Prior.h

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// -*- lsst-c++ -*-
/*
 * LSST Data Management System
 * Copyright 2008-2013 LSST Corporation.
 *
 * This product includes software developed by the
 * LSST Project (http://www.lsst.org/).
 *
 * This program is free software: you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation, either version 3 of the License, or
 * (at your option) any later version.
 *
 * This program is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the LSST License Statement and
 * the GNU General Public License along with this program.  If not,
 * see <http://www.lsstcorp.org/LegalNotices/>.
 */
 
#ifndef LSST_MEAS_MODELFIT_Prior_h_INCLUDED
#define LSST_MEAS_MODELFIT_Prior_h_INCLUDED
 
#include "lsst/base.h"
#include "lsst/afw/math/Random.h"
#include "lsst/meas/modelfit/common.h"
 
namespace lsst { namespace meas { namespace modelfit {

class Prior {
public:
 
    std::string const & getTag() const { return _tag; }

    virtual Scalar evaluate(
        ndarray::Array<Scalar const,1,1> const & nonlinear,
        ndarray::Array<Scalar const,1,1> const & amplitudes
    ) const = 0;

    virtual void evaluateDerivatives(
        ndarray::Array<Scalar const,1,1> const & nonlinear,
        ndarray::Array<Scalar const,1,1> const & amplitudes,
        ndarray::Array<Scalar,1,1> const & nonlinearGradient,
        ndarray::Array<Scalar,1,1> const & amplitudeGradient,
        ndarray::Array<Scalar,2,1> const & nonlinearHessian,
        ndarray::Array<Scalar,2,1> const & amplitudeHessian,
        ndarray::Array<Scalar,2,1> const & crossHessian
    ) const = 0;

    virtual Scalar marginalize(
        Vector const & gradient, Matrix const & hessian,
        ndarray::Array<Scalar const,1,1> const & nonlinear
    ) const = 0;

    virtual Scalar maximize(
        Vector const & gradient, Matrix const & hessian,
        ndarray::Array<Scalar const,1,1> const & nonlinear,
        ndarray::Array<Scalar,1,1> const & amplitudes
    ) const = 0;

    virtual void drawAmplitudes(
        Vector const & gradient, Matrix const & hessian,
        ndarray::Array<Scalar const,1,1> const & nonlinear,
        afw::math::Random & rng,
        ndarray::Array<Scalar,2,1> const & amplitudes,
        ndarray::Array<Scalar,1,1> const & weights,
        bool multiplyWeights=false
    ) const = 0;
 
    virtual ~Prior() {}
 
    // No copying
    Prior (const Prior&) = delete;
    Prior& operator=(const Prior&) = delete;
 
    // No moving
    Prior (Prior&&) = delete;
    Prior& operator=(Prior&&) = delete;
 
protected:
 
    explicit Prior(std::string const & tag="") : _tag(tag) {}
 
private:
    std::string _tag;
};
 
}}} // namespace lsst::meas::modelfit
 
#endif // !LSST_MEAS_MODELFIT_Prior_h_INCLUDED