scipy.interpolate.LSQUnivariateSpline.

roots#

LSQUnivariateSpline.roots()[source]#

Return the zeros of the spline.

See also

sproot
PPoly.roots

Notes

Restriction: only cubic splines are supported by FITPACK. For non-cubic splines, use PPoly.root (see below for an example).

Examples

For some data, this method may miss a root. This happens when one of the spline knots (which FITPACK places automatically) happens to coincide with the true root. A workaround is to convert to PPoly, which uses a different root-finding algorithm.

For example,

>>> x = [1.96, 1.97, 1.98, 1.99, 2.00, 2.01, 2.02, 2.03, 2.04, 2.05]
>>> y = [-6.365470e-03, -4.790580e-03, -3.204320e-03, -1.607270e-03,
...      4.440892e-16,  1.616930e-03,  3.243000e-03,  4.877670e-03,
...      6.520430e-03,  8.170770e-03]
>>> from scipy.interpolate import UnivariateSpline
>>> spl = UnivariateSpline(x, y, s=0)
>>> spl.roots()
array([], dtype=float64)

Converting to a PPoly object does find the roots at x=2:

>>> from scipy.interpolate import splrep, PPoly
>>> tck = splrep(x, y, s=0)
>>> ppoly = PPoly.from_spline(tck)
>>> ppoly.roots(extrapolate=False)
array([2.])