$\pm$"+str(round(mom[1],2))+\
" & "+ str(round(rms[0],2))+"$\pm$"+str(round(rms[1],2))+\
" & "+str(round(self.RMSsysdiff[self.histvarnames[0]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[0]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[0]][self.histstatenames[0]]['Sum']/self.RMS[self.histvarnames[0]][self.histstatenames[0]],2))+\
" & "+str(round(self.RMSsysdiff[self.histvarnames[1]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[1]][self.histstatenames[0]]['Sum'],2))+\
" & "+str(round(self.RMSsyserr[self.histvarnames[1]][self.histstatenames[0]]['Sum']/self.RMS[self.histvarnames[1]][self.histstatenames[0]],2))+\
" & "+str(round(self.RMSsysdiff[self.histvarnames[3]][self.histstatenames[0]]['Sum'],2))+
" & "+str(round(self.RMSsyserr[self.histvarnames[3]][self.histstatenames[0]]['Sum'],2))+
" & "+str(round(self.RMSsyserr[self.histvarnames[3]][self.histstatenames[0]]['Sum']/self.RMS[self.histvarnames[2]][self.histstatenames[0]],2))+"\\\\")
# summary.append("p (MeV/c) & &"+str(self.histstatenames[0])+" & "+str(self.histstatenames[1])+" & $\chi^{2}$/ndf & "+
# +str(self.histstatenames[2])+" & $\chi^{2}$/ndf \\\\")
# print mom, self.RMS, self.RMSErr, self.Chi2
for histvar in self.histvarnames:
summary.append(str(round(mom[0],2))+"$\pm$"+str(round(mom[1],2))+\
"& $\ "+histvar+"$ & "+str(round(self.RMS[histvar][self.histstatenames[0]],2))+ \
"$\pm$"+str(round(self.RMSErr[histvar][self.histstatenames[0]],2))+ \
"$\pm$"+str(round(self.RMSsyserr[histvar][self.histstatenames[0]]["Sum"],2))+ \
" & "+str(round(self.RMS[histvar][self.histstatenames[1]],2))+ \
"$\pm$"+str(round(self.RMSErr[histvar][self.histstatenames[1]],2))+ \
# "$\pm$"+str(round(self.RMSsyserr[histvar][self.histstatenames[1]]["Sum"],2))+\
" & "+str(round(self.Chi2[histvar][self.histstatenames[1]][0],1))+ \
" / "+ str(self.Chi2[histvar][self.histstatenames[1]][1])+ \
" & "+str(round(self.RMS[histvar][self.histstatenames[2]],2))+ \
"$\pm$"+str(round(self.RMSErr[histvar][self.histstatenames[2]],2))+ \
#"$\pm$"+str(round(self.RMSsyserr[histvar][self.histstatenames[2]]["Sum"],2))+\
" & "+str(round(self.Chi2[histvar][self.histstatenames[2]][0],1))+ \
" / "+ str(self.Chi2[histvar][self.histstatenames[2]][1])
+"\\\\")
# print summary[-1]
f.Close()
return [summary, syssummary]
def __plot_profiles_in_same_canvas(self, hist_objs, hist_names, legends,
y_limits, **kwargs):
legend_position = retrieve_kw(kwargs, 'legend_position',
(0.36, 0.20, 0.66, 0.36))
legend_prefix = retrieve_kw(kwargs, 'legend_prefix',
'Z#rightarrowee, ')
legend_header = retrieve_kw(kwargs, 'legend_header', 'Trigger step')
ylabel = retrieve_kw(kwargs, 'ylabel', 'Trigger Efficiency')
title = retrieve_kw(kwargs, 'title', 'Trigger Efficiency')
oname = retrieve_kw(kwargs, 'oname', 'plot_efficiencys')
column = retrieve_kw(kwargs, 'column', 2)
doRatio = retrieve_kw(kwargs, 'doRatio', False)
canvas_size = retrieve_kw(kwargs, 'canvas_size', (1800, 1500))
# FIXME: This must be disable for now, there is some problem into the xaxis scale
# The top and bot axis must be match!
tobject_collector = []
ratio_size_as_fraction = 0.35
from ROOT import TCanvas, TLegend, TProfile, TPad
rows = int(round(len(hist_objs) / float(column)))
canvas = TCanvas('canvas', 'canvas', canvas_size[0], canvas_size[1])
canvas.Divide(rows, column)
leg_holder = []
for index, hist_str in enumerate(hist_names):
hists = hist_objs[hist_str]
pad = canvas.cd(index + 1)
# Force disable if != of 2
if len(hists) != 2:
doRatio = False
if doRatio:
drawopt = 'pE1'
pad.cd()
top = TPad("pad_top", "This is the top pad", 0.0,
ratio_size_as_fraction, 1.0, 1.0)
top.SetBottomMargin(0.0)
top.SetBottomMargin(0.06 / float(top.GetHNDC()))
#top.SetTopMargin (0.04/float(top.GetHNDC()))
top.SetRightMargin(0.05)
top.SetLeftMargin(0.16)
top.SetFillColor(0)
top.Draw(drawopt)
tobject_collector.append(top)
pad.cd()
bot = TPad("pad_bot", "This is the bottom pad", 0.0, 0.0, 1.0,
ratio_size_as_fraction)
bot.SetBottomMargin(0.10 / float(bot.GetHNDC()))
#bot.SetTopMargin (0.02/float(bot.GetHNDC()))
bot.SetTopMargin(0.0)
bot.SetRightMargin(0.05)
bot.SetLeftMargin(0.16)
bot.SetFillColor(0)
bot.Draw(drawopt)
tobject_collector.append(bot)
if type(legend_prefix) is not list:
legend_prefix = [legend_prefix] * len(legends)
if doRatio:
top.cd()
leg = TLegend(legend_position[0], legend_position[1],
legend_position[2], legend_position[3])
from AtlasStyle import setLegend1, atlas_template
setLegend1(leg)
leg.SetHeader(legend_header)
for i, eff in enumerate(hists):
eff.SetLineColor(self._curve_color[i])
eff.SetMarkerColor(self._curve_color[i])
eff.SetMarkerStyle(self._marker_style[i])
if type(eff) is TProfile: eff.SetStats(0)
leg.AddEntry(eff, legend_prefix[i] + legends[i], 'p')
if i is 0: eff.Draw()
else: eff.Draw('same')
leg.SetTextSize(0.03)
leg.SetBorderSize(0)
leg.Draw()
if doRatio:
top.Modified()
top.Update
pad.Modified()
pad.Update()
from ROOT import TProfile, TEfficiency, kFALSE
xmin = 0
xmax = 999
if type(hists[0]) is TProfile:
hists[0].GetYaxis().SetRangeUser(y_limits[index][0],
y_limits[index][1])
elif type(hists[0]) is TEfficiency:
hists[0].GetPaintedGraph().GetYaxis().SetRangeUser(
y_limits[index][0], y_limits[index][1])
hists[0].GetPaintedGraph().GetYaxis().SetTitle('A')
# Fix the X axis
nbins = hists[0].GetTotalHistogram().GetNbinsX()
xmin = hists[0].GetTotalHistogram().GetXaxis().GetBinLowEdge(1)
xmax = hists[0].GetTotalHistogram().GetXaxis().GetBinLowEdge(
nbins + 1)
hists[0].GetPaintedGraph().GetXaxis().SetLimits(xmin, xmax)
else:
hists[0].GetYaxis().SetRangeUser(y_limits[index][0],
y_limits[index][1])
pad.Modified()
pad.Update()
tobject_collector.append(leg)
if doRatio:
atlas_template(top, **kwargs)
top.Update()
from ROOT import TH1
divide = ""
drawopt = 'pE1'
bot.cd()
ref = hists[0].GetPassedHistogram().Clone()
h = hists[1].GetPassedHistogram().Clone()
#ref = hists[0].Clone()
#h = hists[1].Clone()
ref.Sumw2()
h.Sumw2()
ref.Divide(hists[0].GetTotalHistogram().Clone())
h.Divide(hists[1].GetTotalHistogram().Clone())
#ratioplot = TEfficiency(h,ref)
ratioplot = h.Clone()
ratioplot.Sumw2()
ratioplot.SetName(h.GetName() + '_ratio')
ratioplot.Divide(h, ref, 1., 1., '')
#ratioplot.Divide(ref)
ratioplot.SetFillColor(0)
ratioplot.SetFillStyle(0)
ratioplot.SetMarkerColor(1)
ratioplot.SetLineColor(kBlack)
ratioplot.SetMarkerStyle(24)
ratioplot.SetMarkerSize(1.2)
ratioplot.GetYaxis().SetTitle('trigger / ref')
ratioplot.GetYaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetTitleSize(0.10)
ratioplot.GetXaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetLabelSize(0.10)
ratioplot.GetYaxis().SetRangeUser(0.9, 1.07)
ratioplot.Draw(drawopt)
tobject_collector.append(ratioplot)
#atlas_template(bot, **kwargs)
from ROOT import TLine
l1 = TLine(xmin, 1, xmax, 1)
l1.SetLineColor(kRed)
l1.SetLineStyle(2)
l1.Draw()
tobject_collector.append(l1)
bot.Update()
else:
atlas_template(pad, **kwargs)
pad.Update()
canvas.SaveAs(oname + '.pdf')
latex.DrawLatex(1.3 * l, posY_ - relExtraDY * cmsTextSize * t, extraText)
latex1 = TLatex()
latex1.SetNDC()
latex1.SetTextAngle(0)
latex1.SetTextColor(1)
latex1.SetTextSize(0.03)
if expect_or_observe == 'observe':
h[15].SetMarkerStyle(20)
h[15].SetMarkerSize(1)
h[15].SetStats(0)
h[15].Draw("same p e")
leg1.AddEntry(h[15], "DATA", "lp")
leg1.Draw()
leg2.Draw()
leg3.Draw()
fPads2.cd()
fPads2.SetGridy()
fPads2.SetGridx()
divide = TH1D()
if expect_or_observe == 'expect':
divide = hmc
else:
divide = h[15]
divide.Divide(hmc)
divide.SetTitle("")
divide.SetStats(0)
leg_limit_vs_mass_.SetBorderSize(0)
leg_limit_vs_mass_.SetTextSize(0.03)
leg_limit_vs_mass_.SetLineColor(1)
leg_limit_vs_mass_.SetLineStyle(1)
leg_limit_vs_mass_.SetLineWidth(1)
leg_limit_vs_mass_.SetFillColor(0)
leg_limit_vs_mass_.SetFillStyle(1001)
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__Th_limit,
"Theoretical cross-section", "L")
if drawObs:
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__obs_limit,
"Observed 95% CL upper limit", "L")
leg_limit_vs_mass_.AddEntry(graph_limit_vs_mass__exp_limit,
"Expected 95% CL upper limit", "L")
leg_limit_vs_mass_.Draw()
myC.SaveAs(outputDir + "/limits" + "/limit_vs_mass_" + year_this +
"_ctau" + ctau_this_str + plot_tag + ".pdf")
myC.SaveAs(outputDir + "/limits" + "/limit_vs_mass_" + year_this +
"_ctau" + ctau_this_str + plot_tag + ".png")
myC.SaveAs(outputDir + "/limits" + "/limit_vs_mass_" + year_this +
"_ctau" + ctau_this_str + plot_tag + ".C")
##################exclusion region of ctau and Lambda/mass #######################
print "value of the 2D r grid (exp, " + year_this + ") provided from samples: "
print r_exp_2d_grid_
print "value of the 2D r grid (obs, " + year_this + ") provided from samples: "
print r_obs_2d_grid_
lambda_point_boundary_exp_ = np.zeros(N_ctau)
def drawTrainingCurve(input, output):
hist = pickle.load(open(input, "rb"))
tr_acc = hist["acc"]
tr_loss = hist["loss"]
val_acc = hist["val_acc"]
val_loss = hist["val_loss"]
epochs = range(len(tr_acc))
c = TCanvas("c", "c", 800, 500)
#c.SetFillStyle(4000)
#c.SetFrameFillStyle(4000)
gStyle.SetOptStat(0)
uppad = TPad("u", "u", 0., 0.55, 1., 1.)
downpad = TPad("d", "d", 0., 0., 1., 0.55)
uppad.Draw()
#uppad.SetFillStyle(4000)
#uppad.SetFrameFillStyle(4000)
downpad.Draw()
#downpad.SetFillStyle(4000)
#downpad.SetFrameFillStyle(4000)
uppad.cd()
gPad.SetMargin(0.15, 0.05, 0.02, 0.15)
gPad.SetGrid(1, 1)
gStyle.SetGridColor(13)
gr_acc_train = TGraph(len(epochs), array('d', epochs), array('d', tr_acc))
gr_acc_train.SetLineColor(2)
gr_acc_train.SetLineWidth(2)
gr_acc_test = TGraph(len(epochs), array('d', epochs), array('d', val_acc))
gr_acc_test.SetLineColor(4)
gr_acc_test.SetLineWidth(2)
mgup = TMultiGraph("mgup", ";number of epochs;accuracy")
mgup.Add(gr_acc_train, "l")
mgup.Add(gr_acc_test, "l")
mgup.Draw("AL")
mgup.GetXaxis().SetRangeUser(min(epochs), max(epochs))
mgup.GetXaxis().SetLabelSize(0)
mgup.GetYaxis().CenterTitle()
mgup.GetYaxis().SetTitleSize(0.12)
mgup.GetYaxis().SetTitleOffset(0.5)
mgup.GetYaxis().SetLabelSize(0.105)
mgup.GetYaxis().SetNdivisions(8)
l = TLegend(0.6, 0.15, 0.88, 0.6)
l.SetTextSize(0.14)
l.AddEntry(gr_acc_train, "training", "l")
l.AddEntry(gr_acc_test, "validation", "l")
l.Draw("same")
downpad.cd()
gPad.SetMargin(0.15, 0.05, 0.25, 0.02)
gPad.SetGrid(1, 1)
gStyle.SetGridColor(13)
gr_loss_train = TGraph(len(epochs), array('d', epochs),
array('d', tr_loss))
gr_loss_train.SetLineColor(2)
gr_loss_train.SetLineWidth(2)
gr_loss_test = TGraph(len(epochs), array('d', epochs),
array('d', val_loss))
gr_loss_test.SetLineColor(4)
gr_loss_test.SetLineWidth(2)
mgdown = TMultiGraph("mgdown", ";number of epochs;loss")
mgdown.Add(gr_loss_train, "l")
mgdown.Add(gr_loss_test, "l")
mgdown.Draw("AL")
mgdown.GetXaxis().SetRangeUser(min(epochs), max(epochs))
mgdown.GetXaxis().SetLabelSize(0.085)
mgdown.GetXaxis().SetTitleSize(0.11)
mgdown.GetXaxis().SetTitleOffset(0.9)
mgdown.GetXaxis().CenterTitle()
mgdown.GetYaxis().CenterTitle()
mgdown.GetYaxis().SetTitleSize(0.11)
mgdown.GetYaxis().SetTitleOffset(0.55)
mgdown.GetYaxis().SetLabelSize(0.085)
mgdown.GetYaxis().SetNdivisions(8)
c.SaveAs(output)
def drawlegend(self, position=None, **kwargs):
"""Create and draw legend.
Legend position can be controlled in several ways
drawlegend(position)
drawlegend(position=position)
where position is a string which can contain the horizontal position, e.g.
'left', 'center', 'right', 'L', 'C', 'R', 'x=0.3', ...
where 'x' is the position (between 0 an 1) of the left side in the frame.
The position string can also contain the vertical position as e.g.
'top', 'middle', 'bottom', 'T', 'M', 'B', 'y=0.3', ...
where 'y' is the position (between 0 an 1) of the top side in the frame.
Instead of the strings, the exact legend coordinates can be controlled with
the keywords x1, x2, y1 and y2, or, x1, y1, width and height:
drawlegend(x1=0.2,width=0.4)
drawlegend(x1=0.2,width=0.4,y1=0.9,height=0.4)
drawlegend(x1=0.2,x2=0.6,y1=0.9,y2=0.4)
These floats are normalized to the axis frame, ignoring the canvas margins:
x=0 is the left, x=1 is the right, y=0 is the bottom and y=1 is the top side.
Values less than 0, or larger than 1, will put the legend outside the frame.
"""
#if not ratio:
# tsize *= 0.80
# signaltsize *= 0.80
verbosity = LOG.getverbosity(self, kwargs)
hists = self.hists
errstyle = 'lep' if gStyle.GetErrorX() else 'ep'
entries = kwargs.get('entries', [])
bands = kwargs.get('band', [self.errband]) # error bands
bands = ensurelist(bands, nonzero=True)
bandentries = kwargs.get('bandentries', [])
title = kwargs.get('header', None)
title = kwargs.get('title', title) # legend header/title
latex = kwargs.get('latex',
True) # automatically format strings as LaTeX
style = kwargs.get('style', None)
style0 = kwargs.get('style0', None) # style of first histogram
errstyle = kwargs.get('errstyle', errstyle) # style for an error point
styles = kwargs.get('styles', [])
position = kwargs.get('pos', position) # legend position
position = kwargs.get('position', position) or self.position
option = kwargs.get('option', '')
border = kwargs.get('border', False)
transparent = kwargs.get('transparent', True)
x1_user = kwargs.get('x1', None) # legend left side
x2_user = kwargs.get('x2', None) # legend right side
y1_user = kwargs.get('y1', None) # legend top side
y2_user = kwargs.get('y2', None) # legend bottom side
width = kwargs.get('width', -1) # legend width
height = kwargs.get('height', -1) # legend height
tsize = kwargs.get('tsize', _lsize) # text size
twidth = kwargs.get('twidth',
None) or 1 # scalefactor for legend width
theight = kwargs.get('theight',
None) or 1 # scalefactor for legend height
texts = kwargs.get('text', []) # extra text below legend
ncols = kwargs.get('ncols',
self.ncols) or 1 # number of legend columns
colsep = kwargs.get('colsep',
0.06) # seperation between legend columns
bold = kwargs.get('bold', True) # bold legend header
panel = kwargs.get('panel', 1) # panel (top=1, bottom=2)
texts = ensurelist(texts, nonzero=True)
entries = ensurelist(entries, nonzero=False)
bandentries = ensurelist(bandentries, nonzero=True)
headerfont = 62 if bold else 42
# CHECK
LOG.insist(self.canvas, "Canvas does not exist!")
self.canvas.cd(panel)
scale = 485. / min(gPad.GetWh() * gPad.GetHNDC(),
gPad.GetWw() * gPad.GetWNDC())
tsize *= scale # text size
# ENTRIES
#if len(bandentries)==len(bands) and len(entries)>len(hists):
# for band, bandtitle in zip(band,bandentries):
# entries.insert(hists.index(band),bandtitle)
while len(entries) < len(hists):
entries.append(hists[len(entries)].GetTitle())
while len(bandentries) < len(bands):
bandentries.append(bands[len(bandentries)].GetTitle())
hists = hists + bands
entries = entries + bandentries
# STYLES
if style0:
styles[0] = style0
while len(styles) < len(hists):
hist = hists[len(styles)]
if hist in bands:
styles.append('f')
elif style != None:
styles.append(style)
elif hasattr(hist, 'GetFillStyle') and hist.GetFillStyle() > 0:
styles.append('f')
elif 'E0' in hist.GetOption() or 'E1' in hist.GetOption():
styles.append(errstyle)
else:
styles.append('lp')
# NUMBER of LINES
nlines = sum([1 + e.count('\n') for e in entries])
#else: nlines += 0.80
if texts: nlines += sum([1 + t.count('\n') for t in texts])
if ncols > 1: nlines /= float(ncols)
if title: nlines += 1 + title.count('\n')
# DIMENSIONS
if width < 0: width = twidth * 0.35
if height < 0: height = theight * 1.34 * tsize * nlines
if ncols > 1: width *= ncols / (1 - colsep)
x2 = 0.90
x1 = x2 - width
y1 = 0.92
y2 = y1 - height
# POSITION
if not position:
position = 'TRR' if ncols > 1 else 'R' if title else 'TR'
position = position.replace('left', 'L').replace(
'center', 'C').replace('right', 'R').replace( #.lower()
'top', 'T').replace('middle', 'M').replace('bottom', 'B')
if 'C' in position:
if 'R' in position: center = 0.57
elif 'L' in position: center = 0.43
else: center = 0.50
x1 = center - width / 2
x2 = center + width / 2
elif 'LL' in position:
x1 = 0.03
x2 = x1 + width
elif 'L' in position:
x1 = 0.08
x2 = x1 + width
elif 'RR' in position:
x2 = 0.97
x1 = x2 - width
elif 'R' in position:
x2 = 0.92
x1 = x2 - width
elif 'x=' in position:
x1 = float(re.findall(r"x=(\d\.\d+)", position)[0])
x2 = x1 + width
if 'M' in position:
if 'T' in position: middle = 0.57
elif 'B' in position: middle = 0.43
else: middle = 0.50
y1 = middle - height / 2
y2 = middle + height / 2
elif 'TT' in position:
y2 = 0.97
y1 = y2 - height
elif 'T' in position:
y2 = 0.92
y1 = y2 - height
elif 'BB' in position:
y1 = 0.03
y2 = y1 + height
elif 'B' in position:
y1 = 0.08
y2 = y1 + height
elif 'y=' in position:
y2 = float(re.findall(r"y=(\d\.\d+)", position)[0])
y1 = y2 - height
if x1_user != None:
x1 = x1_user
x2 = x1 + width if x2_user == None else x2_user
if y1_user != None:
y1 = y1_user
y2 = y1 - height if y2_user == None else y2_user
L, R = gPad.GetLeftMargin(), gPad.GetRightMargin()
T, B = gPad.GetTopMargin(), gPad.GetBottomMargin()
X1, X2 = L + (1 - L - R) * x1, L + (
1 - L - R) * x2 # convert frame to canvas coordinates
Y1, Y2 = B + (1 - T - B) * y1, B + (
1 - T - B) * y2 # convert frame to canvas coordinates
legend = TLegend(X1, Y1, X2, Y2)
LOG.verb(
"Plot.drawlegend: position=%r, height=%.3f, width=%.3f, (x1,y1,x2,y2)=(%.2f,%.2f,%.2f,%.2f), (X1,Y1,X2,Y2)=(%.2f,%.2f,%.2f,%.2f)"
% (position, height, width, x1, y1, x2, y2, X1, Y1, X2, Y2),
verbosity, 1)
# MARGIN
if ncols >= 2:
margin = 0.090 / width
else:
margin = 0.044 / width
legend.SetMargin(margin)
# STYLE
if transparent: legend.SetFillStyle(0) # 0 = transparent
else: legend.SetFillColor(0)
legend.SetBorderSize(border)
legend.SetTextSize(tsize)
legend.SetTextFont(headerfont) # bold for title
if ncols > 1:
legend.SetNColumns(ncols)
legend.SetColumnSeparation(colsep)
# HEADER
if title:
if latex:
title = maketitle(title)
legend.SetHeader(title)
legend.SetTextFont(42) # no bold for entries
# ENTRIES
if hists:
for hist1, entry1, style1 in columnize(zip(hists, entries, styles),
ncols):
for entry in entry1.split('\n'):
if latex:
entry = maketitle(entry)
legend.AddEntry(hist1, entry, style1)
hist1, style1 = 0, ''
for line in texts:
if latex:
line = maketitle(line)
legend.AddEntry(0, line, '')
if verbosity >= 2:
print ">>> Plot.drawlegend: title=%r, texts=%s, latex=%s" % (
title, texts, latex)
print ">>> Plot.drawlegend: hists=%s" % (hists)
print ">>> Plot.drawlegend: entries=%s" % (entries)
print ">>> Plot.drawlegend: styles=%s" % (styles)
print ">>> Plot.drawlegend: nlines=%s, len(hists)=%s, len(texts)=%s, ncols=%s, margin=%s" % (
nlines, len(hists), len(texts), ncols, margin)
legend.Draw(option)
self.legends.append(legend)
return legend
def makeDiscr(train_discr_dict, discr_dict, outfile, xtitle="discriminator"):
c = ROOT.TCanvas("c", "c", 800, 500)
ROOT.gStyle.SetOptStat(0)
ROOT.gPad.SetMargin(0.15, 0.1, 0.2, 0.1)
#ROOT.gPad.SetLogy(1)
#ROOT.gPad.SetGrid(1,1)
ROOT.gStyle.SetGridColor(17)
l = TLegend(0.17, 0.75, 0.88, 0.88)
l.SetTextSize(0.055)
l.SetBorderSize(0)
l.SetFillStyle(0)
l.SetNColumns(2)
colors = [2, 1, 4, ROOT.kCyan + 2]
counter = 0
for leg, discr in train_discr_dict.iteritems():
a = Hist(30, 0, 1)
#fill_hist_with_ndarray(a, discr)
a.fill_array(discr)
a.SetLineColor(colors[counter])
a.SetLineWidth(2)
a.GetXaxis().SetTitle(xtitle)
a.GetXaxis().SetLabelSize(0.05)
a.GetXaxis().SetTitleSize(0.06)
a.GetXaxis().SetTitleOffset(1.45)
a.GetYaxis().SetTitle("a.u.")
a.GetYaxis().SetTickSize(0)
a.GetYaxis().SetLabelSize(0)
a.GetYaxis().SetTitleSize(0.06)
a.GetYaxis().SetTitleOffset(0.9)
a.Scale(1. / a.Integral())
#a.GetYaxis().SetRangeUser(0.00001,100)
a.GetYaxis().SetRangeUser(0, 0.9)
if counter == 0: a.draw("hist")
else: a.draw("same hist")
l.AddEntry(a, leg, "l")
counter += 1
counter = 0
for leg, discr in discr_dict.iteritems():
a = Hist(30, 0, 1)
#fill_hist_with_ndarray(a, discr)
a.fill_array(discr)
a.SetLineColor(colors[counter])
a.SetMarkerColor(colors[counter])
a.SetMarkerStyle(34)
a.SetMarkerSize(1.8)
a.SetLineWidth(2)
a.GetXaxis().SetTitle(xtitle)
a.GetXaxis().SetLabelSize(0.05)
a.GetXaxis().SetTitleSize(0.06)
a.GetXaxis().SetTitleOffset(1.45)
a.GetYaxis().SetTitle("a.u.")
a.GetYaxis().SetTickSize(0)
a.GetYaxis().SetLabelSize(0)
a.GetYaxis().SetTitleSize(0.06)
a.GetYaxis().SetTitleOffset(0.9)
a.Scale(1. / a.Integral())
#a.GetYaxis().SetRangeUser(0.00001,100)
a.GetYaxis().SetRangeUser(0, 0.4)
a.draw("same p X0")
l.AddEntry(a, leg, "p")
counter += 1
# counter = 0
# for leg,discr in train_discr_dict.iteritems():
# d = Hist(30, 0, 1)
# d.fill_array(discr)
# d.SetLineColor(colors[counter])
# d.SetLineWidth(2)
# l.AddEntry(d,leg,"l")
#
# b = Hist(30, 0, 1)
# d.fill_array(discr_dict[leg.split(" ")[0] + " test"])
# b.SetLineColor(colors[counter])
# b.SetMarkerColor(colors[counter])
# b.SetMarkerStyle(34)
# b.SetMarkerSize(1.8)
# b.SetLineWidth(2)
# l.AddEntry(b,leg,"p")
# counter += 1
l.Draw("same")
c.SaveAs(outfile)
def plot2(key, xsections, histos, names, LogY, weights, outputDIR):
c1=TCanvas(key, key, 800, 600)
pad1 = TPad("pad1", "", 0.00, 0.20, 0.99, 0.99)
pad2 = TPad("pad2", "", 0.00, 0.00, 0.99, 0.20)
pad1.SetGridx()
pad1.SetGridy()
pad2.SetGridy()
pad1.SetFillColor(0)
pad1.SetLineColor(0)
pad2.SetFillColor(0)
pad2.SetLineColor(0)
pad1.SetBottomMargin(0.03)
pad2.SetTopMargin(0.15)
pad2.SetBottomMargin(0.3)
pad1.Draw()
pad2.Draw()
leg1 = TLegend(0.68,0.55,0.86,0.86)
histos[0].GetXaxis().SetLabelSize(0)
histos[0].SetMarkerStyle(20)
for i in range(0,len(histos)):
#if histos[i].Integral()==0: continue
histos[i].Scale(xsections[i]/weights[i])
histos[i].SetLineColor(i+1)
histos[i].SetLineWidth(2)
histo_ratio=histos[1].Clone()
for i in range(2,len(histos)):
histo_ratio.Add(histos[i])
histo_ratio.SetLineWidth(2)
histo_sum=histo_ratio.Clone()
histo_sum.SetLineColor(49)
histo_sum.SetLineWidth(2)
histo_ratio.SetTitle('')
histo_ratio.Divide(histos[0])
histo_ratio.SetLineColor(49)
histo_ratio.SetMaximum(1.5)
histo_ratio.SetMinimum(0.5)
histo_ratio.GetYaxis().SetNdivisions(4,kFALSE)
histo_ratio.GetXaxis().SetTitle(key)
histo_ratio.GetXaxis().SetTitleSize(0.15)
histo_ratio.GetXaxis().SetTitleOffset(0.75)
histo_ratio.GetXaxis().SetLabelSize(0.13)
histo_ratio.GetYaxis().SetTitle('summed/inc')
histo_ratio.GetYaxis().SetTitleSize(0.1)
histo_ratio.GetYaxis().SetTitleOffset(0.3)
histo_ratio.GetYaxis().SetLabelSize(0.13)
pad1.cd()
if LogY:
pad1.SetLogy()
histos[0].SetMaximum(1.2*histos[0].GetMaximum())
histos[0].SetMinimum(0.0001)
histos[0].Draw('pe')
for i in range(1,len(histos)):
histos[i].Draw('same h')
histo_sum.Draw('same h')
leg1.AddEntry(histos[0], names[0])
leg1.AddEntry(histo_sum, 'MGsummed')
for i in range(1,len(histos)):
leg1.AddEntry(histos[i], names[i])
leg1.SetFillStyle(0)
leg1.SetBorderSize(0)
leg1.Draw()
c1.Update()
pad2.cd()
histo_ratio.Draw()
if LogY:
c1.SaveAs(outputDIR + '/' + key + '_log.png')
c1.SaveAs(outputDIR + '/' + key + '_log.pdf')
else:
c1.SaveAs(outputDIR + '/' + key + '.png')
c1.SaveAs(outputDIR + '/' + key + '.pdf')
for i in range(0,len(histos)):
histos[i].Scale(weights[i]/xsections[i])
def main():
filename = read_file_name("NY_OUTPUT.txt")
can = TCanvas("can", "can")
can.SetGrid()
mg = TMultiGraph()
nn = 9
GR = []
NAME = []
px, py = array('d'), array('d')
f = open(filename[2], 'r')
indicator = 0
for line in f:
if (indicator == 0):
indicator = indicator + 1
continue
Name, Total, Pos, Neg, TNum = line.split()
name = Find_Loca(Name)
name = Name.replace(Name[name:], "")
# print(name)
px.append((indicator - 1) % 9)
py.append(float(Total))
if ((indicator) % 9 == 0):
NAME.append(name)
gr = TGraph(nn, px, py)
GR.append(gr)
px, py = array('d'), array('d')
indicator = indicator + 1
# print(GR); print(len(GR))
for i in range(len(GR)):
GR[i].SetLineWidth(2)
if "water" in NAME[i]:
GR[i].SetLineWidth(5)
GR[i].SetLineColor(1)
GR[i].SetMarkerColor(1)
if "wine" in NAME[i]:
GR[i].SetMarkerColor(2)
GR[i].SetLineColor(2)
if "beer" in NAME[i]:
GR[i].SetMarkerColor(5)
GR[i].SetLineColor(5)
if "tea" in NAME[i]:
GR[i].SetMarkerColor(4)
GR[i].SetLineColor(4)
if "coffee" in NAME[i]:
GR[i].SetMarkerColor(3)
GR[i].SetLineColor(3)
if "juice" in NAME[i]:
GR[i].SetMarkerColor(7)
GR[i].SetLineColor(7)
if "COLA" in NAME[i]:
GR[i].SetMarkerColor(6)
GR[i].SetLineColor(6)
GR[i].GetXaxis().SetTitle("days")
GR[i].SetMarkerStyle(20)
# GR[i].Fit("pol4","q")
mg.Add(GR[i])
mg.Draw("ALP")
leg = TLegend(0.65, 0.65, 0.9, 0.8)
leg.SetBorderSize(0)
leg.SetFillColor(10)
for i in range(len(GR)):
leg_entry = leg.AddEntry(GR[i], NAME[i], "l")
leg.Draw()
mg.SetTitle("Total words counts at NY")
mg.GetHistogram().GetXaxis().SetTitle("days")
mg.GetHistogram().GetXaxis().SetTitleOffset(1)
mg.GetHistogram().GetXaxis().SetLabelSize(0.03)
mg.GetHistogram().GetYaxis().SetTitle("Counts")
mg.GetHistogram().GetYaxis().SetTitleOffset(1.3)
mg.GetHistogram().GetYaxis().SetLabelSize(0.03)
mg.GetHistogram().GetXaxis().SetBinLabel(5, "Mon")
mg.GetHistogram().GetXaxis().SetBinLabel(16, "Tue")
mg.GetHistogram().GetXaxis().SetBinLabel(28, "Wed")
mg.GetHistogram().GetXaxis().SetBinLabel(40, "Thu")
mg.GetHistogram().GetXaxis().SetBinLabel(51, "Fri")
mg.GetHistogram().GetXaxis().SetBinLabel(63, "Sat")
mg.GetHistogram().GetXaxis().SetBinLabel(73, "Sun")
mg.GetHistogram().GetXaxis().SetBinLabel(84, "Mon")
mg.GetHistogram().GetXaxis().SetBinLabel(96, "Tue")
# for i in range(len(GR)):
# mg.GetHistogram().GetXaxis().SetBinLabel(i,DAYS)
# mg.GetHistogram().GetXaxis().SetLabel("tt")
can.Modified()
can.Update()
# can.GetFrame().SetBorderSize( 12 )
can.Print("Total_NY.pdf")
yMin=0
yMax = max(eeHist.GetBinContent(eeHist.GetMaximumBin()),eeHist.GetBinContent(mmHist.GetMaximumBin()))*1.5
hCanvas.DrawFrame(0,yMin,30,yMax,"; %s ; %s" %("m(ll) [GeV]","N_{events} / 0.5 GeV"))
ROOT.gStyle.SetOptStat(0)
#~ eeHist.SetLineColor(ROOT.kRed)
#~ eeHist.SetLineColor(ROOT.kRed)
fakeHist = ROOT.TH1F()
fakeHist.SetLineColor(ROOT.kWhite)
legend.SetHeader("Data")
legend.AddEntry(eeHist,"e^{#pm}e^{#mp} + #mu^{#pm}#mu^{#mp}","p")
#~ legend.AddEntry(mmHist,"e^{#pm}#mu^{#mp}","l")
eeHist.Draw("same")
#~ emHist.Draw("samehist")
legend.Draw("same")
line1 = ROOT.TLine(20,0,20,yMax)
line2 = ROOT.TLine(1.6,0,1.6,yMax)
line1.SetLineColor(ROOT.kBlue+3)
line2.SetLineColor(ROOT.kBlue+3)
line1.SetLineWidth(2)
line2.SetLineWidth(2)
line1.SetLineStyle(2)
line2.SetLineStyle(2)
line1.Draw("same")
#~ line2.Draw("same")
def DrawOverlap(histList,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1],
cat='2b'):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
gStyle.SetTitleOffset(1.1, "Y")
#gStyle.SetTitleOffset(1.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
gStyle.SetTickLength(0.0, "x")
i = 0
# histList_=[]
# histList=[]
# histList1=[]
# maximum=[]
## Legend
leg = TLegend(0.2, 0.80, 0.89, 0.89) #,NULL,"brNDC");
leg.SetBorderSize(0)
leg.SetNColumns(3)
# leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
# leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.05)
c = TCanvas("c1", "c1", 0, 0, 500, 500)
c.SetBottomMargin(0.15)
c.SetLeftMargin(0.15)
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
# print ("you have provided "+str(len(fileVec))+" files and "+str(len(histVec))+" histograms to make a overlapping plot" )
# print "opening rootfiles"
c.cd()
print "provided hists", histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(1.5) #1.4 for log
histList[ih].SetMinimum(0.1) #1.4 for log
if logstatus[1] is 0:
maxi = histList[ih].GetMaximum()
histList[ih].SetMaximum(maxi * 2) #1.4 for log
histList[ih].SetMinimum(0) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("PE2 ")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("PE0 same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(100)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(0)
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
print "setting style for hist"
print "color code", colors[ih]
# histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetFillColor(colors[ih])
histList[ih].SetMarkerStyle(20)
histList[ih].SetMarkerSize(1.0)
histList[ih].SetLineWidth(1)
#invert legend between first and second
if ih == 0:
leg.AddEntry(histList[ih + 1], legendtext[ih + 1],
"PEL") #"f")
if ih == 1:
leg.AddEntry(histList[ih - 1], legendtext[ih - 1],
'f') #"PEL")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(1.4)
histList[ih].GetYaxis().SetTitleFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
# histList[ih].GetXaxis().SetLabelSize(0.0000);
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
#histList[ih].GetXaxis().SetTitleOffset(1.14)
histList[ih].GetXaxis().SetTitleFont(42)
histList[ih].GetXaxis().SetLabelFont(42)
histList[ih].GetYaxis().SetLabelFont(42)
histList[ih].GetXaxis().SetNdivisions(507)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
# histList[ih].GetXaxis().SetTickSize(0.00)
i = i + 1
pt = TPaveText(0.01, 0.92, 0.95, 0.96, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.046)
#text = pt.AddText(0.12,0.35,"CMS Internal 36 fb^{-1} (2016) ")
text = pt.AddText(0.12, 0.35,
"CMS Internal 41.5 fb^{-1} (2017) ")
#text = pt.AddText(0.12,0.35,"CMS Internal 59.6 fb^{-1} (2018) ")
#text = pt.AddText(0.6,0.5,"41.5 fb^{-1} (2017) ")
cattxt = TLatex(0.20, 0.75, cat + ' ' + "category")
cattxt.SetTextSize(0.06)
cattxt.SetTextAlign(12)
cattxt.SetNDC(1)
cattxt.SetTextFont(42)
pt.Draw()
cattxt.Draw()
leg.Draw()
outputdirname = 'TFplots/'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
def main():
inputfiles = ["/mnt/disk1/nutufts/kmason/data/sparseinfill_data_test.root"]
outputfile = ["sparseoutput.root"]
CHECKPOINT_FILE = "../training/vplane_24000.tar"
trueadc_h = TH1F('adc value', 'adc value', 100, 0., 100.)
predictadc_h = TH1F('adc value', 'adc value', 100, 0., 100.)
diffs2d_thresh_h = TH2F('h2', 'diff2d', 90, 10., 100., 90, 10., 100.)
diff2d_h = TH2F('h2', 'diff2d', 100, 0., 100., 100, 0., 100.)
if GPUMODE:
DEVICE = torch.device("cuda:%d" % (DEVICE_IDS[0]))
else:
DEVICE = torch.device("cpu")
iotest = load_infill_larcvdata("infillsparsetest",
inputfiles,
batchsize,
nworkers,
"ADCMasked",
"ADC",
plane,
tickbackward=tickbackward,
readonly_products=readonly_products)
inputmeta = larcv.IOManager(larcv.IOManager.kREAD)
inputmeta.add_in_file(inputfiles[0])
inputmeta.initialize()
# setup model
model = SparseInfill((image_height, image_width),
reps,
ninput_features,
noutput_features,
nplanes,
show_sizes=False).to(DEVICE)
# load checkpoint data
checkpoint = torch.load(
CHECKPOINT_FILE,
map_location=CHECKPOINT_MAP_LOCATIONS) # load weights to gpuid
best_prec1 = checkpoint["best_prec1"]
model.load_state_dict(checkpoint["state_dict"])
tstart = time.time()
# values for average accuracies
totacc2 = 0
totacc5 = 0
totacc10 = 0
totacc20 = 0
totalbinacc = 0
# output IOManager
outputdata = larcv.IOManager(larcv.IOManager.kWRITE, "IOManager",
larcv.IOManager.kTickForward)
outputdata.set_out_file("sparseoutput.root")
outputdata.initialize()
# save to output file
ev_out_ADC = outputdata.get_data(larcv.kProductImage2D, "ADC")
ev_out_input = outputdata.get_data(larcv.kProductImage2D, "Input")
ev_out_output = outputdata.get_data(larcv.kProductImage2D, "Output")
ev_out_overlay = outputdata.get_data(larcv.kProductImage2D, "Overlay")
totaltime = 0
for n in xrange(nentries):
starttime = time.time()
print "On entry: ", n
inputmeta.read_entry(n)
ev_meta = inputmeta.get_data(larcv.kProductSparseImage, "ADC")
outmeta = ev_meta.SparseImageArray()[0].meta_v()
model.eval()
infilldict = iotest.get_tensor_batch(DEVICE)
coord_t = infilldict["coord"]
input_t = infilldict["ADCMasked"]
true_t = infilldict["ADC"]
# run through model
predict_t = model(coord_t, input_t, 1)
forwardpasstime = time.time()
predict_t.detach().cpu().numpy()
input_t.detach().cpu().numpy()
true_t.detach().cpu().numpy()
# calculate accuracies
labels = input_t.eq(0).float()
chargelabel = labels * (true_t > 0).float()
totaldeadcharge = chargelabel.sum().float()
totaldead = labels.sum().float()
predictdead = labels * predict_t
truedead = true_t * labels
predictcharge = chargelabel * predict_t
truecharge = chargelabel * true_t
err = (predictcharge - truecharge).abs()
totacc2 += (err.lt(2).float() *
chargelabel.float()).sum().item() / totaldeadcharge
totacc5 += (err.lt(5).float() *
chargelabel.float()).sum().item() / totaldeadcharge
totacc10 += (err.lt(10).float() *
chargelabel.float()).sum().item() / totaldeadcharge
totacc20 += (err.lt(20).float() *
chargelabel.float()).sum().item() / totaldeadcharge
bineq0 = (truedead.eq(0).float() * predictdead.eq(0).float() *
labels).sum().item()
bingt0 = (truedead.gt(0).float() *
predictdead.gt(0).float()).sum().item()
totalbinacc += (bineq0 + bingt0) / totaldead
# construct dense images
ADC_img = larcv.Image2D(image_width, image_height)
Input_img = larcv.Image2D(image_width, image_height)
Output_img = larcv.Image2D(image_width, image_height)
Overlay_img = larcv.Image2D(image_width, image_height)
ADC_img, Input_img, Output_img, Overlay_img, trueadc_h, predictadc_h, diff2d_h, diffs2d_thresh_h = pixelloop(
true_t, coord_t, predict_t, input_t, ADC_img, Input_img,
Output_img, Overlay_img, trueadc_h, predictadc_h, diff2d_h,
diffs2d_thresh_h)
ev_out_ADC.Append(ADC_img)
ev_out_input.Append(Input_img)
ev_out_output.Append(Output_img)
ev_out_overlay.Append(Overlay_img)
outputdata.set_id(ev_meta.run(), ev_meta.subrun(), ev_meta.event())
outputdata.save_entry()
endentrytime = time.time()
print "total entry time: ", endentrytime - starttime
print "forward pass time: ", forwardpasstime - starttime
totaltime += forwardpasstime - starttime
avgacc2 = (totacc2 / nentries) * 100
avgacc5 = (totacc5 / nentries) * 100
avgacc10 = (totacc10 / nentries) * 100
avgacc20 = (totacc20 / nentries) * 100
avgbin = (totalbinacc / nentries) * 100
tend = time.time() - tstart
print "elapsed time, ", tend, "secs ", tend / float(nentries), " sec/batch"
print "average forward pass time: ", totaltime / nentries
print "--------------------------------------------------------------------"
print " For dead pixels that should have charge..."
print "<2 ADC of true: ", avgacc2.item(), "%"
print "<5 ADC of true: ", avgacc5.item(), "%"
print "<10 ADC of true: ", avgacc10.item(), "%"
print "<20 ADC of true: ", avgacc20.item(), "%"
print "binary acc in dead: ", avgbin.item(), "%"
print "--------------------------------------------------------------------"
# create canvas to save as pngs
# ADC values
rt.gStyle.SetOptStat(0)
c1 = TCanvas("ADC Values", "ADC Values", 600, 600)
trueadc_h.GetXaxis().SetTitle("ADC Value")
trueadc_h.GetYaxis().SetTitle("Number of pixels")
c1.UseCurrentStyle()
trueadc_h.SetLineColor(632)
predictadc_h.SetLineColor(600)
c1.SetLogy()
trueadc_h.Draw()
predictadc_h.Draw("SAME")
legend = TLegend(0.1, 0.7, 0.48, 0.9)
legend.AddEntry(trueadc_h, "True Image", "l")
legend.AddEntry(predictadc_h, "Output Image", "l")
legend.Draw()
c1.SaveAs(("ADCValues.png"))
# 2d ADC difference histogram
c2 = TCanvas("diffs2D", "diffs2D", 600, 600)
c2.UseCurrentStyle()
line = TLine(0, 0, 80, 80)
line.SetLineColor(632)
diff2d_h.SetOption("COLZ")
c2.SetLogz()
diff2d_h.GetXaxis().SetTitle("True ADC value")
diff2d_h.GetYaxis().SetTitle("Predicted ADC value")
diff2d_h.Draw()
line.Draw()
c2.SaveAs(("diffs2d.png"))
# 2d ADC difference histogram - thresholded
c3 = TCanvas("diffs2D_thresh", "diffs2D_thresh", 600, 600)
c3.UseCurrentStyle()
line = TLine(10, 10, 80, 80)
line.SetLineColor(632)
diffs2d_thresh_h.SetOption("COLZ")
diffs2d_thresh_h.GetXaxis().SetTitle("True ADC value")
diffs2d_thresh_h.GetYaxis().SetTitle("Predicted ADC value")
diffs2d_thresh_h.Draw()
line.Draw()
c3.SaveAs(("diffs2d_thresh.png"))
# save results
outputdata.finalize()
class PlotGraphs:
def __init__(self,
data,
xlow,
xhigh,
ylow,
yhigh,
xlabel="",
ylabel="",
xLegend=.45,
yLegend=.60,
legendWidth=0.20,
legendHeight=0.45,
fillStyle=3395,
drawOption='APL3',
make_tfile=False):
self.graph_index = {}
self.ngraphs = 0
self.data = data
self.drawOption = drawOption
self.xlow = xlow
self.xhigh = xhigh
self.ylow = ylow
self.yhigh = yhigh
self.xlabel = xlabel
self.ylabel = ylabel
self.multigraph = TMultiGraph("MultiGraph", "")
self.legend_type = {}
if make_tfile:
self.tfile = TFile('tgraphs.root', 'recreate')
self.legend = TLegend(xLegend, yLegend, xLegend + legendWidth,
yLegend + legendHeight)
self.g_ = {}
self.g2_ = {}
self.g3_ = {}
for cat in data.cat:
if data.type[cat] == 'observed':
#self.g_[cat] = TGraph(len(data.x[cat]), data.x[cat], data.y[cat])
self.g_[cat] = TGraphAsymmErrors(len(data.x[cat]), data.x[cat],
data.y[cat], data.exl[cat],
data.exh[cat], data.eyl[cat],
data.eyh[cat])
self.g_[cat].SetName(cat)
if make_tfile:
_gcopy = self.g_[cat].Clone()
self.tfile.Append(_gcopy)
if data.dofit[cat]:
#self.g_[cat].Fit("pol3", "M", "", data.fit_min[cat], data.fit_max[cat])
f1 = TF1(
"f1",
"[0]+[1]*(x-1000.0)/1000.0+[2]*(x-1000.0)*(x-1000.0)/1000000.0+[3]*(x-1000.0)*(x-1000.0)*(x-1000.0)/1000000000.0",
data.fit_min[cat], data.fit_max[cat])
f2 = TF1(
"f2",
"[0]+[1]*(x-1000.0)/1000.0+[2]*(x-1000.0)*(x-1000.0)/1000000.0",
data.fit_min[cat], data.fit_max[cat])
f3 = TF1("f3", "[0]+[1]*(x-1000.0)/1000.0",
data.fit_min[cat], data.fit_max[cat])
_fr = self.g_[cat].Fit("f2", "MEWS", "", data.fit_min[cat],
data.fit_max[cat])
_fr.Print()
elif data.type[cat] == 'expected':
self.g_[cat] = TGraphAsymmErrors(len(data.x[cat]), data.x[cat],
data.y[cat], data.exl[cat],
data.exh[cat], data.eyl[cat],
data.eyh[cat])
self.g2_[cat] = TGraphAsymmErrors(
len(data.x[cat]), data.x[cat], data.y[cat], data.exl2[cat],
data.exh2[cat], data.eyl2[cat], data.eyh2[cat])
self.g3_[cat] = TGraphAsymmErrors(len(data.x[cat]),
data.x[cat], data.y[cat],
data.exl2[cat],
data.exh2[cat], data.y[cat],
data.exl2[cat])
self.g3_[cat].SetFillStyle(1002)
#self.g3_[cat].SetFillStyle(3008)
# 95% quantile
self.g2_[cat].SetMarkerColor(data.fill2_color[cat])
self.g2_[cat].SetMarkerStyle(data.marker_style[cat])
self.g2_[cat].SetMarkerSize(data.marker_size[cat])
self.g2_[cat].SetLineColor(data.fill2_color[cat])
self.g2_[cat].SetLineStyle(data.line_style[cat])
self.g2_[cat].SetLineWidth(data.line_width[cat])
#self.g2_[cat].SetFillColor(data.marker_color[cat]+2)
self.g2_[cat].SetFillColor(data.fill2_color[cat])
#self.g2_[cat].SetFillStyle(3008)
#self.g2_[cat].SetFillStyle(3003)
self.g2_[cat].SetFillStyle(data.fill2_style[cat])
self.g_[cat].SetMarkerColor(data.marker_color[cat])
self.g_[cat].SetMarkerStyle(data.marker_style[cat])
self.g_[cat].SetMarkerSize(data.marker_size[cat])
self.g_[cat].SetLineColor(data.line_color[cat])
self.g_[cat].SetLineStyle(data.line_style[cat])
self.g_[cat].SetLineWidth(data.line_width[cat])
self.g_[cat].SetFillColor(data.fill_color[cat])
if data.fill_style[cat] == None:
self.g_[cat].SetFillStyle(fillStyle)
else:
self.g_[cat].SetFillStyle(data.fill_style[cat])
if data.type[cat] == 'observed':
# only the main observed limit is a line,
# everything else is a filled area
if cat[0:3] == 'obs':
_legend_type = 'lp'
if 'PC' in drawOption:
_draw_option = 'PC'
else:
_draw_option = 'PL'
self.multigraph.Add(self.g_[cat], _draw_option)
elif cat[0:3] == 'SSM':
_legend_type = 'lp'
_draw_option = '3'
self.multigraph.Add(self.g_[cat], _draw_option)
# print theory curve
#self.g_[cat].Print()
elif cat[0:3] == 'Psi':
_legend_type = 'lp'
_draw_option = '3'
self.multigraph.Add(self.g_[cat], _draw_option)
elif cat[0:2] == 'RS':
_legend_type = 'f'
_draw_option = '3'
self.multigraph.Add(self.g_[cat], _draw_option)
else:
_legend_type = 'f'
self.multigraph.Add(self.g_[cat])
#self.multigraph.Add(self.g_[cat])
self.graph_index[cat] = self.ngraphs
self.ngraphs += 1
#self.legend . AddEntry( self.g_[cat], data.tlegend[cat], _legend_type);
self.legend_type[cat] = _legend_type
elif data.type[cat] == 'expected':
self.g3_[cat].SetFillColor(0)
self.g3_[cat].SetMinimum(self.ylow)
self.g3_[cat].SetMaximum(self.yhigh)
self.g3_[cat].GetXaxis().SetLimits(self.xlow, self.xhigh)
self.multigraph.Add(self.g3_[cat], 'C3')
self.ngraphs += 1
# 95 expected band
self.multigraph.Add(self.g2_[cat])
self.ngraphs += 1
self.multigraph.Add(self.g_[cat], 'C3L')
self.graph_index[cat] = self.ngraphs
self.ngraphs += 1
# median line
gline = self.g_[cat].Clone()
gline.SetLineWidth(3)
gline.SetLineColor(ROOT.kBlue)
gline.SetLineStyle(2)
# print graph contents
#gline.Print()
#self.multigraph.Add(gline, 'LXC')
self.multigraph.Add(gline, 'C3X')
self.legend.AddEntry(gline, 'median expected', "l")
self.ngraphs += 1
#self.legend . AddEntry( self.g_[cat], data.tlegend[cat], "f");
self.legend.AddEntry(self.g_[cat], '68% expected', "f")
# 95% expected band legend
self.legend.AddEntry(self.g2_[cat], '95% expected', "f")
keylist = data.legend_index.keys() # keys are indices
keylist.sort()
for key in keylist:
self.legend.AddEntry(self.g_[data.legend_index[key]],
data.tlegend[data.legend_index[key]],
self.legend_type[data.legend_index[key]])
self.legend.SetShadowColor(0)
self.legend.SetFillColor(0)
self.legend.SetLineColor(0)
if make_tfile:
self.tfile.Write()
self.tfile.Close()
def draw(self, yLabelSize=0.045):
self.multigraph.SetMinimum(self.ylow)
self.multigraph.SetMaximum(self.yhigh)
self.multigraph.Draw(self.drawOption)
self.multigraph.GetXaxis().SetNdivisions(405)
self.multigraph.GetYaxis().SetNdivisions(405)
self.multigraph.GetXaxis().SetLimits(self.xlow, self.xhigh)
#self.multigraph.GetYaxis().SetTitle("")
#self.multigraph.GetYaxis().SetLabelSize(yLabelSize)
#self.multigraph.GetXaxis().SetLabelSize(yLabelSize)
# axis labels
#latex = TLatex()
#latex.SetNDC()
##latex.SetTextSize(0.04)
#latex.SetTextSize(yLabelSize)
#latex.SetTextAlign(31) # align right
#latex.DrawLatex(0.95,0.01, self.xlabel)
#latex.SetTextAngle(90)
#latex.DrawLatex(0.04,0.95, self.ylabel)
XLabel(self.xlabel, 0.95, 0.03, text_size=0.07)
YLabel(self.ylabel, 0.04, 0.9, text_size=0.07)
self.legend.SetFillStyle(0)
self.legend.SetBorderSize(0)
#self.legend.SetTextSize(0.04)
self.legend.SetTextSize(yLabelSize)
self.legend.SetTextFont(22)
self.legend.Draw()
return self.multigraph
def draw_line(self, xline, ymin=-0.02, ymax=0.20):
if xline == None:
return
#print 'XXXX', xline
_x = array('d')
_y = array('d')
_x.append(xline)
_y.append(ymin)
_x.append(float(xline))
_y.append(ymax)
g_ = TGraph(len(_x), _x, _y)
self.multigraph.Add(g_, 'L')
def print_values(self, cat1, cat2):
legend = 'PlotGraphs::print_values():'
if cat1 in self.data.cat:
graph1 = self.multigraph.GetListOfGraphs().At(
self.graph_index[cat1])
else:
return None
if cat2 in self.data.cat:
graph2 = self.multigraph.GetListOfGraphs().At(
self.graph_index[cat2])
else:
return None
for x in range(750, 1150, 50):
dmax = 0.0
drelmax = 0.0
v1 = graph1.Eval(x)
v2 = graph2.Eval(x)
d = math.fabs(v2 - v1)
drel = math.fabs((v2 - v1) / v1)
if d > dmax:
dmax = d
if drel > drelmax:
drelmax = drel
print legend, 'x =', x
print legend, cat1, 'value =', v1
print legend, cat2, 'value =', v2
print legend, 'abs diff =', d
print legend, 'abs relative diff =', drel
print legend, 'max abs diff =', dmax
print legend, 'max abs relative diff =', drelmax
def find_intersection(self,
cat1,
cat2,
xmin=250,
xmax=2500,
precision=0.00001):
legend = 'PlotGraphs::find_intersection():'
if cat1 in self.data.cat:
graph1 = self.multigraph.GetListOfGraphs().At(
self.graph_index[cat1])
else:
return None
if cat2 in self.data.cat:
graph2 = self.multigraph.GetListOfGraphs().At(
self.graph_index[cat2])
#graph2.Print()
else:
return None
_x = xmin
print legend, graph1.Eval(_x) - graph2.Eval(_x)
_d = graph1.Eval(_x) - graph2.Eval(_x)
_step = xmax - xmin
while abs(_d) > precision:
_x += _step
if _x > xmax or _x < xmin:
return None
_d2 = graph1.Eval(_x) - graph2.Eval(_x)
_sign1 = _d > 0
_sign2 = _d2 > 0
if _sign1 != _sign2:
_step = -0.5 * _step
_d = _d2
if abs(_d2) < precision:
return _x
