skspatial.objects.Line.best_fit

classmethod Line.best_fit(points: Union[ndarray, Sequence], tol: Optional[float] = None, **kwargs) → Line

Return the line of best fit for a set of points.

Parameters:

pointsarray_like

Input points.

tolfloat | None, optional

Keyword passed to Points.are_collinear() (default None).

kwargsdict, optional

Additional keywords passed to numpy.linalg.svd()

Returns:

Line

The line of best fit.

Raises:

ValueError

If the points are concurrent.

Examples

>>> from skspatial.objects import Line

>>> points = [[0, 0], [1, 2], [2, 1], [2, 3], [3, 2]]
>>> line = Line.best_fit(points)

The point on the line is the centroid of the points.

>>> line.point
Point([1.6, 1.6])

The line direction is a unit vector.

>>> line.direction.round(3)
Vector([0.707, 0.707])