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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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// POSSIBILITY OF SUCH DAMAGE.
//
// Author: keir@google.com (Keir Mierle)
#include "ceres/dense_sparse_matrix.h"
#include <algorithm>
#include "ceres/internal/eigen.h"
#include "ceres/internal/port.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
DenseSparseMatrix::DenseSparseMatrix(int num_rows, int num_cols)
: has_diagonal_appended_(false), has_diagonal_reserved_(false) {
m_.resize(num_rows, num_cols);
m_.setZero();
}
DenseSparseMatrix::DenseSparseMatrix(int num_rows,
int num_cols,
bool reserve_diagonal)
: has_diagonal_appended_(false), has_diagonal_reserved_(reserve_diagonal) {
if (reserve_diagonal) {
// Allocate enough space for the diagonal.
m_.resize(num_rows + num_cols, num_cols);
} else {
m_.resize(num_rows, num_cols);
}
m_.setZero();
}
DenseSparseMatrix::DenseSparseMatrix(const TripletSparseMatrix& m)
: m_(Eigen::MatrixXd::Zero(m.num_rows(), m.num_cols())),
has_diagonal_appended_(false),
has_diagonal_reserved_(false) {
const double* values = m.values();
const int* rows = m.rows();
const int* cols = m.cols();
int num_nonzeros = m.num_nonzeros();
for (int i = 0; i < num_nonzeros; ++i) {
m_(rows[i], cols[i]) += values[i];
}
}
DenseSparseMatrix::DenseSparseMatrix(const ColMajorMatrix& m)
: m_(m), has_diagonal_appended_(false), has_diagonal_reserved_(false) {}
void DenseSparseMatrix::SetZero() { m_.setZero(); }
void DenseSparseMatrix::RightMultiply(const double* x, double* y) const {
VectorRef(y, num_rows()) += matrix() * ConstVectorRef(x, num_cols());
}
void DenseSparseMatrix::LeftMultiply(const double* x, double* y) const {
VectorRef(y, num_cols()) +=
matrix().transpose() * ConstVectorRef(x, num_rows());
}
void DenseSparseMatrix::SquaredColumnNorm(double* x) const {
VectorRef(x, num_cols()) = m_.colwise().squaredNorm();
}
void DenseSparseMatrix::ScaleColumns(const double* scale) {
m_ *= ConstVectorRef(scale, num_cols()).asDiagonal();
}
void DenseSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
*dense_matrix = m_.block(0, 0, num_rows(), num_cols());
}
void DenseSparseMatrix::AppendDiagonal(double* d) {
CHECK(!has_diagonal_appended_);
if (!has_diagonal_reserved_) {
ColMajorMatrix tmp = m_;
m_.resize(m_.rows() + m_.cols(), m_.cols());
m_.setZero();
m_.block(0, 0, tmp.rows(), tmp.cols()) = tmp;
has_diagonal_reserved_ = true;
}
m_.bottomLeftCorner(m_.cols(), m_.cols()) =
ConstVectorRef(d, m_.cols()).asDiagonal();
has_diagonal_appended_ = true;
}
void DenseSparseMatrix::RemoveDiagonal() {
CHECK(has_diagonal_appended_);
has_diagonal_appended_ = false;
// Leave the diagonal reserved.
}
int DenseSparseMatrix::num_rows() const {
if (has_diagonal_reserved_ && !has_diagonal_appended_) {
return m_.rows() - m_.cols();
}
return m_.rows();
}
int DenseSparseMatrix::num_cols() const { return m_.cols(); }
int DenseSparseMatrix::num_nonzeros() const {
if (has_diagonal_reserved_ && !has_diagonal_appended_) {
return (m_.rows() - m_.cols()) * m_.cols();
}
return m_.rows() * m_.cols();
}
ConstColMajorMatrixRef DenseSparseMatrix::matrix() const {
return ConstColMajorMatrixRef(
m_.data(),
((has_diagonal_reserved_ && !has_diagonal_appended_)
? m_.rows() - m_.cols()
: m_.rows()),
m_.cols(),
Eigen::Stride<Eigen::Dynamic, 1>(m_.rows(), 1));
}
ColMajorMatrixRef DenseSparseMatrix::mutable_matrix() {
return ColMajorMatrixRef(m_.data(),
((has_diagonal_reserved_ && !has_diagonal_appended_)
? m_.rows() - m_.cols()
: m_.rows()),
m_.cols(),
Eigen::Stride<Eigen::Dynamic, 1>(m_.rows(), 1));
}
void DenseSparseMatrix::ToTextFile(FILE* file) const {
CHECK(file != nullptr);
const int active_rows = (has_diagonal_reserved_ && !has_diagonal_appended_)
? (m_.rows() - m_.cols())
: m_.rows();
for (int r = 0; r < active_rows; ++r) {
for (int c = 0; c < m_.cols(); ++c) {
fprintf(file, "% 10d % 10d %17f\n", r, c, m_(r, c));
}
}
}
} // namespace internal
} // namespace ceres