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# 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

  [R90] | C. de Boor, “On calculating with b-splines”, J. Approximation Theory, 6, p.50-62, 1972.

  [R91] | M. G. Cox, “The numerical evaluation of b-splines”, J. Inst. Maths Applics, 10, p.134-149, 1972.

  [R92] | P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993.