Matrix generation cleanup 1. Convert a CompressedRowSparseMatrix constructor which takes a TripletSparseMatrix as input into a factory method which allows the input to be transposed. 2. Move the random matrix creation routine for CompressedRowSparseMatrix from being a standalone function to a static method. 3. Add a corresponding random matrix generation static method to TripletSparseMatrix. 4. Add a new constructor to TripletSparseMatrix, which takes as input the row, col and values arrays. Change-Id: Iec7b184646818f432a5e6822bea3b2f3128a82aa
diff --git a/internal/ceres/compressed_row_sparse_matrix.cc b/internal/ceres/compressed_row_sparse_matrix.cc index 9c438f6..ccb85bc 100644 --- a/internal/ceres/compressed_row_sparse_matrix.cc +++ b/internal/ceres/compressed_row_sparse_matrix.cc
@@ -116,6 +116,43 @@ } transpose_rows[0] = 0; } + +void AddRandomBlock(const int num_rows, + const int num_cols, + const int row_block_begin, + const int col_block_begin, + std::vector<int>* rows, + std::vector<int>* cols, + std::vector<double>* values) { + for (int r = 0; r < num_rows; ++r) { + for (int c = 0; c < num_cols; ++c) { + rows->push_back(row_block_begin + r); + cols->push_back(col_block_begin + c); + values->push_back(RandNormal()); + } + } +} + +void AddRandomSymmetricBlock(const int num_rows, + const int row_block_begin, + std::vector<int>* rows, + std::vector<int>* cols, + std::vector<double>* values) { + for (int r = 0; r < num_rows; ++r) { + for (int c = r; c < num_rows; ++c) { + const double v = RandNormal(); + rows->push_back(row_block_begin + r); + cols->push_back(row_block_begin + c); + values->push_back(v); + if (c != r) { + cols->push_back(row_block_begin + r); + rows->push_back(row_block_begin + c); + values->push_back(v); + } + } + } +} + } // namespace // This constructor gives you a semi-initialized CompressedRowSparseMatrix. @@ -136,47 +173,70 @@ cols_.size() * sizeof(double); // NOLINT } -CompressedRowSparseMatrix::CompressedRowSparseMatrix( - const TripletSparseMatrix& m) { - num_rows_ = m.num_rows(); - num_cols_ = m.num_cols(); - storage_type_ = UNSYMMETRIC; +CompressedRowSparseMatrix* CompressedRowSparseMatrix::FromTripletSparseMatrix( + const TripletSparseMatrix& input) { + return CompressedRowSparseMatrix::FromTripletSparseMatrix(input, false); +} - rows_.resize(num_rows_ + 1, 0); - cols_.resize(m.num_nonzeros(), 0); - values_.resize(m.max_num_nonzeros(), 0.0); +CompressedRowSparseMatrix* +CompressedRowSparseMatrix::FromTripletSparseMatrixTransposed( + const TripletSparseMatrix& input) { + return CompressedRowSparseMatrix::FromTripletSparseMatrix(input, true); +} - // 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) { +CompressedRowSparseMatrix* CompressedRowSparseMatrix::FromTripletSparseMatrix( + const TripletSparseMatrix& input, bool transpose) { + int num_rows = input.num_rows(); + int num_cols = input.num_cols(); + const int* rows = input.rows(); + const int* cols = input.cols(); + const double* values = input.values(); + + if (transpose) { + std::swap(num_rows, num_cols); + std::swap(rows, cols); + } + + // index is the list of indices into the TripletSparseMatrix input. + vector<int> index(input.num_nonzeros(), 0); + for (int i = 0; i < input.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())); + std::sort(index.begin(), index.end(), RowColLessThan(rows, 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 + VLOG(1) << "# of rows: " << num_rows << " # of columns: " << num_cols + << " num_nonzeros: " << input.num_nonzeros() << ". Allocating " + << ((num_rows + 1) * sizeof(int) + // NOLINT + input.num_nonzeros() * sizeof(int) + // NOLINT + input.num_nonzeros() * sizeof(double)); // NOLINT + + CompressedRowSparseMatrix* output = + new CompressedRowSparseMatrix(num_rows, num_cols, input.num_nonzeros()); // 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) { + int* output_rows = output->mutable_rows(); + int* output_cols = output->mutable_cols(); + double* output_values = output->mutable_values(); + + output_rows[0] = 0; + for (int i = 0; i < index.size(); ++i) { const int idx = index[i]; - ++rows_[m.rows()[idx] + 1]; - cols_[i] = m.cols()[idx]; - values_[i] = m.values()[idx]; + ++output_rows[rows[idx] + 1]; + output_cols[i] = cols[idx]; + output_values[i] = values[idx]; } // Find the cumulative sum of the row counts. - for (int i = 1; i < num_rows_ + 1; ++i) { - rows_[i] += rows_[i - 1]; + for (int i = 1; i < num_rows + 1; ++i) { + output_rows[i] += output_rows[i - 1]; } - CHECK_EQ(num_nonzeros(), m.num_nonzeros()); + CHECK_EQ(output->num_nonzeros(), input.num_nonzeros()); + return output; } CompressedRowSparseMatrix::CompressedRowSparseMatrix(const double* diagonal, @@ -585,8 +645,8 @@ CHECK_GT(product.size(), 0); vector<int> row_nnz; - CompressedRowSparseMatrix* matrix = - CreateOuterProductMatrix(num_cols, storage_type, blocks, product, &row_nnz); + CompressedRowSparseMatrix* matrix = CreateOuterProductMatrix( + num_cols, storage_type, blocks, product, &row_nnz); const vector<int>& block_offsets = matrix->block_offsets(); @@ -697,10 +757,10 @@ CompressedRowSparseMatrix* CompressedRowSparseMatrix::CreateOuterProductMatrixAndProgram( - const CompressedRowSparseMatrix& m, - const CompressedRowSparseMatrix::StorageType storage_type, - vector<int>* program) { - CHECK(storage_type == LOWER_TRIANGULAR || storage_type == UPPER_TRIANGULAR); + const CompressedRowSparseMatrix& m, + const CompressedRowSparseMatrix::StorageType storage_type, + vector<int>* program) { + CHECK(storage_type == LOWER_TRIANGULAR || storage_type == UPPER_TRIANGULAR); CHECK_NOTNULL(program)->clear(); CHECK_GT(m.num_nonzeros(), 0) << "Congratulations, you found a bug in Ceres. Please report it."; @@ -778,8 +838,8 @@ const CompressedRowSparseMatrix& m, const vector<int>& program, CompressedRowSparseMatrix* result) { - CHECK(result->storage_type() == LOWER_TRIANGULAR || - result->storage_type() == UPPER_TRIANGULAR); + CHECK(result->storage_type() == LOWER_TRIANGULAR || + result->storage_type() == UPPER_TRIANGULAR); result->SetZero(); double* values = result->mutable_values(); const int* rows = result->rows(); @@ -796,7 +856,6 @@ #define COL_BLOCK1 (crsb_cols[idx1]) #define COL_BLOCK2 (crsb_cols[idx2]) - // Iterate row blocks. for (int row_block = 0, m_row_begin = 0; row_block < row_blocks.size(); m_row_begin += row_blocks[row_block++]) { @@ -853,8 +912,19 @@ CHECK_EQ(cursor, program.size()); } -CompressedRowSparseMatrix* CreateRandomCompressedRowSparseMatrix( - const RandomMatrixOptions& options) { +CompressedRowSparseMatrix* CompressedRowSparseMatrix::CreateRandomMatrix( + const CompressedRowSparseMatrix::RandomMatrixOptions& options) { + CHECK_GT(options.num_row_blocks, 0); + CHECK_GT(options.min_row_block_size, 0); + CHECK_GT(options.max_row_block_size, 0); + CHECK_LE(options.min_row_block_size, options.max_row_block_size); + CHECK_GT(options.num_col_blocks, 0); + CHECK_GT(options.min_col_block_size, 0); + CHECK_GT(options.max_col_block_size, 0); + CHECK_LE(options.min_col_block_size, options.max_col_block_size); + CHECK_GT(options.block_density, 0.0); + CHECK_LE(options.block_density, 1.0); + vector<int> row_blocks; vector<int> col_blocks; @@ -889,22 +959,26 @@ // not what the user wants, so do the matrix generation till we have // at least one non-zero entry. while (tsm_values.empty()) { - int row_block_begin = 0; crsb_rows.clear(); crsb_cols.clear(); + tsm_rows.clear(); + tsm_cols.clear(); + tsm_values.clear(); + + int row_block_begin = 0; for (int r = 0; r < options.num_row_blocks; ++r) { int col_block_begin = 0; crsb_rows.push_back(crsb_cols.size()); for (int c = 0; c < options.num_col_blocks; ++c) { // Randomly determine if this block is present or not. if (RandDouble() <= options.block_density) { - for (int i = 0; i < row_blocks[r]; ++i) { - for (int j = 0; j < col_blocks[c]; ++j) { - tsm_rows.push_back(row_block_begin + i); - tsm_cols.push_back(col_block_begin + j); - tsm_values.push_back(RandNormal()); - } - } + AddRandomBlock(row_blocks[r], + col_blocks[c], + row_block_begin, + col_block_begin, + &tsm_rows, + &tsm_cols, + &tsm_values); // Add the block to the block sparse structure. crsb_cols.push_back(c); } @@ -917,21 +991,17 @@ const int num_rows = std::accumulate(row_blocks.begin(), row_blocks.end(), 0); const int num_cols = std::accumulate(col_blocks.begin(), col_blocks.end(), 0); - const int num_nonzeros = tsm_values.size(); - - // Create a TripletSparseMatrix - TripletSparseMatrix tsm(num_rows, num_cols, num_nonzeros); - std::copy(tsm_rows.begin(), tsm_rows.end(), tsm.mutable_rows()); - std::copy(tsm_cols.begin(), tsm_cols.end(), tsm.mutable_cols()); - std::copy(tsm_values.begin(), tsm_values.end(), tsm.mutable_values()); - tsm.set_num_nonzeros(num_nonzeros); - - // Convert the TripletSparseMatrix to a CompressedRowSparseMatrix. - CompressedRowSparseMatrix* matrix = new CompressedRowSparseMatrix(tsm); + const bool kDoNotTranspose = false; + CompressedRowSparseMatrix* matrix = + CompressedRowSparseMatrix::FromTripletSparseMatrix( + TripletSparseMatrix( + num_rows, num_cols, tsm_rows, tsm_cols, tsm_values), + kDoNotTranspose); (*matrix->mutable_row_blocks()) = row_blocks; (*matrix->mutable_col_blocks()) = col_blocks; (*matrix->mutable_crsb_rows()) = crsb_rows; (*matrix->mutable_crsb_cols()) = crsb_cols; + matrix->set_storage_type(CompressedRowSparseMatrix::UNSYMMETRIC); return matrix; }
diff --git a/internal/ceres/compressed_row_sparse_matrix.h b/internal/ceres/compressed_row_sparse_matrix.h index bf67737..1e26f7c 100644 --- a/internal/ceres/compressed_row_sparse_matrix.h +++ b/internal/ceres/compressed_row_sparse_matrix.h
@@ -50,18 +50,33 @@ public: enum StorageType { UNSYMMETRIC, + // Matrix is assumed to be symmetric but only the lower triangular + // part of the matrix is stored. LOWER_TRIANGULAR, + // Matrix is assumed to be symmetric but only the upper triangular + // part of the matrix is stored. UPPER_TRIANGULAR }; - - // Build a matrix with the same content as the TripletSparseMatrix - // m. TripletSparseMatrix objects are easier to construct - // incrementally, so we use them to initialize SparseMatrix - // objects. + // Create a matrix with the same content as the TripletSparseMatrix + // input. We assume that input does not have any repeated + // entries. // - // We assume that m does not have any repeated entries. - explicit CompressedRowSparseMatrix(const TripletSparseMatrix& m); + // The storage type of the matrix is set to UNSYMMETRIC. + // + // Caller owns the result. + static CompressedRowSparseMatrix* FromTripletSparseMatrix( + const TripletSparseMatrix& input); + + // Create a matrix with the same content as the TripletSparseMatrix + // input transposed. We assume that input does not have any repeated + // entries. + // + // The storage type of the matrix is set to UNSYMMETRIC. + // + // Caller owns the result. + static CompressedRowSparseMatrix* FromTripletSparseMatrixTransposed( + const TripletSparseMatrix& input); // Use this constructor only if you know what you are doing. This // creates a "blank" matrix with the appropriate amount of memory @@ -74,17 +89,20 @@ // manually, instead of going via the indirect route of first // constructing a TripletSparseMatrix, which leads to more than // double the peak memory usage. + // + // The storage type is set to UNSYMMETRIC. CompressedRowSparseMatrix(int num_rows, int num_cols, int max_num_nonzeros); // Build a square sparse diagonal matrix with num_rows rows and // columns. The diagonal m(i,i) = diagonal(i); + // + // The storage type is set to UNSYMMETRIC CompressedRowSparseMatrix(const double* diagonal, int num_rows); - virtual ~CompressedRowSparseMatrix(); - // SparseMatrix interface. + virtual ~CompressedRowSparseMatrix(); virtual void SetZero(); virtual void RightMultiply(const double* x, double* y) const; virtual void LeftMultiply(const double* x, double* y) const; @@ -145,10 +163,60 @@ const std::vector<int>& crsb_cols() const { return crsb_cols_; } std::vector<int>* mutable_crsb_cols() { return &crsb_cols_; } + // Create a block diagonal CompressedRowSparseMatrix with the given + // block structure. The individual blocks are assumed to be laid out + // contiguously in the diagonal array, one block at a time. + // + // Caller owns the result. static CompressedRowSparseMatrix* CreateBlockDiagonalMatrix( const double* diagonal, const std::vector<int>& blocks); + // Options struct to control the generation of random block sparse + // matrices in compressed row sparse format. + // + // The random matrix generation proceeds as follows. + // + // First the row and column block structure is determined by + // generating random row and column block sizes that lie within the + // given bounds. + // + // Then we walk the block structure of the resulting matrix, and with + // probability block_density detemine whether they are structurally + // zero or not. If the answer is no, then we generate entries for the + // block which are distributed normally. + struct RandomMatrixOptions { + RandomMatrixOptions() + : num_row_blocks(0), + min_row_block_size(0), + max_row_block_size(0), + num_col_blocks(0), + min_col_block_size(0), + max_col_block_size(0), + block_density(0.0) { + } + + int num_row_blocks; + int min_row_block_size; + int max_row_block_size; + int num_col_blocks; + int min_col_block_size; + int max_col_block_size; + + // 0 < block_density <= 1 is the probability of a block being + // present in the matrix. A given random matrix will not have + // precisely this density. + double block_density; + }; + + // Create a random CompressedRowSparseMatrix whose entries are + // normally distributed and whose structure is determined by + // RandomMatrixOptions. + // + // Caller owns the result. + static CompressedRowSparseMatrix* CreateRandomMatrix( + const RandomMatrixOptions& options); + // Compute the sparsity structure of the product m.transpose() * m // and create a CompressedRowSparseMatrix corresponding to it. // @@ -180,6 +248,10 @@ CompressedRowSparseMatrix* result); private: + + static CompressedRowSparseMatrix* FromTripletSparseMatrix( + const TripletSparseMatrix& input, bool transpose); + int num_rows_; int num_cols_; std::vector<int> rows_; @@ -206,45 +278,8 @@ // carry with it compressed row sparse block information. std::vector<int> crsb_rows_; std::vector<int> crsb_cols_; - - CERES_DISALLOW_COPY_AND_ASSIGN(CompressedRowSparseMatrix); }; -// Options struct to control the generation of random block sparse -// matrices in compressed row sparse format. -// -// The random matrix generation proceeds as follows. -// -// First the row and column block structure is determined by -// generating random row and column block sizes that lie within the -// given bounds. -// -// Then we walk the block structure of the resulting matrix, and with -// probability block_density detemine whether they are structurally -// zero or not. If the answer is no, then we generate entries for the -// block which are distributed normally. -struct RandomMatrixOptions { - int num_row_blocks; - int min_row_block_size; - int max_row_block_size; - int num_col_blocks; - int min_col_block_size; - int max_col_block_size; - - // 0 <= block_density <= 1 is the probability of a block being - // present in the matrix. A given random matrix will not have - // precisely this density. - double block_density; -}; - -// Create a random CompressedRowSparseMatrix whose entries are -// normally distributed and whose structure is determined by -// RandomMatrixOptions. -// -// Caller owns the result. -CompressedRowSparseMatrix* CreateRandomCompressedRowSparseMatrix( - const RandomMatrixOptions& options); - } // namespace internal } // namespace ceres
diff --git a/internal/ceres/compressed_row_sparse_matrix_test.cc b/internal/ceres/compressed_row_sparse_matrix_test.cc index 66e2390..bb8456e 100644 --- a/internal/ceres/compressed_row_sparse_matrix_test.cc +++ b/internal/ceres/compressed_row_sparse_matrix_test.cc
@@ -70,7 +70,7 @@ } class CompressedRowSparseMatrixTest : public ::testing::Test { - protected : + protected: virtual void SetUp() { scoped_ptr<LinearLeastSquaresProblem> problem( CreateLinearLeastSquaresProblemFromId(1)); @@ -78,7 +78,7 @@ CHECK_NOTNULL(problem.get()); tsm.reset(down_cast<TripletSparseMatrix*>(problem->A.release())); - crsm.reset(new CompressedRowSparseMatrix(*tsm)); + crsm.reset(CompressedRowSparseMatrix::FromTripletSparseMatrix(*tsm)); num_rows = tsm->num_rows(); num_cols = tsm->num_cols(); @@ -93,9 +93,11 @@ // With all blocks of size 1, crsb_rows and crsb_cols are equivalent to // rows and cols. - std::copy(crsm->rows(), crsm->rows() + crsm->num_rows() + 1, + std::copy(crsm->rows(), + crsm->rows() + crsm->num_rows() + 1, std::back_inserter(*crsm->mutable_crsb_rows())); - std::copy(crsm->cols(), crsm->cols() + crsm->num_nonzeros(), + std::copy(crsm->cols(), + crsm->cols() + crsm->num_nonzeros(), std::back_inserter(*crsm->mutable_crsb_cols())); } @@ -172,9 +174,10 @@ tsm_appendage.Resize(i, num_cols); tsm->AppendRows(tsm_appendage); - CompressedRowSparseMatrix crsm_appendage(tsm_appendage); - crsm->AppendRows(crsm_appendage); + scoped_ptr<CompressedRowSparseMatrix> crsm_appendage( + CompressedRowSparseMatrix::FromTripletSparseMatrix(tsm_appendage)); + crsm->AppendRows(*crsm_appendage); CompareMatrices(tsm.get(), crsm.get()); } } @@ -219,9 +222,9 @@ EXPECT_EQ(expected_col_blocks, crsm->col_blocks()); EXPECT_EQ(crsm->crsb_cols().size(), - pre_crsb_cols.size() + row_and_column_blocks.size()); + pre_crsb_cols.size() + row_and_column_blocks.size()); EXPECT_EQ(crsm->crsb_rows().size(), - pre_crsb_rows.size() + row_and_column_blocks.size()); + pre_crsb_rows.size() + row_and_column_blocks.size()); for (int i = 0; i < row_and_column_blocks.size(); ++i) { EXPECT_EQ(crsm->crsb_rows()[i + pre_crsb_rows.size()], pre_crsb_rows.back() + i + 1); @@ -234,7 +237,6 @@ EXPECT_EQ(crsm->crsb_rows(), pre_crsb_rows); EXPECT_EQ(crsm->crsb_cols(), pre_crsb_cols); - } TEST_F(CompressedRowSparseMatrixTest, ToDenseMatrix) { @@ -278,8 +280,8 @@ } scoped_ptr<CompressedRowSparseMatrix> matrix( - CompressedRowSparseMatrix::CreateBlockDiagonalMatrix( - diagonal.data(), blocks)); + CompressedRowSparseMatrix::CreateBlockDiagonalMatrix(diagonal.data(), + blocks)); EXPECT_EQ(matrix->num_rows(), 5); EXPECT_EQ(matrix->num_cols(), 5); @@ -351,7 +353,6 @@ cols[5] = 2; cols[6] = 5; - rows[2] = 7; cols[7] = 0; cols[8] = 1; @@ -394,21 +395,19 @@ TEST(CompressedRowSparseMatrix, ComputeOuterProduct) { // "Randomly generated seed." SetRandomState(29823); - int kMaxNumRowBlocks = 10; - int kMaxNumColBlocks = 10; - int kNumTrials = 10; + const int kMaxNumRowBlocks = 10; + const int kMaxNumColBlocks = 10; + const int kNumTrials = 10; // Create a random matrix, compute its outer product using Eigen and // ComputeOuterProduct. Convert both matrices to dense matrices and // compare their upper triangular parts. - for (int num_row_blocks = 1; - num_row_blocks < kMaxNumRowBlocks; + for (int num_row_blocks = 1; num_row_blocks < kMaxNumRowBlocks; ++num_row_blocks) { - for (int num_col_blocks = 1; - num_col_blocks < kMaxNumColBlocks; + for (int num_col_blocks = 1; num_col_blocks < kMaxNumColBlocks; ++num_col_blocks) { for (int trial = 0; trial < kNumTrials; ++trial) { - RandomMatrixOptions options; + CompressedRowSparseMatrix::RandomMatrixOptions options; options.num_row_blocks = num_row_blocks; options.num_col_blocks = num_col_blocks; options.min_row_block_size = 1; @@ -426,7 +425,7 @@ VLOG(2) << "block density: " << options.block_density; scoped_ptr<CompressedRowSparseMatrix> random_matrix( - CreateRandomCompressedRowSparseMatrix(options)); + CompressedRowSparseMatrix::CreateRandomMatrix(options)); Eigen::MappedSparseMatrix<double, Eigen::RowMajor> mapped_random_matrix( random_matrix->num_rows(), @@ -480,5 +479,60 @@ } } +TEST(CompressedRowSparseMatrix, FromTripletSparseMatrix) { + TripletSparseMatrix::RandomMatrixOptions options; + options.num_rows = 5; + options.num_cols = 7; + options.density = 0.5; + + const int kNumTrials = 10; + for (int i = 0; i < kNumTrials; ++i) { + scoped_ptr<TripletSparseMatrix> tsm( + TripletSparseMatrix::CreateRandomMatrix(options)); + scoped_ptr<CompressedRowSparseMatrix> crsm( + CompressedRowSparseMatrix::FromTripletSparseMatrix(*tsm)); + + Matrix expected; + tsm->ToDenseMatrix(&expected); + Matrix actual; + crsm->ToDenseMatrix(&actual); + EXPECT_NEAR((expected - actual).norm() / actual.norm(), + 0.0, + std::numeric_limits<double>::epsilon()) + << "\nexpected: \n" + << expected << "\nactual: \n" + << actual; + } +} + +TEST(CompressedRowSparseMatrix, FromTripletSparseMatrixTransposed) { + TripletSparseMatrix::RandomMatrixOptions options; + options.num_rows = 5; + options.num_cols = 7; + options.density = 0.5; + + const int kNumTrials = 10; + for (int i = 0; i < kNumTrials; ++i) { + scoped_ptr<TripletSparseMatrix> tsm( + TripletSparseMatrix::CreateRandomMatrix(options)); + scoped_ptr<CompressedRowSparseMatrix> crsm( + CompressedRowSparseMatrix::FromTripletSparseMatrixTransposed(*tsm)); + + Matrix tmp; + tsm->ToDenseMatrix(&tmp); + Matrix expected = tmp.transpose(); + Matrix actual; + crsm->ToDenseMatrix(&actual); + EXPECT_NEAR((expected - actual).norm() / actual.norm(), + 0.0, + std::numeric_limits<double>::epsilon()) + << "\nexpected: \n" + << expected << "\nactual: \n" + << actual; + } +} + +// TODO(sameeragarwal) Add tests for the random matrix creation methods. + } // namespace internal } // namespace ceres
diff --git a/internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc b/internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc index d27385a..4030142 100644 --- a/internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc +++ b/internal/ceres/dynamic_compressed_row_sparse_matrix_test.cc
@@ -108,7 +108,7 @@ tsm->ToDenseMatrix(&dense_from_tsm); ASSERT_TRUE((dense.array() == dense_from_tsm.array()).all()); - crsm.reset(new CompressedRowSparseMatrix(*tsm)); + crsm.reset(CompressedRowSparseMatrix::FromTripletSparseMatrix(*tsm)); Matrix dense_from_crsm; crsm->ToDenseMatrix(&dense_from_crsm); ASSERT_TRUE((dense.array() == dense_from_crsm.array()).all());
diff --git a/internal/ceres/schur_complement_solver.cc b/internal/ceres/schur_complement_solver.cc index 81e0d46..26c0e89 100644 --- a/internal/ceres/schur_complement_solver.cc +++ b/internal/ceres/schur_complement_solver.cc
@@ -547,15 +547,16 @@ } // This is an upper triangular matrix. - CompressedRowSparseMatrix crsm(*tsm); + scoped_ptr<CompressedRowSparseMatrix> crsm( + CompressedRowSparseMatrix::FromTripletSparseMatrix(*tsm)); // Map this to a column major, lower triangular matrix. Eigen::MappedSparseMatrix<double, Eigen::ColMajor> eigen_lhs( - crsm.num_rows(), - crsm.num_rows(), - crsm.num_nonzeros(), - crsm.mutable_rows(), - crsm.mutable_cols(), - crsm.mutable_values()); + crsm->num_rows(), + crsm->num_rows(), + crsm->num_nonzeros(), + crsm->mutable_rows(), + crsm->mutable_cols(), + crsm->mutable_values()); event_logger.AddEvent("ToCompressedRowSparseMatrix"); // Compute symbolic factorization if one does not exist.
diff --git a/internal/ceres/triplet_sparse_matrix.cc b/internal/ceres/triplet_sparse_matrix.cc index 8df405c..a7df060 100644 --- a/internal/ceres/triplet_sparse_matrix.cc +++ b/internal/ceres/triplet_sparse_matrix.cc
@@ -35,6 +35,7 @@ #include "ceres/internal/eigen.h" #include "ceres/internal/port.h" #include "ceres/internal/scoped_ptr.h" +#include "ceres/random.h" #include "ceres/types.h" #include "glog/logging.h" @@ -69,6 +70,27 @@ 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()), + rows_(NULL), + cols_(NULL), + values_(NULL) { + // All the sizes should at least be zero + CHECK_GE(num_rows, 0); + CHECK_GE(num_cols, 0); + 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_), @@ -260,5 +282,37 @@ } } +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()); + } + } + } + if (!rows.empty()) { + break; + } + } + + return new TripletSparseMatrix( + options.num_rows, options.num_cols, rows, cols, values); +} + } // namespace internal } // namespace ceres
diff --git a/internal/ceres/triplet_sparse_matrix.h b/internal/ceres/triplet_sparse_matrix.h index f3f5370..1d82e14 100644 --- a/internal/ceres/triplet_sparse_matrix.h +++ b/internal/ceres/triplet_sparse_matrix.h
@@ -31,6 +31,7 @@ #ifndef CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H_ #define CERES_INTERNAL_TRIPLET_SPARSE_MATRIX_H_ +#include <vector> #include "ceres/sparse_matrix.h" #include "ceres/internal/eigen.h" #include "ceres/internal/scoped_ptr.h" @@ -47,6 +48,12 @@ public: TripletSparseMatrix(); TripletSparseMatrix(int num_rows, int num_cols, int max_num_nonzeros); + TripletSparseMatrix(int num_rows, + int num_cols, + const std::vector<int>& rows, + const std::vector<int>& cols, + const std::vector<double>& values); + explicit TripletSparseMatrix(const TripletSparseMatrix& orig); TripletSparseMatrix& operator=(const TripletSparseMatrix& rhs); @@ -105,6 +112,25 @@ static TripletSparseMatrix* CreateSparseDiagonalMatrix(const double* values, int num_rows); + // Options struct to control the generation of random + // TripletSparseMatrix objects. + struct RandomMatrixOptions { + int num_rows; + int num_cols; + // 0 < density <= 1 is the probability of an entry being + // structurally non-zero. A given random matrix will not have + // precisely this density. + double density; + }; + + // Create a random CompressedRowSparseMatrix whose entries are + // normally distributed and whose structure is determined by + // RandomMatrixOptions. + // + // Caller owns the result. + static TripletSparseMatrix* CreateRandomMatrix( + const TripletSparseMatrix::RandomMatrixOptions& options); + private: void AllocateMemory(); void CopyData(const TripletSparseMatrix& orig);
diff --git a/internal/ceres/unsymmetric_linear_solver_test.cc b/internal/ceres/unsymmetric_linear_solver_test.cc index 95797c5..a670f00 100644 --- a/internal/ceres/unsymmetric_linear_solver_test.cc +++ b/internal/ceres/unsymmetric_linear_solver_test.cc
@@ -69,7 +69,8 @@ options.type == DENSE_NORMAL_CHOLESKY) { transformed_A.reset(new DenseSparseMatrix(*A_)); } else if (options.type == SPARSE_NORMAL_CHOLESKY) { - CompressedRowSparseMatrix* crsm = new CompressedRowSparseMatrix(*A_); + CompressedRowSparseMatrix* crsm = + CompressedRowSparseMatrix::FromTripletSparseMatrix(*A_); // Add row/column blocks structure. for (int i = 0; i < A_->num_rows(); ++i) { crsm->mutable_row_blocks()->push_back(1);