lsst::afw::math::SquaredExpCovariogram< T > Class Template Reference

SquaredExpCovariogram. More...

#include <GaussianProcess.h>

Inheritance diagram for lsst::afw::math::SquaredExpCovariogram< T >:

Public Member Functions
	~SquaredExpCovariogram () override
	SquaredExpCovariogram ()
void	setEllSquared (double ellSquared)
	set the _ellSquared hyper parameter (the square of the characteristic length scale of the covariogram)
T	operator() (ndarray::Array< const T, 1, 1 > const &, ndarray::Array< const T, 1, 1 > const &) const override
	Actually evaluate the covariogram function relating two points you want to interpolate from.

Detailed Description

template<typename T>
class lsst::afw::math::SquaredExpCovariogram< T >

SquaredExpCovariogram.

a Covariogram that falls off as the negative exponent of the square of the distance between the points

Contains one hyper parameter (_ellSquared) encoding the square of the characteristic length scale of the covariogram

Definition at line 164 of file GaussianProcess.h.

Constructor & Destructor Documentation

~SquaredExpCovariogram()

template<typename T>

lsst::afw::math::SquaredExpCovariogram< T >::~SquaredExpCovariogram ( )

overridedefault

SquaredExpCovariogram()

template<typename T>

lsst::afw::math::SquaredExpCovariogram< T >::SquaredExpCovariogram ( )

explicit

Definition at line 2000 of file GaussianProcess.cc.

                                                {
    _ellSquared = 1.0;
}

Member Function Documentation

operator()()

template<typename T>

T lsst::afw::math::SquaredExpCovariogram< T >::operator() ( ndarray::Array< const T, 1, 1 > const & p1, ndarray::Array< const T, 1, 1 > const & p2 ) const

overridevirtual

Actually evaluate the covariogram function relating two points you want to interpolate from.

Parameters

[in]	p1	the first point
[in]	p2	the second point

Reimplemented from lsst::afw::math::Covariogram< T >.

Definition at line 2010 of file GaussianProcess.cc.

                                                                                    {
    T d = 0.0;
    for (ndarray::Size i = 0; i < p1.template getSize<0>(); i++) {
        d += (p1[i] - p2[i]) * (p1[i] - p2[i]);
    }
 
    d = d / _ellSquared;
    return T(exp(-0.5 * d));
}

setEllSquared()

template<typename T>

void lsst::afw::math::SquaredExpCovariogram< T >::setEllSquared

(

double

ellSquared

)

set the _ellSquared hyper parameter (the square of the characteristic length scale of the covariogram)

Definition at line 2005 of file GaussianProcess.cc.

                                                              {
    _ellSquared = ellSquared;
}

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The documentation for this class was generated from the following files:

• /j/snowflake/release/lsstsw/stack/lsst-scipipe-10.0.0/Linux64/afw/g5a012ec0e7+477f9c599b/include/lsst/afw/math/GaussianProcess.h
• /j/snowflake/release/lsstsw/stack/lsst-scipipe-10.0.0/Linux64/afw/g5a012ec0e7+477f9c599b/src/math/GaussianProcess.cc