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 – A length 3 sequence describing the given spline (See splev). :

The number of knots must be >= 8. The knots must be a montonically increasing sequence.

mest – An estimate of the number of zeros (Default is 10) :

Returns :

zeros – An array giving the roots of the spline. :

See also

splprep, splrep, splint, spalde, splev, bisplrep, bisplev, UnivariateSpline, BivariateSpline

References

[R10]

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

[R11]

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

[R12]

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