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is_tree(G)

A tree is a connected graph with no undirected cycles.

For directed graphs, G is a tree if the underlying graph is a tree. The underlying graph is obtained by treating each directed edge as a single undirected edge in a multigraph.

Notes

In another convention, a directed tree is known as a polytree and then tree corresponds to an arborescence.

Parameters

G : graph

The graph to test.

Raises

NetworkXPointlessConcept

If G is empty.

Returns

b : bool

A boolean that is True if G is a tree.

Returns True if G is a tree.

See Also

is_arborescence

Examples

>>> G = nx.Graph()
... G.add_edges_from([(1, 2), (1, 3), (2, 4), (2, 5)])
... nx.is_tree(G) # n-1 edges True
>>> G.add_edge(3, 4)
... nx.is_tree(G) # n edges False
See :

Back References

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

networkx.algorithms.tree.recognition.is_tree networkx.algorithms.tree.recognition.is_arborescence

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/tree/recognition.py#216
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