def ensembleTest(self) :
qqFracs = sorted([0.10, 0.12, 0.15, 0.20, 0.25, 0.30, 0.40, 0.60, 1.0])
dists = ['lHadtDeltaY',
'ttbarDeltaAbsY',
'leptonRelativeY',
'ttbarSignedDeltaY'
]
args = sum([[(iStep, dist, qqFrac) for iStep in list(self.orgMelded.indicesOfStepsWithKey(dist))[:None] for qqFrac in qqFracs] for dist in dists],[])
utils.operateOnListUsingQueue(6, utils.qWorker(self.pickleEnsemble), args)
ensembles = dict([(arg,utils.readPickle(self.ensembleFileName(*arg))) for arg in args])
for iStep in sorted(set([iStep for iStep,dist,qqFrac in ensembles])) :
canvas = r.TCanvas()
dists = sorted(set([dist for jStep,dist,qqFrac in ensembles if jStep==iStep]))
legend = r.TLegend(0.7,0.5,0.9,0.9)
graphs = {}
for iDist,dist in enumerate(dists) :
points = sorted([(qqFrac,ensemble.sensitivity) for (jStep, jDist, qqFrac),ensemble in ensembles.iteritems() if jStep==iStep and jDist==dist])
qqs,sens = zip(*points)
graphs[dist] = r.TGraph(len(points),np.array(qqs),np.array(sens))
graphs[dist].SetLineColor(iDist+1)
graphs[dist].Draw('' if iDist else "AL")
graphs[dist].SetMinimum(0)
graphs[dist].SetTitle("Sensitivity @ step %d;fraction of t#bar{t} from q#bar{q};expected uncertainty on R"%iStep)
legend.AddEntry(graphs[dist],dist,'l')
legend.Draw()
utils.tCanvasPrintPdf(canvas, '%s/sensitivity_%d'%(self.globalStem,iStep))
def PEcurves(self) :
if not hasattr(self, 'orgMelded') : return
specs = ([{'var' : "ak5JetPFNTrkHiEffPat[i[%d]]:xcak5JetPFIndicesBtaggedPat"%bIndex, 'left':True, 'right':False} for bIndex in [0,1,2]] +
[{'var' : "TopRatherThanWProbability", 'left':True, 'right':False},
{'var' : "TriDiscriminant", 'left':True, 'right':True}])
pes = {}
for spec in specs :
dists = dict(zip([ss['name'] for ss in self.orgMelded.samples ],
self.orgMelded.steps[next(self.orgMelded.indicesOfStepsWithKey(spec['var']))][spec['var']] ) )
contours = utils.optimizationContours( [dists['top.t#bar{t}']],
[dists[s] for s in ['QCD.Data 2011','top.w_jets']],
**spec
)
utils.tCanvasPrintPdf(contours[0], "%s/PE_%s"%(self.globalStem,spec['var']))
if spec['left']^spec['right'] : pes[spec['var']] = contours[1]
c = r.TCanvas()
leg = r.TLegend(0.5,0.8,1.0,1.0)
graphs = []
for i,(var,pe) in enumerate(pes.iteritems()) :
pur,eff = zip(*pe)
g = r.TGraph(len(pe), np.array(eff), np.array(pur))
g.SetTitle(";efficiency;purity")
g.SetLineColor(i+2)
leg.AddEntry(g,var,'l')
graphs.append(g)
g.Draw('' if i else 'AL')
leg.Draw()
c.Update()
utils.tCanvasPrintPdf(c, "%s/purity_v_efficiency"%self.globalStem)
return
def measureFractions(dist) :
before = next(self.orgMelded.indicesOfStep("label","selection complete"))
distTup = self.orgMelded.steps[next(iter(filter(lambda i: before<i, self.orgMelded.indicesOfStepsWithKey(dist))))][dist]
#distTup = self.orgMelded.steps[next(self.orgMelded.indicesOfStepsWithKey(dist))][dist]
templateSamples = ['top.t#bar{t}','top.w_jets','QCD.Data 2011']
templates = [None] * len(templateSamples)
for ss,hist in zip(self.orgMelded.samples,distTup) :
contents = [hist.GetBinContent(i) for i in range(hist.GetNbinsX()+2)]
if ss['name'] == "top.Data 2011" :
observed = contents
nEventsObserved = sum(observed)
elif ss['name'] in templateSamples :
templates[templateSamples.index(ss['name'])] = contents
else : pass
from core.fractions import componentSolver,drawComponentSolver
cs = componentSolver(observed, templates, 1e4)
csCanvas = drawComponentSolver(cs)
name = "measuredFractions_%s"%dist
utils.tCanvasPrintPdf(csCanvas[0], "%s/%s"%(self.globalStem,name))
with open(self.globalStem+"/%s.txt"%name,"w") as file :
print >> file, cs
print >> file, cs.components
return distTup,cs
def measureQQbarComponent(self) :
dist = "DiscriminantTopQqQg"
dists = dict(zip([ss['name'] for ss in self.orgMelded.samples ],
self.orgMelded.steps[next(self.orgMelded.indicesOfStepsWithKey(dist))][dist] ) )
def contents(name) : return np.array([dists[name].GetBinContent(i) for i in range(dists[name].GetNbinsX()+2)])
from core.fractions import componentSolver, drawComponentSolver
cs = componentSolver(observed = contents('top.Data 2011'),
components = [ contents('top.tt_tauola_fj.wTopAsymP00.tw.nvr'), contents('top.tt_tauola_fj.wNonQQbar.tw.nvr')],
ensembleSize = 1e4,
base = contents('top.w_jets') + contents('QCD.Data 2011')
)
csCanvas = drawComponentSolver(cs)
utils.tCanvasPrintPdf(csCanvas[0], "%s/measuredQQFractions"%self.globalStem)
with open(self.globalStem+"/measuredQQFractions.txt","w") as file : print >> file, cs
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
