bicg1 cg1 coo_csr csr_coo csr_dense csr_dusmm csr_dusmv csr_dussm csr_dussv csr_ssr csr_trans dense_csr ssr_csr ssr_dusmv

csr_dusmv() def csr_dusmv ( trans  , m  , n  , alpha  , val  , rowptr  , colind  , base  , x  , incx  , beta  , y  , incy    ) y <- αAx + βy or y <- αATx + βy (CSR) Purpose This function performs one of the following matrix-vector operations for a sparse matrix in CSR format. y <- αAx + βy or y <- αA^Tx + βy where alpha and beta are scalars, x and y are vectors and A is an m x n sparse matrix. Returns info (int) = 0: Successful exit. = i < 0: The (-i)-th argument is invalid. Parameters [in] trans Specifies the operation to be performed. = 'N': y <- y <- αAx + βy. = 'T' or 'C': y <- αA^Tx + βy. [in] m Number of rows of matrix A. (m >= 0) (If m = 0, returns without computation) [in] n Number of columns of matrix A. (n >= 0) (If n = 0, returns without computation) [in] alpha Scalar α [in] val Numpy ndarray (1-dimensional, float, nnz) Values of nonzero elements of matrix A (where nnz is the number of nonzero elements). [in] rowptr Numpy ndarray (1-dimensional, int32, m + 1) Row pointers of matrix A. [in] colind Numpy ndarray (1-dimensional, int32, nnz) Column indices of matrix A (where nnz is the number of nonzero elements). [in] base Indexing of rowptr and colind. = 0: Zero-based (C style) indexing: Starting index is 0. = 1: One-based (Fortran style) indexing: Starting index is 1. [in] x Numpy ndarray (1-dimensional, float, 1 + (n - 1)*incx (if trans = 'N'), 1 + (m - 1)*incx (if trans = 'T' or 'C')) Vector x. [in] incx Storage spacing between elements of x. [in] beta Scalar β. [in,out] y Numpy ndarray (1-dimensional, float, 1 + (m - 1)*incy (if trans = 'N'), 1 + (n - 1)*incy (if trans = 'T' or 'C')) [in] Input vector y (If beta is supplied as zero, y needs not be set on input). [out] Output vector. (= αAx + βy) [in] incy Storage spacing between elements of y.