// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2012 Google Inc. All rights reserved. // http://code.google.com/p/ceres-solver/ // // 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: keir@google.com (Keir Mierle) #ifndef CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_ #define CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_ #include <vector> #include "ceres/linear_operator.h" namespace ceres { namespace internal { struct CompressedRowBlockStructure; class LinearOperator; class SparseMatrix; // A block Jacobi preconditioner. This is intended for use with conjugate // gradients, or other iterative symmetric solvers. To use the preconditioner, // create one by passing a BlockSparseMatrix as the linear operator "A" to the // constructor. This fixes the sparsity pattern to the pattern of the matrix // A^TA. // // Before each use of the preconditioner in a solve with conjugate gradients, // update the matrix by running Update(A, D). The values of the matrix A are // inspected to construct the preconditioner. The vector D is applied as the // D^TD diagonal term. class BlockJacobiPreconditioner : public LinearOperator { public: // A must remain valid while the BlockJacobiPreconditioner is. BlockJacobiPreconditioner(const LinearOperator& A); virtual ~BlockJacobiPreconditioner(); // Update the preconditioner with the values found in A. The sparsity pattern // must match that of the A passed to the constructor. D is a vector that // must have the same number of rows as A, and is applied as a diagonal in // addition to the block diagonals of A. void Update(const LinearOperator& A, const double* D); // LinearOperator interface. virtual void RightMultiply(const double* x, double* y) const; virtual void LeftMultiply(const double* x, double* y) const; virtual int num_rows() const { return num_rows_; } virtual int num_cols() const { return num_rows_; } private: std::vector<double*> blocks_; std::vector<double> block_storage_; int num_rows_; // The block structure of the matrix this preconditioner is for (e.g. J). const CompressedRowBlockStructure& block_structure_; }; } // namespace internal } // namespace ceres #endif // CERES_INTERNAL_BLOCK_JACOBI_PRECONDITIONER_H_