def draw(ws, res, eff, var, cat, xtitle, trig, nfitparams, xlow=0, xup=400, ymax=1.1, oldres=[]):
# Set variable-width binning
tmpbins = [x * 0.05 for x in range(0, 20)]+[1,10,20,30,40,50,60,70,80,90,100,110,120,140,160,180,200,220,240,280,320,360,400,480,600,750,1000]
if kTrig == "PFMET100HT400" or kTrig == "PFMET80HT400" or kTrig == "PFMET80CJ30x2CSV07" or kTrig == "PFMET100CJ80CSV07": # low stat
tmpbins = [0,10,20,30,40,50,60,70,80,90,100,110,120,140,160,200,240,320,400,480,600,750,1000]
tmpbins2 = [xlow] + [x for x in tmpbins if (x > xlow and x < xup)] + [xup]
bins = RooBinning(len(tmpbins2)-1, numpy.array(tmpbins2, dtype=float))
kColor = 4 # kBlue
kColorErr = 432 # kCyan
new = len(oldres)>0
if new:
kColorOld = kColor
kColorErrOld = kColorErr
kColor = 618 # kMagenta+2
kColorErr = 609 # kMagenta-7
frame1 = ws.var(var).frame(RooFit.Bins(40), RooFit.Title("Data (all, accepted)"))
ds.plotOn(frame1)
ds.plotOn(frame1, RooFit.Cut("%s==%s::accept" % (cat,cat)), RooFit.MarkerColor(kColor), RooFit.LineColor(kColor))
frame2 = ws.var(var).frame(RooFit.Title("; %s; HLT efficiency" % xtitle))
if new:
ws.saveSnapshot("2015alpha", "fit0,fit1,fit2")
ws.loadSnapshot("2012D")
ws.function(eff).plotOn(frame2, RooFit.VisualizeError(oldres[0]), RooFit.FillColor(kColorErrOld))
ws.function(eff).plotOn(frame2, RooFit.LineColor(kColorOld))
ws.loadSnapshot("2015alpha")
ws.function(eff).plotOn(frame2, RooFit.VisualizeError(res), RooFit.FillColor(kColorErr))
ws.function(eff).plotOn(frame2, RooFit.LineColor(kColor))
ds.plotOn(frame2, RooFit.Binning(bins), RooFit.Efficiency(ws.cat(cat)))
nchisq = frame2.chiSquare(nfitparams)
ndof = bins.numBins()-nfitparams
chisq = nchisq * ndof
gPad.SetLeftMargin(0.15); frame2.GetYaxis().SetTitleOffset(1.25); frame2.GetYaxis().SetRangeUser(0,ymax)
#frame1.Draw()
frame2.Draw()
CMS_label()
latex.SetTextSize(0.044)
latex.DrawLatex(0.60, 0.30, "#chi^{2}/ndof = %4.2f/%.0f" % (chisq,ndof))
text = ["** "+trig+" **"]
text.append("chi2/ndof %6.2f = %4.2f/%.0f" % (nchisq, chisq, ndof))
print "chi2/ndof %6.2f = %4.2f/%.0f" % (nchisq, chisq, ndof)
latex.SetTextSize(0.026)
latex.DrawLatex(0.60, 0.26, trig)
for i in xrange(3):
v = ws.var("fit%i" % i)
if v.getVal() > 1:
text.append("p_%i %6.2f +/- %3.2f" % (i, v.getVal(), v.getError()))
latex.DrawLatex(0.60, 0.26-(i+1)*0.03, "p_{%i} %6.2f +/- %3.2f" % (i, v.getVal(), v.getError()))
else:
text.append("p_%i %6.3f +/- %4.3f" % (i, v.getVal(), v.getError()))
latex.DrawLatex(0.60, 0.26-(i+1)*0.03, "p_{%i} %6.3f +/- %4.3f" % (i, v.getVal(), v.getError()))
line.DrawLine(xlow, 1, xup, 1)
text.append("")
return text
class Binned_MassPdf( MassPdf ) :
def __init__( self, Name, Mass, **kwargs ) :
self._name = Name
self._mass = Mass
# get binning
self._bins = kwargs.pop( 'Binning', None )
if not self._bins :
# create binning
from array import array
binBounds = kwargs.pop( 'BinBoundaries', [ self._mass.getMin(), self._mass.getMax() ] )
self._binBounds = array( 'd', binBounds )
self._numBins = len(binBounds) - 1
from ROOT import RooBinning
self._bins = RooBinning( self._numBins, self._binBounds, self._name + '_binning' )
self._mass.setBinning( self._bins, self._name + '_binning' )
self._numBins = self._bins.numBins()
# determine number of events in each bin
self._data = kwargs.pop( 'Data', None )
if self._data :
assert self._mass._var in self._data.get(0),\
'Binned_MassPdf.__init__(): %s is not and observable in the provided data set' % self._mass.GetName()
self._numEvents = self._data.sumEntries()
self._numEventsBins = self._numBins * [ 0. ]
for obsSet in self._data :
bin = self._bins.binNumber( obsSet.getRealValue( self._mass.GetName() ) )
self._numEventsBins[bin] += self._data.weight()
# create bin coefficients
self._coefs = [ ]
for bin in range( 1, self._numBins ) :
self._parseArg( '%s_coef%d' % ( self._name, bin ), kwargs
, Title = '%s bin coefficient %d' % ( self._name, bin )
, Value = self._numEventsBins[bin] / self._numEvents if self._data else 1. / self._numBins
, MinMax = ( 0., 1. )
, ContainerList = self._coefs
)
# create a BinnedPdf
from P2VV.RooFitWrappers import BinnedPdf
pdf = BinnedPdf( Name = self._name
, Observable = self._mass
, Binning = self._bins
, Coefficients = self._coefs
, BinIntegralCoefs = True
)
# initialize
MassPdf.__init__( self, pdf = pdf )
self._check_extraneous_kw( kwargs )
