def plotPulls(optunf="Bayes",
ntest=10,
leff=True,
loufl=False,
optfun="exp",
opttfun="",
gmean=-1.0,
nrebin=4):
if opttfun == "":
opttfun = optfun
if optfun == "blobel":
gmean = 0.0
funttxt, funtxt = funtxts(opttfun, optfun, leff, loufl)
global histos, canv, canv2
histos = []
canv = TCanvas("canv", "thruth vs reco pulls", 600, 800)
canv.Divide(1, 3)
canv2 = TCanvas("canv2", "P(chi^2)", 600, 800)
canv2.Divide(2, 3)
if optunf == "BasisSplines":
bininfo = BinInfo(nrebin)
unfoldtester = UnfoldTester(optunf, nrebin)
else:
bininfo = BinInfo()
unfoldtester = UnfoldTester(optunf)
trainer = Trainer(bininfo, opttfun, optfun)
tester = Tester(bininfo, optfun)
hbininfo = bininfo.create(optfun)
dx = hbininfo["mhi"]
for sigma, ipad in [[0.01 * dx, 1], [0.03 * dx, 2], [0.1 * dx, 3]]:
txt = optunf + ", smear mu, s.d.= " + str(gmean) + ", " + str(
sigma) + ", train: " + funttxt + ", test: " + funtxt + ", " + str(
ntest) + " tests"
hPulls = TProfile("pulls", txt, hbininfo["tbins"], hbininfo["tlo"],
hbininfo["thi"])
hPulls.SetErrorOption("s")
hPulls.SetYTitle("Thruth reco pull")
histos.append(hPulls)
hChisq = TH1D("chisq", "P(chi^2) rec " + txt, 10, 0.0, 1.0)
hChisqm = TH1D("chisqm", "P(chi^2) mea " + txt, 10, 0.0, 1.0)
histos.append(hChisq)
histos.append(hChisqm)
measurement = createMeasurement(gmean, sigma, leff, optfun)
response = trainer.train(measurement, loufl=loufl)
for itest in range(ntest):
print "Test", itest
unfold, hTrue, hMeas = unfoldtester.rununfoldtest(
tester, measurement, response)
unfold.PrintTable(cout, hTrue, 2)
hReco = unfold.Hreco(2)
nbin = hReco.GetNbinsX()
if hbininfo["nrebin"] > 1:
hTrue = hTrue.Rebin(nrebin)
for ibin in range(nbin + 1):
truevalue = hTrue.GetBinContent(ibin)
recvalue = hReco.GetBinContent(ibin)
error = hReco.GetBinError(ibin)
if error > 0.0:
pull = (recvalue - truevalue) / error
hPulls.Fill(hReco.GetBinCenter(ibin), pull)
chisq = unfold.Chi2(hTrue, 2)
hChisq.Fill(TMath.Prob(chisq, hTrue.GetNbinsX()))
chisqm = unfold.Chi2measured()
pchisqm = TMath.Prob(chisqm, hMeas.GetNbinsX() - hReco.GetNbinsX())
print "Chisq measured=", chisqm, "P(chi^2)=", pchisqm
hChisqm.Fill(pchisqm)
canv.cd(ipad)
gStyle.SetErrorX(0)
hPulls.SetMinimum(-3.0)
hPulls.SetMaximum(3.0)
hPulls.SetMarkerSize(1.0)
hPulls.SetMarkerStyle(20)
hPulls.SetStats(False)
hPulls.Draw()
canv2.cd(ipad * 2 - 1)
hChisq.Draw()
canv2.cd(ipad * 2)
hChisqm.Draw()
fname = "RooUnfoldTestPulls_" + optunf + "_" + opttfun + "_" + optfun
if loufl:
fname += "_oufl"
canv.Print(fname + ".pdf")
fname = "RooUnfoldTestChisq_" + optunf + "_" + opttfun + "_" + optfun
if loufl:
fname += "_oufl"
canv2.Print(fname + ".pdf")
return
for ievent in range(NEntries):
if ievent % 100 == 0:
print("Processed %d of %d events..." % (ievent, NEntries))
ntuple.GetEntry(ievent)
n_weight = ntuple.__getattr__('weight')
n_ptPruned = ntuple.__getattr__('ptPruned')
if (170 < n_ptPruned < 1000):
x.append(n_ptPruned)
y.append(n_weight)
print(n_weight)
hprof2d.Fill(n_ptPruned, n_weight)
# hprof2d.LabelsOption("h","pT")
hprof2d.SetMinimum(-0.2)
hprof2d.SetMaximum(0.3)
hprof2d.Draw()
c.SaveAs("old2dhist.png")
# # H = verification
# nbins = 100
# # xedges = 101
# # yedges =4
# H, xedges, yedges = np.histogram2d(x,y,bins=nbins)
#
# # print (xedges)
# print (yedges)
# # H= H.T
# # print (H)