// 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: markshachkov@gmail.com (Mark Shachkov) #include "ceres/power_series_expansion_preconditioner.h" #include "ceres/eigen_vector_ops.h" #include "ceres/parallel_vector_ops.h" #include "ceres/preconditioner.h" namespace ceres::internal { PowerSeriesExpansionPreconditioner::PowerSeriesExpansionPreconditioner( const ImplicitSchurComplement* isc, const int max_num_spse_iterations, const double spse_tolerance, const Preconditioner::Options& options) : isc_(isc), max_num_spse_iterations_(max_num_spse_iterations), spse_tolerance_(spse_tolerance), options_(options) {} PowerSeriesExpansionPreconditioner::~PowerSeriesExpansionPreconditioner() = default; bool PowerSeriesExpansionPreconditioner::Update(const LinearOperator& /*A*/, const double* /*D*/) { return true; } void PowerSeriesExpansionPreconditioner::RightMultiplyAndAccumulate( const double* x, double* y) const { VectorRef yref(y, num_rows()); Vector series_term(num_rows()); Vector previous_series_term(num_rows()); ParallelSetZero(options_.context, options_.num_threads, yref); isc_->block_diagonal_FtF_inverse()->RightMultiplyAndAccumulate( x, y, options_.context, options_.num_threads); ParallelAssign( options_.context, options_.num_threads, previous_series_term, yref); const double norm_threshold = spse_tolerance_ * Norm(yref, options_.context, options_.num_threads); for (int i = 1;; i++) { ParallelSetZero(options_.context, options_.num_threads, series_term); isc_->InversePowerSeriesOperatorRightMultiplyAccumulate( previous_series_term.data(), series_term.data()); ParallelAssign( options_.context, options_.num_threads, yref, yref + series_term); if (i >= max_num_spse_iterations_ || series_term.norm() < norm_threshold) { break; } std::swap(previous_series_term, series_term); } } int PowerSeriesExpansionPreconditioner::num_rows() const { return isc_->num_rows(); } } // namespace ceres::internal