threeML.bayesian.dynesty_sampler module

class threeML.bayesian.dynesty_sampler.DynestyDynamicSampler(likelihood_model=None, data_list=None, **kwargs)

Bases: UnitCubeSampler

sample(quiet=False)

sample using the UltraNest numerical integration method :rtype:

Returns:

setup(nlive_init=500, maxiter_init=None, maxcall_init=None, dlogz_init=0.01, logl_max_init=inf, n_effective_init=inf, nlive_batch=500, wt_function=None, wt_kwargs=None, maxiter_batch=None, maxcall_batch=None, maxiter=None, maxcall=None, maxbatch=None, n_effective=inf, stop_function=None, stop_kwargs=None, use_stop=True, save_bounds=True, print_func=None, live_points=None, bound='multi', sample='auto', periodic=None, reflective=None, update_interval=None, first_update=None, npdim=None, rstate=None, use_pool=None, logl_args=None, logl_kwargs=None, ptform_args=None, ptform_kwargs=None, gradient=None, grad_args=None, grad_kwargs=None, compute_jac=False, enlarge=None, bootstrap=0, walks=25, facc=0.5, slices=5, fmove=0.9, max_move=100, update_func=None, **kwargs)

TODO describe function

Parameters:

• nlive_init

• maxiter_init

• maxcall_init

• dlogz_init

• logl_max_init

• n_effective_init

• nlive_batch

• wt_function

• wt_kwargs

• maxiter_batch

• maxcall_batch

• maxiter

• maxcall

• maxbatch

• n_effective

• stop_function

• stop_kwargs

• use_stop

• save_bounds

• print_func

• live_points

• bound

• sample

• periodic

• reflective

• update_interval

• first_update

• npdim

• rstate

• use_pool

• logl_args

• logl_kwargs

• ptform_args

• ptform_kwargs

• gradient

• grad_args

• grad_kwargs

• compute_jac

• enlarge

• bootstrap

• vol_dec

• vol_check

• walks

• facc

• slices

• fmove

• max_move

• update_func

Returns:

class threeML.bayesian.dynesty_sampler.DynestyNestedSampler(likelihood_model=None, data_list=None, **kwargs)

Bases: UnitCubeSampler

sample(quiet=False)

sample using the UltraNest numerical integration method :rtype:

Returns:

setup(n_live_points=400, maxiter=None, maxcall=None, dlogz=None, logl_max=inf, n_effective=None, add_live=True, print_func=None, save_bounds=True, bound='multi', sample='auto', periodic=None, reflective=None, update_interval=None, first_update=None, npdim=None, rstate=None, use_pool=None, live_points=None, logl_args=None, logl_kwargs=None, ptform_args=None, ptform_kwargs=None, gradient=None, grad_args=None, grad_kwargs=None, compute_jac=False, enlarge=None, bootstrap=0, walks=25, facc=0.5, slices=5, fmove=0.9, max_move=100, update_func=None, **kwargs)

TODO describe function

Parameters:

• n_live_points

• maxiter

• maxcall

• dlogz

• logl_max

• n_effective

• add_live

• print_func

• save_bounds

• bound

• sample

• periodic

• reflective

• update_interval

• first_update

• npdim

• rstate

• use_pool

• live_points

• logl_args

• logl_kwargs

• ptform_args

• ptform_kwargs

• gradient

• grad_args

• grad_kwargs

• compute_jac

• enlarge

• bootstrap

• vol_dec

• vol_check

• walks

• facc

• slices

• fmove

• max_move

• update_func

Returns:

class threeML.bayesian.dynesty_sampler.DynestyPool(dview)

Bases: object

A simple wrapper for dview.

map(function, tasks)