Points class represents multiple points in space.
Vector objects are instantiated with a 1D array, a
Points object is instantiated with a 2D array.
>>> from skspatial.objects import Points
>>> points = Points([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
The centroid of the points is a
>>> points.centroid() Point([4., 5., 6.])
The points can be mean-centered, meaning that the centroid is treated as the origin of a new coordinate system. The original centroid can also be returned by the method.
>>> points_centered, centroid = points.mean_center(return_centroid=True)
>>> points_centered Points([[-3., -3., -3.], [ 0., 0., 0.], [ 3., 3., 3.]])
>>> centroid Point([4., 5., 6.])
The affine rank is the dimension of the smallest affine space that contains all the points. For example, if the points are contained by a line, the affine rank is one.
>>> points.affine_rank() 1
The affine rank is used to test for concurrency, collinearity and coplanarity.
>>> points.are_concurrent() False >>> points.are_collinear() True >>> points.are_coplanar() True