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LSST Data Management Base Package
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Likelihood.h
Go to the documentation of this file.
1// -*- lsst-c++ -*-
2/*
3 * LSST Data Management System
4 * Copyright 2008-2013 LSST Corporation.
5 *
6 * This product includes software developed by the
7 * LSST Project (http://www.lsst.org/).
8 *
9 * This program is free software: you can redistribute it and/or modify
10 * it under the terms of the GNU General Public License as published by
11 * the Free Software Foundation, either version 3 of the License, or
12 * (at your option) any later version.
13 *
14 * This program is distributed in the hope that it will be useful,
15 * but WITHOUT ANY WARRANTY; without even the implied warranty of
16 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
17 * GNU General Public License for more details.
18 *
19 * You should have received a copy of the LSST License Statement and
20 * the GNU General Public License along with this program. If not,
21 * see <http://www.lsstcorp.org/LegalNotices/>.
22 */
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
33namespace lsst { namespace meas { namespace modelfit {
34
70{
71public:
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
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;
135
136protected:
137
138 Likelihood(std::shared_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
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
std::shared_ptr< Model > getModel() const
Return an object that defines the model and its parameters.
Definition: Likelihood.h:105
ndarray::Array< Pixel const, 1, 1 > getUnweightedData() const
Return the vector of unweighted data points .
Definition: Likelihood.h:92
Likelihood(const Likelihood &)=delete
std::shared_ptr< Model > _model
Definition: Likelihood.h:147
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< 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 > getVariance() const
Return the vector of per-data-point variances.
Definition: Likelihood.h:102
int getNonlinearDim() const
Return the number of nonlinear parameters (which parameterize the model matrix)
Definition: Likelihood.h:80
Likelihood & operator=(const 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< Pixel, 1, 1 > _unweightedData
Definition: Likelihood.h:150
ndarray::Array< Scalar const, 1, 1 > getFixed() const
Return the vector of fixed nonlinear parameters.
Definition: Likelihood.h:86
ndarray::Array< Pixel, 1, 1 > _weights
Definition: Likelihood.h:152
ndarray::Array< Pixel const, 1, 1 > getData() const
Return the vector of weighted, scaled data points .
Definition: Likelihood.h:89
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
Likelihood(std::shared_ptr< Model > model, ndarray::Array< Scalar const, 1, 1 > const &fixed)
Definition: Likelihood.h:138
Reports attempts to exceed implementation-defined length limits for some classes.
Definition: Runtime.h:76