randomized_partitioning(G, seed=None, p=0.5, weight=None)
A partitioning is calculated by observing each node and deciding to add it to the partition with probability p, returning a random cut and its corresponding value (the sum of weights of edges connecting different partitions).
Indicator of random number generation state. See Randomness<randomness>
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Probability for each node to be part of the first partition. Should be in [0,1]
Edge attribute key to use as weight. If not specified, edges have weight one.
Value of the minimum cut.
A partitioning of the nodes that defines a minimum cut.
Compute a random partitioning of the graph nodes and its cut value.
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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