scipy.interpolate.UnivariateSpline.derivative#
- UnivariateSpline.derivative(n=1)[source]#
Construct a new spline representing the derivative of this spline.
- Parameters:
- nint, optional
Order of derivative to evaluate. Default: 1
- Returns:
- splineUnivariateSpline
Spline of order k2=k-n representing the derivative of this spline.
See also
Notes
New in version 0.13.0.
Examples
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([ 0.50000001, 1.5 , 2.49999998])
This agrees well with roots \(\pi/2 + n\pi\) of \(\cos(x) = \sin'(x)\).