'HLT2Topo2BodyTOS',
'HLT2Topo3BodyTOS',
'HLT2Topo4BodyTOS'
]
cut = '(%s > 0) && (%s > 0 || %s > 0 || %s > 0) ' % (
tlist[0], tlist[1], tlist[2], tlist[3])
cut += '&& BDTG > 0.5 '
# Get dataset: DsPi and DsK
time.setBins(150)
dsetlist = []
weights = []
for mode, pidcut in [('DsPi', 'PIDK < 0'), ('DsK', 'PIDK > 10')]:
# Get tree
rfile = get_file('data/smalltree-really-new-MC-pre-PID-%s.root' % mode,
'read')
ftree = get_object('ftree', rfile)
print 'Reading from file: %s' % rfile.GetName()
cutstr = cut + ' && ' + pidcut
if pidcut.find(' -5') > 0:
wt = 'wt0'
scale = 1
elif pidcut.find(' 0') > 0:
wt = 'wt1'
scale = 1
elif pidcut.find(' 5') > 0:
wt = 'wt2'
scale = 1
elif pidcut.find(' 10') > 0:
tlist = [
'HLT1TrackAllL0TOS', 'HLT2Topo2BodyTOS', 'HLT2Topo3BodyTOS',
'HLT2Topo4BodyTOS'
]
cut = '(%s > 0) && (%s > 0 || %s > 0 || %s > 0) ' % (tlist[0], tlist[1],
tlist[2], tlist[3])
cut += '&& BDTG > 0.5 '
# Get dataset: DsPi and DsK
time.setBins(150)
dsetlist = []
weights = []
for mode, pidcut in [('DsPi', 'PIDK < 0'), ('DsK', 'PIDK > 10')]:
# Get tree
rfile = get_file('data/smalltree-really-new-MC-pre-PID-%s.root' % mode,
'read')
ftree = get_object('ftree', rfile)
print 'Reading from file: %s' % rfile.GetName()
cutstr = cut + ' && ' + pidcut
if pidcut.find(' -5') > 0:
wt = 'wt0'
scale = 1
elif pidcut.find(' 0') > 0:
wt = 'wt1'
scale = 1
elif pidcut.find(' 5') > 0:
wt = 'wt2'
scale = 1
elif pidcut.find(' 10') > 0:
axes.set_xlim(tfloor, tceil)
axes.set_ylim(0.5, 1.5)
# Dump ratio histogram to ROOT file
xbins = numpy.linspace(tfloor, tceil, nbins + 1)
haccratio = TH1D('haccratio_%s' % accfntype1, 'Acceptance ratio %s' % accfntype1,
nbins, xbins)
haccratio.SetXTitle('B decay time (ps)')
haccratio.SetYTitle('%s/%s acceptance ratio mean' % (mode1, mode2))
for i, mean in enumerate(means):
if i < nbins:
haccratio.SetBinContent(i+1, mean)
haccratio.SetBinError(i+1, varis[i])
rfile1 = get_file(fname1, 'read')
hist1 = get_object('hdataset_%s' % mode1, rfile1)
rfile2 = get_file(fname2, 'read')
hist2 = get_object('hdataset_%s' % mode2, rfile2)
hratio = hist1.Clone('hdataset_ratio')
hratio.Divide(hist2)
if doPrint:
plt.savefig('plots/acceptance-ratio-%s-mean-rms.png' % accfntype1)
plt.savefig('plots/acceptance-ratio-%s-mean-rms.pdf' % accfntype1)
print 'Printed: plots/acceptance-ratio-%s-mean-rms.{png,pdf}' % accfntype1
# save acceptance ratio as ROOT histogram
rfile = TFile('data/acceptance-ratio-hists-%s.root' % constoffset1, 'update')
axes.set_ylabel("%s/%s acceptance ratio mean\n(variance shown as error bars)" % (mode1, mode2))
axes.set_xlim(tfloor, tceil)
axes.set_ylim(0.5, 1.5)
# Dump ratio histogram to ROOT file
xbins = numpy.linspace(tfloor, tceil, nbins + 1)
haccratio = TH1D("haccratio_%s" % accfntype1, "Acceptance ratio %s" % accfntype1, nbins, xbins)
haccratio.SetXTitle("B decay time (ps)")
haccratio.SetYTitle("%s/%s acceptance ratio mean" % (mode1, mode2))
for i, mean in enumerate(means):
if i < nbins:
haccratio.SetBinContent(i + 1, mean)
haccratio.SetBinError(i + 1, varis[i])
rfile1 = get_file(fname1, "read")
hist1 = get_object("hdataset_%s" % mode1, rfile1)
rfile2 = get_file(fname2, "read")
hist2 = get_object("hdataset_%s" % mode2, rfile2)
hratio = hist1.Clone("hdataset_ratio")
hratio.Divide(hist2)
if doPrint:
plt.savefig("plots/acceptance-ratio-%s-mean-rms.png" % accfntype1)
plt.savefig("plots/acceptance-ratio-%s-mean-rms.pdf" % accfntype1)
print "Printed: plots/acceptance-ratio-%s-mean-rms.{png,pdf}" % accfntype1
# save acceptance ratio as ROOT histogram
rfile = TFile("data/acceptance-ratio-hists-%s.root" % constoffset1, "update")
axes.set_xlim(tfloor, tceil)
axes.set_ylim(0.5, 1.5)
# Dump ratio histogram to ROOT file
xbins = numpy.linspace(tfloor, tceil, nbins + 1)
haccratio = TH1D('haccratio_%s' % accfntype1, 'Acceptance ratio %s' % accfntype1,
nbins, xbins)
haccratio.SetXTitle('B decay time (ps)')
haccratio.SetYTitle('%s/%s acceptance ratio mean' % (mode1, mode2))
for i, mean in enumerate(means):
if i < nbins:
haccratio.SetBinContent(i+1, mean)
haccratio.SetBinError(i+1, varis[i])
rfile1 = get_file(fname1, 'read')
hist1 = get_object('hdataset_%s' % mode1, rfile1)
rfile2 = get_file(fname2, 'read')
hist2 = get_object('hdataset_%s' % mode2, rfile2)
hratio = hist1.Clone('hdataset_ratio')
hratio.Divide(hist2)
if doPrint:
plt.savefig('plots/acceptance-ratio-%s-mean-rms.png' % accfntype1)
plt.savefig('plots/acceptance-ratio-%s-mean-rms.pdf' % accfntype1)
print 'Printed: plots/acceptance-ratio-%s-mean-rms.{png,pdf}' % accfntype1
# save acceptance ratio as ROOT histogram
rfile = TFile('data/acceptance-ratio-hists-%s.root' % constoffset1, 'update')
