mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-30 17:10:38 +08:00
Sameer Agarwal
084042c252
Update documentation for Solver::Options::max_num_line_search_step_size_iterations Change-Id: I03edc74e67940bed0be7e5ccaffed9e97114a5a5
86 lines
3.4 KiB
C++
86 lines
3.4 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
|
|
// Copyright 2017 Google Inc. All rights reserved.
|
|
// http://ceres-solver.org/
|
|
//
|
|
// Redistribution and use in source and binary forms, with or without
|
|
// modification, are permitted provided that the following conditions are met:
|
|
//
|
|
// * Redistributions of source code must retain the above copyright notice,
|
|
// this list of conditions and the following disclaimer.
|
|
// * Redistributions in binary form must reproduce the above copyright notice,
|
|
// this list of conditions and the following disclaimer in the documentation
|
|
// and/or other materials provided with the distribution.
|
|
// * Neither the name of Google Inc. nor the names of its contributors may be
|
|
// used to endorse or promote products derived from this software without
|
|
// specific prior written permission.
|
|
//
|
|
// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
|
|
// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
|
|
// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
|
|
// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
|
|
// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
|
|
// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
|
|
// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
|
|
// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
|
|
// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
|
|
// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
|
|
// POSSIBILITY OF SUCH DAMAGE.
|
|
//
|
|
// Author: sameeragarwal@google.com (Sameer Agarwal)
|
|
|
|
#ifndef CERES_INTERNAL_INVERT_PSD_MATRIX_H_
|
|
#define CERES_INTERNAL_INVERT_PSD_MATRIX_H_
|
|
|
|
#include "ceres/internal/eigen.h"
|
|
#include "glog/logging.h"
|
|
#include "Eigen/Dense"
|
|
|
|
namespace ceres {
|
|
namespace internal {
|
|
|
|
// Helper routine to compute the inverse or pseudo-inverse of a
|
|
// symmetric positive semi-definite matrix.
|
|
//
|
|
// assume_full_rank controls whether a Cholesky factorization or an
|
|
// Singular Value Decomposition is used to compute the inverse and the
|
|
// pseudo-inverse respectively.
|
|
//
|
|
// The template parameter kSize can either be Eigen::Dynamic or a
|
|
// positive integer equal to the number of rows of m.
|
|
template <int kSize>
|
|
typename EigenTypes<kSize, kSize>::Matrix InvertPSDMatrix(
|
|
const bool assume_full_rank,
|
|
const typename EigenTypes<kSize, kSize>::Matrix& m) {
|
|
using MType = typename EigenTypes<kSize, kSize>::Matrix;
|
|
const int size = m.rows();
|
|
|
|
// If the matrix can be assumed to be full rank, then if it is small
|
|
// (< 5) and fixed size, use Eigen's optimized inverse()
|
|
// implementation.
|
|
//
|
|
// https://eigen.tuxfamily.org/dox/group__TutorialLinearAlgebra.html#title3
|
|
if (assume_full_rank) {
|
|
if (kSize > 0 && kSize < 5) {
|
|
return m.inverse();
|
|
}
|
|
return m.template selfadjointView<Eigen::Upper>().llt().solve(
|
|
MType::Identity(size, size));
|
|
}
|
|
|
|
Eigen::JacobiSVD<MType> svd(m, Eigen::ComputeThinU | Eigen::ComputeThinV);
|
|
const double tolerance =
|
|
std::numeric_limits<double>::epsilon() * size * svd.singularValues()(0);
|
|
|
|
return svd.matrixV() *
|
|
(svd.singularValues().array() > tolerance)
|
|
.select(svd.singularValues().array().inverse(), 0)
|
|
.matrix()
|
|
.asDiagonal() *
|
|
svd.matrixU().adjoint();
|
|
}
|
|
|
|
} // namespace internal
|
|
} // namespace ceres
|
|
|
|
#endif // CERES_INTERNAL_INVERT_PSD_MATRIX_H_
|