scipy.interpolate.splev¶

scipy.interpolate.
splev
(x, tck, der=0, ext=0)[source]¶ Evaluate a Bspline or its derivatives.
Given the knots and coefficients of a Bspline representation, evaluate the value of the smoothing polynomial and its derivatives. This is a wrapper around the FORTRAN routines splev and splder of FITPACK.
 Parameters
 xarray_like
An 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. tck3tuple or a BSpline object
If a tuple, then it should be a sequence of length 3 returned by
splrep
orsplprep
containing the knots, coefficients, and degree of the spline. (Also see Notes.) derint, optional
The order of derivative of the spline to compute (must be less than or equal to k, the degree of the spline).
 extint, optional
Controls the value returned for elements of
x
not in the interval defined by the knot sequence.if ext=0, return the extrapolated value.
if ext=1, return 0
if ext=2, raise a ValueError
if ext=3, return the boundary value.
The default value is 0.
 Returns
 yndarray or list of ndarrays
An array of values representing the spline function evaluated at the points in x. If tck was returned from
splprep
, then this is a list of arrays representing the curve in Ndimensional space.
Notes
Manipulating the tcktuples directly is not recommended. In new code, prefer using
BSpline
objects.References
 1
C. de Boor, “On calculating with bsplines”, J. Approximation Theory, 6, p.5062, 1972.
 2
M. G. Cox, “The numerical evaluation of bsplines”, J. Inst. Maths Applics, 10, p.134149, 1972.
 3
P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993.