networkx.algorithms.dag.transitive_reduction¶
- transitive_reduction(G)[source]¶
Returns transitive reduction of a directed graph
The transitive reduction of G = (V,E) is a graph G- = (V,E-) such that for all v,w in V there is an edge (v,w) in E- if and only if (v,w) is in E and there is no path from v to w in G with length greater than 1.
- Parameters
- GNetworkX DiGraph
A directed acyclic graph (DAG)
- Returns
- NetworkX DiGraph
The transitive reduction of
G
- Raises
- NetworkXError
If
G
is not a directed acyclic graph (DAG) transitive reduction is not uniquely defined and aNetworkXError
exception is raised.
References
https://en.wikipedia.org/wiki/Transitive_reduction
Examples
To perform transitive reduction on a DiGraph:
>>> DG = nx.DiGraph([(1, 2), (2, 3), (1, 3)]) >>> TR = nx.transitive_reduction(DG) >>> list(TR.edges) [(1, 2), (2, 3)]
To avoid unnecessary data copies, this implementation does not return a DiGraph with node/edge data. To perform transitive reduction on a DiGraph and transfer node/edge data:
>>> DG = nx.DiGraph() >>> DG.add_edges_from([(1, 2), (2, 3), (1, 3)], color='red') >>> TR = nx.transitive_reduction(DG) >>> TR.add_nodes_from(DG.nodes(data=True)) >>> TR.add_edges_from((u, v, DG.edges[u, v]) for u, v in TR.edges) >>> list(TR.edges(data=True)) [(1, 2, {'color': 'red'}), (2, 3, {'color': 'red'})]