Plot.setDefaults(stack = stack, weight = weight, addOverFlowBin=None)
plots, fisherInfoVariables = process.getPlotList( args.scaleLumi, args.level )
plotting.fill(plots, read_variables = read_variables, sequence = sequence, max_events = -1 if args.small else -1)
if args.addFisherInformation:
for i, plot in enumerate(plots):
if fisherInfoVariables[i] is None: continue
fiHistoListIndex = len(plot.histos)-3 if args.backgrounds else len(plot.histos)-1
bins = plot.binning
var = fisherInfoVariables[i] #replace with better solution than FI_plots!!
hist = w.getFisherInformationHisto( ttXSample, var, bins, selectionString=cutInterpreter.cutString(args.selection), weightString=ttXWeightString, variables=args.variables, nEventsThresh = args.binThreshold, **fisherInfo_WC)
plot.histos[fiHistoListIndex] = [plot.fromHisto( 'histo_%i'%i, hist ).histos]
if args.backgrounds:
#get list of contents of bg histo
bgContentList = histo_to_list( plot.histos_added[-1][0] )
#get list of contents of signal histo
sigContentList = histo_to_list( plot.histos[fiHistoListIndex-1][0] )
#calculate purity for each bin
purityBinList = [ sig / ( sig + bgContentList[j] ) if (sig + bgContentList[j])!=0 else 0 for j, sig in enumerate( sigContentList ) ]
# multiply ideal fisher info histo purity
for l in range(bins[0]):
plot.histos[fiHistoListIndex+1][0].SetBinContent(l+1, plot.histos[fiHistoListIndex][0].GetBinContent(l+1) * purityBinList[l])
drawPlots(plots)
hist = w.getFisherInformationHisto(
ttXSample,
var,
bins,
selectionString=cutInterpreter.cutString(args.selection),
weightString=ttXWeightString,
variables=args.variables,
nEventsThresh=args.binThreshold,
**fisherInfo_WC)
plot.histos[fiHistoListIndex] = [
plot.fromHisto('histo_%i' % i, hist).histos
]
if args.addFisherInformationBackground:
#get list of contents of bg histo
bgContentList = histo_to_list(plot.histos_added[len(params) +
1][0])
#get list of contents of bg histo
nonInfoContentList = histo_to_list(
plot.histos_added[len(params)][0])
#get list of contents of signal histo
sigContentList = histo_to_list(plot.histos[len(params) - 1][0])
#calculate purity for each bin
purityBinList = [
(sig + nonInfoContentList[j]) /
(sig + nonInfoContentList[j] + bgContentList[j]) if
(sig + nonInfoContentList[j] + bgContentList[j]) != 0 else 0
for j, sig in enumerate(sigContentList)
]
# multiply ideal fisher info histo purity
for l in range(bins[0]):
plot.histos[fiHistoListIndex + 1][0].SetBinContent(