dfs_tree(G, source=None, depth_limit=None)

Parameters

G : NetworkX graph

source : node, optional

Specify starting node for depth-first search.

depth_limit : int, optional (default=len(G))

Specify the maximum search depth.

Returns

T : NetworkX DiGraph

An oriented tree

Returns oriented tree constructed from a depth-first-search from source.

See Also

bfs_tree

dfs_labeled_edges

dfs_postorder_nodes

dfs_preorder_nodes

edge_dfs

Examples

>>> G = nx.path_graph(5)
... T = nx.dfs_tree(G, source=0, depth_limit=2)
... list(T.edges())
[(0, 1), (1, 2)]

>>> T = nx.dfs_tree(G, source=0)
... list(T.edges())
[(0, 1), (1, 2), (2, 3), (3, 4)]

See :

Back References

The following pages refer to to this document either explicitly or contain code examples using this.

networkx.algorithms.traversal.breadth_first_search.bfs_tree networkx.algorithms.traversal.depth_first_search.dfs_tree

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /networkx/algorithms/traversal/depth_first_search.py#97
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