// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2010, 2011, 2012 Google Inc. All rights reserved.
// http://code.google.com/p/ceres-solver/
//
// 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
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// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/block_sparse_matrix.h"
#include <cstddef>
#include <algorithm>
#include <vector>
#include "ceres/block_structure.h"
#include "ceres/internal/eigen.h"
#include "ceres/small_blas.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
BlockSparseMatrix::~BlockSparseMatrix() {}
BlockSparseMatrix::BlockSparseMatrix(
CompressedRowBlockStructure* block_structure)
: num_rows_(0),
num_cols_(0),
num_nonzeros_(0),
values_(NULL),
block_structure_(block_structure) {
CHECK_NOTNULL(block_structure_.get());
// Count the number of columns in the matrix.
for (int i = 0; i < block_structure_->cols.size(); ++i) {
num_cols_ += block_structure_->cols[i].size;
}
// Count the number of non-zero entries and the number of rows in
// the matrix.
for (int i = 0; i < block_structure_->rows.size(); ++i) {
int row_block_size = block_structure_->rows[i].block.size;
num_rows_ += row_block_size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
int col_block_id = cells[j].block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
num_nonzeros_ += col_block_size * row_block_size;
}
}
CHECK_GE(num_rows_, 0);
CHECK_GE(num_cols_, 0);
CHECK_GE(num_nonzeros_, 0);
VLOG(2) << "Allocating values array with "
<< num_nonzeros_ * sizeof(double) << " bytes."; // NOLINT
values_.reset(new double[num_nonzeros_]);
CHECK_NOTNULL(values_.get());
}
void BlockSparseMatrix::SetZero() {
fill(values_.get(), values_.get() + num_nonzeros_, 0.0);
}
void BlockSparseMatrix::RightMultiply(const double* x, double* y) const {
CHECK_NOTNULL(x);
CHECK_NOTNULL(y);
for (int i = 0; i < block_structure_->rows.size(); ++i) {
int row_block_pos = block_structure_->rows[i].block.position;
int row_block_size = block_structure_->rows[i].block.size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
int col_block_id = cells[j].block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
MatrixVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
values_.get() + cells[j].position, row_block_size, col_block_size,
x + col_block_pos,
y + row_block_pos);
}
}
}
void BlockSparseMatrix::LeftMultiply(const double* x, double* y) const {
CHECK_NOTNULL(x);
CHECK_NOTNULL(y);
for (int i = 0; i < block_structure_->rows.size(); ++i) {
int row_block_pos = block_structure_->rows[i].block.position;
int row_block_size = block_structure_->rows[i].block.size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
int col_block_id = cells[j].block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
MatrixTransposeVectorMultiply<Eigen::Dynamic, Eigen::Dynamic, 1>(
values_.get() + cells[j].position, row_block_size, col_block_size,
x + row_block_pos,
y + col_block_pos);
}
}
}
void BlockSparseMatrix::SquaredColumnNorm(double* x) const {
CHECK_NOTNULL(x);
VectorRef(x, num_cols_).setZero();
for (int i = 0; i < block_structure_->rows.size(); ++i) {
int row_block_size = block_structure_->rows[i].block.size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
int col_block_id = cells[j].block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
const MatrixRef m(values_.get() + cells[j].position,
row_block_size, col_block_size);
VectorRef(x + col_block_pos, col_block_size) += m.colwise().squaredNorm();
}
}
}
void BlockSparseMatrix::ScaleColumns(const double* scale) {
CHECK_NOTNULL(scale);
for (int i = 0; i < block_structure_->rows.size(); ++i) {
int row_block_size = block_structure_->rows[i].block.size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
int col_block_id = cells[j].block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
MatrixRef m(values_.get() + cells[j].position,
row_block_size, col_block_size);
m *= ConstVectorRef(scale + col_block_pos, col_block_size).asDiagonal();
}
}
}
void BlockSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
CHECK_NOTNULL(dense_matrix);
dense_matrix->resize(num_rows_, num_cols_);
dense_matrix->setZero();
Matrix& m = *dense_matrix;
for (int i = 0; i < block_structure_->rows.size(); ++i) {
int row_block_pos = block_structure_->rows[i].block.position;
int row_block_size = block_structure_->rows[i].block.size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
int col_block_id = cells[j].block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
int jac_pos = cells[j].position;
m.block(row_block_pos, col_block_pos, row_block_size, col_block_size)
+= MatrixRef(values_.get() + jac_pos, row_block_size, col_block_size);
}
}
}
void BlockSparseMatrix::ToTripletSparseMatrix(
TripletSparseMatrix* matrix) const {
CHECK_NOTNULL(matrix);
matrix->Reserve(num_nonzeros_);
matrix->Resize(num_rows_, num_cols_);
matrix->SetZero();
for (int i = 0; i < block_structure_->rows.size(); ++i) {
int row_block_pos = block_structure_->rows[i].block.position;
int row_block_size = block_structure_->rows[i].block.size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
int col_block_id = cells[j].block_id;
int col_block_size = block_structure_->cols[col_block_id].size;
int col_block_pos = block_structure_->cols[col_block_id].position;
int jac_pos = cells[j].position;
for (int r = 0; r < row_block_size; ++r) {
for (int c = 0; c < col_block_size; ++c, ++jac_pos) {
matrix->mutable_rows()[jac_pos] = row_block_pos + r;
matrix->mutable_cols()[jac_pos] = col_block_pos + c;
matrix->mutable_values()[jac_pos] = values_[jac_pos];
}
}
}
}
matrix->set_num_nonzeros(num_nonzeros_);
}
// Return a pointer to the block structure. We continue to hold
// ownership of the object though.
const CompressedRowBlockStructure* BlockSparseMatrix::block_structure()
const {
return block_structure_.get();
}
void BlockSparseMatrix::ToTextFile(FILE* file) const {
CHECK_NOTNULL(file);
for (int i = 0; i < block_structure_->rows.size(); ++i) {
const int row_block_pos = block_structure_->rows[i].block.position;
const int row_block_size = block_structure_->rows[i].block.size;
const vector<Cell>& cells = block_structure_->rows[i].cells;
for (int j = 0; j < cells.size(); ++j) {
const int col_block_id = cells[j].block_id;
const int col_block_size = block_structure_->cols[col_block_id].size;
const int col_block_pos = block_structure_->cols[col_block_id].position;
int jac_pos = cells[j].position;
for (int r = 0; r < row_block_size; ++r) {
for (int c = 0; c < col_block_size; ++c) {
fprintf(file, "% 10d % 10d %17f\n",
row_block_pos + r,
col_block_pos + c,
values_[jac_pos++]);
}
}
}
}
}
} // namespace internal
} // namespace ceres