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https://github.com/ceres-solver/ceres-solver.git
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dd2b17d7dd
Change-Id: I6c9f50e4c006faf4e75a8f417455db18357f3187
198 lines
6.2 KiB
C++
198 lines
6.2 KiB
C++
// Ceres Solver - A fast non-linear least squares minimizer
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// Copyright 2010, 2011, 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/dense_sparse_matrix.h"
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#include <algorithm>
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#include "ceres/matrix_proto.h"
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#include "ceres/triplet_sparse_matrix.h"
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#include "ceres/internal/eigen.h"
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#include "ceres/internal/port.h"
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namespace ceres {
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namespace internal {
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DenseSparseMatrix::DenseSparseMatrix(int num_rows, int num_cols)
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: has_diagonal_appended_(false),
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has_diagonal_reserved_(false) {
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// Allocate enough space for the diagonal.
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m_.resize(num_rows, num_cols);
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m_.setZero();
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}
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DenseSparseMatrix::DenseSparseMatrix(const TripletSparseMatrix& m)
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: m_(Eigen::MatrixXd::Zero(m.num_rows(), m.num_cols())),
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has_diagonal_appended_(false),
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has_diagonal_reserved_(false) {
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const double *values = m.values();
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const int *rows = m.rows();
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const int *cols = m.cols();
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int num_nonzeros = m.num_nonzeros();
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for (int i = 0; i < num_nonzeros; ++i) {
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m_(rows[i], cols[i]) += values[i];
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}
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}
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DenseSparseMatrix::DenseSparseMatrix(const Matrix& m)
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: m_(m),
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has_diagonal_appended_(false),
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has_diagonal_reserved_(false) {
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}
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#ifndef CERES_NO_PROTOCOL_BUFFERS
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DenseSparseMatrix::DenseSparseMatrix(const SparseMatrixProto& outer_proto)
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: m_(Eigen::MatrixXd::Zero(
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outer_proto.dense_matrix().num_rows(),
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outer_proto.dense_matrix().num_cols())),
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has_diagonal_appended_(false),
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has_diagonal_reserved_(false) {
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const DenseSparseMatrixProto& proto = outer_proto.dense_matrix();
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for (int i = 0; i < m_.rows(); ++i) {
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for (int j = 0; j < m_.cols(); ++j) {
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m_(i, j) = proto.values(m_.cols() * i + j);
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}
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}
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}
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#endif
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void DenseSparseMatrix::SetZero() {
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m_.setZero();
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}
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void DenseSparseMatrix::RightMultiply(const double* x, double* y) const {
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VectorRef(y, num_rows()) += matrix() * ConstVectorRef(x, num_cols());
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}
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void DenseSparseMatrix::LeftMultiply(const double* x, double* y) const {
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VectorRef(y, num_cols()) +=
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matrix().transpose() * ConstVectorRef(x, num_rows());
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}
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void DenseSparseMatrix::SquaredColumnNorm(double* x) const {
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VectorRef(x, num_cols()) = m_.colwise().squaredNorm();
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}
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void DenseSparseMatrix::ScaleColumns(const double* scale) {
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m_ *= ConstVectorRef(scale, num_cols()).asDiagonal();
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}
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void DenseSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
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*dense_matrix = m_;
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}
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#ifndef CERES_NO_PROTOCOL_BUFFERS
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void DenseSparseMatrix::ToProto(SparseMatrixProto* outer_proto) const {
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CHECK(!has_diagonal_appended_) << "Not supported.";
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outer_proto->Clear();
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DenseSparseMatrixProto* proto = outer_proto->mutable_dense_matrix();
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proto->set_num_rows(num_rows());
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proto->set_num_cols(num_cols());
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int num_nnz = num_nonzeros();
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for (int i = 0; i < num_nnz; ++i) {
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proto->add_values(m_.data()[i]);
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}
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}
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#endif
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void DenseSparseMatrix::AppendDiagonal(double *d) {
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CHECK(!has_diagonal_appended_);
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if (!has_diagonal_reserved_) {
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Matrix tmp = m_;
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m_.resize(m_.rows() + m_.cols(), m_.cols());
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m_.setZero();
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m_.block(0, 0, tmp.rows(), tmp.cols()) = tmp;
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has_diagonal_reserved_ = true;
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}
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m_.bottomLeftCorner(m_.cols(), m_.cols()) =
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ConstVectorRef(d, m_.cols()).asDiagonal();
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has_diagonal_appended_ = true;
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}
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void DenseSparseMatrix::RemoveDiagonal() {
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CHECK(has_diagonal_appended_);
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has_diagonal_appended_ = false;
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// Leave the diagonal reserved.
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}
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int DenseSparseMatrix::num_rows() const {
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if (has_diagonal_reserved_ && !has_diagonal_appended_) {
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return m_.rows() - m_.cols();
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}
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return m_.rows();
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}
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int DenseSparseMatrix::num_cols() const {
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return m_.cols();
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}
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int DenseSparseMatrix::num_nonzeros() const {
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if (has_diagonal_reserved_ && !has_diagonal_appended_) {
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return (m_.rows() - m_.cols()) * m_.cols();
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}
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return m_.rows() * m_.cols();
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}
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ConstAlignedMatrixRef DenseSparseMatrix::matrix() const {
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if (has_diagonal_reserved_ && !has_diagonal_appended_) {
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return ConstAlignedMatrixRef(
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m_.data(), m_.rows() - m_.cols(), m_.cols());
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}
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return ConstAlignedMatrixRef(m_.data(), m_.rows(), m_.cols());
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}
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AlignedMatrixRef DenseSparseMatrix::mutable_matrix() {
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if (has_diagonal_reserved_ && !has_diagonal_appended_) {
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return AlignedMatrixRef(
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m_.data(), m_.rows() - m_.cols(), m_.cols());
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}
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return AlignedMatrixRef(m_.data(), m_.rows(), m_.cols());
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}
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void DenseSparseMatrix::ToTextFile(FILE* file) const {
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CHECK_NOTNULL(file);
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const int active_rows =
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(has_diagonal_reserved_ && !has_diagonal_appended_)
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? (m_.rows() - m_.cols())
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: m_.rows();
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for (int r = 0; r < active_rows; ++r) {
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for (int c = 0; c < m_.cols(); ++c) {
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fprintf(file, "% 10d % 10d %17f\n", r, c, m_(r, c));
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}
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}
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}
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} // namespace internal
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} // namespace ceres
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