spinglass.community: Finding communities in graphs based on statistical meachanics
In igraph: Network Analysis and Visualization

spinglass.community

R Documentation

Finding communities in graphs based on statistical meachanics

Description

spinglass.community() was renamed to cluster_spinglass() to create a more consistent API.

Usage

spinglass.community(
  graph,
  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
)

Arguments

`graph`	The input graph, can be directed but the direction of the edges is neglected.
`weights`	The weights of the edges. It must be a positive numeric vector, `NULL` or `NA`. If it is `NULL` and the input graph has a ‘weight’ edge attribute, then that attribute will be used. If `NULL` and no such attribute is present, then the edges will have equal weights. Set this to `NA` if the graph was a ‘weight’ edge attribute, but you don't want to use it for community detection. A larger edge weight means a stronger connection for this function.
`vertex`	This parameter can be used to calculate the community of a given vertex without calculating all communities. Note that if this argument is present then some other arguments are ignored.
`spins`	Integer constant, the number of spins to use. This is the upper limit for the number of communities. It is not a problem to supply a (reasonably) big number here, in which case some spin states will be unpopulated.
`parupdate`	Logical constant, whether to update the spins of the vertices in parallel (synchronously) or not. This argument is ignored if the second form of the function is used (i.e. the ‘`vertex`’ argument is present). It is also not implemented in the “neg” implementation.
`start.temp`	Real constant, the start temperature. This argument is ignored if the second form of the function is used (i.e. the ‘`vertex`’ argument is present).
`stop.temp`	Real constant, the stop temperature. The simulation terminates if the temperature lowers below this level. This argument is ignored if the second form of the function is used (i.e. the ‘`vertex`’ argument is present).
`cool.fact`	Cooling factor for the simulated annealing. This argument is ignored if the second form of the function is used (i.e. the ‘`vertex`’ argument is present).
`update.rule`	Character constant giving the ‘null-model’ of the simulation. Possible values: “simple” and “config”. “simple” uses a random graph with the same number of edges as the baseline probability and “config” uses a random graph with the same vertex degrees as the input graph.
`gamma`	Real constant, the gamma argument of the algorithm. This specifies the balance between the importance of present and non-present edges in a community. Roughly, a comunity is a set of vertices having many edges inside the community and few edges outside the community. The default 1.0 value makes existing and non-existing links equally important. Smaller values make the existing links, greater values the missing links more important.
`implementation`	Character scalar. Currently igraph contains two implementations for the Spin-glass community finding algorithm. The faster original implementation is the default. The other implementation, that takes into account negative weights, can be chosen by supplying ‘neg’ here.
`gamma.minus`	Real constant, the gamma.minus parameter of the algorithm. This specifies the balance between the importance of present and non-present negative weighted edges in a community. Smaller values of gamma.minus, leads to communities with lesser negative intra-connectivity. If this argument is set to zero, the algorithm reduces to a graph coloring algorithm, using the number of spins as the number of colors. This argument is ignored if the ‘orig’ implementation is chosen.