add_cycle(G_to_add_to, nodes_for_cycle, **attr)

Parameters

G_to_add_to : graph

A NetworkX graph

nodes_for_cycle: iterable container :

A container of nodes. A cycle will be constructed from the nodes (in order) and added to the graph.

attr : keyword arguments, optional (default= no attributes)

Attributes to add to every edge in cycle.

Add a cycle to the Graph G_to_add_to.

See Also

add_path

add_star

Examples

>>> G = nx.Graph()  # or DiGraph, MultiGraph, MultiDiGraph, etc
... nx.add_cycle(G, [0, 1, 2, 3])
... nx.add_cycle(G, [10, 11, 12], weight=7)

See :

Back References

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

networkx.algorithms.cycles.minimum_cycle_basis networkx.classes.function.add_path networkx.classes.function.add_star networkx.algorithms.components.strongly_connected.strongly_connected_components networkx.algorithms.components.strongly_connected.strongly_connected_components_recursive networkx.algorithms.cycles.cycle_basis networkx.classes.function.add_cycle networkx.algorithms.components.strongly_connected.kosaraju_strongly_connected_components

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/classes/function.py#295
type: <class 'function'>
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