def getEigSorted(matrix):
    """Obtains eigenvalues and eigenvectors of a diagonalizable matrix. The
    eigenvalues are sorted descending.

    Parameters:
        matrix (`numpy.ndarray`): :math:`(3 \\times 3)` diagonalizable matrix.

    Returns:
        Two elements are returned; they are described below.

            - **sortedEigVal** (`numpy.ndarray`): :math:`(3 \\times 1)` array                with the eigenvalues ordered descending.
            - **sortedEigVec** (`numpy.ndarray`): :math:`(3 \\times 3)` array                with the eigenvectors, such that the column                 ``sortedEigVec[:, i]`` is the eigenvector corresponding to the                eigenvalue ``sortedEigVal[i]``
    Examples:
        >>> from numpy import array
        >>> from jelinekstat.tools import getEigSorted
        >>> matrix = array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
        >>> sortedEigVal, sortedEigVec = getEigSorted(matrix)
        >>> sortedEigVal
        array([  1.61168440e+01,  -9.75918483e-16,  -1.11684397e+00])
        >>> sortedEigVec
        array([[-0.23197069,  0.40824829, -0.78583024],
               [-0.52532209, -0.81649658, -0.08675134],
               [-0.8186735 ,  0.40824829,  0.61232756]])
    """
    import numpy as np
    eigVal, eigVec = np.linalg.eig(matrix)
    idx = eigVal.argsort()[::-1]
    sortedEigVal = eigVal[idx]
    sortedEigVec = eigVec[:, (idx)]
    return sortedEigVal, sortedEigVec
