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SciPy

This is documentation for an old release of SciPy (version 0.19.0). Read this page in the documentation of the latest stable release (version 1.15.1).

scipy.interpolate.splder

scipy.interpolate.splder(tck, n=1)[source]

Compute the spline representation of the derivative of a given spline

Parameters:

tck : BSpline instance or a tuple of (t, c, k)

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 iff the input argument tck is a tuple, otherwise a BSpline object is constructed and returned.

Notes

New in version 0.13.0.

Examples

This can be used for finding maxima of a curve:

>>>
>>> from scipy.interpolate import splrep, splder, sproot
>>> 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([ 0.50000001,  1.5       ,  2.49999998])

This agrees well with roots π/2+nπ of cos(x)=sin(x).