random_labeled_tree#

random_labeled_tree(n, *, seed=None)[source]#

Returns a labeled tree on n nodes chosen uniformly at random.

Generating uniformly distributed random Prüfer sequences and converting them into the corresponding trees is a straightforward method of generating uniformly distributed random labeled trees. This function implements this method.

Parameters:

nint: The number of nodes, greater than zero.
seedrandom_state: Indicator of random number generation state. See Randomness

Returns:

networkx.Graph: A networkx.Graph with nodes in the set {0, …, n - 1}.

Raises:

NetworkXPointlessConcept: If n is zero (because the null graph is not a tree).

Examples

>>> G = nx.random_labeled_tree(5, seed=42)
>>> nx.is_tree(G)
True
>>> G.edges
EdgeView([(0, 1), (0, 3), (0, 2), (2, 4)])

A tree with arbitrarily directed edges can be created by assigning generated edges to a DiGraph:

>>> DG = nx.DiGraph()
>>> DG.add_edges_from(G.edges)
>>> nx.is_tree(DG)
True
>>> DG.edges
OutEdgeView([(0, 1), (0, 3), (0, 2), (2, 4)])