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SciPy

This is documentation for an old release of SciPy (version 0.17.1). Read this page in the documentation of the latest stable release (version 1.15.1).

scipy.interpolate.InterpolatedUnivariateSpline.derivative

InterpolatedUnivariateSpline.derivative(n=1)[source]

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

New in version 0.13.0.

Examples

This can be used for finding maxima of a curve:

>>>
>>> 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 π/2+nπ of cos(x) = sin’(x).