def latexfitresults(filename, regionList, sampleList, dataname='obsData', showSum=False, doAsym=True, blinded=False, splitBins=False): """ Calculate before/after-fit yields in all channels given @param filename The filename containing afterFit workspace @param regionList A list of regions to be considered @param sampleList A list of samples to be considered @param dataname The name of dataset (default='obsData') @param showSum Calculates sum of all regions if set to true (default=False) @param doAsym Calculates asymmetric errors taken from MINOS (default=True) @param blinded Observed event count will not be shown if set to True (default=False) @param splitBins Calculates bin-by-bin yields for all regions if set to True (default=False) """ """ pick up workspace from file """ workspacename = 'w' w = Util.GetWorkspaceFromFile(filename, 'w') if w == None: print "ERROR : Cannot open workspace : ", workspacename sys.exit(1) """ pick up after-fit RooExpandedFitResult from workspace """ resultAfterFit = w.obj('RooExpandedFitResult_afterFit') if resultAfterFit == None: print "ERROR : Cannot open fit result after fit RooExpandedFitResult_afterFit" sys.exit(1) """ pick up before-fit RooExpandedFitResult from workspace """ resultBeforeFit = w.obj('RooExpandedFitResult_beforeFit') if resultBeforeFit == None: print "ERROR : Cannot open fit result before fit RooExpandedFitResult_beforeFit" sys.exit(1) """ pick up dataset from workspace """ data_set = w.data(dataname) if data_set == None: print "ERROR : Cannot open dataset : ", "data_set" + suffix sys.exit(1) """ pick up channel category (RooCategory) from workspace """ regionCat = w.obj("channelCat") if not blinded: data_set.table(regionCat).Print("v") """ find full (long) name list of regions (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50) """ regionFullNameList = [ Util.GetFullRegionName(regionCat, region) for region in regionList ] """ load afterFit workspace snapshot (=set all parameters to values after fit) """ snapshot = 'snapshot_paramsVals_RooExpandedFitResult_afterFit' w.loadSnapshot(snapshot) if not w.loadSnapshot(snapshot): print "ERROR : Cannot load snapshot : ", snapshot sys.exit(1) """ define set, for all names/yields to be saved in """ tablenumbers = {} """ if showSum=True define names for sum of all regions and add to regionList """ sumName = "" for index, reg in enumerate(regionList): if index == 0: sumName = reg else: sumName = sumName + " + " + reg regionListWithSum = list(regionList) if showSum: regionListWithSum.append(sumName) tablenumbers['names'] = regionListWithSum """ make a list of channelCat calls for every region """ regionCatList = [ 'channelCat==channelCat::' + region.Data() for region in regionFullNameList ] """ retrieve number of observed (=data) events per region """ regionDatasetList = [ data_set.reduce(regioncat) for regioncat in regionCatList ] for index, data in enumerate(regionDatasetList): data.SetName("data_" + regionList[index]) data.SetTitle("data_" + regionList[index]) nobs_regionList = [data.sumEntries() for data in regionDatasetList] """ if showSum=True calculate the total number of observed events in all regions """ sumNobs = 0. for nobs in nobs_regionList: sumNobs += nobs if showSum: nobs_regionList.append(sumNobs) tablenumbers['nobs'] = nobs_regionList """ FROM HERE ON OUT WE CALCULATE THE FITTED NUMBER OF EVENTS __AFTER__ THE FIT """ """ get a list of pdf's and variables per region """ pdfinRegionList = [Util.GetRegionPdf(w, region) for region in regionList] varinRegionList = [Util.GetRegionVar(w, region) for region in regionList] """ if splitBins=True get the list of Nbins, binMax and binMin; make a list of new region names for each bin """ varNbinsInRegionList = [] varBinLowInRegionList = [] varBinHighInRegionList = [] rangeNameBinsInRegionList = [] if splitBins: varNbinsInRegionList = [ Util.GetRegionVar(w, region).getBinning().numBins() for region in regionList ] varBinLowInRegionList = [[ Util.GetRegionVar(w, region).getBinning( (region + "binning")).binLow(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx, region in enumerate(regionList)] varBinHighInRegionList = [[ Util.GetRegionVar(w, region).getBinning( (region + "binning")).binHigh(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx, region in enumerate(regionList)] rangeNameBinsInRegionList = [[ regionList[idx] + "_bin" + str(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx, region in enumerate(regionList)] for index, region in enumerate(regionList): if varNbinsInRegionList[index] == 1: print " \n YieldsTable.py: WARNING: you have called -P (= per-bin yields) but this region ", region, " has only 1 bin \n" """ if splitBins=True reshuffle the regionName list; each region name is followed by names of each bin (i.e. regionNameList=['SR3J','SR3J_bin1','SR3j_bin2','SR4J','SR4J_bin1']) """ regionListWithBins = [] if splitBins: for index, region in enumerate(regionList): regionListWithBins.append(region) for ibin in range(0, varNbinsInRegionList[index]): regionListWithBins.append( rangeNameBinsInRegionList[index][ibin]) tablenumbers['names'] = regionListWithBins """ calculate number of observed(=data) events per bin """ nobs_regionListWithBins = [] if splitBins: binFuncInRegionList = [ RooBinningCategory("bin_" + region, "bin_" + region, varinRegionList[index]) for index, region in enumerate(regionList) ] for index, data in enumerate(regionDatasetList): data.addColumn(binFuncInRegionList[index]) if not blinded: data.table(binFuncInRegionList[index]).Print("v") nobs_regionListWithBins.append(data.sumEntries()) for ibin in range(0, varNbinsInRegionList[index]): nobs_regionListWithBins.append( (data.reduce(binFuncInRegionList[index].GetName() + "==" + binFuncInRegionList[index].GetName() + "::" + varinRegionList[index].GetName() + "_bin" + str(ibin))).sumEntries()) tablenumbers['nobs'] = nobs_regionListWithBins """ if blinded=True, set all numbers of observed events to -1 """ if blinded: for index, nobs in enumerate(nobs_regionListWithBins): nobs_regionListWithBins[index] = -1 tablenumbers['nobs'] = nobs_regionListWithBins """ get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples) """ rrspdfinRegionList = [] for index, pdf in enumerate(pdfinRegionList): prodList = pdf.pdfList() foundRRS = 0 for idx in range(prodList.getSize()): if prodList[idx].InheritsFrom("RooRealSumPdf"): rrspdfInt = prodList[idx].createIntegral( RooArgSet(varinRegionList[index])) rrspdfinRegionList.append(rrspdfInt) if splitBins: origMin = varinRegionList[index].getMin() origMax = varinRegionList[index].getMax() for ibin in range(0, varNbinsInRegionList[index]): rangeName = rangeNameBinsInRegionList[index][ibin] varinRegionList[index].setRange( rangeName, varBinLowInRegionList[index][ibin], varBinHighInRegionList[index][ibin]) rrspdfInt = prodList[idx].createIntegral( RooArgSet(varinRegionList[index]), rangeName) rrspdfinRegionList.append(rrspdfInt) varinRegionList[index].setRange(origMin, origMax) foundRRS += 1 if foundRRS > 1 or foundRRS == 0: print " \n\n WARNING: ", pdf.GetName( ), " has ", foundRRS, " instances of RooRealSumPdf" print pdf.GetName(), " component list:", prodList.Print("v") """ calculate total pdf number of fitted events and error """ nFittedInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList) ] pdfFittedErrInRegionList = [ Util.GetPropagatedError(pdf, resultAfterFit, doAsym) for pdf in rrspdfinRegionList ] """ if showSum=True calculate the total number of fitted events in all regions """ if showSum: pdfInAllRegions = RooArgSet() for index, pdf in enumerate(rrspdfinRegionList): pdfInAllRegions.add(pdf) pdfSumInAllRegions = RooAddition("pdf_AllRegions_AFTER", "pdf_AllRegions_AFTER", RooArgList(pdfInAllRegions)) nPdfSumVal = pdfSumInAllRegions.getVal() nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultAfterFit, doAsym) nFittedInRegionList.append(nPdfSumVal) pdfFittedErrInRegionList.append(nPdfSumError) tablenumbers['TOTAL_FITTED_bkg_events'] = nFittedInRegionList tablenumbers['TOTAL_FITTED_bkg_events_err'] = pdfFittedErrInRegionList """ calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf """ for isam, sample in enumerate(sampleList): sampleName = getName(sample) nSampleInRegionVal = [] nSampleInRegionError = [] sampleInAllRegions = RooArgSet() for ireg, region in enumerate(regionList): sampleInRegion = getPdfInRegions(w, sample, region) sampleInRegionVal = 0. sampleInRegionError = 0. if not sampleInRegion == None: sampleInRegionVal = sampleInRegion.getVal() sampleInRegionError = Util.GetPropagatedError( sampleInRegion, resultAfterFit, doAsym) sampleInAllRegions.add(sampleInRegion) else: print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region =", region, "\n" nSampleInRegionVal.append(sampleInRegionVal) nSampleInRegionError.append(sampleInRegionError) """ if splitBins=True calculate numbers of fitted events plus error per bin """ if splitBins: origMin = varinRegionList[ireg].getMin() origMax = varinRegionList[ireg].getMax() for ibin in range(0, varNbinsInRegionList[ireg]): rangeName = rangeNameBinsInRegionList[ireg][ibin] sampleInRegion = getPdfInRegionsWithRangeName( w, sample, region, rangeName) sampleInRegionVal = 0. sampleInRegionError = 0. if not sampleInRegion == None: varinRegionList[ireg].setRange( rangeName, varBinLowInRegionList[ireg][ibin], varBinHighInRegionList[ireg][ibin]) sampleInRegionVal = sampleInRegion.getVal() sampleInRegionError = Util.GetPropagatedError( sampleInRegion, resultAfterFit, doAsym) else: print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=", region, " bin=", ibin, " \n" nSampleInRegionVal.append(sampleInRegionVal) nSampleInRegionError.append(sampleInRegionError) varinRegionList[ireg].setRange(origMin, origMax) """ if showSum=True calculate the total number of fitted events in all regions """ if showSum: sampleSumInAllRegions = RooAddition( (sampleName + "_AllRegions_FITTED"), (sampleName + "_AllRegions_FITTED"), RooArgList(sampleInAllRegions)) nSampleSumVal = sampleSumInAllRegions.getVal() nSampleSumError = Util.GetPropagatedError(sampleSumInAllRegions, resultAfterFit, doAsym) nSampleInRegionVal.append(nSampleSumVal) nSampleInRegionError.append(nSampleSumError) tablenumbers['Fitted_events_' + sampleName] = nSampleInRegionVal tablenumbers['Fitted_err_' + sampleName] = nSampleInRegionError print "\n starting BEFORE-FIT calculations \n" """ FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS __BEFORRE__ THE FIT """ """ load beforeFit workspace snapshot (=set all parameters to values before fit) """ w.loadSnapshot('snapshot_paramsVals_RooExpandedFitResult_beforeFit') """ check if any of the initial scaling factors is != 1 """ _result = w.obj('RooExpandedFitResult_beforeFit') _muFacs = _result.floatParsFinal() for i in range(len(_muFacs)): if "mu_" in _muFacs[i].GetName() and _muFacs[i].getVal() != 1.0: print " \n WARNING: scaling factor %s != 1.0 (%g) expected MC yield WILL BE WRONG!" % ( _muFacs[i].GetName(), _muFacs[i].getVal()) """ get a list of pdf's and variables per region """ pdfinRegionList = [Util.GetRegionPdf(w, region) for region in regionList] varinRegionList = [Util.GetRegionVar(w, region) for region in regionList] """ get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples) """ rrspdfinRegionList = [] for index, pdf in enumerate(pdfinRegionList): prodList = pdf.pdfList() foundRRS = 0 for idx in range(prodList.getSize()): if prodList[idx].InheritsFrom("RooRealSumPdf"): rrspdfInt = prodList[idx].createIntegral( RooArgSet(varinRegionList[index])) rrspdfinRegionList.append(rrspdfInt) if splitBins: origMin = varinRegionList[index].getMin() origMax = varinRegionList[index].getMax() for ibin in range(0, varNbinsInRegionList[index]): rangeName = rangeNameBinsInRegionList[index][ibin] varinRegionList[index].setRange( rangeName, varBinLowInRegionList[index][ibin], varBinHighInRegionList[index][ibin]) rrspdfInt = prodList[idx].createIntegral( RooArgSet(varinRegionList[index]), rangeName) rrspdfinRegionList.append(rrspdfInt) varinRegionList[index].setRange(origMin, origMax) foundRRS += 1 if foundRRS > 1 or foundRRS == 0: print " \n\n WARNING: ", pdf.GetName( ), " has ", foundRRS, " instances of RooRealSumPdf" print pdf.GetName(), " component list:", prodList.Print("v") """ calculate total pdf number of expected events and error """ nExpInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList) ] pdfExpErrInRegionList = [ Util.GetPropagatedError(pdf, resultBeforeFit, doAsym) for pdf in rrspdfinRegionList ] """ if showSum=True calculate the total number of expected events in all regions """ if showSum: pdfInAllRegions = RooArgSet() for index, pdf in enumerate(rrspdfinRegionList): pdfInAllRegions.add(pdf) pdfSumInAllRegions = RooAddition("pdf_AllRegions_BEFORE", "pdf_AllRegions_BEFORE", RooArgList(pdfInAllRegions)) nPdfSumVal = pdfSumInAllRegions.getVal() nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultBeforeFit, doAsym) nExpInRegionList.append(nPdfSumVal) pdfExpErrInRegionList.append(nPdfSumError) tablenumbers['TOTAL_MC_EXP_BKG_events'] = nExpInRegionList tablenumbers['TOTAL_MC_EXP_BKG_err'] = pdfExpErrInRegionList """ calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf """ for isam, sample in enumerate(sampleList): sampleName = getName(sample) nMCSampleInRegionVal = [] nMCSampleInRegionError = [] MCSampleInAllRegions = RooArgSet() for ireg, region in enumerate(regionList): MCSampleInRegion = getPdfInRegions(w, sample, region) MCSampleInRegionVal = 0. MCSampleInRegionError = 0. if not MCSampleInRegion == None: MCSampleInRegionVal = MCSampleInRegion.getVal() MCSampleInRegionError = Util.GetPropagatedError( MCSampleInRegion, resultBeforeFit, doAsym) MCSampleInAllRegions.add(MCSampleInRegion) else: print " \n WARNING: sample=", sampleName, " non-existent (empty) in region=", region nMCSampleInRegionVal.append(MCSampleInRegionVal) nMCSampleInRegionError.append(MCSampleInRegionError) """ if splitBins=True calculate numbers of fitted events plus error per bin """ if splitBins: origMin = varinRegionList[ireg].getMin() origMax = varinRegionList[ireg].getMax() for ibin in range(0, varNbinsInRegionList[ireg]): rangeName = rangeNameBinsInRegionList[ireg][ibin] MCSampleInRegion = getPdfInRegionsWithRangeName( w, sample, region, rangeName) MCSampleInRegionVal = 0. MCSampleInRegionError = 0. if not MCSampleInRegion == None: varinRegionList[ireg].setRange( rangeName, varBinLowInRegionList[ireg][ibin], varBinHighInRegionList[ireg][ibin]) MCSampleInRegionVal = MCSampleInRegion.getVal() MCSampleInRegionError = Util.GetPropagatedError( MCSampleInRegion, resultBeforeFit, doAsym) else: print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=", region, " bin=", ibin, " \n" nMCSampleInRegionVal.append(MCSampleInRegionVal) nMCSampleInRegionError.append(MCSampleInRegionError) varinRegionList[ireg].setRange(origMin, origMax) """ if showSum=True calculate the total number of fitted events in all regions """ if showSum: MCSampleSumInAllRegions = RooAddition( (sampleName + "_AllRegions_MC"), (sampleName + "_AllRegions_MC"), RooArgList(MCSampleInAllRegions)) nMCSampleSumVal = MCSampleSumInAllRegions.getVal() nMCSampleSumError = Util.GetPropagatedError( MCSampleSumInAllRegions, resultBeforeFit, doAsym) nMCSampleInRegionVal.append(nMCSampleSumVal) nMCSampleInRegionError.append(nMCSampleSumError) tablenumbers['MC_exp_events_' + sampleName] = nMCSampleInRegionVal tablenumbers['MC_exp_err_' + sampleName] = nMCSampleInRegionError """ sort the tablenumbers set """ map_listofkeys = tablenumbers.keys() map_listofkeys.sort() """ print the sorted tablenumbers set """ for name in map_listofkeys: if tablenumbers.has_key(name): print name, ": ", tablenumbers[name] return tablenumbers
def latexfitresults(filename,regionList,sampleList,dataname='obsData',showSum=False, doAsym=True, blinded=False, splitBins=False): """ Calculate before/after-fit yields in all channels given @param filename The filename containing afterFit workspace @param regionList A list of regions to be considered @param sampleList A list of samples to be considered @param dataname The name of dataset (default='obsData') @param showSum Calculates sum of all regions if set to true (default=False) @param doAsym Calculates asymmetric errors taken from MINOS (default=True) @param blinded Observed event count will not be shown if set to True (default=False) @param splitBins Calculates bin-by-bin yields for all regions if set to True (default=False) """ """ pick up workspace from file """ workspacename = 'w' w = Util.GetWorkspaceFromFile(filename,'w') if w==None: print "ERROR : Cannot open workspace : ", workspacename sys.exit(1) """ pick up after-fit RooExpandedFitResult from workspace """ resultAfterFit = w.obj('RooExpandedFitResult_afterFit') if resultAfterFit==None: print "ERROR : Cannot open fit result after fit RooExpandedFitResult_afterFit" sys.exit(1) """ pick up before-fit RooExpandedFitResult from workspace """ resultBeforeFit = w.obj('RooExpandedFitResult_beforeFit') if resultBeforeFit==None: print "ERROR : Cannot open fit result before fit RooExpandedFitResult_beforeFit" sys.exit(1) """ pick up dataset from workspace """ data_set = w.data(dataname) if data_set==None: print "ERROR : Cannot open dataset : ", "data_set"+suffix sys.exit(1) """ pick up channel category (RooCategory) from workspace """ regionCat = w.obj("channelCat") if not blinded: data_set.table(regionCat).Print("v") """ find full (long) name list of regions (i.e. short=SR3J, long=SR3J_meffInc30_JVF25pt50) """ regionFullNameList = [ Util.GetFullRegionName(regionCat, region) for region in regionList] """ load afterFit workspace snapshot (=set all parameters to values after fit) """ snapshot = 'snapshot_paramsVals_RooExpandedFitResult_afterFit' w.loadSnapshot(snapshot) if not w.loadSnapshot(snapshot): print "ERROR : Cannot load snapshot : ", snapshot sys.exit(1) """ define set, for all names/yields to be saved in """ tablenumbers = {} """ if showSum=True define names for sum of all regions and add to regionList """ sumName = "" for index, reg in enumerate(regionList): if index == 0: sumName = reg else: sumName = sumName + " + " + reg regionListWithSum = list(regionList) if showSum: regionListWithSum.append(sumName) tablenumbers['names'] = regionListWithSum """ make a list of channelCat calls for every region """ regionCatList = [ 'channelCat==channelCat::' +region.Data() for region in regionFullNameList] """ retrieve number of observed (=data) events per region """ print regionCatList srindex = regionFullNameList.index("SR_cuts") regionDatasetList = [data_set.reduce(regioncat) for regioncat in regionCatList] for index, data in enumerate(regionDatasetList): print "data," , data, data.GetName() data.SetName("data_" + regionList[index]) data.SetTitle("data_" + regionList[index]) nobs_regionList = [ data.sumEntries() for data in regionDatasetList] if blinded : nobs_regionList[srindex] = -1 """ if showSum=True calculate the total number of observed events in all regions """ sumNobs = 0. for nobs in nobs_regionList: sumNobs += nobs if showSum: nobs_regionList.append(sumNobs) tablenumbers['nobs'] = nobs_regionList """ FROM HERE ON OUT WE CALCULATE THE FITTED NUMBER OF EVENTS __AFTER__ THE FIT """ """ get a list of pdf's and variables per region """ pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in regionList] varinRegionList = [ Util.GetRegionVar(w, region) for region in regionList] """ if splitBins=True get the list of Nbins, binMax and binMin; make a list of new region names for each bin """ varNbinsInRegionList = [] varBinLowInRegionList = [] varBinHighInRegionList = [] rangeNameBinsInRegionList = [] if splitBins: varNbinsInRegionList = [Util.GetRegionVar(w, region).getBinning().numBins() for region in regionList] varBinLowInRegionList = [[Util.GetRegionVar(w, region).getBinning((region+"binning")).binLow(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx,region in enumerate(regionList)] varBinHighInRegionList = [[Util.GetRegionVar(w, region).getBinning((region+"binning")).binHigh(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx,region in enumerate(regionList)] rangeNameBinsInRegionList = [[regionList[idx]+"_bin"+str(ibin) for ibin in range(0, varNbinsInRegionList[idx]) ] for idx,region in enumerate(regionList)] for index,region in enumerate(regionList): if varNbinsInRegionList[index]==1: print " \n YieldsTable.py: WARNING: you have called -P (= per-bin yields) but this region ", region, " has only 1 bin \n" """ if splitBins=True reshuffle the regionName list; each region name is followed by names of each bin (i.e. regionNameList=['SR3J','SR3J_bin1','SR3j_bin2','SR4J','SR4J_bin1']) """ regionListWithBins = [] if splitBins: for index,region in enumerate(regionList): regionListWithBins.append(region) for ibin in range(0,varNbinsInRegionList[index]): regionListWithBins.append(rangeNameBinsInRegionList[index][ibin]) tablenumbers['names'] = regionListWithBins """ calculate number of observed(=data) events per bin """ nobs_regionListWithBins = [] if splitBins: binFuncInRegionList = [RooBinningCategory("bin_"+region,"bin_"+region,varinRegionList[index]) for index,region in enumerate(regionList)] for index, data in enumerate(regionDatasetList): data.addColumn(binFuncInRegionList[index]) if not blinded: data.table(binFuncInRegionList[index]).Print("v") nobs_regionListWithBins.append(data.sumEntries()) for ibin in range(0,varNbinsInRegionList[index]): nobs_regionListWithBins.append((data.reduce(binFuncInRegionList[index].GetName()+"=="+binFuncInRegionList[index].GetName()+"::"+varinRegionList[index].GetName()+"_bin"+str(ibin))).sumEntries()) tablenumbers['nobs'] = nobs_regionListWithBins """ if blinded=True, set all numbers of observed events to -1 """ if blinded and splitBins: for index, nobs in enumerate(nobs_regionListWithBins): nobs_regionListWithBins[index] = -1 tablenumbers['nobs'] = nobs_regionListWithBins """ get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples) """ rrspdfinRegionList = [] for index,pdf in enumerate(pdfinRegionList): prodList = pdf.pdfList() foundRRS = 0 for idx in range(prodList.getSize()): if prodList[idx].InheritsFrom("RooRealSumPdf"): rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index])) rrspdfinRegionList.append(rrspdfInt) if splitBins: origMin = varinRegionList[index].getMin() origMax = varinRegionList[index].getMax() for ibin in range(0,varNbinsInRegionList[index]): rangeName = rangeNameBinsInRegionList[index][ibin] varinRegionList[index].setRange(rangeName,varBinLowInRegionList[index][ibin],varBinHighInRegionList[index][ibin]) rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]),rangeName) rrspdfinRegionList.append(rrspdfInt) varinRegionList[index].setRange(origMin,origMax) foundRRS += 1 if foundRRS >1 or foundRRS==0: print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf" print pdf.GetName(), " component list:", prodList.Print("v") """ calculate total pdf number of fitted events and error """ nFittedInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)] pdfFittedErrInRegionList = [ Util.GetPropagatedError(pdf, resultAfterFit, doAsym) for pdf in rrspdfinRegionList] """ if showSum=True calculate the total number of fitted events in all regions """ if showSum: pdfInAllRegions = RooArgSet() for index, pdf in enumerate(rrspdfinRegionList): pdfInAllRegions.add(pdf) pdfSumInAllRegions = RooAddition( "pdf_AllRegions_AFTER", "pdf_AllRegions_AFTER", RooArgList(pdfInAllRegions)) nPdfSumVal = pdfSumInAllRegions.getVal() nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultAfterFit, doAsym) nFittedInRegionList.append(nPdfSumVal) pdfFittedErrInRegionList.append(nPdfSumError) tablenumbers['TOTAL_FITTED_bkg_events'] = nFittedInRegionList tablenumbers['TOTAL_FITTED_bkg_events_err'] = pdfFittedErrInRegionList """ calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf """ for isam, sample in enumerate(sampleList): sampleName=getName(sample) nSampleInRegionVal = [] nSampleInRegionError = [] sampleInAllRegions = RooArgSet() for ireg, region in enumerate(regionList): sampleInRegion=getPdfInRegions(w,sample,region) sampleInRegionVal = 0. sampleInRegionError = 0. if not sampleInRegion==None: sampleInRegionVal = sampleInRegion.getVal() sampleInRegionError = Util.GetPropagatedError(sampleInRegion, resultAfterFit, doAsym) sampleInAllRegions.add(sampleInRegion) else: print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region =",region, "\n" nSampleInRegionVal.append(sampleInRegionVal) nSampleInRegionError.append(sampleInRegionError) """ if splitBins=True calculate numbers of fitted events plus error per bin """ if splitBins: origMin = varinRegionList[ireg].getMin() origMax = varinRegionList[ireg].getMax() for ibin in range(0,varNbinsInRegionList[ireg]): rangeName = rangeNameBinsInRegionList[ireg][ibin] sampleInRegion=getPdfInRegionsWithRangeName(w,sample,region,rangeName) sampleInRegionVal = 0. sampleInRegionError = 0. if not sampleInRegion==None: varinRegionList[ireg].setRange(rangeName,varBinLowInRegionList[ireg][ibin],varBinHighInRegionList[ireg][ibin]) sampleInRegionVal = sampleInRegion.getVal() sampleInRegionError = Util.GetPropagatedError(sampleInRegion, resultAfterFit, doAsym) else: print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=",region, " bin=",ibin, " \n" nSampleInRegionVal.append(sampleInRegionVal) nSampleInRegionError.append(sampleInRegionError) varinRegionList[ireg].setRange(origMin,origMax) """ if showSum=True calculate the total number of fitted events in all regions """ if showSum: sampleSumInAllRegions = RooAddition( (sampleName+"_AllRegions_FITTED"), (sampleName+"_AllRegions_FITTED"), RooArgList(sampleInAllRegions)) nSampleSumVal = sampleSumInAllRegions.getVal() nSampleSumError = Util.GetPropagatedError(sampleSumInAllRegions, resultAfterFit, doAsym) nSampleInRegionVal.append(nSampleSumVal) nSampleInRegionError.append(nSampleSumError) tablenumbers['Fitted_events_'+sampleName] = nSampleInRegionVal tablenumbers['Fitted_err_'+sampleName] = nSampleInRegionError print "\n starting BEFORE-FIT calculations \n" """ FROM HERE ON OUT WE CALCULATE THE EXPECTED NUMBER OF EVENTS __BEFORRE__ THE FIT """ """ load beforeFit workspace snapshot (=set all parameters to values before fit) """ w.loadSnapshot('snapshot_paramsVals_RooExpandedFitResult_beforeFit') """ check if any of the initial scaling factors is != 1 """ _result = w.obj('RooExpandedFitResult_beforeFit') _muFacs = _result.floatParsFinal() for i in range(len(_muFacs)): if "mu_" in _muFacs[i].GetName() and _muFacs[i].getVal() != 1.0: print " \n WARNING: scaling factor %s != 1.0 (%g) expected MC yield WILL BE WRONG!" % (_muFacs[i].GetName(), _muFacs[i].getVal()) """ get a list of pdf's and variables per region """ pdfinRegionList = [ Util.GetRegionPdf(w, region) for region in regionList] varinRegionList = [ Util.GetRegionVar(w, region) for region in regionList] """ get a list of RooRealSumPdf per region (RooRealSumPdf is the top-pdf per region containing all samples) """ rrspdfinRegionList = [] for index,pdf in enumerate(pdfinRegionList): prodList = pdf.pdfList() foundRRS = 0 for idx in range(prodList.getSize()): if prodList[idx].InheritsFrom("RooRealSumPdf"): rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index])) rrspdfinRegionList.append(rrspdfInt) if splitBins: origMin = varinRegionList[index].getMin() origMax = varinRegionList[index].getMax() for ibin in range(0,varNbinsInRegionList[index]): rangeName = rangeNameBinsInRegionList[index][ibin] varinRegionList[index].setRange(rangeName,varBinLowInRegionList[index][ibin],varBinHighInRegionList[index][ibin]) rrspdfInt = prodList[idx].createIntegral(RooArgSet(varinRegionList[index]),rangeName) rrspdfinRegionList.append(rrspdfInt) varinRegionList[index].setRange(origMin,origMax) foundRRS += 1 if foundRRS >1 or foundRRS==0: print " \n\n WARNING: ", pdf.GetName(), " has ", foundRRS, " instances of RooRealSumPdf" print pdf.GetName(), " component list:", prodList.Print("v") """ calculate total pdf number of expected events and error """ nExpInRegionList = [ pdf.getVal() for index, pdf in enumerate(rrspdfinRegionList)] pdfExpErrInRegionList = [ Util.GetPropagatedError(pdf, resultBeforeFit, doAsym) for pdf in rrspdfinRegionList] """ if showSum=True calculate the total number of expected events in all regions """ if showSum: pdfInAllRegions = RooArgSet() for index, pdf in enumerate(rrspdfinRegionList): pdfInAllRegions.add(pdf) pdfSumInAllRegions = RooAddition( "pdf_AllRegions_BEFORE", "pdf_AllRegions_BEFORE", RooArgList(pdfInAllRegions)) nPdfSumVal = pdfSumInAllRegions.getVal() nPdfSumError = Util.GetPropagatedError(pdfSumInAllRegions, resultBeforeFit, doAsym) nExpInRegionList.append(nPdfSumVal) pdfExpErrInRegionList.append(nPdfSumError) tablenumbers['TOTAL_MC_EXP_BKG_events'] = nExpInRegionList tablenumbers['TOTAL_MC_EXP_BKG_err'] = pdfExpErrInRegionList """ calculate the fitted number of events and propagated error for each requested sample, by splitting off each sample pdf """ for isam, sample in enumerate(sampleList): sampleName=getName(sample) nMCSampleInRegionVal = [] nMCSampleInRegionError = [] MCSampleInAllRegions = RooArgSet() for ireg, region in enumerate(regionList): MCSampleInRegion = getPdfInRegions(w,sample,region) MCSampleInRegionVal = 0. MCSampleInRegionError = 0. if not MCSampleInRegion==None: MCSampleInRegionVal = MCSampleInRegion.getVal() MCSampleInRegionError = Util.GetPropagatedError(MCSampleInRegion, resultBeforeFit, doAsym) MCSampleInAllRegions.add(MCSampleInRegion) else: print " \n WARNING: sample=", sampleName, " non-existent (empty) in region=",region nMCSampleInRegionVal.append(MCSampleInRegionVal) nMCSampleInRegionError.append(MCSampleInRegionError) """ if splitBins=True calculate numbers of fitted events plus error per bin """ if splitBins: origMin = varinRegionList[ireg].getMin() origMax = varinRegionList[ireg].getMax() for ibin in range(0,varNbinsInRegionList[ireg]): rangeName = rangeNameBinsInRegionList[ireg][ibin] MCSampleInRegion=getPdfInRegionsWithRangeName(w,sample,region,rangeName) MCSampleInRegionVal = 0. MCSampleInRegionError = 0. if not MCSampleInRegion==None: varinRegionList[ireg].setRange(rangeName,varBinLowInRegionList[ireg][ibin],varBinHighInRegionList[ireg][ibin]) MCSampleInRegionVal = MCSampleInRegion.getVal() MCSampleInRegionError = Util.GetPropagatedError(MCSampleInRegion, resultBeforeFit, doAsym) else: print " \n YieldsTable.py: WARNING: sample =", sampleName, " non-existent (empty) in region=",region, " bin=",ibin, " \n" nMCSampleInRegionVal.append(MCSampleInRegionVal) nMCSampleInRegionError.append(MCSampleInRegionError) varinRegionList[ireg].setRange(origMin,origMax) """ if showSum=True calculate the total number of fitted events in all regions """ if showSum: MCSampleSumInAllRegions = RooAddition( (sampleName+"_AllRegions_MC"), (sampleName+"_AllRegions_MC"), RooArgList(MCSampleInAllRegions)) nMCSampleSumVal = MCSampleSumInAllRegions.getVal() nMCSampleSumError = Util.GetPropagatedError(MCSampleSumInAllRegions, resultBeforeFit, doAsym) nMCSampleInRegionVal.append(nMCSampleSumVal) nMCSampleInRegionError.append(nMCSampleSumError) tablenumbers['MC_exp_events_'+sampleName] = nMCSampleInRegionVal tablenumbers['MC_exp_err_'+sampleName] = nMCSampleInRegionError """ sort the tablenumbers set """ map_listofkeys = tablenumbers.keys() map_listofkeys.sort() """ print the sorted tablenumbers set """ for name in map_listofkeys: if tablenumbers.has_key(name) : print name, ": ", tablenumbers[name] return tablenumbers