def __init__(self, reconstructedHist, migrationMatrix):
super(UnfoldingTUnfold, self).__init__(reconstructedHist,
migrationMatrix)
### Be careful of underflow/overflow bins, may want to set to zero for all?
self.tunfold = ROOT.TUnfoldDensity(
cloneTNamedUUIDName(migrationMatrix),
ROOT.TUnfold.kHistMapOutputVert)
errCode = self.tunfold.SetInput(cloneTNamedUUIDName(reconstructedHist))
if errCode >= 10000:
print(
"Warning: TUnfold doesn't think input data can make unfolding work"
)
def binArrayToHist(self, a, th2=False):
if th2:
result = cloneTNamedUUIDName(self.migrationMatrix)
result.Reset()
nBins = result.GetNbinsX()
assert (hist.GetNbinsY() == nBins)
assert (a.shape == (nBins, nBins))
for iBin in range(1, nBins + 1):
for jBin in range(1, nBins + 1):
result.SetBinContent(iBin, jBin, a[iBin - 1][jBin - 1])
return result
else:
result = cloneTNamedUUIDName(self.reconstructedHist)
result.Reset()
nBins = result.GetNbinsX()
for iBin in range(1, nBins + 1):
result.SetBinContent(iBin, a[iBin - 1])
return result
def getMigrationMatrix(self):
return cloneTNamedUUIDName(self.migrationMatrix)
def getReconstructedHist(self):
return cloneTNamedUUIDName(self.reconstructedHist)
def getCovarianceMatrix(self):
return cloneTNamedUUIDName(self.covarianceMatrix)
def getResult(self):
return cloneTNamedUUIDName(self.resultHist)