def GetStack(self, colors='', pr=''):
if pr == '': pr = self.processList
elif isinstance(pr, str) and ',' in pr:
pr = pr.replace(' ', '').split(',')
npr = len(pr)
if isinstance(colors, dict): colors = [colors[p] for p in pr]
elif colors == '': colors = [1] * npr
elif isinstance(colors, str) and ',' in colors:
colors = colors.replace(' ', '').split(',')
hStack = THStack('hStack', '')
for p, col in zip(pr, colors):
if isinstance(self.histoname, list):
for hname in self.histoname:
self.indic[p][hname].SetFillColor(col)
self.indic[p][hname].SetFillStyle(1000)
self.indic[p][hname].SetLineColor(0)
self.indic[p][hname].SetLineStyle(0)
self.indic[p][hname].SetLineWidth(0)
hStack.Add(self.indic[p][hname])
else:
self.indic[p][self.histoname].SetFillColor(col)
self.indic[p][self.histoname].SetFillStyle(1000)
self.indic[p][self.histoname].SetLineColor(0)
self.indic[p][self.histoname].SetLineStyle(0)
self.indic[p][self.histoname].SetLineWidth(0)
hStack.Add(self.indic[p][self.histoname])
return hStack
def make_pdf_plot(key, pos=(0.7, 0.7, 0.9, 0.9)):
h = getHist(f_all, key)
h.SetLineStyle(1)
h.SetLineWidth(5)
#h.SetFillStyle(1001)
h.SetLineColor(kBlack)
hs = THStack("hs_" + key, "")
h0 = getHist(f_0, key)
h1 = getHist(f_1, key)
h2 = getHist(f_2, key)
h0.SetLineStyle(5)
h0.SetFillStyle(3005)
h0.SetFillColor(kRed)
h0.SetLineColor(kRed)
hs.Add(h0)
h1.SetLineStyle(5)
h1.SetFillStyle(3005)
h1.SetFillColor(kBlue)
h1.SetLineColor(kBlue)
hs.Add(h1)
h2.SetLineStyle(5)
h2.SetFillStyle(3005)
h2.SetFillColor(kGreen)
h2.SetLineColor(kGreen)
hs.Add(h2)
leg = TLegend(pos[0], pos[1], pos[2], pos[3])
leg.AddEntry(h, 'total')
leg.AddEntry(h0, 'y == Pred == 0')
leg.AddEntry(h1, 'y == Pred == 1')
leg.AddEntry(h2, 'y == Pred == 2')
return h, hs, leg
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 study_cal_eff():
# Import data and MC files:
f_data = TFile.Open("../trees_5gev_e/data_nn50.root", 'read')
t_data = f_data.data
f_mc = TFile.Open("../trees_5gev_e/lucas.root", 'read')
t_mc = f_mc.lumical
t_mc.AddFriend("lumical_noise=lumical",
"../trees_5gev_e/lucas_geocuts_noise_cal.root")
t_mc.AddFriend("lumical_eff=lumical",
"../trees_5gev_e/lucas_geocuts_noise_cal_eff.root")
c = TCanvas()
hs = THStack("hs", "title")
t_data.Draw("energy*(layer > 1)>>h_data50(200, 0, 50)",
"energy*(layer > 1) > 0")
h_data50 = gROOT.FindObject("h_data50")
h_data50.SetTitle("Data")
h_data50.SetLineWidth(2)
h_data50.SetLineColor(1)
hs.Add(h_data50, "histo")
t_mc.Draw("cal_energy_new/0.0885>>h_mc(200, 0, 50)",
"cal_energy_new/0.0885 > 0", "", 100000)
h_mc = gROOT.FindObject("h_mc")
h_mc.SetTitle("MC smearing and cal eff")
h_mc.SetLineWidth(2)
h_mc.SetLineColor(3)
h_mc.Scale(t_data.GetEntries() / 100000) #t_mc.GetEntries())
hs.Add(h_mc, "histo")
t_mc.Draw("cal_energy_smeared7/0.0885>>h_mc7(200, 0, 50)",
"cal_energy_smeared7/0.0885 > 0", "", 100000)
h_mc7 = gROOT.FindObject("h_mc7")
h_mc7.SetTitle("MC smearing=0.7*#sigma")
h_mc7.SetLineWidth(2)
h_mc7.SetLineColor(2)
h_mc7.Scale(t_data.GetEntries() / 100000) #t_mc.GetEntries())
hs.Add(h_mc7, "histo")
print(h_mc7.GetEntries())
hs.Draw("nostack")
hs.SetTitle(
"Deposited energy in the pads of calorimeter;E, [MIP]; N_{hits}")
c.SetGridx()
c.SetGridy()
c.BuildLegend()
c.Update()
input("wait")
def getStack(self, lumi, name, var, nbin, xmin, xmax, cut, options,
xlabel):
hs = THStack(name, "")
for b in self.blocks:
AuxName = "auxStack_block_" + name + "_" + b.name
haux = b.getTH1F(lumi, AuxName, var, nbin, xmin, xmax, cut,
options, xlabel)
haux.SetFillColor(b.color)
hs.Add(haux)
del haux
can_aux = TCanvas("can_%s_%s" % (name, b.name))
can_aux.cd()
hs.Draw()
del can_aux
if xmax != xmin:
hs.GetXaxis().SetTitle(xlabel)
b = int((xmax - xmin) / nbin)
ylabel = "Events / " + str(b) + " GeV"
else:
ylabel = "# events"
hs.GetYaxis().SetTitle(ylabel)
return hs
def __draw_stack(self, regions, th1d_dict, output_name):
canvas = TCanvas("canvas", 'A basic canvas', 1000, 600)
stack = THStack("stack", "stack")
leg = Plotting.Create_Legend(0.60, 0.60, 0.95, 0.95)
for region in regions:
hist = th1d_dict[region]
hist.SetLineColor(1)
hist.SetLineWidth(1)
hist.SetMarkerColor(self.__get_colour(region))
hist.SetMarkerStyle(0)
hist.SetFillColor(self.__get_colour(region))
leg.AddEntry(hist, self.__get_label(region), "f")
stack.Add(hist)
del hist
stack.Draw("HIST")
stack.GetYaxis().SetTitle("Events")
stack.GetXaxis().SetTitle("True #it{E_{T}^{miss}} [GeV]")
leg.Draw()
canvas.Print(output_name)
def plot_calibrations(group_data, voltage, cal_pars_list, stacked=False):
group_name = str(group_data[0].run_number)
run = group_data[2]
name = str(run.run_number)
hists_and_lines = []
for cal_pars in cal_pars_list:
pars = parameters.gain_pars[cal_pars]
run.calibrate_energies(voltage, pars)
hist = make_hist(name, run.calibrated_energies, 0, 3500)
K_line = TLine(1460.820, 0, 1460.820, 1000000)
K_line.SetLineColor(632)
Tl_line = TLine(2614.511, 0, 2614.511, 1000000)
Tl_line.SetLineColor(632)
hists_and_lines.append([hist, K_line, Tl_line])
if stacked:
print('Plotting stacked calibrated histograms.')
run_canvas = TCanvas()
run_canvas.SetLogy()
colors = [808, 397, 436, 424, 628, 852, 800, 863, 403, 797]
color_index = 0
hs = THStack('hs', 'Group %s Histograms' % group_name)
for entry in hists_and_lines:
title = str(run.run_number)
entry[0].SetLineColor(colors[color_index])
color_index += 1
hs.Add(entry[0])
hs.Draw('nostack')
K_line = TLine(1460.820, 0, 1460.820, 1000000)
K_line.SetLineColor(632)
K_line.Draw()
Tl_line = TLine(2614.511, 0, 2614.511, 1000000)
Tl_line.SetLineColor(632)
Tl_line.Draw()
run_canvas.BuildLegend()
path = 'output/group_' + str(group_data[0].run_number) + '/'
run_canvas.Print((path + str(group_data[0].run_number) +
'_stacked_calibrated_histogram.pdf['))
run_canvas.Print((path + str(group_data[0].run_number) +
'_stacked_calibrated_histogram.pdf'))
run_canvas.Print((path + str(group_data[0].run_number) +
'_stacked_calibrated_histogram.pdf]'))
else:
print('Plotting calibrated energy histogram.')
run_canvas = TCanvas("run_canvas", "run canvas")
run_canvas.Divide(3, int(len(cal_pars_list) / 2))
canvas_index = 1
for entry in hists_and_lines:
pad = run_canvas.cd(canvas_index)
pad.SetLogy()
entry[0].Draw()
entry[1].Draw()
entry[2].Draw()
pad.Update()
canvas_index += 1
path = 'output/group_' + group_name + '/'
run_canvas.Print((path + name + '_calibrated_histograms.pdf['))
run_canvas.Print((path + name + '_calibrated_histograms.pdf'))
run_canvas.Print((path + name + '_calibrated_histograms.pdf]'))
def make_stack(tfile, stack_procs, chan, sys, distr):
global mc_stack_n
hs = THStack("mc_stack_%d" % mc_stack_n, "mc_stack_%d" % mc_stack_n)
for proc in stack_procs.split(','):
histo_name = std_histo_name(args.chan, proc, args.sys, args.distr)
logging.debug(histo_name)
if not tfile.Get(histo_name):
logging.warning(histo_name + ' not in the file ' + args.in_file)
continue
histo = tfile.Get(histo_name)
if args.scale_stack:
histo.Scale(args.scale_stack)
logging.debug(proc + ' ' + str(histo.Integral()))
# histo styling
col = plotting_root.nick_info[proc]['color']
histo.SetFillColor(col)
#histo.SetLineColor( col ); # it's needed for shapes
histo.SetMarkerStyle(20)
#histo.SetLineStyle(proc_ocurance);
histo.SetMarkerColor(col)
hs.Add(histo, "HIST")
mc_stack_n += 1
return hs
def stack_n_legend(used_histos,
shift=0.,
exp_legend=False,
sort_dy=False,
leg=None):
'''stack_n_legend(used_histos)
used_histos = [(histo, nick of process, channel), ...]
first check if there are different channels -- then add the channel name to the legend
also the line style changes for different channels of the same process for histograms
(not sure if it is a good hack)
'''
channels = [c for _, _, c in used_histos]
homogeneous_channels = all(c == channels[0] for c in channels)
# build Stach and legend
hs = THStack("mc_stack", "mc_stack")
#leg = TLegend(0.7 - (0.15 if not homogeneous_channels else 0.), 0.4, 0.89, 0.89)
if not leg:
if exp_legend:
leg = TLegend(0.8 - shift, 0.55, 1. - shift, 0.92)
else:
leg = TLegend(0.7 - shift, 0.55, 0.89 - shift, 0.92)
leg.SetBorderSize(0)
process_counter = {} # for distinguishing processes in different channels
def sort_w_dy_option(histo_nick):
order = nick_order.get(histo_nick, 1)
if sort_dy and 'dy' in histo_nick:
order = 0
return order
#for histo, nick, channel in sorted(used_histos, key=lambda h_n: nick_order.get(h_n[1], 1)):
for histo, nick, channel in sorted(
used_histos, key=lambda h_n: sort_w_dy_option(h_n[1])):
logging.debug("plotting stack_n_legend: %s %s" % (nick, channel))
proc_ocurance = process_counter.setdefault(nick, 1)
process_counter[nick] += 1
col = nick_colour[nick]
histo.SetFillColor(col)
#histo.SetLineColor( col ); # it's needed for shapes
histo.SetMarkerStyle(20)
histo.SetLineStyle(proc_ocurance)
histo.SetMarkerColor(col)
#used_histos.append(histo) # hopefully root wont screw this up
hs.Add(histo, "HIST")
# to have legend in the same order
for histo, nick, channel in sorted(
used_histos, key=lambda h_n: -sort_w_dy_option(h_n[1])):
if homogeneous_channels:
leg.AddEntry(histo, nick_info[nick]['legend'], "F")
else:
leg.AddEntry(histo, "%s %s" % (nick, channel), "F")
return hs, leg
def Stack(can, reverse=False):
if can.GetPrimitive('pad_top'):
return Stack(can.GetPrimitive('pad_top'), reverse=reverse)
from ROOT import TH1, THStack
stack = THStack('stack', 'stack')
xaxislabel, yaxislabel = '', ''
binlabels = []
if reverse:
the_primitives = reversed(can.GetListOfPrimitives())
else:
the_primitives = can.GetListOfPrimitives()
for i in the_primitives:
if issubclass(type(i), TH1):
stack.Add(i)
if not xaxislabel: xaxislabel = i.GetXaxis().GetTitle()
if not yaxislabel: yaxislabel = i.GetYaxis().GetTitle()
if not binlabels and i.GetXaxis().GetBinLabel(1):
for j in range(i.GetNbinsX()):
binlabels.append(i.GetXaxis().GetBinLabel(j + 1))
can.Clear()
tobject_collector.append(stack)
can.cd()
stack.Draw('hist')
stack.GetXaxis().SetTitle(xaxislabel)
stack.GetYaxis().SetTitle(yaxislabel)
if binlabels:
for i in range(stack.GetXaxis().GetNbins()):
stack.GetXaxis().SetBinLabel(i + 1, binlabels[i])
can.Modified()
can.Update()
can.RedrawAxis()
return
def backgroundStack( self ):
#implement reordering here by total yield
bkgStack = THStack()
for p in reversed( self.__processes ):
if not p.isSignal():
bkgStack.Add( p.nominal() )
return bkgStack
def plot_hist_diff(histlist1, histlist2, labellist, log, overflow, filename,
options):
canv = TCanvas("c1", "c1", 800, 600)
canv.SetTopMargin(10)
canv.SetRightMargin(100)
if log: gPad.SetLogy()
histstack = THStack("stack", histlist1[0].GetTitle())
legend = TLegend(0.76, 0.88 - 0.08 * len(histlist1), 0.91, 0.88, '', 'NDC')
colorlist = [4, 8, 2, 6, 1]
if options: options += " NOSTACK"
else: options = "NOSTACK"
maximum = 0
for i in range(len(histlist1)):
entries = histlist1[i].GetEntries()
bad_entries = histlist2[i].GetEntries()
histlist1[i].SetLineColorAlpha(colorlist[i], 0.65)
histlist1[i].SetLineWidth(3)
if entries: histlist1[i].Scale(1. / entries)
if bad_entries: histlist2[i].Scale(1. / bad_entries)
histlist1[i].Add(histlist2[i], -1.)
nbins = histlist1[i].GetNbinsX()
legend.AddEntry(
histlist1[i], "#splitline{" + labellist[i] +
"}{#splitline{%d total jets}{%d bad jets}}" %
(entries, bad_entries), "l")
if overflow:
histlist1[i].SetBinContent(
nbins, histlist1[i].GetBinContent(nbins) +
histlist1[i].GetBinContent(nbins + 1)) #overflow
histlist1[i].SetBinContent(
1, histlist1[i].GetBinContent(0) +
histlist1[i].GetBinContent(1)) #underflow
if histlist1[i].GetMaximum() > maximum:
maximum = histlist1[i].GetMaximum()
histstack.Add(histlist1[i])
#if i == 0: histlist[i].Draw(options)
#else: histlist[i].Draw(same+options)
histstack.SetMaximum(maximum * 1.4)
histstack.Draw(options)
histstack.GetXaxis().SetTitle(histlist1[0].GetXaxis().GetTitle())
histstack.GetYaxis().SetTitle(histlist1[0].GetYaxis().GetTitle())
legend.SetTextSize(0.02)
legend.SetFillStyle(0)
legend.SetBorderSize(0)
legend.Draw("SAME")
canv.SaveAs(filename)
if log: gPad.Clear()
canv.Clear()
del canv
def study_trigger():
# Import data and MC files:
f_data = TFile.Open("../trees_5gev_e/.root", 'read')
t_data = f_data.data
f_mc = TFile.Open("../trees_5gev_e/lucas.root", 'read')
t_mc = f_mc.lumical
t_mc.AddFriend("lumical_tr_clusters=lumical", "../trees_5gev_e/.root")
c = TCanvas()
t_data.Draw("tr1_n_clusters>>h_data(6, 0, 6)")
h_data = gROOT.FindObject("h_data")
h_data.SetTitle("Data")
h_data.SetLineWidth(2)
h_data.SetLineColor(1)
t_mc.Draw("tr1_n_hits>>h_mc(6, 0, 6)")
h_mc = gROOT.FindObject("h_mc")
h_mc.SetTitle("MC")
h_mc.SetLineWidth(2)
h_mc.SetLineColor(2)
h_mc.Scale(t_data.GetEntries() / t_mc.GetEntries())
t_mc.Draw("tr1_n_clusters>>h_mc2(6, 0, 6)", "n_triggers == 3")
h_mc2 = gROOT.FindObject("h_mc2")
h_mc2.SetTitle("MC w/ trigger")
h_mc2.SetLineWidth(2)
h_mc2.SetLineColor(4)
h_mc2.Scale(t_data.GetEntries() / t_mc.GetEntries())
hs = THStack("hs", "title")
hs.Add(h_data, "histo")
hs.Add(h_mc, "histo")
hs.Add(h_mc2, "histo")
hs.Draw("nostack")
hs.SetTitle(
"Number of clusters in the 1st tracker;N_{particles}; N_{events}")
c.SetGridx()
c.SetGridy()
c.BuildLegend()
c.Update()
input("wait")
class FractionJetHistograms (Histograms) :
'''eta distribution of the energy fraction per component'''
def __init__ (self, name) :
self.histos = []
for i in range (8) : # NB here we start from 0 on purpose, for simplicity
self.histos.append (TH2F (name + '_' + str (len (self.histos)), '', 240, -6, 6, 100, 0, 1))
super (FractionJetHistograms, self).__init__ (name)
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def fillJet (self, jet) :
try:
for i in range (1, 8) :
self.histos[i].Fill (jet.eta (), jet.component (i).fraction ())
except:
pass
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def fillEvent (self, jets) :
for jet in jets:
self.fillJet (jet)
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def summary (self) :
'''to be run after the event loop, before saving'''
self.summ = THStack (self.name + '_summ', 'total energy')
self.mean = []
for i in range (1, 8) :
# self.mean.append (self.histos[i].ProfileX ())
self.mean.append (self.fromProfileToHisto (self.histos[i].ProfileX (), 10 + i * 2))
self.summ.Add (self.mean[len (self.mean) - 1])
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def fromProfileToHisto (self, profile, color = 0) :
thename = profile.GetName ().replace('pfx', 'ave')
histo = TH1F (thename, '', profile.GetNbinsX (), profile.GetXaxis ().GetXmin (), profile.GetXaxis ().GetXmax ())
histo.SetFillColor (color)
for iBin in range (1, profile.GetNbinsX () + 1) :
histo.SetBinContent (iBin, profile.GetBinContent (iBin))
histo.SetBinError (iBin, profile.GetBinError (iBin))
return histo
# .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... .... ....
def Write (self, dir) :
'''overloads mother function, to save lists contents'''
self.dir = dir.mkdir( self.name )
self.dir.cd ()
self.summ.Write ()
for i in range (1, 8) :
self.histos[i].Write ()
self.mean[i-1].Write ()
dir.cd ()
def makeStack(mchists):
"""make stack plot"""
stack = THStack("hs", "")
index = 3
for hist in mchists:
hist.SetLineColor(index)
hist.SetFillColor(index)
stack.Add(hist)
index += 1
return stack
def myStack(colorlist_, backgroundlist_, legendname_):
hs = THStack("hs", "")
leg1 = myLegend()
for j in range(len(colorlist_)):
h = backgroundlist_[j]
h.SetFillColor(colorlist_[j])
h.SetLineColor(colorlist_[j])
hs.Add(h, "")
leg1.AddEntry(h, legendname_[j], "f")
return [hs, leg1]
class TheStack: from ROOT import THStack theStack = THStack() theHistogram = None def __init__(self,processes,lumi,plot,zScaleFac): self.theStack = THStack() for process in processes: temphist = process.loadHistogram(plot,lumi,zScaleFac) self.theStack.Add(temphist.Clone()) if self.theHistogram == None: self.theHistogram = temphist.Clone() else: self.theHistogram.Add(temphist.Clone()) def Add(self,addstack): for h in addstack.theStack.GetHists(): self.theStack.Add(h.Clone()) self.theHistogram.Add(h.Clone())
def plotstuff3(cuts,cutname):
hs = THStack("hs",cutname);
hs.Add(gDirectory.Get("h1"))
leg = TLegend(0.6,0.75,0.9,0.9)
events.Draw("eleClT-posClT>>h0(200,-10,10)",cuts[0],"goff")
leg.AddEntry(gDirectory.Get("h0"),"after base cuts")
hs.Add(gDirectory.Get("h0"))
gDirectory.Get("h0").SetLineColor(1)
#gDirectory.Get("h1").SetTitle(cutname)
for i in range(1,len(cuts)):
events.Draw("eleClT-posClT>>h{0}(100,-10,10)".format(i),makeCutString(cuts[0:i+1]),"goff")
leg.AddEntry(gDirectory.Get("h{0}".format(i)),"after {0} cut".format(cutnames[i]))
hs.Add(gDirectory.Get("h{0}".format(i)))
gDirectory.Get("h{0}".format(i)).SetLineColor(i+1)
hs.Draw("nostack")
leg.Draw()
hs.GetXaxis().SetTitle("tEle-tPos [ns]")
hs.GetYaxis().SetTitle("events/(0.1 ns)")
c.Print(sys.argv[1]+".pdf")
class TheStack: from ROOT import THStack theStack = THStack() theHistogram = None def __init__(self,processes,lumi,plot,zScaleFac,genMass=False,CIBins=False,cumulative=False): self.theStack = THStack() for process in processes: temphist = process.loadHistogram(plot,lumi,zScaleFac,genMass=genMass,CIBins=CIBins) if cumulative: temphist = makeHistoCumulative(temphist) self.theStack.Add(temphist.Clone()) if self.theHistogram == None: self.theHistogram = temphist.Clone() else: self.theHistogram.Add(temphist.Clone()) def Add(self,addstack): for h in addstack.theStack.GetHists(): self.theStack.Add(h.Clone()) self.theHistogram.Add(h.Clone())
def stack(wrps):
"""
Applies only to HistoWrappers. Returns StackWrapper.
Checks lumi to be equal among all wrappers.
>>> from ROOT import TH1I
>>> h1 = TH1I("h1", "", 2, .5, 4.5)
>>> h1.Fill(1,4)
1
>>> w1 = wrappers.HistoWrapper(h1, lumi=2.)
>>> h2 = TH1I("h2", "", 2, .5, 4.5)
>>> h2.Fill(1,3)
1
>>> h2.Fill(3,6)
2
>>> w2 = wrappers.HistoWrapper(h2, lumi=2.)
>>> w3 = stack([w1, w2])
>>> w3.histo.Integral()
13.0
>>> w3.lumi
2.0
"""
wrps = iterableize(wrps)
stk_wrp = None
lumi = 0.
info = None
sample = ""
for wrp in wrps:
if not isinstance(wrp, wrappers.HistoWrapper): # histo check
raise WrongInputError(
"stack accepts only HistoWrappers. wrp: "
+ str(wrp)
)
if not stk_wrp: # stack init
stk_wrp = THStack(wrp.name, wrp.title)
lumi = wrp.lumi
info = wrp.all_info()
sample = wrp.sample
elif lumi != wrp.lumi: # lumi check
raise NoLumiMatchError(
"stack needs lumis to match. (%f != %f)" % (lumi, wrp.lumi)
)
if sample != wrp.sample: # add to stack
sample = ""
if wrp.legend:
wrp.histo.SetTitle(wrp.legend)
stk_wrp.Add(wrp.histo)
if not info:
raise TooFewWrpsError(
"At least one Wrapper must be provided."
)
if not sample:
del info["sample"]
return wrappers.StackWrapper(stk_wrp, **info)
def DrawStackHistograms(histograms, outname, blind=True, verbose=False):
#hists_sorted = sorted(histograms, key=lambda h: h.Integral())
hs = THStack("h_stack", "")
h_obs = None
l = TLegend(0.77, 0.60, 0.90, 0.87)
for hist in histograms:
hname = hist.GetName()
if "data_obs" in hname:
if not blind:
h_obs = hist
SetHistogramStyle(h_obs, "Observed")
l.AddEntry(h_obs, "Observed", "p")
else:
SetHistogramStyle(hist)
label = GetLabelName(hist)
hs.Add(hist)
l.AddEntry(hist, label, "f")
h_est = hs.GetStack().Last().Clone()
if verbose:
est_err = Double(0.)
nbins_est = h_est.GetNbinsX()
est_yields = h_est.IntegralAndError(1, nbins_est, est_err)
print "predicted yields :", est_yields, "+/-", est_err
if not blind:
print "observed yields :", h_obs.Integral()
# draw
# SetCMSStyle() TODO
canvas = TCanvas()
gPad.SetLogy()
#ymax_hs = hs.GetMaximum()
#ymax = ymax_hs if h_obs is None else max(ymax_hs, h_obs.GetMaximum())
ymax = 10000
ymin = 0.1
hs.SetMaximum(ymax)
hs.SetMinimum(ymin)
hs.Draw("HIST")
l.Draw("same")
if not blind:
h_obs.Draw("same")
canvas.SaveAs(outname)
def plotstuff(cut1,cut2,cut3,cutname):
events.Draw("eleClT-posClT>>h1(200,-10,10)",cut1,"goff")
events.Draw("eleClT-posClT>>h2(200,-10,10)",cut2,"goff")
events.Draw("eleClT-posClT>>h3(200,-10,10)",cut3,"goff")
hs = THStack("hs","Effect of "+cutname+" cut");
hs.Add(gDirectory.Get("h1"))
hs.Add(gDirectory.Get("h2"))
hs.Add(gDirectory.Get("h3"))
hs.Draw("nostack")
leg = TLegend(0.6,0.75,0.9,0.9)
leg.AddEntry(gDirectory.Get("h1"),"passed all but this cut")
leg.AddEntry(gDirectory.Get("h2"),"passed all cuts")
leg.AddEntry(gDirectory.Get("h3"),"failed this cut")
leg.Draw()
gDirectory.Get("h1").SetLineColor(1)
gDirectory.Get("h2").SetLineColor(4)
gDirectory.Get("h3").SetLineColor(2)
hs.GetXaxis().SetTitle("tEle-tPos [ns]")
hs.GetYaxis().SetTitle("events/(0.1 ns)")
c.Print(sys.argv[1]+".pdf")
class TreeStack(object):
def __init__(self, name):
'''Name is the name you want for your treestack.'''
self.name = name
self.trees = dict()
self.styles = dict()
self.treenames = []
self.hists = []
self.histsum = None
self.stack = THStack('_'.join([self.name, 'stack']), 'title')
def add(self, name, tree, style=None):
'''Add a new tree with name "name".
Your tree should have the method Project.
You may implement tree weighting in this function.
style should behave like in tools.style
'''
self.trees[name] = tree
self.styles[name] = style
self.treenames.append(name)
def hname(self, name):
return '_'.join([self.name, name])
def project(self, var, cut, bins, xmin, xmax):
'''Fill the histograms with all trees,
using:
var : variable to plot
cut : cut to use
These variables will be passed to the Project method of your trees.
bins, xmin, xmax defins the histogram binning.
'''
for name in self.treenames:
tree = self.trees[name]
hname = self.hname(name)
hist = TH1F(hname, hname, bins, xmin, xmax)
self.hists.append(hist)
self.styles[name].formatHisto(hist)
tree.Project(hname, var, cut)
for hist in self.hists:
if self.histsum is None:
self.histsum = hist.Clone(self.hname('sum'))
else:
self.histsum.Add(hist)
self.stack.Add(hist)
def draw(self):
'''Draw the stack. Call project first.'''
self.stack.Draw()
def create_stacked_histo_array(mymatrix):
#creating 1d array of stacked histograms for each analysis setup (e.g. number of rows in mymatrix)
stack_hist_array = np.empty([mymatrix.shape[0], mymatrix.shape[1] - 1],
dtype=object)
mleg = ROOT.TLegend(0.65, 0.8, 0.75, 0.99)
mleg.SetBorderSize(0)
for i in range(mymatrix.shape[0]): #iterate over variations (rows)
for j in range(mymatrix.shape[1] -
1): #iterate over signal files to draw
hs = THStack(str(mymatrix[i][j].GetName()),
"") #create stack histo for each variation
hs.Add(mymatrix[i][mymatrix.shape[1] - 1]) #add background first
hs.Add(mymatrix[i][j])
if j == 0:
#only draw background once since it is independent of signal sample
mleg.AddEntry(mymatrix[i][mymatrix.shape[1] - 1],
mymatrix[i][mymatrix.shape[1] - 1].GetName(),
"L")
mleg.AddEntry(mymatrix[i][j], mymatrix[i][j].GetName(), "L")
stack_hist_array[i][j] = hs
del hs
return stack_hist_array, mleg
class TheStack: from ROOT import THStack theStack = THStack() theHistogram = None def __init__(self,processes,lumi,plot,files,fromTree=False): self.theStack = THStack() for process in processes: temphist = process.loadHistogram(lumi,files,plot,fromTree) self.theStack.Add(temphist.Clone()) if self.theHistogram == None: self.theHistogram = temphist.Clone() else: self.theHistogram.Add(temphist.Clone())
class TheStack2D: from ROOT import THStack theStack = THStack() theHistogram = None def __init__(self,processes,lumi,plot,zScale): self.theStack = THStack() for process in processes: temphist = process.loadHistogramProjected(plot,lumi,zScale) self.theStack.Add(temphist.Clone()) if self.theHistogram == None: self.theHistogram = temphist.Clone() else: self.theHistogram.Add(temphist.Clone())
def plot_ripples_shutter(self, path):
""" Plot ripples vs. shutter. That is one plot per pixel and one for the
total. """
system('mkdir -p %s' % path)
name = 'ripples_per_shutter_px%s_MPA%s'
x_title = 'Shutter'
y_title = 'Ripple count'
# Get number of shutters
no_shutters = len(self._MPAs[0].get_no_hits_shutter())
# Create THStack and its TLegend
stack = THStack(name % ('all', 'all'), name % ('all', 'all'))
leg = TLegend(.9, .5, 1., .9)
# Plots for each pixel and each MPA
for idx_mpa, MPA in enumerate(self._MPAs):
# Histogram for all pixels on one MPA
h_mpa = TH1F(name % ('all', idx_mpa), name % ('all', idx_mpa),
no_shutters, .5, no_shutters + .5)
for px in range(0, self._no_pxs_x * self._no_pxs_y):
# Histogram for one pixel on one MPA
h_mpa_px = TH1F(name % (px, idx_mpa), name % (px, idx_mpa),
no_shutters, .5, no_shutters + .5)
for shutter in range(0, no_shutters):
h_mpa_px.Fill(shutter + 1,
MPA.get_no_hits_shutter()[shutter][px])
h_mpa.Fill(shutter + 1,
MPA.get_no_hits_shutter()[shutter][px])
self._save_histo(h_mpa_px,
'%s/%s.pdf' % (path, name % (px, idx_mpa)),
x_title, y_title)
self._save_histo(h_mpa,
'%s/%s.pdf' % (path, name % ('all', idx_mpa)),
x_title, y_title)
h_mpa.SetFillColor(self._get_fill_color(idx_mpa))
stack.Add(h_mpa)
leg.AddEntry(h_mpa, 'MPA%s' % idx_mpa, 'f')
self._save_histo(stack, '%s/%s.pdf' % (path, name % ('all', 'all')),
x_title, y_title, leg)
def plot_cts_bx(self, path):
""" Plots counts vs. bunch crossing. """
system('mkdir -p %s' % path)
name = 'counts_per_bx_MPA%s'
x_title = 'BX'
y_title = 'Event count'
# Get number of shutters
no_shutters = len(self._MPAs[0].get_no_hits_shutter())
# Create THStack and its TLegend
stack = THStack(name % ('all'), name % ('all'))
leg = TLegend(.9, .5, 1., .9)
# Get max of all MPA's
max_bx = 0
for MPA in self._MPAs:
max_bx = max(max_bx, MPA.get_max())
# Plots for each pixel and each MPA
for idx_mpa, MPA in enumerate(self._MPAs):
# Histogram for one MPA
h_mpa = TH1F(name % (idx_mpa), name % (idx_mpa), 100, 0, 100)
for shutter in range(0, no_shutters):
for mem in range(0, self._no_mems):
if MPA.get_no_hits_shutter()[shutter][mem] != 0:
h_mpa.Fill(MPA.get_no_hits_shutter()[shutter][mem])
self._save_histo(h_mpa,
'%s/%s.pdf' % (path, name % (idx_mpa)),
x_title,
y_title,
logy=True)
h_mpa.SetLineColor(self._get_fill_color(idx_mpa))
stack.Add(h_mpa)
leg.AddEntry(h_mpa, 'MPA%s' % idx_mpa, 'l')
self._save_histo(stack,
'%s/%s.pdf' % (path, name % ('all')),
x_title,
y_title,
leg,
logy=True,
draw_option='nostack')
def plotstuff2(cut1,cut2,cutname):
events.Draw("eleClT-posClT>>h1(200,-10,10)",cut1,"goff")
events.Draw("eleClT-posClT>>h2(200,-10,10)",cut2,"goff")
hs = THStack("hs",cutname);
hs.Add(gDirectory.Get("h1"))
hs.Add(gDirectory.Get("h2"))
hs.Draw("nostack")
leg = TLegend(0.6,0.75,0.9,0.9)
leg.AddEntry(gDirectory.Get("h1"),"after base cuts")
leg.AddEntry(gDirectory.Get("h2"),"after vertexing cuts")
leg.Draw()
gDirectory.Get("h1").SetLineColor(1)
gDirectory.Get("h2").SetLineColor(2)
hs.GetXaxis().SetTitle("tEle-tPos [ns]")
hs.GetYaxis().SetTitle("events/(0.1 ns)")
c.Print(sys.argv[1]+".pdf")
class TheStack2DRun2: from ROOT import THStack theStack = THStack() theHistogram = None def __init__(self,processes,lumi,plot,zScale,CIBins=False): self.theStack = THStack() for index, process in enumerate(processes[0]): temphist = process.loadHistogramProjected(plot,lumi[0],zScale[0]) temphist.Add(processes[1][index].loadHistogramProjected(plot,lumi[1],zScale[1])) temphist.Add(processes[2][index].loadHistogramProjected(plot,lumi[2],zScale[2])) self.theStack.Add(temphist.Clone()) if self.theHistogram == None: self.theHistogram = temphist.Clone() else: self.theHistogram.Add(temphist.Clone())
