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// 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
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// 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_dense_matrix.h"
#include <utility>
#include <vector>
#include "ceres/internal/eigen.h"
#include "ceres/parallel_vector_ops.h"
#include "glog/logging.h"
namespace ceres::internal {
BlockRandomAccessDenseMatrix::BlockRandomAccessDenseMatrix(
std::vector<Block> blocks, ContextImpl* context, int num_threads)
: blocks_(std::move(blocks)), context_(context), num_threads_(num_threads) {
const int num_blocks = blocks_.size();
num_rows_ = NumScalarEntries(blocks_);
values_ = std::make_unique<double[]>(num_rows_ * num_rows_);
cell_infos_ = std::make_unique<CellInfo[]>(num_blocks * num_blocks);
for (int i = 0; i < num_blocks * num_blocks; ++i) {
cell_infos_[i].values = values_.get();
}
SetZero();
}
CellInfo* BlockRandomAccessDenseMatrix::GetCell(const int row_block_id,
const int col_block_id,
int* row,
int* col,
int* row_stride,
int* col_stride) {
*row = blocks_[row_block_id].position;
*col = blocks_[col_block_id].position;
*row_stride = num_rows_;
*col_stride = num_rows_;
return &cell_infos_[row_block_id * blocks_.size() + col_block_id];
}
// Assume that the user does not hold any locks on any cell blocks
// when they are calling SetZero.
void BlockRandomAccessDenseMatrix::SetZero() {
ParallelSetZero(context_, num_threads_, values_.get(), num_rows_ * num_rows_);
}
} // namespace ceres::internal