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
[R78] P.W. Gaffney, The calculation of indefinite integrals of b-splines”, J. Inst. Maths Applics, 17, p.37-41, 1976. [R79] P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993.