scipy.interpolate.sproot¶
- scipy.interpolate.sproot(tck, mest=10)[source]¶
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
A tuple (t,c,k) 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, UnivariateSpline, BivariateSpline
References
[R85] C. de Boor, “On calculating with b-splines”, J. Approximation Theory, 6, p.50-62, 1972. [R86] M.G. Cox, “The numerical evaluation of b-splines”, J. Inst. Maths Applics, 10, p.134-149, 1972. [R87] P. Dierckx, “Curve and surface fitting with splines”, Monographs on Numerical Analysis, Oxford University Press, 1993.