Description Usage Arguments Details Value Examples

Perform Spinglass algorythm and find networks communities

1 | ```
NetworkCommunity(networkeco, run = 100)
``` |

`networkeco` |
A network object (either qgraph or igraph) or a list created by the NetworkEco or NetworkEcoSeries functions. |

`run` |
Number of runs for the spinglass algorithm. Computation may be heavy for high numbers. |

The function perform spinglass algorithm on the provided network.
(see spinglass.community() function of the igraph package for more details)
The provided graph is internally transformed into a igraph object if
needed. The function returns a number of summary statistics from the n runs
of the spinglass algorithm. Each run of the spinglass algorithm is done
with a different seed, to ensure different outputs. The seeds are internally
recycled by the *with_seed* fuction of the *withr* package, so
that the global environment is not modified.
The frequencies at which a number of communities are recognised in the
network and the average assignements (rounded or not) of the nodes into
these communities are returned by the function. The latter can help
to statistically define groups for network graphical representations.

A list containing the number of runs, the number of possible communities defined by the spinglass algorithm (with frequencies) and the mean and rounded mean of the assignement of the nodes of the network to these communities.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 | ```
#### Artificial data:
SyntheticTrial <- SyntheticData(SpeciesNum = 21, CommunityNum = 3,
SpCo = NULL, Length = 500,
Parameters = list(a=rep(60, 3),
b=c(0,250,500),
c=rep(0.01,3)),
pal = c("#008585", "#FBF2C4", "#C7522B"))
# Building first network:
Network <- DistEco(SyntheticTrial[,2:ncol(SyntheticTrial)],
transpose = TRUE, plot = c("network"), spinglass = FALSE,
return.network = TRUE)
### Spinglass algorithm (increase number of run for better accuracy):
SpinglassTrial <- NetworkCommunity(Network, run = 5)
### Network with spinglass groups:
DistEco(SyntheticTrial[,2:ncol(SyntheticTrial)], transpose = TRUE,
plot = c("network"), spinglass = FALSE, return.network = FALSE,
manual.groups = as.factor(SpinglassTrial$Memberships$RoundedMean))
``` |

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