scipy.interpolate.splev(x, tck, der=0)

Evaulate a B-spline and its derivatives.


Given the knots and coefficients of a B-spline representation, evaluate the value of the smoothing polynomial and it’s derivatives. This is a wrapper around the FORTRAN routines splev and splder of FITPACK.


x (u) – a 1-D array of points at which to return the value of the
smoothed spline or its derivatives. If tck was returned from splprep, then the parameter values, u should be given.
tck – A sequence of length 3 returned by splrep or splprep containg the
knots, coefficients, and degree of the spline.
der – The order of derivative of the spline to compute (must be less than
or equal to k).

Outputs: (y, )

y – an array of values representing the spline function or curve.
If tck was returned from splrep, then this is a list of arrays representing the curve in N-dimensional space.
See also:

splprep, splrep, sproot, spalde, splint - evaluation, roots, integral bisplrep, bisplev - bivariate splines UnivariateSpline, BivariateSpline - an alternative wrapping

of the FITPACK functions
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.

Previous topic


Next topic


This Page

Quick search