Sampler class that performs Monte Carlo sampling, while iteratively updating the analytic distribution from which points are drawn. More...

#include <AdaptiveImportanceSampler.h>

Inheritance diagram for lsst::meas::modelfit::AdaptiveImportanceSampler:

Public Member Functions
	AdaptiveImportanceSampler (afw::table::Schema &sampleSchema, std::shared_ptr< afw::math::Random > rng, std::map< int, ImportanceSamplerControl > const &ctrls, bool doSaveIterations=false)
	Construct a new sampler.

void	run (SamplingObjective const &objective, std::shared_ptr< Mixture > proposal, afw::table::BaseCatalog &samples) const override

double	computeNormalizedPerplexity (afw::table::BaseCatalog const &samples) const

double	computeEffectiveSampleSizeFraction (afw::table::BaseCatalog const &samples) const

Detailed Description

Sampler class that performs Monte Carlo sampling, while iteratively updating the analytic distribution from which points are drawn.

Between the iterations defined in the control object, the prior is applied to the samples, and the mixture distribution is updated using expectation-maximization to match the samples.

Definition at line 70 of file AdaptiveImportanceSampler.h.

Constructor & Destructor Documentation

◆ AdaptiveImportanceSampler()

lsst::meas::modelfit::AdaptiveImportanceSampler::AdaptiveImportanceSampler	(	afw::table::Schema &	sampleSchema,
		std::shared_ptr< afw::math::Random >	rng,
		std::map< int, ImportanceSamplerControl > const &	ctrls,
		bool	doSaveIterations = false )

Construct a new sampler.

Parameters

[in,out]	sampleSchema	Schema for the catalog of samples filled by the Sampler; will be modified to include sampler-specific fields.
[in]	rng	Random number generator to use to generate samples.
[in]	ctrls	Vector of control objects that define the iterations.
[in]	doSaveIterations	Whether to save intermediate SampleSets and associated proposal distributions.

Member Function Documentation

◆ computeEffectiveSampleSizeFraction()

double lsst::meas::modelfit::AdaptiveImportanceSampler::computeEffectiveSampleSizeFraction ( afw::table::BaseCatalog const & samples ) const

◆ computeNormalizedPerplexity()

double lsst::meas::modelfit::AdaptiveImportanceSampler::computeNormalizedPerplexity ( afw::table::BaseCatalog const & samples ) const

◆ run()

void lsst::meas::modelfit::AdaptiveImportanceSampler::run	(	SamplingObjective const &	objective,
		std::shared_ptr< Mixture >	proposal,
		afw::table::BaseCatalog &	samples ) const

overridevirtual

Implements lsst::meas::modelfit::Sampler.

The documentation for this class was generated from the following file:

/j/snowflake/release/lsstsw/stack/lsst-scipipe-9.0.0/Linux64/meas_modelfit/ga5288a1d22+b66f8cf76b/include/lsst/meas/modelfit/AdaptiveImportanceSampler.h