`scipy.linalg._flapack:dsyevx`

Summary

Compute selected eigenvalues and optionally eigenvectors of a real symmetric matrix (LAPACK dsyevx).

a : ndarray: Symmetric matrix of shape (n, n).
compute_v : int, optional: If nonzero, eigenvectors are computed as well as eigenvalues. Default is 1.
range : str, optional: 'A' for all eigenvalues, 'V' for those in (vl, vu], 'I' for those indexed il through iu. Default is 'A'.
lower : int, optional: If nonzero, the lower triangle of a is referenced; otherwise the upper. Default is 0.
vl : float, optional: Lower bound of the interval; used only when range is 'V'. Default is 0.0.
vu : float, optional: Upper bound of the interval; used only when range is 'V'. Default is 1.0.
il : int, optional: Index of the smallest eigenvalue to return, 1-based; used only when range is 'I'. Default is 1.
iu : int, optional: Index of the largest eigenvalue to return, 1-based; used only when range is 'I'. Default is n.
abstol : float, optional: Absolute error tolerance for the eigenvalues. Default is 0.0.
lwork : int, optional: Size of the workspace. Default is max(8 * n, 1). Use dsyevx_lwork for the optimal value.
overwrite_a : int, optional: If nonzero, a may be overwritten in place. Default is 0.

w : ndarray: Eigenvalues in ascending order, length n. Real for every flavor.
z : ndarray: The m computed eigenvectors as columns, or empty when compute_v is 0.
m : int: Number of eigenvalues found.
ifail : ndarray: Indices of eigenvectors that failed to converge, 1-based.
info : int: 0 on success; if negative, the -info-th argument had an illegal value; if positive, the algorithm failed to converge.