def fitTo(self, dataset, silent=True, refit=2, args=(), **kwargs):
"""Fit it!
>>> dataset = ...
>>> eff = Efficiency1D( ... )
>>> result = eff.fitTo ( dataset )
"""
vargs = [] ## i for i in args ]
vargs.append(ROOT.RooFit.ConditionalObservables(self.vars))
vargs = tuple(vargs)
##
draw = kwargs.pop('draw', False)
from ostap.logger.utils import roo_silent
with roo_silent(silent):
result, frame = self.pdf_fit.fitTo(dataset,
draw=False,
nbins=100,
silent=silent,
refit=refit,
args=vargs,
**kwargs)
if draw: self.draw(dataset)
self.__fit_result = result
return result
def __init__(self,
histo,
xaxis=None,
yaxis=None,
density=True,
silent=False):
#
assert isinstance(histo, ROOT.TH2), "``histo'' is not ROOT.TH2"
self.__histo = histo
## use mass-variable
#
name = histo.GetName()
if not xaxis: xaxis = histo.xminmax()
if not yaxis: yaxis = histo.yminmax()
self.__xaxis = self.make_var(xaxis, 'x_%s' % name, 'x-axis(%s)' % name,
xaxis, *(histo.xminmax()))
self.__yaxis = self.make_var(yaxis, 'y_%s' % name, 'y-axis(%s)' % name,
yaxis, *(histo.yminmax()))
self.__density = True if density else False
self.__silent = silent
with roo_silent(silent):
self.__vlst = ROOT.RooArgList(self.xaxis, self.yaxis)
self.__vimp = ROOT.RooFit.Import(histo, density)
self.__dset = ROOT.RooDataHist(
rootID('hds_'),
"Data set for histogram '%s'" % histo.GetTitle(), self.__vlst,
self.__vimp)
