LSST Applications  21.0.0+04719a4bac,21.0.0-1-ga51b5d4+f5e6047307,21.0.0-11-g2b59f77+a9c1acf22d,21.0.0-11-ga42c5b2+86977b0b17,21.0.0-12-gf4ce030+76814010d2,21.0.0-13-g1721dae+760e7a6536,21.0.0-13-g3a573fe+768d78a30a,21.0.0-15-g5a7caf0+f21cbc5713,21.0.0-16-g0fb55c1+b60e2d390c,21.0.0-19-g4cded4ca+71a93a33c0,21.0.0-2-g103fe59+bb20972958,21.0.0-2-g45278ab+04719a4bac,21.0.0-2-g5242d73+3ad5d60fb1,21.0.0-2-g7f82c8f+8babb168e8,21.0.0-2-g8f08a60+06509c8b61,21.0.0-2-g8faa9b5+616205b9df,21.0.0-2-ga326454+8babb168e8,21.0.0-2-gde069b7+5e4aea9c2f,21.0.0-2-gecfae73+1d3a86e577,21.0.0-2-gfc62afb+3ad5d60fb1,21.0.0-25-g1d57be3cd+e73869a214,21.0.0-3-g357aad2+ed88757d29,21.0.0-3-g4a4ce7f+3ad5d60fb1,21.0.0-3-g4be5c26+3ad5d60fb1,21.0.0-3-g65f322c+e0b24896a3,21.0.0-3-g7d9da8d+616205b9df,21.0.0-3-ge02ed75+a9c1acf22d,21.0.0-4-g591bb35+a9c1acf22d,21.0.0-4-g65b4814+b60e2d390c,21.0.0-4-gccdca77+0de219a2bc,21.0.0-4-ge8a399c+6c55c39e83,21.0.0-5-gd00fb1e+05fce91b99,21.0.0-6-gc675373+3ad5d60fb1,21.0.0-64-g1122c245+4fb2b8f86e,21.0.0-7-g04766d7+cd19d05db2,21.0.0-7-gdf92d54+04719a4bac,21.0.0-8-g5674e7b+d1bd76f71f,master-gac4afde19b+a9c1acf22d,w.2021.13
LSST Data Management Base Package
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
#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
#define PTR(...)
Definition: base.h:41
Base class for optimizer/sampler likelihood functions that compute likelihood at a point.
Definition: Likelihood.h:70
ndarray::Array< Pixel, 1, 1 > _variance
Definition: Likelihood.h:151
ndarray::Array< Pixel const, 1, 1 > getVariance() const
Return the vector of per-data-point variances.
Definition: Likelihood.h:102
boost::shared_ptr< Model > _model
Definition: Likelihood.h:147
ndarray::Array< Pixel const, 1, 1 > getData() const
Return the vector of weighted, scaled data points .
Definition: Likelihood.h:89
Likelihood(const Likelihood &)=delete
Likelihood & operator=(const Likelihood &)=delete
ndarray::Array< Scalar const, 1, 1 > getFixed() const
Return the vector of fixed nonlinear parameters.
Definition: Likelihood.h:86
int getDataDim() const
Return the number of data points.
Definition: Likelihood.h:74
ndarray::Array< Pixel, 1, 1 > _data
Definition: Likelihood.h:149
Likelihood(Likelihood &&)=delete
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
ndarray::Array< Scalar const, 1, 1 > _fixed
Definition: Likelihood.h:148
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 > getUnweightedData() const
Return the vector of unweighted data points .
Definition: Likelihood.h:92
Likelihood(boost::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed)
Definition: Likelihood.h:138
int getNonlinearDim() const
Return the number of nonlinear parameters (which parameterize the model matrix)
Definition: Likelihood.h:80
boost::shared_ptr< Model > getModel() const
Return an object that defines the model and its parameters.
Definition: Likelihood.h:105
ndarray::Array< Pixel, 1, 1 > _unweightedData
Definition: Likelihood.h:150
ndarray::Array< Pixel, 1, 1 > _weights
Definition: Likelihood.h:152
int getAmplitudeDim() const
Return the number of linear parameters (columns of the model matrix)
Definition: Likelihood.h:77
int getFixedDim() const
Return the number of fixed nonlinear parameters (set on Likelihood construction)
Definition: Likelihood.h:83
Abstract base class and concrete factories that define multi-shapelet galaxy models.
Definition: Model.h:56
int getFixedDim() const
Return the number of fixed nonlinear parameters.
Definition: Model.h:130
Reports attempts to exceed implementation-defined length limits for some classes.
Definition: Runtime.h:76
A base class for image defects.