scipy.interpolate.

splev#

scipy.interpolate.splev(x, tck, der=0, ext=0)[source]#

Evaluate a B-spline or its derivatives.

Legacy

This function is considered legacy and will no longer receive updates. While we currently have no plans to remove it, we recommend that new code uses more modern alternatives instead. Specifically, we recommend constructing a BSpline object and using its __call__ method.

Given the knots and coefficients of a B-spline representation, evaluate the value of the smoothing polynomial and its derivatives. This is a wrapper around the FORTRAN routines splev and splder of FITPACK.

Parameters:

xarray_like

An array of points at which to return the value of the smoothed spline or its derivatives. If tck was returned from splprep, then the parameter values, u should be given.

tckBSpline instance or tuple

If a tuple, then it should be a sequence of length 3 returned by splrep or splprep containing the knots, coefficients, and degree of the spline. (Also see Notes.)

derint, optional

The order of derivative of the spline to compute (must be less than or equal to k, the degree of the spline).

extint, optional

Controls the value returned for elements of x not in the interval defined by the knot sequence.

if ext=0, return the extrapolated value.
if ext=1, return 0
if ext=2, raise a ValueError
if ext=3, return the boundary value.

The default value is 0.

Returns:

yndarray or list of ndarrays: An array of values representing the spline function evaluated at the points in x. If tck was returned from splprep, then this is a list of arrays representing the curve in an N-D space.