def PlotRate(datasetsMgr, histoList, bkg, PU):
# Get Histogram name and its kwargs
taus = "SingleTau"
saveName = "Rate_%s_PU%s" % (taus, PU)
kwargs = GetHistoKwargs(saveName, opts)
hList = []
legDict = {}
algos = getAlgos()
# For-loop: All tau algorithms
for i, hName in enumerate(histoList, 0):
algo = hName.split("_")[0]
#if algo == "DiTau":
# taus = "DiTau"
# algo = hName.split("_")[-1]
if "ditau" in hName.lower():
return
#algo = hName.split("_")[-1]
#tau = hName.split("_")[1]
#if tau == "DiTau":
# taus = "DiTau"
# algo = hName.split("_")[-1]
aux.PrintFlushed("Plotting rate (%s-%s)" % (algo, taus), False)
h = datasetsMgr.getDataset(bkg).getDatasetRootHisto(
hName).getHistogram()
h.SetName(hName)
legDict[hName] = algos[i] #algo
hList.append(h)
# Create the rate histograms
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
# Set legend labels
for i, h in enumerate(p.histoMgr.getHistos(), 0):
hName = h.getName()
algo = h.getName().split("_")[0]
p.histoMgr.forHisto(hName, styles.getTauAlgoStyle(algo))
p.histoMgr.setHistoDrawStyle(hName, "HIST")
p.histoMgr.setHistoLegendStyle(hName, "L")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legDict)
# Draw and save the plot
saveName = "Rate_%s_PU%s" % (taus, PU)
plots.drawPlot(p, saveName, **kwargs)
# Add additional canvas text
histograms.addPileupText("PU=%s" % (PU))
histograms.addText(0.70, 0.88, taus, 17)
#histograms.addText(0.75, 0.88, taus, 17)
#histograms.addText(0.60, 0.78, plots._legendLabels[bkg], 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
#print
return
def PlotEfficiency(datasetsMgr, histoList, signal, PU):
# Get Histogram name and its kwargs
taus = "SingleTau"
saveName = "Efficiency_%s_%s" % (taus, signal)
kwargs = GetHistoKwargs(saveName, opts)
hList = []
legDict = {}
# For-loop: All tau algorithms
count = -1
for i, hName in enumerate(histoList, 0):
algo = hName.split("_")[0]
if algo == "DiTau":
if "TT_" in signal or "GluGlu" in signal:
pass
else:
return
taus = "DiTau"
algo = hName.split("_")[-1]
count += 1
aux.PrintFlushed("Plotting efficiency (%s-%s-%s)" %
(algo, taus, signal), False) #count==0)
h = datasetsMgr.getDataset(signal).getDatasetRootHisto(
hName).getHistogram()
h.SetName(hName)
legDict[hName] = algo
hList.append(h)
# Create the rate histograms
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
# Set legend labels
for h in p.histoMgr.getHistos():
hName = h.getName()
algo = h.getName().split("_")[0]
if algo == "DiTau":
algo = hName.split("_")[-1]
p.histoMgr.forHisto(hName, styles.getTauAlgoStyle(algo))
p.histoMgr.setHistoDrawStyle(hName, "HIST")
p.histoMgr.setHistoLegendStyle(hName, "L")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legDict)
# Draw and save the plot
saveName = "Efficiency_%s_%s" % (taus, signal)
plots.drawPlot(p, saveName, **kwargs)
# Add additional canvas text
histograms.addPileupText("PU=%s" % (PU))
# histograms.addText(0.75, 0.88, taus, 17)
histograms.addText(0.60, 0.88, plots._legendLabels[signal], 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
#print
return
def PlotTurnOns(datasetsMgr, histoList, signal, PU, saveName=None):
# Get Histogram name and its kwargs
myRegex = "(?:TurnOn)(.*)"
m = re.search(myRegex, histoList[0])
threshold = m.group(1)
if saveName==None:
#saveName = "TurnOns_%sGeV_%s" % (threshold, signal)
saveName = "TurnOns_%s_%s" % (threshold, signal)
kwargs = GetHistoKwargs(saveName, opts)
hList = []
legDict = {}
algos = getAlgos()
if "_all" in saveName:
algos = ["Inclusive", "1-prong", "3-prong", "#geq 1 #pi^{0}'s", "0 #pi^{0}'s"]
# For-loop: All tau algorithms
for l, hName in enumerate(histoList, 0):
algo = hName.split("_")[0]
msg = "Turn-on for \"%s\" algorithm (%s)" % (algo, signal)
aux.PrintFlushed(msg, False)
#aux.Print(msg, True)
h = datasetsMgr.getDataset(signal).getDatasetRootHisto(hName).getHistogram()
h.SetName(hName)
legDict[hName] = algos[l]
hList.append(h)
# Create the rate histograms
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
# Set legend labels
for i, h in enumerate(p.histoMgr.getHistos(), 0):
hName = h.getName()
algo = h.getName().split("_")[0]
if algo == "DiTau":
algo = hName.split("_")[-1]
if "_all" in saveName:
p.histoMgr.forHisto(hName, styles.getCaloStyle(i))
else:
p.histoMgr.forHisto(hName, styles.getTauAlgoStyle(algo))
p.histoMgr.setHistoDrawStyle(hName, "AP")
p.histoMgr.setHistoLegendStyle(hName, "P")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legDict)
# Draw and save the plot
saveName = saveName.replace("TurnOns_", "")
plots.drawPlot(p, saveName, **kwargs)
# Add additional canvas text
histograms.addPileupText("PU=%s" % (PU) )
histograms.addText(0.22, 0.86, plots._legendLabels[signal], 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
return
def PlotTurnOns(datasetsMgr, histoList, signal, PU):
# Get Histogram name and its kwargs
myRegex = "(?:TurnOn)(.*)"
m = re.search(myRegex, histoList[0])
threshold = m.group(1)
saveName = "TurnOns_%sGeV_%s" % (threshold, signal)
kwargs = GetHistoKwargs(saveName, opts)
hList = []
legDict = {}
# For-loop: All tau algorithms
for l, hName in enumerate(histoList, 0):
algo = hName.split("_")[0]
aux.PrintFlushed("Turn-on for \"%s\" algorithm (%s)" % (algo, signal),
False) #l==0)
h = datasetsMgr.getDataset(signal).getDatasetRootHisto(
hName).getHistogram()
h.SetName(hName)
legDict[hName] = algo
hList.append(h)
# Create the rate histograms
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
# Set legend labels
for h in p.histoMgr.getHistos():
hName = h.getName()
algo = h.getName().split("_")[0]
if algo == "DiTau":
algo = hName.split("_")[-1]
p.histoMgr.forHisto(hName, styles.getTauAlgoStyle(algo))
p.histoMgr.setHistoDrawStyle(hName, "AP")
p.histoMgr.setHistoLegendStyle(hName, "LP")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legDict)
# Draw and save the plot
plots.drawPlot(p, saveName, **kwargs)
# Add additional canvas text
histograms.addPileupText("PU=%s" % (PU))
# histograms.addText(0.75, 0.88, taus, 17)
histograms.addText(0.60, 0.88 - 0.50, plots._legendLabels[signal], 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
#print
return
def PlotRate(datasetsMgr, histoList, bkg, PU, taus):
# Get Histogram name and its kwargs
saveName = "Rate_%s_PU%s" % (
taus, PU
) # "Rate_" here incuded to apply customisations with kwargs. Drop later
kwargs = GetHistoKwargs(saveName, opts)
hList = []
legDict = {}
algos = getAlgos()
# For-loop: All tau algorithms
for i, hName in enumerate(histoList, 0):
algo = hName.split("_")[0]
aux.PrintFlushed("Plotting rate (%s-%s)" % (algo, taus), False)
h = datasetsMgr.getDataset(bkg).getDatasetRootHisto(
hName).getHistogram()
h.SetName(hName)
legDict[hName] = algos[i]
hList.append(h)
# Create the rate histograms
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
# Set legend labels
for i, h in enumerate(p.histoMgr.getHistos(), 0):
hName = h.getName()
algo = h.getName().split("_")[0]
p.histoMgr.forHisto(hName, styles.getTauAlgoStyle(algo))
p.histoMgr.setHistoDrawStyle(hName, "HIST")
p.histoMgr.setHistoLegendStyle(hName, "L")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legDict)
# Draw and save the plot
saveName = saveName.replace("Rate_",
"") #drop "Rate_" only AFTER getting kwargs
plots.drawPlot(p, saveName, **kwargs)
# Add additional canvas text
histograms.addPileupText("PU=%s" % (PU))
histograms.addText(0.66, 0.86, taus, 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
#print
return
def PlotRateVsEff(datasetsMgr, effHistoList, rateHistoList, signal, bkg, PU):
# Definitions
tgraphs = []
legendDict = {}
aux.PrintFlushed("Plotting ROC (%s-%s)" % (bkg, signal), False) #count==0)
# Get Histogram name and its kwargs
if "ditau" in effHistoList[0].lower():
if "TT_" in signal or "GluGlu" in signal:
pass
else:
return
saveName = "RateVsEff_DiTau_%s_PU%s" % (signal.split("_")[0], PU)
else:
saveName = "RateVsEff_SingleTau_%s_PU%s" % (signal.split("_")[0], PU)
kwargs_ = GetHistoKwargs(saveName, opts)
for i in range(0, len(effHistoList)):
if (i == 0):
g0 = convert2RateVsEffTGraph(datasetsMgr, effHistoList[i],
rateHistoList[i], signal, bkg)
g0.SetName("Calo")
elif (i == 1):
g1 = convert2RateVsEffTGraph(datasetsMgr, effHistoList[i],
rateHistoList[i], signal, bkg)
g1.SetName("Tk")
elif (i == 2):
g2 = convert2RateVsEffTGraph(datasetsMgr, effHistoList[i],
rateHistoList[i], signal, bkg)
g2.SetName("VtxIso")
elif (i == 3):
g3 = convert2RateVsEffTGraph(datasetsMgr, effHistoList[i],
rateHistoList[i], signal, bkg)
g3.SetName("RelIso")
elif (i == 4):
g4 = convert2RateVsEffTGraph(datasetsMgr, effHistoList[i],
rateHistoList[i], signal, bkg)
g4.SetName("Iso")
# Create the Rate Vs Efficiency TGraphs
p = plots.ComparisonManyPlot(g0, [g1, g2, g3, g4], saveFormats=[])
# Set individual styles
for index, h in enumerate(p.histoMgr.getHistos()):
hName = h.getName()
legendDict[hName] = styles.getCaloLegend(index)
p.histoMgr.forHisto(hName, styles.getCaloStyle(index))
p.histoMgr.setHistoDrawStyle(h.getName(),
"LX") # "X" = Do not draw error bars
p.histoMgr.setHistoLegendStyle(h.getName(), "LP")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legendDict)
# Draw and save the plot
plots.drawPlot(p, saveName,
**kwargs_) #the "**" unpacks the kwargs_ dictionary
# Draw Error bands
for i, g in enumerate([g0, g1, g2, g3, g4]):
shapes, min, max = DrawErrorBand(g)
for shape in shapes:
shape.SetFillColor(
p.histoMgr.getHistos()[i].getRootHisto().GetFillColor())
shape.SetFillStyle(3002)
shape.Draw("f same")
ROOT.gPad.RedrawAxis()
histograms.addPileupText("PU=%s" % (PU))
histograms.addText(0.60, 0.38, plots._legendLabels[signal], 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
return
def main(opts):
# Set the ROOTeError verbosity
ROOT.gErrorIgnoreLevel = 3000 # kUnset=-1, kPrint=0, kInfo=1000, kWarning=2000, kError=3000, kBreak=4000
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setGridX(opts.gridX)
style.setGridY(opts.gridY)
style.setOptStat(False)
# Obtain dsetMgrCreator and register it to module selector
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=opts.mcrab)
# Setup & configure the dataset manager
datasetsMgr = GetDatasetsFromDir(opts)
datasetsMgr.updateNAllEventsToPUWeighted()
if opts.verbose:
datasetsMgr.PrintCrossSections()
datasetsMgr.PrintInfo()
# Setup & configure the dataset manager (no collision data => not needed)
if 0:
datasetsMgr.loadLuminosities()
datasetsMgr.updateNAllEventsToPUWeighted()
# Print information
if opts.verbose:
datasetsMgr.PrintCrossSections()
# datasetsMgr.PrintLuminosities()
# Print dataset information (before merge)
datasetsMgr.PrintInfo()
# Merge histograms (see NtupleAnalysis/python/tools/plots.py)
plots.mergeRenameReorderForDataMC(datasetsMgr)
# Get Luminosity
if 0:
intLumi = datasetsMgr.getDataset("Data").getLuminosity()
# Apply new dataset order?
newOrder = ReorderDatasets(datasetsMgr.getAllDatasetNames(),
bReverse=False)
datasetsMgr.selectAndReorder(newOrder)
# Print dataset information (after merge)
if 0:
datasetsMgr.PrintInfo() #Requires python 2.7.6 or 2.6.6
# Plot Histograms
histoList = datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDirectoryContent(opts.folder)
histoPaths = [os.path.join(opts.folder, h) for h in histoList]
histoType = type(
datasetsMgr.getDataset(datasetsMgr.getAllDatasetNames()
[0]).getDatasetRootHisto(h).getHistogram())
plotCount = 0
inList = ["ETResolution"]
# For-loop: All# histos in opts.folder
for i, h in enumerate(histoPaths, 1):
# Only do Et (don't expect dependence on PU for eta, phi
if "etresolution" not in h.lower():
continue
# Forwards region not yet available for Calos
if "_F" in h:
continue
bSkip = True
for s in inList:
bSkip = False
if bSkip:
continue
histoType = str(
type(
datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDatasetRootHisto(
h).getHistogram()))
if "TH1" not in histoType:
continue
aux.PrintFlushed(h, plotCount == 0)
plotCount += 1
PlotHisto(datasetsMgr, h)
print
Print(
"All plots saved under directory %s" %
(ShellStyles.NoteStyle() + aux.convertToURL(opts.saveDir, opts.url) +
ShellStyles.NormalStyle()), True)
return
def main(opts):
# Set the ROOTeError verbosity
ROOT.gErrorIgnoreLevel = 3000 # kUnset=-1, kPrint=0, kInfo=1000, kWarning=2000, kError=3000, kBreak=4000
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setGridX(opts.gridX)
style.setGridY(opts.gridY)
style.setOptStat(False)
# Obtain dsetMgrCreator and register it to module selector
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=opts.mcrab)
# Setup & configure the dataset manager
datasetsMgr = GetDatasetsFromDir(opts)
datasetsMgr.updateNAllEventsToPUWeighted()
if opts.verbose:
datasetsMgr.PrintCrossSections()
datasetsMgr.PrintInfo()
# Setup & configure the dataset manager (no collision data => not needed)
if 0:
datasetsMgr.loadLuminosities()
datasetsMgr.updateNAllEventsToPUWeighted()
# Print information
if opts.verbose:
datasetsMgr.PrintCrossSections()
# datasetsMgr.PrintLuminosities()
# Print dataset information (before merge)
datasetsMgr.PrintInfo()
# Merge histograms (see NtupleAnalysis/python/tools/plots.py)
plots.mergeRenameReorderForDataMC(datasetsMgr)
# Get Luminosity
if 0:
intLumi = datasetsMgr.getDataset("Data").getLuminosity()
# Apply new dataset order?
newOrder = ReorderDatasets(datasetsMgr.getAllDatasetNames())
datasetsMgr.selectAndReorder(newOrder)
# Print dataset information (after merge)
if 0:
datasetsMgr.PrintInfo() #Requires python 2.7.6 or 2.6.6
# Plot Histograms
histoList = datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDirectoryContent(opts.folder)
histoPaths = [os.path.join(opts.folder, h) for h in histoList]
histoType = type(
datasetsMgr.getDataset(datasetsMgr.getAllDatasetNames()
[0]).getDatasetRootHisto(h).getHistogram())
plotCount = 0
skipList = [
"L1TkTau_MatchTk_d0", "L1TkTau_MatchTk_d0Abs", "L1TkTau_SigTks_d0",
"L1TkTau_SigTks_d0Abs", "L1TkTau_SigTks_d0Sig",
"L1TkTau_SigTks_d0SigAbs", "L1TkTau_IsoTks_d0", "L1TkTau_IsoTks_d0Abs",
"L1TkTau_IsoTks_d0Sig", "L1TkTau_IsoTks_d0SigAbs",
"L1TkTau_ResolutionCaloEt_F", "L1TkTau_ResolutionCaloEta_F",
"L1TkTau_ResolutionCaloPhi_F", "L1TkIsoTau_ResolutionCaloEt_F",
"L1TkIsoTau_ResolutionCaloEta_F", "L1TkIsoTau_ResolutionCaloPhi_F",
"DiTau_Rate_Calo_F", "DiTau_Rate_Tk_F", "DiTau_Rate_VtxIso_F",
"DiTau_Rate_RelIso_F", "Calo_Rate_F", "Tk_Rate_F", "VtxIso_Rate_F",
"RelIso_Rate_F"
]
# For-loop: All histos in opts.folder
for i, h in enumerate(histoPaths, 1):
# Obsolete quantity
if h in skipList:
continue
histoType = str(
type(
datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDatasetRootHisto(
h).getHistogram()))
if "TH1" not in histoType:
continue
aux.PrintFlushed(h, plotCount == 0)
plotCount += 1
PlotHisto(datasetsMgr, h)
print
Print(
"All plots saved under directory %s" %
(ShellStyles.NoteStyle() + aux.convertToURL(opts.saveDir, opts.url) +
ShellStyles.NormalStyle()), True)
return
# Check & assign ROOT file
CheckRootFile(opts.rootFile)
# opts.rootFile = f
# Create directory and subdirectories
CreatePseudoDir(opts, args)
aux.Print("%sFile %d/%d: %s%s" % (hs, i, nFiles, f, ns), i==1)
Print("Created pseudo-multicrab directory %s!" % (ss + opts.dirName + ns), True)
sys.exit()
elif nFiles > 0:
Verbose("Multiple ROOT files mode", True)
# For-loop: All ROOT files
for i, f in enumerate(opts.rootFiles, 1):
# Check & assign ROOT file
CheckRootFile(f)
opts.rootFile = f
# Create directory and subdirectories
CreatePseudoDir(opts, args)
aux.PrintFlushed("%sFile %d/%d: %s%s" % (hs, i, nFiles, f, ns), i==1)
print
Print("Created pseudo-multicrab %s" % (ss + opts.taskDirName + ns), True)
sys.exit()
else:
sys.exit()
def PlotHistos(datasetsMgr, histoList, signal, PU, saveName=None):
# Get Histogram name and its kwargs
kwargs = GetHistoKwargs(saveName, opts)
hList = []
legDict = {}
algos = getAlgos()
if "_all" in saveName:
algos = ["Inclusive", "1-prong", "3-prong", "#geq 1 #pi^{0}'s", "0 #pi^{0}'s"]
if "_cif" in saveName:
#algos = ["Inclusive", "Central", "Intermediate", "Forward"]
algos = ["Inclusive", "|#eta| < 0.8 (C)", "0.8 < |#eta| < 1.6 (I)", "|#eta| > 1.6 (F)"]
# For-loop: All tau algorithms
for l, hName in enumerate(histoList, 0):
algo = hName.split("_")[0]
msg = "Resolution for \"%s\" algorithm (%s)" % (algo, signal)
aux.PrintFlushed(msg, False)
h = datasetsMgr.getDataset(signal).getDatasetRootHisto(hName).getHistogram()
h.SetName(hName)
legDict[hName] = algos[l]
hList.append(h)
# Create the rate histograms
if opts.normalizeToOne:
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
norm = True
for hist in p.histoMgr.getHistos():
if hist.getRootHisto().Integral() == 0:
norm = False
break
if (norm):
p.histoMgr.forEachHisto(lambda h: h.getRootHisto().Scale(1.0/h.getRootHisto().Integral()) )
else:
aux.Print("Cannot normalise empty histo \"%s\" for dataset \"%s\"" % (hName, signal), True)
else:
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
# Set legend labels
for i, h in enumerate(p.histoMgr.getHistos(), 0):
hName = h.getName()
p.histoMgr.forHisto(hName, styles.getCaloStyle(i))
#p.histoMgr.setHistoDrawStyle(hName, "HIST")
#p.histoMgr.setHistoLegendStyle(hName, "L")
p.histoMgr.setHistoDrawStyle(hName, "AP")
p.histoMgr.setHistoLegendStyle(hName, "P")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legDict)
# Draw and save the plot
plots.drawPlot(p, saveName, **kwargs)
# Add additional canvas text
histograms.addPileupText("PU=%s" % (PU) )
histograms.addText(0.22, 0.86, plots._legendLabels[signal], 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
return
def Plot2dHistograms(datasetsMgr, dsetName, histoName, index):
msg = "%s%s (%s)%s" % (ShellStyles.SuccessStyle(), histoName, dsetName, ShellStyles.NormalStyle() )
aux.PrintFlushed(msg, index==1)
# Custom Filtering of datasets
dsetsMgr = datasetsMgr.deepCopy()
if opts.verbose:
dsetsMgr.PrintInfo()
# Get Histogram name and its kwargs
saveName = histoName.rsplit("/")[-1] + "_" + dsetName.split("_")[0] + dsetName.split("_")[-1]
kwargs_ = GetHistoKwargs(saveName, opts)
for i, d in enumerate(dsetsMgr.getAllDatasetNames(), 0):
if d == dsetName:
continue
else:
# Remove dataset from manager but do NOT close the file!
dsetsMgr.remove(d, close=False)
# Sanity check
nDatasets = len(dsetsMgr.getAllDatasets())
if nDatasets > 1:
raise Exception("More than 1 datasets detected in the dataset manager! Can only support 1 dataset. Please use the -i option to choose exactly 1 dataset'")
# Get the reference histo and the list of histos to compare
datasets0 = dsetsMgr.getAllDatasets()[0].getName()
histoList = [getHisto(dsetsMgr, datasets0, histoName)]
# Create the 2d plot
Verbose("Creating the 2d plot", True)
if opts.normalizeToLumi:
p = plots.MCPlot(dsetsMgr, histoName, normalizeToLumi=opts.intLumi, saveFormats=[])
elif opts.normalizeByCrossSection:
p = plots.MCPlot(dsetsMgr, histoName, normalizeByCrossSection=True, saveFormats=[], **{})
elif opts.normalizeToOne:
p = plots.MCPlot(dsetsMgr, histoName, normalizeToOne=True, saveFormats=[], **{})
else:
raise Exception("One of the options --normalizeToOne, --normalizeByCrossSection, --normalizeToLumi must be enabled (set to \"True\").")
Verbose("Setting universal histo styles", True)
p.histoMgr.setHistoDrawStyleAll("COLZ")
#p.histoMgr.setHistoLegendStyleAll("L")
Verbose("Customising histograms", True)
p.histoMgr.forEachHisto(lambda h: h.getRootHisto().GetZaxis().SetTitleOffset(1.3)) #fixme
Verbose("Setting plot styles to histograms", True)
for index, h in enumerate(p.histoMgr.getHistos()):
plots._plotStyles[p.histoMgr.getHistos()[index].getDataset().getName()].apply(p.histoMgr.getHistos()[index].getRootHisto())
Verbose("Drawing the plot", True)
plots.drawPlot(p, saveName, **kwargs_) #the "**" unpacks the kwargs_ dictionary
# Add fit line for shrinking cone?
const= 0.0
coeff= 0.0
step = 1
xmin = 0
xmax = 0
if "GenP_VisEt_Vs" in histoName:
const= 3.5
coeff= 1.0
step = 100
xmin = 0
xmax = 30
if "GenP_PtLdg_Vs" in histoName:
const= 2.5 #2.0
coeff= 1.0
step = 100
xmin = 0
xmax = 30
if "VtxIso_Vs_RelIso" in histoName:
const= -0.5
coeff= 0.3 #0.4
step = 100
xmin = 0
xmax = 0#3
if "GenP_VisEt_Vs" in histoName or "GenP_PtLdg_Vs" in histoName:
gr = getCustomTGraph(histoName, const, coeff, xmin, xmax, step)
gr.SetLineWidth(3)
gr.Draw("L same")
Verbose("Removing the legend", True)
p.removeLegend()
Verbose("Adding text on canvas", True)
histograms.addText(0.22, 0.89, plots._legendLabels[datasets0], 18)
#histograms.addText(0.5, 0.89, plots._legendLabels[datasets0], 18)
Verbose("Saving the canvas", True)
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, opts.url)
return
def main(opts):
# Set the ROOTeError verbosity
ROOT.gErrorIgnoreLevel = 3000 # kUnset=-1, kPrint=0, kInfo=1000, kWarning=2000, kError=3000, kBreak=4000
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setGridX(opts.gridX)
style.setGridY(opts.gridY)
style.setOptStat(False)
# Obtain dsetMgrCreator and register it to module selector
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=opts.mcrab)
# Setup & configure the dataset manager
datasetsMgr = GetDatasetsFromDir(opts)
datasetsMgr.updateNAllEventsToPUWeighted()
if opts.verbose:
datasetsMgr.PrintCrossSections()
datasetsMgr.PrintInfo()
# Setup & configure the dataset manager (no collision data => not needed)
if 0:
datasetsMgr.loadLuminosities()
datasetsMgr.updateNAllEventsToPUWeighted()
# Print information
if opts.verbose:
datasetsMgr.PrintCrossSections()
# datasetsMgr.PrintLuminosities()
# Print dataset information (before merge)
datasetsMgr.PrintInfo()
# Merge histograms (see NtupleAnalysis/python/tools/plots.py)
plots.mergeRenameReorderForDataMC(datasetsMgr)
# Get Luminosity
if 0:
intLumi = datasetsMgr.getDataset("Data").getLuminosity()
# Print dataset information (after merge)
if 0:
datasetsMgr.PrintInfo() #Requires python 2.7.6 or 2.6.6
# Sanity check
nDatasets = len(datasetsMgr.getAllDatasetNames())
if (nDatasets) > 1:
raise Exception(
"More than 1 datasets found! Please choose only 1 dataset (-i \"regex\") and retry"
)
# Plot Histograms
histoList = datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDirectoryContent(opts.folder)
histoPaths = [os.path.join(opts.folder, h) for h in histoList]
histoType = type(
datasetsMgr.getDataset(datasetsMgr.getAllDatasetNames()
[0]).getDatasetRootHisto(h).getHistogram())
plotCount = 0
# For-loop: All# histos in opts.folder
for i, h in enumerate(histoPaths, 1):
histoType = str(
type(
datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDatasetRootHisto(
h).getHistogram()))
if "TH1" in histoType or "TDirectoryFile" in histoType:
continue
else:
# print "histoType = ", histoType
pass
if "GenP" in h:
continue
aux.PrintFlushed(h, plotCount == 0)
plotCount += 1
PlotHisto(datasetsMgr, h, histoType)
print
Print(
"All plots saved under directory %s" %
(ShellStyles.NoteStyle() + aux.convertToURL(opts.saveDir, opts.url) +
ShellStyles.NormalStyle()), True)
return
def PlotEfficiency(datasetsMgr, histoList, signal, PU, taus):
# Get Histogram name and its kwargs
saveName = "Efficiency_%s_%s" % (taus, signal)
#saveName = "Efficiency_%s_PU%s" % (taus, PU) # "Rate_" here incuded to apply customisations with kwargs. Drop later
kwargs = GetHistoKwargs(saveName, opts)
hList = []
legDict = {}
algos = getAlgos()
# For-loop: All tau algorithms
count = -1
for i, hName in enumerate(histoList, 0):
algo = hName.split("_")[0]
if algo == "DiTau":
if "TT_" in signal or "GluGlu" in signal:
pass
else:
return
algo = hName.split("_")[-1]
count += 1
aux.PrintFlushed("Plotting efficiency (%s-%s-%s)" %
(algo, taus, signal), False) #count==0)
h = datasetsMgr.getDataset(signal).getDatasetRootHisto(
hName).getHistogram()
h.SetName(hName)
legDict[hName] = algos[i]
hList.append(h)
# Create the rate histograms
p = plots.ComparisonManyPlot(hList[0], hList[1:], saveFormats=[])
# Set legend labels
for h in p.histoMgr.getHistos():
hName = h.getName()
algo = h.getName().split("_")[0]
if algo == "DiTau":
algo = hName.split("_")[-1]
p.histoMgr.forHisto(hName, styles.getTauAlgoStyle(algo))
p.histoMgr.setHistoDrawStyle(hName, "HIST")
p.histoMgr.setHistoLegendStyle(hName, "L")
# Set legend labels
p.histoMgr.setHistoLegendLabelMany(legDict)
# Draw and save the plot
saveName = saveName.replace(
"Efficiency_",
"") # drop "Efficiency_" only AFTER getting histo kwargs
#saveName = "%s_%s_%s" % (taus, algo, signal) # drop "Efficiency_" only AFTER getting histo kwargs
plots.drawPlot(p, saveName, **kwargs)
# Add additional canvas text
histograms.addPileupText("PU=%s" % (PU))
histograms.addText(0.66, 0.86, plots._legendLabels[signal], 17)
# Save the plots in custom list of saveFormats
aux.SavePlot(p, opts.saveDir, saveName, opts.saveFormats, True)
#print
return
