blob: aaeefa332df7b471c4c73e3a6d3fc5f818b2090c [file] [log] [blame]
// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2018 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)
#include "ceres/iterative_refiner.h"
#include <string>
#include "Eigen/Core"
#include "ceres/dense_cholesky.h"
#include "ceres/sparse_cholesky.h"
#include "ceres/sparse_matrix.h"
namespace ceres::internal {
SparseIterativeRefiner::SparseIterativeRefiner(const int max_num_iterations)
: max_num_iterations_(max_num_iterations) {}
SparseIterativeRefiner::~SparseIterativeRefiner() = default;
void SparseIterativeRefiner::Allocate(int num_cols) {
residual_.resize(num_cols);
correction_.resize(num_cols);
lhs_x_solution_.resize(num_cols);
}
void SparseIterativeRefiner::Refine(const SparseMatrix& lhs,
const double* rhs_ptr,
SparseCholesky* cholesky,
double* solution_ptr) {
const int num_cols = lhs.num_cols();
Allocate(num_cols);
ConstVectorRef rhs(rhs_ptr, num_cols);
VectorRef solution(solution_ptr, num_cols);
std::string ignored_message;
for (int i = 0; i < max_num_iterations_; ++i) {
// residual = rhs - lhs * solution
lhs_x_solution_.setZero();
lhs.RightMultiplyAndAccumulate(solution_ptr, lhs_x_solution_.data());
residual_ = rhs - lhs_x_solution_;
// solution += lhs^-1 residual
cholesky->Solve(residual_.data(), correction_.data(), &ignored_message);
solution += correction_;
}
};
DenseIterativeRefiner::DenseIterativeRefiner(const int max_num_iterations)
: max_num_iterations_(max_num_iterations) {}
DenseIterativeRefiner::~DenseIterativeRefiner() = default;
void DenseIterativeRefiner::Allocate(int num_cols) {
residual_.resize(num_cols);
correction_.resize(num_cols);
}
void DenseIterativeRefiner::Refine(const int num_cols,
const double* lhs_ptr,
const double* rhs_ptr,
DenseCholesky* cholesky,
double* solution_ptr) {
Allocate(num_cols);
ConstMatrixRef lhs(lhs_ptr, num_cols, num_cols);
ConstVectorRef rhs(rhs_ptr, num_cols);
VectorRef solution(solution_ptr, num_cols);
std::string ignored_message;
for (int i = 0; i < max_num_iterations_; ++i) {
residual_ = rhs - lhs * solution;
// solution += lhs^-1 residual
cholesky->Solve(residual_.data(), correction_.data(), &ignored_message);
solution += correction_;
}
};
} // namespace ceres::internal