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// Ceres Solver - A fast non-linear least squares minimizer
// Copyright 2022 Google Inc. All rights reserved.
// http://ceres-solver.org/
//
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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
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// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/triplet_sparse_matrix.h"
#include <algorithm>
#include <memory>
#include <random>
#include "ceres/compressed_row_sparse_matrix.h"
#include "ceres/crs_matrix.h"
#include "ceres/internal/eigen.h"
#include "ceres/internal/export.h"
#include "ceres/types.h"
#include "glog/logging.h"
namespace ceres::internal {
TripletSparseMatrix::TripletSparseMatrix()
: num_rows_(0), num_cols_(0), max_num_nonzeros_(0), num_nonzeros_(0) {}
TripletSparseMatrix::~TripletSparseMatrix() = default;
TripletSparseMatrix::TripletSparseMatrix(int num_rows,
int num_cols,
int max_num_nonzeros)
: num_rows_(num_rows),
num_cols_(num_cols),
max_num_nonzeros_(max_num_nonzeros),
num_nonzeros_(0) {
// All the sizes should at least be zero
CHECK_GE(num_rows, 0);
CHECK_GE(num_cols, 0);
CHECK_GE(max_num_nonzeros, 0);
AllocateMemory();
}
TripletSparseMatrix::TripletSparseMatrix(const int num_rows,
const int num_cols,
const std::vector<int>& rows,
const std::vector<int>& cols,
const std::vector<double>& values)
: num_rows_(num_rows),
num_cols_(num_cols),
max_num_nonzeros_(values.size()),
num_nonzeros_(values.size()) {
// All the sizes should at least be zero
CHECK_GE(num_rows, 0);
CHECK_GE(num_cols, 0);
CHECK_EQ(rows.size(), cols.size());
CHECK_EQ(rows.size(), values.size());
AllocateMemory();
std::copy(rows.begin(), rows.end(), rows_.get());
std::copy(cols.begin(), cols.end(), cols_.get());
std::copy(values.begin(), values.end(), values_.get());
}
TripletSparseMatrix::TripletSparseMatrix(const TripletSparseMatrix& orig)
: SparseMatrix(),
num_rows_(orig.num_rows_),
num_cols_(orig.num_cols_),
max_num_nonzeros_(orig.max_num_nonzeros_),
num_nonzeros_(orig.num_nonzeros_) {
AllocateMemory();
CopyData(orig);
}
TripletSparseMatrix& TripletSparseMatrix::operator=(
const TripletSparseMatrix& rhs) {
if (this == &rhs) {
return *this;
}
num_rows_ = rhs.num_rows_;
num_cols_ = rhs.num_cols_;
num_nonzeros_ = rhs.num_nonzeros_;
max_num_nonzeros_ = rhs.max_num_nonzeros_;
AllocateMemory();
CopyData(rhs);
return *this;
}
bool TripletSparseMatrix::AllTripletsWithinBounds() const {
for (int i = 0; i < num_nonzeros_; ++i) {
// clang-format off
if ((rows_[i] < 0) || (rows_[i] >= num_rows_) ||
(cols_[i] < 0) || (cols_[i] >= num_cols_)) {
return false;
}
// clang-format on
}
return true;
}
void TripletSparseMatrix::Reserve(int new_max_num_nonzeros) {
CHECK_LE(num_nonzeros_, new_max_num_nonzeros)
<< "Reallocation will cause data loss";
// Nothing to do if we have enough space already.
if (new_max_num_nonzeros <= max_num_nonzeros_) return;
std::unique_ptr<int[]> new_rows =
std::make_unique<int[]>(new_max_num_nonzeros);
std::unique_ptr<int[]> new_cols =
std::make_unique<int[]>(new_max_num_nonzeros);
std::unique_ptr<double[]> new_values =
std::make_unique<double[]>(new_max_num_nonzeros);
for (int i = 0; i < num_nonzeros_; ++i) {
new_rows[i] = rows_[i];
new_cols[i] = cols_[i];
new_values[i] = values_[i];
}
rows_ = std::move(new_rows);
cols_ = std::move(new_cols);
values_ = std::move(new_values);
max_num_nonzeros_ = new_max_num_nonzeros;
}
void TripletSparseMatrix::SetZero() {
std::fill(values_.get(), values_.get() + max_num_nonzeros_, 0.0);
num_nonzeros_ = 0;
}
void TripletSparseMatrix::set_num_nonzeros(int num_nonzeros) {
CHECK_GE(num_nonzeros, 0);
CHECK_LE(num_nonzeros, max_num_nonzeros_);
num_nonzeros_ = num_nonzeros;
}
void TripletSparseMatrix::AllocateMemory() {
rows_ = std::make_unique<int[]>(max_num_nonzeros_);
cols_ = std::make_unique<int[]>(max_num_nonzeros_);
values_ = std::make_unique<double[]>(max_num_nonzeros_);
}
void TripletSparseMatrix::CopyData(const TripletSparseMatrix& orig) {
for (int i = 0; i < num_nonzeros_; ++i) {
rows_[i] = orig.rows_[i];
cols_[i] = orig.cols_[i];
values_[i] = orig.values_[i];
}
}
void TripletSparseMatrix::RightMultiplyAndAccumulate(const double* x,
double* y) const {
for (int i = 0; i < num_nonzeros_; ++i) {
y[rows_[i]] += values_[i] * x[cols_[i]];
}
}
void TripletSparseMatrix::LeftMultiplyAndAccumulate(const double* x,
double* y) const {
for (int i = 0; i < num_nonzeros_; ++i) {
y[cols_[i]] += values_[i] * x[rows_[i]];
}
}
void TripletSparseMatrix::SquaredColumnNorm(double* x) const {
CHECK(x != nullptr);
VectorRef(x, num_cols_).setZero();
for (int i = 0; i < num_nonzeros_; ++i) {
x[cols_[i]] += values_[i] * values_[i];
}
}
void TripletSparseMatrix::ScaleColumns(const double* scale) {
CHECK(scale != nullptr);
for (int i = 0; i < num_nonzeros_; ++i) {
values_[i] = values_[i] * scale[cols_[i]];
}
}
void TripletSparseMatrix::ToCRSMatrix(CRSMatrix* crs_matrix) const {
CompressedRowSparseMatrix::FromTripletSparseMatrix(*this)->ToCRSMatrix(
crs_matrix);
}
void TripletSparseMatrix::ToDenseMatrix(Matrix* dense_matrix) const {
dense_matrix->resize(num_rows_, num_cols_);
dense_matrix->setZero();
Matrix& m = *dense_matrix;
for (int i = 0; i < num_nonzeros_; ++i) {
m(rows_[i], cols_[i]) += values_[i];
}
}
void TripletSparseMatrix::AppendRows(const TripletSparseMatrix& B) {
CHECK_EQ(B.num_cols(), num_cols_);
Reserve(num_nonzeros_ + B.num_nonzeros_);
for (int i = 0; i < B.num_nonzeros_; ++i) {
rows_.get()[num_nonzeros_] = B.rows()[i] + num_rows_;
cols_.get()[num_nonzeros_] = B.cols()[i];
values_.get()[num_nonzeros_++] = B.values()[i];
}
num_rows_ = num_rows_ + B.num_rows();
}
void TripletSparseMatrix::AppendCols(const TripletSparseMatrix& B) {
CHECK_EQ(B.num_rows(), num_rows_);
Reserve(num_nonzeros_ + B.num_nonzeros_);
for (int i = 0; i < B.num_nonzeros_; ++i, ++num_nonzeros_) {
rows_.get()[num_nonzeros_] = B.rows()[i];
cols_.get()[num_nonzeros_] = B.cols()[i] + num_cols_;
values_.get()[num_nonzeros_] = B.values()[i];
}
num_cols_ = num_cols_ + B.num_cols();
}
void TripletSparseMatrix::Resize(int new_num_rows, int new_num_cols) {
if ((new_num_rows >= num_rows_) && (new_num_cols >= num_cols_)) {
num_rows_ = new_num_rows;
num_cols_ = new_num_cols;
return;
}
num_rows_ = new_num_rows;
num_cols_ = new_num_cols;
int* r_ptr = rows_.get();
int* c_ptr = cols_.get();
double* v_ptr = values_.get();
int dropped_terms = 0;
for (int i = 0; i < num_nonzeros_; ++i) {
if ((r_ptr[i] < num_rows_) && (c_ptr[i] < num_cols_)) {
if (dropped_terms) {
r_ptr[i - dropped_terms] = r_ptr[i];
c_ptr[i - dropped_terms] = c_ptr[i];
v_ptr[i - dropped_terms] = v_ptr[i];
}
} else {
++dropped_terms;
}
}
num_nonzeros_ -= dropped_terms;
}
std::unique_ptr<TripletSparseMatrix>
TripletSparseMatrix::CreateSparseDiagonalMatrix(const double* values,
int num_rows) {
std::unique_ptr<TripletSparseMatrix> m =
std::make_unique<TripletSparseMatrix>(num_rows, num_rows, num_rows);
for (int i = 0; i < num_rows; ++i) {
m->mutable_rows()[i] = i;
m->mutable_cols()[i] = i;
m->mutable_values()[i] = values[i];
}
m->set_num_nonzeros(num_rows);
return m;
}
void TripletSparseMatrix::ToTextFile(FILE* file) const {
CHECK(file != nullptr);
for (int i = 0; i < num_nonzeros_; ++i) {
fprintf(file, "% 10d % 10d %17f\n", rows_[i], cols_[i], values_[i]);
}
}
std::unique_ptr<TripletSparseMatrix> TripletSparseMatrix::CreateFromTextFile(
FILE* file) {
CHECK(file != nullptr);
int num_rows = 0;
int num_cols = 0;
std::vector<int> rows;
std::vector<int> cols;
std::vector<double> values;
while (true) {
int row, col;
double value;
if (fscanf(file, "%d %d %lf", &row, &col, &value) != 3) {
break;
}
rows.push_back(row);
cols.push_back(col);
values.push_back(value);
num_rows = std::max(num_rows, row + 1);
num_cols = std::max(num_cols, col + 1);
}
VLOG(1) << "Read " << rows.size() << " nonzeros from file.";
return std::make_unique<TripletSparseMatrix>(
num_rows, num_cols, rows, cols, values);
}
std::unique_ptr<TripletSparseMatrix> TripletSparseMatrix::CreateRandomMatrix(
const TripletSparseMatrix::RandomMatrixOptions& options,
std::mt19937& prng) {
CHECK_GT(options.num_rows, 0);
CHECK_GT(options.num_cols, 0);
CHECK_GT(options.density, 0.0);
CHECK_LE(options.density, 1.0);
std::vector<int> rows;
std::vector<int> cols;
std::vector<double> values;
std::uniform_real_distribution<double> uniform01(0.0, 1.0);
std::normal_distribution<double> standard_normal;
while (rows.empty()) {
rows.clear();
cols.clear();
values.clear();
for (int r = 0; r < options.num_rows; ++r) {
for (int c = 0; c < options.num_cols; ++c) {
if (uniform01(prng) <= options.density) {
rows.push_back(r);
cols.push_back(c);
values.push_back(standard_normal(prng));
}
}
}
}
return std::make_unique<TripletSparseMatrix>(
options.num_rows, options.num_cols, rows, cols, values);
}
} // namespace ceres::internal