# scipy.interpolate.splint

scipy.interpolate.splint(a, b, tck, full_output=0)

  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)

  See also

  `splprep`, `splrep`, `sproot`, `spalde`, `splev`
  `bisplrep`, `bisplev`
  `BSpline`

  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.

  Examples

  Examples are given in the tutorial.

scipy.interpolate.splev scipy.interpolate.sproot