from scipy.linalg import eig

def distanceM():
    return np.array([[0.0, 0.8, 0.6, 0.1, 0.0, 0.0], [0.8, 0.0, 0.9, 0.0, 
        0.0, 0.0], [0.6, 0.9, 0.0, 0.0, 0.0, 0.2], [0.1, 0.0, 0.0, 0.0, 0.6,
        0.7], [0.0, 0.0, 0.0, 0.6, 0.0, 0.8][0.0, 0.0, 0.2, 0.7, 0.8, 0.0]])
if __name__ == '__main__':
    w = distanceM()
D = diag(w)
L = D - w
w, vr = eig(L)
print(vr)
how to perform a generalised eigendecomposition here?