'Construct a new spline representing the derivative of this spline.
Parameters
n : int, optional
Order of derivative to evaluate. Default: 1
Returns
spline : UnivariateSpline
Spline of order k2=k-n representing the derivative of this
spline.
See Also
splder, antiderivative
Notes
.. versionadded:: 0.13.0
Examples
This can be used for finding maxima of a curve:
>>> from scipy.interpolate import UnivariateSpline
>>> x = np.linspace(0, 10, 70)
>>> y = np.sin(x)
>>> spl = UnivariateSpline(x, y, k=4, s=0)
Now, differentiate the spline and find the zeros of the
derivative. (NB: `sproot` only works for order 3 splines, so we
fit an order 4 spline):
>>> spl.derivative().roots() / np.pi
array([ 0.50000001,  1.5       ,  2.49999998])
This agrees well with roots :math:`\pi/2 + n\pi` of
:math:`\cos(x) = \sin\'(x)`.'

def derivative(self, n=1):

    tck = fitpack.splder(self._eval_args, n)
    return UnivariateSpline._from_tck(tck, self.ext)
