dgecon dgecov dgels dgesv dlange dlansy dpocon dposv dsyev

dsyev() def dsyev ( jobz  , uplo  , n  , a  , w    ) Eigenvalues and eigenvectors of a symmetric matrix Purpose dsyev computes all eigenvalues and, optionally, eigenvectors of a real symmetric matrix A. Returns info (int) = 0: Successful exit = -1: The argument jobz had an illegal value (jobz != 'V' nor 'N') = -2: The argument uplo had an illegal value (uplo != 'U' nor 'L') = -3: The argument n had an illegal value (n < 0) = -4: The argument a is invalid. = -5: The argument w is invalid. = i > 0: The algorithm failed to converge; i off-diagonal elements of an intermediate tridiagonal form did not converge to zero. Parameters [in] jobz = 'N': Compute eigenvalues only. = 'V': Compute eigenvalues and eigenvectors. [in] uplo = 'U': Upper triangle of A is stored. = 'L': Lower triangle of A is stored. [in] n Order of the matrix A. (n >= 0) (If n = 0, returns without computation) [in,out] a Numpy ndarray (2-dimensional, float, n x n) [in] n x n symmetric matrix A. The upper or lower triangular part is to be stored in accordance with uplo. [out] jobz = 'V': If info = 0, a contains the orthonormal eigenvectors of the matrix A.   jobz = 'N': The lower triangle (if uplo = 'L') or the upper triangle (if uplo = 'U') of a, including the diagonal, is destroyed. [out] w Numpy ndarray (1-dimensional, float, n) If info = 0, the eigenvalues in ascending order. Reference LAPACK Example Program Compute all eigenvalues and eigenvectors of the symmetric matrix A, where ( 2.20 -0.11 -0.32 ) A = ( -0.11 2.93 0.81 ) ( -0.32 0.81 2.37 ) def TestDsyev(): n = 3 a = np.array([ [2.2, 0.0, 0.0], [-0.11, 2.93, 0.0], [-0.32, 0.81, 2.37]]) w = np.empty(3) info = dsyev('V', 'U', n, a, w) print(w, info) print(a) Example Results >>> TestDsyev() [1.70705955 2.22943643 3.56350402] 0 [[-0.39932208 0.48102644 -0.78048411] [ 0.89452139 0.39099459 -0.21669038] [-0.20093126 0.78468898 0.58642121]]