scipy.interpolate.sproot¶

scipy.interpolate.
sproot
(tck, mest=10)[source]¶ Find the roots of a cubic Bspline.
Given the knots (>=8) and coefficients of a cubic Bspline return the roots of the spline.
 Parameters
 tcktuple or a BSpline object
If a tuple, then it should be a sequence of length 3, containing the vector of knots, the Bspline 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.
 mestint, optional
An estimate of the number of zeros (Default is 10).
 Returns
 zerosndarray
An array giving the roots of the spline.
Notes
Manipulating the tcktuples directly is not recommended. In new code, prefer using the
BSpline
objects.References
 1
C. de Boor, “On calculating with bsplines”, J. Approximation Theory, 6, p.5062, 1972.
 2
M. G. Cox, “The numerical evaluation of bsplines”, J. Inst. Maths Applics, 10, p.134149, 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.