input_files,
tree,
'mvis',
toString(cuts_est),
'weight',
global_weights,
fakefactor=fakefactor,
ffInputs=['l2_pt', 'l2_decayMode', 'mvis'])
closure.computeCDF('True')
closure.computeCDF('Est')
for name, bins in var_bins.items():
plotClosure(fakeType + '_' + name,
closure,
bins,
doErrors=False,
yRange=[0.5, 2.],
plotDir=plotDir)
#for nbins in [100,50,25]:
#cdf = closure.data['True']['CDFInvert']
#bins = [cdf.Eval(i/float(nbins)) for i in xrange(nbins+1)]
#plotClosure(fakeType+'_NBins'+str(nbins), closure, bins)
plotSummary(fakeType, closure, 0, 600)
#
writeNonClosure(closure, output_file,
'{FAKETYPE}_Histo_Smooth_Ratio'.format(FAKETYPE=fakeType))
#canvas.Write()
global_weights = inputs['Weights']
tree = inputs['Tree']
fakefactor = inputs['FakeFactor']
cuts_true = inputs['CutsIso']
cuts_est = inputs['CutsAntiIso']
closure = Closure()
closure.fillData('True', input_files, tree, 'mvis', toString(cuts_true), 'weight', global_weights)
#closure.fillData('Est', input_files, tree, 'mvis', toString(cuts_est), 'weight', global_weights, fakefactor=fakefactor, ffInputs=['l2_pt', 'l2_decayMode', 'mvis'])
closure.fillData('Est', input_files, tree, 'mvis', toString(cuts_est), 'weight', global_weights, fakefactor=fakefactor, ffInputs=['l2_pt', 'l2_decayMode'])
closure.computeCDF('True')
closure.computeCDF('Est')
for name,bins in var_bins.items():
plotClosure(fakeType+'_'+name, closure, bins, doErrors=False, yRange=[0.5,2.], plotDir=plotDir)
#for nbins in [100,50,25]:
#cdf = closure.data['True']['CDFInvert']
#bins = [cdf.Eval(i/float(nbins)) for i in xrange(nbins+1)]
#plotClosure(fakeType+'_NBins'+str(nbins), closure, bins)
plotSummary(fakeType, closure, 0, 600)
#
writeNonClosure(closure, output_file, '{FAKETYPE}_Histo_Smooth_Ratio'.format(FAKETYPE=fakeType))
#canvas.Write()
##cdfTrue.SetName('{FAKETYPE}_CDF_True'.format(FAKETYPE=fakeType))
##cdfEst.SetName('{FAKETYPE}_CDF_Est'.format(FAKETYPE=fakeType))
#histoTrue.SetName('{FAKETYPE}_Histo_True_{H}'.format(FAKETYPE=fakeType,H=binid))
global_weights = inputs['Weights']
tree = inputs['Tree']
fakefactor = inputs['FakeFactor']
cuts_true = inputs['CutsIso']
cuts_est = inputs['CutsAntiIso']
closure = Closure()
closure.fillData('True', input_files, tree, 'l1_reliso05', toString(cuts_true), 'weight', global_weights)
closure.fillData('Est', input_files, tree, 'l1_reliso05', toString(cuts_est), 'weight', global_weights, fakefactor=fakefactor, ffInputs=['l2_pt', 'l2_decayMode', 'mvis'])
closure.computeCDF('True')
closure.computeCDF('Est')
for name,bins in var_bins.items():
plotClosure(fakeType+'_'+name, closure, bins, doErrors=False, yRange=[0.5,2.], plotDir=plotDir, xTitle='iso(#mu)')
#for nbins in [100,50,25]:
#cdf = closure.data['True']['CDFInvert']
#bins = [cdf.Eval(i/float(nbins)) for i in xrange(nbins+1)]
#plotClosure(fakeType+'_NBins'+str(nbins), closure, bins)
plotSummary(fakeType, closure, 0, 600)
#
writeNonClosure(closure, output_file, '{FAKETYPE}_Histo_Smooth_Ratio'.format(FAKETYPE=fakeType))
#canvas.Write()
##cdfTrue.SetName('{FAKETYPE}_CDF_True'.format(FAKETYPE=fakeType))
##cdfEst.SetName('{FAKETYPE}_CDF_Est'.format(FAKETYPE=fakeType))
#histoTrue.SetName('{FAKETYPE}_Histo_True_{H}'.format(FAKETYPE=fakeType,H=binid))