A concrete Likelihood class that does not require its parameters and data to be in the same UnitSystem. More...

#include <UnitTransformedLikelihood.h>

Inheritance diagram for lsst::meas::modelfit::UnitTransformedLikelihood:

Public Member Functions
void	computeModelMatrix (ndarray::Array< Pixel, 2,-1 > const &modelMatrix, ndarray::Array< Scalar const, 1, 1 > const &nonlinear, bool doApplyWeights=true) const override
	Evaluate the model for the given vector of nonlinear parameters.

	UnitTransformedLikelihood (std::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed, UnitSystem const &fitSys, geom::SpherePoint const &position, std::vector< std::shared_ptr< EpochFootprint > > const &epochFootprintList, UnitTransformedLikelihoodControl const &ctrl)
	Initialize a UnitTransformedLikelihood with data from multiple exposures.

	UnitTransformedLikelihood (std::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed, UnitSystem const &fitSys, geom::SpherePoint const &position, afw::image::Exposure< Pixel > const &exposure, afw::detection::Footprint const &footprint, shapelet::MultiShapeletFunction const &psf, UnitTransformedLikelihoodControl const &ctrl)
	Initialize a UnitTransformedLikelihood with data from multiple exposures.

virtual	~UnitTransformedLikelihood ()

int	getDataDim () const
	Return the number of data points.

int	getAmplitudeDim () const
	Return the number of linear parameters (columns of the model matrix)

int	getNonlinearDim () const
	Return the number of nonlinear parameters (which parameterize the model matrix)

int	getFixedDim () const
	Return the number of fixed nonlinear parameters (set on Likelihood construction)

ndarray::Array< Scalar const, 1, 1 >	getFixed () const
	Return the vector of fixed nonlinear parameters.

ndarray::Array< Pixel const, 1, 1 >	getData () const
	Return the vector of weighted, scaled data points \(z\).

ndarray::Array< Pixel const, 1, 1 >	getUnweightedData () const
	Return the vector of unweighted data points \(y\).

ndarray::Array< Pixel const, 1, 1 >	getWeights () const
	Return the vector of weights \(w\) applied to data points and model matrix rows.

ndarray::Array< Pixel const, 1, 1 >	getVariance () const
	Return the vector of per-data-point variances.

std::shared_ptr< Model >	getModel () const
	Return an object that defines the model and its parameters.

Protected Attributes
std::shared_ptr< Model >	_model

ndarray::Array< Scalar const, 1, 1 >	_fixed

ndarray::Array< Pixel, 1, 1 >	_data

ndarray::Array< Pixel, 1, 1 >	_unweightedData

ndarray::Array< Pixel, 1, 1 >	_variance

ndarray::Array< Pixel, 1, 1 >	_weights

Detailed Description

A concrete Likelihood class that does not require its parameters and data to be in the same UnitSystem.

This is the main concrete Likelihood class using when fitting sources, even in the case where the measurement UnitSystem is the same as that of the data; we always prefer to fit in a special UnitSystem (see Units and Coordinate Systems), using this class to transform the model realization when comparing to the data. This makes forced photometry and modelfit measurements just as easy as single-frame measurements (aside from data access); one can simply initialize a UnitTransformedLikelihood with multiple exposures instead of a single exposure to fit simultaneously to multiple exposures.

Definition at line 102 of file UnitTransformedLikelihood.h.

Constructor & Destructor Documentation

◆ UnitTransformedLikelihood() [1/2]

lsst::meas::modelfit::UnitTransformedLikelihood::UnitTransformedLikelihood	(	std::shared_ptr< Model >	model,
		ndarray::Array< Scalar const, 1, 1 > const &	fixed,
		UnitSystem const &	fitSys,
		geom::SpherePoint const &	position,
		std::vector< std::shared_ptr< EpochFootprint > > const &	epochFootprintList,
		UnitTransformedLikelihoodControl const &	ctrl )

explicit

Initialize a UnitTransformedLikelihood with data from multiple exposures.

Parameters

[in]	model	Object that defines the model to fit and its parameters.
[in]	fixed	Model parameters that are held fixed.
[in]	fitSys	Geometric and photometric system to fit in
[in]	position	ICRS sky position of object being fit
[in]	epochFootprintList	List of shared pointers to EpochFootprint
[in]	ctrl	Control object with various options

◆ UnitTransformedLikelihood() [2/2]

lsst::meas::modelfit::UnitTransformedLikelihood::UnitTransformedLikelihood	(	std::shared_ptr< Model >	model,
		ndarray::Array< Scalar const, 1, 1 > const &	fixed,
		UnitSystem const &	fitSys,
		geom::SpherePoint const &	position,
		afw::image::Exposure< Pixel > const &	exposure,
		afw::detection::Footprint const &	footprint,
		shapelet::MultiShapeletFunction const &	psf,
		UnitTransformedLikelihoodControl const &	ctrl )

explicit

Initialize a UnitTransformedLikelihood with data from multiple exposures.

Parameters

[in]	model	Object that defines the model to fit and its parameters.
[in]	fixed	Model parameters that are held fixed.
[in]	fitSys	Geometric and photometric system to fit in
[in]	position	ICRS sky position of object being fit
[in]	exposure	Exposure containing the data to fit
[in]	footprint	Footprint that defines the pixels to include in the fit
[in]	psf	Shapelet approximation to the PSF
[in]	ctrl	Control object with various options

◆ ~UnitTransformedLikelihood()

virtual lsst::meas::modelfit::UnitTransformedLikelihood::~UnitTransformedLikelihood ( )

virtual

Member Function Documentation

◆ computeModelMatrix()

void lsst::meas::modelfit::UnitTransformedLikelihood::computeModelMatrix	(	ndarray::Array< Pixel, 2,-1 > const &	modelMatrix,
		ndarray::Array< Scalar const, 1, 1 > const &	nonlinear,
		bool	doApplyWeights = true ) const

overridevirtual

Evaluate the model for the given vector of nonlinear parameters.

Parameters

[out]	modelMatrix	The dataDim x amplitudeDim matrix \(B\) that expresses the model projected in such a way that it can be compared to the data when multiplied by an amplitude vector \(\alpha\). It should be weighted if the data vector is. The caller is responsible for guaranteeing that the shape of the matrix correct, but implementations should not assume anything about the initial values of the matrix elements.
[in]	nonlinear	Vector of nonlinear parameters at which to evaluate the model.
[in]	doApplyWeights	If False, do not apply the weights to the modelMatrix.

Implements lsst::meas::modelfit::Likelihood.

◆ getAmplitudeDim()

int lsst::meas::modelfit::Likelihood::getAmplitudeDim ( ) const

inlineinherited

Return the number of linear parameters (columns of the model matrix)

Definition at line 77 of file Likelihood.h.

77{ return _model->getAmplitudeDim(); }

lsst::meas::modelfit::Likelihood::_model

std::shared_ptr< Model > _model

Definition Likelihood.h:147

◆ getData()

ndarray::Array< Pixel const, 1, 1 > lsst::meas::modelfit::Likelihood::getData ( ) const

inlineinherited

Return the vector of weighted, scaled data points \(z\).

Definition at line 89 of file Likelihood.h.

89{ return _data; }

lsst::meas::modelfit::Likelihood::_data

ndarray::Array< Pixel, 1, 1 > _data

Definition Likelihood.h:149

◆ getDataDim()

int lsst::meas::modelfit::Likelihood::getDataDim ( ) const

inlineinherited

Return the number of data points.

Definition at line 74 of file Likelihood.h.

74{ return _data.getSize<0>(); }

◆ getFixed()

ndarray::Array< Scalar const, 1, 1 > lsst::meas::modelfit::Likelihood::getFixed ( ) const

inlineinherited

Return the vector of fixed nonlinear parameters.

Definition at line 86 of file Likelihood.h.

86{ return _fixed; }

lsst::meas::modelfit::Likelihood::_fixed

ndarray::Array< Scalar const, 1, 1 > _fixed

Definition Likelihood.h:148

◆ getFixedDim()

int lsst::meas::modelfit::Likelihood::getFixedDim ( ) const

inlineinherited

Return the number of fixed nonlinear parameters (set on Likelihood construction)

Definition at line 83 of file Likelihood.h.

83{ return _model->getFixedDim(); }

◆ getModel()

std::shared_ptr< Model > lsst::meas::modelfit::Likelihood::getModel ( ) const

inlineinherited

Return an object that defines the model and its parameters.

Definition at line 105 of file Likelihood.h.

105{ return _model; }

◆ getNonlinearDim()

int lsst::meas::modelfit::Likelihood::getNonlinearDim ( ) const

inlineinherited

Return the number of nonlinear parameters (which parameterize the model matrix)

Definition at line 80 of file Likelihood.h.

80{ return _model->getNonlinearDim(); }

◆ getUnweightedData()

ndarray::Array< Pixel const, 1, 1 > lsst::meas::modelfit::Likelihood::getUnweightedData ( ) const

inlineinherited

Return the vector of unweighted data points \(y\).

Definition at line 92 of file Likelihood.h.

92{ return _unweightedData; }

lsst::meas::modelfit::Likelihood::_unweightedData

ndarray::Array< Pixel, 1, 1 > _unweightedData

Definition Likelihood.h:150

◆ getVariance()

ndarray::Array< Pixel const, 1, 1 > lsst::meas::modelfit::Likelihood::getVariance ( ) const

inlineinherited

Return the vector of per-data-point variances.

Definition at line 102 of file Likelihood.h.

102{ return _variance; }

lsst::meas::modelfit::Likelihood::_variance

ndarray::Array< Pixel, 1, 1 > _variance

Definition Likelihood.h:151

◆ getWeights()

ndarray::Array< Pixel const, 1, 1 > lsst::meas::modelfit::Likelihood::getWeights ( ) const

inlineinherited

Return the vector of weights \(w\) applied to data points and model matrix rows.

Will be an empty array if no weights are applied.

Definition at line 99 of file Likelihood.h.

99{ return _weights; }

lsst::meas::modelfit::Likelihood::_weights

ndarray::Array< Pixel, 1, 1 > _weights

Definition Likelihood.h:152

Member Data Documentation

◆ _data

ndarray::Array<Pixel,1,1> lsst::meas::modelfit::Likelihood::_data

protectedinherited

Definition at line 149 of file Likelihood.h.

◆ _fixed

ndarray::Array<Scalar const,1,1> lsst::meas::modelfit::Likelihood::_fixed

protectedinherited

Definition at line 148 of file Likelihood.h.

◆ _model

std::shared_ptr<Model> lsst::meas::modelfit::Likelihood::_model

protectedinherited

Definition at line 147 of file Likelihood.h.

◆ _unweightedData

ndarray::Array<Pixel,1,1> lsst::meas::modelfit::Likelihood::_unweightedData

protectedinherited

Definition at line 150 of file Likelihood.h.

◆ _variance

ndarray::Array<Pixel,1,1> lsst::meas::modelfit::Likelihood::_variance

protectedinherited

Definition at line 151 of file Likelihood.h.

◆ _weights

ndarray::Array<Pixel,1,1> lsst::meas::modelfit::Likelihood::_weights

protectedinherited

Definition at line 152 of file Likelihood.h.

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

/j/snowflake/release/lsstsw/stack/lsst-scipipe-8.0.0/Linux64/meas_modelfit/g591dd9f2cf+65b5bd823e/include/lsst/meas/modelfit/UnitTransformedLikelihood.h

Public Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ UnitTransformedLikelihood() [1/2]

◆ UnitTransformedLikelihood() [2/2]

◆ ~UnitTransformedLikelihood()

Member Function Documentation

◆ computeModelMatrix()

◆ getAmplitudeDim()

◆ getData()

◆ getDataDim()

◆ getFixed()

◆ getFixedDim()

◆ getModel()

◆ getNonlinearDim()

◆ getUnweightedData()

◆ getVariance()

◆ getWeights()

Member Data Documentation

◆ _data

◆ _fixed

◆ _model

◆ _unweightedData

◆ _variance

◆ _weights