edge_boundary#
- edge_boundary(G, nbunch1, nbunch2=None, data=False, keys=False, default=None)[source]#
Returns the edge boundary of nbunch1.
The edge boundary of a set S with respect to a set T is the set of edges (u, v) such that u is in S and v is in T. If T is not specified, it is assumed to be the set of all nodes not in S.
- Parameters:
- GNetworkX graph
- nbunch1iterable
Iterable of nodes in the graph representing the set of nodes whose edge boundary will be returned. (This is the set S from the definition above.)
- nbunch2iterable
Iterable of nodes representing the target (or “exterior”) set of nodes. (This is the set T from the definition above.) If not specified, this is assumed to be the set of all nodes in G not in nbunch1.
- keysbool
This parameter has the same meaning as in
MultiGraph.edges().- databool or object
This parameter has the same meaning as in
MultiGraph.edges().- defaultobject
This parameter has the same meaning as in
MultiGraph.edges().
- Returns:
- iterator
An iterator over the edges in the boundary of nbunch1 with respect to nbunch2. If keys, data, or default are specified and G is a multigraph, then edges are returned with keys and/or data, as in
MultiGraph.edges().
Notes
Any element of nbunch that is not in the graph G will be ignored.
nbunch1 and nbunch2 are usually meant to be disjoint, but in the interest of speed and generality, that is not required here.
Examples
>>> G = nx.wheel_graph(6)
When nbunch2=None:
>>> list(nx.edge_boundary(G, (1, 3))) [(1, 0), (1, 2), (1, 5), (3, 0), (3, 2), (3, 4)]
When nbunch2 is given:
>>> list(nx.edge_boundary(G, (1, 3), (2, 0))) [(1, 0), (1, 2), (3, 0), (3, 2)]
Additional backends implement this function
graphblas : OpenMP-enabled sparse linear algebra backend.