This is documentation for an old release of SciPy (version 0.7.). Read this page in the documentation of the latest stable release (version 1.15.1).
scipy.interpolate.spalde¶
- scipy.interpolate.spalde(x, tck)¶
Evaluate all derivatives of a B-spline.
Description:
Given the knots and coefficients of a cubic B-spline compute all derivatives up to order k at a point (or set of points).
Inputs:
tck – A length 3 sequence describing the given spline (See splev). x – 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.
Outputs: (results, )
- results – An array (or a list of arrays) containing all derivatives
- up to order k inclusive for each point x.
- See also:
splprep, splrep, splint, sproot, splev - evaluation, roots, integral bisplrep, bisplev - bivariate splines UnivariateSpline, BivariateSpline - an alternative wrapping
of the FITPACK functions
Notes: Based on algorithms from:
- de Boor C : On calculating with b-splines, J. Approximation Theory
- 6 (1972) 50-62.
- Cox M.G. : The numerical evaluation of b-splines, J. Inst. Maths
- applics 10 (1972) 134-149.
- Dierckx P. : Curve and surface fitting with splines, Monographs on
- Numerical Analysis, Oxford University Press, 1993.
