def main(opts):
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setOptStat(True)
style.setGridX(True)
style.setGridY(True)
# Obtain dsetMgrCreator and register it to module selector
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=opts.mcrab)
# Get list of eras, modes, and optimisation modes
erasList = dsetMgrCreator.getDataEras()
modesList = dsetMgrCreator.getSearchModes()
optList = dsetMgrCreator.getOptimizationModes()
sysVarList = dsetMgrCreator.getSystematicVariations()
sysVarSrcList = dsetMgrCreator.getSystematicVariationSources()
# If user does not define optimisation mode do all of them
if opts.optMode == None:
if len(optList) < 1:
optList.append("")
optModes = optList
else:
optModes = [opts.optMode]
# For-loop: All opt Mode
for opt in optModes:
opts.optMode = opt
# Setup & configure the dataset manager
datasetsMgr = GetDatasetsFromDir(opts)
datasetsMgr.updateNAllEventsToPUWeighted()
datasetsMgr.loadLuminosities() # from lumi.json
if opts.verbose:
datasetsMgr.PrintCrossSections()
datasetsMgr.PrintLuminosities()
# Get the PSets:
if 0:
datasetsMgr.printSelections()
#PrintPSet("BJetSelection", datasetsMgr, depth=150)
# ZJets and DYJets overlap!
if "ZJetsToQQ_HT600toInf" in datasetsMgr.getAllDatasetNames(
) and "DYJetsToQQ_HT180" in datasetsMgr.getAllDatasetNames():
Print(
"Cannot use both ZJetsToQQ and DYJetsToQQ due to duplicate events? Investigate. Removing ZJetsToQQ datasets for now ..",
True)
datasetsMgr.remove(
filter(lambda name: "ZJetsToQQ" in name,
datasetsMgr.getAllDatasetNames()))
# Merge histograms (see NtupleAnalysis/python/tools/plots.py)
plots.mergeRenameReorderForDataMC(datasetsMgr)
# Get luminosity if a value is not specified
if opts.intLumi < 0:
opts.intLumi = datasetsMgr.getDataset("Data").getLuminosity()
# Remove datasets
removeList = ["QCD-b", "Charged"]
if not opts.useMC:
removeList.append("QCD")
for i, d in enumerate(removeList, 0):
msg = "Removing dataset %s" % d
Verbose(
ShellStyles.WarningLabel() + msg + ShellStyles.NormalStyle(),
i == 0)
datasetsMgr.remove(
filter(lambda name: d in name,
datasetsMgr.getAllDatasetNames()))
# Print summary of datasets to be used
if 0:
datasetsMgr.PrintInfo()
# Merge EWK samples
datasetsMgr.merge("EWK", aux.GetListOfEwkDatasets())
# Print dataset information
datasetsMgr.PrintInfo()
# List of TDirectoryFile (_CRone, _CRtwo, _VR, _SR)
tdirs = [
"LdgTrijetPt_", "LdgTrijetMass_", "LdgTrijetBJetBdisc_",
"TetrajetBJetPt_", "TetrajetBJetEta_", "TetrajetBJetBdisc_",
"LdgTetrajetPt_", "LdgTetrajetMass_"
]
region = ["CRone", "CRtwo"]
hList = []
for d in tdirs:
for r in region:
hList.append(d + r)
# Get the folders with the binned histograms
folderList_ = datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDirectoryContent(
opts.folder)
folderList = [h for h in folderList_ if h in hList]
# For-loop: All folders
histoPaths = []
for f in folderList:
folderPath = os.path.join(opts.folder, f)
histoList = datasetsMgr.getDataset(
datasetsMgr.getAllDatasetNames()[0]).getDirectoryContent(
folderPath)
pathList = [os.path.join(folderPath, h) for h in histoList]
histoPaths.extend(pathList)
# Get all the bin labels
binLabels = GetBinLabels("CRone", histoPaths)
for i, t in enumerate(tdirs, 1):
myList = []
for p in histoPaths:
if t in p:
myList.append(p)
msg = "{:<9} {:>3} {:<1} {:<3} {:<50}".format(
"Histogram", "%i" % i, "/", "%s:" % (len(tdirs)),
t.replace("_", ""))
Print(ShellStyles.SuccessStyle() + msg + ShellStyles.NormalStyle(),
i == 1)
PlotHistograms(datasetsMgr, myList, binLabels, opts)
# Save the plots
Print(
"All plots saved under directory %s" %
(ShellStyles.NoteStyle() + aux.convertToURL(opts.saveDir, opts.url) +
ShellStyles.NormalStyle()), True)
return
def main(opts):
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setGridX(opts.gridx)
style.setGridY(opts.gridy)
style.setLogX(opts.logx)
style.setLogY(opts.logy)
# Create legend and set style
histograms.createLegend.moveDefaults(dx=-0.1, dh=-0.15)
histograms.uncertaintyMode.set(histograms.Uncertainty.StatOnly)
styles.ratioLineStyle.append(styles.StyleLine(lineColor=13))
# Define some variables
nameList = []
allShapeNuisances = []
signalTable = {}
myDatacardPattern = ""
myRootfilePattern = ""
# Find out the mass points
if opts.cardPattern == None:
mySettings = limitTools.GeneralSettings(".", [])
myDatacardPattern = mySettings.getDatacardPattern(
limitTools.LimitProcessType.TAUJETS)
myRootfilePattern = mySettings.getRootfilePattern(
limitTools.LimitProcessType.TAUJETS)
else:
myDatacardPattern = opts.cardPattern.replace("MMM", "M%s").replace(
"MM", "%s")
myRootfilePattern = opts.rootfilePattern.replace("MMM", "M%s").replace(
"MM", "%s")
# Get mass points to consider
massPoints = DatacardReader.getMassPointsForDatacardPattern(
".", myDatacardPattern)
Print(
"The following masses will be considered: %s" %
(ShellStyles.HighlightAltStyle() + ", ".join(massPoints) +
ShellStyles.NormalStyle()), True)
# For-loop: All mass points
for i, m in enumerate(massPoints, 1):
# Obtain luminosity from the datacard
myLuminosity = float(
limitTools.readLuminosityFromDatacard(".", myDatacardPattern % m))
# Do the plots
doPlot(opts, int(m), nameList, allShapeNuisances, myLuminosity,
myDatacardPattern, myRootfilePattern, signalTable)
# Print signal table
Print("Max contracted uncertainty for signal:", True)
table = []
align = "{:>30} {:>15} {:>15}"
hLine = "=" * 60
table.append(hLine)
table.append(align.format("Systematic", "Minimum", "Maximum"))
table.append(hLine)
# For-loop: All signal
for i, k in enumerate(signalTable.keys(), 1):
# Print("Key = %s" % (k), False)
minVal = "%.3f" % (signalTable[k]["min"])
maxVal = "%.3f" % (signalTable[k]["max"])
msg = align.format(k, minVal, maxVal)
table.append(msg)
table.append(hLine)
for row in table:
Print(row, False)
msg = "All results under directory %s" % (
ShellStyles.SuccessStyle() + opts.dirName + ShellStyles.NormalStyle())
Print(msg, True)
return
def main(opts):
# Suppress warnings about weight being re-applied
ROOT.gErrorIgnoreLevel = ROOT.kError
# Obtain dsetMgrCreator and register it to module selector
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=opts.mcrab)
# Get list of eras, modes, and optimisation modes
erasList = dsetMgrCreator.getDataEras()
modesList = dsetMgrCreator.getSearchModes()
optList = dsetMgrCreator.getOptimizationModes()
sysVarList = dsetMgrCreator.getSystematicVariations()
sysVarSrcList = dsetMgrCreator.getSystematicVariationSources()
# If user does not define optimisation mode do all of them
if opts.optMode == None:
if len(optList) < 1:
optList.append("")
else:
pass
optModes = optList
else:
optModes = [opts.optMode]
opts.optMode = ""
mcrabName = opts.mcrab
RunEra = mcrabName.split("_")[1]
# Setup ROOT and style
ROOT.gROOT.SetBatch(opts.batchMode)
style = tdrstyle.TDRStyle()
style.setOptStat(True)
style.setGridX(True)
style.setGridY(True)
# Setup & configure the dataset manager
datasetsMgr = GetDatasetsFromDir(opts)
# Remove some QCD samples (the cross sections of these samples are not calculated)
if 0:
msg = "Removing following samples:"
Print(ShellStyles.ErrorStyle() + msg + ShellStyles.NormalStyle(), True)
for d in getDatasetsToExclude():
Print(d, False)
datasetsMgr.remove(d)
# Get run-range
minRunRange, maxRunRange, runRange = GetRunRange(datasetsMgr)
# Get int lumi
intLumi = GetLumi(datasetsMgr)
# Update to PU & load luminosities
datasetsMgr.updateNAllEventsToPUWeighted()
datasetsMgr.loadLuminosities()
#datasetsMgr.normalizeMCByLuminosity()
# Print luminisoties and cross-sections
datasetsMgr.PrintLuminosities()
datasetsMgr.PrintCrossSections()
# Default merging & ordering: "Data", "QCD", "SingleTop", "Diboson"
plots.mergeRenameReorderForDataMC(datasetsMgr)
# Get datasets
datasetsMgr.mergeMC()
dataset_Data = datasetsMgr.getDataDatasets()
dataset_MC = datasetsMgr.getMCDatasets()
# Define lists of Triggers to be plotted and Variables
xVars = ["pt6thJet", "eta6thJet", "phi6thJet", "Ht", "nBTagJets", "pu", "JetMulti", "BJetMulti"]
trgList = ["1BTag", "2BTag", "OR", "OR_PFJet450"]
if opts.fast:
trgList = ["OR_PFJet450"]
xVars = ["pt6thJet", "Ht"]
nPlots = len(trgList)*len(xVars)
counter = 0
# For-loop: All signal triggers
for i, trg in enumerate(trgList, 1):
# For-loop: All x-variables
for j, xVar in enumerate(xVars, 1):
counter+=1
msg = "{:<9} {:>3} {:<1} {:<3} {:<50}".format("Histogram", "%i" % counter, "/", "%s:" % (nPlots), "%s Vs %s" % (trg, xVar))
Print(ShellStyles.SuccessStyle() + msg + ShellStyles.NormalStyle(), counter==1)
# Define names
hNumerator = "hNum_%s_RefTrg_OfflineSel_Signal%s" % (xVar, trg)
hDenominator = "hDen_%s_RefTrg_OfflineSel" % (xVar)
plotName = "Eff_%s_%s" % (xVar, trg)
# Get Efficiency Plots
_kwargs = GetHistoKwargs(xVar, opts)
eff_Data = GetEfficiency(datasetsMgr, dataset_Data, hNumerator, hDenominator , **_kwargs)
eff_MC = GetEfficiency(datasetsMgr, dataset_MC, hNumerator, hDenominator, **_kwargs)
# Apply Styles
styles.dataStyle.apply(eff_Data)
styles.mcStyle.apply(eff_MC)
# Create the plot
p = plots.ComparisonPlot(histograms.HistoGraph(eff_Data, "eff_Data", "p", "P"),
histograms.HistoGraph(eff_MC, "eff_MC" , "p", "P"),
saveFormats=[])
# Define the legend entries
p.histoMgr.setHistoLegendLabelMany(
{
"eff_Data": "Data",
"eff_MC" : "Simulation"
}
)
# Draw and save the plot
p.setLuminosity(intLumi)
plots.drawPlot(p, plotName, **_kwargs)
# Draw
histograms.addText(0.65, 0.06, "Runs "+ runRange, 17)
histograms.addText(0.65, 0.10, "2016", 17)
# Save the canvas to a file
SavePlot(p, plotName, os.path.join(opts.saveDir, opts.optMode), saveFormats=[".pdf", ".png", ".C"] )
Print("All plots saved under directory %s" % (ShellStyles.NoteStyle() + aux.convertToURL(opts.saveDir, opts.url) + ShellStyles.NormalStyle()), True)
return
def drawAllInOne(self, myAllShapeNuisances, luminosity):
myMaxSize = len(myAllShapeNuisances)
# Create pads
canvasHeight = _cHeaderHeight + _cBodyHeight * myMaxSize + _cFooterHeight
c = ROOT.TCanvas("", "", 600, canvasHeight)
c.Divide(1, myMaxSize)
myHeightBefore = canvasHeight
myHeightAfter = canvasHeight
for i in range(0, myMaxSize):
myHeightBefore = myHeightAfter
p = c.cd(i + 1)
myTopMargin = 0.0
myBottomMargin = 0.0
if i == 0:
# Top histogram with header
myHeightAfter -= _cHeaderHeight + _cBodyHeight
myTopMargin = float(_cHeaderHeight) / float(_cHeaderHeight +
_cBodyHeight)
elif i == myMaxSize - 1:
# Bottom histogram with x axis label and title
myHeightAfter -= _cFooterHeight + _cBodyHeight
myBottomMargin = float(_cFooterHeight) / float(_cFooterHeight +
_cBodyHeight)
else:
# Middle histogram, only body
myHeightAfter -= _cBodyHeight
(xlow, ylow, xup, yup) = [ROOT.Double(x) for x in [0.0] * 4]
p.GetPadPar(xlow, ylow, xup, yup)
p.SetPad(xlow,
float(myHeightAfter) / float(canvasHeight), xup,
float(myHeightBefore) / float(canvasHeight))
p.SetBorderMode(0)
p.SetFillStyle(4000)
p.SetTopMargin(myTopMargin)
p.SetBottomMargin(myBottomMargin)
# Draw plots
if len(self._ratioPlotList) == 0:
self.Verbose("No ratioplots in list. Cannot draw all-in-one plot!",
False)
return
o = self._ratioPlotList[0].getFrame2()
myEmptyPlot = aux.Clone(
o) # Keep the clone if it is needed to draw the x axis
# For-loop: All nuisances
for i in range(0, myMaxSize):
p = c.cd(i + 1)
# Find plot
myPlotIndex = None
for j in range(0, len(self._systNameList)):
if myAllShapeNuisances[i] == self._systNameList[j]:
myPlotIndex = j
plot = None
if myPlotIndex != None:
plot = self._ratioPlotList[myPlotIndex].getFrame2()
else:
if i == myMaxSize - 1:
plot = myEmptyPlot # Use this to draw the x axis
else:
plot = self._ratioPlotList[0].getFrame2(
) # Only the empty frame matters
# Draw plot
if i == myMaxSize - 1:
# Bottom histogram
plot.GetXaxis().SetTitleOffset(0.6 * myMaxSize +
0.6) # 6.6/10, 3.6/5
else:
plot.GetXaxis().SetTitleSize(0)
plot.GetXaxis().SetLabelSize(0)
plot.GetYaxis().SetLabelSize(26)
plot.GetYaxis().SetTitleOffset(0.34 * myMaxSize +
0.1) # 3.5/10, 1.8/5
plot.SetMinimum(0.601) # 0.001
plot.SetMaximum(1.399) # 1.999
# Plot frame for every nuisance
plot.Draw()
# Plot content only if affected
if myPlotIndex != None:
self._ratioPlotList[myPlotIndex].ratioHistoMgr.draw()
self._ratioPlotList[0].ratioLine.Draw("L")
p.RedrawAxis()
# Labels for shape nuisance and dataset
myHeight = 0.82
if i == 0:
myHeight = myHeight * float(_cBodyHeight) / float(
_cHeaderHeight + _cBodyHeight)
elif i == myMaxSize - 1:
myHeight = (myHeight * float(_cBodyHeight) +
float(_cFooterHeight)) / float(_cFooterHeight +
_cBodyHeight)
histograms.addText(x=0.18,
y=myHeight,
text=myAllShapeNuisances[i],
size=30)
myHeight = 0.08
if i == 0:
myHeight = myHeight * float(_cBodyHeight) / float(
_cHeaderHeight + _cBodyHeight)
elif i == myMaxSize - 1:
myHeight = (myHeight * float(_cBodyHeight) +
float(_cFooterHeight)) / float(_cFooterHeight +
_cBodyHeight)
histograms.addText(x=0.93,
y=myHeight,
text=self._dsetName,
size=30,
align="right")
# Header labels
if i == 0:
histograms.addStandardTexts(lumi=luminosity,
cmsTextPosition="outframe")
# Labels for non-existing nuisances
if myPlotIndex == None:
myHeight = 0.44
if i == 0:
myHeight = myHeight * float(_cBodyHeight) / float(
_cHeaderHeight + _cBodyHeight)
elif i == myMaxSize - 1:
myHeight = (myHeight * float(_cBodyHeight) +
float(_cFooterHeight)) / float(_cFooterHeight +
_cBodyHeight)
histograms.addText(x=0.555,
y=myHeight,
text="Not affected",
size=30,
align="center")
# Save plot
plotName = "shapeSystRatioOnlyAll_%s" % (self._dsetName)
saveName = os.path.join(opts.dirName, plotName)
backup = ROOT.gErrorIgnoreLevel
ROOT.gErrorIgnoreLevel = ROOT.kError
# For-loop: All formats to save
for i, ext in enumerate([".png", ".C", ".eps"], 1):
fName = saveName + ext
c.Print(fName)
msg = "Created file %s" % (ShellStyles.SuccessStyle() + fName +
ShellStyles.NormalStyle())
self.Verbose(msg, i == 1)
ROOT.gErrorIgnoreLevel = backup
return
def doPlot(opts, mass, nameList, allShapeNuisances, luminosity,
myDatacardPattern, rootFilePattern, signalTable):
fName = rootFilePattern % mass
f = ROOT.TFile.Open(fName)
content = f.GetListOfKeys()
# Suppress the warning message of missing dictionary for some iterator
backup = ROOT.gErrorIgnoreLevel
ROOT.gErrorIgnoreLevel = ROOT.kError
diriter = content.MakeIterator()
ROOT.gErrorIgnoreLevel = backup
# Find the datacard and nuisance names
myCardReader = DatacardReader.DataCardReader(".", mass, myDatacardPattern,
rootFilePattern)
myDatasetNames = myCardReader.getDatasetNames()
# Find the name stem and the name of the uncertainties
datasets = []
shapes = []
for d in myDatasetNames:
myLabel = d
myStatus = not d in nameList
if d == myDatasetNames[0]:
myStatus = True
if not str(mass) in d:
myLabel = "%sm%d" % (d, mass)
myShapeNuisanceNames = myCardReader.getShapeNuisanceNames(d)
myFilteredShapeNuisances = []
for n in myShapeNuisanceNames:
if not "statBin" in n and not n.endswith(
"_statUp") and not n.endswith("_statDown"):
myFilteredShapeNuisances.append(n)
if myStatus:
myDataset = DatasetContainer(column=d,
label=myLabel,
nuisances=myFilteredShapeNuisances,
cardReader=myCardReader,
verbose=opts.verbose)
datasets.append(myDataset)
nameList.append(d)
for n in myFilteredShapeNuisances:
if not n in shapes:
shapes.append(n)
rebinList = None
if opts.h2tb:
rebinList = systematics._dataDrivenCtrlPlotBinning[
"LdgTetrajetMass_AfterAllSelections"]
## Do the actual plots
myDsets = ["Hp%s" % (mass), "FakeB", "TT_GenuineB", "SingleTop_GenuineB"]
for i, d in enumerate(datasets, 1):
if d.GetName() not in myDsets:
msg = "Skipping dataset %s" % (d.GetName())
Print(ShellStyles.WarningStyle() + msg + ShellStyles.NormalStyle(),
False)
continue
if opts.verbose:
d.debug()
msg = "{:>10}, {:<20}".format("m = %d GeV" % (mass), d.GetName())
if i < len(datasets):
Print(
ShellStyles.HighlightAltStyle() + msg +
ShellStyles.NormalStyle(), False)
else:
Print(ShellStyles.SuccessStyle() + msg + ShellStyles.NormalStyle(),
False)
d.doPlot(opts, shapes, f, mass, luminosity, signalTable, rebinList)
Verbose("Closing ROOT file %s" % (fName), True)
f.Close()
for counter, d in enumerate(myDirs, 1):
msg = "{:<9} {:>3} {:<1} {:<3} {:<50}".format("Directory",
"%i" % counter, "/",
"%i:" % len(myDirs),
"%s" % d)
Print(
ShellStyles.HighlightAltStyle() + msg + ShellStyles.NormalStyle(),
counter == 1)
myResults.append(Result(opts, d))
# Inform user of success
msg = "{:<9} {:>3} {:<1} {:<3} {:<50}".format("Directory",
"%i" % counter, "/",
"%i:" % len(myDirs),
"Success")
Print(ShellStyles.SuccessStyle() + msg + ShellStyles.NormalStyle(),
True)
Verbose("The results are stored in the following directories:",
counter == 1)
for i, r in enumerate(myResults, 1):
msg = str(i) + ") " + r.getBaseDir()
Verbose(msg, False)
if 0:
Print("Printing results for all directories:", True)
for r in myResults:
r.printResultsAlt()
else:
Verbose("Printing results for all directories:", True)
r.printResults(unblindedStatus=opts.unblinded, nDigits=opts.precision)
os.chdir(output_directory_name)
for filename in filenames:
if "datacard" in filename and ".txt" in filename:
datacard_names.append(filename)
if len(datacard_names) == 0:
Print("No datacards found in input directory", True)
sys.exit(1)
# remove old Combine output and limits from copied directory
#os.system("rm -rf CombineResults*")
Verbose("Looping over datacards:", True)
# For-loop: All datacards (replace bin-by-bin uncertainties with Barlow-Beeston command)
for i, dcard_name in enumerate(datacard_names, 1):
Print("Processing %s" % dcard_name, i == 1)
f_in = file("../" + input_path + "/" + dcard_name)
with open(dcard_name, "w") as f:
# For-loop: All lines in open file
for line in f_in:
if "kmax" in line:
f.write("kmax * number of parameters\n")
elif not "statBin" in line:
f.write(line)
f.write("\n\n* autoMCStats 0")
f.truncate()
dirName = ShellStyles.SuccessStyle(
) + output_directory_name + ShellStyles.NormalStyle()
Print("Barlow-Beeston datacards stored in directory %s" % (dirName), True)
def main(opts):
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setGridX(False)
style.setGridY(False)
style.setOptStat(False)
# Obtain dsetMgrCreator and register it to module selector
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=opts.mcrab)
# Get list of eras, modes, and optimisation modes
erasList = dsetMgrCreator.getDataEras()
modesList = dsetMgrCreator.getSearchModes()
optList = dsetMgrCreator.getOptimizationModes()
sysVarList = dsetMgrCreator.getSystematicVariations()
sysVarSrcList = dsetMgrCreator.getSystematicVariationSources()
# If user does not define optimisation mode do all of them
if opts.optMode == None:
if len(optList) < 1:
optList.append("")
else:
pass
optModes = optList
else:
optModes = [opts.optMode]
# For-loop: All optimisation modes
for opt in optModes:
opts.optMode = opt
# Setup & configure the dataset manager
datasetsMgr = GetDatasetsFromDir(opts)
datasetsMgr.updateNAllEventsToPUWeighted()
datasetsMgr.loadLuminosities() # from lumi.json
if 0:
datasetsMgr.printSelections()
# Print PSets used for FakeBMeasurement
if 0:
datasetsMgr.printSelections()
PrintPSet("BJetSelection", datasetsMgr)
PrintPSet("TopSelectionBDT", datasetsMgr)
PrintPSet("FakeBMeasurement", datasetsMgr)
sys.exit()
# Set/Overwrite cross-sections
for d in datasetsMgr.getAllDatasets():
if "ChargedHiggs" in d.getName():
datasetsMgr.getDataset(d.getName()).setCrossSection(1.0)
if opts.verbose:
datasetsMgr.PrintCrossSections()
datasetsMgr.PrintLuminosities()
datasetsMgr.PrintInfo()
# Filter the datasets
datasetsMgr.remove(
filter(lambda name: "Charged" in name,
datasetsMgr.getAllDatasetNames()))
# datasetsMgr.remove(filter(lambda name: "Charged" in name and not "M_500" in name, datasetsMgr.getAllDatasetNames()))
# ZJets and DYJets overlap!
if "ZJetsToQQ_HT600toInf" in datasetsMgr.getAllDatasetNames(
) and "DYJetsToQQ_HT180" in datasetsMgr.getAllDatasetNames():
Print(
"Cannot use both ZJetsToQQ and DYJetsToQQ due to duplicate events? Investigate. Removing ZJetsToQQ datasets for now ..",
True)
datasetsMgr.remove(
filter(lambda name: "ZJetsToQQ" in name,
datasetsMgr.getAllDatasetNames()))
# Merge histograms (see NtupleAnalysis/python/tools/plots.py)
plots.mergeRenameReorderForDataMC(datasetsMgr)
# Get Luminosity
if opts.intLumi < 0:
if "Data" in datasetsMgr.getAllDatasetNames():
opts.intLumi = datasetsMgr.getDataset("Data").getLuminosity()
else:
opts.intLumi = 1.0
# Re-order datasets (different for inverted than default=baseline)
if 0:
newOrder = ["Data"]
newOrder.extend(aux.GetListOfEwkDatasets())
datasetsMgr.selectAndReorder(newOrder)
# Print post-merged data dataset summary
datasetsMgr.PrintInfo()
# Merge EWK samples
datasetsMgr.merge("EWK", aux.GetListOfEwkDatasets())
plots._plotStyles["EWK"] = styles.getAltEWKStyle()
# Print post EWK-merge dataset summary
datasetsMgr.PrintInfo()
# Get all histograms from the in the selected folder inside the ROOT files
allHistos = datasetsMgr.getAllDatasets()[0].getDirectoryContent(
opts.folder)
hList = [
h for h in allHistos if "CRSelections" in h and "_Vs" not in h
]
hList.extend(
[h for h in allHistos if "AllSelections" in h and "_Vs" not in h])
# hList.extend([h for h in allHistos if "StandardSelections" in h and "_Vs" not in h])
# Create a list with strings included in the histogram names you want to plot
myHistos = [
"LdgTrijetPt", "LdgTrijetMass", "TetrajetBJetPt",
"TetrajetBJetEta", "LdgTetrajetPt", "LdgTetrajetMass", "MVAmax2",
"MVAmax1", "HT", "MET"
]
#myHistos = ["LdgTrijetPt", "LdgTrijetMass", "LdgTetrajetMass", "MVAmax2", "MVAmax1", "Njets", "NBjets",
# "Bjet3Bdisc", "Bjet2Bdisc", "Bjet1Bdisc", "Bjet3Pt", "Bjet2Pt", "Bjet1Pt"]
# For-loop: All histos
for i, h in enumerate(myHistos, 1):
hGraphList = []
for b in ["Baseline_", "Inverted_"]:
#for r in ["_AfterAllSelections", "_AfterCRSelections"]:
for r in ["_AfterCRSelections", "_AfterAllSelections"]:
histoName = b + h + r
hgQCD, kwargs = GetPurityHistoGraph(
datasetsMgr, opts.folder, histoName)
# Do not draw SR in multigraph plot!
if GetControlRegionLabel(histoName) != "SR":
hGraphList.append(hgQCD)
# Plot individual purity graphs?
if 0:
PlotHistoGraph(hgQCD, kwargs)
msg = "{:<9} {:>3} {:<1} {:<3} {:<50}".format(
"Histogram", "%i" % i, "/", "%s:" % (len(myHistos)), h)
Print(ShellStyles.SuccessStyle() + msg + ShellStyles.NormalStyle(),
i == 1)
PlotHistoGraphs(hGraphList, kwargs)
Print(
"All plots saved under directory %s" %
(ShellStyles.NoteStyle() + aux.convertToURL(opts.saveDir, opts.url) +
ShellStyles.NormalStyle()), True)
return
def main(opts):
# Apply TDR style
style = tdrstyle.TDRStyle()
style.setOptStat(False)
style.setGridX(True) #opts.gridX)
style.setGridY(True) #opts.gridY)
style.setLogX(False) #opts.logX)
style.setLogY(False) #opts.logY)
# Obtain dsetMgrCreator and register it to module selector
dsetMgrCreator = dataset.readFromMulticrabCfg(directory=opts.mcrab)
# Get list of eras, modes, and optimisation modes
erasList = dsetMgrCreator.getDataEras()
modesList = dsetMgrCreator.getSearchModes()
optList = dsetMgrCreator.getOptimizationModes()
sysVarList = dsetMgrCreator.getSystematicVariations()
sysVarSrcList = dsetMgrCreator.getSystematicVariationSources()
# If user does not define optimisation mode do all of them
if opts.optMode == None:
if len(optList) < 1:
optList.append("")
else:
pass
optModes = optList
else:
optModes = [opts.optMode]
# For-loop: All optimisation modes
for opt in optModes:
opts.optMode = opt
# Setup & configure the dataset manager
datasetsMgr = GetDatasetsFromDir(opts)
datasetsMgr.updateNAllEventsToPUWeighted()
datasetsMgr.loadLuminosities() # from lumi.json
if 0:
datasetsMgr.printSelections()
# Set/Overwrite cross-sections
for d in datasetsMgr.getAllDatasets():
if "ChargedHiggs" in d.getName():
datasetsMgr.getDataset(d.getName()).setCrossSection(1.0)
if opts.verbose:
datasetsMgr.PrintCrossSections()
datasetsMgr.PrintLuminosities()
# Custom Filtering of datasets
if 0:
datasetsMgr.remove(
filter(lambda name: "Charged" in name and not "M_500" in name,
datasetsMgr.getAllDatasetNames()))
# ZJets and DYJets overlap!
if "ZJetsToQQ_HT600toInf" in datasetsMgr.getAllDatasetNames(
) and "DYJetsToQQ_HT180" in datasetsMgr.getAllDatasetNames():
Print(
"Cannot use both ZJetsToQQ and DYJetsToQQ due to duplicate events? Investigate. Removing ZJetsToQQ datasets for now ..",
True)
datasetsMgr.remove(
filter(lambda name: "ZJetsToQQ" in name,
datasetsMgr.getAllDatasetNames()))
# Merge histograms (see NtupleAnalysis/python/tools/plots.py)
plots.mergeRenameReorderForDataMC(datasetsMgr)
datasetsMgr.PrintInfo()
# Get Luminosity
if opts.intLumi < 0.0:
if "Data" in datasetsMgr.getAllDatasetNames():
opts.intLumi = datasetsMgr.getDataset("Data").getLuminosity()
else:
opts.intLumi = 1.0
# Merge EWK samples
if opts.dataset == "EWK":
datasetsMgr.merge("EWK", aux.GetListOfEwkDatasets())
plots._plotStyles["EWK"] = styles.getAltEWKStyle()
# Print dataset information
datasetsMgr.PrintInfo()
# Get all histogram names in the given ROOT folder
histoNames = datasetsMgr.getAllDatasets()[0].getDirectoryContent(
opts.folder)
histoList = [
os.path.join(opts.folder, h) for h in histoNames if "_SR" in h
]
# For-loop: All histos in SR
nHistos = len(histoList)
for i, h in enumerate(histoList, 1):
msg = "{:<9} {:>3} {:<1} {:<3} {:<50}".format(
"Histogram", "%i" % i, "/", "%s:" % (nHistos), h)
Print(ShellStyles.SuccessStyle() + msg + ShellStyles.NormalStyle(),
i == 1)
PlotHistograms(datasetsMgr, h)
# Inform user where the plots where saved
Print(
"All plots saved under directory %s" %
(ShellStyles.NoteStyle() + aux.convertToURL(opts.saveDir, opts.url) +
ShellStyles.NormalStyle()), True)
return
import ROOT
ROOT.gROOT.SetBatch(True)
ROOT.PyConfig.IgnoreCommandLineOptions = True
import HiggsAnalysis.NtupleAnalysis.tools.dataset as dataset
import HiggsAnalysis.NtupleAnalysis.tools.plots as plots
import HiggsAnalysis.NtupleAnalysis.tools.aux as aux
import HiggsAnalysis.NtupleAnalysis.tools.analysisModuleSelector as analysisModuleSelector
import HiggsAnalysis.NtupleAnalysis.tools.ShellStyles as ShellStyles
import HiggsAnalysis.NtupleAnalysis.tools.pseudoMultiCrabCreator as pseudoMultiCrabCreator
#================================================================================================
# Definitions
#================================================================================================
ss = ShellStyles.SuccessStyle()
ns = ShellStyles.NormalStyle()
ts = ShellStyles.NoteStyle()
hs = ShellStyles.HighlightAltStyle()
es = ShellStyles.ErrorStyle()
#================================================================================================
# Class Definition
#================================================================================================
class NewShape:
'''
Container class for information of data and MC at certain point of the selection flow
'''
def __init__(self,
dsetMgr,