LSSTApplications  19.0.0-14-gb0260a2+72efe9b372,20.0.0+7927753e06,20.0.0+8829bf0056,20.0.0+995114c5d2,20.0.0+b6f4b2abd1,20.0.0+bddc4f4cbe,20.0.0-1-g253301a+8829bf0056,20.0.0-1-g2b7511a+0d71a2d77f,20.0.0-1-g5b95a8c+7461dd0434,20.0.0-12-g321c96ea+23efe4bbff,20.0.0-16-gfab17e72e+fdf35455f6,20.0.0-2-g0070d88+ba3ffc8f0b,20.0.0-2-g4dae9ad+ee58a624b3,20.0.0-2-g61b8584+5d3db074ba,20.0.0-2-gb780d76+d529cf1a41,20.0.0-2-ged6426c+226a441f5f,20.0.0-2-gf072044+8829bf0056,20.0.0-2-gf1f7952+ee58a624b3,20.0.0-20-geae50cf+e37fec0aee,20.0.0-25-g3dcad98+544a109665,20.0.0-25-g5eafb0f+ee58a624b3,20.0.0-27-g64178ef+f1f297b00a,20.0.0-3-g4cc78c6+e0676b0dc8,20.0.0-3-g8f21e14+4fd2c12c9a,20.0.0-3-gbd60e8c+187b78b4b8,20.0.0-3-gbecbe05+48431fa087,20.0.0-38-ge4adf513+a12e1f8e37,20.0.0-4-g97dc21a+544a109665,20.0.0-4-gb4befbc+087873070b,20.0.0-4-gf910f65+5d3db074ba,20.0.0-5-gdfe0fee+199202a608,20.0.0-5-gfbfe500+d529cf1a41,20.0.0-6-g64f541c+d529cf1a41,20.0.0-6-g9a5b7a1+a1cd37312e,20.0.0-68-ga3f3dda+5fca18c6a4,20.0.0-9-g4aef684+e18322736b,w.2020.45
LSSTDataManagementBasePackage
Likelihood.h
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23 
24 #ifndef LSST_MEAS_MODELFIT_Likelihood_h_INCLUDED
25 #define LSST_MEAS_MODELFIT_Likelihood_h_INCLUDED
26 
27 #include "ndarray_fwd.h"
28 
29 #include "lsst/pex/exceptions.h"
32 
33 namespace lsst { namespace meas { namespace modelfit {
34 
70 {
71 public:
72 
74  int getDataDim() const { return _data.getSize<0>(); }
75 
77  int getAmplitudeDim() const { return _model->getAmplitudeDim(); }
78 
80  int getNonlinearDim() const { return _model->getNonlinearDim(); }
81 
83  int getFixedDim() const { return _model->getFixedDim(); }
84 
86  ndarray::Array<Scalar const,1,1> getFixed() const { return _fixed; }
87 
89  ndarray::Array<Pixel const,1,1> getData() const { return _data; }
90 
92  ndarray::Array<Pixel const,1,1> getUnweightedData() const { return _unweightedData; }
93 
99  ndarray::Array<Pixel const,1,1> getWeights() const { return _weights; }
100 
102  ndarray::Array<Pixel const,1,1> getVariance() const { return _variance; }
103 
105  PTR(Model) getModel() const { return _model; }
106 
120  virtual void computeModelMatrix(
121  ndarray::Array<Pixel,2,-1> const & modelMatrix,
122  ndarray::Array<Scalar const,1,1> const & nonlinear,
123  bool doApplyWeights=true
124  ) const = 0;
125 
126  virtual ~Likelihood() {}
127 
128  // No copying
129  Likelihood ( const Likelihood & ) = delete;
130  Likelihood & operator= ( const Likelihood & ) = delete;
131 
132  // No moving
133  Likelihood ( Likelihood && ) = delete;
134  Likelihood & operator= ( Likelihood && ) = delete;
135 
136 protected:
137 
138  Likelihood(PTR(Model) model, ndarray::Array<Scalar const,1,1> const & fixed) :
139  _model(model), _fixed(fixed) {
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)"
144  );
145  }
146 
148  ndarray::Array<Scalar const,1,1> _fixed;
149  ndarray::Array<Pixel,1,1> _data;
150  ndarray::Array<Pixel,1,1> _unweightedData;
151  ndarray::Array<Pixel,1,1> _variance;
152  ndarray::Array<Pixel,1,1> _weights;
153 };
154 
155 }}} // namespace lsst::meas::modelfit
156 
157 #endif // !LSST_MEAS_MODELFIT_Likelihood_h_INCLUDED
LSST_THROW_IF_NE
#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.
Definition: asserts.h:38
lsst::meas::modelfit::Likelihood::_variance
ndarray::Array< Pixel, 1, 1 > _variance
Definition: Likelihood.h:151
lsst::meas::modelfit::Likelihood::getModel
boost::shared_ptr< Model > getModel() const
Return an object that defines the model and its parameters.
Definition: Likelihood.h:105
lsst::meas::modelfit::Likelihood::operator=
Likelihood & operator=(const Likelihood &)=delete
lsst::meas::modelfit::Likelihood::getAmplitudeDim
int getAmplitudeDim() const
Return the number of linear parameters (columns of the model matrix)
Definition: Likelihood.h:77
lsst::meas::modelfit::Model::getFixedDim
int getFixedDim() const
Return the number of fixed nonlinear parameters.
Definition: Model.h:130
lsst::meas::modelfit::Model
Abstract base class and concrete factories that define multi-shapelet galaxy models.
Definition: Model.h:56
lsst::meas::modelfit::Likelihood::getFixed
ndarray::Array< Scalar const, 1, 1 > getFixed() const
Return the vector of fixed nonlinear parameters.
Definition: Likelihood.h:86
PTR
#define PTR(...)
Definition: base.h:41
lsst::meas::modelfit::Likelihood
Base class for optimizer/sampler likelihood functions that compute likelihood at a point.
Definition: Likelihood.h:70
lsst::meas::modelfit::Likelihood::computeModelMatrix
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.
lsst::meas::modelfit::Likelihood::getNonlinearDim
int getNonlinearDim() const
Return the number of nonlinear parameters (which parameterize the model matrix)
Definition: Likelihood.h:80
lsst::meas::modelfit::Likelihood::Likelihood
Likelihood(Likelihood &&)=delete
lsst::meas::modelfit::Likelihood::~Likelihood
virtual ~Likelihood()
Definition: Likelihood.h:126
lsst.pex::exceptions::LengthError
Reports attempts to exceed implementation-defined length limits for some classes.
Definition: Runtime.h:76
lsst::meas::modelfit::Likelihood::getData
ndarray::Array< Pixel const, 1, 1 > getData() const
Return the vector of weighted, scaled data points .
Definition: Likelihood.h:89
Model.h
lsst::meas::modelfit::Likelihood::Likelihood
Likelihood(const Likelihood &)=delete
lsst
A base class for image defects.
Definition: imageAlgorithm.dox:1
common.h
lsst::meas::modelfit::Likelihood::getVariance
ndarray::Array< Pixel const, 1, 1 > getVariance() const
Return the vector of per-data-point variances.
Definition: Likelihood.h:102
lsst::meas::modelfit::Likelihood::_unweightedData
ndarray::Array< Pixel, 1, 1 > _unweightedData
Definition: Likelihood.h:150
lsst::meas::modelfit::Likelihood::_fixed
ndarray::Array< Scalar const, 1, 1 > _fixed
Definition: Likelihood.h:148
lsst::meas::modelfit::Likelihood::getUnweightedData
ndarray::Array< Pixel const, 1, 1 > getUnweightedData() const
Return the vector of unweighted data points .
Definition: Likelihood.h:92
lsst::meas::modelfit::Likelihood::getDataDim
int getDataDim() const
Return the number of data points.
Definition: Likelihood.h:74
lsst::meas::modelfit::Likelihood::_weights
ndarray::Array< Pixel, 1, 1 > _weights
Definition: Likelihood.h:152
lsst::meas::modelfit::Likelihood::getFixedDim
int getFixedDim() const
Return the number of fixed nonlinear parameters (set on Likelihood construction)
Definition: Likelihood.h:83
std::size_t
lsst::meas::modelfit::Likelihood::Likelihood
Likelihood(boost::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed)
Definition: Likelihood.h:138
lsst::meas::modelfit::Likelihood::_data
ndarray::Array< Pixel, 1, 1 > _data
Definition: Likelihood.h:149
lsst::meas::modelfit::Likelihood::_model
boost::shared_ptr< Model > _model
Definition: Likelihood.h:147
lsst::meas::modelfit::Likelihood::getWeights
ndarray::Array< Pixel const, 1, 1 > getWeights() const
Return the vector of weights applied to data points and model matrix rows.
Definition: Likelihood.h:99
exceptions.h