// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2015 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: keir@google.com (Keir Mierle) #include "ceres/block_jacobi_preconditioner.h" #include "ceres/block_sparse_matrix.h" #include "ceres/block_structure.h" #include "ceres/block_random_access_diagonal_matrix.h" #include "ceres/casts.h" #include "ceres/integral_types.h" #include "ceres/internal/eigen.h" namespace ceres { namespace internal { BlockJacobiPreconditioner::BlockJacobiPreconditioner( const BlockSparseMatrix& A) { const CompressedRowBlockStructure* bs = A.block_structure(); std::vector blocks(bs->cols.size()); for (int i = 0; i < blocks.size(); ++i) { blocks[i] = bs->cols[i].size; } m_.reset(new BlockRandomAccessDiagonalMatrix(blocks)); } BlockJacobiPreconditioner::~BlockJacobiPreconditioner() {} bool BlockJacobiPreconditioner::UpdateImpl(const BlockSparseMatrix& A, const double* D) { const CompressedRowBlockStructure* bs = A.block_structure(); const double* values = A.values(); m_->SetZero(); for (int i = 0; i < bs->rows.size(); ++i) { const int row_block_size = bs->rows[i].block.size; const std::vector& cells = bs->rows[i].cells; for (int j = 0; j < cells.size(); ++j) { const int block_id = cells[j].block_id; const int col_block_size = bs->cols[block_id].size; int r, c, row_stride, col_stride; CellInfo* cell_info = m_->GetCell(block_id, block_id, &r, &c, &row_stride, &col_stride); MatrixRef m(cell_info->values, row_stride, col_stride); ConstMatrixRef b(values + cells[j].position, row_block_size, col_block_size); m.block(r, c, col_block_size, col_block_size) += b.transpose() * b; } } if (D != NULL) { // Add the diagonal. int position = 0; for (int i = 0; i < bs->cols.size(); ++i) { const int block_size = bs->cols[i].size; int r, c, row_stride, col_stride; CellInfo* cell_info = m_->GetCell(i, i, &r, &c, &row_stride, &col_stride); MatrixRef m(cell_info->values, row_stride, col_stride); m.block(r, c, block_size, block_size).diagonal() += ConstVectorRef(D + position, block_size).array().square().matrix(); position += block_size; } } m_->Invert(); return true; } void BlockJacobiPreconditioner::RightMultiply(const double* x, double* y) const { m_->RightMultiply(x, y); } } // namespace internal } // namespace ceres