/external/ceres-solver/internal/ceres/ |
D | linear_least_squares_problems.cc | 196 int nnz = 0; in LinearLeastSquaresProblem1() local 200 rows[nnz] = 0; in LinearLeastSquaresProblem1() 201 cols[nnz] = 0; in LinearLeastSquaresProblem1() 202 values[nnz++] = 1; in LinearLeastSquaresProblem1() 204 rows[nnz] = 0; in LinearLeastSquaresProblem1() 205 cols[nnz] = 2; in LinearLeastSquaresProblem1() 206 values[nnz++] = 2; in LinearLeastSquaresProblem1() 211 rows[nnz] = 1; in LinearLeastSquaresProblem1() 212 cols[nnz] = 0; in LinearLeastSquaresProblem1() 213 values[nnz++] = 3; in LinearLeastSquaresProblem1() [all …]
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D | triplet_sparse_matrix_test.cc | 300 int nnz = 0; in TEST() local 303 m.mutable_rows()[nnz] = i; in TEST() 304 m.mutable_cols()[nnz] = j; in TEST() 305 m.mutable_values()[nnz++] = i+j; in TEST() 308 m.set_num_nonzeros(nnz); in TEST()
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D | suitesparse.cc | 61 triplet.nnz = A->num_nonzeros(); in CreateSparseMatrix() 70 return cholmod_triplet_to_sparse(&triplet, triplet.nnz, &cc_); in CreateSparseMatrix() 81 triplet.nnz = A->num_nonzeros(); in CreateSparseMatrixTranspose() 92 return cholmod_triplet_to_sparse(&triplet, triplet.nnz, &cc_); in CreateSparseMatrixTranspose()
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D | compressed_row_sparse_matrix.cc | 451 int nnz = 0; in CompressAndFillProgram() local 454 (*program)[product[0].index] = nnz; in CompressAndFillProgram() 461 crsm_cols[++nnz] = current.col; in CompressAndFillProgram() 467 (*program)[current.index] = nnz; in CompressAndFillProgram()
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/external/eigen/Eigen/src/SparseCore/ |
D | SparseBlock.h | 135 Index nnz = tmp.nonZeros(); 145 if(nnz>free_size) 148 … typename SparseMatrixType::Storage newdata(m_matrix.data().allocatedSize() - block_size + nnz); 153 std::memcpy(&newdata.value(start), &tmp.data().value(0), nnz*sizeof(Scalar)); 154 std::memcpy(&newdata.index(start), &tmp.data().index(0), nnz*sizeof(Index)); 156 std::memcpy(&newdata.value(start+nnz), &matrix.data().value(end), tail_size*sizeof(Scalar)); 157 std::memcpy(&newdata.index(start+nnz), &matrix.data().index(end), tail_size*sizeof(Index)); 159 newdata.resize(m_matrix.outerIndexPtr()[m_matrix.outerSize()] - block_size + nnz); 166 matrix.data().resize(start + nnz + tail_size); 168 …std::memmove(&matrix.data().value(start+nnz), &matrix.data().value(end), tail_size*sizeof(Scalar)); [all …]
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D | ConservativeSparseSparseProduct.h | 47 Index nnz = 0; in conservative_sparse_sparse_product_impl() local 60 indices[nnz] = i; in conservative_sparse_sparse_product_impl() 61 ++nnz; in conservative_sparse_sparse_product_impl() 69 for(Index k=0; k<nnz; ++k) in conservative_sparse_sparse_product_impl() 92 if(nnz>1) std::sort(indices.data(),indices.data()+nnz); in conservative_sparse_sparse_product_impl() 93 for(Index k=0; k<nnz; ++k) in conservative_sparse_sparse_product_impl()
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D | MappedSparseMatrix.h | 108 …inline MappedSparseMatrix(Index rows, Index cols, Index nnz, Index* outerIndexPtr, Index* innerInd… 109 …: m_outerSize(IsRowMajor?rows:cols), m_innerSize(IsRowMajor?cols:rows), m_nnz(nnz), m_outerIndex(o…
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D | SparseSelfAdjointView.h | 351 Index nnz = count.sum(); 354 dest.resizeNonZeros(nnz);
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/external/eigen/bench/ |
D | sparse_setter.cpp | 302 const int nnz, in coo_tocsr() argument 312 for (int n = 0; n < nnz; n++){ in coo_tocsr() 322 Bp[n_row] = nnz; in coo_tocsr() 325 for(int n = 0; n < nnz; n++){ in coo_tocsr() 384 I nnz = 0; in csr_sum_duplicates() local 397 Aj[nnz] = j; in csr_sum_duplicates() 398 Ax[nnz] = x; in csr_sum_duplicates() 399 nnz++; in csr_sum_duplicates() 401 Ap[i+1] = nnz; in csr_sum_duplicates()
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/external/eigen/Eigen/src/OrderingMethods/ |
D | Ordering.h | 131 Index nnz = mat.nonZeros(); in operator() local 133 Index Alen = internal::colamd_recommended(nnz, m, n); in operator() 141 for(Index i=0; i < nnz; i++) A(i) = mat.innerIndexPtr()[i]; in operator()
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D | Eigen_Colamd.h | 264 inline Index colamd_recommended ( Index nnz, Index n_row, Index n_col) in colamd_recommended() argument 266 if ((nnz) < 0 || (n_row) < 0 || (n_col) < 0) in colamd_recommended() 269 return (2 * (nnz) + colamd_c (n_col) + colamd_r (n_row) + (n_col) + ((nnz) / 5)); in colamd_recommended() 334 Index nnz ; /* nonzeros in A */ in colamd() local 392 nnz = p [n_col] ; in colamd() 393 if (nnz < 0) /* nnz must be >= 0 */ in colamd() 396 stats [COLAMD_INFO1] = nnz ; in colamd() 397 COLAMD_DEBUG0 (("colamd: number of entries negative %d\n", nnz)) ; in colamd() 421 need = 2*nnz + n_col + Col_size + Row_size ; in colamd() 454 n_col2, max_deg, 2*nnz) ; in colamd()
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/external/eigen/unsupported/Eigen/src/IterativeSolvers/ |
D | IncompleteCholesky.h | 147 Index nnz = m_L.nonZeros(); in factorize() local 148 Map<ScalarType> vals(m_L.valuePtr(), nnz); //values in factorize() 149 Map<IndexType> rowIdx(m_L.innerIndexPtr(), nnz); //Row indices in factorize()
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/external/eigen/Eigen/src/SuperLUSupport/ |
D | SuperLUSupport.h | 114 union {int nnz;int lda;}; member 186 res.storage.nnz = mat.nonZeros(); in Map() 245 res.storage.nnz = mat.nonZeros(); 704 m_l.resizeNonZeros(Lstore->nnz); 706 m_u.resizeNonZeros(Ustore->nnz);
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/external/eigen/doc/ |
D | SparseQuickReference.dox | 25 sm1.reserve(nnz); // Allocate room for nnz nonzeros elements. 28 <td> Note that when calling reserve(), it is not required that nnz is the exact number of nonzero e…
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D | TutorialSparse.dox | 192 …st of a single purely random insertion into a SparseMatrix is \c O(nnz), where \c nnz is the curre…
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/external/eigen/Eigen/src/SparseLU/ |
D | SparseLU.h | 493 Index nnz = m_mat.nonZeros(); in factorize() local 497 Index info = Base::memInit(m, n, nnz, lwork, m_perfv.fillfactor, m_perfv.panel_size, m_glu); in factorize()
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/external/chromium_org/third_party/libjingle/source/talk/media/testdata/ |
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