// Ceres Solver - A fast non-linear least squares minimizer // Copyright 2010, 2011, 2012 Google Inc. All rights reserved. // http://code.google.com/p/ceres-solver/ // // 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_sparse_matrix.h" #include <algorithm> #include <set> #include <utility> #include <vector> #include "ceres/internal/port.h" #include "ceres/internal/scoped_ptr.h" #include "ceres/mutex.h" #include "ceres/triplet_sparse_matrix.h" #include "ceres/types.h" #include "glog/logging.h" namespace ceres { namespace internal { BlockRandomAccessSparseMatrix::BlockRandomAccessSparseMatrix( const vector<int>& blocks, const set<pair<int, int> >& block_pairs) : kMaxRowBlocks(10 * 1000 * 1000), blocks_(blocks) { CHECK_LT(blocks.size(), kMaxRowBlocks); // Build the row/column layout vector and count the number of scalar // rows/columns. int num_cols = 0; vector<int> col_layout; for (int i = 0; i < blocks_.size(); ++i) { col_layout.push_back(num_cols); num_cols += blocks_[i]; } // Count the number of scalar non-zero entries and build the layout // object for looking into the values array of the // TripletSparseMatrix. int num_nonzeros = 0; for (set<pair<int, int> >::const_iterator it = block_pairs.begin(); it != block_pairs.end(); ++it) { const int row_block_size = blocks_[it->first]; const int col_block_size = blocks_[it->second]; num_nonzeros += row_block_size * col_block_size; } VLOG(1) << "Matrix Size [" << num_cols << "," << num_cols << "] " << num_nonzeros; tsm_.reset(new TripletSparseMatrix(num_cols, num_cols, num_nonzeros)); tsm_->set_num_nonzeros(num_nonzeros); int* rows = tsm_->mutable_rows(); int* cols = tsm_->mutable_cols(); double* values = tsm_->mutable_values(); int pos = 0; for (set<pair<int, int> >::const_iterator it = block_pairs.begin(); it != block_pairs.end(); ++it) { const int row_block_size = blocks_[it->first]; const int col_block_size = blocks_[it->second]; layout_[IntPairToLong(it->first, it->second)] = new CellInfo(values + pos); pos += row_block_size * col_block_size; } // Fill the sparsity pattern of the underlying matrix. for (set<pair<int, int> >::const_iterator it = block_pairs.begin(); it != block_pairs.end(); ++it) { const int row_block_id = it->first; const int col_block_id = it->second; const int row_block_size = blocks_[row_block_id]; const int col_block_size = blocks_[col_block_id]; int pos = layout_[IntPairToLong(row_block_id, col_block_id)]->values - values; for (int r = 0; r < row_block_size; ++r) { for (int c = 0; c < col_block_size; ++c, ++pos) { rows[pos] = col_layout[row_block_id] + r; cols[pos] = col_layout[col_block_id] + c; values[pos] = 1.0; DCHECK_LT(rows[pos], tsm_->num_rows()); DCHECK_LT(cols[pos], tsm_->num_rows()); } } } } // Assume that the user does not hold any locks on any cell blocks // when they are calling SetZero. BlockRandomAccessSparseMatrix::~BlockRandomAccessSparseMatrix() { for (LayoutType::iterator it = layout_.begin(); it != layout_.end(); ++it) { delete it->second; } } CellInfo* BlockRandomAccessSparseMatrix::GetCell(int row_block_id, int col_block_id, int* row, int* col, int* row_stride, int* col_stride) { const LayoutType::iterator it = layout_.find(IntPairToLong(row_block_id, col_block_id)); if (it == layout_.end()) { return NULL; } // Each cell is stored contiguously as its own little dense matrix. *row = 0; *col = 0; *row_stride = blocks_[row_block_id]; *col_stride = blocks_[col_block_id]; return it->second; } // Assume that the user does not hold any locks on any cell blocks // when they are calling SetZero. void BlockRandomAccessSparseMatrix::SetZero() { if (tsm_->num_nonzeros()) { VectorRef(tsm_->mutable_values(), tsm_->num_nonzeros()).setZero(); } } } // namespace internal } // namespace ceres