def scaleHistsForProcess(self, group, processName, chan, expandedTheory, append=""):
weightHist = group.FindObject(self.weightHistName(chan, processName, append))
if not weightHist:
raise ValueError("Failed to find %s. Skipping" % self.weightHistName(chan, processName, append))
if 'scale' not in self.theoryVariations[processName]:
return []
scaleVars = self.theoryVariations[processName]['scale']
scaleHists = HistTools.getScaleHists(weightHist, processName, self.rebin,
entries=scaleVars['entries'],
exclude=scaleVars['exclude'],
central=scaleVars['central']) if not self.isUnrolledFit else \
HistTools.getTransformed3DScaleHists(weightHist, HistTools.makeUnrolledHist,
[self.unrolledBinsX, self.unrolledBinsY], processName,
entries=scaleVars['entries'],
exclude=scaleVars['exclude'])
if expandedTheory:
name = processName if not self.correlateScaleUnc else ""
expandedScaleHists = HistTools.getExpandedScaleHists(weightHist, name, self.rebin,
entries=scaleVars['entries'],
pairs=scaleVars['groups'],
) if not self.isUnrolledFit else \
HistTools.getTransformed3DExpandedScaleHists(weightHist,
HistTools.makeUnrolledHist,
[self.unrolledBinsX, self.unrolledBinsY], name,
entries=scaleVars['entries'],
pairs=scaleVars['groups'],
)
scaleHists.extend(expandedScaleHists)
return scaleHists
def loadHistsForProcess(self, processName, scaleNorm=1, expandedTheory=True):
plotsToRead = self.listOfHistsByProcess(processName)
group = HistTools.makeCompositeHists(self.inputFile, processName,
{proc : self.crossSectionMap[proc] for proc in self.processes[processName]},
self.lumi, plotsToRead, rebin=self.rebin, overflow=False)
fitVariable = self.getFitVariable(processName)
#TODO:Make optional
processedHists = []
for chan in self.channels:
histName = "_".join([fitVariable, chan]) if chan != "all" else fitVariable
hist = group.FindObject(histName)
if not hist:
raise RuntimeError("Failed to produce hist %s for process %s" % (histName, processName))
#TODO: Make optional
if "data" not in processName.lower():
HistTools.removeZeros(hist)
HistTools.addOverflow(hist)
processedHists.append(histName)
self.yields[chan].update({processName : round(hist.Integral(), 3) if hist.Integral() > 0 else 0.0001})
if chan == self.channels[0]:
self.yields["all"][processName] = self.yields[chan][processName]
else:
self.yields["all"][processName] += self.yields[chan][processName]
if processName in self.theoryVariations:
weightHist = group.FindObject(self.weightHistName(chan, processName))
if not weightHist:
logging.warning("Failed to find %s. Skipping" % self.weightHistName(chan, processName))
continue
theoryVars = self.theoryVariations[processName]
scaleHists = HistTools.getScaleHists(weightHist, processName, self.rebin,
entries=theoryVars['scale']['entries'],
central=(theoryVars['scale']['central'] if 'scale' in theoryVars else -1))
if expandedTheory:
expandedScaleHists = HistTools.getExpandedScaleHists(weightHist, processName, self.rebin,
entries=theoryVars['scale']['entries'],
central=(theoryVars['scale']['central'] if 'scale' in theoryVars else -1),
)
scaleHists.extend(expandedScaleHists)
pdfHists = []
pdfVars = filter(lambda x: 'pdf' in x, theoryVars.keys())
for var in pdfVars:
pdfVar = theoryVars[var]
pdfType = "SymmMC"
if "hessian" in pdfVar['combine']:
pdfType = "Hessian" if "assym" not in pdfVar['combine'] else "AssymHessian"
pdfFunction = "get%sPDFVariationHists" % pdfType
pdfHists += getattr(HistTools, pdfFunction)(weightHist, pdfVar['entries'], processName,
self.rebin, central=pdfVar['central'],
pdfName=pdfVar['name'])
if expandedTheory and "hessian" in pdfVar['combine']:
allPdfHists = HistTools.getAllSymmetricHessianVariationHists(weightHist, pdfVar['entries'], processName,
self.rebin, central=pdfVar['central'])
pdfHists.extend(allPdfHists)
cenHist, _ = HistTools.getLHEWeightHists(weightHist, pdfVar['entries'][:1], processName, "pdf", self.rebin)
if len(cenHist) and cenHist[0]:
pdfHists.append(cenHist[0].Clone())
group.extend(scaleHists+pdfHists)
if chan == self.channels[0]:
theoryVarLabels = []
for h in group:
theoryVarLabels.extend(re.findall("_".join([self.fitVariable, "(.*)", chan]), h.GetName()))
self.variations[processName].extend(set(theoryVarLabels))
#TODO: Make optional
map(HistTools.addOverflow, filter(lambda x: (x.GetName() not in processedHists), group))
if "data" not in group.GetName().lower():
map(HistTools.removeZeros, filter(lambda x: (x.GetName() not in processedHists), group))
#TODO: You may want to combine channels before removing zeros
self.combineChannels(group, processName)
self.histData[processName] = group
