docs_old/bipartite.md

In Ecological-Complexity-Lab/infomap_ecology_package: Community Detection using Infomap, Inspired by Ecological Networks

Bipartite monolayer network example

Data set

A weighted bipartite network describing a plant-flower visitor interaction web (25 plant species and 79 flower visitor species) in the vicinity of Bristol, U.K. To distinguish between the two node sets we number the pollinator species from 1-79 and the plants from 80-104. Data can be obtained using data(memmott1999) using package bipartite in R.

Input

A link list with columns from, to and weight. Because this is a bipartite network the from column can only contain nodes 1-79 and the to column nodes 84-104.

R Code

# Import data
library(bipartite)
data(memmott1999)

network_object <- create_monolayer_network(memmott1999, bipartite = T, directed = F, group_names = c('A','P'))
infomap_object <- run_infomap_monolayer(network_object, infomap_executable='Infomap',
flow_model = 'undirected',
silent=T, trials=20, two_level=T, seed=123)

# Plot the matrix (plotting function in beta)
plot_modular_matrix(infomap_object)

Infomap

Under the hood, the function run_infomap_monolayer runs:

./Infomap infomap.txt . --tree -i link-list --seed 123 -N 20 -f undirected -2

With this command, Infomap detects modules that contain both plants and pollinators. -f undirected indicates flow on an undirected network. -2 indicates a two-level solution, with no hierarchical modules.

Output

A tree file is produced by Infomap, but is parsed by run_infomap_monolayer from infomapecology (in R: ?run_infomap_monolayer).

Ecological-Complexity-Lab/infomap_ecology_package documentation built on June 6, 2024, 5:28 a.m.