def fit(hhh):
hh = hhh.Clone("h" + hhh.GetName())
nbins = hh.GetNbinsX()
for i in range(1, nbins):
### FIXME : 288 is hard-coded pedestal
val = hh.GetBinContent(i)
hh.SetBinContent(i, val)
hh.SetBinError(i, 0.01 * (val + 288.))
func = TF1("langaus", langaufun, 0, 60, 4)
func.SetParameter(0, .5)
func.SetParameter(1, 17) ## most probable value
func.SetParameter(2, 170) ## normalization (area)
func.SetParameter(3, 2) ## width of gaussian
## the way I set up the histogram the peak is usually
## around bin 15-17. We get some of the pre-pulse
## but avoid the undershoot by cutting off pretty early
func.SetRange(10, 27)
hh.Fit("langaus", "R")
peaktime = func.GetParameter(1)
peak = func.Eval(peaktime)
hh.Write()
## if you comment out these next two lines it'll probably go faster
gPad.Modified()
gPad.Update()
return peak
def plotPerLumiSection(options):
"""Save profile histograms per lumisection to PDF files"""
name = options['name'] + '_perLS'
f = openRootFileR(name)
histname = plotName(options['title'] + '_perLS', timestamp=False)
filename = plotName(options['title'] + '_perLS', timestamp=True)
filepath = plotPath(options['title'] + '_perLS', timestamp=True)
print '<<< Save plot:', filepath
hist = f.Get(histname)
canvas = TCanvas()
canvas.SetLogy(options['logy'])
gStyle.SetOptStat(options['optstat'])
hist.Draw()
gPad.Update()
hist.GetXaxis().SetTitle('Lumisection')
hist.GetYaxis().SetTitle(options['ytitle'])
hist.GetYaxis().SetTitleOffset(1.2)
for axis in [hist.GetXaxis(), hist.GetYaxis()]:
axis.SetTitleFont(133)
axis.SetTitleSize(16)
axis.SetLabelFont(133)
axis.SetLabelSize(12)
axis.CenterTitle()
drawSignature(filename)
gPad.Modified()
gPad.Update()
#canvas.Print(filepath)
#canvas.Close()
#closeRootFile(f, name)
return [canvas, hist, f]
def SaveHisto2D(histin, tokens, data=False):
proc = 'DY' if not data else 'DATA'
histname = histin.GetName()
cam = TCanvas(histname, histname, 2000, 2000)
cam.SetTopMargin(0.1)
cam.SetBottomMargin(0.15)
cam.SetLeftMargin(0.215)
cam.SetRightMargin(0.15)
cam.cd().SetLogz()
histin.Draw("colztextE")
histin.SetTitle(histname)
#needed to move the axis a bit
z_begin = 0.875
palette = histin.GetListOfFunctions().FindObject("palette")
palette.SetX1NDC(z_begin)
palette.SetX2NDC(z_begin + 0.05)
histin.GetZaxis().SetTitle('N_SS/N_OS')
gPad.Modified()
gPad.Update()
cam.SaveAs('plots/%s/Ratio_%s_%s.png' % (tokens, tokens, proc))
cam.SaveAs('plots/%s/Ratio_%s_%s.pdf' % (tokens, tokens, proc))
#cam.SaveAs('plots/%s/Ratio_%s_DY.C' %(histname.split('_')[-1],histname))
return
def plotGraph(self, x='vv', y='acc'):
'''
Plot a graph with specified quantities on x and y axes , and saves the graph
'''
if (x not in self.quantities.keys()) or (y not in self.quantities.keys()):
raise RuntimeError('selected quantities not available, available quantities are: \n{}'.format(self.quantities.keys()))
xq = self.quantities[x]
yq = self.quantities[y]
#graph = TGraphAsymmErrors()
#graph = TGraph()
graph = TGraphErrors()
for i,s in enumerate(self.samples):
graph.SetPoint(i,getattr(s, xq.name), getattr(s, yq.name) )
#if xq.err:
# graph.SetPointEXhigh(i, getattr(s, xq.name+'_errup')) # errup errdn
# graph.SetPointEXlow (i, getattr(s, xq.name+'_errdn'))
if yq.err:
graph.SetPointError(i, 0, getattr(s, yq.name+'_errup'))
# graph.SetPointEYhigh(i, getattr(s, yq.name+'_errup'))
# graph.SetPointEYlow (i, getattr(s, yq.name+'_errdn'))
c = TCanvas()
graph.SetLineWidth(2)
graph.SetMarkerStyle(22)
graph.SetTitle(';{x};{y}'.format(y=yq.title,x=xq.title))
graph.Draw('APLE')
if yq.forceRange:
graph.SetMinimum(yq.Range[0])
graph.SetMaximum(yq.Range[1])
gPad.Modified()
gPad.Update()
if yq.name=='expNevts':
line = TLine(gPad.GetUxmin(),3,gPad.GetUxmax(),3)
line.SetLineColor(ROOT.kBlue)
line.Draw('same')
#graph.SetMinimum(0.01)
#graph.SetMaximum(1E06)
if xq.log: c.SetLogx()
if yq.log: c.SetLogy()
c.SetGridx()
c.SetGridy()
c.SaveAs('./plots/{}{}/{}_{}VS{}.pdf'.format(self.label,suffix,self.name,yq.name,xq.name))
c.SaveAs('./plots/{}{}/{}_{}VS{}.C'.format(self.label,suffix,self.name,yq.name,xq.name))
c.SaveAs('./plots/{}{}/{}_{}VS{}.png'.format(self.label,suffix,self.name,yq.name,xq.name))
self.graphs['{}VS{}'.format(yq.name,xq.name)] = graph
# add the graph container for memory?
graph_saver.append(graph)
def draw_data(self):
self.mframe = self.xvar.frame()
self.data.plotOn(self.mframe)
self.underlying_model.plotOn(self.mframe)
for icomp, compname in enumerate(self.pdfs):
self.underlying_model.plotOn(self.mframe,
RooFit.Components(compname),
RooFit.LineColor(icomp + 1))
self.mframe.Draw()
gPad.Modified()
gPad.Update()
def ReadOneFile(PairsDat, alpha, h2d):
hist_px = TH1F("px", "; p_{x} [MeV]; Entries", 120, -20, 100)
hist_py = TH1F("py", "; p_{y} [MeV]; Entries", 200, -10, 10)
hist_pz = TH1F("pz", "; p_{z} [MeV]; Entries", 200, -1000, 1000)
with open(PairsDat, "r") as fp:
lines = fp.readlines()
for line in lines:
if len(line.split()) < 2:
continue
pdgCode = float(line.split()[1])
sign = np.sign(pdgCode)
e = 1 #float(line.split()[9])
charge = -sign
px = float(line.split()[6]) * e
py = float(line.split()[7]) * e
pz = float(line.split()[8]) * e
hist_px.Fill(px * 1000)
hist_py.Fill(py * 1000)
hist_pz.Fill(pz * 1000)
canvx = TCanvas("px", "px")
hist_px.Draw()
gPad.SetLogy()
gPad.Update()
gPad.Modified()
canvy = TCanvas("py", "py")
hist_py.Draw()
gPad.SetLogy()
gPad.Update()
gPad.Modified()
canvz = TCanvas("pz", "pz")
hist_pz.Draw()
gPad.SetLogy()
gPad.Update()
gPad.Modified()
bla = raw_input()
def lumiVsRunHisto(histograms,
tree,
minRun=165000,
maxRun=168000,
minLum=0,
maxLum=3000):
nbinsLum = maxLum - minLum
nbinsRun = maxRun - minRun
histograms.hlumVSrun = TH2F('hlumVSrun', ';Run number;Lumi number',
nbinsRun, minRun, maxRun, nbinsLum, minLum,
maxLum)
tree.Draw('lumi:run>>' + histograms.hlumVSrun.GetName(), '', 'col')
gPad.Modified()
gPad.Update()
def drawTH2DColMap(h, c):
"""
Drawing a TH2D as color map requires some tweaking for a (more or less) nice result
Most importantly the color axis has to be moved to the left for readable axis labels
"""
from ROOT import gPad, TPaletteAxis
c.SetRightMargin(0.175) # make some space for color axis
c.cd()
h.Draw("colz")
c.Update() # draw first, since the TPaletteAxis won't be available else
p = h.GetListOfFunctions().FindObject("palette")
p.SetX1NDC(0.84) # move to the right
p.SetX2NDC(0.89)
gPad.Modified()
gPad.Update()
def plotPerTimeStamp(options):
"""Save profile histograms per timestamp to PDF files"""
name = options['name'] + '_' + options['scan'] + '_perTime'
if options['extra']:
name += '_' + options['extra']
f = openRootFileR(options['name'] + '_perTime')
histname = plotName(name, timestamp=False)
filename = plotName(name, timestamp=True)
filepath = plotPath(name, timestamp=True)
print '<<< Save plot:', filepath
hist = f.Get(histname)
hist.SetErrorOption(options['error'])
if options['big']:
canvas = TCanvas('c', '', 8000, 1200)
else:
canvas = TCanvas('c', '', 1400, 500)
canvas.SetLogy(options['logy'])
gStyle.SetOptStat(options['optstat'])
hist.Draw()
gPad.Update()
hist.GetXaxis().SetTimeDisplay(1)
hist.GetXaxis().SetTimeFormat('#splitline{%d.%m.%y}{%H:%M:%S}%F1969-12-31' \
+' 22:00:00')
hist.GetXaxis().SetLabelOffset(0.03)
hist.GetXaxis().SetTitle('')
if 'xmin' in options and 'xmax' in options:
hist.GetXaxis().SetRangeUser(options['xmin'], options['xmax'])
hist.GetYaxis().SetTitle(options['ytitle'])
hist.GetYaxis().SetTitleOffset(1.2)
for axis in [hist.GetXaxis(), hist.GetYaxis()]:
axis.SetTitleFont(133)
axis.SetTitleSize(16)
axis.SetLabelFont(133)
axis.SetLabelSize(12)
axis.CenterTitle()
if options['big']:
axis.SetTickLength(0.01)
if options['big']:
hist.GetYaxis().SetTitleOffset(0.25)
drawSignature(filename)
gPad.Modified()
gPad.Update()
if options['retrn']:
return [canvas, hist, f]
else:
canvas.Print(filepath)
canvas.Close()
closeRootFile(f, options['name'] + '_perTime')
def draw(self, var, cut):
same = ''
hists = []
for comp in self.comps.values():
comp.tree.Draw(var, cut, 'histnorm'+same)
hist = comp.tree.GetHistogram()
hists.append(hist)
if hasattr(comp, 'style'):
comp.style.formatHisto(hist)
if same == '':
var = var.split('>>')[0]
same = 'same'
maxy = max(h.GetMaximum() for h in hists)
hists[0].GetYaxis().SetRangeUser(0, maxy*1.1)
gPad.Modified()
gPad.Update()
def analyzeRuns(histograms):
histo = histograms.hlumVSrun
px = histo.ProjectionX()
lumis = []
for bin in range(1, histo.GetNbinsX()):
if px.GetBinContent(bin) == 0:
continue
run = px.GetBinLowEdge(bin)
histograms.runHisto = histo.ProjectionY("", bin, bin, "")
histograms.runHisto.SetTitle('run %d' % run)
histograms.runHisto.Draw()
gPad.Modified()
gPad.Update()
tmp = lumisProcessed(histograms.runHisto, run)
lumis.extend(tmp)
pprint.pprint(lumis)
def drawdiff(h, opt="", useabs=True):
hd = draw(h[0], opt=opt, copy=" Difference")
if useabs:
if "TH2" in h[0].ClassName():
for i in range(0, h[0].GetNbinsX()):
for j in range(0, h[0].GetNbinsY()):
hd.SetBinContent(
i + 1,
j + 1,
abs(
h[0].GetBinContent(i + 1, j + 1)
- h[1].GetBinContent(i + 1, j + 1)
),
)
else:
hd.Add(h[1], -1)
gPad.Modified()
gPad.Update()
def plotPerBxStep(options):
"""Save histograms (per BX and step) to PDF files"""
name = options['scan'] + '_' + options['name'] + options['extra']
if 'method' in options:
name += '_' + options['method']
f = openRootFileR(name)
for bx in options['crossings']:
for step in range(len(O['nominalPos'][options['scan']])):
histname = plotName(name+'_bx'+str(bx)+'_step'+str(step), \
timestamp=False)
filename = plotName(name+'_bx'+str(bx)+'_step'+str(step), \
timestamp=True)
filepath = plotPath(name+'_bx'+str(bx)+'_step'+str(step), \
timestamp=True)
print '<<< Save plot:', filepath
hist = f.Get(histname)
canvas = TCanvas()
canvas.SetLogx(options['logx'])
canvas.SetLogy(options['logy'])
gStyle.SetOptStat(options['optstat'])
gStyle.SetOptFit(options['optfit'])
hist.Draw()
gPad.Update()
hist.GetXaxis().SetTitle(options['xtitle'])
hist.GetXaxis().SetRangeUser(options['xmin'], options['xmax'])
hist.GetYaxis().SetTitle(options['ytitle'])
hist.GetYaxis().SetTitleOffset(1.2)
for axis in [hist.GetXaxis(), hist.GetYaxis()]:
axis.SetTitleFont(133)
axis.SetTitleSize(16)
axis.SetLabelFont(133)
axis.SetLabelSize(12)
axis.CenterTitle()
stats = hist.FindObject('stats')
stats.SetTextFont(133)
stats.SetTextSize(16)
drawSignature(filename)
gPad.Modified()
gPad.Update()
if 'custom' in options:
extragraphs = options['custom'](hist)
canvas.Print(filepath)
canvas.Close()
closeRootFile(f, name)
def printCanvas(histogram, title):
"to print histogram for debugging"
can = TCanvas()
histogram.Draw("colz")
gStyle.SetOptStat("")
histogram.SetTitle("")
histogram.GetXaxis().SetTitle("pixel number")
histogram.GetYaxis().SetTitle("pixel number")
histogram.GetZaxis().SetTitle("measured energy in cells")
gPad.Update()
palette = histogram.GetListOfFunctions().FindObject("palette")
can.SetRightMargin(0.2)
palette.SetX1NDC(0.8)
palette.SetX2NDC(0.815)
palette.SetY1NDC(0.1)
palette.SetY2NDC(0.9)
gPad.Modified()
gPad.Update()
can.Print(title + ".png")
def printCanvas(histogram,title,theRange,maximum):
can=TCanvas()
histogram.Draw("colz")
gStyle.SetOptStat("")
histogram.SetTitle("")
histogram.GetXaxis().SetTitle("pixel number")
histogram.GetYaxis().SetTitle("pixel number")
histogram.GetZaxis().SetTitle("measured energy in cells")
histogram.GetXaxis().SetRangeUser(theRange[0]-20,theRange[1]+20)
histogram.GetYaxis().SetRangeUser(theRange[2]-20,theRange[3]+20)
histogram.GetZaxis().SetRangeUser(0,maximum)
gPad.Update()
palette=histogram.GetListOfFunctions().FindObject("palette")
can.SetRightMargin(0.2)
palette.SetX1NDC(0.8)
palette.SetX2NDC(0.815)
palette.SetY1NDC(0.1)
palette.SetY2NDC(0.9)
gPad.Modified()
gPad.Update()
print ("title",title)
can.Print("test/"+str(title)+".png")
def TwoFileSAME3VsLumi(F1graph1, F1graph2, F1graph3, F2graph1, F2graph2, F2graph3, title, type, DoInclusive):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
F1graph1.SetMarkerColor(kBlack)#electrons
F1graph2.SetMarkerColor(kBlue)#electrons
F1graph3.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerColor(kBlack)#electrons
F2graph2.SetMarkerColor(kBlue)#electrons
F2graph3.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerStyle(kOpenStar)#inclusive
F2graph2.SetMarkerStyle(kOpenStar)#electrons
F2graph3.SetMarkerStyle(kOpenStar)#muons
multigraph = TMultiGraph()
if(DoInclusive or type == "ZmassBARELL" or type == "ZwidthBARELL" or type == "ZmultBARELL"):
multigraph.Add(F1graph1,"AP")
multigraph.Add(F2graph1,"AP")
multigraph.Add(F1graph2,"AP")
multigraph.Add(F1graph3,"AP")
multigraph.Add(F2graph2,"AP")
multigraph.Add(F2graph3,"AP")
multigraph.Draw("AP")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetXaxis().SetLimits(0.,40.)
multigraph.GetYaxis().SetTitleOffset(1.4)
gPad.Modified()
if(type == "Zmass" or type == "ZmassBARELL"):
multigraph.SetMaximum(1.008*gPad.GetUymax())
multigraph.GetYaxis().SetTitle("M_{l^{+}l^{-}} [GeV]")
elif(type == "Zwidth" or type == "ZwidthBARELL"):
multigraph.SetMaximum(1.1*gPad.GetUymax())
multigraph.GetYaxis().SetTitle("#Gamma [GeV]")
elif(type == "Zmult" or type == "ZmultBARELL"):
multigraph.SetMaximum(1.2*gPad.GetUymax())
multigraph.GetYaxis().SetTitle("#Z")
elif(type == "SIP"):
multigraph.GetYaxis().SetTitle("SIP")
multigraph.SetMaximum(1.1*gPad.GetUymax())
printLumiPrelOut(canvas)
canvas.Update()
down = gPad.GetUymin()
up = gPad.GetUymax()
MC_muMass = 90.92
MC_eleMass = 90.63
Data_muMass = 90.95
Data_eleMass = 90.68
lineB = TLine(5.57,down,5.57, up)
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.58,down,8.58,up)
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.9,down,12.9,up)
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.57,down,16.57,up)
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.7,down,19.7,up)
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(26.9,down,26.9,up)
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
if(type == "Zmass"):
lineMC_ele = TLine(0.,MC_eleMass,40., MC_eleMass)
lineMC_ele.SetLineColor(kBlue)
lineMC_ele.SetLineStyle(1)
lineMC_ele.Draw()
lineMC_mu = TLine(0.,MC_muMass,40., MC_muMass)
lineMC_mu.SetLineColor(kRed)
lineMC_mu.SetLineStyle(1)
lineMC_mu.Draw()
lineData_ele = TLine(0.,Data_eleMass,40., Data_eleMass)
lineData_ele.SetLineColor(kBlue)
lineData_ele.SetLineStyle(2)
lineData_ele.Draw()
lineData_mu = TLine(0.,Data_muMass,40., Data_muMass)
lineData_mu.SetLineColor(kRed)
lineData_mu.SetLineStyle(2)
lineData_mu.Draw()
legend = TLegend(0.80,0.75,0.965,0.93)
if(type == "Zmass" or type == "Zwidth" or type == "Zmult"):
legend.AddEntry(F1graph2,"e^{+}e^{-}","P")
legend.AddEntry(F1graph3,"#mu^{+}#mu^{-}","P")
legend.AddEntry(F2graph2,"e^{+}e^{-} ICHEP","P")
legend.AddEntry(F2graph3,"#mu^{+}#mu^{-} ICHEP","P")
else:
legend.AddEntry(F1graph1,"EBEB","P")
legend.AddEntry(F2graph1,"EBEB ICHEP","P")
legend.AddEntry(F1graph2,"EBEE","P")
legend.AddEntry(F1graph3,"EEEE","P")
legend.AddEntry(F2graph2,"EBEE ICHEP","P")
legend.AddEntry(F2graph3,"EEEE ICHEP","P")
legend.SetTextFont(32)
legend.Draw()
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
ref_pts = array('d', [0.0, 1.0])
ref = ROOT.TGraph(2, ref_pts, ref_pts) # draw a diagonal line for reference
ref.SetLineColor(ROOT.kBlack)
ref.SetLineWidth(1)
x = 0.35
y = 0.65
latex_ = TLatex(x, y, "")
c1 = TCanvas("c1", "c1")
c1.cd()
roc_baseline.Add(ref)
roc_baseline.Draw('ACP')
roc_baseline.SetTitle("ROC Curve for BDT Evaluation")
roc_baseline.GetXaxis().SetTitle("Signal Efficiency")
roc_baseline.GetYaxis().SetTitle("Background Efficiency")
leg_baseline.Draw("same")
latex_.Draw("same")
gPad.Modified()
roc_baseline.GetXaxis().SetLimits(0.0, 1.0)
roc_baseline.SetMinimum(0.0)
roc_baseline.SetMaximum(1.0)
c1.Update()
c1.SaveAs(dir_ + "/dist/EVERYTHING/ROC_new_vars_comp_" + str(i) + ".pdf")
c1.SaveAs(dir_ + "/dist/EVERYTHING/ROC_new_vars_comp_" + str(i) + ".png")
raw_input("<<<waiting")
def mistagSFtopEMu(year_, ana_):
if year_ == 2017:
dir = "monohbb.v06.00.05.2017_NCU/withSingleTop/" + ana_ + "/"
if year_ == 2018:
dir = "monohbb.v06.00.05.2018_NCU/withSingleTop/" + ana_ + "/"
print "Top Electron Region"
print " "
openfile1 = TFile(dir + "TopE.root") #
topmatchTopE = openfile1.Get("h_TopMatch")
WmatchTopE = openfile1.Get("h_Wmatch")
unmatchTopE = openfile1.Get("h_unmatch")
wjetsTopE = openfile1.Get("h_sumWJets")
dibosonTopE = openfile1.Get("h_sumDiboson")
unsubtractedDataTopE = openfile1.Get("h_Data")
failMCsubtractTopE = openfile1.Get("h_ttFailed")
passMCsubtractTopE = openfile1.Get("h_ttPassed")
subtractedDataTopE = openfile1.Get("SubtractedData")
datafailTopE = openfile1.Get("SubtractedDataFailed")
datapassTopE = openfile1.Get("SubtractedDataPassed") #
totaldataTopE = openfile1.Get("h_totaldata")
totalMCtopE = openfile1.Get("h_tt")
passedTopEdataBfrSubtract = openfile1.Get("h_Data_Passed")
wjetsTopEpassed = openfile1.Get("h_sumWJetsPassed")
dibosonTopEpassed = openfile1.Get("h_sumDibosonPassed")
failedTopEdataBfrSubtract = openfile1.Get("h_Data_Failed")
wjetsTopEfailed = openfile1.Get("h_sumWJetsFailed")
dibosonTopEfailed = openfile1.Get("h_sumDibosonFailed")
stTopE = openfile1.Get("h_sumST")
stTopEpassed = openfile1.Get("h_sumSTPassed")
stTopEfailed = openfile1.Get("h_sumSTFailed")
print "Top Muon Region"
print " "
openfile2 = TFile(dir + "TopMu.root") #
topmatchTopMu = openfile2.Get("h_TopMatch")
WmatchTopMu = openfile2.Get("h_Wmatch")
unmatchTopMu = openfile2.Get("h_unmatch")
wjetsTopMu = openfile2.Get("h_sumWJets")
dibosonTopMu = openfile2.Get("h_sumDiboson")
unsubtractedDataTopMu = openfile2.Get("h_Data")
failMCsubtractTopMu = openfile2.Get("h_ttFailed")
passMCsubtractTopMu = openfile2.Get("h_ttPassed")
subtractedDataTopMu = openfile2.Get("SubtractedData")
datafailTopMu = openfile2.Get("SubtractedDataFailed")
datapassTopMu = openfile2.Get("SubtractedDataPassed") #
totaldataTopMu = openfile2.Get("h_totaldata")
totalMCtopMu = openfile2.Get("h_tt")
passedTopMudataBfrSubtract = openfile2.Get("h_Data_Passed")
wjetsTopMupassed = openfile2.Get("h_sumWJetsPassed")
dibosonTopMupassed = openfile2.Get("h_sumDibosonPassed")
failedTopMudataBfrSubtract = openfile2.Get("h_Data_Failed")
wjetsTopMufailed = openfile2.Get("h_sumWJetsFailed")
dibosonTopMufailed = openfile2.Get("h_sumDibosonFailed")
stTopMu = openfile2.Get("h_sumST")
stTopMupassed = openfile2.Get("h_sumSTPassed")
stTopMufailed = openfile2.Get("h_sumSTFailed")
print "get histograms from root files: done"
print " "
SubtractedDataPassedTopE = datapassTopE.Clone("SubtractedDataPassedTopE")
SubtractedDataPassedTopMu = datapassTopMu.Clone(
"SubtractedDataPassedTopMu")
#merge histogram"
print "merge histograms"
print " "
topmatchMerge = topmatchTopE + topmatchTopMu
WmatchMerge = WmatchTopE + WmatchTopMu
unmatchMerge = unmatchTopE + unmatchTopMu
wjetsMerge = wjetsTopE + wjetsTopMu
stMerge = stTopE + stTopMu
dibosonMerge = dibosonTopE + dibosonTopMu
unsubtractedDataMerge = unsubtractedDataTopE + unsubtractedDataTopMu
failMCsubtractMerge = failMCsubtractTopE.Clone("failMCsubtractMerge")
failMCsubtractMerge = failMCsubtractMerge + failMCsubtractTopMu
passMCsubtractMerge = passMCsubtractTopE.Clone("passMCsubtractMerge")
passMCsubtractMerge = passMCsubtractMerge + passMCsubtractTopMu
subtractedDataMerge = subtractedDataTopE + subtractedDataTopMu
ttData_fraction = arr.array('d')
ttData_error = arr.array('d')
totaldataMerge = totaldataTopE + totaldataTopMu
totaldata = totaldataMerge.Integral()
totaldataMerge.Rebin(14)
datafailMerge = datafailTopE + datafailTopMu
faildata = datafailMerge.Integral()
datafailMerge.Rebin(14)
datafailMerge.Sumw2()
datafailMerge.Divide(totaldataMerge)
frac_ttData_fail = datafailMerge.Integral()
ttData_fraction.append(frac_ttData_fail)
ttData_error.append(datafailMerge.GetBinError(1))
datapassMerge = datapassTopE + datapassTopMu
passdata = datapassMerge.Integral()
datapassMerge.Rebin(14)
datapassMerge.Sumw2()
datapassMerge.Divide(totaldataMerge)
frac_ttData_pass = datapassMerge.Integral()
ttData_fraction.append(frac_ttData_pass)
ttData_error.append(datapassMerge.GetBinError(1))
ttMC_fraction = arr.array('d')
ttMC_error = arr.array('d')
totalMCmerge = totalMCtopE + totalMCtopMu
totalMCmerge.Rebin(14)
MCfailTopE = failMCsubtractTopE.Clone("MCfailTopE")
MCfailTopMu = failMCsubtractTopMu.Clone("MCfailTopMu")
MCfailMerge = MCfailTopE + MCfailTopMu
MCfailMerge.Rebin(14)
MCfailMerge.Sumw2()
MCfailMerge.Divide(totalMCmerge)
frac_Failed_fin = MCfailMerge.Integral()
ttMC_fraction.append(frac_Failed_fin)
ttMC_error.append(MCfailMerge.GetBinError(1))
MCpassTopE = passMCsubtractTopE.Clone("MCpassTopE")
MCpassTopMu = passMCsubtractTopMu.Clone("MCpassTopMu")
MCpassMerge = MCpassTopE + MCpassTopMu
MCpassMerge.Rebin(14)
MCpassMerge.Sumw2()
MCpassMerge.Divide(totalMCmerge)
frac_Passed_fin = MCpassMerge.Integral()
ttMC_fraction.append(frac_Passed_fin)
ttMC_error.append(MCpassMerge.GetBinError(1))
#print "\nttMC_fraction:", ttMC_fraction
#print "ttMC_error:", ttMC_error
sfMerge = datapassMerge.Clone("sfMerge")
sfMerge.Sumw2()
sfMerge.Divide(MCpassMerge)
stacklist = []
stacklist.append(dibosonMerge)
stacklist.append(stMerge)
stacklist.append(wjetsMerge)
stacklist.append(unmatchMerge)
stacklist.append(WmatchMerge)
stacklist.append(topmatchMerge)
print "merge histograms: done"
print " "
print "draw histograms"
print " "
#----------------------- canvas 1 -----------------------#
c1 = TCanvas("c1", "", 800, 900) #width-height
c1.SetTopMargin(0.4)
c1.SetBottomMargin(0.05)
c1.SetRightMargin(0.1)
c1.SetLeftMargin(0.15)
gStyle.SetOptStat(0)
binvalues1 = []
for i in range(14):
binvalue = unsubtractedDataMerge.GetBinContent(i)
binvalues1.append(binvalue)
totalmax = max(binvalues1) + 100
padMain = TPad("padMain", "", 0.0, 0.25, 1.0, 0.97)
padMain.SetTopMargin(0.4)
padMain.SetRightMargin(0.05)
padMain.SetLeftMargin(0.17)
padMain.SetBottomMargin(0.03)
padMain.SetTopMargin(0.1)
padRatio = TPad("padRatio", "", 0.0, 0.0, 1.0, 0.25)
padRatio.SetRightMargin(0.05)
padRatio.SetLeftMargin(0.17)
padRatio.SetTopMargin(0.05)
padRatio.SetBottomMargin(0.3)
padMain.Draw()
padRatio.Draw()
padMain.cd()
gPad.GetUymax()
leg1 = myLegend(coordinate=[0.45, 0.57, 0.65, 0.6])
unsubtractedDataMerge.SetMaximum(totalmax)
unsubtractedDataMerge.SetLineColor(1)
unsubtractedDataMerge.SetMarkerStyle(20)
unsubtractedDataMerge.SetMarkerSize(1.5)
unsubtractedDataMerge.GetXaxis().SetLabelSize(0)
unsubtractedDataMerge.GetXaxis().SetTitleSize(0)
unsubtractedDataMerge.GetXaxis().SetTitle("DDB")
unsubtractedDataMerge.GetYaxis().SetTitle("Events/Bin")
leg1.AddEntry(unsubtractedDataMerge, "Data", "lep")
unsubtractedDataMerge.Draw("e1")
stackhisto = myStack(colorlist_=[627, 800, 854, 813, 822, 821],
backgroundlist_=stacklist,
legendname_=[
"Diboson", "Single Top", "W+Jets",
"Top (unmtch.)", "Top (W-mtch.)", "Top (mtch.)"
])
stackhisto[0].Draw("histsame")
unsubtractedDataMerge.Draw("e1same")
stackhisto[1].Draw()
leg1.Draw()
lt = TLatex()
lt.DrawLatexNDC(0.23, 0.85,
"#scale[0.8]{CMS} #scale[0.65]{#bf{#it{Internal}}}")
if ana_ == "Inclusive":
lt.DrawLatexNDC(0.17, 0.92, "#scale[0.7]{#bf{" + ana_ + "}}")
if ana_ == "PT-200-350" or ana_ == "PT-350-500" or ana_ == "PT-500-2000":
words = ana_.split("-")
if words[2] == "2000":
lt.DrawLatexNDC(0.17, 0.92,
"#scale[0.7]{#bf{p_{T} " + words[1] + "-Inf GeV}}")
else:
lt.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-" +
words[2] + " GeV}}")
else:
words = ana_.split("-")
lt.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{" + words[0] + " " + words[1] + "-" +
words[2] + " GeV}}")
lt.DrawLatexNDC(0.23, 0.8, "#scale[0.7]{#bf{t#bar{t} CR (e+#mu)}}")
lt.DrawLatexNDC(0.23, 0.75, "#scale[0.5]{#bf{2-prong (bq) enriched}}")
if year_ == 2017:
lt.DrawLatexNDC(0.71, 0.92, "#scale[0.7]{#bf{41.5 fb^{-1} (13 TeV)}}")
if year_ == 2018:
lt.DrawLatexNDC(0.71, 0.92,
"#scale[0.7]{#bf{58.827 fb^{-1} (13 TeV)}}")
padRatio.cd()
gPad.GetUymax()
h_totalBkg = topmatchMerge.Clone("h_totalBkg")
h_totalBkg = h_totalBkg + WmatchMerge + unmatchMerge + wjetsMerge + dibosonMerge
ratio = dataPredRatio(data_=unsubtractedDataMerge, totalBkg_=h_totalBkg)
ratio.SetLineColor(1)
ratio.SetLineWidth(3)
ratio.SetMarkerSize(1.5)
ratio.GetXaxis().SetLabelSize(0.13)
ratio.GetXaxis().SetTitleOffset(1)
ratio.GetXaxis().SetTitleSize(0.13)
ratio.GetXaxis().SetTickLength(0.1)
ratio.GetYaxis().SetLabelSize(0.12)
ratio.GetYaxis().SetTitleOffset(0.5)
ratio.GetYaxis().SetTitleSize(0.13)
ratio.GetYaxis().SetNdivisions(405)
ratio.GetYaxis().SetTitle("#frac{Data-Pred}{Pred}")
ratio.GetXaxis().SetTitle("DDB")
ratio.Draw("e1")
c1.SaveAs(dir + "Merge_all.pdf") #
#----------------------- canvas 2 -----------------------#
c2 = myCanvas(c="c2")
gPad.GetUymax()
leg2 = myLegend()
binvalues2 = []
for i in range(14):
binvalue = subtractedDataMerge.GetBinContent(i)
binvalues2.append(binvalue)
ttmax = max(binvalues2) + 50
failMCsubtractMerge.SetMaximum(ttmax)
failMCsubtractMerge.SetFillColor(821)
failMCsubtractMerge.SetLineColor(821) #922
failMCsubtractMerge.GetXaxis().SetTitle("DDB")
failMCsubtractMerge.GetYaxis().SetTitle("Events/Bin")
leg2.AddEntry(failMCsubtractMerge, "t#bar{t}", "f")
passMCsubtractMerge.SetFillColor(622)
passMCsubtractMerge.SetLineColor(622)
#passMCsubtractMerge.GetXaxis().SetTitle("DDB")
#passMCsubtractMerge.GetYaxis().SetTitle("Events/Bin")
leg2.AddEntry(passMCsubtractMerge, "t#bar{t} mistag", "f")
subtractedDataMerge.SetLineColor(1)
subtractedDataMerge.SetMarkerStyle(20)
subtractedDataMerge.SetMarkerSize(1.5)
#subtractedDataMerge.GetXaxis().SetTitle("DDB")
#subtractedDataMerge.GetYaxis().SetTitle("Events/Bin")
leg2.AddEntry(subtractedDataMerge, "Subtracted Data", "lep")
failMCsubtractMerge.Draw("hist")
passMCsubtractMerge.Draw("histsame")
subtractedDataMerge.Draw("e1same")
leg2.Draw()
lt2 = TLatex()
if ana_ == "Inclusive":
lt2.DrawLatexNDC(0.17, 0.92, "#scale[0.7]{#bf{" + ana_ + "}}")
if ana_ == "PT-200-350" or ana_ == "PT-350-500" or ana_ == "PT-500-2000":
words = ana_.split("-")
if words[2] == "2000":
lt2.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-Inf GeV}}")
else:
lt2.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-" +
words[2] + " GeV}}")
else:
words = ana_.split("-")
lt2.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{" + words[0] + " " + words[1] + "-" +
words[2] + " GeV}}")
lt2.DrawLatexNDC(0.23, 0.85,
"#scale[0.8]{CMS} #scale[0.65]{#bf{#it{Internal}}}")
lt2.DrawLatexNDC(0.23, 0.8, "#scale[0.7]{#bf{t#bar{t} CR (e+#mu)}}")
lt2.DrawLatexNDC(0.23, 0.75, "#scale[0.5]{#bf{2-prong (bq) enriched}}")
if year_ == 2017:
lt2.DrawLatexNDC(0.71, 0.92, "#scale[0.7]{#bf{41.5 fb^{-1} (13 TeV)}}")
if year_ == 2018:
lt2.DrawLatexNDC(0.71, 0.92,
"#scale[0.7]{#bf{58.827 fb^{-1} (13 TeV)}}")
c2.SaveAs(dir + "Merged_subtrac.pdf") #
#----------------------- canvas 3 -----------------------#
c3 = myCanvas(c="c3", size=[700, 900])
pad1 = TPad("pad1", "", 0.01, 0.25, 0.93, 1.0)
pad1.SetTopMargin(0.1)
pad1.SetRightMargin(0.05)
pad1.SetLeftMargin(0.17)
pad1.SetBottomMargin(0.05)
pad2 = TPad("pad2", "", 0.0, 0.0, 0.375, 0.24)
pad2.SetTopMargin(0.0)
pad2.SetRightMargin(0.0)
pad2.SetLeftMargin(0.0)
pad2.SetBottomMargin(0.0)
pad3 = TPad("pad3", "", 0.38, 0.025, 0.94, 0.25)
pad2.SetTopMargin(0.05)
pad2.SetRightMargin(0.0)
pad2.SetLeftMargin(0.45)
pad2.SetBottomMargin(0.2)
pad1.Draw()
pad2.Draw()
pad3.Draw()
#* Pad 1 *#
pad1.cd()
leg3 = myLegend(coordinate=[0.65, 0.4, 0.75, 0.5])
xaxisname = arr.array('d', [1, 2])
zero1 = np.zeros(2)
gPad.Modified()
gPad.SetGridy()
gr1 = TGraphErrors(2, xaxisname, ttMC_fraction, zero1, ttMC_error)
gr1.SetTitle("t#bar{t}")
gr1.SetLineColor(870)
gr1.SetLineWidth(3)
gr1.SetMarkerStyle(20)
gr1.SetMarkerColor(870)
leg3.AddEntry(gr1, "t#bar{t}", "lep")
gr2 = TGraphErrors(2, xaxisname, ttData_fraction, zero1, ttData_error)
gr2.SetTitle("t#bar{t} Data")
gr2.SetLineColor(1)
gr2.SetLineWidth(2)
gr2.SetMarkerStyle(20)
gr2.SetMarkerColor(1)
leg3.AddEntry(gr2, "t#bar{t} Data", "lep")
mg = TMultiGraph("mg", "")
mg.Add(gr1)
mg.Add(gr2)
mg.GetHistogram().SetMaximum(1.5)
mg.GetHistogram().SetMinimum(0)
mg.GetYaxis().SetTitle("Fraction")
mg.GetXaxis().SetLimits(0, 3)
mg.GetXaxis().SetTickLength(0.03)
mg.GetXaxis().SetNdivisions(103)
mg.GetXaxis().ChangeLabel(2, -1, -1, -1, -1, -1, "Fail")
mg.GetXaxis().ChangeLabel(1, -1, 0)
mg.GetXaxis().ChangeLabel(-1, -1, 0)
mg.GetXaxis().ChangeLabel(3, -1, -1, -1, -1, -1, "Pass")
mg.Draw("AP")
leg3.Draw()
lt3 = TLatex()
if ana_ == "Inclusive":
lt3.DrawLatexNDC(0.17, 0.92, "#scale[0.7]{#bf{" + ana_ + "}}")
if ana_ == "PT-200-350" or ana_ == "PT-350-500" or ana_ == "PT-500-2000":
words = ana_.split("-")
if words[2] == "2000":
lt3.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-Inf GeV}}")
else:
lt3.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{p_{T} " + words[1] + "-" +
words[2] + " GeV}}")
else:
words = ana_.split("-")
lt3.DrawLatexNDC(
0.17, 0.92, "#scale[0.7]{#bf{" + words[0] + " " + words[1] + "-" +
words[2] + " GeV}}")
lt3.DrawLatexNDC(0.19, 0.855,
"#scale[0.8]{CMS} #scale[0.65]{#bf{#it{Internal}}}")
lt3.DrawLatexNDC(0.19, 0.805, "#scale[0.7]{#bf{t#bar{t} CR (e+#mu)}}")
lt3.DrawLatexNDC(0.19, 0.755, "#scale[0.5]{#bf{2-prong (bq) enriched}}")
if year_ == 2017:
lt3.DrawLatexNDC(0.71, 0.92, "#scale[0.7]{#bf{41.5 fb^{-1} (13 TeV)}}")
if year_ == 2018:
lt3.DrawLatexNDC(0.71, 0.92,
"#scale[0.7]{#bf{58.827 fb^{-1} (13 TeV)}}")
lt3.Draw()
pad1.Update()
#* Pad 2 *#
pad2.cd()
MCpassMerge.SetFillColor(0)
MCpassMerge.SetLineColor(870)
MCpassMerge.SetLineWidth(3)
MCpassMerge.SetMarkerColor(870)
MCpassMerge.SetMarkerStyle(20)
MCpassMerge.GetYaxis().SetTitle("Fraction")
MCpassMerge.GetYaxis().SetTitleSize(0.09)
MCpassMerge.GetYaxis().SetLabelSize(0.1)
MCpassMerge.GetYaxis().SetNdivisions(404)
MCpassMerge.SetMaximum(0.3)
MCpassMerge.SetMinimum(0.0)
MCpassMerge.GetXaxis().SetTitle("")
MCpassMerge.GetXaxis().SetLabelOffset(0.02)
MCpassMerge.GetXaxis().SetLabelSize(0.09)
MCpassMerge.GetXaxis().SetNdivisions(104)
MCpassMerge.GetXaxis().ChangeLabel(2, -1, -1, -1, -1, -1, "Pass")
MCpassMerge.GetXaxis().ChangeLabel(1, -1, 0)
MCpassMerge.GetXaxis().ChangeLabel(-1, -1, 0)
datapassMerge.SetFillColor(0)
datapassMerge.SetLineColor(1)
datapassMerge.SetLineWidth(2)
datapassMerge.SetMarkerColor(1)
datapassMerge.SetMarkerStyle(20)
MCpassMerge.Draw("e1")
datapassMerge.Draw("e1histsame")
#* Pad 3 *#
pad3.cd()
SF = sfMerge.Integral()
print "******"
print "mistag SF:", SF
SFfinal = round(SF, 3)
SFtext = "SF = " + str(SFfinal)
mistagSFmax = SF + 0.2
mistagSFmin = SF - 0.2
sfMerge.SetLineColor(797)
sfMerge.SetMarkerColor(797)
sfMerge.SetLineWidth(3)
sfMerge.SetMaximum(mistagSFmax)
sfMerge.SetMinimum(mistagSFmin)
sfMerge.GetXaxis().SetTitle(" ")
sfMerge.GetXaxis().SetLabelOffset(999)
sfMerge.GetXaxis().SetLabelSize(0)
sfMerge.GetXaxis().SetTickLength(0)
sfMerge.GetYaxis().SetLabelSize(0.1)
sfMerge.GetYaxis().SetNdivisions(404)
sfMerge.GetYaxis().SetTitle(" ")
sfMerge.Draw("e1hist")
pt = TPaveText(0.21, 0.72, 0.31, 0.8, "brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(42)
pt.SetTextSize(0.1)
pt.AddText(SFtext)
pt.Draw()
c3.SaveAs(dir + "Merge_SF.pdf") #
passedBfrSubtactDataMerge = (passedTopEdataBfrSubtract +
passedTopMudataBfrSubtract).Integral()
failedBfrSubtractDataMerge = (failedTopEdataBfrSubtract +
failedTopMudataBfrSubtract).Integral()
passbackground = (wjetsTopEpassed + wjetsTopMupassed + dibosonTopEpassed +
dibosonTopMupassed + stTopEpassed +
stTopMupassed).Integral()
failbackground = (wjetsTopEfailed + wjetsTopMufailed + dibosonTopEfailed +
dibosonTopMufailed + stTopEfailed +
stTopMufailed).Integral()
totalbackground = (wjetsMerge + dibosonMerge + stMerge).Integral()
#get the statistical uncertainty#
dx = ttData_error[1]
print "data efficiency error", dx
dy = ttMC_error[1]
print "MC efficiency error", dy
x = datapassMerge.Integral()
y = MCpassMerge.Integral()
statUnc = TMath.Sqrt(((dx**2) / (y**2)) + ((x**2) * (dy**2) / (y**4)))
#print "statistical Uncertainty in Top (e+muon) CR", statUnc
#print " "
print "relative statistical Uncertainty in Top (e+muon) CR", statUnc / SF * 100, " %"
print " "
print "DDB Mistag SF and stat: ", round(SF, 3), " +- ", round(statUnc,
3), " (stat)"
#print "theoretical statistical uncertainty of data efficiency", TMath.Sqrt((x*(1-x))/(subtractedDataMerge.Integral()))
#print "theoretical statistical uncertainty of MC efficiency", TMath.Sqrt((y*(1-y))/(totalMCmerge.Integral()))
#print " "
header = ["Process", "Number of Events", "Top (e+muon)"]
row1 = [
" ", "DDB mistag SF",
str(SFfinal) + " +- " + str(round(statUnc, 3)) + " (stat)"
]
row2 = ["tt MC", "Pass (not normalized)", ""]
row3 = [
" ", "Pass (normalized)",
str(round(passMCsubtractMerge.Integral(), 2))
]
row4 = [" ", "Fail (not normalized)", ""]
row5 = [
" ", "Fail (normalized)",
str(round(failMCsubtractMerge.Integral(), 2))
]
row6 = [" ", "Total (not normalized)", ""]
row7 = [" ", "Total (normalized)", str(round(totalMCmerge.Integral(), 2))]
inforMC = [row2, row3, row4, row5, row6, row7]
row8 = [
"tt DATA", "Pass (before subtraction)",
str(round(passedBfrSubtactDataMerge, 2))
]
row9 = [" ", "Pass (after subtraction)", str(round(passdata, 2))]
row10 = [
" ", "Fail (before subtraction)",
str(round(failedBfrSubtractDataMerge, 2))
]
row11 = [" ", "Fail (after subtraction)", str(round(faildata, 2))]
row12 = [
" ", "Total (before subtraction)",
str(round(unsubtractedDataMerge.Integral(), 2))
]
row13 = [" ", "Total (after subtraction)", str(round(totaldata, 2))]
inforDATA = [row8, row9, row10, row11, row12, row13]
row14 = ["Background", "Pass (normalized)", str(round(passbackground, 2))]
row15 = [" ", "Fail (normalized)", str(round(failbackground, 2))]
row16 = [" ", "Total (normalized)", str(round(totalbackground, 2))]
inforBKG = [row14, row15, row16]
DDB_mistagSF.makeTable(header, row1, inforMC, inforDATA, inforBKG)
def make_time_rod_evo(error_dict, rod_dict, results, doLock):
c2 = TCanvas( 'c2', 'c2', 1000, 600)
leg = TLegend(0.18,0.85,0.45,0.55)
leg.SetLineColor(0)
leg.SetFillStyle(0)
leg.SetShadowColor(0)
leg.SetBorderSize(0)
leg.SetNColumns(2)
R15 = TLine(431,0,431,60)
R15.SetLineColorAlpha(kPink+10,0.4)
R15.SetLineWidth(4)
R16 = TLine(1820,0,1820,60)
R16.SetLineColorAlpha(kMagenta+10,0.4)
R16.SetLineWidth(4)
R17 = TLine(3376,0,3376,60)
R17.SetLineColorAlpha(kGreen-3,0.4)
R17.SetLineWidth(4)
TS1 = TLine(431,0,432,60)
TS1.SetLineColorAlpha(kPink+10,0.5)
TS1.SetLineWidth(5)
TS2 = TLine(1415,0,1415,60)
TS2.SetLineColorAlpha(kMagenta+3,0.5)
TS2.SetLineWidth(5)
leg2 = TLegend(0.18,0.45,0.35,0.55)
leg2.SetLineColor(0)
leg2.SetFillStyle(0)
leg2.SetShadowColor(0)
leg2.SetBorderSize(0)
gStyle.SetLegendTextSize(0.030)
leg2.AddEntry(R15, "End of 2015", 'lf')
leg2.AddEntry(R16, "End of 2016", 'lf')
leg2.AddEntry(R17, "End of 2017", 'lf')
#leg2.AddEntry(TS2, "TS2", 'lf')
for key,val in rod_dict.items():
TS1.SetY2(val*0.5)
TS2.SetY2(val+1)
R15.SetY2(val*0.3)
R16.SetY2(val*0.5)
R17.SetY2(val*0.8)
times = {}
times.clear()
for e in error_bits:
times['0x'+e] = [0]
for error in results:
pos_rod = error.text.find("ROD") + 4
pos_lock = error.text.find("Lock") + 15
pos_buff = error.text.find("buffer") + 17
if error.msgID == 'TRT::ROD05Module':
rod = '0x'+str(error.text[pos_rod:pos_rod+6])
else:
rod = str(error.text[pos_rod:pos_rod+8])
lock = str(error.text[pos_lock:pos_lock+3])
buff = str(error.text[pos_buff:pos_buff+3])
if key == rod and doLock and lock != '0xf':
times[lock].append(error.sb_total_time)
leg.Clear()
mg = TMultiGraph()
for e in error_bits:
errs = []
for i,x in enumerate(times['0x'+e]):
errs.append(i+0.0)
errs.append(errs[-1])
#times['0x'+e].append(1800.0)
times['0x'+e].append(results[-1].sb_total_time)
gr = TGraph(len(times['0x'+e]), array(times['0x'+e]), array(errs))
gr.SetMarkerSize(0.7)
if bin(int('0x'+e, 16))[2:].zfill(4) == '0111':
leg.AddEntry(gr,'GOL 3',"lp");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1011':
leg.AddEntry(gr,'GOL 2',"lp");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1101':
leg.AddEntry(gr,'GOL 1',"lp");
elif bin(int('0x'+e, 16))[2:].zfill(4) == '1110':
leg.AddEntry(gr,'GOL 0',"lp");
else:
leg.AddEntry(gr,bin(int('0x'+e, 16))[2:].zfill(4),"lp");
mg.Add(gr,"pl");
mg.SetTitle("; Hours of stable beams; # of rocketio io lock errors");
mg.Draw("PMC PLC a");
R15.Draw()
R16.Draw()
R17.Draw()
#TS1.Draw()
#TS2.Draw()
AtlasStyle.ATLAS_LABEL(0.19,.88, 1, "Internal")
leg.Draw()
leg2.Draw()
AtlasStyle.myText(0.4, 0.88, kBlack, "ROD: " + key)
leg.SetMargin(0.5)
gPad.Modified()
mg.GetXaxis().SetLimits(0,results[-1].sb_total_time)
mg.SetMinimum(0.)
mg.SetMaximum(val+1)
c2.Update()
c2.Print("plots/time_"+key+".pdf")
c2.Clear()
def plotPostFitValues(channel,var,DM,year,*parameters,**kwargs):
"""Draw post-fit values for parameter using MultiDimFit and FitDiagnostics output."""
if DM=='DM0' and 'm_2' in var: return
print green("\n>>> plotPostFitValues %s, %s"%(DM, var))
if len(parameters)==1 and isinstance(parameters[0],list): parameters = parameters[0]
parameters = [p.replace('$CAT',DM).replace('$CHANNEL',channel) for p in list(parameters)]
title = kwargs.get('title', "" )
name = kwargs.get('name', "" )
indir = kwargs.get('indir', "output_%d"%year )
outdir = kwargs.get('outdir', "postfit_%d"%year )
tag = kwargs.get('tag', "" )
plotlabel = kwargs.get('plotlabel', "" )
compareFD = kwargs.get('compareFD', False ) and N==1
era = "%d-13TeV"%year
isBBB = any("_bin_" in p for p in parameters)
filename = '%s/higgsCombine.%s_%s-%s%s-%s.MultiDimFit.mH90.root'%(indir,channel,var,DM,tag,era)
filenamesFD = '%s/fitDiagnostics.%s_%s-%s%s-%s_TES*p*.root'%(indir,channel,var,DM,tag,era)
ensureDirectory(outdir)
if not name:
name = formatParameter(parameters[0]).replace('_'+DM,'')
if len(parameters)>1:
name = "comparison_%s"%(name) #re.sub(r"bin_\d+","bin",name)
canvasname = "%s/postfit-%s_%s_%s%s%s"%(outdir,name,var,DM,tag,plotlabel)
print '>>> file "%s"'%(filename)
graphs = [ ]
graphsFD = [ ]
tvals = [ ]
pvals = [ -2.2, +2.2 ]
tes = measureTES(filename)
for parameter in parameters[:]:
graph = getTGraphOfParameter(filename,'tes',parameter,xvals=tvals,yvals=pvals)
if graph:
graphs.append(graph)
else:
parameters.remove(parameter)
if compareFD:
graphFD = getTGraphOfParameter_FD(filenamesFD,parameter,xvals=tvals,yvals=pvals)
if graphFD: graphsFD.append(graphFD)
if len(parameters)!=len(graphs):
warning("plotPostFitValues: len(parameters) = %d != %d = len(graphs)"%(len(parameters),len(graphs)))
exit(1)
N = len(parameters)
compareFD = compareFD and len(graphsFD)>0
parameters = [formatParameter(p).replace('_'+DM,'') for p in parameters]
graphsleg = columnize(graphs,3) if N>6 else columnize(graphs,2) if N>3 else graphs # reordered for two columns
paramsleg = columnize(parameters,3) if N>6 else columnize(parameters,2) if N>3 else parameters # reordered for two columns
xtitle = 'tau energy scale'
ytitle = "%s post-fit value"%(parameters[0] if N==1 else "MultiDimFit")
xmin, xmax = min(tvals), max(tvals)
ymin, ymax = min(pvals), max(pvals)
colors = [ kBlack, kBlue, kRed, kGreen, kMagenta, kOrange, kTeal, kAzure+2, kYellow-3 ]
canvas = TCanvas("canvas","canvas",100,100,800,650)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetTopMargin( 0.07 ); canvas.SetBottomMargin( 0.13 )
canvas.SetLeftMargin( 0.11 ); canvas.SetRightMargin( 0.05 )
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
canvas.cd()
maxmargin = 0.18*abs(ymax-ymin)
minmargin = 0.20*abs(ymax-ymin) #(0.20 if N<5 else 0.10*ceil(N/2))
ymin = 0.0 if ymin>=0 else ymin-minmargin
ymax = ymax + minmargin
textsize = 0.045 if N==1 else 0.036
lineheight = 0.055 if N==1 else 0.045
x1, width = 0.42, 0.25
y1, height = 0.15, lineheight*(ceil(N/3.) if N>6 else ceil(N/2.) if N>3 else N)
if title: height += lineheight
if compareFD: height += lineheight
if N>6:
if isBBB: width = 0.62; x1 = 0.25
else: width = 0.70; x1 = 0.20
elif N>3: width = 0.52; x1 = 0.36
legend = TLegend(x1,y1,x1+width,y1+height)
legend.SetTextSize(textsize)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
if title:
legend.SetTextFont(62)
legend.SetHeader(title)
legend.SetTextFont(42)
if N>6:
legend.SetNColumns(3)
legend.SetColumnSeparation(0.02)
elif N>3:
legend.SetNColumns(2)
legend.SetColumnSeparation(0.03)
frame = canvas.DrawFrame(xmin,ymin,xmax,ymax)
frame.GetYaxis().SetTitleSize(0.060)
frame.GetXaxis().SetTitleSize(0.060)
frame.GetXaxis().SetLabelSize(0.050)
frame.GetYaxis().SetLabelSize(0.050)
frame.GetXaxis().SetLabelOffset(0.01)
frame.GetYaxis().SetLabelOffset(0.01)
frame.GetXaxis().SetTitleOffset(0.98)
frame.GetYaxis().SetTitleOffset(0.84)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetTitle(xtitle)
for i, (parameter,graph) in enumerate(zip(parameters,graphs)):
graph.SetLineColor(colors[i%len(colors)])
graph.SetLineWidth(2)
graph.SetLineStyle(1)
graph.Draw('LSAME')
for parameter,graph in zip(paramsleg,graphsleg):
if N==1:
legend.AddEntry(graph, "MultiDimFit", 'l')
else:
legend.AddEntry(graph, parameter, 'l')
line = TLine(tes, ymin, tes, ymax)
#line.SetLineWidth(1)
line.SetLineStyle(7)
line.Draw('SAME')
latex = TLatex()
latex.SetTextSize(0.045)
latex.SetTextAlign(13)
latex.SetTextFont(42)
latex.DrawLatex(tes+0.02*(xmax-xmin),ymax-0.04*(ymax-ymin),"tes = %.3f"%tes)
if compareFD:
graphFD.SetLineColor(kBlue)
graphFD.SetLineWidth(2)
graphFD.SetLineStyle(2)
graphFD.Draw('LSAME')
legend.AddEntry(graphFD, "FitDiagnostics", 'l')
legend.Draw()
CMS_lumi.relPosX = 0.12
CMS_lumi.CMS_lumi(canvas,13,0)
gPad.SetTicks(1,1)
gPad.Modified()
frame.Draw('SAMEAXIS')
canvas.SaveAs(canvasname+".png")
if args.pdf: canvas.SaveAs(canvasname+".pdf")
canvas.Close()
def plotCorrelation(channel,var,DM,year,*parameters,**kwargs):
"""Calculate and plot correlation between parameters."""
if DM=='DM0' and 'm_2' in var: return
print green("\n>>> plotCorrelation %s, %s"%(DM, var))
if len(parameters)==1 and isinstance(parameters[0],list): parameters = parameters[0]
parameters = [p.replace('$CAT',DM).replace('$CHANNEL',channel) for p in list(parameters)]
title = kwargs.get('title', "" )
name = kwargs.get('name', "" )
indir = kwargs.get('indir', "output_%d"%year )
outdir = kwargs.get('outdir', "postfit_%d"%year )
tag = kwargs.get('tag', "" )
plotlabel = kwargs.get('plotlabel', "" )
order = kwargs.get('order', False )
era = "%d-13TeV"%year
filename = '%s/higgsCombine.%s_%s-%s%s-%s.MultiDimFit.mH90.root'%(indir,channel,var,DM,tag,era)
ensureDirectory(outdir)
print '>>> file "%s"'%(filename)
# HISTOGRAM
parlist = getParameters(filename,parameters)
if order:
parlist.sort(key=lambda x: -x.sigma)
N = len(parlist)
hist = TH2F("corr","corr",N,0,N,N,0,N)
for i in xrange(N): # diagonal
hist.SetBinContent(i+1,N-i,1.0)
hist.GetXaxis().SetBinLabel(1+i,parlist[i].title)
hist.GetYaxis().SetBinLabel(N-i,parlist[i].title)
for xi, yi in combinations(range(N),2): # off-diagonal
r = parlist[xi].corr(parlist[yi])
hist.SetBinContent(1+xi,N-yi,r)
hist.SetBinContent(1+yi,N-xi,r)
#print "%20s - %20s: %5.3f"%(par1,par2,r)
#hist.Fill(par1.title,par2.title,r)
#hist.Fill(par2.title,par1.title,r)
# SCALE
canvasH = 160+64*max(10,N)
canvasW = 300+70*max(10,N)
scaleH = 800./canvasH
scaleW = 1000./canvasW
scaleF = 640./(canvasH-160)
tmargin = 0.06
bmargin = 0.14
lmargin = 0.22
rmargin = 0.12
canvas = TCanvas('canvas','canvas',100,100,canvasW,canvasH)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetTopMargin( tmargin ); canvas.SetBottomMargin( bmargin )
canvas.SetLeftMargin( lmargin ); canvas.SetRightMargin( rmargin )
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
canvas.cd()
frame = hist
frame.GetXaxis().SetLabelSize(0.054*scaleF)
frame.GetYaxis().SetLabelSize(0.072*scaleF)
frame.GetZaxis().SetLabelSize(0.034)
frame.GetXaxis().SetLabelOffset(0.005)
frame.GetYaxis().SetLabelOffset(0.003)
frame.GetXaxis().SetNdivisions(508)
#gStyle.SetPalette(kBlackBody)
#frame.SetContour(3);
gStyle.SetPaintTextFormat(".2f")
frame.SetMarkerSize(1.5*scaleF)
#frame.SetMarkerColor(kRed)
hist.Draw('COLZ TEXT')
# TEXT
if title:
latex = TLatex()
latex.SetTextSize(0.045)
latex.SetTextAlign(33)
latex.SetTextFont(42)
latex.DrawLatexNDC(0.96*lmargin,0.80*bmargin,title)
CMS_lumi.relPosX = 0.14
CMS_lumi.CMS_lumi(canvas,13,0)
gPad.SetTicks(1,1)
gPad.Modified()
frame.Draw('SAMEAXIS')
canvasname = "%s/postfit-correlation_%s_%s%s%s"%(outdir,var,DM,tag,plotlabel)
canvas.SaveAs(canvasname+".png")
if args.pdf: canvas.SaveAs(canvasname+".pdf")
canvas.Close()
def TwoFileSAME2VsLumi(F1graph1, F1graph2, F2graph1, F2graph2, title, type):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
F1graph1.SetMarkerColor(kBlue)#electrons
F1graph2.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerColor(kBlue)#electrons
F2graph2.SetMarkerColor(kRed)#muons
F2graph1.SetMarkerStyle(kOpenStar)
F2graph2.SetMarkerStyle(kOpenStar)
multigraph = TMultiGraph()
multigraph.Add(F1graph1,"AP")
multigraph.Add(F1graph2,"AP")
multigraph.Add(F2graph1,"AP")
multigraph.Add(F2graph2,"AP")
multigraph.Draw("AP")
multigraph.GetXaxis().SetLimits(0.,40.)
#TGaxis.SetMaxDigits(2)
#TGaxis.SetExponentOffset(-0.06, 0.02, "y")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetYaxis().SetTitleOffset(1.4)
if(type == "ISO"):
multigraph.GetYaxis().SetTitle("Isolation")
gPad.Modified()
multigraph.SetMinimum(0.5*gPad.GetUymin())
multigraph.SetMaximum(1.5*gPad.GetUymax())
elif(type == "SIP"):
multigraph.GetYaxis().SetTitle("SIP")
printLumiPrelOut(canvas)
canvas.Update()
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.57,down,5.57, up)
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.58,down,8.58,up)
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.9,down,12.9,up)
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.57,down,16.57,up)
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.7,down,19.7,up)
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(26.9,down,26.9,up)
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
legend = TLegend(0.80,0.75,0.965,0.93)
legend.AddEntry(F1graph1,"e^{+}e^{-}","P")
legend.AddEntry(F1graph2,"#mu^{+}#mu^{-}","P")
legend.AddEntry(F2graph1,"e^{+}e^{-} ICHEP","P")
legend.AddEntry(F2graph2,"#mu^{+}#mu^{-} ICHEP","P")
legend.SetTextFont(32)
legend.Draw()
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
def main():
parser = ArgumentParser(description='Scan over ROOT files to find the '+ \
'lumisections belonging to a specific run.')
parser.add_argument('-b', action='store_true', help='enable batch mode')
parser.add_argument('--dataset', required=True, choices=['PromptReco2015', \
'ReRecoOct2015', 'ReRecoDec2015', 'PromptReco2016', \
'2015ReRecoJan2017', '2016ReRecoJan2017'], \
help='specify data-taking period and reconstruction')
parser.add_argument('-n', nargs=1, default=1, type=int, help='Specify '+ \
'the number of ZeroBias datasets to be included')
parser.add_argument('-run', nargs=1, required=True, type=int, \
help='Specify the run number for the selection of '+ \
'the lumisections')
parser.add_argument('-range', nargs=2, type=int, help='Specify a range '+ \
'in lumisections for the histogram')
parser.add_argument('-X', dest='coords', action='append_const', \
const='vtx_x', help='look for vtx_x')
parser.add_argument('-Y', dest='coords', action='append_const', \
const='vtx_y', help='look for vtx_y')
parser.add_argument('-noscan', action='store_const', const=True, \
default=False, help='don\'t repeat the scan of the '+ \
'ROOT files, just do the plotting')
parser.add_argument('-title', nargs=1, help='Specify a title for the '+ \
'histogram')
args = parser.parse_args()
from importlib import import_module
from lsctools import config
from lsctools.config import options as O, EOSPATH as eos
from lsctools.tools import openRootFileU, closeRootFile, writeFiles, \
plotName, plotTitle, loadFiles, plotPath, \
drawSignature
from lsctools.prepare import loopOverRootFiles
from ROOT import TChain, TObject, TProfile, TCanvas, gStyle, gPad
getattr(config, 'PCC' + args.dataset)()
O['fulltrees'] = O['fulltrees'][:args.n]
run = args.run[0]
files = []
if args.noscan:
files = loadFiles('fulltrees_' + str(run))
else:
def action(tree, filename):
condition = 'run == ' + str(run)
if tree.GetEntries(condition) > 0:
files.append(filename)
print '<<< Found file:', filename
loopOverRootFiles(action, 'fulltrees')
writeFiles(files, 'fulltrees_' + str(run))
chain = TChain(O['treename']['fulltrees'])
for filename in files:
chain.Add(eos + filename)
name = 'vtxPos_perLS'
title1 = 'run' + str(run) + '_perLS'
title2 = 'Run ' + str(run)
if (args.title):
title2 = args.title[0] + ' (' + title2 + ')'
f = openRootFileU(name)
if args.range:
mini = args.range[0]
maxi = args.range[1]
title1 += '_from' + str(mini) + 'to' + str(maxi)
else:
print '<<< Get minimum lumisection'
mini = int(chain.GetMinimum('LS'))
print '<<< Get maximum lumisection'
maxi = int(chain.GetMaximum('LS'))
for coord in args.coords:
print '<<< Analyze coordinate', coord
histname = plotName(coord + '_' + title1, timestamp=False)
histtitl = plotTitle('- ' + title2)
histfile = plotName(coord + '_' + title1)
histpath = plotPath(coord + '_' + title1)
hist = TProfile(histname, histtitl, maxi - mini + 1, mini - 0.5,
maxi + 0.5)
chain.Draw(coord + '*1e4:LS>>' + histname, 'run == ' + str(run),
'goff')
hist.Write('', TObject.kOverwrite)
print '<<< Save plot:', histpath
canvas = TCanvas()
gStyle.SetOptStat(0)
hist.Draw()
hist.GetXaxis().SetTitle('LS')
hist.GetYaxis().SetTitle(coord + ' [#mum]')
hist.GetYaxis().SetTitleOffset(1.2)
for axis in [hist.GetXaxis(), hist.GetYaxis()]:
axis.SetTitleFont(133)
axis.SetTitleSize(16)
axis.SetLabelFont(133)
axis.SetLabelSize(12)
axis.CenterTitle()
drawSignature(histfile)
gPad.Modified()
gPad.Update()
canvas.Print(histpath)
canvas.Close()
closeRootFile(f, name)
def doPlots(f, f_sim, name):
plots = []
cwm = plot()
cwm.name = "chargeWeightedMean"
cwm.lowerBoundary = 0
cwm.upperBoundary = 90
cwm.nBins = 180
cwm.xAxisLabel = "Charge weighted mean"
cwm.yAxisLabel = "Events / " + cwm.binWidth()
#plots.append(cwm)
hwm = plot()
hwm.name = "hitWeightedMean"
hwm.lowerBoundary = 0
hwm.upperBoundary = 90
hwm.nBins = 180
hwm.xAxisLabel = "Hit weighted mean"
hwm.yAxisLabel = "Events / " + hwm.binWidth()
#plots.append(hwm)
sc = plot()
sc.name = "sumCharge"
sc.lowerBoundary = 0
sc.upperBoundary = 80
sc.nBins = 80
sc.xAxisLabel = "Cluster charge"
sc.yAxisLabel = "Events / " + sc.binWidth()
plots.append(sc)
mc = plot()
mc.name = "maxCharge"
mc.lowerBoundary = 0
mc.upperBoundary = 40
mc.nBins = 40
mc.xAxisLabel = "Seed charge"
mc.yAxisLabel = "Events / " + mc.binWidth()
plots.append(mc)
cs = plot()
cs.name = "clusterSize"
cs.lowerBoundary = 0
cs.upperBoundary = 10
cs.nBins = 10
cs.xAxisLabel = "Cluster Size"
cs.yAxisLabel = "Events / " + cs.binWidth()
plots.append(cs)
can = TCanvas()
#can.SaveAs("clusterPlots_Pos" + cfg.position + ".pdf[")
can.SaveAs(name + ".pdf[")
for p in plots:
hist = TH1D(p.name, p.name, p.nBins, p.lowerBoundary, p.upperBoundary)
hist_sim = TH1D(p.name + "_sim", p.name + "_sim", p.nBins,
p.lowerBoundary, p.upperBoundary)
#if p.name=="sumCharge":
# reweightHist(hist_sim, 1.2)
#distance_from_track = 0 +/- 400
t.Draw(p.name + ">>" + p.name,
"distance_from_track<300&&distance_from_track>-300", "")
t_sim.Draw(p.name + ">>" + p.name + "_sim")
hist.GetXaxis().SetTitle(p.xAxisLabel)
hist.GetYaxis().SetTitle(p.yAxisLabel)
hist.SetStats(True)
hist_sim.GetXaxis().SetTitle(p.xAxisLabel)
hist_sim.GetYaxis().SetTitle(p.yAxisLabel)
hist_sim.SetStats(True)
hist_sim.SetMarkerColor(kRed)
hist_sim.SetLineColor(kRed)
hist_sim.SetMarkerStyle(kOpenCircle)
hist.SetName("Data")
hist_sim.SetName("Simulation")
hist.Draw("e")
can.Update()
statbox = hist.GetListOfFunctions().FindObject('stats')
#"""Moves the statbox to a new location. Uses the NDC coordinates where the canvas is 1 wide and tall, (0,0) is the bottom left."""
if not p.name == "sumCharge":
statbox.SetY1NDC(0.4)
statbox.SetY2NDC(0.6)
else:
statbox.SetX1NDC(0.5)
statbox.SetX2NDC(0.7)
hist_sim.Draw("e")
can.Update()
statbox_sim = hist_sim.GetListOfFunctions().FindObject('stats')
statbox_sim.SetTextColor(kRed)
#if hist.GetMaximum() > hist_sim.GetMaximum():
if hist.GetMaximum() / hist.GetEntries() > hist_sim.GetMaximum(
) / hist_sim.GetEntries():
hist.DrawNormalized("e")
gPad.Modified()
hist_sim.DrawNormalized("esames")
else:
hist_sim.DrawNormalized("e")
gPad.Modified()
hist.DrawNormalized("esames")
#hist.Draw("esames")
#can.SaveAs("clusterPlots_Pos" + cfg.position + ".pdf")
can.SaveAs(name + ".pdf")
#hist = f.Get("clusterShape")
#hist_sim = f_sim.Get("clusterShape")
#
#hist.GetXaxis().SetRangeUser(0, 10)
#hist_sim.GetXaxis().SetRangeUser(0, 10)
#
#hist.GetYaxis().SetRangeUser(0, 50)
#hist_sim.GetYaxis().SetRangeUser(0, 50)
#
#hist.GetXaxis().SetTitle("Channel relative to seed")
#hist.GetYaxis().SetTitle("Adc response")
#hist.SetName("Data")
#hist.SetStats(True)
#
#hist_sim.GetXaxis().SetTitle("Channel relative to seed")
#hist_sim.GetYaxis().SetTitle("Adc response")
#hist_sim.SetName("Simulation")
#hist_sim.SetStats(True)
#
#hist_sim.SetMarkerColor(kRed)
#hist_sim.SetLineColor(kRed)
#hist_sim.SetMarkerStyle(kOpenCircle)
#
#
#
#hist.Draw("e")
#can.Update()
#statbox = hist.GetListOfFunctions().FindObject('stats')
##statbox.SetLabel("Data")
##hist_sim.Draw("e")
##statbox_sim = hist_sim.GetListOfFunctions().FindObject('stats')
##statbox_sim.SetName("Simulation")
#
#statbox.SetX1NDC(0.2)
#statbox.SetX2NDC(0.4)
##statbox.SetY1NDC(y1)
##statbox.SetY2NDC(y2)
#
#hist_sim.Draw("e")
#can.Update()
#statbox_sim = hist_sim.GetListOfFunctions().FindObject('stats')
#statbox_sim.SetTextColor(kRed)
#
#
#
#
#if hist.GetMaximum() > hist_sim.GetMaximum():
# hist.Draw("e")
# gPad.Modified()
# hist_sim.Draw("esames")
#else:
# hist_sim.Draw("e")
# gPad.Modified()
# hist.Draw("esames")
#
#
#
#
#can.SaveAs("clusterPlots_Pos" + cfg.position + ".pdf")
can.SaveAs(name + ".pdf]")
def plotUpperLimits(labels, masses, **kwargs):
print color("plotUpperLimits()", color="magenta", prepend=">>>\n>>> ")
# https://raw.githubusercontent.com/nucleosynthesis/HiggsAnalysis-CombinedLimit/combine_tutorial_SWAN/combine_tutorials_2016/combine_intro/plotPvalue.py
# SIGNAL strength & mass
extralabel = kwargs.get('extralabel', "")
# LOOP over LABELS
for label in labels:
print color("plotUpperLimits - %s" % (label),
color="grey",
prepend="\n>>> ")
N = len(masses)
yellow = TGraph(2 * N) # yellow band
green = TGraph(2 * N) # green band
median = TGraph(N) # median line
up2s = []
down2s = []
for i, mass in enumerate(masses):
filename = getOutputFilename(label, mass, extralabel=extralabel)
limits = getLimits(filename)
yellow.SetPoint(i, mass, limits[4]) # + 2 sigma
green.SetPoint(i, mass, limits[3]) # + 1 sigma
median.SetPoint(i, mass, limits[2]) # median
green.SetPoint(2 * N - 1 - i, mass, limits[1]) # - 1 sigma
yellow.SetPoint(2 * N - 1 - i, mass, limits[0]) # - 2 sigma
down2s.append(limits[0])
up2s.append(limits[4])
ymax = max(up2s) * 1.20
ymin = min(down2s)
doLog = ymin and ymax / min(down2s) > 4
xtitle = "m_{X} [GeV]"
ytitle = "95% upper limit on #sigma#timesBR(X #rightarrow #tau#tau) [pb]"
if "bbA" in extralabel:
xtitle = "m_{A} [GeV]"
ytitle = "95% upper limit on #sigma#timesBR(A #rightarrow #tau#tau) [pb]"
W, H = 800, 600
T, B = 0.08 * H, 0.12 * H
L, R = 0.12 * W, 0.04 * W
canvas = TCanvas("canvas", "canvas", 100, 100, W, H)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetTopMargin(T / H)
canvas.SetBottomMargin(B / H)
canvas.SetLeftMargin(L / W)
canvas.SetRightMargin(R / W)
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
canvas.cd()
if doLog:
ymin = 0.1 #10**(floor(log(ymin,10))-1)
ymax = 1000 #10**(ceil(log(ymax,10))+1)
#ymin, ymax = 0.1, 1000
canvas.SetLogy()
else:
ymin *= 0 if ymin > 0 else 1.20
frame = canvas.DrawFrame(min(masses), ymin, max(masses), ymax)
frame.GetYaxis().SetTitleSize(0.055)
frame.GetXaxis().SetTitleSize(0.055)
frame.GetXaxis().SetLabelSize(0.044)
frame.GetYaxis().SetLabelSize(0.044)
frame.GetXaxis().SetLabelOffset(0.010)
frame.GetXaxis().SetTitleOffset(1.04)
frame.GetYaxis().SetTitleOffset(1.08)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetTitle(xtitle)
yellow.SetFillColor(kOrange)
yellow.SetLineColor(kOrange)
yellow.SetFillStyle(1001)
yellow.Draw('F')
green.SetFillColor(kGreen + 1)
green.SetLineColor(kGreen + 1)
green.SetFillStyle(1001)
green.Draw('Fsame')
median.SetLineColor(1)
median.SetLineWidth(2)
median.SetLineStyle(2)
median.Draw('Lsame')
CMS_lumi.CMS_lumi(canvas, 13, 0)
gPad.SetTicks(1, 1)
gPad.Modified()
frame.Draw('sameaxis')
width = 0.28
height = 0.20
#x1 = 0.16; x2 = x1 + width # Left
x2 = 0.80
x1 = x2 - width # Right
x2 = x1 + width
y1 = 0.68
y2 = y1 + height
legend = TLegend(x1, y1, x2, y2)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.040)
legend.SetTextFont(62)
legend.SetHeader("%s" % (label_dict[label + extralabel]))
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 " "
canvas.SaveAs("%s/upperLimit-%s%s.png" %
(PLOTS_DIR, label, extralabel))
canvas.SaveAs("%s/upperLimit-%s%s%s.pdf" %
(PLOTS_DIR, label, extralabel))
canvas.Close()
def overlap(outdir, file1, file2 = 0):
file_1 = TFile(file1, "r")
# file_2 = TFile(file2, "r")
h_name = ["h_mass_sum_reco_jet_cone", "h_mass_pair_reco_jet_cone1", "h_mass_pair_reco_jet_cone2", "h_mass_true_reco_jet_cone"]
for h in h_name:
h_good = h + "_good"
h_bad = h + "_wrong"
cname = "c_"+ h + "good_bad_jet_association"
canvas_name = TCanvas(cname, "c_", 800, 600)
canvas_name.cd()
file_1.cd()
h_1 = gDirectory.Get(h_good)
# h_reco1 = gDirectory.Get(h_reco)
# file_2.cd()
h_2 = gDirectory.Get(h_bad)
# h_reco2 = gDirectory.Get(h_reco)
h_1.SetLineColor(4)
# h_reco1.SetLineColor(2)
h_2.SetLineColor(2)
# h_reco2.SetLineColor(6)
# if (h == "h_beta_"):
# h_reco2.Draw("HIST E")
# h_gen2.Draw("HIST E SAMES")
# else :
# h_gen2.Draw("HIST E")
# h_reco2.Draw("HIST E SAMES")
h_1.Draw("HIST E")
h_2.Draw("HIST E SAMES")
# # # h_reclu.GetYaxis().SetRangeUser(0, 0.21)
# # h_reclu.GetXaxis().SetRangeUser(-20, 20)
# # h_reclu.GetXaxis().SetTitle("M_{comp} - M_{true} [GeV]")
# # # fit_1.Draw("SAMES")
# # # fit_2.Draw("SAMES")
# # # if file3:
# # h_3.Draw("HIST E sames")
# # # fit_3.Draw("SAMES")
gPad.Update()
stat_2 = h_2.GetListOfFunctions().FindObject("stats")
# stat_2.SetOptStat(0000)
stat_2.SetX1NDC(0.75)
stat_2.SetX2NDC(0.9)
stat_2.SetY1NDC(0.6)
stat_2.SetY2NDC(0.75)
stat_2.SetTextColor(2)
stat_2.SetBorderSize(2)
# stat_2.SetTitle("162.3 GeV Fit")
gPad.Modified()
gPad.Update()
stat_1 = h_1.GetListOfFunctions().FindObject("stats")
stat_1.SetX1NDC(0.75)
stat_1.SetX2NDC(0.9)
stat_1.SetY1NDC(0.45)
stat_1.SetY2NDC(0.6)
stat_1.SetTextColor(4)
stat_1.SetBorderSize(4)
# stat_1.SetTitle("240 GeV Fit")
gPad.Modified()
gPad.Update()
# # stat_3 = h_3.GetListOfFunctions().FindObject("stats")
# # stat_3.SetX1NDC(0.75)
# # stat_3.SetX2NDC(0.9)
# # stat_3.SetY1NDC(0.30)
# # stat_3.SetY2NDC(0.45)
# # #stat_3.SetTitle("240 GeV Fit")
# # gPad.Modified()
# # gPad.Update()
mylegend = TLegend(0.15, 0.7, 0.4, 0.85)
mylegend.SetFillColor(0)
mylegend.SetBorderSize(2)
mylegend.SetTextSize(0.02)
mylegend.AddEntry(h_1, "good jets pairing", "l")
mylegend.AddEntry(h_2, "wrong jets pairing", "l")
# mylegend.AddEntry(h_gen2, "gen jets without cuts (curr.)", "l")
# mylegend.AddEntry(h_reco2, "reco jets without cuts (curr.)", "l")
mylegend.Draw()
# # l = TLatex()
# # l.SetTextSize(0.04)
# # l.SetTextColor(16)
# # l.DrawLatex(-18, 1500, "Preliminary results")
# # l.DrawLatex(-18, 1900, "Without Detector")
# # canvas_name.Update()
raw_input("hit a key to exit")
# write into the output file and close the file
outfilename = "{}.root".format(outdir)
outfile = TFile(outfilename, "UPDATE")
canvas_name.Write("", TObject.kOverwrite)
outfile.Write()
outfile.Close()
def compareUpperLimits(labels, masses, filelabels, **kwargs):
print color("compareUpperLimits()", color="magenta", prepend=">>>\n>>> ")
# SIGNAL strength & mass
extralabel = kwargs.get('extralabel', "")
plotlabel = kwargs.get('plotlabel', "")
# LOOP over LABELS
for label in labels:
print color("plotUpperLimits - %s" % (label),
color="grey",
prepend="\n>>> ")
ymax = -99999
ymin = 99999
medians = []
for filelabel, title in filelabels:
N = len(masses)
median = TGraph(N) # median line
median.SetTitle(title)
medians.append(median)
for i, mass in enumerate(masses):
filename = getOutputFilename(label, mass, extralabel=filelabel)
limits = getLimits(filename)
median.SetPoint(i, mass, limits[2]) # median
if limits[2] > ymax: ymax = limits[2]
if limits[2] < ymin: ymin = limits[2]
median0 = medians[0]
doLog = ymin and ymax / ymin > 6
ymax = ymax * 1.40
xtitle = "m_{X} [GeV]"
ytitle = "95% upper limit on #sigma#timesBR(X #rightarrow #tau#tau) [pb]"
if "bbA" in filelabels[0][0]:
xtitle = "m_{A} [GeV]"
ytitle = "95% upper limit on #sigma#timesBR(A #rightarrow #tau#tau) [pb]"
W, H = 800, 800
T, B = 0.10 * H, 0.16 * H
L, R = 0.12 * W, 0.04 * W
# MAIN plot
canvas = TCanvas("canvas", "canvas", 100, 100, W, H)
canvas.Divide(2)
canvas.cd(1)
gPad.SetPad("pad1", "pad1", 0, 0.37, 1, 1, 0, -1, 0)
gPad.SetTopMargin(T / H)
gPad.SetBottomMargin(0.01)
gPad.SetLeftMargin(L / W)
gPad.SetRightMargin(R / W)
gPad.SetTickx(0)
gPad.SetTicky(0)
gPad.SetGrid()
if doLog:
ymin = 10**(floor(log(ymin, 10)))
ymax = 10**(ceil(log(ymax, 10)))
gPad.SetLogy()
else:
ymin *= 0 if ymin > 0 else 1.20
width = 0.25
height = 0.05 + len(medians) * 0.05
#x1 = 0.16; x2 = x1 + width # Left
x2 = 0.70
x1 = x2 - width # Right
x2 = x1 + width
y1 = 0.86
y2 = y1 - height
legend = TLegend(x1, y1, x2, y2)
frame = gPad.DrawFrame(min(masses), ymin, max(masses), ymax)
frame.GetYaxis().CenterTitle()
frame.GetYaxis().SetTitleSize(0.055)
frame.GetXaxis().SetTitleSize(0.058)
frame.GetXaxis().SetLabelSize(0.050 * 0)
frame.GetYaxis().SetLabelSize(0.053)
frame.GetXaxis().SetLabelOffset(0.012)
frame.GetXaxis().SetTitleOffset(1.02)
frame.GetYaxis().SetTitleOffset(1.08)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().CenterTitle(True)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetTitle(xtitle)
option = 'L'
for i, median in enumerate(medians):
median.SetLineColor(colors[i % len(colors)])
median.SetLineStyle(styles[i % len(styles)])
median.SetLineWidth(2 if styles[i % len(styles)] != kDotted else 3)
median.Draw('L')
legend.AddEntry(median, median.GetTitle(), 'L')
if i == 0: option += ' SAME'
CMS_lumi.CMS_lumi(gPad, 13, 0)
gPad.SetTicks(1, 1)
gPad.Modified()
frame.Draw('sameaxis')
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.SetTextSize(0.041)
legend.SetTextFont(62)
legend.SetHeader("%s" % (label_dict[label + extralabel]))
legend.SetTextFont(42)
legend.Draw()
# RATIO plot
canvas.cd(2)
gPad.SetPad("pad2", "pad2", 0, 0, 1, 0.36, 0, -1, 0)
gPad.SetTopMargin(0.05)
gPad.SetBottomMargin(0.24)
gPad.SetLeftMargin(L / W)
gPad.SetRightMargin(R / W)
frame_ratio = gPad.DrawFrame(min(masses), 0.36, max(masses), 1.20)
frame_ratio.GetYaxis().CenterTitle()
frame_ratio.GetYaxis().SetTitleSize(0.055 * 1.79)
frame_ratio.GetXaxis().SetTitleSize(0.058 * 1.79)
frame_ratio.GetXaxis().SetLabelSize(0.052 * 1.79)
frame_ratio.GetYaxis().SetLabelSize(0.050 * 1.79)
frame_ratio.GetXaxis().SetLabelOffset(0.012)
frame_ratio.GetXaxis().SetTitleOffset(1.00)
frame_ratio.GetYaxis().SetTitleOffset(0.63)
frame_ratio.GetXaxis().SetNdivisions(508)
frame_ratio.GetYaxis().CenterTitle(True)
frame_ratio.GetYaxis().SetTitle("ratio")
frame_ratio.GetXaxis().SetTitle(xtitle)
frame_ratio.GetYaxis().SetNdivisions(5)
option = 'L'
ratios = []
for i, median in enumerate(medians):
ratio = makeRatioTGraphs(median, median0)
ratio.SetLineColor(median.GetLineColor())
ratio.SetLineStyle(median.GetLineStyle())
ratio.SetLineWidth(median.GetLineWidth())
ratio.Draw('L')
ratios.append(ratio)
if i == 1: option += ' SAME'
gPad.SetTicks(1, 1)
gPad.Modified()
frame_ratio.Draw('sameaxis')
print " "
canvas.SaveAs("%s/upperLimit-%s%s_compare.png" %
(PLOTS_DIR, label, plotlabel))
canvas.SaveAs("%s/upperLimit-%s%s_compare.pdf" %
(PLOTS_DIR, label, plotlabel))
canvas.Close()
def drawHistsWithRatio(hists, name, **kwargs):
"""Draw histograms with ratios."""
title = kwargs.get('title', "")
xtitle = kwargs.get('xtitle', "")
ytitle = kwargs.get('ytitle', "")
rtitle = kwargs.get('rtitle', "Ratio")
xmin = kwargs.get('xmin', hists[0].GetXaxis().GetXmin())
xmax = kwargs.get('xmax', hists[0].GetXaxis().GetXmax())
ymin = kwargs.get('ymin', None)
ymax = kwargs.get('ymax', None)
rmin = kwargs.get('rmin', 0.45)
rmax = kwargs.get('rmax', 1.55)
logx = kwargs.get('logx', False)
logy = kwargs.get('logy', False)
denom = kwargs.get('denom', 1) - 1 # denominator for ratio
textsize = kwargs.get('textsize', 0.045)
texts = kwargs.get('text', [])
#textheight = kwargs.get('textheight', 1.09 )
#ctext = kwargs.get('ctext', [ ] ) # corner text
#cposition = kwargs.get('cposition', 'topleft' ).lower() # cornertext
#ctextsize = kwargs.get('ctextsize', 1.4*legendtextsize )
colors = kwargs.get('colors', linecolors)
if not isinstance(texts, list) or isinstance(texts, tuple):
texts = [texts]
if ymax == None:
ymax = 1.12 * max(h.GetMaximum() for h in hists)
# MAIN plot
canvas = TCanvas('canvas', 'canvas', 100, 100, 800, 800)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameBorderMode(0)
canvas.Divide(2)
canvas.SetMargin(0.0, 0.0, 0.0, 0.0)
canvas.cd(1)
gPad.SetPad('pad1', 'pad1', 0, 0.33, 1, 1)
gPad.SetMargin(0.12, 0.04, 0.02, 0.08)
gPad.SetFillColor(0)
gPad.SetBorderMode(0)
gPad.SetTickx(0)
gPad.SetTicky(0)
gPad.SetGrid()
gPad.Draw()
canvas.cd(2)
gPad.SetPad('pad2', 'pad2', 0, 0, 1, 0.33)
gPad.SetMargin(0.12, 0.04, 0.30, 0.03)
gPad.SetFillColor(0)
gPad.SetFillStyle(4000)
gPad.SetFrameFillStyle(0)
gPad.SetBorderMode(0)
gPad.Draw()
# MAIN plot
canvas.cd(1)
for i, hist in enumerate(hists):
color = colors[i % len(colors)]
hist.SetLineColor(color)
hist.SetLineWidth(2)
hist.Draw('HIST SAME')
frame = hists[0]
frame.GetYaxis().SetTitleSize(0.060)
frame.GetXaxis().SetTitleSize(0)
frame.GetXaxis().SetLabelSize(0)
frame.GetYaxis().SetLabelSize(0.052)
frame.GetXaxis().SetLabelOffset(0.010)
frame.GetXaxis().SetTitleOffset(0.98)
frame.GetYaxis().SetTitleOffset(1.05)
frame.GetXaxis().SetNdivisions(508)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetTitle(xtitle)
if logx:
gPad.Update()
gPad.SetLogx()
if logy:
gPad.Update()
gPad.SetLogy()
if ymin: frame.SetMinimum(ymin)
if ymax: frame.SetMaximum(ymax)
width = 0.25
height = 1.1 * textsize * len([l for l in texts + hists if l])
x1, y1 = 0.65, 0.88
x2, y2 = x1 + width, y1 - height
legend = TLegend(x1, y1, x2, y2)
legend.SetTextSize(textsize)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetMargin(0.05 / width)
if title:
legend.SetTextFont(62)
legend.SetHeader(title)
legend.SetTextFont(42)
for hist in hists:
legend.AddEntry(hist, hist.GetTitle(), 'l')
for text in texts:
legend.AddEntry(0, text, '')
legend.Draw()
gPad.SetTicks(1, 1)
gPad.Modified()
frame.Draw('AXIS SAME')
CMS_style.CMS_lumi(gPad, 13, 0)
# RATIO plot
canvas.cd(2)
ratios = []
for i, hist in enumerate(hists):
if i == denom: continue
ratio = hist.Clone(hist.GetName() + "_ratio")
ratio.Divide(hists[denom])
ratio.Draw('HIST SAME')
ratios.append(ratio)
frame_ratio = ratios[0]
frame_ratio.GetYaxis().SetRangeUser(rmin, rmax)
frame_ratio.GetYaxis().CenterTitle()
frame_ratio.GetYaxis().SetTitleSize(0.13)
frame_ratio.GetXaxis().SetTitleSize(0.13)
frame_ratio.GetXaxis().SetLabelSize(0.12)
frame_ratio.GetYaxis().SetLabelSize(0.11)
frame_ratio.GetXaxis().SetLabelOffset(0.012)
frame_ratio.GetXaxis().SetTitleOffset(1.02)
frame_ratio.GetYaxis().SetTitleOffset(0.48)
frame_ratio.GetXaxis().SetNdivisions(508)
frame_ratio.GetYaxis().CenterTitle(True)
frame_ratio.GetYaxis().SetTitle(rtitle)
frame_ratio.GetXaxis().SetTitle(xtitle)
frame_ratio.GetYaxis().SetNdivisions(505)
if logx:
gPad.Update()
gPad.SetLogx()
line = TLine(xmin, 1., xmax, 1.)
line.SetLineColor(hists[denom].GetLineColor())
line.SetLineWidth(hists[denom].GetLineWidth())
line.SetLineStyle(1)
line.Draw('SAME')
gPad.SetTicks(1, 1)
gPad.Update()
gPad.SetGrid()
gPad.Modified()
frame_ratio.Draw('SAME AXIS')
canvas.SaveAs(name + ".png")
canvas.SaveAs(name + ".pdf")
canvas.Close()
def SAME2VsLumi(g1, g2,title, ptype, dataPeriod):
canvas = makeCMSCanvas(str(random.random()),"canvas",900,700)
canvas.cd()
graph1=copy.deepcopy(g1)
graph2=copy.deepcopy(g2)
graph1.SetMarkerColor(kBlue)#electrons
graph2.SetMarkerColor(kRed)#muons
multigraph = TMultiGraph()
multigraph.Add(graph1,"AP")
multigraph.Add(graph2,"AP")
multigraph.Draw("AP")
TGaxis.SetMaxDigits(2)
TGaxis.SetExponentOffset(-0.06, 0.02, "y")
multigraph.GetXaxis().SetTitle("L [fb^{-1}]")
multigraph.GetYaxis().SetTitleOffset(1.4)
if(ptype == "ISO"):
multigraph.GetYaxis().SetTitle("Isolation")
gPad.Modified()
multigraph.SetMinimum(0.5*gPad.GetUymin())
multigraph.SetMaximum(1.5*gPad.GetUymax())
elif(ptype == "SIP"):
multigraph.GetYaxis().SetTitle("SIP")
multigraph.SetMinimum(min(multigraph.GetHistogram().GetMinimum(),1.))
multigraph.SetMaximum(max(multigraph.GetHistogram().GetMinimum(),2.2))
min(multigraph.GetHistogram().GetMinimum(),1.)
printLumiPrelOut(canvas)
# Draw legend
legend = TLegend(0.93,0.84,0.99,0.93)
legend.AddEntry(graph1,"e^{+}e^{-}","P")
legend.AddEntry(graph2,"#mu^{+}#mu^{-}","P")
legend.SetFillColor(kWhite)
legend.SetLineColor(kBlack)
legend.SetTextFont(43)
legend.SetTextSize(20)
legend.Draw()
canvas.Update()
# Draw letters for data-taking periods
if(dataPeriod == "data2017"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "ISO"):
textLetters.DrawLatex(2., 0.8*gPad.GetUymax(),"B")
textLetters.DrawLatex(9.5, 0.8*gPad.GetUymax(),"C")
textLetters.DrawLatex(16., 0.8*gPad.GetUymax(),"D")
textLetters.DrawLatex(23., 0.8*gPad.GetUymax(),"E")
textLetters.DrawLatex(36., 0.8*gPad.GetUymax(),"F")
elif(ptype == "SIP"):
textLetters.DrawLatex(2., 1.5,"B")
textLetters.DrawLatex(9.5, 1.5,"C")
textLetters.DrawLatex(16., 1.5,"D")
textLetters.DrawLatex(23., 1.5,"E")
textLetters.DrawLatex(36., 1.5,"F")
if(dataPeriod == "data2018"):
textLetters = TLatex()
textLetters.SetTextColor(kGray+1)
textLetters.SetTextSize(0.03)
if(ptype == "ISO"):
textLetters.DrawLatex(6., 0.8*gPad.GetUymax(), "A")
textLetters.DrawLatex(16., 0.8*gPad.GetUymax(), "B")
textLetters.DrawLatex(23., 0.8*gPad.GetUymax(), "C")
textLetters.DrawLatex(43., 0.8*gPad.GetUymax(), "D")
elif(ptype == "SIP"):
textLetters.DrawLatex(6., 1.5, "A")
textLetters.DrawLatex(16., 1.5, "B")
textLetters.DrawLatex(23., 1.5, "C")
textLetters.DrawLatex(43., 1.5, "D")
# ****
if(dataPeriod == "data2018"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineA = TLine(13.48, down, 13.48, up) # Run2018A up to 13.48 fb-1
lineA.SetLineColor(kBlack)
lineA.SetLineStyle(2)
lineA.Draw()
lineB = TLine(20.265, down, 20.265, up) # Run2018B up to 20.265 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(26.877, down, 26.877, up) # Run2018C up to 26.877 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
# ****
if(dataPeriod == "data2017"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(4.793, down, 4.793, up) # Run2017B up to 4.793 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(14.549, down, 14.549, up) # Run2017C up to 14.549 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(18.868, down, 18.868, up) # Run2017D up to 18.868 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(28.293, down, 28.293, up) # Run2017E up to 28.293 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
# ****
if(dataPeriod == "data2016"):
# draw vertical lines that divide different data taking periods
down = gPad.GetUymin()
up = gPad.GetUymax()
lineB = TLine(5.789, down, 5.789, up) # Run2016B up to 5.789 fb-1
lineB.SetLineColor(kBlack)
lineB.SetLineStyle(2)
lineB.Draw()
lineC = TLine(8.366, down, 8.366, up) # Run2016C up to 8.366 fb-1
lineC.SetLineColor(kBlack)
lineC.SetLineStyle(2)
lineC.Draw()
lineD = TLine(12.616, down, 12.616, up) # Run2016D up to 12.616 fb-1
lineD.SetLineColor(kBlack)
lineD.SetLineStyle(2)
lineD.Draw()
lineE = TLine(16.624, down, 16.624, up) # Run2016E up to 16.624 fb-1
lineE.SetLineColor(kBlack)
lineE.SetLineStyle(2)
lineE.Draw()
lineF = TLine(19.725, down, 19.725, up) # Run2016F up to 19.725 fb-1
lineF.SetLineColor(kBlack)
lineF.SetLineStyle(2)
lineF.Draw()
lineG = TLine(27.268, down, 27.268, up) # Run2016G up to 27.268 fb-1
lineG.SetLineColor(kBlack)
lineG.SetLineStyle(2)
lineG.Draw()
# ****
canvas.SaveAs(title + ".root")
canvas.SaveAs(title + ".pdf")
canvas.SaveAs(title + ".png")
return;
def plot_results(caldac, no_mpa_light, x1, y1, c1, backup):
savestr = str(caldac)
col = 1
xvec = np.array(x1, dtype='uint16')
xdacval = 0.
thdacvv = []
yarrv = []
xdvals = []
linearr = []
stackarr = []
fitfuncarr = []
fitparameterarray = []
for i in range(0, no_mpa_light):
if (backup.GetDirectory("MPA_" + str(i))):
backup.cd("MPA_" + str(i))
else:
backup.mkdir("MPA_" + str(i))
backup.cd("MPA_" + str(i))
calibconfxmlroot = calibconfsxmlroot[i]
xdvals.append(0.)
c1.cd(i + 1)
thdacv = []
yarr = np.array(y1[i])
linearr.append([])
gr1 = []
lines = []
fitfuncarr.append([])
fitfuncs = []
fitparameterarray.append([])
fitparams = []
yarrv.append(yarr)
stackarr.append(
THStack('a', 'pixel curves;DAC Value (1.456 mV);Counts (1/1.456)'))
for iy1 in range(0, len(yarr[0, :])):
yvec = yarr[:, iy1]
# if max(yvec)==0:
# print "zero"
gr1.append(
TH1I(str(iy1), ';DAC Value (1.456 mV);Counts (1/1.456)',
len(x1), 0, x1[-1]))
gr1[iy1].Sumw2(ROOT.kFALSE)
for j in np.nditer(xvec):
gr1[iy1].SetBinContent(gr1[iy1].FindBin(j),
(np.array(yvec, dtype='int')[j]))
gr1[iy1].Sumw2(ROOT.kTRUE)
color = iy1 % 9 + 1
gr1[iy1].SetLineColor(color)
gr1[iy1].SetMarkerColor(color)
gr1[iy1].SetFillColor(color)
gr1[iy1].SetLineStyle(1)
gr1[iy1].SetLineWidth(1)
gr1[iy1].SetFillStyle(1)
gr1[iy1].SetMarkerStyle(1)
gr1[iy1].SetMarkerSize(.5)
gr1[iy1].SetMarkerStyle(20)
fitfuncs.append(TF1('gaus', 'gaus', 0, 256))
fitfuncs[iy1].SetNpx(256)
fitfuncs[iy1].SetParameters(gr1[iy1].GetMaximum(),
gr1[iy1].GetMean(), gr1[iy1].GetRMS())
cloned = gr1[iy1].Clone()
cloned.SetDirectory(0)
fitparams.append([])
mean = 0
if gr1[iy1].GetMaximum() < -1:
gr1[iy1].Fit(fitfuncs[iy1], 'rq +rob=0.95', '', 0, 256)
fitparams[iy1].append(fitfuncs[iy1].GetParameter(0))
fitparams[iy1].append(fitfuncs[iy1].GetParameter(1))
fitparams[iy1].append(fitfuncs[iy1].GetParameter(2))
fitparams[iy1].append(fitfuncs[iy1].GetParError(0))
fitparams[iy1].append(fitfuncs[iy1].GetParError(1))
fitparams[iy1].append(fitfuncs[iy1].GetParError(2))
if (fitfuncs[iy1].GetNDF() > 0):
fitparams[iy1].append(fitfuncs[iy1].GetChisquare() /
fitfuncs[iy1].GetNDF())
else:
fitparams[iy1].append(0)
mean = fitfuncs[iy1].GetParameter(1)
else:
for kk in range(0, 7):
fitparams[iy1].append(0)
fitparameterarray[i].append(fitparams[iy1])
fitfuncarr[i].append(fitfuncs[iy1])
stackarr[i].Add(cloned)
if iy1 == (len(yarr[0, :]) - 1):
stackarr[i].Draw('nostack hist e1 x0')
# for fitfuncs1 in fitfuncarr[i]:
# fitfuncs1.Draw("same")
# for lines1 in linearr[i]:
# lines1.Draw("same")
if (stackarr[i].GetMaximum() > 1):
Maximum = TMath.Power(
10, (round(TMath.Log10(stackarr[i].GetMaximum())) - 1))
stackarr[i].SetMinimum(.1)
stackarr[i].SetMaximum(Maximum)
# gPad.SetLogy()
gPad.Modified()
gPad.Update()
gr1[iy1].SetLineColor(1)
gr1[iy1].SetMarkerColor(1)
gr1[iy1].SetFillColor(1)
gr1[iy1].Write(str(iy1) + 'CAL' + savestr)
# fitfuncs[iy1].Write(str(iy1)+savestr+'fit')
# print thdacv
backup.cd()
if (backup.GetDirectory("Canvas")):
backup.cd("Canvas")
else:
backup.mkdir("Canvas")
backup.cd("Canvas")
c1.Write('CALDAC_' + savestr)
c1.Clear('D')
return 0
