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bundles / scipy latest / scipy / interpolate / _fitpack2 / UnivariateSpline / derivative

function

scipy.interpolate._fitpack2:UnivariateSpline.derivative

source: /scipy/interpolate/_fitpack2.py :552

Signature

def   derivative ( self n = 1 )

Summary

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.

Notes

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

See also

antiderivative
splder

Aliases

  • scipy.interpolate.UnivariateSpline.derivative