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_dussm() def csr_dussm ( uplo  , trans  , diag  , order  , n  , nrhs  , val  , rowptr  , colind  , base  , x    ) Solution of AX = B or ATX = B (Triangular matrices) (CSR) Purpose This function solves one of the following systems of equations for a sparse matrix in CSR format. A*X = B or A^T*X = B where A is an n x n upper or lower sparse triangular matrix, and B and X are n x nrhs dense matrices. Returns info (int) = 0: Successful exit. = i < 0: The (-i)-th argument is invalid. = i > 0: The matrix is singular (i-th diagonal element is zero). Parameters [in] uplo Specifies whether the matrix is an upper or lower triangular matrix as follows: = 'U': A is an upper triangular matrix. = 'L': A is an lower triangular matrix. The other triangular elements (not including diagonal elements) are ignored. [in] trans Specifies the equation to be solved as follows: = 'N': A*X = B. = 'T' or 'C': A^T*X = B. [in] diag Specifies whether or not A is assumed to be unit triangular. = 'N': A is not assumed to be unit triangular. = 'U': A is assumed to be unit triangular. (diagonal elements are assumed to be ones. val[]s at diagonal element positions (if exist) are ignored.) [in] order Storage order of x[]. = 'C': Column major. = 'R': Row major. [in] n Number of rows and columns of matrix A. (n >= 0) (If n = 0, returns without computation) [in] nrhs Number of columns of matrices B and C. (nrhs >= 0) (if nrhs = 0, returns without computation) [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, n + 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] ldx Leading dimension of two dimensional array x[]. (ldx >= n) [in,out] x Numpy ndarray (2-dimensional, float, n x nrhs) [in] Right-hand side matrix B. [out] Solution matrix X.