pmrf.distributions.maf

Functions

get_adapter(backend)

Classes

MAFDistribution(maf_or_path[, backend, ...])

A generic NumPyro-compatible distribution wrapper for MAF-based models.

pmrf.distributions.maf.get_adapter(backend)[source]

class pmrf.distributions.maf.MAFDistribution(maf_or_path, backend='margarine_maf', validate_args=None)[source]

Bases: Distribution

A generic NumPyro-compatible distribution wrapper for MAF-based models. The actual implementation is delegated to a backend adapter.

support = RealVector(Real(), 1)

has_rsample = False

save(path)[source]

classmethod load(path, backend='margarine_maf', validate_args=None)[source]: Load a MAFDistribution from a file using the specified backend.

classmethod generate(data, weights=None, backend='margarine_maf', validate_args=None, **kwargs)[source]

sample(key, sample_shape=())[source]

Returns a sample from the distribution having shape given by sample_shape + batch_shape + event_shape. Note that when sample_shape is non-empty, leading dimensions (of size sample_shape) of the returned sample will be filled with iid draws from the distribution instance.

Parameters:

key (jax.random.PRNGKey) – the rng_key key to be used for the distribution.
sample_shape (tuple) – the sample shape for the distribution.

Returns:

an array of shape sample_shape + batch_shape + event_shape

Return type:

numpy.ndarray

log_prob(value)[source]

Evaluates the log probability density for a batch of samples given by value.

Parameters:: value – A batch of samples from the distribution.
Returns:: an array with shape value.shape[:-self.event_shape]
Return type:: numpy.ndarray

icdf(u)[source]

The inverse cumulative distribution function of this distribution.

Parameters:: q – quantile values, should belong to [0, 1].
Returns:: the samples whose cdf values equals to q.

property min

property max