canvProfile = prepare_single_canvas(
'upstreamEnergy_e' + str(energy) + 'GeV_eta' + str(eta),
'Upstream energy vs energy in first layer for #eta = ' +
str(eta))
draw_1histogram(hUpstremCellProfile,
'E_{firstLayer} ' + energyUnit,
'upstream energy ' + energyUnit)
hUpstremCellProfile.Fit(fitProfile, "SR")
for ibin in reversed(
range(0,
hUpstremCellProfile.GetXaxis().GetNbins())):
if hUpstremCellProfile.GetBinContent(ibin) > 0:
lastNonEmpty = ibin
break
hUpstremCellProfile.GetXaxis().SetRange(0, lastNonEmpty + 3)
legendProfile = draw_text([str(energy) + ' GeV e^{-}, B = 4T'],
[0.67, 0.18, 0.85, 0.28], 9, 0)
legendProfile.SetTextSize(0.05)
legendProfile.SetTextFont(42)
canvProfile.Update()
# save canvases filled for each energy and eta
if calo_init.output(ifile):
canvProfile.SaveAs(
calo_init.output(ifile) + "_previewProfile_eta" +
str(eta) + "_e" + str(energy) + "GeV.png")
else:
canvProfile.SaveAs("upstremCorrection_previewProfile_eta" +
str(eta) + "_" + str(layer * width) +
"cm.png")
if calo_init.args.previewPhi:
canvPhi = prepare_single_canvas(
'phi_e' + str(energy) + 'GeV__eta' + str(eta),
cRes.cd()
# Fit energy resolution
fRes = TF1("res", "sqrt([0]*[0] + pow([1]/sqrt(x),2))",5,600)
fRes.SetParName(0,"const")
fRes.SetParName(1,"sqrt")
fRes.SetLineColor(colour)
fitResult = gRes.Fit(fRes, 'S')
# Draw graph and all labels
gRes.Draw("ape")
if calo_init.args.axisMax:
gRes.GetYaxis().SetRangeUser(0, calo_init.args.axisMax)
formula = "#frac{#sigma_{E}}{E} = " + str(round(fitResult.Get().Parameter(0)*100,2))+"% #oplus #frac{"+str(round(fitResult.Get().Parameter(1)*100,2))+"%}{#sqrt{E}}"
if not calo_init.args.noLinearity:
draw_text([formula], [0.55,0.8,0.95,0.95], colour, 0).SetTextSize(0.05)
else:
draw_text([formula], [0.55,0.7,0.95,0.85], colour, 0).SetTextSize(0.05)
if calo_init.args.technical:
constString = "const: "+str(round(fitResult.Get().Parameter(0),4))+" #pm "+str(round(fitResult.Get().Error(0),4))
samplingString = "sampl: "+str(round(fitResult.Get().Parameter(1),4))+" #pm "+str(round(fitResult.Get().Error(1),4))
draw_text([constString, samplingString], [0.55,0.68,0.88,0.76], colour+1, 0).SetTextSize(0.05)
draw_text(["energy resolution"], [0.2,0.88, 0.45,0.98], 1, 0).SetTextSize(0.05)
if calo_init.args.noLinearity and calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.67,0.88, 0.95,0.98], kGray+3, 0).SetTextSize(0.05)
cRes.Update()
if not calo_init.args.noLinearity:
padLin.cd()
gLin.Draw("ape")
draw_text(["linearity"], [0.2,0.78, 0.4,0.88], 1, 0).SetTextSize(0.05*factor)
if calo_init.args.specialLabel:
# add second axis
canv.SetRightMargin(0.1)
all_graphs[0].GetXaxis().SetRangeUser(0, 68)
all_graphs[0].GetXaxis().SetLabelOffset(0.02)
gPad.RangeAxis(0, gPad.GetUymin(), 68, gPad.GetUxmax())
axis = TGaxis(gPad.GetUxmin(), gPad.GetUymin(), gPad.GetUxmax(),
gPad.GetUymin(),
gPad.GetUxmin() * calo_init.args.X0density,
gPad.GetUxmax() * calo_init.args.X0density, 506, "-")
axis.SetLabelSize(0.05)
axis.SetTitleSize(0.07)
axis.SetTitleOffset(0.9)
axis.SetLabelOffset(0.02)
axis.Draw()
axis.SetLabelFont(42)
unit1 = draw_text(['(cm)'], [0.91, 0.09, 1, 0.14], 1, 0)
unit1.SetTextSize(0.05)
unit1.SetTextFont(42)
unit2 = draw_text(['(X_{0})'], [0.91, 0.16, 1, 0.21], 1, 0)
unit2.SetTextSize(0.05)
unit2.SetTextFont(42)
canv.Update()
# Draw all labels
if calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.57, 0.88, 0.85, 0.98],
kGray + 3, 0).SetTextSize(0.05)
canv.Update()
# Save canvas and root file with graph, const term and sampling term
if calo_init.output(0):
if calo_init.args.axisMax:
all_graphs[0].SetMaximum(calo_init.args.axisMax)
if calo_init.args.axisMin:
all_graphs[0].SetMinimum(calo_init.args.axisMin)
canv.Update()
lines = []
for iLine, line in enumerate(avgSF):
lines.append(TLine(0, avgSF[iLine], 65, avgSF[iLine]))
lines[iLine].SetLineColor(colour[iLine])
all_graphs[iLine].SetMarkerColor(colour[iLine])
all_graphs[iLine].SetLineColor(colour[iLine])
lines[iLine].Draw('same')
if len(graphTitles) > 1:
draw_text(graphTitles, [0.18,0.9 - 0.07 * len(graphTitles),0.4,0.95], 0.4, 0).SetTextSize(0.06)
# Draw all labels
if calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.57,0.88, 0.85,0.98], kGray+3, 0).SetTextSize(0.05)
canv.Update()
# Save canvas and root file with graph, const term and sampling term
if calo_init.output(0):
canv.SaveAs(calo_init.output(0)+".eps")
canv.SaveAs(calo_init.output(0)+".png")
plots = TFile(calo_init.output(0)+".root","RECREATE")
if calo_init.args.preview:
cPreview.SaveAs("preview_"+calo_init.output(0)+".png")
else:
canv.SaveAs("sampling_fraction_plots.eps")
dSigma = result.Get().Error(2)
resolution_list.append("#color["+str(colours[ifile])+"]{"+legend[ifile]+str(round(sigma / mean * 100 ,2))+" %}")
mean_list.append("#color["+str(colours[ifile])+"]{"+legend[ifile]+str(round((mean-energy)/energy*100 ,1))+" %}")
prepare_histogram(hEn, ';E_{beam} '+energyUnit+';fraction of events', colours[ifile])
hEn.GetXaxis().SetRangeUser(0.9 * energy, 1.1* energy)
if ifile == 0:
hEn.DrawCopy()
else:
hEn.DrawCopy("sameep")
fit.Draw("same")
canv.Update()
if not calo_init.args.noLinearity:
draw_text(["energy resolution", "#color[1]{#sigma_{E_{rec}}/#LTE_{rec}#GT}"]
+ resolution_list,
[0.17,0.8-0.05*len(resolution_list),0.42,0.88], 1, 1)
draw_text(["linearity", "#color[1]{(#LTE_{rec}#GT-E_{beam})/E_{beam}}"]
+ mean_list,
[0.7,0.8-0.05*len(resolution_list),0.95,0.88], 1, 1)
else:
draw_text(["energy resolution", "#color[1]{#sigma_{E_{rec}}/#LTE_{rec}#GT}"]
+ resolution_list,
[0.6,0.7-0.07*len(resolution_list),0.95,0.78], 1, 0)
if calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.57,0.88, 0.85,0.98], kGray+3, 0).SetTextSize(0.05)
canv.Update()
if calo_init.output(ifile):
canv.Print("energyDistribution_"+calo_init.output(0)+".png")
else:
all_graphs[0].GetXaxis().SetRangeUser(0,68)
all_graphs[0].GetXaxis().SetLabelOffset(0.02)
gPad.RangeAxis(0,gPad.GetUymin(),68,gPad.GetUxmax())
axis = TGaxis(gPad.GetUxmin(),
gPad.GetUymin(),
gPad.GetUxmax(),
gPad.GetUymin(),
gPad.GetUxmin() * calo_init.args.X0density,
gPad.GetUxmax() * calo_init.args.X0density,506,"-")
axis.SetLabelSize(0.05)
axis.SetTitleSize(0.07)
axis.SetTitleOffset(0.9)
axis.SetLabelOffset(0.02)
axis.Draw()
axis.SetLabelFont(42)
unit1 = draw_text(['(cm)'],[0.91,0.09,1,0.14] , 1, 0)
unit1.SetTextSize(0.05)
unit1.SetTextFont(42)
unit2 = draw_text(['(X_{0})'],[0.91,0.16,1,0.21] , 1, 0)
unit2.SetTextSize(0.05)
unit2.SetTextFont(42)
canv.Update()
# Draw all labels
if calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.57,0.88, 0.85,0.98], kGray+3, 0).SetTextSize(0.05)
canv.Update()
# Save canvas and root file with graph, const term and sampling term
if calo_init.output(0):
# Set proper names for the plot legend
if len(calo_init.args.legend) > 1:
graphTitles = calo_init.args.legend
elif calo_init.args.legend:
graphTitles, check = calo_init.substitute(calo_init.args.legend[0])
else:
graphTitles=[]
for ileg, legend in enumerate(graphTitles):
graphTitles[ileg] = legend.replace("formula","#frac{#sigma_{E}}{E} = #frac{"+str(round(samplTerm[ileg]*100.,2))+"%}{#sqrt{E}} #oplus "+str(abs(round(constTerm[ileg]*100.,2)))+"%")
graphTitles = ['#color['+str(colour[i])+']{'+t+'}' for i,t in enumerate(graphTitles)]
# Draw all labels
if not calo_init.args.noLinearity:
padRes.cd()
draw_text(graphTitles, [0.4,0.85 - 0.07 * len(graphTitles),0.95,0.95], 1, 0).SetTextSize(0.04)
else:
draw_text(graphTitles, [0.3,0.8 - 0.07 * len(graphTitles),0.95,0.86], 1, 0).SetTextSize(0.04)
if not (calo_init.args.noLinearity and calo_init.args.title):
draw_text(["energy resolution"], [0.2,0.88, 0.4,0.98], 1, 0).SetTextSize(0.05)
else:
cRes.SetTopMargin(0.1)
draw_text([calo_init.args.title], [0.,0.9, 1,1], 1, 0).SetTextSize(0.05)
if calo_init.args.noLinearity and calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.67,0.88, 0.95,0.98], 1, 0).SetTextSize(0.05)
if not calo_init.args.noLinearity:
padLin.cd()
draw_text(["linearity"], [0.2,0.78, 0.4,0.88], 1, 0).SetTextSize(0.05*factor)
if calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.67,0.78, 0.95,0.88], 1, 0).SetTextSize(0.05*factor)
# fill energy-dependent graphs
param0.SetPoint(ifile,energyGraph,result.Get().Parameter(0))
param0.SetPointError(ifile,energyErrorGraph,result.Get().Error(0))
param1.SetPoint(ifile,energyGraph,result.Get().Parameter(1))
param1.SetPointError(ifile,energyErrorGraph,result.Get().Error(1))
if calo_init.args.preview:
canvProfile = prepare_single_canvas( 'upstreamEnergy_e'+str(energy)+'GeV_eta'+str(eta), 'Upstream energy vs energy in first layer for #eta = '+str(eta))
draw_1histogram(hUpstremCellProfile, 'E_{firstLayer} '+energyUnit,'upstream energy '+energyUnit)
hUpstremCellProfile.Fit(fitProfile, "SR")
for ibin in reversed(range(0,hUpstremCellProfile.GetXaxis().GetNbins())):
if hUpstremCellProfile.GetBinContent(ibin) > 0:
lastNonEmpty = ibin
break
hUpstremCellProfile.GetXaxis().SetRange(0, lastNonEmpty + 3)
legendProfile = draw_text([str(energy)+' GeV e^{-}, B = 4T'], [0.67,0.18, 0.85,0.28], 9, 0)
legendProfile.SetTextSize(0.05)
legendProfile.SetTextFont(42)
canvProfile.Update()
# save canvases filled for each energy and eta
if calo_init.output(ifile):
canvProfile.SaveAs(calo_init.output(ifile) + "_previewProfile_eta" + str(eta) + "_e"+str(energy)+"GeV.png")
else:
canvProfile.SaveAs("upstremCorrection_previewProfile_eta"+str(eta)+"_"+str(layer*width)+"cm.png")
if calo_init.args.previewPhi:
canvPhi = prepare_single_canvas( 'phi_e'+str(energy)+'GeV__eta'+str(eta), 'Phi distribution of first layer deposits for #eta = '+str(eta))
draw_1histogram(hCellPhi, '#varphi ' + angleUnit,'E_{firstLayer} ' + energyUnit)
# Draw all labels
if calo_init.args.specialLabel:
canvProfile.cd()
draw_text([calo_init.args.specialLabel], [0.57,0.88, 0.85,0.98], kGray+3, 0).SetTextSize(0.05)
else:
graphTitles = []
for ileg, legend in enumerate(graphTitles):
graphTitles[ileg] = legend.replace(
"formula", "#frac{#sigma_{E}}{E} = #frac{" +
str(round(samplTerm[ileg] * 100., 2)) + "%}{#sqrt{E}} + " +
str(round(constTerm[ileg] * 100., 2)) + "%")
graphTitles = [
'#color[' + str(colour[i]) + ']{' + t + '}'
for i, t in enumerate(graphTitles)
]
# Draw all labels
if not calo_init.args.noLinearity:
padRes.cd()
draw_text(graphTitles, [0.55, 0.95 - 0.08 * len(graphTitles), 0.95, 0.95],
1, 0).SetTextSize(0.04)
elif not calo_init.args.specialLabel:
draw_text(graphTitles, [0.55, 0.95 - 0.08 * len(graphTitles), 0.95, 0.95],
1, 0).SetTextSize(0.04)
else:
draw_text(graphTitles, [0.55, 0.9 - 0.08 * len(graphTitles), 0.95, 0.85],
1, 0).SetTextSize(0.04)
draw_text(["energy resolution"], [0.2, 0.88, 0.4, 0.98], 1,
0).SetTextSize(0.05)
if calo_init.args.noLinearity and calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.67, 0.88, 0.95, 0.98], 1,
0).SetTextSize(0.05)
if not calo_init.args.noLinearity:
padLin.cd()
draw_text(["linearity"], [0.2, 0.78, 0.4, 0.88], 1,
0).SetTextSize(0.05 * factor)
fitResult = gRes.Fit(fRes, 'S')
# Draw
cRes = TCanvas("resolution", "Energy resolution", 1200, 900)
gRes.Draw("ape")
if calo_init.args.axisMax:
gRes.GetYaxis().SetRangeUser(0, calo_init.args.axisMax)
formula = str(round(fitResult.Get().Parameter(0), 4)) + " #oplus #frac{" + str(
round(fitResult.Get().Parameter(1), 4)) + "}{#sqrt{E}}"
constString = "const: " + str(round(fitResult.Get().Parameter(0),
4)) + " #pm " + str(
round(fitResult.Get().Error(0), 4))
samplingString = "sampl: " + str(round(fitResult.Get().Parameter(1),
4)) + " #pm " + str(
round(fitResult.Get().Error(1), 4))
draw_text([formula], [0.55, 0.8, 0.88, 0.86], colour, 0)
draw_text([constString, samplingString], [0.55, 0.7, 0.88, 0.78], colour + 1,
0)
cRes.Update()
# Save canvas and root file with graph, const term and sampling term
if calo_init.output(0):
cRes.SaveAs(calo_init.output(0) + ".png")
plots = TFile(calo_init.output(0) + ".root", "RECREATE")
else:
cRes.SaveAs("energy_resolution_plots.png")
plots = TFile("energy_resolution_plots.root", "RECREATE")
gRes.Write()
const = numpy.zeros(1, dtype=float)
sampl = numpy.zeros(1, dtype=float)
constErr = numpy.zeros(1, dtype=float)
mean_list.append("#color[" + str(colours[ifile]) + "]{" + legend[ifile] +
str(round((mean - energy) / energy * 100, 1)) + " %}")
prepare_histogram(hEn, ';E_{beam} ' + energyUnit + ';fraction of events',
colours[ifile])
hEn.GetXaxis().SetRangeUser(0.9 * energy, 1.1 * energy)
if ifile == 0:
hEn.DrawCopy()
else:
hEn.DrawCopy("sameep")
fit.Draw("same")
canv.Update()
if not calo_init.args.noLinearity:
draw_text(
["energy resolution", "#color[1]{#sigma_{E_{rec}}/#LTE_{rec}#GT}"] +
resolution_list, [0.17, 0.8 - 0.05 * len(resolution_list), 0.42, 0.88],
1, 1)
draw_text(["linearity", "#color[1]{(#LTE_{rec}#GT-E_{beam})/E_{beam}}"] +
mean_list, [0.7, 0.8 - 0.05 * len(resolution_list), 0.95, 0.88],
1, 1)
else:
draw_text(
["energy resolution", "#color[1]{#sigma_{E_{rec}}/#LTE_{rec}#GT}"] +
resolution_list, [0.6, 0.7 - 0.07 * len(resolution_list), 0.95, 0.78],
1, 0)
if calo_init.args.specialLabel:
draw_text([calo_init.args.specialLabel], [0.57, 0.88, 0.85, 0.98],
kGray + 3, 0).SetTextSize(0.05)
canv.Update()
if calo_init.output(ifile):
