`scipy.interpolate._fitpack2:UnivariateSpline.derivative`

Signature

def derivative(self, n = 1)

Construct a new spline representing the derivative of this spline.

spline : UnivariateSpline: Spline of order k2=k-n representing the derivative of this spline.

This can be used for finding maxima of a curve:

import numpy as np
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([0.5, 1.5, 2.5])

This agrees well with roots :math:`\pi/2 + n\pi` of :math:`\cos(x) = \sin'(x)`.