multidim.PointCloud.sever

PointCloud.sever()

Subdivide a SimplicialComplex or PointCloud into several smaller partitions, using the known 0-dimensional persistence diagram. This is an iterator (it _yields_ the terms).

Two points end up in the same partition if and only if they are connected by a sequence of edges of length < cutoff.

Yields:

pairs (indices, subpointcloud) of persistently connected

SimplicialComplexes/PointClouds.

The first term gives indices of the these points from the original `PointCloud`

The second term gives a new `PointCloud` with its own sequential index.

See also

make_pers0()

func:reset

Notes

This uses the 0-dimensional Persistence Diagram; therefore, you should run self.reset() and self.make_pers0(cutoff) first.

Examples

>>> pc = PointCloud(np.array([[0.,0.],[0.,0.5],[1.,0.],[5.,0.],[6.,0.],[5.,-0.6]]), max_length=-1.0)
>>> pc.make_pers0(cutoff=1.9)
>>> for indices,sub_pc in pc.sever():
...     print(indices)
...     print(sub_pc)
...     print(sub_pc.coords)
[0 1 2]
A SimplicialComplex with 3 points, 0 edges, and 0 faces.
     0    1
0  0.0  0.0
1  0.0  0.5
2  1.0  0.0
[3 4 5]
A SimplicialComplex with 3 points, 0 edges, and 0 faces.
     0    1
0  5.0  0.0
1  6.0  0.0
2  5.0 -0.6