`scipy.interpolate._fitpack_py:splder`

source: build-install/usr/lib/python3.14/site-packages/scipy/interpolate/_fitpack_py.py:771

Signature

def splder(tck, n = 1)

Summary

Compute the spline representation of the derivative of a given spline.

Parameters

tck : BSpline instance or tuple: BSpline instance or a tuple (t,c,k) containing the vector of knots, the B-spline coefficients, and the degree of the spline whose derivative to compute
n : int, optional: Order of derivative to evaluate. Default: 1

Returns

: `BSpline` instance or tuple: Spline of order k2=k-n representing the derivative of the input spline. A tuple is returned if the input argument tck is a tuple, otherwise a BSpline object is constructed and returned.

Notes

Array API Standard Support

splder is not in-scope for support of Python Array API Standard compatible backends other than NumPy.

See dev-arrayapi for more information.

Examples

This can be used for finding maxima of a curve:

from scipy.interpolate import splrep, splder, sproot
import numpy as np
x = np.linspace(0, 10, 70)
y = np.sin(x)
spl = splrep(x, y, k=4)

✓

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):

dspl = splder(spl)

✓

sproot(dspl) / 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)`. A comparison between `splev`, `splder` and `spalde` to compute the derivatives of a B-spline can be found in the `spalde` examples section.

Aliases

scipy.interpolate.splder