| 123456789101112131415161718192021222324252627282930313233343536373839404142434445464748495051525354555657585960616263646566676869707172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129 | // 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: sameeragarwal@google.com (Sameer Agarwal)#ifndef CERES_INTERNAL_BLOCK_RANDOM_ACCESS_SPARSE_MATRIX_H_#define CERES_INTERNAL_BLOCK_RANDOM_ACCESS_SPARSE_MATRIX_H_#include <cstdint>#include <memory>#include <set>#include <unordered_map>#include <utility>#include <vector>#include "ceres/block_random_access_matrix.h"#include "ceres/triplet_sparse_matrix.h"#include "ceres/internal/port.h"#include "ceres/types.h"#include "ceres/small_blas.h"namespace ceres {namespace internal {// A thread safe square block sparse implementation of// BlockRandomAccessMatrix. Internally a TripletSparseMatrix is used// for doing the actual storage. This class augments this matrix with// an unordered_map that allows random read/write access.class BlockRandomAccessSparseMatrix : public BlockRandomAccessMatrix { public:  // blocks is an array of block sizes. block_pairs is a set of  // <row_block_id, col_block_id> pairs to identify the non-zero cells  // of this matrix.  BlockRandomAccessSparseMatrix(      const std::vector<int>& blocks,      const std::set<std::pair<int, int>>& block_pairs);  BlockRandomAccessSparseMatrix(const BlockRandomAccessSparseMatrix&) = delete;  void operator=(const BlockRandomAccessSparseMatrix&) = delete;  // The destructor is not thread safe. It assumes that no one is  // modifying any cells when the matrix is being destroyed.  virtual ~BlockRandomAccessSparseMatrix();  // BlockRandomAccessMatrix Interface.  CellInfo* GetCell(int row_block_id,                    int col_block_id,                    int* row,                    int* col,                    int* row_stride,                    int* col_stride) final;  // This is not a thread safe method, it assumes that no cell is  // locked.  void SetZero() final;  // Assume that the matrix is symmetric and only one half of the  // matrix is stored.  //  // y += S * x  void SymmetricRightMultiply(const double* x, double* y) const;  // Since the matrix is square, num_rows() == num_cols().  int num_rows() const final { return tsm_->num_rows(); }  int num_cols() const final { return tsm_->num_cols(); }  // Access to the underlying matrix object.  const TripletSparseMatrix* matrix() const { return tsm_.get(); }  TripletSparseMatrix* mutable_matrix() { return tsm_.get(); } private:  int64_t IntPairToLong(int row, int col) const {    return row * kMaxRowBlocks + col;  }  void LongToIntPair(int64_t index, int* row, int* col) const {    *row = index / kMaxRowBlocks;    *col = index % kMaxRowBlocks;  }  const int64_t kMaxRowBlocks;  // row/column block sizes.  const std::vector<int> blocks_;  std::vector<int> block_positions_;  // A mapping from <row_block_id, col_block_id> to the position in  // the values array of tsm_ where the block is stored.  typedef std::unordered_map<long int, CellInfo* > LayoutType;  LayoutType layout_;  // In order traversal of contents of the matrix. This allows us to  // implement a matrix-vector which is 20% faster than using the  // iterator in the Layout object instead.  std::vector<std::pair<std::pair<int, int>, double*>> cell_values_;  // The underlying matrix object which actually stores the cells.  std::unique_ptr<TripletSparseMatrix> tsm_;  friend class BlockRandomAccessSparseMatrixTest;};}  // namespace internal}  // namespace ceres#endif  // CERES_INTERNAL_BLOCK_RANDOM_ACCESS_SPARSE_MATRIX_H_
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