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- // Ceres Solver - A fast non-linear least squares minimizer
- // Copyright 2022 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
- // CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE)
- // ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
- // POSSIBILITY OF SUCH DAMAGE.
- //
- // 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
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