def templates(self, iStep, dist, qqFrac) :
if not hasattr(self,'orgMelded') : print 'run meldScale() before asking for templates()'; return
topQQs = [s['name'] for s in self.orgMelded.samples if 'wTopAsym' in s['name']]
asymm = [eval(name.replace("top.tt_tauola_fj.wTopAsym","").replace(".tw.nvr","").replace("P",".").replace("N","-.")) for name in topQQs]
distTup = self.orgMelded.steps[iStep][dist]
edges = utils.edgesRebinned( distTup[ self.orgMelded.indexOfSampleWithName("S.M.") ], targetUncRel = 0.015, offset = 2 )
def nparray(name, scaleToN = None) :
hist_orig = distTup[ self.orgMelded.indexOfSampleWithName(name) ]
hist = hist_orig.Rebin(len(edges)-1, "%s_rebinned"%hist_orig.GetName(), edges)
bins = np.array([hist.GetBinContent(j) for j in range(hist.GetNbinsX()+2)])
if scaleToN : bins *= (scaleToN / sum(bins))
return bins
nTT = sum(nparray('top.t#bar{t}'))
observed = nparray('top.Data 2011')
base = ( nparray('QCD.Data 2011') +
nparray('top.w_jets') +
nparray('top.tt_tauola_fj.wNonQQbar.tw.nvr', scaleToN = (1-qqFrac) * nTT )
)
templates = [base + nparray(qqtt, qqFrac*nTT ) for qqtt in topQQs]
return zip(asymm, templates), observed
def setup(self,*_) :
import numpy as np
orig = self.fromCache( [self.sample], [self.dist], tag = self.tag)[self.sample][self.dist]
if not orig : return
edges = utils.edgesRebinned(orig, targetUncRel = 0.065)
hist = orig.Rebin(len(edges)-1, "tmp", edges)
vals = [hist.GetBinContent(i) for i in range(1,len(edges))]
del hist
iZero = edges.index(0)
R = np.array(vals[iZero:])
L = np.array(vals[:iZero])[::-1]
p = R / ( R + L )
self.p = r.TH1D(self.name, ";|%s|;p of correct qDir"%self.var, len(edges[iZero:])-1, edges[iZero:])
for i in range(len(p)) : self.p.SetBinContent(i+1,p[i])
self.p.SetBinContent(len(edges[iZero:])+2, edges[-1])
if self.path is not None :
c = r.TCanvas()
self.p.Draw('hist')
utils.tCanvasPrintPdf(c,'%s/%s'%(self.path,'.'.join([self.name,self.sample,self.tag])))
del c
