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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2023 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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// 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
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/dense_qr_solver.h"
#include <cstddef>
#include "Eigen/Dense"
#include "ceres/dense_qr.h"
#include "ceres/dense_sparse_matrix.h"
#include "ceres/internal/eigen.h"
#include "ceres/linear_solver.h"
#include "ceres/types.h"
#include "ceres/wall_time.h"
namespace ceres::internal {
DenseQRSolver::DenseQRSolver(const LinearSolver::Options& options)
: options_(options), dense_qr_(DenseQR::Create(options)) {}
LinearSolver::Summary DenseQRSolver::SolveImpl(
DenseSparseMatrix* A,
const double* b,
const LinearSolver::PerSolveOptions& per_solve_options,
double* x) {
EventLogger event_logger("DenseQRSolver::Solve");
const int num_rows = A->num_rows();
const int num_cols = A->num_cols();
const int num_augmented_rows =
num_rows + ((per_solve_options.D != nullptr) ? num_cols : 0);
if (lhs_.rows() != num_augmented_rows || lhs_.cols() != num_cols) {
lhs_.resize(num_augmented_rows, num_cols);
rhs_.resize(num_augmented_rows);
}
lhs_.topRows(num_rows) = A->matrix();
rhs_.head(num_rows) = ConstVectorRef(b, num_rows);
if (num_rows != num_augmented_rows) {
lhs_.bottomRows(num_cols) =
ConstVectorRef(per_solve_options.D, num_cols).asDiagonal();
rhs_.tail(num_cols).setZero();
}
LinearSolver::Summary summary;
summary.termination_type = dense_qr_->FactorAndSolve(
lhs_.rows(), lhs_.cols(), lhs_.data(), rhs_.data(), x, &summary.message);
summary.num_iterations = 1;
event_logger.AddEvent("Solve");
return summary;
}
} // namespace ceres::internal