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Diffstat (limited to 'extern/ceres/internal/ceres/compressed_col_sparse_matrix_utils.h')
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diff --git a/extern/ceres/internal/ceres/compressed_col_sparse_matrix_utils.h b/extern/ceres/internal/ceres/compressed_col_sparse_matrix_utils.h new file mode 100644 index 00000000000..da2109fba3e --- /dev/null +++ b/extern/ceres/internal/ceres/compressed_col_sparse_matrix_utils.h @@ -0,0 +1,144 @@ +// 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) + +#ifndef CERES_INTERNAL_COMPRESSED_COL_SPARSE_MATRIX_UTILS_H_ +#define CERES_INTERNAL_COMPRESSED_COL_SPARSE_MATRIX_UTILS_H_ + +#include <vector> +#include "ceres/internal/port.h" + +namespace ceres { +namespace internal { + +// Extract the block sparsity pattern of the scalar compressed columns +// matrix and return it in compressed column form. The compressed +// column form is stored in two vectors block_rows, and block_cols, +// which correspond to the row and column arrays in a compressed +// column sparse matrix. +// +// If c_ij is the block in the matrix A corresponding to row block i +// and column block j, then it is expected that A contains at least +// one non-zero entry corresponding to the top left entry of c_ij, +// as that entry is used to detect the presence of a non-zero c_ij. +void CompressedColumnScalarMatrixToBlockMatrix( + const int* scalar_rows, + const int* scalar_cols, + const std::vector<int>& row_blocks, + const std::vector<int>& col_blocks, + std::vector<int>* block_rows, + std::vector<int>* block_cols); + +// Given a set of blocks and a permutation of these blocks, compute +// the corresponding "scalar" ordering, where the scalar ordering of +// size sum(blocks). +void BlockOrderingToScalarOrdering( + const std::vector<int>& blocks, + const std::vector<int>& block_ordering, + std::vector<int>* scalar_ordering); + +// Solve the linear system +// +// R * solution = rhs +// +// Where R is an upper triangular compressed column sparse matrix. +template <typename IntegerType> +void SolveUpperTriangularInPlace(IntegerType num_cols, + const IntegerType* rows, + const IntegerType* cols, + const double* values, + double* rhs_and_solution) { + for (IntegerType c = num_cols - 1; c >= 0; --c) { + rhs_and_solution[c] /= values[cols[c + 1] - 1]; + for (IntegerType idx = cols[c]; idx < cols[c + 1] - 1; ++idx) { + const IntegerType r = rows[idx]; + const double v = values[idx]; + rhs_and_solution[r] -= v * rhs_and_solution[c]; + } + } +} + +// Solve the linear system +// +// R' * solution = rhs +// +// Where R is an upper triangular compressed column sparse matrix. +template <typename IntegerType> +void SolveUpperTriangularTransposeInPlace(IntegerType num_cols, + const IntegerType* rows, + const IntegerType* cols, + const double* values, + double* rhs_and_solution) { + for (IntegerType c = 0; c < num_cols; ++c) { + for (IntegerType idx = cols[c]; idx < cols[c + 1] - 1; ++idx) { + const IntegerType r = rows[idx]; + const double v = values[idx]; + rhs_and_solution[c] -= v * rhs_and_solution[r]; + } + rhs_and_solution[c] = rhs_and_solution[c] / values[cols[c + 1] - 1]; + } +} + +// Given a upper triangular matrix R in compressed column form, solve +// the linear system, +// +// R'R x = b +// +// Where b is all zeros except for rhs_nonzero_index, where it is +// equal to one. +// +// The function exploits this knowledge to reduce the number of +// floating point operations. +template <typename IntegerType> +void SolveRTRWithSparseRHS(IntegerType num_cols, + const IntegerType* rows, + const IntegerType* cols, + const double* values, + const int rhs_nonzero_index, + double* solution) { + std::fill(solution, solution + num_cols, 0.0); + solution[rhs_nonzero_index] = 1.0 / values[cols[rhs_nonzero_index + 1] - 1]; + + for (IntegerType c = rhs_nonzero_index + 1; c < num_cols; ++c) { + for (IntegerType idx = cols[c]; idx < cols[c + 1] - 1; ++idx) { + const IntegerType r = rows[idx]; + if (r < rhs_nonzero_index) continue; + const double v = values[idx]; + solution[c] -= v * solution[r]; + } + solution[c] = solution[c] / values[cols[c + 1] - 1]; + } + + SolveUpperTriangularInPlace(num_cols, rows, cols, values, solution); +} + +} // namespace internal +} // namespace ceres + +#endif // CERES_INTERNAL_COMPRESSED_COL_SPARSE_MATRIX_UTILS_H_ |