// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 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