_directed_neighbor_switch_rev(G, w, unsat, h_node_residual_in, chords, h_partition_out, partition)

Notes

Same operation as directed_neighbor_switch except it handles this operation for incoming edges instead of outgoing.

Parameters

G : networkx directed graph

graph within which the edge swap will take place.

w : integer

node id for which we need to perform a neighbor switch.

unsat: set of integers :

set of node ids that have the same degree as w and are unsaturated.

h_node_residual_in: dict of integers :

for a given node, keeps track of the remaining stubs to be added.

chords: set of tuples :

keeps track of available positions to add edges.

h_partition_out: dict of integers :

for a given node, keeps track of its partition id (out degree).

partition: integer :

partition id to check if chords have to be updated.

The reverse of directed_neighbor_switch.

Examples

See :

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/generators/joint_degree_seq.py#426
type: <class 'function'>
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