def get_likelihood_parameters(self):
"""Tell likelihood about the linear power likelihood parameters"""
params = []
params.append(
likelihood_parameter.LikelihoodParameter(
name='g_star',
min_value=0.95,
max_value=0.99,
value=self.linP_params['g_star']))
params.append(
likelihood_parameter.LikelihoodParameter(
name='f_star',
min_value=0.95,
max_value=0.99,
value=self.linP_params['f_star']))
params.append(
likelihood_parameter.LikelihoodParameter(
name='Delta2_star',
min_value=0.25,
max_value=0.4,
value=self.linP_params['Delta2_star']))
params.append(
likelihood_parameter.LikelihoodParameter(
name='n_star',
min_value=-2.35,
max_value=-2.25,
value=self.linP_params['n_star']))
params.append(
likelihood_parameter.LikelihoodParameter(
name='alpha_star',
min_value=-0.27,
max_value=-0.16,
value=self.linP_params['alpha_star']))
return params
def set_sigT_kms_parameters(self):
"""Setup sigT_kms likelihood parameters for thermal model"""
self.sigT_kms_params=[]
Npar=len(self.ln_sigT_kms_coeff)
for i in range(Npar):
name='ln_sigT_kms_'+str(i)
if i==0:
xmin=-0.2
xmax=0.2
else:
xmin=-0.2
xmax=0.2
value=self.ln_sigT_kms_coeff[i]
par = likelihood_parameter.LikelihoodParameter(name=name,
value=value,min_value=xmin,max_value=xmax)
self.sigT_kms_params.append(par)
return
def set_gamma_parameters(self):
"""Setup gamma likelihood parameters for thermal model"""
self.gamma_params=[]
Npar=len(self.ln_gamma_coeff)
for i in range(Npar):
name='ln_gamma_'+str(i)
if i==0:
xmin=-0.2
xmax=0.2
else:
xmin=-0.2
xmax=0.2
# note non-trivial order in coefficients
value=self.ln_gamma_coeff[Npar-i-1]
par = likelihood_parameter.LikelihoodParameter(name=name,
value=value,min_value=xmin,max_value=xmax)
self.gamma_params.append(par)
return
def get_likelihood_parameters(self):
""" Return a list of likelihood parameters """
## It apperas to me that the min max values here
## aren't actually used, which is what allows us to set
## custom prior volumes using Likelihood.free_param_limits
## So I will leave these for now, but this should be
## cleared up eventually.
params = []
params.append(
likelihood_parameter.LikelihoodParameter(name='ombh2',
min_value=0.019,
max_value=0.025,
value=self.cosmo.ombh2))
params.append(
likelihood_parameter.LikelihoodParameter(name='omch2',
min_value=0.10,
max_value=0.15,
value=self.cosmo.omch2))
params.append(
likelihood_parameter.LikelihoodParameter(
name='As',
min_value=1.0e-09,
max_value=3.0e-09,
value=self.cosmo.InitPower.As))
params.append(
likelihood_parameter.LikelihoodParameter(
name='ns',
min_value=0.90,
max_value=1.05,
value=self.cosmo.InitPower.ns))
params.append(
likelihood_parameter.LikelihoodParameter(name='H0',
min_value=63,
max_value=77,
value=self.cosmo.H0))
params.append(
likelihood_parameter.LikelihoodParameter(name='mnu',
min_value=0.0,
max_value=1.0,
value=camb_cosmo.get_mnu(
self.cosmo)))
return params