lsst.meas.modelfit  13.0-10-g4e34388+11
Public Member Functions | List of all members
lsst::meas::modelfit::MultiShapeletPsfLikelihood Class Reference

Likelihood object used to fit multishapelet models to PSF model images; mostly for internal use by GeneralPsfFitter. More...

#include <GeneralPsfFitter.h>

Inheritance diagram for lsst::meas::modelfit::MultiShapeletPsfLikelihood:
lsst::meas::modelfit::Likelihood

Public Member Functions

 MultiShapeletPsfLikelihood (ndarray::Array< Pixel const, 2, 1 > const &image, afw::geom::Point2I const &xy0, boost::shared_ptr< Model > model, Scalar sigma, ndarray::Array< Scalar const, 1, 1 > const &fixed)
 
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. More...
 
virtual ~MultiShapeletPsfLikelihood ()
 
- Public Member Functions inherited from lsst::meas::modelfit::Likelihood
int getDataDim () const
 Return the number of data points. More...
 
int getAmplitudeDim () const
 Return the number of linear parameters (columns of the model matrix) More...
 
int getNonlinearDim () const
 Return the number of nonlinear parameters (which parameterize the model matrix) More...
 
int getFixedDim () const
 Return the number of fixed nonlinear parameters (set on Likelihood construction) More...
 
ndarray::Array< Scalar const, 1, 1 > getFixed () const
 Return the vector of fixed nonlinear parameters. More...
 
ndarray::Array< Pixel const, 1, 1 > getData () const
 Return the vector of weighted, scaled data points \(z\). More...
 
ndarray::Array< Pixel const, 1, 1 > getUnweightedData () const
 Return the vector of unweighted data points \(y\). More...
 
ndarray::Array< Pixel const, 1, 1 > getWeights () const
 Return the vector of weights \(w\) applied to data points and model matrix rows. More...
 
ndarray::Array< Pixel const, 1, 1 > getVariance () const
 Return the vector of per-data-point variances. More...
 
boost::shared_ptr< ModelgetModel () const
 Return an object that defines the model and its parameters. More...
 
virtual ~Likelihood ()
 
 Likelihood (const Likelihood &)=delete
 
Likelihoodoperator= (const Likelihood &)=delete
 
 Likelihood (Likelihood &&)=delete
 
Likelihoodoperator= (Likelihood &&)=delete
 

Additional Inherited Members

- Protected Member Functions inherited from lsst::meas::modelfit::Likelihood
 Likelihood (boost::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed)
 
- Protected Attributes inherited from lsst::meas::modelfit::Likelihood
boost::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

Likelihood object used to fit multishapelet models to PSF model images; mostly for internal use by GeneralPsfFitter.

Definition at line 313 of file GeneralPsfFitter.h.

Constructor & Destructor Documentation

◆ MultiShapeletPsfLikelihood()

lsst::meas::modelfit::MultiShapeletPsfLikelihood::MultiShapeletPsfLikelihood ( ndarray::Array< Pixel const, 2, 1 > const &  image,
afw::geom::Point2I const &  xy0,
boost::shared_ptr< Model model,
Scalar  sigma,
ndarray::Array< Scalar const, 1, 1 > const &  fixed 
)

◆ ~MultiShapeletPsfLikelihood()

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

Member Function Documentation

◆ computeModelMatrix()

void lsst::meas::modelfit::MultiShapeletPsfLikelihood::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]modelMatrixThe 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]nonlinearVector of nonlinear parameters at which to evaluate the model.
[in]doApplyWeightsIf False, do not apply the weights to the modelMatrix.

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


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