- scipy.interpolate.splint(a, b, tck, full_output=0)¶
Evaluate the definite integral of a B-spline.
Given the knots and coefficients of a B-spline, evaluate the definite integral of the smoothing polynomial between two given points.
a, b : float
The end-points of the integration interval.
tck : tuple
A tuple (t,c,k) 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.
integral : float
The resulting integral.
wrk : ndarray
An array containing the integrals of the normalized B-splines defined on the set of knots.
splint silently assumes that the spline function is zero outside the data interval (a, b).
[R61] P.W. Gaffney, The calculation of indefinite integrals of b-splines”, J. Inst. Maths Applics, 17, p.37-41, 1976. [R62] P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993.