svd.cc

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/* SPDX-FileCopyrightText: 2015 Blender Authors
 *
 * SPDX-License-Identifier: GPL-2.0-or-later */
 
#ifndef __EIGEN3_SVD_C_API_CC__
#define __EIGEN3_SVD_C_API_CC__
 
/* Eigen gives annoying huge amount of warnings here, silence them! */
#if defined(__GNUC__) && !defined(__clang__)
#  pragma GCC diagnostic ignored "-Wlogical-op"
#endif
 
#ifdef __EIGEN3_SVD_C_API_CC__
/* Quiet warning. */
#endif
 
#include <Eigen/Core>
#include <Eigen/Dense>
#include <Eigen/SVD>
 
#include "svd.h"
 
using Eigen::JacobiSVD;
 
using Eigen::NoQRPreconditioner;
 
using Eigen::ComputeThinU;
using Eigen::ComputeThinV;
 
using Eigen::Map;
using Eigen::MatrixXf;
using Eigen::VectorXf;
 
using Eigen::Matrix4f;
 
void EIG_svd_square_matrix(const int size, const float *matrix, float *r_U, float *r_S, float *r_V)
{
  /* Since our matrix is squared, we can use thinU/V. */
  unsigned int flags = (r_U ? ComputeThinU : 0) | (r_V ? ComputeThinV : 0);
 
  /* Blender and Eigen matrices are both column-major. */
  JacobiSVD<MatrixXf, NoQRPreconditioner> svd(Map<MatrixXf>((float *)matrix, size, size), flags);
 
  if (r_U) {
    Map<MatrixXf>(r_U, size, size) = svd.matrixU();
  }
 
  if (r_S) {
    Map<VectorXf>(r_S, size) = svd.singularValues();
  }
 
  if (r_V) {
    Map<MatrixXf>(r_V, size, size) = svd.matrixV();
  }
}
 
#endif /* __EIGEN3_SVD_C_API_CC__ */