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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
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// POSSIBILITY OF SUCH DAMAGE.
//
// Author: sameeragarwal@google.com (Sameer Agarwal)
#include "ceres/triplet_sparse_matrix.h"
#include <algorithm>
#include <cstddef>
#include "ceres/internal/eigen.h"
#include "ceres/internal/port.h"
#include "ceres/random.h"
#include "ceres/types.h"
#include "glog/logging.h"
namespace ceres {
namespace internal {
TripletSparseMatrix::TripletSparseMatrix()
: num_rows_(0), num_cols_(0), max_num_nonzeros_(0), num_nonzeros_(0) {}
TripletSparseMatrix::~TripletSparseMatrix() {}
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;
int* new_rows = new int[new_max_num_nonzeros];
int* new_cols = new int[new_max_num_nonzeros];
double* new_values = new 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_.reset(new_rows);
cols_.reset(new_cols);
values_.reset(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_.reset(new int[max_num_nonzeros_]);
cols_.reset(new int[max_num_nonzeros_]);
values_.reset(new 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::RightMultiply(const double* x, double* y) const {
for (int i = 0; i < num_nonzeros_; ++i) {
y[rows_[i]] += values_[i] * x[cols_[i]];
}
}
void TripletSparseMatrix::LeftMultiply(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::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;
}
TripletSparseMatrix* TripletSparseMatrix::CreateSparseDiagonalMatrix(
const double* values, int num_rows) {
TripletSparseMatrix* m =
new 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]);
}
}
TripletSparseMatrix* TripletSparseMatrix::CreateRandomMatrix(
const TripletSparseMatrix::RandomMatrixOptions& options) {
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;
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 (RandDouble() <= options.density) {
rows.push_back(r);
cols.push_back(c);
values.push_back(RandNormal());
}
}
}
}
return new TripletSparseMatrix(
options.num_rows, options.num_cols, rows, cols, values);
}
} // namespace internal
} // namespace ceres