MB_Model

class megabeast.singlepop_dust_model.MB_Model(params)[source]

Bases: object

MegaBEAST model that provides member functions to compute the likelihood and priors for a specific physical model

Methods Summary

lnlike(phi, star_lnpgriddata, beast_moddata)

Compute the log(likelihood) for the ensemble parameters

lnprior(phi)

Compute the log(priors) for the ensemble parameters

start_params()

Get the start parameters for the fit

Methods Documentation

lnlike(phi, star_lnpgriddata, beast_moddata)[source]

Compute the log(likelihood) for the ensemble parameters

Parameters:
phi: floats

ensemble parameters

star_lnpgriddata: dictonary

contains arrays of the likelihood*grid_weight values and indexs to the BEAST model grid

beast_moddata: dictonary

contains arrays of the beast parameters for the full beast physics grid

Returns:
log(likelihood): float
lnprior(phi)[source]

Compute the log(priors) for the ensemble parameters

Parameters:
phi: floats

ensemble parameters

megabeast_modeldict

MegaBEAST physical model including priors

Returns:
log(prior): floats

0 if allowed -infinite if not allowed

start_params()[source]

Get the start parameters for the fit

Returns:
values, namestuple

names give the parameters names and values for all the submodels with non-fixed priors