pybop.samplers.chain_processor#

Classes#

`ChainProcessor`	Base class for chain processing.
`MultiChainProcessor`	Processor for simultaneous chains.
`SingleChainProcessor`	Processor for individual chains.

class pybop.samplers.chain_processor.ChainProcessor(mcmc_sampler)[source]#

Base class for chain processing.

This clas architecture implements a strategy-pattern for selection between multi-chain and single-chain samplers as implemented in child classes.

Parameters:: mcmc_sampler (pybop.BasePintsSampler) – A BasePintsSampler object.

abstractmethod _extract_log_pdf(fy_value, chain_idx)[source]#: Extract log-pdf for an accepted sample.

get_evaluation_metrics(chain_idx)[source]#: Get evaluation metrics for the current sample.

store_samples(values, chain_idx)[source]#: Store samples based on memory configuration. Samples shape: [n_chains, n_iterations, n_parameters]

update_accepted_sample(chain_idx, y, fy_value)[source]#: Update stored values for an accepted sample.

class pybop.samplers.chain_processor.MultiChainProcessor(mcmc_sampler)[source]#

Processor for simultaneous chains.

_extract_log_pdf(fy_value, chain_idx)[source]#: Extract log PDF value for multi-chain mode.

class pybop.samplers.chain_processor.SingleChainProcessor(mcmc_sampler)[source]#

Processor for individual chains.

_extract_log_pdf(fy_value, chain_idx)[source]#: Extract log PDF value for single chain mode.