gtsam/cpp/NoiseModel.cpp

76 lines
1.7 KiB
C++

/*
* NoiseModel.cpp
*
* Created on: Jan 13, 2010
* Author: Richard Roberts
* Author: Frank Dellaert
*/
#include "NoiseModel.h"
namespace ublas = boost::numeric::ublas;
typedef ublas::matrix_column<Matrix> column;
namespace gtsam {
Matrix GaussianNoiseModel::Whiten(const Matrix& H) const {
size_t n = H.size2(), m = H.size1();
Matrix W = zeros(m, n);
for (int j = 0; j < n; j++) {
Vector wj = whiten(column(H, j));
for (int i = 0; i < m; i++)
W(i, j) = wj(i);
}
return W;
}
Vector Isotropic::whiten(const Vector& v) const {
return v * invsigma_;
}
Vector Isotropic::unwhiten(const Vector& v) const {
return v * sigma_;
}
Diagonal::Diagonal(const Vector& sigmas) :
sigmas_(sigmas), invsigmas_(1.0 / sigmas) {
}
Diagonal::Diagonal(const Diagonal& d) :
sigmas_(d.sigmas_), invsigmas_(d.invsigmas_) {
}
Vector Diagonal::whiten(const Vector& v) const {
return emul(v, invsigmas_);
}
Vector Diagonal::unwhiten(const Vector& v) const {
return emul(v, sigmas_);
}
Variances::Variances(const Vector& variances) {
sigmas_.resize(variances.size());
std::transform(variances.begin(), variances.end(), sigmas_.begin(), sqrt);
invsigmas_ = reciprocal(sigmas_);
}
FullCovariance::FullCovariance(const Matrix& cov) :
sqrt_covariance_(square_root_positive(cov)), sqrt_inv_covariance_(
inverse_square_root(cov)) {
}
FullCovariance::FullCovariance(const FullCovariance& cov) :
sqrt_covariance_(cov.sqrt_covariance_), sqrt_inv_covariance_(
cov.sqrt_inv_covariance_) {
}
Vector FullCovariance::whiten(const Vector& v) const {
return sqrt_inv_covariance_ * v;
}
Vector FullCovariance::unwhiten(const Vector& v) const {
return sqrt_covariance_ * v;
}
} // gtsam