lib.parameter.Prior

class lib.parameter.Prior(dist='uniform', limits=None, **kwargs)

Bases: lib.utils.BaseClass

Class that describes a 1D prior distribution.

Parameters

• dist (string) – Distribution name.

• rv (scipy.stats.rv_continuous) – Random variate.

• attrs (dict) – Arguments used to initialize rv.

Initialize Prior.

Parameters

• dist (string) – Distribution name in scipy.stats

• limits (tuple, default=None) – Limits. See set_limits().

• kwargs (dict) – Arguments for scipy.stats.dist(), typically loc, scale (mean and standard deviation in case of a normal distribution 'dist' == 'norm')

Methods

copy	Return shallow copy of self.
deepcopy
from_state	Instantiate and initalize class with state dictionary.
is_limited	Whether distribution has (at least one) finite limit.
is_mpi_broadcast
is_mpi_gathered
is_mpi_root
is_mpi_scattered
is_proper	Whether distribution is proper, i.e. has finite integral.
isin	Whether x is within prior, i.e. within limits - strictly positive probability.
load	Load class in numpy binary format from disk.
load_auto	If different formats are possible, this method should between them based on file name extension.
log_critical
log_debug
log_error
log_info
log_warning
sample	Draw size samples from prior.
save	Save class to disk.
save_auto	If different formats are possible, this method should between them based on file name extension.
set_limits	Set limits.

Attributes

logger
mpiattrs	MPI attributes
mpicomm
mpiroot
mpistate

__call__(x)

Return probability density at x.

copy()

Return shallow copy of self.

classmethod from_state(state, mpiroot=0, mpicomm=None)

Instantiate and initalize class with state dictionary.

is_limited()

Whether distribution has (at least one) finite limit.

is_proper()

Whether distribution is proper, i.e. has finite integral.

isin(x)

Whether x is within prior, i.e. within limits - strictly positive probability.

classmethod load(filename, mpiroot=0, mpicomm=None)

Load class in numpy binary format from disk. If the loaded state contains __class__ and that exists in cls._registry, return instance of cls._registry[__class__] (instead of cls).

load_auto(*args, **kwargs)

If different formats are possible, this method should between them based on file name extension.

property mpiattrs

MPI attributes

sample(size=None, random_state=None)

Draw size samples from prior. Possible only if prior is proper.

Parameters

• size (int, default=None) – Number of samples to draw. If None, return one sample (float).

• random_state (int, numpy.random.Generator, numpy.random.RandomState, default=None) – If integer, a new numpy.random.RandomState instance is used, seeded with random_state. If random_state is a numpy.random.Generator or numpy.random.RandomState instance then that instance is used. If None, the numpy.random.RandomState singleton is used.

Returns

samples – Samples drawn from prior.

Return type

float, array

save(filename)

Save class to disk.

save_auto(*args, **kwargs)

If different formats are possible, this method should between them based on file name extension.

set_limits(limits=None)

Set limits.

Parameters

limits (tuple, default=None) – Tuple corresponding to lower, upper limits. None means \(-\infty\) for lower bound and \(\infty\) for upper bound. Defaults to \(-\infty,\infty\).