def __init__(self, statfunc=None, hyperpars={}, pars={}, name='prior'): # Posterior hyper-parameters self.hyperpars = [] for key in hyperpars.keys(): val = hyperpars[key] param = Parameter(name, key, val, alwaysfrozen=True) self.__dict__[key] = param self.hyperpars.append(param) # References to parameters in source model self.pars = [] for key in pars.keys(): self.__dict__[key] = pars[key] self.pars.append(pars[key]) self._statfuncset = False self.statfunc = (lambda x: None) if statfunc is not None: self.statfunc = statfunc self._statfuncset = True Likelihood.__init__(self, name)
def __init__(self, gp_stat): statname = 'GPStat' self.gp_stat = gp_stat Likelihood.__init__(self, statname)
def __init__(self, name='fermi'): Likelihood.__init__(self, name)
def __init__(self, fit): sherpa_name = 'sherpa_stat' self.fit = fit Likelihood.__init__(self, sherpa_name)