# scipy.interpolate.sproot

scipy.interpolate.sproot(tck, mest=10)

  Find the roots of a cubic B-spline.

  Given the knots (>=8) and coefficients of a cubic B-spline return the roots of the spline.

  Parameters
    tck tuple or a BSpline object

      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. The number of knots must be >= 8, and the degree must be 3. The knots must be a montonically increasing sequence.

    mest int, optional

      An estimate of the number of zeros (Default is 10).

  Returns
    zeros ndarray

      An array giving the roots of the spline.

  See also

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

  Notes

  Manipulating the tck-tuples directly is not recommended. In new code, prefer using the `BSpline` objects.

  References

  1

    C. de Boor, “On calculating with b-splines”, J. Approximation Theory, 6, p.50-62, 1972.

  2

    M. G. Cox, “The numerical evaluation of b-splines”, J. Inst. Maths Applics, 10, p.134-149, 1972.

  3

    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.splint scipy.interpolate.spalde