24 #ifndef LSST_MEAS_MODELFIT_Likelihood_h_INCLUDED 25 #define LSST_MEAS_MODELFIT_Likelihood_h_INCLUDED 27 #include "ndarray_fwd.h" 33 namespace lsst {
namespace meas {
namespace modelfit {
121 ndarray::Array<Pixel,2,-1>
const & modelMatrix,
122 ndarray::Array<Scalar const,1,1>
const & nonlinear,
123 bool doApplyWeights=
true 141 fixed.getSize<0>(), static_cast<std::size_t>(model->
getFixedDim()),
143 "Fixed parameter vector size (%d) does not match Model fixed parameter dimensionality (%d)" 157 #endif // !LSST_MEAS_MODELFIT_Likelihood_h_INCLUDED virtual void computeModelMatrix(ndarray::Array< Pixel, 2,-1 > const &modelMatrix, ndarray::Array< Scalar const, 1, 1 > const &nonlinear, bool doApplyWeights=true) const =0
Evaluate the model for the given vector of nonlinear parameters.
ndarray::Array< Pixel const, 1, 1 > getWeights() const
Return the vector of weights applied to data points and model matrix rows.
ndarray::Array< Pixel, 1, 1 > _unweightedData
ndarray::Array< Pixel const, 1, 1 > getData() const
Return the vector of weighted, scaled data points .
Likelihood & operator=(const Likelihood &)=delete
#define LSST_THROW_IF_NE(N1, N2, EXC_CLASS, MSG)
Check whether the given values are equal, and throw an LSST Exception if they are not...
int getFixedDim() const
Return the number of fixed nonlinear parameters (set on Likelihood construction)
Reports attempts to exceed implementation-defined length limits for some classes. ...
ndarray::Array< Pixel const, 1, 1 > getUnweightedData() const
Return the vector of unweighted data points .
Abstract base class and concrete factories that define multi-shapelet galaxy models.
Likelihood(const Likelihood &)=delete
ndarray::Array< Scalar const, 1, 1 > getFixed() const
Return the vector of fixed nonlinear parameters.
A base class for image defects.
Likelihood(boost::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed)
ndarray::Array< Pixel, 1, 1 > _data
ndarray::Array< Pixel, 1, 1 > _weights
int getFixedDim() const
Return the number of fixed nonlinear parameters.
Base class for optimizer/sampler likelihood functions that compute likelihood at a point...
ndarray::Array< Scalar const, 1, 1 > _fixed
int getNonlinearDim() const
Return the number of nonlinear parameters (which parameterize the model matrix)
boost::shared_ptr< Model > getModel() const
Return an object that defines the model and its parameters.
ndarray::Array< Pixel, 1, 1 > _variance
int getAmplitudeDim() const
Return the number of linear parameters (columns of the model matrix)
ndarray::Array< Pixel const, 1, 1 > getVariance() const
Return the vector of per-data-point variances.
boost::shared_ptr< Model > _model
int getDataDim() const
Return the number of data points.