mirror of
https://github.com/ceres-solver/ceres-solver.git
synced 2026-08-29 16:40:38 +08:00
Sameer Agarwal
6d06e9b98f
Like SparseCholesky, the DenseCholesky interface abstracts away the solution of dense linear systems using Cholesky factorization. This allows the client code to not worry about the type of dense linear algebra library being used. DenseNormalCholeskySolver and DenseSchurComplementSolver code is considerably simpler as a result. Change-Id: Ie15f09ee376d5f9a64609e6a55ad83e99c76352a
93 lines
3.4 KiB
C++
93 lines
3.4 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2015 Google Inc. All rights reserved.
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// http://ceres-solver.org/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
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#include "ceres/dense_normal_cholesky_solver.h"
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#include <cstddef>
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#include "Eigen/Dense"
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#include "ceres/blas.h"
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#include "ceres/dense_sparse_matrix.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/linear_solver.h"
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#include "ceres/types.h"
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#include "ceres/wall_time.h"
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namespace ceres {
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namespace internal {
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DenseNormalCholeskySolver::DenseNormalCholeskySolver(
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const LinearSolver::Options& options)
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: options_(options), cholesky_(DenseCholesky::Create(options_)) {}
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LinearSolver::Summary DenseNormalCholeskySolver::SolveImpl(
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DenseSparseMatrix* A,
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const double* b,
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const LinearSolver::PerSolveOptions& per_solve_options,
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double* x) {
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EventLogger event_logger("DenseNormalCholeskySolver::Solve");
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const int num_rows = A->num_rows();
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const int num_cols = A->num_cols();
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ConstColMajorMatrixRef Aref = A->matrix();
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Matrix lhs(num_cols, num_cols);
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lhs.setZero();
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event_logger.AddEvent("Setup");
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// lhs += A'A
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//
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// Using rankUpdate instead of GEMM, exposes the fact that its the
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// same matrix being multiplied with itself and that the product is
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// symmetric.
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lhs.selfadjointView<Eigen::Upper>().rankUpdate(Aref.transpose());
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// rhs = A'b
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Vector rhs = Aref.transpose() * ConstVectorRef(b, num_rows);
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if (per_solve_options.D != NULL) {
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ConstVectorRef D(per_solve_options.D, num_cols);
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lhs += D.array().square().matrix().asDiagonal();
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}
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event_logger.AddEvent("Product");
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LinearSolver::Summary summary;
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summary.num_iterations = 1;
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summary.termination_type = cholesky_->FactorAndSolve(
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num_cols, lhs.data(), rhs.data(), x, &summary.message);
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event_logger.AddEvent("FactorAndSolve");
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return summary;
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}
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} // namespace internal
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} // namespace ceres
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