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Spinglass Community Detection

Source: R/communities.R
community_spinglass.Rd

Community detection based on the spinglass model of statistical mechanics, optimized by simulated annealing. Negative edge weights are supported with implementation = "neg". A disconnected graph raises a warning and only its largest component is partitioned, so the result has one row per node of that component.

Usage

community_spinglass(
  x,
  weights = NULL,
  vertex = NULL,
  spins = 25,
  parupdate = FALSE,
  start.temp = 1,
  stop.temp = 0.01,
  cool.fact = 0.99,
  update.rule = c("config", "random", "simple"),
  gamma = 1,
  implementation = c("orig", "neg"),
  gamma.minus = 1,
  seed = NULL,
  ...
)

com_sg(
  x,
  weights = NULL,
  vertex = NULL,
  spins = 25,
  parupdate = FALSE,
  start.temp = 1,
  stop.temp = 0.01,
  cool.fact = 0.99,
  update.rule = c("config", "random", "simple"),
  gamma = 1,
  implementation = c("orig", "neg"),
  gamma.minus = 1,
  seed = NULL,
  ...
)

Arguments

x

Network input.

weights

Edge weights. NULL uses the network weights and NA runs unweighted. Weights are passed unchanged.

vertex

Vertex whose community is searched (single community mode). NULL (default) partitions the whole network.

spins

Number of spins, the upper limit on the number of communities. Default 25.

parupdate

Logical. Whether spins are updated in parallel. Default FALSE.

start.temp

Starting temperature. Default 1.

stop.temp

Stopping temperature. Default 0.01.

cool.fact

Cooling factor. Default 0.99.

update.rule

Null model of the update rule, one of "config" (default), "random" or "simple".

gamma

Weight of the null model term. Default 1.

implementation

"orig" (default) or "neg", the implementation that supports negative weights.

gamma.minus

Weight of the null model term for negative edges in the "neg" implementation. Default 1.

seed

Random seed for reproducibility. Default NULL.

...

Passed to to_igraph, whose only other argument is directed; anything else raises an "unused argument" error.

Value

A cograph_communities data frame with columns node and community. See communities for its attributes.

References

Reichardt, J., & Bornholdt, S. (2006). Statistical mechanics of community detection. Physical Review E, 74, 016110.

Examples

community_spinglass(regulation_net, seed = 1)
#> Community structure (spinglass)
#>   Nodes: 10  | Communities: 2  | Modularity: -3.7742 
#>   Sizes: 5, 5 
#> 
#>        node community
#>     Explore         2
#>        Plan         1
#>     Monitor         1
#>       Adapt         2
#>     Reflect         2
#>     Discuss         2
#>  Synthesize         2
#>    Evaluate         1
#>      Create         1
#>       Share         1