/usr/include/CGAL/Eigen_vcm_traits.h is in libcgal-dev 4.7-4.
This file is owned by root:root, with mode 0o644.
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// All rights reserved.
//
// This file is part of CGAL (www.cgal.org).
// 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.
//
// Licensees holding a valid commercial license may use this file in
// accordance with the commercial license agreement provided with the software.
//
// This file is provided AS IS with NO WARRANTY OF ANY KIND, INCLUDING THE
// WARRANTY OF DESIGN, MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE.
//
// $URL$
// $Id$
//
// Author(s) : Jocelyn Meyron and Quentin Mérigot
//
#ifndef CGAL_EIGEN_VCM_TRAITS_H
#define CGAL_EIGEN_VCM_TRAITS_H
#include <Eigen/Dense>
#include <Eigen/Eigenvalues>
#include <CGAL/array.h>
namespace CGAL {
/// A model of the concept `VCMTraits` using \ref thirdpartyEigen.
/// \cgalModels `VCMTraits`
class Eigen_vcm_traits{
// Construct the covariance matrix
static Eigen::Matrix3f
construct_covariance_matrix (const cpp11::array<double,6>& cov) {
Eigen::Matrix3f m;
m(0,0) = cov[0]; m(0,1) = cov[1]; m(0,2) = cov[2];
m(1,1) = cov[3]; m(1,2) = cov[4];
m(2,2) = cov[5];
m(1, 0) = m(0,1); m(2, 0) = m(0, 2); m(2, 1) = m(1, 2);
return m;
}
// Diagonalize a selfadjoint matrix
static bool
diagonalize_selfadjoint_matrix (Eigen::Matrix3f &m,
Eigen::Matrix3f &eigenvectors,
Eigen::Vector3f &eigenvalues) {
Eigen::SelfAdjointEigenSolver<Eigen::Matrix3f> eigensolver(m);
if (eigensolver.info() != Eigen::Success) {
return false;
}
eigenvalues = eigensolver.eigenvalues();
eigenvectors = eigensolver.eigenvectors();
return true;
}
public:
static bool
diagonalize_selfadjoint_covariance_matrix(
const cpp11::array<double,6>& cov,
cpp11::array<double, 3>& eigenvalues)
{
Eigen::Matrix3f m = construct_covariance_matrix(cov);
// Diagonalizing the matrix
Eigen::Vector3f eigenvalues_;
Eigen::Matrix3f eigenvectors_;
bool res = diagonalize_selfadjoint_matrix(m, eigenvectors_, eigenvalues_);
if (res)
{
eigenvalues[0]=eigenvalues_[0];
eigenvalues[1]=eigenvalues_[1];
eigenvalues[2]=eigenvalues_[2];
}
return res;
}
// Extract the eigenvector associated to the largest eigenvalue
static bool
extract_largest_eigenvector_of_covariance_matrix (
const cpp11::array<double,6>& cov,
cpp11::array<double,3> &normal)
{
// Construct covariance matrix
Eigen::Matrix3f m = construct_covariance_matrix(cov);
// Diagonalizing the matrix
Eigen::Vector3f eigenvalues;
Eigen::Matrix3f eigenvectors;
if (! diagonalize_selfadjoint_matrix(m, eigenvectors, eigenvalues)) {
return false;
}
// Eigenvalues are already sorted by increasing order
normal[0]=eigenvectors(0,0);
normal[1]=eigenvectors(1,0);
normal[2]=eigenvectors(2,0);
return true;
}
};
} // namespace CGAL
#endif // CGAL_EIGEN_VCM_TRAITS_H
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