| 1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374757677787980818283848586878889909192939495969798 | // 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)//// Block structure objects are used to carry information about the// dense block structure of sparse matrices. The BlockSparseMatrix// object uses the BlockStructure objects to keep track of the matrix// structure and operate upon it. This allows us to use more cache// friendly block oriented linear algebra operations on the matrix// instead of accessing it one scalar entry at a time.#ifndef CERES_INTERNAL_BLOCK_STRUCTURE_H_#define CERES_INTERNAL_BLOCK_STRUCTURE_H_#include <vector>#include "ceres/internal/port.h"#include "ceres/types.h"namespace ceres {namespace internal {typedef int32 BlockSize;struct Block {  Block() : size(-1), position(-1) {}  Block(int size_, int position_) : size(size_), position(position_) {}  BlockSize size;  int position;  // Position along the row/column.};struct Cell {  Cell() : block_id(-1), position(-1) {}  Cell(int block_id_, int position_)      : block_id(block_id_), position(position_) {}  // Column or row block id as the case maybe.  int block_id;  // Where in the values array of the jacobian is this cell located.  int position;};// Order cell by their block_id;bool CellLessThan(const Cell& lhs, const Cell& rhs);struct CompressedList {  CompressedList() {}  // Construct a CompressedList with the cells containing num_cells  // entries.  CompressedList(int num_cells) : cells(num_cells) {}  Block block;  std::vector<Cell> cells;};typedef CompressedList CompressedRow;typedef CompressedList CompressedColumn;struct CompressedRowBlockStructure {  std::vector<Block> cols;  std::vector<CompressedRow> rows;};struct CompressedColumnBlockStructure {  std::vector<Block> rows;  std::vector<CompressedColumn> cols;};}  // namespace internal}  // namespace ceres#endif  // CERES_INTERNAL_BLOCK_STRUCTURE_H_
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