| // Ceres Solver - A fast non-linear least squares minimizer | |
| // Copyright 2022 Google Inc. All rights reserved. | |
| // http://ceres-solver.org/ | |
| // | |
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| // | |
| // Author: sameeragarwal@google.com (Sameer Agarwal) | |
| #include "ceres/block_random_access_diagonal_matrix.h" | |
| #include <algorithm> | |
| #include <memory> | |
| #include <set> | |
| #include <utility> | |
| #include <vector> | |
| #include "Eigen/Dense" | |
| #include "ceres/compressed_row_sparse_matrix.h" | |
| #include "ceres/internal/export.h" | |
| #include "ceres/parallel_for.h" | |
| #include "ceres/parallel_vector_ops.h" | |
| #include "ceres/stl_util.h" | |
| #include "ceres/types.h" | |
| #include "glog/logging.h" | |
| namespace ceres::internal { | |
| BlockRandomAccessDiagonalMatrix::BlockRandomAccessDiagonalMatrix( | |
| const std::vector<Block>& blocks, ContextImpl* context, int num_threads) | |
| : context_(context), num_threads_(num_threads) { | |
| m_ = CompressedRowSparseMatrix::CreateBlockDiagonalMatrix(nullptr, blocks); | |
| double* values = m_->mutable_values(); | |
| layout_.reserve(blocks.size()); | |
| for (auto& block : blocks) { | |
| layout_.emplace_back(std::make_unique<CellInfo>(values)); | |
| values += block.size * block.size; | |
| } | |
| } | |
| CellInfo* BlockRandomAccessDiagonalMatrix::GetCell(int row_block_id, | |
| int col_block_id, | |
| int* row, | |
| int* col, | |
| int* row_stride, | |
| int* col_stride) { | |
| if (row_block_id != col_block_id) { | |
| return nullptr; | |
| } | |
| auto& blocks = m_->row_blocks(); | |
| const int stride = blocks[row_block_id].size; | |
| // Each cell is stored contiguously as its own little dense matrix. | |
| *row = 0; | |
| *col = 0; | |
| *row_stride = stride; | |
| *col_stride = stride; | |
| return layout_[row_block_id].get(); | |
| } | |
| // Assume that the user does not hold any locks on any cell blocks | |
| // when they are calling SetZero. | |
| void BlockRandomAccessDiagonalMatrix::SetZero() { | |
| ParallelSetZero( | |
| context_, num_threads_, m_->mutable_values(), m_->num_nonzeros()); | |
| } | |
| void BlockRandomAccessDiagonalMatrix::Invert() { | |
| auto& blocks = m_->row_blocks(); | |
| const int num_blocks = blocks.size(); | |
| ParallelFor(context_, 0, num_blocks, num_threads_, [this, blocks](int i) { | |
| auto* cell_info = layout_[i].get(); | |
| auto& block = blocks[i]; | |
| MatrixRef b(cell_info->values, block.size, block.size); | |
| b = b.selfadjointView<Eigen::Upper>().llt().solve( | |
| Matrix::Identity(block.size, block.size)); | |
| }); | |
| } | |
| void BlockRandomAccessDiagonalMatrix::RightMultiplyAndAccumulate( | |
| const double* x, double* y) const { | |
| CHECK(x != nullptr); | |
| CHECK(y != nullptr); | |
| auto& blocks = m_->row_blocks(); | |
| const int num_blocks = blocks.size(); | |
| ParallelFor( | |
| context_, 0, num_blocks, num_threads_, [this, blocks, x, y](int i) { | |
| auto* cell_info = layout_[i].get(); | |
| auto& block = blocks[i]; | |
| ConstMatrixRef b(cell_info->values, block.size, block.size); | |
| VectorRef(y + block.position, block.size).noalias() += | |
| b * ConstVectorRef(x + block.position, block.size); | |
| }); | |
| } | |
| } // namespace ceres::internal |