// 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 // 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 #include #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& rows, const std::vector& cols, const std::vector& 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) { if ((rows_[i] < 0) || (rows_[i] >= num_rows_) || (cols_[i] < 0) || (cols_[i] >= num_cols_)) return false; } 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 rows; std::vector cols; std::vector 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