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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
// 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/compressed_col_sparse_matrix_utils.h"
#include <algorithm>
#include <vector>
#include "ceres/internal/export.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
using std::vector;
void CompressedColumnScalarMatrixToBlockMatrix(const int* scalar_rows,
const int* scalar_cols,
const vector<int>& row_blocks,
const vector<int>& col_blocks,
vector<int>* block_rows,
vector<int>* block_cols) {
CHECK(block_rows != nullptr);
CHECK(block_cols != nullptr);
block_rows->clear();
block_cols->clear();
const int num_row_blocks = row_blocks.size();
const int num_col_blocks = col_blocks.size();
vector<int> row_block_starts(num_row_blocks);
for (int i = 0, cursor = 0; i < num_row_blocks; ++i) {
row_block_starts[i] = cursor;
cursor += row_blocks[i];
}
// This loop extracts the block sparsity of the scalar sparse matrix
// It does so by iterating over the columns, but only considering
// the columns corresponding to the first element of each column
// block. Within each column, the inner loop iterates over the rows,
// and detects the presence of a row block by checking for the
// presence of a non-zero entry corresponding to its first element.
block_cols->push_back(0);
int c = 0;
for (int col_block = 0; col_block < num_col_blocks; ++col_block) {
int column_size = 0;
for (int idx = scalar_cols[c]; idx < scalar_cols[c + 1]; ++idx) {
vector<int>::const_iterator it = std::lower_bound(
row_block_starts.begin(), row_block_starts.end(), scalar_rows[idx]);
// Since we are using lower_bound, it will return the row id
// where the row block starts. For everything but the first row
// of the block, where these values will be the same, we can
// skip, as we only need the first row to detect the presence of
// the block.
//
// For rows all but the first row in the last row block,
// lower_bound will return row_block_starts.end(), but those can
// be skipped like the rows in other row blocks too.
if (it == row_block_starts.end() || *it != scalar_rows[idx]) {
continue;
}
block_rows->push_back(it - row_block_starts.begin());
++column_size;
}
block_cols->push_back(block_cols->back() + column_size);
c += col_blocks[col_block];
}
}
void BlockOrderingToScalarOrdering(const vector<int>& blocks,
const vector<int>& block_ordering,
vector<int>* scalar_ordering) {
CHECK_EQ(blocks.size(), block_ordering.size());
const int num_blocks = blocks.size();
// block_starts = [0, block1, block1 + block2 ..]
vector<int> block_starts(num_blocks);
for (int i = 0, cursor = 0; i < num_blocks; ++i) {
block_starts[i] = cursor;
cursor += blocks[i];
}
scalar_ordering->resize(block_starts.back() + blocks.back());
int cursor = 0;
for (int i = 0; i < num_blocks; ++i) {
const int block_id = block_ordering[i];
const int block_size = blocks[block_id];
int block_position = block_starts[block_id];
for (int j = 0; j < block_size; ++j) {
(*scalar_ordering)[cursor++] = block_position++;
}
}
}
} // namespace internal
} // namespace ceres
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