def trigger(nbins, low, high):
# dataFile = TFile("../anaRoots/data.root","OPEN")
# treeTrig = dataFile.Get("Trigger")
# cutter = cuts[region]
can = TCanvas("can", "can", 1000, 900)
# can.SetBottomMargin(0.3)
# can.SetRightMargin(0.06)
gStyle.SetOptStat(0)
histNumerator = TH1F('histNumerator', ";Photon p_{T} [GeV];Efficiency",
nbins, low, high)
treeTrig['Data'].Draw('TrigPhoton_pt>>histNumerator',
'((isHLT165==1) && (isPrescaled==1))')
# treeTrig['Data'].Draw('TrigPhoton_pt>>histNumerator','((isHLT165==True))')
histDenominator = TH1F('histDenominator', ";Photon p_{T} [GeV];Efficiency",
nbins, low, high)
treeTrig['Data'].Draw('TrigPhoton_pt>>histDenominator', '(isPrescaled==1)')
histNumerator.Sumw2()
histDenominator.Sumw2()
histNumerator.SetMaximum(1.1)
print histNumerator.Integral()
print histDenominator.Integral()
histNumerator.Divide(histDenominator)
histNumerator.Draw('e1')
latex2 = TLatex()
latex2.SetNDC()
latex2.SetTextSize(0.035)
latex2.SetTextAlign(31) # align right
latex2.DrawLatex(
0.87, 0.95,
"Work In Progress, " + str(lumi) + " fb^{-1} at #sqrt{s} = 13 TeV")
can.SaveAs("plots/trigger.pdf")
can.Close()
def __make_summary_plot(self, name, ibin2, successful):
# Nominal histogram
successful_tmp = copy(successful)
successful_tmp.sort()
filename = f"finalcross{self.case}{self.typean}mult{ibin2}.root"
filepath = join(self.nominal_analyzer_merged.d_resultsallpdata,
filename)
nominal_histo = self.__get_histogram(filepath, name)
histos = []
ml_trials = []
for succ in successful_tmp:
filename = f"finalcross{self.case}{self.typean}mult{ibin2}.root"
filepath = join(self.analyzers_syst[succ].d_resultsallpdata,
filename)
histos.append(self.__get_histogram(filepath, name))
ml_trials.append(
list(map(itemgetter(self.mcopt), self.ml_wps[succ])))
nptbins = self.nominal_processer_mc.p_nptfinbins
gr = [TGraphErrors(0) for _ in range(nptbins)]
for ipt in range(nptbins):
gr[ipt].SetTitle("pT bin %d" % ipt)
gr[ipt].SetPoint(0, self.cent_cv_cut[ipt],
nominal_histo.GetBinContent(ipt + 1))
gr[ipt].SetPointError(0, 0.0001,
nominal_histo.GetBinError(ipt + 1))
for iml, succ in enumerate(successful_tmp):
gr[ipt].SetPoint(iml + 1, ml_trials[succ][ipt],
histos[succ].GetBinContent(ipt + 1))
gr[ipt].SetPointError(iml + 1, 0.0001,
histos[succ].GetBinError(ipt + 1))
canvas = TCanvas("cvsml%d" % ibin2, "", 1200, 800)
if len(gr) <= 6:
canvas.Divide(3, 2)
elif len(gr) <= 12:
canvas.Divide(4, 3)
else:
canvas.Divide(5, 4)
for i, graph in enumerate(gr):
canvas.cd(i + 1)
graph.Draw("a*")
save_path = join(self.nominal_analyzer_merged.d_resultsallpdata,
self.syst_out_dir,
f"ml_wp_syst_{name}_vs_MLcut_ibin2_{ibin2}.eps")
canvas.SaveAs(save_path)
save_path = join(self.nominal_analyzer_merged.d_resultsallpdata,
self.syst_out_dir,
f"ml_wp_syst_{name}_vs_MLcut_ibin2_{ibin2}.root")
file_out = TFile.Open(save_path, "RECREATE")
file_out.cd()
for i, graph in enumerate(gr):
graph.Write("%s%d" % (graph.GetName(), i))
canvas.Write()
file_out.Close()
canvas.Close()
def writeHistogramsToFileTest():
print ">>> write a root file with a histogram."
filein = TFile("tree.root", "read")
fileout = TFile("test.root", "recreate")
tree = filein.Get("dir1/tree2")
hist1 = TH1D("hist1", "hist1", 100, 0, 40)
tree.Draw("normal5 >> hist1")
hist2 = TH1D("hist2", "hist2", 100, 0, 40)
hist2.SetLineColor(kRed)
tree.Draw("normal5 + 5 >> hist2")
# ...
canvas = TCanvas("canvas", "canvas", 100, 100, 600, 800)
hist1.Draw()
hist2.Draw("same")
# ...
canvas.SaveAs("test.png")
fileout.Write()
fileout.Close()
canvas.Close()
def checklatex(texts, tag=""):
"""Check legend entries: colors, titles, ..."""
# https://root.cern.ch/doc/master/classTPaveText.html
LOG.header("checklegend" + tag.replace('_', ' '))
output = ensuredir('plots')
fname = "%s/testLatex%s" % (output, tag)
xdim = 500
ydim = 50 * (len(texts) + 2.5)
print ">>> Canvas: %sx%s (nlines=%d)" % (xdim, ydim, len(texts))
canvas = TCanvas('canvas', 'canvas', xdim, int(ydim))
#pave1 = TPaveText(0.0,0,0.5,1,'ARC') #,'BR')
pave2 = TPaveText(0.04, 0.04, 0.96, 0.96) #'ARC') #,'BR')
#pave1.SetBorderSize(0)
pave2.SetBorderSize(0)
#pave1.SetTextAlign(12)
pave2.SetTextAlign(12)
#pave1.SetTextFont(42)
pave2.SetTextFont(42)
#pave1.SetFillColor(0)
pave2.SetFillColor(0)
#pave1.SetCornerRadius(0.05)
#pave2.SetCornerRadius(0.05)
#pave1.SetMargin(0.12)
#pave1.SetTextSize(tsize)
#pave2.Copy(pave1)
for line in texts:
latex = makelatex(line)
print ">>> %r -> %r" % (line, latex)
#pave1.AddText(line)
pave2.AddText(latex)
#pave1.Draw()
pave2.Draw()
canvas.SaveAs(fname + ".png")
#canvas.SaveAs(fname+".pdf")
canvas.Close()
def drawEWKNLOCorr():
filename1 = path + "merged_kfactors_zjets.root"
filename2 = path + "merged_kfactors_wjets.root"
histname = "kfactor_monojet_ewk"
file1 = ensureTFile(filename1)
file2 = ensureTFile(filename2)
hist1 = file1.Get(histname)
hist2 = file2.Get(histname)
hist1.SetDirectory(0)
hist2.SetDirectory(0)
file1.Close()
file2.Close()
c1 = TCanvas("c1", "sf plot", 800, 600)
hist1.SetTitle("EWK NLO SF")
hist1.GetXaxis().SetTitle("V p_{T} (GeV)")
hist1.GetYaxis().SetTitle("EWK NLO SF")
hist1.GetYaxis().SetRangeUser(0.7, 1.0)
hist1.SetLineColor(4)
hist2.SetLineColor(2)
hist1.SetLineWidth(3)
hist1.SetMarkerStyle(8)
hist1.SetMarkerColor(4)
hist2.SetMarkerStyle(8)
hist2.SetMarkerColor(2)
leg = TLegend(0.7, 0.65, 0.85, 0.8)
leg.AddEntry(hist1, "Z+Jets")
leg.AddEntry(hist2, "W+Jets")
hist1.Draw("LP HIST")
hist2.Draw("LP HIST SAME")
leg.Draw("SAME")
gStyle.SetOptStat(0)
c1.SaveAs("./plotsSF/EWKNLOCorr.pdf")
c1.SaveAs("./plotsSF/EWKNLOCorr.png")
c1.Close()
def plot_2(var, cuts):
for s in attr:
c1 = TCanvas("c1", "Signals", 800, 800)
c1.cd()
c1.SetGrid()
#gStyle.SetTitleFontSize(8.1)
if s in ('elf', 'muf', 'chm', 'cm', 'nm'):
c1.SetLogx()
for cc in channel:
#hist[cc][s].SetMaximum(0.44)
hist[cc][s].Draw('colz same')
if CHS == 1:
hist_CHS[cc][s].Draw('colz same')
legend = TLegend(0.90, 0.90, 0.99, 0.99)
#legend.SetHeader('Samples')
for cc in channel:
legend.AddEntry(hist[cc][s], cc)
if CHS == 1:
legend.AddEntry(hist_CHS[cc][s], cc + 'CHS')
legend.Draw()
c1.Print(path1 + s + var + cuts.replace('(', '_').replace(
')', '_').replace('&&', 'A').replace('>', 'LG').replace(
'<', 'LS').replace('=', 'EQ').replace('.', 'P').replace(
'-', 'N').replace('Jet', 'J').replace('GenBquark', 'GBQ') +
".pdf")
c1.Update()
c1.Close()
print('|||||||||||||||||||||||||||||||||||||||||||||||||||')
def plot_histograms(histos,
use_log_y=False,
ratio=False,
legend_titles=None,
title="",
x_label="",
y_label_up="",
y_label_ratio="",
save_path="./plot.eps",
**kwargs):
"""
Throws all given histograms into one canvas. If desired, a ratio plot will be added.
"""
linestyles = kwargs.get("linestyles", None)
markerstyles = kwargs.get("markerstyles", None)
colors = kwargs.get("colors", None)
canvas_name = kwargs.get("canvas_name", "Canvas")
style_histograms(histos, linestyles, markerstyles, colors)
canvas = TCanvas('canvas', canvas_name, 800, 800)
pad_up_start = 0.4 if ratio else 0.
pad_up = TPad("pad_up", "", 0., pad_up_start, 1., 1.)
if ratio:
pad_up.SetBottomMargin(0.)
pad_up.Draw()
put_in_pad(pad_up, use_log_y, histos, title, "", y_label_up)
pad_up.cd()
legend = None
if legend_titles is not None:
legend = TLegend(.45, .65, .85, .85)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetFillStyle(0)
legend.SetTextFont(42)
legend.SetTextSize(0.02)
for h, l in zip(histos, legend_titles):
legend.AddEntry(h, l)
legend.Draw()
canvas.cd()
pad_ratio = None
histos_ratio = None
if ratio:
histos_ratio = divide_all_by_first(histos)
pad_ratio = TPad("pad_ratio", "", 0., 0.05, 1., pad_up_start)
pad_ratio.SetTopMargin(0.)
pad_ratio.SetBottomMargin(0.3)
pad_ratio.Draw()
put_in_pad(pad_ratio, False, histos_ratio, "", x_label, y_label_ratio)
canvas.SaveAs(save_path)
canvas.Close()
def plotHist(h):
colors = [633, 416 + 1, 862, 800, 921, 922, 1]
n = len(h)
c1 = TCanvas("c1", "Signals", 800, 600)
c1.cd()
#c1.GetPad(1).SetPadTopMargin(0.06)
#c1.GetPad(1).SetPadRightMargin(0.05)
c1.GetPad(0).SetTicky(2)
for i in range(n):
col = sample[
h[i].GetTitle()]['linecolor'] if n > len(colors) else colors[i]
h[i].SetMarkerColor(col)
h[i].SetLineColor(col)
if "Counter" in h[0].GetName():
h[0].GetYaxis().SetRangeUser(0., -1)
else:
for i in range(n):
h[i].SetMarkerStyle(20)
#h[i].SetMarkerSize(1)
h[i].SetLineWidth(2)
ymax = 0.
for i in range(n):
if h[i].GetMaximum() > ymax: ymax = h[i].GetMaximum()
h[0].SetMaximum(ymax * 1.2)
if h[0].Integral() / h[0].GetNbinsX() < 1.:
#h[0].GetYaxis().SetTitle("Efficiency")
h[0].GetYaxis().SetRangeUser(0., 1.)
style = "HIST" if "Counter" in h[0].GetName() or "Barrel" in h[0].GetName(
) or "Endcap" in h[0].GetName() or h[0].GetName().startswith(
"Gen") else "PE1"
h[0].Draw(style)
for i in range(1, n):
h[i].Draw("SAME, " + style)
leg = TLegend(0.50, 0.55 - 0.05 * n, 0.85, 0.55)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
for i in range(n):
if h[i].GetTitle() != "":
if h[i].GetTitle() in sample.keys():
leg.AddEntry(h[i], sample[h[i].GetTitle()]['label'], "pl")
else:
leg.AddEntry(h[i], h[i].GetTitle(), "pl")
leg.Draw()
drawCMS(-1, "Simulation", True)
c1.Print("plots/Leptons/" + h[-1].GetName() + ".png")
c1.Print("plots/Leptons/" + h[-1].GetName() + ".pdf")
#raw_input("Press Enter to continue...")
c1.Close()
return True
def draweffb(btag):
upline = TGraph()
downline = TGraph()
if btag == '2b':
eff_b = {
800: [0.961, 1.040],
1000: [0.955, 1.046],
1200: [0.944, 1.058],
1400: [0.913, 1.093],
1600: [0.889, 1.119],
1800: [0.877, 1.133],
2000: [0.873, 1.138],
2500: [0.869, 1.141],
3000: [0.868, 1.142],
3500: [0.868, 1.143],
4000: [0.868, 1.143],
4500: [0.866, 1.145],
5000: [0.862, 1.150]
}
else:
eff_b = {
800: [1.007, 0.993],
1000: [1.009, 0.991],
1200: [1.013, 0.988],
1400: [1.025, 0.976],
1600: [1.033, 0.968],
1800: [1.038, 0.963],
2000: [1.041, 0.961],
2500: [1.050, 0.952],
3000: [1.054, 0.948],
3500: [1.057, 0.945],
4000: [1.059, 0.944],
4500: [1.061, 0.941],
5000: [1.063, 0.940]
}
for i, signal in enumerate(signal_list):
upline.SetPoint(i, signal, eff_b[signal][1])
downline.SetPoint(i, signal, eff_b[signal][0])
c1 = TCanvas("c1", "sf plot", 800, 600)
upline.SetTitle("b-tagging uncertainty %s" % btag)
upline.GetXaxis().SetTitle("m_{X} (GeV)")
upline.GetYaxis().SetTitle("Uncertainty")
upline.GetYaxis().SetRangeUser(0.7, 1.3)
upline.SetLineColor(4)
downline.SetLineColor(2)
upline.SetLineWidth(3)
downline.SetLineWidth(3)
leg = TLegend(0.7, 0.75, 0.85, 0.85)
leg.AddEntry(upline, "+ 1 s. d.", "L")
leg.AddEntry(downline, "- 1 s. d.", "L")
upline.Draw("AC")
downline.Draw("C SAME")
leg.Draw("SAME")
c1.SaveAs("./plotsSF/effb_%s.pdf" % btag)
c1.SaveAs("./plotsSF/effb_%s.png" % btag)
c1.Close()
def LoopPlotOnCanvas(pdf_name, list_histo):
for idx, inst in enumerate(list_histo, 1):
# inst is a class object -> inst.histo = TH1/TH2
# Open file #
if idx == 1:
c2 = TCanvas()
c2.Print(pdf_name + '.pdf[')
c2.Close()
# Print each plot #
inst.PlotOnCanvas(pdf_name=pdf_name + '.pdf')
# Close file #
if idx == len(list_histo):
c2 = TCanvas()
c2.Print(pdf_name +
'.pdf') # Otherwise last plot does not have title
c2.Print(pdf_name + '.pdf]')
c2.Close()
logging.info('Plots saved at %s' % (pdf_name + '.pdf'))
def drawDsPlot(ds,catNum = 0):
from ROOT import RooAbsData,TCanvas
etaHist = RooAbsData.createHistogram(ds,'eta',100);
theCanvas = TCanvas('dsCanvas','Eta histogram (category' + str(catNum) + ')' )
etaHist.Draw("hist PFC");
theCanvas.SaveAs("etaCat"+str(catNum)+"Hist"+TIME_NOW+".pdf");
#s = raw_input("Press Enter to continue...");
theCanvas.Close();
def plotHists(hists,xtitle,plotname,header,ctexts=[ ],otext="",logy=False,y1=0.70):
colors = [ kBlue, kRed, kGreen+2, kOrange, kMagenta+1 ]
canvas = TCanvas('canvas','canvas',100,100,800,700)
canvas.SetMargin(0.12,0.03,0.14,0.06 if otext else 0.03)
textsize = 0.040
height = 1.28*(len(hists)+1)*textsize
y1
legend = TLegend(0.65,y1,0.88,y1-height)
legend.SetTextSize(textsize)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetTextFont(62)
legend.SetHeader(header)
legend.SetTextFont(42)
legend.SetMargin(0.2)
latex = TLatex()
latex.SetTextAlign(13)
latex.SetTextFont(42)
latex.SetNDC(True)
frame = hists[0]
frame.GetXaxis().SetTitle(xtitle)
frame.GetYaxis().SetTitle("Fraction [%]")
frame.GetXaxis().SetLabelSize(0.074)
frame.GetYaxis().SetLabelSize(0.046)
frame.GetXaxis().SetTitleSize(0.048)
frame.GetYaxis().SetTitleSize(0.052)
frame.GetXaxis().SetTitleOffset(1.38)
frame.GetYaxis().SetTitleOffset(1.12)
frame.GetXaxis().SetLabelOffset(0.009)
frame.SetMaximum(1.25*max(h.GetMaximum() for h in hists))
if logy:
canvas.SetLogy()
frame.SetMinimum(1e-3)
else:
frame.SetMinimum(0)
for i, hist in enumerate(hists):
hist.Draw('HISTE0E1SAME')
hist.SetLineWidth(2)
hist.SetLineColor(colors[i%len(colors)])
legend.AddEntry(hist,hist.GetTitle(),'le')
legend.Draw()
for i, text in enumerate(ctexts):
textsize = 0.024 #if i>0 else 0.044
latex.SetTextSize(textsize)
latex.DrawLatex(0.14,0.98-canvas.GetTopMargin()-1.7*i*textsize,text)
if otext:
latex.SetTextSize(0.05)
latex.SetTextAlign(31)
latex.DrawLatex(1.-canvas.GetRightMargin(),1.-0.84*canvas.GetTopMargin(),otext)
canvas.SaveAs(plotname+".png")
canvas.SaveAs(plotname+".pdf")
canvas.Close()
for hist in hists:
gDirectory.Delete(hist.GetName())
def draw2d(hist, xtitle, ytitle, number=False, nxbins=0, nybins=0):
"""Draw 2D histogram."""
tsize = 0.045
lines = []
xmin, xmax = hist.GetXaxis().GetXmin(), hist.GetXaxis().GetXmax()
ymin, ymax = hist.GetYaxis().GetXmin(), hist.GetYaxis().GetXmax()
canvas = TCanvas('canvas', 'canvas', 100, 100, 900, 800)
canvas.SetMargin(0.11, 0.16, 0.10, 0.02) # LRBT
canvas.SetLogz()
hist.GetXaxis().SetTitle(xtitle)
hist.GetYaxis().SetTitle(ytitle)
hist.GetZaxis().SetTitle("Events")
hist.GetXaxis().SetTitleSize(tsize)
hist.GetYaxis().SetTitleSize(tsize)
hist.GetZaxis().SetTitleSize(tsize)
hist.GetXaxis().SetLabelSize(0.9 * tsize)
hist.GetYaxis().SetLabelSize(0.9 * tsize)
hist.GetZaxis().SetLabelSize(0.9 * tsize)
hist.GetXaxis().SetTitleOffset(1.04)
hist.GetYaxis().SetTitleOffset(1.14)
hist.GetZaxis().SetTitleOffset(1.08)
hist.Draw('COLZ')
if number:
latex = TLatex()
latex.SetTextSize(0.8 * tsize)
latex.SetTextAlign(22)
latex.SetTextFont(62)
latex.SetTextColor(kRed)
for ix in range(1, hist.GetXaxis().GetNbins() + 1):
x = hist.GetXaxis().GetBinCenter(ix)
for iy in range(1, hist.GetYaxis().GetNbins() + 1):
y = hist.GetYaxis().GetBinCenter(iy)
latex.DrawLatex(x, y, str(Unroll.GetBin(x, y)))
if nxbins > 0: # divide with nlines
for i in range(1, nxbins):
x = xmin + (xmax - xmin) * i / nxbins
line = TLine(x, ymin, x, ymax)
line.SetLineColor(kRed)
line.SetLineStyle(kDashed)
line.SetLineWidth(1)
line.Draw()
lines.append(line)
if nybins > 0: # divide with nlines
for i in range(1, nybins):
y = ymin + (ymax - ymin) * i / nybins
line = TLine(xmin, y, xmax, y)
line.SetLineColor(kRed)
line.SetLineStyle(kDashed)
line.SetLineWidth(2)
line.Draw()
lines.append(line)
canvas.RedrawAxis()
canvas.SaveAs(hist.GetName() + ".png")
#canvas.SaveAs(hist.GetName()+".pdf")
canvas.Close()
def draw_syst(self, save_dir, results_dir, root_dir=None):
"""Draw all fits one-by-one
Args:
save_dir: directory where to save plots
results_dir: where to find intermediate results of the multi trial
root_dir: TDirectory where to save summary plots
"""
gStyle.SetOptStat(0)
gStyle.SetOptStat(0000)
gStyle.SetPalette(1)
gStyle.SetCanvasColor(0)
gStyle.SetFrameFillColor(0)
bins1_ranges = self.pars_factory.bins1_edges_low.copy()
bins1_ranges.append(self.pars_factory.bins1_edges_up[-1])
for (ibin1, ibin2), fit in self.syst_fits.items():
if not fit:
self.logger.warning(
"No systematic fit for bins (%i, %i). Skip...", ibin1,
ibin2)
continue
bin_id_match = self.pars_factory.bin_matching[ibin1]
# Some variables set for drawing
title = f"{self.pars_factory.bins1_edges_low[ibin1]:.1f} < #it{{p}}_{{T}} < " \
f"{self.pars_factory.bins1_edges_up[ibin1]:.1f}" \
f"(prob > {self.pars_factory.prob_cut_fin[bin_id_match]:.2f})"
suffix_write = self.pars_factory.make_suffix(ibin1, ibin2)
fit.results_path = os.path.join(
results_dir, f"multi_trial_bin1_{ibin1}_bin2_{ibin2}.root")
# Central fits
canvas = TCanvas("fit_canvas", suffix_write, 1400, 800)
fit.draw(canvas, title=title)
if self.pars_factory.apply_weights is False:
canvas.SaveAs(
make_file_path(save_dir, "multi_trial", "eps", None,
suffix_write))
else:
canvas.SaveAs(
make_file_path(save_dir, "multi_trial_weights", "eps",
None, suffix_write))
if root_dir:
root_dir.cd()
canvas.Write(f"multi_trial_{suffix_write}")
canvas.Close()
def plotRatio(var,name,hist1,hist2):
"""Plot minimal ratio of two histograms."""
canvas = TCanvas('canvas','canvas',100,100,800,800)
canvas.Divide(2)
canvas.cd(1)
gPad.SetPad('pad1','pad1',0,0.42,1,1,0,-1,0)
gPad.SetTopMargin( 0.10 ); gPad.SetBottomMargin( 0.01 )
hist1.Draw()
hist2.Draw('SAME')
hist1.SetLineColor(kBlue)
hist2.SetLineColor(kRed)
hist1.SetLineWidth(2)
hist2.SetLineWidth(2)
hist1.SetLineStyle(1)
hist2.SetLineStyle(2)
hist1.Draw('HIST')
hist2.Draw('HIST SAMES')
gPad.Update()
stats1 = hist1.GetListOfFunctions().FindObject('stats')
stats2 = hist2.GetListOfFunctions().FindObject('stats')
stats1.SetY1NDC(.74); stats1.SetY2NDC(.94)
stats2.SetY1NDC(.50); stats2.SetY2NDC(.70)
stats1.Draw()
stats2.Draw()
canvas.cd(2)
gPad.SetPad('pad2','pad2',0,0,1,0.41,0,-1,0)
gPad.SetTopMargin( 0.05 ); gPad.SetBottomMargin( 0.24 )
ratio = hist1.Clone('ratio')
ratio.Divide(hist2)
for i, (y1, y2, r) in enumerate(zip(hist1,hist2,ratio),0):
if hist1.GetBinContent(i)==0 and hist2.GetBinContent(i)==0:
ratio.SetBinContent(i,1)
ratio.GetXaxis().SetTitle(var)
ratio.GetXaxis().SetLabelSize(0.045)
ratio.GetYaxis().SetLabelSize(0.045)
ratio.GetXaxis().SetTitleSize(0.060)
ratio.SetMinimum(0.2)
ratio.SetMaximum(1.8)
ratio.Draw()
statsr = ratio.GetListOfFunctions().FindObject('stats')
statsr.SetY1NDC(.65); statsr.SetY2NDC(.98)
canvas.SaveAs(name)
canvas.Close()
gDirectory.Delete(hist1.GetName())
gDirectory.Delete(hist2.GetName())
gDirectory.Delete(ratio.GetName())
def LoopPlotOnCanvas(pdf_name, list_histo):
#c = TCanvas('c','c')
canvas = TCanvas('c', 'c', 600, 600)
canvas.Print(pdf_name + '.pdf[')
canvas.Close()
for idx, inst in enumerate(list_histo, 1):
canvas, title = inst.PlotOnCanvas(pdf_name=pdf_name + '.pdf')
# if isinstance(canvas,list):
# for c in canvas:
# c.Print(pdf_name+'.pdf')
# if idx == len(list_histo):
# canvas[-1].Print(pdf_name+'.pdf]')
# for c in canvas:
# c.Close()
canvas.Print(pdf_name + '.pdf', 'Title:' + title)
if idx == len(list_histo):
canvas.Print(pdf_name + '.pdf]')
canvas.Close()
logging.info('Plots saved at %s' % (pdf_name + '.pdf'))
def plot2D(histname, hist, log=False, year=''):
"""Plot efficiency."""
dir = ensureDirectory('plots/Efficiency')
name = "%s/%s" % (dir, histname)
if log:
name += "_log"
xtitle = 'jet p_{T} [GeV]'
ytitle = 'jet #eta'
ztitle = 'b tag efficiencies' if '_b_' in histname else 'b miss-tag rate'
name = name + "_" + str(year)
canvas = TCanvas('canvas', 'canvas', 100, 100, 800, 700)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetTopMargin(0.07)
canvas.SetBottomMargin(0.13)
canvas.SetLeftMargin(0.12)
canvas.SetRightMargin(0.17)
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
if log:
canvas.SetLogz()
canvas.cd()
hist.Draw('COLZTEXT77')
hist.GetXaxis().SetTitle(xtitle)
hist.GetYaxis().SetTitle(ytitle)
hist.GetZaxis().SetTitle(ztitle)
hist.GetXaxis().SetLabelSize(0.048)
hist.GetYaxis().SetLabelSize(0.048)
hist.GetZaxis().SetLabelSize(0.048)
hist.GetXaxis().SetTitleSize(0.058)
hist.GetYaxis().SetTitleSize(0.058)
hist.GetZaxis().SetTitleSize(0.056)
hist.GetXaxis().SetTitleOffset(1.03)
hist.GetYaxis().SetTitleOffset(1.04)
hist.GetZaxis().SetTitleOffset(1.03)
hist.GetZaxis().SetLabelOffset(-0.005 if log else 0.005)
hist.SetMinimum(0.01 if log else 0.0)
hist.SetMaximum(1.0)
gStyle.SetPaintTextFormat('.2f')
hist.SetMarkerSize(1.0)
hist.SetMarkerColor(kRed)
hist.SetMarkerSize(1)
canvas.SaveAs(name + '.pdf')
canvas.SaveAs(name + '.png')
canvas.Close()
def DrawHists2d(self, options=None):
for hist in self.hists2d:
name = hist.GetName()
canvas = TCanvas(name, name)
if hist.GetLogY(): gPad.SetLogy(1)
if options: hist.SetOption(options)
hist.Draw()
for ext in self.GetExtensions():
canvas.SaveAs("%s/%s%s" %
(self.GetOutputDir(), canvas.GetTitle(), ext))
canvas.Write()
canvas.Clear()
canvas.Close()
return
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 compare_variables(sample, var_list, name):
cv = TCanvas("cv", "cv", 1000, 800)
cv.SetGrid()
cv.cd()
if "CSV" in name:
leg = TLegend(0.12, 0.6, 0.45, 0.88)
elif "pT" in name:
leg = TLegend(0.62, 0.6, 0.95, 0.88)
nomefile[sample] = TFile.Open(
NTUPLEDIR + samples[sample]['file'] + ".root", 'read')
leg.SetHeader(samples[sample]['leg_name'])
massimo = 0
for i, s in enumerate(var_list):
histo[s] = nomefile[sample].Get(samples[sample]['type'] + "/" + s)
histo[s].SetLineColor(colors[i])
histo[s].SetLineWidth(3)
histo[s].SetTitle("")
if "CSV" in name:
histo[s].GetXaxis().SetTitle("CSV score")
elif "pT" in name:
histo[s].GetXaxis().SetTitle("p_{T} [GeV]")
leg.AddEntry(histo[s], variables[s]['legend_label'])
histo[s].GetXaxis().SetRangeUser(variables[s]['xmin'],
variables[s]['xmax'])
if sample == "ZH_MS-40_ctauS-1":
print i, s, massimo
massimo = max(massimo, histo[s].GetMaximum())
histo[s].Draw("same")
histo[s].SetMaximum(massimo * 1.2)
uncert[s] = histo[s].Clone(s + "_err")
uncert[s].SetMarkerStyle(0)
uncert[s].SetFillColor(colors[i])
uncert[s].SetFillStyle(3001)
uncert[s].Draw("SAME,E2")
if variables[s]['log']:
cv.SetLogy()
leg.Draw()
latex = TLatex()
latex.SetNDC()
latex.SetTextAlign(33)
latex.SetTextSize(0.04)
latex.SetTextFont(62)
latex.DrawLatex(0.20, 0.96, "CMS")
latex.SetTextFont(52)
latex.DrawLatex(0.36, 0.96, "Simulation")
cv.Print(PLOTDIR + name + "_" + sample + '.png')
cv.Print(PLOTDIR + name + "_" + sample + '.pdf')
cv.Close()
def plotEfficiencies2D(filename, prefix, workingpoint, label=""):
print ">>>\n>>> plotEfficiencies2D - %s" % (filename)
file = TFile(filename, 'READ')
dirname = "bTagEff"
histnames = [
"%s_%s_%s_eff" % (prefix, "udsg", workingpoint),
"%s_%s_%s_eff" % (prefix, "b", workingpoint),
]
for histname in histnames:
print ">>> %s" % (histname)
flavor = "b"
if "udsg" in histname: flavor = "light"
if "_c_" in histname: flavor = "c"
range = [0.25, 0.70]
if flavor == "light": range = [0.0, 0.10]
hist = file.Get("%s/%s" % (dirname, histname))
canvas = TCanvas("canvas", "canvas", 100, 100, 800, 600)
canvas.SetBottomMargin(0.12)
canvas.SetRightMargin(0.11)
canvas.SetLeftMargin(0.10)
canvas.SetTopMargin(0.08)
hist.Draw("colz")
hist.SetTitle("")
hist.GetZaxis().SetRangeUser(*range)
#hist.GetXaxis().SetRangeUser(0,100)
#hist.GetYaxis().SetRangeUser(0,200)
hist.GetXaxis().SetTitle("%s jet p_{T}" % (flavor))
hist.GetYaxis().SetTitle("%s jet #eta" % (flavor))
hist.GetYaxis().CenterTitle()
hist.GetXaxis().SetLabelSize(0.042)
hist.GetYaxis().SetLabelSize(0.042)
hist.GetXaxis().SetTitleSize(0.05)
hist.GetYaxis().SetTitleSize(0.05)
hist.GetXaxis().SetTitleOffset(1.10)
hist.GetYaxis().SetTitleOffset(0.99)
gStyle.SetOptStat(0)
CMS_lumi.CMS_lumi(canvas, 13, 0)
canvas.SaveAs("%s/%s%s.png" % (OUT_DIR, histname, label))
canvas.Close()
file.Close()
def getCurve(h):
# Temporary draw
c = TCanvas()
c.cd()
h.Smooth()
h.SetContour(2)
#h.Draw("COLZ")
h.Draw("CONT Z LIST")
c.Update()
# Get contours
curves = []
conts = TObjArray(gROOT.GetListOfSpecials().FindObject("contours"))
gs = TGraphSmooth("normal")
gin = TGraph(conts.At(0).At(0))
gout = gs.SmoothSuper(gin, "", 3)
x_m = array('d', [])
x_p = array('d', [])
y_m = array('d', [])
y_p = array('d', [])
for p in xrange(0, gout.GetN()):
gr_x = ROOT.Double(0.)
gr_y = ROOT.Double(0.)
gout.GetPoint(p, gr_x, gr_y)
x_m.append(-gr_x)
y_m.append(-gr_y)
x_p.append(gr_x)
y_p.append(gr_y)
# if opt == 'w':
# x_p[0] = 0.
# x_m[0] = 0.
curves.append(TGraph(len(x_p), x_p, y_p))
curves.append(TGraph(len(x_m), x_m, y_m))
curves.append(TGraph(len(x_p), x_p, y_m))
curves.append(TGraph(len(x_m), x_m, y_p))
c.Close()
return curves
def PlotOnCanvas(self, pdf_name):
tdrstyle.setTDRStyle()
canvas = TCanvas("c1", "c1", 600, 600)
self.histo.SetTitleOffset(1.6, 'xyz')
if self.option == "colz":
canvas.SetRightMargin(0.2)
self.histo.SetContour(100)
self.histo.Draw(self.option)
if self.logx:
canvas.SetLogx()
if self.logy:
canvas.SetLogy()
if self.logz:
canvas.SetLogz()
canvas.Print(pdf_name, 'Title:' + self.title)
canvas.Close()
def PlotOnCanvas(self, pdf_name):
tdrstyle.setTDRStyle()
canvas = TCanvas("c1", "c1", 600, 600)
self.histo.SetTitleOffset(1.6, 'xyz')
self.histo.SetMinimum(0)
self.histo.SetLineWidth(2)
self.histo.SetTitle(self.title)
if self.logx:
canvas.SetLogx()
if self.logy:
canvas.SetLogy()
self.histo.SetMinimum(1)
self.histo.Draw(self.option)
canvas.Print(pdf_name,
'Title:' + self.title + " (sample : %s)" % self.filename)
canvas.Close()
def drawQCDNNLOCorr():
filename = path + "lindert_qcd_nnlo_sf.root"
histname1 = "eej"
histname2 = "evj"
histname3 = "vvj"
file1 = ensureTFile(filename)
hist1 = file1.Get(histname1)
hist2 = file1.Get(histname2)
hist3 = file1.Get(histname3)
hist1.SetDirectory(0)
hist2.SetDirectory(0)
hist3.SetDirectory(0)
file1.Close()
c1 = TCanvas("c1", "sf plot", 800, 600)
hist1.SetTitle("QCD NNLO SF")
hist1.GetXaxis().SetTitle("V p_{T} (GeV)")
hist1.GetYaxis().SetTitle("QCD NNLO SF")
hist1.GetYaxis().SetRangeUser(1., 1.18)
hist1.SetLineColor(3)
hist2.SetLineColor(2)
hist3.SetLineColor(4)
hist1.SetLineWidth(3)
hist2.SetLineWidth(3)
hist3.SetLineWidth(3)
hist1.SetMarkerStyle(8)
hist1.SetMarkerColor(3)
hist2.SetMarkerStyle(8)
hist2.SetMarkerColor(2)
hist3.SetMarkerStyle(8)
hist3.SetMarkerColor(4)
leg = TLegend(0.15, 0.6, 0.3, 0.8)
leg.AddEntry(hist1, "DY+Jets")
leg.AddEntry(hist2, "W+Jets")
leg.AddEntry(hist3, "Z+Jets")
c1.SetLogx()
hist1.Draw("LP HIST")
hist2.Draw("LP HIST SAME")
hist3.Draw("LP HIST SAME")
leg.Draw("SAME")
gStyle.SetOptStat(0)
c1.SaveAs("./plotsSF/QCDNNLOCorr.pdf")
c1.SaveAs("./plotsSF/QCDNNLOCorr.png")
c1.Close()
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 Draw(self, option_=None):
name = self.hist.GetName()
canvas = TCanvas(name, name)
canvas.Draw()
if self.hist.GetLogY(): gPad.SetLogy(1)
if option_: option = option_
else: option = self.options
self.h().Draw(option)
self.h().SetTitle("")
self.h().GetXaxis().SetTitle(self.GetXaxis())
self.h().GetYaxis().SetTitle(self.GetYaxis())
if self.hist.GetLegend():
self.hist.GetLegend().Draw()
for ext in self.hist.GetExtensions():
canvas.SaveAs("%s/%s%s" %
(self.hist.GetOutputDir(), canvas.GetTitle(), ext))
canvas.Write()
canvas.Clear()
canvas.Close()
def draw(fitter, save_name, **kwargs):
"""Draw helper function
This can safely be ignored in view of understanding this script
and it doesn't do anything but drawing a fit. It won't change
any number.
"""
c = TCanvas("canvas", "", 500, 500)
try:
fitter.draw(c, **kwargs)
# NOTE The broad-except is only used to make this script running under
# any circumstances and ignore any reason for which a fit could not
# be drawn.
except Exception as e: # pylint: disable=broad-except
print(f"Could not draw fit")
print(fitter)
print(e)
c.SaveAs(save_name)
c.Close()
def draweffplot(filename1, histname1, name1, ptvseta):
if 'Electron' in filename1:
lepton = "electron"
else:
lepton = "muon"
file1 = ensureTFile(filename1)
hist1 = file1.Get(histname1)
hist = hist1
hist.SetDirectory(0)
file1.Close()
if '2016' in filename1:
year = '2016'
elif '2017' in filename1:
year = '2017'
elif '2018' in filename1:
year = '2018'
c1 = TCanvas("c1", "sf plot", 800, 600)
hist.SetOption("COLZ")
hist.SetTitle("%s trigger scale factor %s" % (lepton, year))
if ptvseta:
hist.GetXaxis().SetTitle("#eta")
hist.GetYaxis().SetTitle("p_{T}")
if lepton == "muon":
if year == '2016':
hist.GetYaxis().SetRangeUser(0, 800)
else:
hist.GetYaxis().SetRangeUser(0, 1200)
else:
if year == '2017':
hist.GetYaxis().SetRangeUser(0, 1000)
else:
hist.GetYaxis().SetRangeUser(0, 1000)
hist.GetYaxis().SetTitleOffset(1.2)
else:
hist.GetXaxis().SetTitle("p_{T}")
hist.GetYaxis().SetTitle("#eta")
hist.GetZaxis().SetRangeUser(0.7, 1.0)
hist.Draw()
gStyle.SetOptStat(0)
c1.SaveAs("./plotsSF/%s_trigger_sf_%s.pdf" % (lepton, year))
c1.SaveAs("./plotsSF/%s_trigger_sf_%s.png" % (lepton, year))
c1.Close()
def checklegend(samples,tag=""):
"""Check legend entries: colors, titles, ..."""
# https://root.cern.ch/doc/master/classTLegend.html
LOG.header("checklegend"+tag.replace(' ',''))
output = ensuredir('plots')
fname = "%s/testStyle_legend%s"%(output,tag)
#height = 0.05*(len(samples))
xdim = 550
ydim = 50*(len(samples)+2)
#width = 0.4
#x1, y1 = 0.1, 0.9
print ">>> Canvas: %sx%s (nsamples=%d)"%(xdim,ydim,len(samples))
canvas = TCanvas('canvas','canvas',xdim,ydim)
#legend = TLegend(x1,y1,x1+width,y1-height)
legend = TLegend(0,0,1,1)
legend.SetBorderSize(0)
legend.SetMargin(0.12)
#legend.SetTextSize(tsize)
#legend.SetNColumns(ncols)
#legend.SetColumnSeparation(colsep)
#legend.SetHeader("HTT style",'C')
legend.SetTextFont(42) # bold for title
hists = [ ]
for sample in samples:
color = STYLE.getcolor(sample,verb=2)
title = STYLE.gettitle(sample,latex=True,verb=2)
style = 'ep' if 'Data' in sample else 'f'
hist = TH1F(sample,title,1,0,1)
hist.SetFillColor(color)
#hist.SetLineColor(kBlack)
hist.SetLineWidth(2)
hist.SetMarkerColor(kBlack)
#hist.SetMarkerStyle(1)
legend.AddEntry(hist,title,style)
if 'Data' in sample: hist.Draw('E1')
hists.append(hist)
legend.Draw()
canvas.SaveAs(fname+".png")
canvas.SaveAs(fname+".pdf")
canvas.Close()
