skspatial.objects.Circle.best_fit

classmethod Circle.best_fit(points: Union[ndarray, Sequence]) → Circle

Return the sphere of best fit for a set of 2D points.

Parameters

pointsarray_like

Input 2D points.

Returns

Circle

The circle of best fit.

Raises

ValueError

If the points are not 2D. If there are fewer than three points. If the points are collinear.

References

https://meshlogic.github.io/posts/jupyter/curve-fitting/fitting-a-circle-to-cluster-of-3d-points/

Examples

>>> import numpy as np

>>> from skspatial.objects import Circle

>>> points = [[1, 1], [2, 2], [3, 1]]
>>> circle = Circle.best_fit(points)

>>> circle.point
Point([2., 1.])

>>> np.round(circle.radius, 2)
1.0