def inverse_matrix(matrix):
return numpy.linalg.inv(matrix)<EOL>
Return inverse of square transformation matrix.

    >>> M0 = random_rotation_matrix()
    >>> M1 = inverse_matrix(M0.T)
    >>> numpy.allclose(M1, numpy.linalg.inv(M0.T))
    True
    >>> for size in range(1, 7):
    ...     M0 = numpy.random.rand(size, size)
    ...     M1 = inverse_matrix(M0)
    ...     if not numpy.allclose(M1, numpy.linalg.inv(M0)): print(size)