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scipy.interpolate.

# splint

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

  Evaluate the definite integral of a B-spline between two given points.

  Legacy

  This function is considered legacy and will no longer receive updates. While we currently have no plans to remove it, we recommend that new code uses more modern alternatives instead. Specifically, we recommend constructing a `BSpline` object and using its `integrate` method.

  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.

  Array API Standard Support

  `splint` is not in-scope for support of Python Array API Standard compatible backends other than NumPy.

  See Support for the array API standard for more information.

  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.