Python scipy interpolate.BSpline usage and code examples English original link: https://docs.scipy.org/doc/scipy-0.19.1/reference/generated/scipy.interpolate.BSpline.html

This article is transferred from: https://vimsky.com/examples/usage/python-scipy.interpolate.BSpline.html Usage: class scipy.interpolate.BSpline(t, c, k, extrapolate=True, axis=0) with B- spline-based univariate splines.

where are the B-spline basis functions of degree k and knot t.

Parameters: t: ndarray, shape (n+k+1,) knot

c: ndarray, shape (>=n, ...) spline coefficients

k : int B-spline order

extrapolate : bool or 'periodic', optional Whether to extrapolate beyond the base interval, t[k] ... t[n], or return nans. If True, infer the first and last polynomials of the b-spline function active on the base interval. If 'periodic', use periodic extrapolation. The default value is True.

axis : int, optional parameter Axis of interpolation. The default value is zero.

Note: B-spline primitives pass

implementation details

Splines of order k+1k need coefficients at least, so n >= k+1. Additional coefficients, c[j] with j > n, will be ignored.

The B-spline basic elements of degree k form a unit partition on the basic interval, t[k]