// 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/
//
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// modification, are permitted provided that the following conditions are met:
//
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// this list of conditions and the following disclaimer.
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// this list of conditions and the following disclaimer in the documentation
// and/or other materials provided with the distribution.
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// used to endorse or promote products derived from this software without
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//
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/compressed_row_sparse_matrix.h"
#include <algorithm>
#include <vector>
#include "ceres/crs_matrix.h"
#include "ceres/internal/port.h"
#include "ceres/triplet_sparse_matrix.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
namespace {
// Helper functor used by the constructor for reordering the contents
// of a TripletSparseMatrix. This comparator assumes thay there are no
// duplicates in the pair of arrays rows and cols, i.e., there is no
// indices i and j (not equal to each other) s.t.
//
// rows[i] == rows[j] && cols[i] == cols[j]
//
// If this is the case, this functor will not be a StrictWeakOrdering.
struct RowColLessThan {
RowColLessThan(const int* rows, const int* cols)
: rows(rows), cols(cols) {
}
bool operator()(const int x, const int y) const {
if (rows[x] == rows[y]) {
return (cols[x] < cols[y]);
}
return (rows[x] < rows[y]);
}
const int* rows;
const int* cols;
};
} // namespace
// This constructor gives you a semi-initialized CompressedRowSparseMatrix.
CompressedRowSparseMatrix::CompressedRowSparseMatrix(int num_rows,
int num_cols,
int max_num_nonzeros) {
num_rows_ = num_rows;
num_cols_ = num_cols;
rows_.resize(num_rows + 1, 0);
cols_.resize(max_num_nonzeros, 0);
values_.resize(max_num_nonzeros, 0.0);
VLOG(1) << "# of rows: " << num_rows_
<< " # of columns: " << num_cols_
<< " max_num_nonzeros: " << cols_.size()
<< ". Allocating " << (num_rows_ + 1) * sizeof(int) + // NOLINT
cols_.size() * sizeof(int) + // NOLINT
cols_.size() * sizeof(double); // NOLINT
}
CompressedRowSparseMatrix::CompressedRowSparseMatrix(
const TripletSparseMatrix& m) {
num_rows_ = m.num_rows();
num_cols_ = m.num_cols();
rows_.resize(num_rows_ + 1, 0);
cols_.resize(m.num_nonzeros(), 0);
values_.resize(m.max_num_nonzeros(), 0.0);
// index is the list of indices into the TripletSparseMatrix m.
vector<int> index(m.num_nonzeros(), 0);
for (int i = 0; i < m.num_nonzeros(); ++i) {
index[i] = i;
}
// Sort index such that the entries of m are ordered by row and ties
// are broken by column.
sort(index.begin(), index.end(), RowColLessThan(m.rows(), m.cols()));
VLOG(1) << "# of rows: " << num_rows_
<< " # of columns: " << num_cols_
<< " max_num_nonzeros: " << cols_.size()
<< ". Allocating "
<< ((num_rows_ + 1) * sizeof(int) + // NOLINT
cols_.size() * sizeof(int) + // NOLINT
cols_.size() * sizeof(double)); // NOLINT
// Copy the contents of the cols and values array in the order given
// by index and count the number of entries in each row.
for (int i = 0; i < m.num_nonzeros(); ++i) {
const int idx = index[i];
++rows_[m.rows()[idx] + 1];
cols_[i] = m.cols()[idx];
values_[i] = m.values()[idx];
}
// Find the cumulative sum of the row counts.
for (int i = 1; i < num_rows_ + 1; ++i) {
rows_[i] += rows_[i-1];
}
CHECK_EQ(num_nonzeros(), m.num_nonzeros());
}
CompressedRowSparseMatrix::CompressedRowSparseMatrix(const double* diagonal,
int num_rows) {
CHECK_NOTNULL(diagonal);
num_rows_ = num_rows;
num_cols_ = num_rows;
rows_.resize(num_rows + 1);
cols_.resize(num_rows);
values_.resize(num_rows);
rows_[0] = 0;
for (int i = 0; i < num_rows_; ++i) {
cols_[i] = i;
values_[i] = diagonal[i];
rows_[i + 1] = i + 1;
}
CHECK_EQ(num_nonzeros(), num_rows);
}
CompressedRowSparseMatrix::~CompressedRowSparseMatrix() {
}
void CompressedRowSparseMatrix::SetZero() {
fill(values_.begin(), values_.end(), 0);
}
void CompressedRowSparseMatrix::RightMultiply(const double* x,
double* y) const {
CHECK_NOTNULL(x);
CHECK_NOTNULL(y);
for (int r = 0; r < num_rows_; ++r) {
for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
y[r] += values_[idx] * x[cols_[idx]];
}
}
}
void CompressedRowSparseMatrix::LeftMultiply(const double* x, double* y) const {
CHECK_NOTNULL(x);
CHECK_NOTNULL(y);
for (int r = 0; r < num_rows_; ++r) {
for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
y[cols_[idx]] += values_[idx] * x[r];
}
}
}
void CompressedRowSparseMatrix::SquaredColumnNorm(double* x) const {
CHECK_NOTNULL(x);
fill(x, x + num_cols_, 0.0);
for (int idx = 0; idx < rows_[num_rows_]; ++idx) {
x[cols_[idx]] += values_[idx] * values_[idx];
}
}
void CompressedRowSparseMatrix::ScaleColumns(const double* scale) {
CHECK_NOTNULL(scale);
for (int idx = 0; idx < rows_[num_rows_]; ++idx) {
values_[idx] *= scale[cols_[idx]];
}
}
void CompressedRowSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
CHECK_NOTNULL(dense_matrix);
dense_matrix->resize(num_rows_, num_cols_);
dense_matrix->setZero();
for (int r = 0; r < num_rows_; ++r) {
for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
(*dense_matrix)(r, cols_[idx]) = values_[idx];
}
}
}
void CompressedRowSparseMatrix::DeleteRows(int delta_rows) {
CHECK_GE(delta_rows, 0);
CHECK_LE(delta_rows, num_rows_);
num_rows_ -= delta_rows;
rows_.resize(num_rows_ + 1);
}
void CompressedRowSparseMatrix::AppendRows(const CompressedRowSparseMatrix& m) {
CHECK_EQ(m.num_cols(), num_cols_);
if (cols_.size() < num_nonzeros() + m.num_nonzeros()) {
cols_.resize(num_nonzeros() + m.num_nonzeros());
values_.resize(num_nonzeros() + m.num_nonzeros());
}
// Copy the contents of m into this matrix.
copy(m.cols(), m.cols() + m.num_nonzeros(), &cols_[num_nonzeros()]);
copy(m.values(), m.values() + m.num_nonzeros(), &values_[num_nonzeros()]);
rows_.resize(num_rows_ + m.num_rows() + 1);
// new_rows = [rows_, m.row() + rows_[num_rows_]]
fill(rows_.begin() + num_rows_,
rows_.begin() + num_rows_ + m.num_rows() + 1,
rows_[num_rows_]);
for (int r = 0; r < m.num_rows() + 1; ++r) {
rows_[num_rows_ + r] += m.rows()[r];
}
num_rows_ += m.num_rows();
}
void CompressedRowSparseMatrix::ToTextFile(FILE* file) const {
CHECK_NOTNULL(file);
for (int r = 0; r < num_rows_; ++r) {
for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
fprintf(file,
"% 10d % 10d %17f\n",
r,
cols_[idx],
values_[idx]);
}
}
}
void CompressedRowSparseMatrix::ToCRSMatrix(CRSMatrix* matrix) const {
matrix->num_rows = num_rows_;
matrix->num_cols = num_cols_;
matrix->rows = rows_;
matrix->cols = cols_;
matrix->values = values_;
// Trim.
matrix->rows.resize(matrix->num_rows + 1);
matrix->cols.resize(matrix->rows[matrix->num_rows]);
matrix->values.resize(matrix->rows[matrix->num_rows]);
}
void CompressedRowSparseMatrix::SolveLowerTriangularInPlace(
double* solution) const {
for (int r = 0; r < num_rows_; ++r) {
for (int idx = rows_[r]; idx < rows_[r + 1] - 1; ++idx) {
solution[r] -= values_[idx] * solution[cols_[idx]];
}
solution[r] /= values_[rows_[r + 1] - 1];
}
}
void CompressedRowSparseMatrix::SolveLowerTriangularTransposeInPlace(
double* solution) const {
for (int r = num_rows_ - 1; r >= 0; --r) {
solution[r] /= values_[rows_[r + 1] - 1];
for (int idx = rows_[r + 1] - 2; idx >= rows_[r]; --idx) {
solution[cols_[idx]] -= values_[idx] * solution[r];
}
}
}
CompressedRowSparseMatrix* CompressedRowSparseMatrix::CreateBlockDiagonalMatrix(
const double* diagonal,
const vector<int>& blocks) {
int num_rows = 0;
int num_nonzeros = 0;
for (int i = 0; i < blocks.size(); ++i) {
num_rows += blocks[i];
num_nonzeros += blocks[i] * blocks[i];
}
CompressedRowSparseMatrix* matrix =
new CompressedRowSparseMatrix(num_rows, num_rows, num_nonzeros);
int* rows = matrix->mutable_rows();
int* cols = matrix->mutable_cols();
double* values = matrix->mutable_values();
fill(values, values + num_nonzeros, 0.0);
int idx_cursor = 0;
int col_cursor = 0;
for (int i = 0; i < blocks.size(); ++i) {
const int block_size = blocks[i];
for (int r = 0; r < block_size; ++r) {
*(rows++) = idx_cursor;
values[idx_cursor + r] = diagonal[col_cursor + r];
for (int c = 0; c < block_size; ++c, ++idx_cursor) {
*(cols++) = col_cursor + c;
}
}
col_cursor += block_size;
}
*rows = idx_cursor;
*matrix->mutable_row_blocks() = blocks;
*matrix->mutable_col_blocks() = blocks;
CHECK_EQ(idx_cursor, num_nonzeros);
CHECK_EQ(col_cursor, num_rows);
return matrix;
}
CompressedRowSparseMatrix* CompressedRowSparseMatrix::Transpose() const {
CompressedRowSparseMatrix* transpose =
new CompressedRowSparseMatrix(num_cols_, num_rows_, num_nonzeros());
int* transpose_rows = transpose->mutable_rows();
int* transpose_cols = transpose->mutable_cols();
double* transpose_values = transpose->mutable_values();
for (int idx = 0; idx < num_nonzeros(); ++idx) {
++transpose_rows[cols_[idx] + 1];
}
for (int i = 1; i < transpose->num_rows() + 1; ++i) {
transpose_rows[i] += transpose_rows[i - 1];
}
for (int r = 0; r < num_rows(); ++r) {
for (int idx = rows_[r]; idx < rows_[r + 1]; ++idx) {
const int c = cols_[idx];
const int transpose_idx = transpose_rows[c]++;
transpose_cols[transpose_idx] = r;
transpose_values[transpose_idx] = values_[idx];
}
}
for (int i = transpose->num_rows() - 1; i > 0 ; --i) {
transpose_rows[i] = transpose_rows[i - 1];
}
transpose_rows[0] = 0;
return transpose;
}
} // namespace internal
} // namespace ceres