Gaussian.cpp

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/*
 * Copyright (C) 2016-2019 Istituto Italiano di Tecnologia (IIT)
 *
 * This software may be modified and distributed under the terms of the
 * BSD 3-Clause license. See the accompanying LICENSE file for details.
 */
 
#include <BayesFilters/Gaussian.h>
 
#include <exception>
 
using namespace bfl;
using namespace Eigen;
 
Gaussian::Gaussian() noexcept :
    GaussianMixture(1, 1, 0, false)
{ }
 
 
Gaussian::Gaussian(const std::size_t dim_linear) noexcept :
    GaussianMixture(1, dim_linear, 0, false)
{ }
 
 
Gaussian::Gaussian
(
    const std::size_t dim_linear,
    const std::size_t dim_circular,
    const bool use_quaternion
) noexcept :
    GaussianMixture(1, dim_linear, dim_circular, use_quaternion)
{ }
 
 
void Gaussian::resize(const std::size_t dim_linear, const std::size_t dim_circular)
{
    GaussianMixture::resize(1, dim_linear, dim_circular);
}
 
 
Ref<VectorXd> Gaussian::mean()
{
    return mean_.col(0);
}
 
 
const Ref<const VectorXd> Gaussian::mean() const
{
    return mean_.col(0);
}
 
 
double& Gaussian::mean(const std::size_t i)
{
    return mean_(i, 0);
}
 
 
const double& Gaussian::mean(const std::size_t i) const
{
    return mean_(i, 0);
}
 
 
Ref<MatrixXd> Gaussian::covariance()
{
    return covariance_;
}
 
 
const Ref<const MatrixXd> Gaussian::covariance() const
{
    return covariance_;
}
 
 
double& Gaussian::covariance(const std::size_t i, const std::size_t j)
{
 
    return covariance_(i, j);
}
 
 
const double& Gaussian::covariance(const std::size_t i, const std::size_t j) const
{
    return covariance_(i, j);
}
 
 
double& Gaussian::weight()
{
    return weight_(0);
}
 
 
const double& Gaussian::weight() const
{
    return weight_(0);
}