'Return all derivatives of the spline at the point x.
Parameters
x : float
The point to evaluate the derivatives at.
Returns
der : ndarray, shape(k+1,)
Derivatives of the orders 0 to k.
Examples
>>> from scipy.interpolate import UnivariateSpline
>>> x = np.linspace(0, 3, 11)
>>> y = x**2
>>> spl = UnivariateSpline(x, y)
>>> spl.derivatives(1.5)
array([2.25, 3.0, 2.0, 0])'

def derivatives(self, x):

    (d, ier) = dfitpack.spalde(*(self._eval_args + (x,)))
    if (not (ier == 0)):
        raise ValueError(('Error    code    returned    by    spalde:    %s' % ier))
    return d
