def book(out_name, hs=[]):
bins = binning()
h = ROOT.TH1F(out_name, '', len(bins) - 1, bins)
hs.append(h)
return h
def cutplayMangle(filename):
debug = False
file = ROOT.TFile.Open(filename)
if not file.IsOpen():
raise RuntimeError('could not open %s' % filename)
norm = norm_from_file(filename)
x = file.Get('SimpleTriggerEfficiency/triggers_pass_num')
cutscans = {}
nm1 = None
# Extract from the big list of bins the numbers separately for each
# cut.
for i in xrange(1, x.GetNbinsX() + 1):
label = x.GetXaxis().GetBinLabel(i)
if label == 'nm1':
nm1 = x.GetBinContent(i), x.GetBinError(i)
continue
try:
cut, cut_val = label.split('X')
except ValueError:
print 'warning: could not parse label %s' % label
continue
if not cutscans.has_key(cut):
cutscans[cut] = []
cutscans[cut].append((cut_val, x.GetBinContent(i)))
h_intot = file.Get('SimpleTriggerEfficiency/triggers_pass_den')
ntot = h_intot.GetBinContent(1), h_intot.GetBinError(1)
file.Close()
output_fn = filename.replace('.root', '_mangled.root')
output_file = ROOT.TFile(output_fn, 'RECREATE')
sample_name = os.path.basename(filename).replace('.root', '')
try:
sample = getattr(Samples, sample_name)
except AttributeError:
sample = None
h_ntot = ROOT.TH1F('ntot', '', 1, 0, 1)
scale = ntot[0] / norm if sample is not None else 1.
h_ntot.SetBinContent(1, ntot[0] / scale)
h_ntot.SetBinError(1, ntot[1] / scale)
if nm1 is not None:
h_nm1 = ROOT.TH1F('nm1', '', 1, 0, 1)
h_nm1.SetBinContent(1, nm1[0])
h_nm1.SetBinError(1, nm1[1])
else:
raise ValueError('did not find nm1 value in input')
output_hists = []
for cut_name, scan in cutscans.iteritems():
if debug:
print 'cut: %s' % cut_name
hmin = depize(scan[0][0])
hminplus1 = depize(scan[1][0])
binwidth = hminplus1 - hmin
hmaxminus1 = depize(scan[-1][0])
hmax = hmaxminus1 + binwidth
if debug:
print 'hmin: ', hmin, ' hminplus1: ', hminplus1, ' binwidth: ', binwidth, ' hmaxminus1: ', hmaxminus1, ' hmax: ', hmax
hist = ROOT.TH1F(cut_name, '', len(scan), hmin, hmax)
output_hists.append(hist)
for cut_bin_name, nevents in scan:
bin = hist.FindBin(depize(cut_bin_name) + 0.00001)
bin_edge = hist.GetBinLowEdge(bin)
if debug:
print 'cut bin name: %s ibin: %i bin_edge: %s number of events: %f' % (
cut_bin_name, bin, bin_edge, nevents)
hist.SetBinContent(bin, nevents)
output_file.Write()
output_file.Close()
def dphi(v0, v1):
phi0 = phi(v0)
phi1 = phi(v1)
res = phi0 - phi1
while res > pi:
res -= 2*pi
while res <= -pi:
res += 2*pi
return res
h_y_x = []
for i in xrange(0,10):
h_y_x.append(ROOT.TH2F('svdist2d_%i'%i, '%i um <= svdist2d < %i um;x (cm);y (cm)'%(100*i,100*(i+1)), 200, -0.1, 0.1, 200, -0.1, 0.1))
h_dz = ROOT.TH1F('h_dz', '', 100, -0.2, 0.2)
h_dphi = ROOT.TH1F('h_phi', '', 100, -pi, pi)
h_y_x_g = [[] for x in xrange(10)]
h_dzs = [ROOT.TH1F('h_dz_%i' % x, '', 100, -0.2, 0.2) for x in xrange(10)]
h_dphis = [ROOT.TH1F('h_dphi_%i' % x, '', 100, -pi, pi) for x in xrange(10)]
for sample, ntracks01, svdist2d, v0, v1 in events:
svdist2d *= 10000
bin = int(svdist2d / 100)
#print svdist2d, bin, event[3][0]-0.244, event[3][1]-0.3928, event[4][0]-0.244, event[4][1]-0.3928
dz = v0[-1] - v1[-1]
v0 = debs(v0)
v1 = debs(v1)
dp = dphi(v0, v1)