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: x : array_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.
tck : tuple
A tuple (t, c, k), containing the vector of knots, the B-spline coefficients, and the degree of the spline (see splev).
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
[R75] C. de Boor: On calculating with b-splines, J. Approximation Theory 6 (1972) 50-62. [R76] M. G. Cox : The numerical evaluation of b-splines, J. Inst. Maths applics 10 (1972) 134-149. [R77] P. Dierckx : Curve and surface fitting with splines, Monographs on Numerical Analysis, Oxford University Press, 1993.