1 // Ceres Solver - A fast non-linear least squares minimizer 2 // Copyright 2013 Google Inc. All rights reserved. 3 // http://code.google.com/p/ceres-solver/ 4 // 5 // Redistribution and use in source and binary forms, with or without 6 // modification, are permitted provided that the following conditions are met: 7 // 8 // * Redistributions of source code must retain the above copyright notice, 9 // this list of conditions and the following disclaimer. 10 // * Redistributions in binary form must reproduce the above copyright notice, 11 // this list of conditions and the following disclaimer in the documentation 12 // and/or other materials provided with the distribution. 13 // * Neither the name of Google Inc. nor the names of its contributors may be 14 // used to endorse or promote products derived from this software without 15 // specific prior written permission. 16 // 17 // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" 18 // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE 19 // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE 20 // ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE 21 // LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR 22 // CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF 23 // SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS 24 // INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN 25 // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) 26 // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE 27 // POSSIBILITY OF SUCH DAMAGE. 28 // 29 // Author: sameeragarwal (at) google.com (Sameer Agarwal) 30 31 #include "ceres/compressed_col_sparse_matrix_utils.h" 32 33 #include <vector> 34 #include <algorithm> 35 #include "ceres/internal/port.h" 36 #include "glog/logging.h" 37 38 namespace ceres { 39 namespace internal { 40 41 void CompressedColumnScalarMatrixToBlockMatrix(const int* scalar_rows, 42 const int* scalar_cols, 43 const vector<int>& row_blocks, 44 const vector<int>& col_blocks, 45 vector<int>* block_rows, 46 vector<int>* block_cols) { 47 CHECK_NOTNULL(block_rows)->clear(); 48 CHECK_NOTNULL(block_cols)->clear(); 49 const int num_row_blocks = row_blocks.size(); 50 const int num_col_blocks = col_blocks.size(); 51 52 vector<int> row_block_starts(num_row_blocks); 53 for (int i = 0, cursor = 0; i < num_row_blocks; ++i) { 54 row_block_starts[i] = cursor; 55 cursor += row_blocks[i]; 56 } 57 58 // This loop extracts the block sparsity of the scalar sparse matrix 59 // It does so by iterating over the columns, but only considering 60 // the columns corresponding to the first element of each column 61 // block. Within each column, the inner loop iterates over the rows, 62 // and detects the presence of a row block by checking for the 63 // presence of a non-zero entry corresponding to its first element. 64 block_cols->push_back(0); 65 int c = 0; 66 for (int col_block = 0; col_block < num_col_blocks; ++col_block) { 67 int column_size = 0; 68 for (int idx = scalar_cols[c]; idx < scalar_cols[c + 1]; ++idx) { 69 vector<int>::const_iterator it = lower_bound(row_block_starts.begin(), 70 row_block_starts.end(), 71 scalar_rows[idx]); 72 // Since we are using lower_bound, it will return the row id 73 // where the row block starts. For everything but the first row 74 // of the block, where these values will be the same, we can 75 // skip, as we only need the first row to detect the presence of 76 // the block. 77 // 78 // For rows all but the first row in the last row block, 79 // lower_bound will return row_block_starts.end(), but those can 80 // be skipped like the rows in other row blocks too. 81 if (it == row_block_starts.end() || *it != scalar_rows[idx]) { 82 continue; 83 } 84 85 block_rows->push_back(it - row_block_starts.begin()); 86 ++column_size; 87 } 88 block_cols->push_back(block_cols->back() + column_size); 89 c += col_blocks[col_block]; 90 } 91 } 92 93 void BlockOrderingToScalarOrdering(const vector<int>& blocks, 94 const vector<int>& block_ordering, 95 vector<int>* scalar_ordering) { 96 CHECK_EQ(blocks.size(), block_ordering.size()); 97 const int num_blocks = blocks.size(); 98 99 // block_starts = [0, block1, block1 + block2 ..] 100 vector<int> block_starts(num_blocks); 101 for (int i = 0, cursor = 0; i < num_blocks ; ++i) { 102 block_starts[i] = cursor; 103 cursor += blocks[i]; 104 } 105 106 scalar_ordering->resize(block_starts.back() + blocks.back()); 107 int cursor = 0; 108 for (int i = 0; i < num_blocks; ++i) { 109 const int block_id = block_ordering[i]; 110 const int block_size = blocks[block_id]; 111 int block_position = block_starts[block_id]; 112 for (int j = 0; j < block_size; ++j) { 113 (*scalar_ordering)[cursor++] = block_position++; 114 } 115 } 116 } 117 } // namespace internal 118 } // namespace ceres 119
