scipy.interpolate.splint¶
-
scipy.interpolate.
splint
(a, b, tck, full_output=0)[source]¶ Evaluate the definite integral of a B-spline between two given points.
Parameters: - a, b : float
The end-points of the integration interval.
- tck : tuple or a BSpline instance
If a tuple, then it should be a sequence of length 3, containing the vector of knots, the B-spline coefficients, and the degree of the spline (see
splev
).- full_output : int, optional
Non-zero to return optional output.
Returns: - integral : float
The resulting integral.
- wrk : ndarray
An array containing the integrals of the normalized B-splines defined on the set of knots. (Only returned if full_output is non-zero)
Notes
splint
silently assumes that the spline function is zero outside the data interval (a, b).Manipulating the tck-tuples directly is not recommended. In new code, prefer using the
BSpline
objects.References
[1] P.W. Gaffney, The calculation of indefinite integrals of b-splines”, J. Inst. Maths Applics, 17, p.37-41, 1976. [2] P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993.