def plot_corr_root(sumx,
sumy,
sumz,
momentx,
momenty,
momentz,
ecal,
energy,
hits,
ratio,
out_file,
label,
compare=False,
gprev=0):
c1 = TCanvas("c1", "", 200, 10, 700, 500) #make
c1.SetGrid()
color = 2
gact, names = get_correlation(sumx, sumy, sumz, momentx, momenty, momentz,
ecal, energy, hits, ratio)
gact = get_dia(gact)
print(gact.shape[0], len(names))
Egraph = ROOT.TGraph2D()
fill_graph2D(Egraph, gact)
Egraph.Draw('colz')
ylen = len(names)
c1.Update()
Egraph.GetYaxis().SetLabelOffset(1)
Egraph.GetYaxis().SetNdivisions(10 * ylen)
Egraph.GetXaxis().SetLabelOffset(1)
Egraph.GetXaxis().SetNdivisions(10 * ylen)
ty = ROOT.TText()
ty.SetTextAlign(32)
ty.SetTextSize(0.011)
ty.SetTextFont(72)
tx = ROOT.TText()
tx.SetTextAlign(32)
tx.SetTextSize(0.011)
tx.SetTextFont(72)
tx.SetTextAngle(70)
y = np.arange(ylen)
for i in y:
ty.DrawText(-0.42, y[i], names[i])
tx.DrawText(y[i], -0.42, names[ylen - i - 1])
print(len(names))
c1.Update()
legend = TLegend(.6, .8, .9, .9)
if compare:
mse_corr = np.sum(np.square(gprev - gact)) / ylen
legend.SetHeader('{} mse_corr/num_features = {:.4f} '.format(
label, mse_corr))
else:
#legend.AddEntry(Egraph, label, "l")
legend.SetHeader(label)
legend.Draw()
c1.Update()
c1.Print(out_file + '_' + label + '.pdf')
return gact
def drawAppMVAOutputPlots(region, method, isMC):
MCstr = ""
if isMC:
MCstr = "BsMC12"
Region = region[:1].upper() + region[
1:] #capitalize first letter for retrieving file names
HistName = "ApplicationOutput" + MCstr + Region + method
CvsName = "canvasMVA_" + MCstr + method + region
canvas = TCanvas(CvsName, CvsName)
stackBDT = THStack(HistName, HistName)
histos = []
appFiles = []
canvas.Draw()
# note: TMVApp file name structure: "TMVApp"+Region+method+sample+".root"
# "BsMC12TMVApp"+Region+method+sample+".root"
appFile = TFile(MCstr + "TMVApp" + Region + method + ".root")
histo = appFile.Get("MVA_" + method).Clone(HistName)
histo.Scale(1 / histo.GetEntries())
stackBDT.Add(histo)
for sample in range(3):
appFiles.append(
TFile(MCstr + "TMVApp" + Region + method + str(sample) + ".root"))
histos.append(appFiles[sample].Get("MVA_" + method).Clone("HistName" +
str(sample)))
histos[sample].SetLineColor(2 * sample)
histos[sample].Scale(1 / histos[sample].GetEntries())
stackBDT.Add(histos[sample])
stackBDT.Draw("nostack")
if isMC:
applicationBDTLegend = TLegend(0.2, 0.7, 0.5, 0.9, "", "brNDC")
#applicationBDTLegend.SetHeader("Bs MC "+region.split("BsMC")[1])
applicationBDTLegend.SetHeader("Bs MC " + Region)
else:
applicationBDTLegend = TLegend(0.55, 0.7, 0.85, 0.9, "", "brNDC")
applicationBDTLegend.SetHeader(Region)
applicationBDTLegend.AddEntry(histo, "Full sample", "l")
applicationBDTLegend.AddEntry(histos[0],
"Trained on 0, tested on 1, applied on 2",
"l")
applicationBDTLegend.AddEntry(histos[1],
"Trained on 1, tested on 2, applied on 0",
"l")
applicationBDTLegend.AddEntry(histos[2],
"Trained on 2, tested on 0, applied on 1",
"l")
applicationBDTLegend.Draw("same")
applicationBDTLegend.SetFillColor(0)
applicationBDTLegend.SetLineColor(0)
canvas.SaveAs(figuresDir + "Application" + method + "Output_" + MCstr +
region + ".pdf")
def make_legend(self):
l = TLegend(0.15, 0.85, 0.4, 0.7)
if self.country != "wo China":
l.SetHeader(self.country, "c")
else:
l.SetHeader("World (without Mainland China)", "c")
for name in self.hists:
l.AddEntry(self.hists[name], name)
self.legend = l
def EMTFEta(plotter):
## variables for the plot
xTitle = "Generated muon |#eta|"
title = "%s;%s;%s" % (topTitle, xTitle, yTitle)
toPlot = "TMath::Abs(%s)" % (geneta)
h_bins = "(20,1.2,2.4)"
nBins = int(h_bins[1:-1].split(',')[0])
minBin = float(h_bins[1:-1].split(',')[1])
maxBin = float(h_bins[1:-1].split(',')[2])
c = newCanvas()
gPad.SetGridx(xGrid)
gPad.SetGridy(yGrid)
base = TH1F("base", title, nBins, minBin, maxBin)
base.SetMinimum(0)
base.SetMaximum(plotter.yMax)
base.GetXaxis().SetLabelSize(0.05)
base.GetYaxis().SetLabelSize(0.05)
base.GetXaxis().SetTitleSize(0.05)
base.GetYaxis().SetTitleSize(0.05)
base.Draw("")
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
denom_cut = AND(ok_eta(1.2, 2.4), ok_2_csc_lcts())
h1 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>20")), ok_emtf(20),
"same", kBlue)
h2 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>15")), ok_emtf(15),
"same", kRed)
h3 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>10")), ok_emtf(10),
"same", kGreen + 2)
h4 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>5")), ok_emtf(5),
"same", kOrange + 2)
h5 = draw_geff(plotter.tree, title, h_bins, toPlot,
AND(denom_cut, TCut("genParticle.pt>3")), ok_emtf(0),
"same", kBlack)
leg = TLegend(0.45, 0.2, .75, 0.5, "", "brNDC")
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetTextSize(0.05)
leg.SetHeader("EMTF")
leg.AddEntry(h1, "p_{T} > 20 GeV", "l")
leg.AddEntry(h2, "p_{T} > 15 GeV", "l")
leg.AddEntry(h3, "p_{T} > 10 GeV", "l")
leg.AddEntry(h4, "p_{T} > 5 GeV", "l")
leg.AddEntry(h5, "p_{T} > 0 GeV", "l")
leg.Draw("same")
c.Print("%sEff_EMTF_eta_Pt20_%s" %
(plotter.targetDir + subdirectory, plotter.ext))
del c, base, h1, leg, h2, h3, h4, h5
def saveDebugGraph(self, fitList, titleList, name, fitGraph):
canvas = TCanvas("Debug_%s" % (name), "y", 1000, 700)
# Add a legend
legend = TLegend(0.8, 0.9, 1.0, 0.7)
legend.SetHeader("Fits:")
# Remove Debug.root if it already exists
if os.path.exists("Debug.root") and self.GraphNumber == 0:
os.remove("Debug.root")
self.GraphNumber += 1
# Make sure we did point skimming and created goodPoints and badPoints
if not self.goodPoints is None: # goodPoints and badPoints are created together, so we only need to check one
self.goodPoints.Draw("AP3")
self.badPoints.Draw("P3")
legend.AddEntry(self.goodPoints, "Good Points")
legend.AddEntry(self.badPoints, "Bad Points")
else:
fitGraph.SetMarkerColor(4)
fitGraph.SetMarkerStyle(7)
fitGraph.Draw("AP3")
count = 0 # Counting variable
for fit in fitList: # Draw fits
legend.AddEntry(fit, titleList[count])
fit.SetLineColor(count+6)
fit.Draw("same")
canvas.Update()
count += 1
legend.Draw()
canvas.Update()
file = TFile("Debug.root", "UPDATE")
canvas.Write()
file.Close()
def plot_2(var):
for s in enumerate(attr):
c1 = TCanvas("c1", "Signals", 800, 800)
c1.cd()
c1.SetGrid()
#gStyle.SetTitleFontSize(8.1)
if s[1] in ('elf', 'muf', 'chm', 'cm', 'nm'):
c1.SetLogx()
for cc in channel:
hist[cc][s[1]].Draw('colz same')
#hist['qcd'][s[1]].Draw()
#hist['ctau0'][s[1]].Draw('same')
#hist['ttt'][s[1]].Draw('same')
legend = TLegend(0.91, 0.91, 0.99, 0.99)
legend.SetHeader('samples')
for cc in channel:
legend.AddEntry(hist[cc][s[1]], cc)
#legend.AddEntry(hist['qcd'][s[1]],'qcd')
#legend.AddEntry(hist['ctau0'][s[1]],'ctau0')
#legend.AddEntry(hist['ttt'][s[1]],'ttt')
legend.Draw()
c1.Print(path1 + s[1] + var + cutting.replace('(', '_').replace(
')', '_').replace('&&', 'A').replace('>', 'LG').replace(
'<', 'LS').replace('=', 'EQ').replace('.', 'P').replace(
'-', 'N').replace('Jet', 'J').replace('GenBquark', 'GBQ') +
".pdf")
c1.Update()
def makePDFs(root_file, subsystem, x_folder):
print "Analyzing %s vs %s" % (subsystem, x_folder)
what = "running_wm_rec_selection_vs_rec_tot"
cert = root_file.Get("DQM_None_DCS_%s_vs_DQM_%s_DCS_%s/%s/%s" % (subsystem,
subsystem,
subsystem,
x_folder,
what))
dcs = root_file.Get("DQM_None_DCS_None_vs_DQM_None_DCS_%s/%s/%s" % (subsystem,
x_folder,
what))
total = root_file.Get("DQM_None_DCS_None_vs_DQM_%s_DCS_%s/%s/%s" % (subsystem,
subsystem,
x_folder,
what))
d = TCanvas(subsystem, subsystem, 800, 800)
cert.SetMinimum(0.95)
cert.SetMaximum(1.01)
cert.Draw("AP")
dcs.SetMarkerColor(kRed)
dcs.Draw("P")
total.SetMarkerColor(kBlue)
total.Draw("P")
leg = TLegend(0.6, 0.8, 0.9, 0.9);
leg.SetTextFont(102)
leg.SetHeader("Info");
leg.AddEntry(cert, "Cert_Eff([DQM+DCS]/[DCS])", "lp");
leg.AddEntry(dcs, "DCS_Eff([DCS]/[ALL])", "lp");
leg.AddEntry(total, "Total_Eff([DQM+DCS]/[ALL])", "lp");
leg.Draw();
d.SaveAs("%s_%s.pdf" % (subsystem, x_folder))
def histo_creation(lumi2017_param, variable_param, binHist_param,
minHist_param, maxHist_param, titleX_param, titleY_param):
histo = []
legend = TLegend(0.5, 0.5, 0.9, 0.9)
canvas = TCanvas()
if (lumi2017_param):
legend.SetHeader("41.53 fb-1", "C")
canvas.SetName(variable_param + "2017")
else:
legend.SetHeader("35.9 fb-1", "C")
canvas.SetName(variable_param + "2016")
for i in range(len(MC_sample)):
foo = TH1F("essaie{}".format(i), "essaie{}".format(i), binHist_param,
minHist_param, maxHist_param)
rootfile[i].Get('events').Project("essaie{}".format(i), variable_param,
"weight")
histo.append(foo)
histo[i].SetFillColor(color[i])
histo[i].Scale(luminosity2017 * 1000 * cross_sec[i] / eventsN0[i])
if (not lumi2017_param):
histo[i].Scale(lumiRatio)
print(histo[i].GetEntries() * lumiRatio * luminosity2017 * 1000 *
cross_sec[i] / eventsN0[i])
histo[i].Draw()
legend.AddEntry(histo[i], MC_name[i], "f")
stack = THStack(variable_param, "")
for i in range(len(MC_sample)):
stack.Add(histo[len(MC_sample) - (i + 1)])
stack.Draw("HIST")
stack.GetXaxis().SetTitle(titleX_param)
stack.GetYaxis().SetTitle(titleY_param)
legend.Draw()
if (lumi2017_param):
canvas.SaveAs(localisation + "/results/MC_" + variable_param +
"2017.png")
else:
canvas.SaveAs(localisation + "/results/MC_" + variable_param +
"2016.png")
canvas.Write()
def createLegends(sample, h1, h2, h3, h4):
if sample == "data":
leg = TLegend(0.65, 0.75, 0.92, 0.90)
if sample == "zjets":
leg = TLegend(0.60, 0.75, 0.90, 0.90)
leg.SetHeader("Likelihood")
if sample == "truth":
leg = TLegend(0.60, 0.55, 0.90, 0.72)
leg.SetHeader("Truth-matching")
leg.SetFillStyle(0)
#leg.SetBorderSize(0)
leg.SetTextFont(62)
leg.SetTextSize(0.03)
leg.AddEntry(h1, "p_{T} #in [10, 60] GeV ", "l")
leg.AddEntry(h2, "p_{T} #in [60, 90] GeV ", "l")
leg.AddEntry(h3, "p_{T} #in [90, 130] GeV ", "l")
leg.AddEntry(h4, "p_{T} #in [130, 1000] GeV ", "l")
return leg
def draw_subdet(graphs, subdet):
l_min = 0
l_max = 0
subdet_str = ''
if subdet == 1:
l_min = 1
l_max = 4
subdet_str = 'TIB'
if subdet == 2:
l_min = 5
l_max = 9
subdet_str = 'TOB'
if subdet == 3:
l_min = 11
l_max = 13
subdet_str = 'TIDm'
if subdet == 4:
l_min = 14
l_max = 16
subdet_str = 'TIDp'
if subdet == 5:
l_min = 17
l_max = 24
subdet_str = 'TECm'
if subdet == 6:
l_min = 26
l_max = 33
subdet_str = 'TECp'
leg = TLegend(.92, .3, .99, .7)
leg.SetHeader('')
leg.SetBorderSize(0)
min_y = 1.
for layer in range(l_min, l_max + 1):
if layer == l_min: graphs[layer - 1].Draw('AP')
else: graphs[layer - 1].Draw('P')
graphs[layer - 1].SetMarkerColor(1 + layer - l_min)
min_y = graphs[layer - 1].GetMinimum(
) if graphs[layer - 1].GetMinimum() < min_y else min_y
leg.AddEntry(graphs[layer - 1], ' ' + get_short_layer_name(layer), 'p')
graphs[l_min - 1].SetTitle(subdet_str)
haxis = graphs[l_min - 1].GetHistogram()
haxis.GetYaxis().SetRangeUser(min_y, 1.)
leg.Draw()
c1.Print('SiStripHitEffTrendPlot_Subdet' + str(subdet) + '.png')
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 limitCompare(method):
signal, particle, particleP = "XZH", "Z", "Z'"
channels = ["0bonly", "bbonly"]
colors = [1,
610 + 4] #, 632, 800+7, 800, 416+1, 860+10, 600, 616, 921, 922]
masses, vals, graphs = {}, {}, {}
for j, c in enumerate(channels):
masses[c], vals[c] = fillValues("./combine/" + method + "/" + signal +
c + "_M%d.txt")
graphs[c] = TGraph()
n = 0
#print vals[c]
for i, m in enumerate(masses[c]):
#if not signals[i] >= 1000: continue
graphs[c].SetPoint(n, m, vals[c][m][3])
n = n + 1
graphs[c].SetLineColor(colors[j])
graphs[c].SetLineWidth(3)
graphs[c].Draw("SAME, L")
comp = TCanvas("comp", "Exclusion Limits", 800, 600)
comp.cd()
#c1.SetPad(c1.GetPad(0))
comp.GetPad(0).SetTopMargin(0.06)
comp.GetPad(0).SetRightMargin(0.05)
comp.GetPad(0).SetTicks(1, 1)
comp.GetPad(0).SetLogy()
for c in channels:
graphs[c].Draw("SAME, L")
graphs[channels[0]].GetXaxis().SetRangeUser(800., 5000.)
graphs[channels[0]].GetYaxis().SetRangeUser(0.25, 2.5e4)
graphs[channels[0]].GetXaxis().SetTitle("m_{" + particleP + "} (GeV)")
graphs[channels[0]].GetYaxis().SetTitle("#sigma(" + particleP +
") #bf{#it{#Beta}}(" + particleP +
" #rightarrow " + particle +
"H) (fb)")
drawAnalysis(signal)
#drawRegion(signal, True)
drawCMS(LUMI, YEAR, "Preliminary")
# legend
top = 0.9
leg = TLegend(0.4, top - len(channels) * 0.2 / 5., 0.99, top)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("95% CL expected limits")
for c in channels:
leg.AddEntry(graphs[c], getChannel(c), "l")
leg.Draw()
comp.Update()
comp.Print("plotsLimit/Multi.png")
comp.Print("plotsLimit/Multi.pdf")
def L1TrackMuonPt(plotter):
## variables for the plot
topTitle = ""
xTitle = "Generated muon p_{T} [GeV]"
title = "%s;%s;%s" % (topTitle, xTitle, yTitle)
toPlot = genpt
h_bins = "(20,0,100)"
nBins = int(h_bins[1:-1].split(',')[0])
minBin = float(h_bins[1:-1].split(',')[1])
maxBin = float(h_bins[1:-1].split(',')[2])
c = newCanvas()
base = TH1F("base", title, nBins, minBin, maxBin)
base.SetMinimum(0)
base.SetMaximum(plotter.yMax)
base.GetXaxis().SetLabelSize(0.05)
base.GetYaxis().SetLabelSize(0.05)
base.GetXaxis().SetTitleSize(0.05)
base.GetYaxis().SetTitleSize(0.05)
base.Draw("")
CMS_lumi.CMS_lumi(c, iPeriod, iPos)
denom_cut = AND(ok_eta(1.2, 2.4), ok_2_csc_lcts())
h1 = draw_geff(plotter.tree, title, h_bins, toPlot, denom_cut,
ok_l1trackmuon(20), "same", kBlue)
h2 = draw_geff(plotter.tree, title, h_bins, toPlot, denom_cut,
ok_l1trackmuon(15), "same", kRed)
h3 = draw_geff(plotter.tree, title, h_bins, toPlot, denom_cut,
ok_l1trackmuon(10), "same", kGreen + 2)
h4 = draw_geff(plotter.tree, title, h_bins, toPlot, denom_cut,
ok_l1trackmuon(5), "same", kOrange + 2)
h5 = draw_geff(plotter.tree, title, h_bins, toPlot, denom_cut,
ok_l1trackmuon(0), "same", kBlack)
leg = TLegend(0.45, 0.2, .75, 0.5, "", "brNDC")
leg.SetBorderSize(0)
leg.SetFillStyle(0)
leg.SetTextSize(0.05)
leg.SetHeader("L1TrackMuon")
leg.AddEntry(h1, "p_{T} > 20 GeV", "l")
leg.AddEntry(h2, "p_{T} > 15 GeV", "l")
leg.AddEntry(h3, "p_{T} > 10 GeV", "l")
leg.AddEntry(h4, "p_{T} > 5 GeV", "l")
leg.AddEntry(h5, "p_{T} > 0 GeV", "l")
leg.Draw("same")
c.Print("%sEff_L1TrackMuon_pt_Pt20_%s" %
(plotter.targetDir + subdirectory, plotter.ext))
del c, base, h1, leg, h2, h3, h4, h5
def plot2Dhist():
observed_sel = ["TT", "TL", "LT", "LL"]
charges = ["OS", "SS"]
flavours = ["ElEl", "MuMu"]
#input_path = "../OutputPlots_MMRates_LHFit_2DPt/"
input_path = "../OutputPlots_MMRates_LHFit_25ns_v7_FinalSelection_NominalBinning/"
set_fancy_2D_style()
for ch in charges:
for flav in flavours:
for sl in observed_sel:
path = input_path + ch + "_" + flav + "_" + sl + "/" + ch + "_" + flav + "_" + sl + "_Lep0Pt_VS_Lep1Pt.root"
myfile = TFile(path)
myhist = myfile.Get("observed")
c = TCanvas("c1", "Temp", 50, 50, 1000, 800)
header = None
if ch == "OS": header = "2 Lep SS Real CR"
elif ch == "SS": header = "2 Lep SS Fake CR"
legend = TLegend(0.2, 0.8, 0.4, 0.85)
# (x1,y1 (--> bottom left corner), x2, y2 (--> top right corner) )
legend.SetHeader(header)
legend.SetBorderSize(0) # no border
legend.SetFillStyle(0)
# Legend transparent background
legend.SetTextSize(0.04) # Increase entry font size!
legend.SetTextFont(42) # Helvetica
leg_ATLAS = TLatex()
leg_lumi = TLatex()
leg_ATLAS.SetTextSize(0.03)
leg_ATLAS.SetNDC()
leg_lumi.SetTextSize(0.03)
leg_lumi.SetNDC()
myhist.Draw("colz text")
legend.Draw()
leg_ATLAS.DrawLatex(0.2, 0.75,
"#bf{#it{ATLAS}} Work In Progress")
leg_lumi.DrawLatex(
0.2, 0.7, "#sqrt{s} = 13 TeV, #int L dt = 3.2 fb^{-1}")
canvasname = ch + "_" + flav + "_" + sl + "_observed"
c.SaveAs(canvasname + ".png")
def setup_canvas(hist_name):
canvas = TCanvas(hist_name, hist_name, 0, 0, 800, 800)
canvas.SetMargin(0.13, 0.05, 0.12, 0.05)
canvas.SetTicks(1, 1)
leg = TLegend(0.3, 0.15, 0.75, 0.4)
leg.SetNColumns(3)
leg.SetBorderSize(0)
leg.SetTextSize(0.03)
leg.SetTextFont(42)
leg.SetMargin(0.2)
leg.SetHeader("Train setup: #it{N}_{ev}^{training}, #it{n}_{#it{#varphi}}" +\
" #times #it{n}_{#it{r}} #times #it{n}_{#it{z}}", "C")
return canvas, leg
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 checkForOutliers(hist, qaContainer):
""" Checks for outliers in selected histograms.
Outliers are calculated by looking at the standard deviation. See: :func:`hasSignalOutlier()`.
This function is mainly a proof of concept, but could become more viable with a bit more work.
Note:
This function will add a large TLegend to the histogram noting the mean and the number of
outliers. It will also display the recalculated mean excluding the outlier(s).
Args:
hist (TH1): The histogram to be processed.
qaContainer (:class:`~processRuns.qa.qaFunctionContainer`): Contains information
about the QA function and histograms, as well as the run being processed.
Returns:
None
"""
# If outlier data point, print warning banner
if hist.GetName() == "":
tempList = hasSignalOutlier(
hist
) # array of info from hasSignalOutlier function, to print on legend
numOutliers = tempList[0]
mean = tempList[1]
stdev = tempList[2]
newMean = tempList[3]
newStdev = tempList[4]
if (numOutliers):
# Create TLegend and fill with information if there is an outlier.
leg = TLegend(0.15, 0.5, 0.7, 0.8)
SetOwnership(leg, False)
leg.SetBorderSize(4)
leg.SetShadowColor(2)
leg.SetHeader("#splitline{OUTLIER SIGNAL DETECTED}{IN %s BINS!}" %
numOutliers)
leg.AddEntry(
None, "Mean: %s, Stdev: %s" % ('%.2f' % mean, '%.2f' % stdev),
"")
leg.AddEntry(
None, "New mean: %s, New Stdev: %s" %
('%.2f' % newMean, '%.2f' % newStdev), "")
leg.SetTextSize(0.04)
leg.SetTextColor(2)
leg.Draw()
def runAllSamples(self):
gStyle.SetOptStat(0)
gROOT.SetBatch(True)
dict_run_hist = dict(
(k, self.runSample(k, h)) for k, h in self.dict_path_dir.items())
max_list = [
tuple(h.GetMaximum() for h in hist)
for hist in dict_run_hist.values()
]
max_h = max(max_list)
gROOT.SetBatch(False)
legend = TLegend(0.15, 0.7, 0.45, 0.83)
legend.SetHeader("Legend", "C")
c = TCanvas("C", "C", 2000, 500)
c.Divide(3, 1)
c.SetLogy()
i = 0
for k, (h, h_in, h_out) in dict_run_hist.items():
h.SetLineColor(i + 1)
h_in.SetLineColor(i + 1)
h_out.SetLineColor(i + 1)
legend.AddEntry(h, k, "l")
opt = "hist"
if i != 0:
opt += " same"
h.SetTitle("Runs")
h.SetMaximum(max_h[0])
h_in.SetMaximum(max_h[1])
h_out.SetMaximum(max_h[2])
c.cd(1)
h.Draw(opt)
c.cd(2)
h_in.Draw(opt)
c.cd(3)
h_out.Draw(opt)
i += 1
legend.Draw()
c.Print("test.png")
def setup_canvas(suffix, hist_name, opt_name, x_label, y_label):
full_name = "%s_canvas_%s_%s" % (hist_name, suffix, opt_name)
canvas = TCanvas(full_name, full_name, 0, 0, 800, 800)
canvas.SetMargin(0.12, 0.05, 0.12, 0.05)
canvas.SetTicks(1, 1)
frame = canvas.DrawFrame(-5, -0.5, +5, +0.5)
setup_frame(frame, x_label, y_label)
leg = TLegend(0.5, 0.7, 0.9, 0.9)
leg.SetBorderSize(0)
leg.SetTextFont(42)
leg.SetTextSize(0.03)
leg.SetHeader("Train setup: #it{N}_{ev}^{training}, #it{n}_{#it{#varphi}}" +\
" #times #it{n}_{#it{r}} #times #it{n}_{#it{z}}", "C")
return canvas, frame, leg
def draw_bragg_max(self):
#three histograms for bragg maxima
self.bragg_maxima_can = TCanvas("max_can_" + self.name, "Bragg maxima")
self.bragg_histograms = [TH1D(self.name + "line%i" %i, "Bragg max", 100, 130, 230)
for i in range(3)]
for i, line in enumerate(self.spectral_lines):
self.ntuple.Draw("maxC>>%sline%i" %(self.name, i), line, "goff")
for i, hist in enumerate(self.bragg_histograms):
hist.SetLineStyle(i + 1)
if i: hist.Draw("same")
else:
hist.Draw()
hist.GetYaxis().SetRangeUser(0,75)
leg_hist = TLegend(0.75,0.75,0.98,0.98)
leg_hist.SetHeader("Bragg maxima")
[leg_hist.AddEntry(hist,"alpha energy %i" %(i+1),"l") for i, hist in
enumerate(self.bragg_histograms)]
leg_hist.Draw();
h_Night = f2.Get(folder + '/' + histo)
h_Night.SetMarkerStyle(8)
h_Night.SetMarkerSize(0.5)
mainPad.cd()
h_Base.Draw()
h_Night.Draw("same p")
c1.Update()
var_name = histo.split("_", 1)[1]
leg = TLegend(0.330986, 0.884087, 0.879499, 0.97053)
leg.SetHeader(folder + '' + var_name, "C")
leg.SetNColumns(2)
leg.SetFillStyle(0)
leg.SetBorderSize(0)
leg.AddEntry(h_Base, "Baseline", "l")
leg.AddEntry(h_Night, "Nightly", "p")
leg.Draw()
c1.Update()
ratioPad.cd()
h1clone = h_Night.Clone()
h1clone.Sumw2()
h1clone.SetStats(0)
h1clone.Divide(h_Base)
def plot1D(histname, histnum2D, histden2D, year, channel, title="", log=False):
"""Plot efficiency."""
dir = ensureDirectory('plots/%d' % year)
name = "%s/%s_%s" % (dir, histname, channel)
if log:
name += "_log"
header = ""
xtitle = 'jet p_{T} [GeV]'
ytitle = 'b tag efficiencies' if '_b_' in histname else 'b mistag rate'
xmin, xmax = 20 if log else 10, histnum2D.GetXaxis().GetXmax()
ymin, ymax = 5e-3 if log else 0.0, 2.0
colors = [kBlue, kRed, kOrange]
x1, y1 = (0.27, 0.44) if '_b_' in histname else (0.55, 0.80)
width, height = 0.3, 0.16
x2, y2 = x1 + width, y1 - height
hists = createEff1D(histnum2D, histden2D)
canvas = TCanvas('canvas', 'canvas', 100, 100, 800, 700)
canvas.SetFillColor(0)
canvas.SetBorderMode(0)
canvas.SetFrameFillStyle(0)
canvas.SetFrameBorderMode(0)
canvas.SetTopMargin(0.04)
canvas.SetBottomMargin(0.13)
canvas.SetLeftMargin(0.12)
canvas.SetRightMargin(0.05)
canvas.SetTickx(0)
canvas.SetTicky(0)
canvas.SetGrid()
gStyle.SetOptTitle(0)
if log:
canvas.SetLogx()
canvas.SetLogy()
canvas.cd()
frame = hists[0]
for i, hist in enumerate(hists):
hist.SetLineColor(colors[i % len(colors)])
hist.SetMarkerColor(colors[i % len(colors)])
hist.SetLineWidth(2)
hist.SetMarkerSize(2)
hist.SetMarkerStyle(1)
hist.Draw('PE0SAME')
frame.GetXaxis().SetTitle(xtitle)
frame.GetYaxis().SetTitle(ytitle)
frame.GetXaxis().SetLabelSize(0.048)
frame.GetYaxis().SetLabelSize(0.048)
frame.GetXaxis().SetTitleSize(0.058)
frame.GetYaxis().SetTitleSize(0.058)
frame.GetXaxis().SetTitleOffset(1.03)
frame.GetYaxis().SetTitleOffset(1.04)
frame.GetXaxis().SetLabelOffset(-0.004 if log else 0.005)
frame.GetXaxis().SetRangeUser(xmin, xmax)
frame.SetMinimum(ymin)
frame.SetMaximum(ymax)
if title:
latex = TLatex()
latex.SetTextSize(0.04)
latex.SetTextAlign(13)
latex.SetTextFont(62)
latex.SetNDC(True)
latex.DrawLatex(0.15, 0.94, title)
legend = TLegend(x1, y1, x2, y2)
legend.SetTextSize(0.04)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
if header:
legend.SetTextFont(62)
legend.SetHeader(header)
legend.SetTextFont(42)
for hist in hists:
legend.AddEntry(hist, hist.GetTitle(), 'lep')
legend.Draw()
canvas.SaveAs(name + '.pdf')
canvas.SaveAs(name + '.png')
canvas.Close()
if out > 0:
hist.Scale(1. / hist.Integral())
###hist.Draw('HISTE')
###canvas.SaveAs(histname+".png")
###canvas.SaveAs(histname+".pdf")
###canvas.Close()
hists.append(hist)
gStyle.SetOptTitle(False)
canvas = TCanvas('canvas', 'canvas', 100, 100, 800, 600)
canvas.SetTopMargin(0.03)
legend = TLegend(0.7, 0.7, 0.85, 0.5)
legend.SetTextSize(0.04)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
legend.SetFillColor(0)
legend.SetTextFont(62)
legend.SetHeader(trigger)
legend.SetTextFont(42)
plotname = "%s_nTau_%s_comparison" % (trigger, filter)
hists[0].SetMaximum(1.18 * max(h.GetMaximum() for h in hists))
for hist in hists:
hist.Draw('HISTSAME')
legend.AddEntry(hist, hist.GetTitle(), 'l')
legend.Draw()
canvas.SaveAs(plotname + ".png")
canvas.SaveAs(plotname + ".pdf")
canvas.Close()
for hist in hists:
gDirectory.Delete(hist.GetName())
file.Close()
def DrawOverlap(fileVec,
histVec,
titleVec,
legendtext,
pngname,
logstatus=[0, 0],
xRange=[-99999, 99999, 1],
text_="",
x_=0.5,
y_=0.5,
legendloc=[0.53, 0.13, 0.93, 0.39]):
gStyle.SetOptTitle(0)
gStyle.SetOptStat(0)
#gStyle.SetTitleOffset(1.1,"Y");
#gStyle.SetTitleOffset(0.9,"X");
gStyle.SetLineWidth(3)
gStyle.SetFrameLineWidth(3)
i = 0
histList_ = []
histList = []
histList1 = []
maximum = []
## Legend
legpos = legendloc
leg = TLegend(legpos[0], legpos[1], legpos[2], legpos[3])
leg.SetBorderSize(0)
leg.SetNColumns(2)
leg.SetLineColor(1)
leg.SetLineStyle(1)
leg.SetLineWidth(1)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.049)
from PlotTemplates import myCanvas1D
c = myCanvas1D()
c.SetLogy(logstatus[1])
c.SetLogx(logstatus[0])
#c.SetBottomMargin(0.15)
#c.SetLeftMargin(0.15)
#c1_2 = TPad("c1_2","newpad",0.04,0.13,1,0.994)
#c1_2.Draw()
print("you have provided " + str(len(fileVec)) + " files and " +
str(len(histVec)) + " histograms to make a overlapping plot")
print "opening rootfiles"
c.cd()
#c1_2.SetBottomMargin(0.013)
#c1_2.SetLogy(logstatus[1])
#c1_2.SetLogx(logstatus[0])
#c1_2.cd()
ii = 0
inputfile = {}
print str(fileVec[(len(fileVec) - 1)])
for ifile_ in range(len(fileVec)):
print("opening file " + fileVec[ifile_])
inputfile[ifile_] = TFile(fileVec[ifile_])
print "fetching histograms"
for ihisto_ in range(len(histVec)):
print("printing histo " + str(histVec[ihisto_]))
histo = inputfile[ifile_].Get(histVec[ihisto_])
#status_ = type(histo) is TGraphAsymmErrors
histList.append(histo)
# for ratio plot as they should nt be normalize
histList1.append(histo)
#print histList[ii].Integral()
#histList[ii].Rebin(xRange[2])
#histList[ii].Scale(1.0/histList[ii].Integral())
maximum.append(histList[ii].GetMaximum())
maximum.sort()
ii = ii + 1
print histList
for ih in range(len(histList)):
tt = type(histList[ih])
if logstatus[1] is 1:
histList[ih].SetMaximum(100) #1.4 for log
histList[ih].SetMinimum(0.00001) #1.4 for log
if logstatus[1] is 0:
histList[ih].SetMaximum(1.4) #1.4 for log
histList[ih].SetMinimum(0.001) #1.4 for log
# print "graph_status =" ,(tt is TGraphAsymmErrors)
# print "hist status =", (tt is TH1D) or (tt is TH1F)
if ih == 0:
if tt is TGraphAsymmErrors:
histList[ih].Draw("APL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist")
if ih > 0:
#histList[ih].SetLineWidth(2)
if tt is TGraphAsymmErrors:
histList[ih].Draw("PL same")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].Draw("hist same")
if tt is TGraphAsymmErrors:
histList[ih].SetMaximum(10)
histList[ih].SetMarkerColor(colors[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetMarkerStyle(markerStyle[ih])
histList[ih].SetMarkerSize(1)
leg.AddEntry(histList[ih], legendtext[ih], "PL")
if (tt is TH1D) or (tt is TH1F) or (tt is TH1) or (tt is TH1I):
histList[ih].SetLineStyle(linestyle[ih])
histList[ih].SetLineColor(colors[ih])
histList[ih].SetLineWidth(3)
leg.AddEntry(histList[ih], legendtext[ih], "L")
histList[ih].GetYaxis().SetTitle(titleVec[1])
histList[ih].GetYaxis().SetTitleSize(0.052)
histList[ih].GetYaxis().SetTitleOffset(1.08)
histList[ih].GetYaxis().SetLabelSize(.052)
histList[ih].GetXaxis().SetRangeUser(xRange[0], xRange[1])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitle(titleVec[0])
histList[ih].GetXaxis().SetLabelSize(0.052)
histList[ih].GetXaxis().SetTitleSize(0.052)
histList[ih].GetXaxis().SetTitleOffset(1.14)
#histList[ih].GetXaxis().SetTickLength(0.07)
histList[ih].GetXaxis().SetNdivisions(508)
from PlotTemplates import SetCMSAxis
histList[ih] = SetCMSAxis(histList[ih], 1.0, 1.15)
#histList[ih].GetXaxis().SetMoreLogLabels();
#histList[ih].GetXaxis().SetNoExponent();
#histList[ih].GetTGaxis().SetMaxDigits(3);
i = i + 1
'''
pt = TPaveText(0.0877181,0.9,0.9580537,0.96,"brNDC")
pt.SetBorderSize(0)
pt.SetTextAlign(12)
pt.SetFillStyle(0)
pt.SetTextFont(22)
pt.SetTextSize(0.046)
text = pt.AddText(0.2,0.5,"CMS Internal")
'''
from PlotTemplates import drawenergy1D
pt_ = drawenergy1D(False)
for ipt in pt_:
ipt.Draw()
'''
if len(text_) >0:
ltx = TLatex()
ltx.SetTextFont(42)
ltx.SetTextSize(0.049)
#text_f = "#font[42]{Phase Scan}"
ltx.DrawTextNDC(x_,y_,text_)
'''
from PlotTemplates import ExtraText
text_ex = ExtraText(text_, x_, y_)
text_ex.Draw()
ExtraText("ECAL Endcaps", 0.4, 0.85)
ltx_ = TLatex()
ltx_.SetTextFont(42)
ltx_.SetTextSize(0.049)
ltx_.DrawLatexNDC(0.32, 0.81, "L1 e-#gamma object p_{T} > 10 GeV")
#text_ex.Draw()
#pt = TPaveText(0.0877181,0.9,0.9580537,0.96,"brNDC")
#text = pt.AddText(0.65,0.5,"Phase Scan data #sqrt{s} = 13 TeV (2018)")
#pt.Draw()
# t2a = TPaveText(0.0877181,0.81,0.9580537,0.89,"brNDC")
# t2a.SetBorderSize(0)
# t2a.SetFillStyle(0)
# t2a.SetTextSize(0.040)
# t2a.SetTextAlign(12)
# t2a.SetTextFont(62)
# histolabel1= str(fileVec[(len(fileVec)-1)])
# text1 = t2a.AddText(0.06,0.5,"CMS Internal")
# t2a.Draw()
leg.SetHeader("Matched TP energy")
leg.Draw()
#
# c.cd()
outputdirname = './'
histname = outputdirname + pngname
c.SaveAs(histname + '.png')
c.SaveAs(histname + '.pdf')
#outFile.cd()
#mc.Write()
#data.Write()
#dataUp.Write()
#dataDown.Write()
#ratio.Write()
#ratioUp.Write()
#ratioDown.Write()
#outFile.Close()
#print "Histograms written to ../data/PU.root file"
leg = TLegend(0.5, 0.7, 0.98, 0.9)
leg.SetBorderSize(0)
leg.SetFillStyle(0) #1001
leg.SetFillColor(0)
leg.SetHeader("Pile-up reweighting")
leg.AddEntry(dataUp, "Up", "pl")
leg.AddEntry(data, "Central", "pl")
leg.AddEntry(dataDown, "Down", "pl")
#leg.AddEntry(mc, "MC 25ns", "pl")
leg.AddEntry(mc, scenario, "pl")
c1 = TCanvas("c1", "PileUp reweighting", 800, 800)
c1.cd()
c1.GetPad(0).SetTopMargin(0.06)
c1.GetPad(0).SetRightMargin(0.05)
c1.GetPad(0).SetTicks(1, 1)
dataDown.SetTitle(";number of true interactions")
dataDown.GetXaxis().SetRangeUser(0., 100)
dataDown.Draw("HIST")
dataUp.Draw("SAME, HIST")
if 'y-title' in plots[plot]:
p.GetYaxis().SetTitle(plots[plot]['y-title'])
if 'y-min' in plots[plot]:
p.SetMinimum(plots[plot]['y-min'])
if 'y-max' in plots[plot]:
p.SetMaximum(plots[plot]['y-max'])
if 'x-max' in plots[plot]:
p.GetXaxis().SetRangeUser(plots[plot]['x-min'], plots[plot]['x-max'])
c2.SetGrid()
if plots[plot].get('y-log', False):
c2.SetLogy(1)
else:
c2.SetLogy(0)
if irun > 0 or ilumisection > 0 or ibx > 0:
drawoptions ='same'
legend.SetHeader(layer)
p.Draw(drawoptions)
legend.AddEntry(p.GetName(), '%i %s ls:%i-%i bx:%s' % (run, runs[run]['comments'], lumisection[0], lumisection[1], bx), 'lp')
# legend.AddEntry(p.GetName(), '%i LS %i-%i (%.2f - %.2f e33 cm^{-2}/s)' % (run, lumisection[0], lumisection[1], instLumi[run][lumisection[0]], instLumi[run][lumisection[1]]), 'lp')
ROOT.gPad.Modified()
ROOT.gPad.Update()
# end of loop over histos
# end of loop over bx intervals
# end of loop of lumisections
# end of loop over runs
latexLabel = TLatex()
latexLabel.SetTextSize(0.75 * c1.GetTopMargin())
latexLabel.SetNDC()
latexLabel.SetTextFont(42) # helvetica
# latexLabel.DrawLatex(0.27, 0.96, layer)
legend.Draw()
W = 800
T = 0.08 * H
B = 0.12 * H
L = 0.12 * W
R = 0.1 * W
legendHeightPer = 0.04
legendStart = 0.6
legendEnd = 0.97 - (R / W)
# legend = TLegend(0.7,0.7,0.88,0.88)
legend = TLegend(legendStart, 1 - T / H - 0.01 - legendHeightPer * (6),
legendEnd, 0.99 - (T / H) - 0.01)
legend.SetBorderSize(0)
legend.SetFillColor(0)
legend.SetHeader(myDir[idir], "L")
TGaxis.SetMaxDigits(3)
c = TCanvas('c', '', W, H)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetFrameFillStyle(0)
c.SetFrameBorderMode(0)
c.SetLeftMargin(L / W)
c.SetRightMargin(R / W)
c.SetTopMargin(T / H)
c.SetBottomMargin(B / H)
c.SetTickx(0)
c.SetTicky(0)
c.Draw()
c.cd()
legend.SetBorderSize(0)
yMin=0
yMax = max(eeHist.GetBinContent(eeHist.GetMaximumBin()),emHist.GetBinContent(mmHist.GetMaximumBin()))*1.5
hCanvas.DrawFrame(0,yMin,5,yMax,"; %s ; %s" %("#Delta R(ll)","N_{events} [a.u.]"))
ROOT.gStyle.SetOptStat(0)
eeHist.SetLineColor(ROOT.kRed)
eeHist.SetLineWidth(2)
eeHist.SetLineStyle(2)
#~ eeHist.SetLineColor(ROOT.kRed)
fakeHist = ROOT.TH1F()
fakeHist.SetLineColor(ROOT.kWhite)
legend.SetHeader("t#bar{t} Simulation")
legend.AddEntry(eeHist,"e^{#pm}e^{#mp}","l")
legend.AddEntry(emHist,"#mu^{#pm}#mu^{#mp}","l")
eeHist.Draw("samehist")
mmHist.Draw("samehist")
legend.Draw("same")
line1 = ROOT.TLine(0.3,0,0.3,yMax)
line2 = ROOT.TLine(1.6,0,1.6,yMax)
line1.SetLineColor(ROOT.kBlue+3)
line2.SetLineColor(ROOT.kBlue+3)
line1.SetLineWidth(2)
line2.SetLineWidth(2)
line1.SetLineStyle(2)
def efficiencytracking(var):
# plots the efficiency vs pT, eta and phi for all the species(it extracts the
# Efficiency from qa - tracking - efficiency if you have ran with-- make - eff)
hadron_list = [
"pion",
"proton",
"kaon",
"electron",
"muon",
]
color_list = [1, 2, 4, 6, 8]
marker_list = [20, 21, 22, 34, 45]
fileo2 = TFile("../codeHF/AnalysisResults_O2.root")
c1 = TCanvas("c1", "Efficiency")
gStyle.SetOptStat(0)
gStyle.SetErrorX(0)
gStyle.SetFrameLineWidth(2)
gStyle.SetTitleSize(0.045, "x")
gStyle.SetTitleSize(0.045, "y")
gStyle.SetMarkerSize(1)
gStyle.SetLabelOffset(0.015, "x")
gStyle.SetLabelOffset(0.02, "y")
gStyle.SetTickLength(-0.02, "x")
gStyle.SetTickLength(-0.02, "y")
gStyle.SetTitleOffset(1.1, "x")
gStyle.SetTitleOffset(1.0, "y")
c1.SetCanvasSize(800, 600)
c1.cd()
c1.SetGridy()
c1.SetGridx()
eff_list = []
if var == "Pt":
hempty = TH1F("hempty", ";Transverse Momentum(GeV/c);Efficiency", 100,
0.05, 10)
gPad.SetLogx()
elif var == "Eta":
hempty = TH1F("hempty", ";Pseudorapidity;Efficiency", 100, -4.0, 4.0)
elif var == "Phi":
hempty = TH1F("hempty", ";Azimuthal angle(rad);Efficiency", 100, 0.0,
6.0)
hempty.GetYaxis().CenterTitle()
hempty.GetXaxis().CenterTitle()
hempty.GetXaxis().SetNoExponent()
hempty.GetXaxis().SetMoreLogLabels(1)
hempty.Draw()
leg = TLegend(0.55, 0.15, 0.89, 0.35, "P")
leg.SetNColumns(2)
leg.SetHeader("Minimum bias KrKr #sqrt{s} = 6.46TeV", "C")
leg.SetFillColor(0)
for i, had in enumerate(hadron_list):
leff = fileo2.Get("qa-tracking-efficiency-%s/Efficiency" % had)
if var == "Pt":
eff = leff.At(0)
elif var == "Eta":
eff = leff.At(1)
elif var == "Phi":
eff = leff.At(2)
gPad.Update()
eff.Paint("p")
gr = eff.GetPaintedGraph().Clone()
for j in range(0, gr.GetN()):
gr.GetEXlow()[j] = 0
gr.GetEXhigh()[j] = 0
gr.SetLineColor(color_list[i])
gr.SetMarkerColor(color_list[i])
gr.SetMarkerStyle(marker_list[i])
eff_list.append(gr)
gr.Draw(" same p")
leg.AddEntry(eff_list[i], had, "p")
leg.Draw()
saveCanvas(c1, "efficiency_tracking_%s" % var)
gComptonPhotMFP.SetPoint(i, hPrimaryEnergy[i].GetMean(), MFPComptonPhot)
gComptonPhotMassicCS.SetPoint(i, hPrimaryEnergy[i].GetMean(),
massicCSComptonPhot)
# plot histograms
idx_1 = 3
idx_2 = 10
idx_3 = 28
leg = TLegend(.63, .62, .97, .93)
leg.SetBorderSize(0)
leg.SetFillColor(0)
leg.SetFillStyle(0)
leg.SetTextFont(42)
leg.SetTextSize(0.035)
leg.SetHeader("prim. photon energy", "C")
leg.AddEntry(hLStep[idx_1], "40 keV")
leg.AddEntry(hLStep[idx_2], "110 keV")
leg.AddEntry(hLStep[idx_3], "290 keV")
#step length histo
c1 = TCanvas("c1", "c1", 200, 10, 1200, 500)
c1.Divide(2)
c1.cd(1)
c1.cd(1).SetLogy()
hLStep[idx_1].Draw("hist")
hLStep[idx_2].Draw("hist,same")
hLStep[idx_2].SetLineColor(kBlue)
hLStep[idx_3].Draw("hist,same")
hLStep[idx_3].SetLineColor(kRed)
leg.Draw("same")
