// 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: sameeragarwal@google.com (Sameer Agarwal) #include "ceres/block_random_access_dense_matrix.h" #include #include #include "ceres/internal/eigen.h" #include "ceres/parallel_vector_ops.h" #include "glog/logging.h" namespace ceres::internal { BlockRandomAccessDenseMatrix::BlockRandomAccessDenseMatrix( std::vector blocks, ContextImpl* context, int num_threads) : blocks_(std::move(blocks)), context_(context), num_threads_(num_threads) { const int num_blocks = blocks_.size(); num_rows_ = NumScalarEntries(blocks_); values_ = std::make_unique(num_rows_ * num_rows_); cell_infos_ = std::make_unique(num_blocks * num_blocks); for (int i = 0; i < num_blocks * num_blocks; ++i) { cell_infos_[i].values = values_.get(); } SetZero(); } CellInfo* BlockRandomAccessDenseMatrix::GetCell(const int row_block_id, const int col_block_id, int* row, int* col, int* row_stride, int* col_stride) { *row = blocks_[row_block_id].position; *col = blocks_[col_block_id].position; *row_stride = num_rows_; *col_stride = num_rows_; return &cell_infos_[row_block_id * blocks_.size() + col_block_id]; } // Assume that the user does not hold any locks on any cell blocks // when they are calling SetZero. void BlockRandomAccessDenseMatrix::SetZero() { ParallelSetZero(context_, num_threads_, values_.get(), num_rows_ * num_rows_); } } // namespace ceres::internal