I would like to separate existing data of vertices and edges into two or more graphs that are not connected. I would like to give the following as example:
Imagine two hexagons on top of each other but are lying in different Z.
Hexagon 1 has the following vertices A(0,0,1), B(1,0,2), C(2,1,2), D(1,2,1), E(0,2,1), F(-1,2,1). The connectivity is as following: A-B, B-C, C-D, D-E, E-F, F-A. This part of Graph 1 as all the vertices are connected in this layer.
Hexagon2 has the following vertices A1(0,0,6), B1(1,0,7), C1(2,1,7), D1(1,2,8), E1(0,2,7), F1(-1,2,6). The connectivity is as following: A1-B1, B1-C1, C1-D1, D1-E1, E1-F1, F1-A1. This is part of Graph 2
My data is in the following form: list of Vertices and list of Edges that i can form graphs with. I would like to eliminate graph 2 and give only vertices and connectivity of graph 1 to polygon determination part of my algorithm. My real data contains around 1000 connected polygons as graph 1 and around 100 (much larger in area) polygons as graph 2. I would like to eliminate graph 2.
The problem you’re describing relates to connected components.
The Python Networkx module has functions for dealing with this type of graph problems. You’re looking for the connected_components function which returns all of the components, you can then pick the appropriate one (possible by number of vertices).