abc

jaxns.samplers.abc

Module Contents

class AbstractSampler[source]

Helper class that provides a standard way to create an ABC using inheritance.

abstract pre_process(state)[source]

Run this periodically on the state to produce a data pytree that can be used by the sampler, and updated quickly.

Parameters:: state (jaxns.internals.types.StaticStandardNestedSamplerState) – the current state of the sampler
Returns:: any valid pytree
Return type:: SamplerState

abstract post_process(sample_collection, sampler_state)[source]

Post process the sampler state, after the sampler has been run. Should be quick.

Parameters:

sample_collection (jaxns.internals.types.StaticStandardSampleCollection) – a sample collection post sample step
sampler_state (SamplerState) – data pytree produced by the sampler

Returns:

the updated sampler state

Return type:

SamplerState

abstract get_sample(key, log_L_constraint, sampler_state)[source]

Produce a single i.i.d. sample from the model within the log_L_constraint.

Parameters:

key (jaxns.internals.types.PRNGKey) – PRNGkey
log_L_constraint (jaxns.internals.types.FloatArray) – the constraint to sample within
sampler_state (SamplerState) – the data pytree needed and produced by the sampler

Returns:

an i.i.d. sample, and batched phantom samples

Return type:

Tuple[jaxns.internals.types.Sample, jaxns.internals.types.Sample]

abstract num_phantom()[source]

The number of phantom samples produced by the sampler.