<SYSTEM_TASK:>
Solve the following problem using Python, implementing the functions described below, one line at a time
<END_TASK>
<USER_TASK:>
Description:
 def _eigsorted(cov, asc=True):
 """ Computes eigenvalues and eigenvectors of a covariance matrix and returns them sorted by eigenvalue. Parameters cov : ndarray covariance matrix asc : bool, default=True determines whether we are sorted smallest to largest (asc=True), or largest to smallest (asc=False) Returns ------- eigval : 1D ndarray eigenvalues of covariance ordered largest to smallest eigvec : 2D ndarray eigenvectors of covariance matrix ordered to match `eigval` ordering. I.e eigvec[:, 0] is the rotation vector for eigval[0] """


    eigval, eigvec = np.linalg.eigh(cov)
    order = eigval.argsort()
    if not asc:
        # sort largest to smallest
        order = order[::-1]

    return eigval[order], eigvec[:, order]