scipy.interpolate.spalde#
- scipy.interpolate.spalde(x, tck)[source]#
Evaluate all derivatives of a B-spline.
Given the knots and coefficients of a cubic B-spline compute all derivatives up to order k at a point (or set of points).
- Parameters
- xarray_like
A point or a set of points at which to evaluate the derivatives. Note that
t(k) <= x <= t(n-k+1)
must hold for each x.- tcktuple
A tuple
(t, c, k)
, containing the vector of knots, the B-spline coefficients, and the degree of the spline (seesplev
).
- Returns
- results{ndarray, list of ndarrays}
An array (or a list of arrays) containing all derivatives up to order k inclusive for each point x.
References
- 1
C. de Boor: On calculating with b-splines, J. Approximation Theory 6 (1972) 50-62.
- 2
M. G. Cox : The numerical evaluation of b-splines, J. Inst. Maths applics 10 (1972) 134-149.
- 3
P. Dierckx : Curve and surface fitting with splines, Monographs on Numerical Analysis, Oxford University Press, 1993.
Examples
Examples are given in the tutorial.