Samplers

class ionworkspipeline.samplers.Sampler(**kwargs: Any)

Base class for all monte-carlo style samplers.

Samplers explore the parameter space to identify posterior distributions, whereas optimizers provide a point-based solution.

Parameters

**kwargs

Arguments passed to the underlying sampling algorithm.

Extends: ionworkspipeline.data_fits.parameter_estimators.parameter_estimator.ParameterEstimator

run(x0: ndarray) → SamplerResult

Run the sampling algorithm to explore the parameter space.

Parameters

x0

Initial point to start the Markov chain or sampling process.

Returns

SamplerResult

The result of the sampling, containing the chain of samples and their associated costs/likelihoods.

class ionworkspipeline.samplers.Pints(method: str = 'DramACMC', log_to_screen: bool = False, max_iterations: int = 1000, burnin_iterations: int | None = None, initial_phase_iterations: int | None = None, **kwargs)

Sampler using the Pints library: Probabilistic Inference for Bayesian Models.

Wraps Pints’ MCMCController class for MCMC sampling.

Parameters

methodstr, optional

Sampling method. Default is “DramACMC”. Must be one of: “DramACMC”, “HamiltonianMCMC”, “HaarioBardenetACMC”, “MALAMCMC”, “MetropolisRandomWalkMCMC”, “MonomialGammaHamiltonianMCMC”, “NoUTurnMCMC”, “PopulationMCMC”, “RelativisticMCMC”, “SliceDoublingMCMC”, “SliceRankShrinkingMCMC”, or “SliceStepoutMCMC”.

log_to_screenbool, optional

Whether to print information at runtime. Default is False.

max_iterationsint, optional

Maximum number of iterations. Default is 1000.

burnin_iterationsint, optional

Number of initial iterations to discard. Default is 10% of max_iterations.

initial_phase_iterationsint, optional

Number of iterations in initial phase. Only used for methods that need an initial phase. Default is equal to burnin_iterations.

**kwargs

Additional parameters passed to the pints MCMC sampler. See pints documentation for details.

Notes

  • The log PDF values are cached internally to work around a pints limitation.

  • For methods that need an initial phase, initial_phase_iterations must not exceed burnin_iterations, which in turn must not exceed max_iterations.

Extends: ionworkspipeline.data_fits.parameter_estimators.samplers.sampler.Sampler

run(x0)

Sample the objective function.

Parameters

x0array_like

Initial parameter values to start sampling from.

Returns

SamplerResult:

The result of the sampling, containing: - samples: Array of shape (n_iterations, n_parameters) containing all samples - cost: Array of shape (n_iterations,) containing log probability densities - x: The parameter values with highest log probability - iterations: Number of iterations performed

set_objective(objective)

Set the objective function to be minimized.

class ionworkspipeline.samplers.GridSearch(npts: int = 10)

Grid search sampler - explores parameter space on a regular grid.

Evaluates the objective at all combinations of grid points across dimensions.

Parameters

nptsint, optional

Number of points to use in each dimension. Default is 10.

Extends: ionworkspipeline.data_fits.parameter_estimators.samplers.sampler.Sampler

run(x0: ndarray) → SamplerResult

Run the sampling algorithm to explore the parameter space.

Parameters

x0

Initial point to start the Markov chain or sampling process.

Returns

SamplerResult

The result of the sampling, containing the chain of samples and their associated costs/likelihoods.

class ionworkspipeline.samplers.PointEstimate

Point estimate sampler - returns the initial guess as a single sample.

Useful for evaluating a single parameter set within a sampling framework.

Extends: ionworkspipeline.data_fits.parameter_estimators.samplers.sampler.Sampler

run(x0: ndarray) → SamplerResult

Run the sampling algorithm to explore the parameter space.

Parameters

x0

Initial point to start the Markov chain or sampling process.

Returns

SamplerResult

The result of the sampling, containing the chain of samples and their associated costs/likelihoods.

class ionworkspipeline.samplers.Dummy(*args, **kwargs)

Alias for PointEstimate sampler.

Extends: ionworkspipeline.data_fits.parameter_estimators.samplers.point_estimate_sampler.PointEstimate