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 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.
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.