def StatTest(self, numexp):
diff = ROOT.TH1D(self.hmeasured)
diffq = ROOT.TH1D(self.hmeasured)
diff.Reset()
diffq.Reset()
numevents = self.hmeasured.Integral()
for exp in range(0, numexp):
self.Generate(numevents)
genunfolded = self.GetUnfolded(self.genmeasured)
print "exp", self.gentruth.Integral(), genunfolded.Integral(
), self.genmeasured.Integral(), numevents
for b in range(1, genunfolded.GetNbinsX() + 1):
bdiff = genunfolded.GetBinContent(
b) - self.gentruth.GetBinContent(b)
diff.SetBinContent(b, diff.GetBinContent(b) + bdiff)
diffq.SetBinContent(b, diff.GetBinContent(b) + bdiff * bdiff)
for b in range(1, diff.GetNbinsX() + 1):
mean = diff.GetBinContent(b) / float(numexp)
meanq = diff.GetBinContent(b) / float(numexp)
diff.SetBinContent(b, mean / self.gentruth.GetBinContent(b))
diff.SetBinError(
b,
math.sqrt(abs(meanq - mean * mean)) /
self.gentruth.GetBinContent(b))
return diff
def write_txt(txt, name):
if txt:
ttxt = ROOT.TText(0., 0., txt)
ttxt.SetName(name)
return ttxt.Write()
else:
return 0.
def DoScanLcurve(self, npoints, tau_min=0, tau_max=20):
#reset unfolding (if any) since the method messes up with the output
self.unfoldingdone = False
lcurve = ROOT.TGraph()
spline_x = ROOT.TSpline3()
spline_y = ROOT.TSpline3()
best = self.unfolder.ScanLcurve(npoints, tau_min, tau_max, lcurve,
spline_x, spline_y)
lcurve.GetXaxis().SetTitle('log(#chi^{2})')
lcurve.GetYaxis().SetTitle('log(regularization)')
graph_x = spline2graph(spline_x)
graph_y = spline2graph(spline_y)
graph_x.get_xaxis().SetTitle('log(#tau)')
graph_y.get_xaxis().SetTitle('log(#tau)')
graph_x.get_yaxis().SetTitle('log(#chi^{2})')
graph_y.get_yaxis().SetTitle('log(regularization)')
return self.unfolder.GetTau(), lcurve, graph_x, graph_y
def DoScanTau(self, npoints, tau_min=0., tau_max=20., mode='RhoAvg'):
#reset unfolding (if any) since the method messes up with the output
self.unfoldingdone = False
scan_mode = URUnfolding.scantaumodes[mode]
spline = ROOT.TSpline3()
best = self.unfolder.ScanTau(npoints, tau_min, tau_max, spline,
scan_mode)
#, const char* distribution = 0, const char* projectionMode = 0, TGraph** lCurvePlot = 0, TSpline** logTauXPlot = 0, TSpline** logTauYPlot = 0)
#convert spline in Graph
scan = spline2graph(spline)
scan.get_xaxis().SetTitle('log(#tau)')
scan.get_yaxis().SetTitle(mode)
return self.unfolder.GetTau(), scan, best
def InitUnfolder(self):
self.ScaleDistributions(self.scale)
log.debug('Initializing unfolder.')
self.unfolder = ROOT.TUnfoldDensity(
self.matrix, URUnfolding.orientations[self.orientation],
URUnfolding.regularizations[self.regmode],
URUnfolding.constraints[self.constraint],
URUnfolding.densities[self.density])
log.debug('Loading histogram %s into unfolder' %
self.measured.GetName())
if self.cov_matrix:
status = self.unfolder.SetInput(self.measured, 0., 0.,
self.cov_matrix)
else:
status = self.unfolder.SetInput(self.measured)
if status >= 10000:
raise RuntimeError('Unfolding status %i. Unfolding impossible!' %
status)
def write_float(h, name):
return ROOT.RooRealVar(name, name, h).Write()
def Generate(self, numevents):
if (not hasattr(self, 'gentruth')) or self.gentruth == 0:
self.hmiss = ROOT.TH1D(self.truth)
self.hmiss.Add(self.matrix.ProjectionX(), -1.)
self.hfake = ROOT.TH1D(self.measured)
self.hfake.Add(self.hmatrix.ProjectionY(), -1.)
self.gentruth = ROOT.TH1D(self.htruth)
self.genmeasured = ROOT.TH1D(self.htruth)
maxima = [
self.hmiss.GetMaximum(),
self.hfake.GetMaximum(),
self.matrix.GetMaximum()
]
maxima.sort()
self.maxval = maxima[2]
newfile = rootpy.io.root_open("output_prova2.root", 'recreate')
self.hmiss.Write()
self.hfake.Write()
self.gentruth.Write()
self.genmeasured.Write()
newfile.Close()
self.gentruth.Reset()
self.genmeasured.Reset()
nev = numpy.random.poisson(numevents)
print "nev =", nev
nbinsx = self.hmiss.GetNbinsX()
nbinsy = self.hfake.GetNbinsX()
print "nbinsx, nbinsy =", nbinsx, nbinsy
while nev != 0:
#if nev%1000 == 0:
# print "nev =",nev
binx = numpy.random.random_integers(0, nbinsx)
biny = numpy.random.random_integers(0, nbinsy)
test = numpy.random.uniform(0, self.maxval)
if binx > 0 and biny > 0:
dest = self.matrix.GetBinContent(binx, biny)
if test < dest:
nev = nev - 1
self.gentruth.SetBinContent(
binx,
self.gentruth.GetBinContent(binx) + 1)
self.genmeasured.SetBinContent(
biny,
self.genmeasured.GetBinContent(biny) + 1)
elif binx == 0:
dest = self.hfake.GetBinContent(biny)
if test < dest:
nev = nev - 1
self.genmeasured.SetBinContent(
biny,
self.genmeasured.GetBinContent(biny) + 1)
elif biny == 0:
dest = self.hmiss.GetBinContent(binx)
if test < dest:
self.gentruth.SetBinContent(
binx,
self.gentruth.GetBinContent(binx) + 1)
for i in range(1, nbinsx + 1):
self.gentruth.SetBinError(
i, math.sqrt(self.gentruth.GetBinContent(i)))
for i in range(1, nbinsy + 1):
self.genmeasured.SetBinError(
i, math.sqrt(self.genmeasured.GetBinContent(i)))