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

Notes

If a source is not specified then a source is chosen arbitrarily and repeatedly until all components in the graph are searched.

The implementation of this function is adapted from David Eppstein's depth-first search function in :None:None:`PADS`, with modifications to allow depth limits based on the Wikipedia article ":None:None:`Depth-limited search`".

            <Unimplemented 'target' '.. _PADS: http://www.ics.uci.edu/~eppstein/PADS'>
           
            <Unimplemented 'target' '.. _Depth-limited search: https://en.wikipedia.org/wiki/Depth-limited_search'>
           

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

pred: dict

A dictionary with nodes as keys and predecessor nodes as values.

Returns dictionary of predecessors in 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(4)
... nx.dfs_predecessors(G, source=0) {1: 0, 2: 1, 3: 2}
>>> nx.dfs_predecessors(G, source=0, depth_limit=2)
{1: 0, 2: 1}
See :

Back References

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

networkx.algorithms.traversal.depth_first_search.dfs_predecessors

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


GitHub : /networkx/algorithms/traversal/depth_first_search.py#142
type: <class 'function'>
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