def get_unbound_pdf(self, name, title):
"""Get the physics PDF.
Return:
ROOT.BifurcatedCB.
"""
return load_pdf_by_name('BifurcatedCB')(
name, title, *(self.get_observables() + self.get_fit_parameters()))
def get_unbound_pdf(self, name, title):
"""Get the physics PDF.
Return:
ROOT.RooIpatia2.
"""
return load_pdf_by_name('RooIpatia2', True)(
name, title, *(self.get_observables() + self.get_fit_parameters()))
def action_BLINDRATIO(name, title, action_params, external_vars):
"""Configure a ratio between two variables.
The first is the numerator, the second the denominator. At least needs to be a shared variable,
and currently two constrained variables are not possible.
The third is a randomization string; the fourth a mean and the fifth a width.
"""
from analysis.utils.pdf import load_pdf_by_name
Ratio = load_pdf_by_name('RooRatio')
if len(action_params) != 5:
raise ValueError(
"Wrong number of arguments for BLINDRATIO -> {}".format(
action_params))
if not any(v.startswith('@') for v in action_params):
raise ValueError(
"At least one parameter of a BLINDRATIO must be a reference")
constraint = None
processed_vars = []
for variable in action_params[:2]:
if variable.startswith('@'):
processed_variable, const = external_vars[variable[1:]]
if const:
if not constraint:
constraint = const
else:
raise NotImplementedError(
"Two constrained variables in SCALE are not allowed")
elif ':' in variable:
from analysis.fit.result import FitResult
fit_name, var_name = variable.split(':')
result = FitResult.from_yaml_file(fit_name)
try:
value = result.get_fit_parameter(var_name)[0]
except KeyError:
value = result.get_const_parameter(var_name)
processed_variable = ROOT.RooFit.RooConst(value)
else:
processed_variable = ROOT.RooFit.RooConst(float(variable))
processed_vars.append(processed_variable)
parameter = Ratio(name, title, *processed_vars)
blind_str, blind_central, blind_sigma = action_params[2:]
ref_var = deepcopy(parameter)
parameter = ROOT.RooUnblindPrecision(name + "_blind", title + "_blind",
blind_str, float(blind_central),
float(blind_sigma), ref_var)
return parameter, constraint
def action_RATIO(name, title, action_params, external_vars):
"""Configure a ratio between two variables.
The first is the numerator, the second the denomiator. At least needs to be a shared variable,
and currently two constrained variables are not possible.
"""
from analysis.utils.pdf import load_pdf_by_name
Ratio = load_pdf_by_name('RooRatio')
if len(action_params) != 2:
raise ValueError(
"Wrong number of arguments for RATIO -> {}".format(action_params))
if not any(v.startswith('@') for v in action_params):
raise ValueError(
"At least one parameter of a RATIO must be a reference")
constraint = None
processed_vars = []
for variable in action_params:
if variable.startswith('@'):
processed_variable, const = external_vars[variable[1:]]
if const:
if not constraint:
constraint = const
else:
raise NotImplementedError(
"Two constrained variables in SCALE are not allowed")
elif ':' in variable:
from analysis.fit.result import FitResult
fit_name, var_name = variable.split(':')
result = FitResult.from_yaml_file(fit_name)
try:
value = result.get_fit_parameter(var_name)[0]
except KeyError:
value = result.get_const_parameter(var_name)
processed_variable = ROOT.RooFit.RooConst(value)
else:
processed_variable = ROOT.RooFit.RooConst(float(variable))
processed_vars.append(processed_variable)
parameter = Ratio(name, title, *processed_vars)
return parameter, constraint