def buildWeightedHisto(histos={}, fractions={}, histoName='', histoTitle='') :
"was getFinalRate"
hout = first(histos).Clone(histoName if histoName else 'final_rate') # should pick a better default
hout.SetTitle(histoTitle)
hout.Reset()
flatFraction = type(first(fractions)) is float
if flatFraction :
print "averaging flat ",histoName
print 'keys -> ',histos.keys()
for b in getBinIndices(hout) :
tot, err2 = binWeightedSum(histos, fractions, b)
hout.SetBinContent(b, tot)
hout.SetBinError(b, sqrt(err2))
else :
bH, bF = getBinning(first(histos)), getBinning(first(fractions))
assert bH == bF,"different binning %s: %s, %s: %s"%(first(histos).GetName(), bH, first(fractions).GetName(), bF)
weightedHistos = dict((p, h.Clone(h.GetName()+'_weighted_for_'+histoName)) for p,h in histos.iteritems()) # preserve originals
print "averaging 2d ",histoName
for b in getBinIndices(hout):
print "bin %d (w=%.1f): %.3f = %s"%(b,
sum(fractions[p].GetBinContent(b) for p in fractions.keys()),
sum(fractions[p].GetBinContent(b)*weightedHistos[p].GetBinContent(b) for p in fractions.keys()),
'+'.join("%.2f*%.2f"%(fractions[p].GetBinContent(b), weightedHistos[p].GetBinContent(b))
for p in fractions.keys()))
for p,h in weightedHistos.iteritems() :
h.Multiply(fractions[p])
hout.Add(h)
return hout
def buildWeightedHistoTwice(histosA={}, fractionsA={}, histosB={}, fractionsB={},
histoName='', histoTitle='') :
"was getFinalRate"
assert not set(histosA)-set(histosB),"different keys A[%s], B[%s]"%(str(histosA.keys()), str(histosB.keys()))
assert type(first(fractionsA)) is type(first(fractionsB)),"etherogenous fractions A %s, B %s"%(type(first(fractionsA)), type(first(fractionsB)))
hout = first(histosA).Clone(histoName if histoName else 'final_rate') # should pick a better default
hout.SetTitle(histoTitle)
hout.Reset()
flatFraction = type(first(fractionsA)) is float
if flatFraction :
print "averaging flat ",histoName
print 'keys -> ',histosA.keys()
for b in getBinIndices(hout) :
totA, errA2 = binWeightedSum(histosA, fractionsA, b)
totB, errB2 = binWeightedSum(histosB, fractionsB, b)
hout.SetBinContent(b, totA + totB)
hout.SetBinError(b, sqrt(errA2 + errB2))
else :
bHA, bFA = getBinning(first(histosA)), getBinning(first(fractionsA))
bHB, bFB = getBinning(first(histosB)), getBinning(first(fractionsB))
assert bHA == bFA,"different binning %s: %s, %s: %s"%(first(histosA).GetName(), bHA, first(fractionsA).GetName(), bFA)
assert bHB == bFB,"different binning %s: %s, %s: %s"%(first(histosB).GetName(), bHB, first(fractionsB).GetName(), bFB)
assert bHA == bHB,"different binning %s: %s, %s: %s"%(first(histosA).GetName(), bHA, first(histosB).GetName(), bHB)
weightedHistosA = dict((p, h.Clone(h.GetName()+'_weighted_for_'+histoName)) for p,h in histosA.iteritems()) # preserve originals
weightedHistosB = dict((p, h.Clone(h.GetName()+'_weighted_for_'+histoName)) for p,h in histosB.iteritems())
print "averaging 2d ",histoName
for b in getBinIndices(hout):
print "bin %d (w=%.1f): %.3f = %s"%(b,
sum(fractionsA[p].GetBinContent(b)+fractionsB[p].GetBinContent(b) for p in fractionsA.keys()),
sum(fractionsA[p].GetBinContent(b)*weightedHistosA[p].GetBinContent(b)
+fractionsB[p].GetBinContent(b)*weightedHistosB[p].GetBinContent(b)
for p in fractionsA.keys()),
'+'.join(["%.2f*%.2f"%(fractionsA[p].GetBinContent(b),
weightedHistosA[p].GetBinContent(b))
for p in fractionsA.keys()]+
["%.2f*%.2f"%(fractionsB[p].GetBinContent(b),
weightedHistosB[p].GetBinContent(b))
for p in fractionsB.keys()]))
for p in weightedHistosA.keys() :
hA, fA = weightedHistosA[p], fractionsA[p]
hB, fB = weightedHistosB[p], fractionsB[p]
hA.Multiply(fA)
hB.Multiply(fB)
hout.Add(hA)
hout.Add(hB)
return hout
def frac2str(frac) :
flatFraction = type(first(frac)) is float
return ('\n'.join([''.join("%12s"%s for s in fakeProcesses()),
''.join("%12s"%("%.3f"%frac[s]) for s in fakeProcesses())])
if flatFraction
else '\n'.join([''.join("%12s"%s for s in fakeProcesses())]
+[''.join("%12s"%("%.3f"%frac[s].GetBinContent(b)) for s in fakeProcesses())
for b in getBinIndices(first(frac))]))
def normalizeHistos(histos) :
"Normalize the input histos so that in each bin the sum of the different processes amounts to 1.0"
basename = guessBaseHistoname([h.GetName() for h in histos.values() if h])
tot = first(histos).Clone(basename+'_tot')
tot.Reset()
for h in histos.values() : tot.Add(h)
for b in getBinIndices(tot) : tot.SetBinError(b, 0.0) # norm is a constraint, without error
for h in histos.values() : h.Divide(tot)
def histo1dToTxt(h):
"represent a TH1 as a string with name, bin edges, contents, and errors"
bins = getBinIndices(h)
hisName = h.GetName()
binEdge = [h.GetBinLowEdge(b) for b in bins]
binEdge.append(binEdge[-1] + h.GetBinWidth(bins[-1]))
binCont = getBinContents(h)
binErr = [be(h, b) for b in bins]
def lf2s(l):
return ", ".join(["%.3f" % e for e in l])
return "\n".join(
[
"%s : %s" % (n, v)
for n, v in [("hisName", hisName)] + [(l, lf2s(eval(l))) for l in ["binEdge", "binCont", "binErr"]]
]
)
