139 lines
5.3 KiB
C++
139 lines
5.3 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2012 Google Inc. All rights reserved.
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// http://code.google.com/p/ceres-solver/
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//
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// Redistribution and use in source and binary forms, with or without
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// modification, are permitted provided that the following conditions are met:
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//
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// * Redistributions of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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// * Redistributions in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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// * Neither the name of Google Inc. nor the names of its contributors may be
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// used to endorse or promote products derived from this software without
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// specific prior written permission.
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//
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// THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
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// AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
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// IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
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// ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE
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// LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
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// CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF
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// SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS
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// INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN
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// CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
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// ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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// POSSIBILITY OF SUCH DAMAGE.
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//
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// Author: keir@google.com (Keir Mierle)
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#include "ceres/block_jacobi_preconditioner.h"
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#include "Eigen/Cholesky"
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#include "ceres/block_sparse_matrix.h"
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#include "ceres/block_structure.h"
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#include "ceres/casts.h"
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#include "ceres/integral_types.h"
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#include "ceres/internal/eigen.h"
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namespace ceres {
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namespace internal {
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BlockJacobiPreconditioner::BlockJacobiPreconditioner(
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const BlockSparseMatrix& A)
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: num_rows_(A.num_rows()),
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block_structure_(*A.block_structure()) {
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// Calculate the amount of storage needed.
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int storage_needed = 0;
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for (int c = 0; c < block_structure_.cols.size(); ++c) {
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int size = block_structure_.cols[c].size;
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storage_needed += size * size;
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}
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// Size the offsets and storage.
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blocks_.resize(block_structure_.cols.size());
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block_storage_.resize(storage_needed);
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// Put pointers to the storage in the offsets.
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double* block_cursor = &block_storage_[0];
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for (int c = 0; c < block_structure_.cols.size(); ++c) {
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int size = block_structure_.cols[c].size;
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blocks_[c] = block_cursor;
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block_cursor += size * size;
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}
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}
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BlockJacobiPreconditioner::~BlockJacobiPreconditioner() {}
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bool BlockJacobiPreconditioner::UpdateImpl(const BlockSparseMatrix& A,
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const double* D) {
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const CompressedRowBlockStructure* bs = A.block_structure();
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// Compute the diagonal blocks by block inner products.
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std::fill(block_storage_.begin(), block_storage_.end(), 0.0);
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const double* values = A.values();
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for (int r = 0; r < bs->rows.size(); ++r) {
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const int row_block_size = bs->rows[r].block.size;
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const vector<Cell>& cells = bs->rows[r].cells;
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for (int c = 0; c < cells.size(); ++c) {
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const int col_block_size = bs->cols[cells[c].block_id].size;
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ConstMatrixRef m(values + cells[c].position,
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row_block_size,
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col_block_size);
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MatrixRef(blocks_[cells[c].block_id],
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col_block_size,
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col_block_size).noalias() += m.transpose() * m;
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// TODO(keir): Figure out when the below expression is actually faster
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// than doing the full rank update. The issue is that for smaller sizes,
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// the rankUpdate() function is slower than the full product done above.
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//
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// On the typical bundling problems, the above product is ~5% faster.
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//
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// MatrixRef(blocks_[cells[c].block_id],
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// col_block_size,
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// col_block_size)
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// .selfadjointView<Eigen::Upper>()
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// .rankUpdate(m);
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//
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}
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}
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// Add the diagonal and invert each block.
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for (int c = 0; c < bs->cols.size(); ++c) {
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const int size = block_structure_.cols[c].size;
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const int position = block_structure_.cols[c].position;
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MatrixRef block(blocks_[c], size, size);
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if (D != NULL) {
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block.diagonal() +=
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ConstVectorRef(D + position, size).array().square().matrix();
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}
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block = block.selfadjointView<Eigen::Upper>()
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.llt()
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.solve(Matrix::Identity(size, size));
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}
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return true;
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}
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void BlockJacobiPreconditioner::RightMultiply(const double* x,
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double* y) const {
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for (int c = 0; c < block_structure_.cols.size(); ++c) {
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const int size = block_structure_.cols[c].size;
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const int position = block_structure_.cols[c].position;
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ConstMatrixRef D(blocks_[c], size, size);
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ConstVectorRef x_block(x + position, size);
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VectorRef y_block(y + position, size);
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y_block += D * x_block;
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}
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}
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void BlockJacobiPreconditioner::LeftMultiply(const double* x, double* y) const {
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RightMultiply(x, y);
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}
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} // namespace internal
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} // namespace ceres
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