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Make Eigen_vcm_traits template of floating types with static_casts for Eigen conversion

This commit is contained in:
Simon Giraudot 2015-08-21 09:16:46 +02:00
parent 9e0e0b7c8a
commit a3bcd62a42
1 changed files with 34 additions and 29 deletions
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63
Solver_interface/include/CGAL/Eigen_vcm_traits.h
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@ -30,15 +30,20 @@ namespace CGAL {
/// A model of the concept `VCMTraits` using \ref thirdpartyEigen.
/// \cgalModels `VCMTraits`
template <typename FT>
class Eigen_vcm_traits{
// Construct the covariance matrix
static Eigen::Matrix3f
construct_covariance_matrix (const cpp11::array<double,6>& cov) {
construct_covariance_matrix (const cpp11::array<FT,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(0,0) = static_cast<float>(cov[0]);
m(0,1) = static_cast<float>(cov[1]);
m(0,2) = static_cast<float>(cov[2]);
m(1,1) = static_cast<float>(cov[3]);
m(1,2) = static_cast<float>(cov[4]);
m(2,2) = static_cast<float>(cov[5]);
m(1, 0) = m(0,1); m(2, 0) = m(0, 2); m(2, 1) = m(1, 2);
@ -65,8 +70,8 @@ class Eigen_vcm_traits{
public:
static bool
diagonalize_selfadjoint_covariance_matrix(
const cpp11::array<double,6>& cov,
cpp11::array<double, 3>& eigenvalues)
const cpp11::array<FT,6>& cov,
cpp11::array<FT, 3>& eigenvalues)
{
Eigen::Matrix3f m = construct_covariance_matrix(cov);
@ -77,9 +82,9 @@ public:
if (res)
{
eigenvalues[0]=eigenvalues_[0];
eigenvalues[1]=eigenvalues_[1];
eigenvalues[2]=eigenvalues_[2];
eigenvalues[0]=static_cast<FT>(eigenvalues_[0]);
eigenvalues[1]=static_cast<FT>(eigenvalues_[1]);
eigenvalues[2]=static_cast<FT>(eigenvalues_[2]);
}
return res;
@ -87,9 +92,9 @@ public:
static bool
diagonalize_selfadjoint_covariance_matrix(
const cpp11::array<double,6>& cov,
cpp11::array<double, 3>& eigenvalues,
cpp11::array<double, 9>& eigenvectors)
const cpp11::array<FT,6>& cov,
cpp11::array<FT, 3>& eigenvalues,
cpp11::array<FT, 9>& eigenvectors)
{
Eigen::Matrix3f m = construct_covariance_matrix(cov);
@ -100,18 +105,18 @@ public:
if (res)
{
eigenvalues[0]=eigenvalues_[0];
eigenvalues[1]=eigenvalues_[1];
eigenvalues[2]=eigenvalues_[2];
eigenvectors[0]=eigenvectors_(0,0);
eigenvectors[1]=eigenvectors_(1,0);
eigenvectors[2]=eigenvectors_(2,0);
eigenvectors[3]=eigenvectors_(0,1);
eigenvectors[4]=eigenvectors_(1,1);
eigenvectors[5]=eigenvectors_(2,1);
eigenvectors[6]=eigenvectors_(0,2);
eigenvectors[7]=eigenvectors_(1,2);
eigenvectors[8]=eigenvectors_(2,2);
eigenvalues[0]=static_cast<FT>(eigenvalues_[0]);
eigenvalues[1]=static_cast<FT>(eigenvalues_[1]);
eigenvalues[2]=static_cast<FT>(eigenvalues_[2]);
eigenvectors[0]=static_cast<FT>(eigenvectors_(0,0));
eigenvectors[1]=static_cast<FT>(eigenvectors_(1,0));
eigenvectors[2]=static_cast<FT>(eigenvectors_(2,0));
eigenvectors[3]=static_cast<FT>(eigenvectors_(0,1));
eigenvectors[4]=static_cast<FT>(eigenvectors_(1,1));
eigenvectors[5]=static_cast<FT>(eigenvectors_(2,1));
eigenvectors[6]=static_cast<FT>(eigenvectors_(0,2));
eigenvectors[7]=static_cast<FT>(eigenvectors_(1,2));
eigenvectors[8]=static_cast<FT>(eigenvectors_(2,2));
}
return res;
@ -120,8 +125,8 @@ public:
// 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)
const cpp11::array<FT,6>& cov,
cpp11::array<FT,3> &normal)
{
// Construct covariance matrix
Eigen::Matrix3f m = construct_covariance_matrix(cov);
@ -134,9 +139,9 @@ public:
}
// Eigenvalues are already sorted by increasing order
normal[0]=eigenvectors(0,0);
normal[1]=eigenvectors(1,0);
normal[2]=eigenvectors(2,0);
normal[0]=static_cast<FT>(eigenvectors(0,0));
normal[1]=static_cast<FT>(eigenvectors(1,0));
normal[2]=static_cast<FT>(eigenvectors(2,0));
return true;
}