MTL Index

Concept index

ColumnMatrix A Column-Oriented MTL Matrix DiagonalMatrix A Diagonally-Oriented Matrix IndexedIterator IndexedIterator Indexer Maps from Matrix coordinates to TwoD coordinates MTL_Object_Model The MTL Object Memory Model Matrix The MTL Matrix Concept Offset Maps from TwoD coordinates to linear memory OneDIndexer OneDIndexer RowMatrix A Row-Oriented MTL Matrix TwoDStorage The MTL TwoD Storage Concept Vector The MTL Vector Concept

Class index

Dim __bracket<Strided> __mult__8<int M, int N> __mult_fixn<int M> _bogus add<int N> Add y <- x + y add_op<int M, IterY> array2D<OneD_> Array 2-D Container band_view<Matrix> Band View Matrix Type Constructor banded_indexer<size_type, Orien> banded_offset<size_t, int MM, int NN> Banded Offset Class banded_view_offset<size_t, int MM, int NN> Banded View Offset Class blk<int BM, int BN> block_view<Matrix, int BM = 0, int BN = 0> Block View Matrix Type Constructor choose<Cat> column_matrix<TwoDGen, IndexerGen> column matrix column_matrix_traits<Matrix> Column Matrix Traits columns_type<Matrix> compressed1D<T, SizeType = int, int IND_OFFSET = index_from_zero, Orien = no_orientation_tag> Compressed Sparse Vector compressed2D<T, SizeType, int IND_OFFSET> Sparse matrix storage format with internal storage compressed_iter<int isConst, Value, Index, int IND_OFFSET> Compressed Storage Iterator const_sparse_iterator<Iterator, T> constant_stride_generator<RandomAccessIterator> copy<int N> Copy y <- x copy__2<int M, int N> Copy B <- A dense_iterator<RandomAccessIterator, int IND_OFFSET=0, SizeType=int> dense iterator dense_iterator__2<T, int isConst, int IND_OFFSET=0, SizeType=int> diagonal_matrix_old<TwoDGen, IndexerGen> Diagonal Matrix diagonal_matrix_traits<Matrix> Diagonal Matrix Traits dimension<sizet, int MM = DYNAMIC_SIZED, int NN = DYNAMIC_SIZED> The Dimension Class dims<int MM, int NN> Row Orientation dims__2<int MM, int NN> Column Orientation dot<int N> Dot Product s <- x . y elt_inserter entry1<T> expr_traits<TwoDGen, IndexerGen> ext_comp2D<T, SizeType, int IND_OFFSET> Sparse matrix storage format with external storage external2D<T, OffsetGen, int MM = 0, int NN = 0> External2D Storage Type external_vec<T, int NN = 0, SizeType=unsigned int, Orien = column_tag> External 1-D Container gen_scaled1D<A, T> general_stride_iterator<RandomAccessIterator, StrideGen> generic_dense2D<RepType, RepPtr, OffsetGen, int MM, int NN> Generic Dense 2-D Container get_value_type<Dim, T> get_value_type__2<T> get_value_type__3<T> givens_rotation<T> Givens Plane Rotation givens_rotation__2<T> The specialization for complex numbers. givens_rotation__3 The specialization for complex numbers. givens_rotation__4 The specialization for complex numbers. harwell_boeing_stream<T> A Matrix File Input Stream for Harwell-Boeing Matrix Files insert_iterator lapack_matrix<T, int External=mtl::internal> Lapack Matrix linalg_category<T, SizeType, int IND_OFFSET, Orien> linalg_category__2<TwoDGen, IndexerGen> linalg_category__3<TwoDGen, IndexerGen> linalg_traits<Linalg> Linear Algebra Object (Matrix and Vector) Traits make_dimsizes<Dim, T> make_dimsizes__2<T> make_dimsizes__3<T> make_info<T> matrix< T, Shape = rectangle<>, Storage = dense<>, Orientation = row_major > Matrix type generators class. matrix_implementation<TwoDGen, IndexerGen> The main MTL matrix implementation type. matrix_market_stream<T> A Matrix File Input Stream for Matrix Market Files matrix_traits<Matrix> The "traits" class for MTL matrices. modified_givens<T> Modified Givens Transformation mtl_multiplies<S, T, R> mult<int M, int N> Multiplication y <- A x + y mult__2<int M, int N, int K> Multiplication C <- A * B mult_fixn<int M> not_strideable Identifies matrices that can not be used with the rows and columns functions not_strided_tag number_traits<number_type> packed_offset<size_t, int MM, int NN> Packed Offset Class packed_strider partitioned<SubMatrix> Dense2D Storage Type rank_one<int M, int N> Rank One Update A <- A + x * y^T rect_offset<size_t, int MM, int NN> Rectangular Offset Class row_matrix<TwoDGen, IndexerGen> row matrix row_matrix_traits<Matrix> Row Matrix Traits rows_type<Matrix> scale_iterator<RandomAccessIterator, T> scale iterator scale_iterator__2<Iterator, T> scaled1D<RandomAccessContainerRef> Scaled Container scaled2D<TwoD, T> Scaled 2D container adaptor set<int N> Set elements of vector x to alpha set__2<int M, int N> Set matrix A to alpha sparse1D<RepType, Orien = column_tag> Sparse 1-D Container Adaptor sparse_iterator<Iterator, T> Sparse Vector Iterator stride_iterator<RandomAccessIterator> strideable Identifies matrices that can be used with the rows and columns functions strided1D<RandomAccessContainerRef> Strided Vector Adaptor strided_band_view_offset<size_t, int MM, int NN> Strided Band View Offset Class strided_banded_offset<size_t, int MM, int NN> Strided Banded Offset strided_iterator<RandomAccessIterator, int isConst> strided iterator strided_offset<size_t, int MM, int NN> Strided Rectangular Offset Class strided_packed_offset<size_t, int MM, int NN> Strided Packed Offset Class strided_tag symmetric_matrix_old<Base_, Uplo, bool IsHerm > symmetric and hermitian symmetric_view<Matrix, uplo_e Uplo> Symmetric View Matrix Type Constructor transform_iterator<Iterator, AdaptableUnaryFunction> Tranforming Iterator transform_iterator__2<RandomAccessIterator, AdaptableUnaryFunction> tri_view<uplo_e Uplo> Triangle View Creation Helper Fuctor triangle_matrix_old<Base_, Uplo> triangle triangle_view<Matrix, uplo_e Uplo> Triangle View Matrix Type Constructor

Function index

scaled Shortcut for Creating a Scaled Argument strided Shortcut for Creating a Strided Argument blocked Blocked Matrix Generator blocked Blocked Matrix Generator rows Access the row-wise view of the matrix columns Access the column-wise view of the matrix trans Swap the orientation of a matrix. sum Sum: s <- sum_i(x(i)) scale Scale: A <- alpha*A or x <- alpha x set_diagonal Set Diagonal: A(i,i) <- alpha two_norm Two Norm: s <- sqrt(sum_i(|x(i)^2|)) sum_squares Sum of the Squares one_norm One Norm: s <- sum(|x_i|) or s <- max_j(sum_i(|A(i,j)|)) infinity_norm Infinity Norm: s <- max_i(sum_j(|A(i,j)|)) or s <- max_i(|x(i)|) max_index Max Index: i <- index of max(|x(i)|) max_abs_index Maximum Absolute Index: i <- index of max(|x(i)|) min_index Minimum Index: i <- index of min(x(i)) min_abs_index Minimum Absolute Index: i <- index of min(|x(i)|) max Max Value: s <- max(x(i)) min Min Value: s <- min(x_i) transpose Transpose in Place: A <- A^T conj_transpose Transpose in Place: A <- A^T transpose Transpose: B <- A^T mult Multiplication: z <- A x + y _mult Matrix Vector Multiplication: y <- A x tri_solve Triangular Solve: x <- T^{-1} * x tri_solve Triangular Solve: B <- A^{-1} * B or B <- B * A^{-1} rank_one_update Rank One Update: A <- A + x * y^T rank_one_conj Rank One Update with conj(): A <- A + x * conj(y^T) rank_two_update Rank Two Update: A <- A + x * y^T + y * x^T rank_two_conj Rank Two Update with conj(): A <- A + x * conj(y^T) + y * conj(x^T) scatter Scatter y <- x gather Gather y <- x copy Copy: B <- A or y <- x __add Add: z <- x + y add Add: w <- x + y + z add Add: B <- A + B or y <- x + y ele_mult Element-wise Multiplication: z <- x O* y ele_mult Element-wise Multiply: B <- A O* B ele_div Element-wise Division: z <- x O/ y swap Swap: B <-> A or y <-> x dot Dot Product: s <- x . y + s dot Dot Product: s <- x . y dot Dot Product (extended precision): s <- x . y + s dot_conj Dot Conjugate: s <- x . conj(y) + s dot_conj Dot Conjugate: s <- x . conj(y) copy Copy transform Transform (one input iterator) transform Transform (two input iterators) fill Fill swap_ranges Swap Ranges accumulate Accumulate (with default operation) accumulate Accumulate (with user-supplied operation) inner_product Inner Product (user supplied operators) inner_product Inner Product (with default operators) lu_factor LU Factorization of a general (dense) matrix lu_solve LU Solve lu_inverse LU Inverse trans_iter Helper function for creating a transforming iterator read_dense_matlab Read a Dense Real Matrix from a Matlab file (.mat) write_dense_matlab Write a Dense Real Matrix to a Matlab file (.mat) read_sparse_matlab Read a Sparse Real Matrix from a Matlab file (.mat) write_sparse_matlab Write a Sparse Real Matrix to a Matlab file (.mat) gecon Estimate the reciprocal of the condition number of a general matrix. geev Compute the eigenvalues. geqpf QR Factorization with Column Pivoting. geqrf QR Factorization of a General Matrix gesv Solution to a linear system in a general matrix. getrf LU factorization of a general matrix A. getrs Solution to a system using LU factorization geequ Equilibrate and reduce condition number. gelqf Compute an LQ factorization. orglq Generate a matrix Q with orthonormal rows. orgqr Generate a matrix Q with orthonormal columns.

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