# 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. 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

 [R105] P.W. Gaffney, The calculation of indefinite integrals of b-splines”, J. Inst. Maths Applics, 17, p.37-41, 1976.
 [R106] P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993.

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