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 (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 - 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. 
 
