A fct that plot a visNetwork plot of a adjacency matrix or an Sbm fit from the sbm package.
Arguments
- x
Sbm model of class `BipartiteSBM_fit`, `SimpleSBM_fit` or simple numeric `matrix`.
- labels
labels for nodes. If it's simple sbm it should be a single character ("default" -> c("nodes")). If sbm is bipartite a named character (names are row and col) ("default" -> c(row = 'row', col = 'col')).
- node_names
if NULL do nothing specific, but list of nodes are given the graph get interactive and nodes names are showed by clicking on a block. In bipartite case a named list:
"row": character: node names in rows
"col": character: node names in columns
In unipartite case a single character vector containing the nodes names (Default = NULL).
- directed
Boolean indicating whether or not the network is directed by default, a asymmetrical matrix will be seen as directed.
- settings
list of settings
Details
List of parameters
"edge_threshold": "default" erases as many small edges as it can without isolating any nodes (no connection). It can also be a numeric value between 0 and 1, relative (between min and max) filter for small edges value
"edge_color": character: color of edges (default: "lightblue")
"arrows": boolean: should edges be arrows
"arrow_thickness": numeric: arrows size
"arrow_start": character: "row" or "col" or labels value according to row or columns. The arrow will start from selected to the the other value
"node_color": named character: Bipartite case c(row = "row_color", col = "col_color"). Unipartite case c("node_color")
"node_shape": named character: Bipartite case c(row = "row_shape", col = "col_shape"). Unipartite case c("node_shape"). Value from visNetwork shape argument of visEdges function ("triangle","dot","square",etc...)
"digits": integer: number of digits to show when numbers are shown (default: 2)
Examples
# my_sbm_uni <- sbm::estimateSimpleSBM(sbm::fungusTreeNetwork$tree_tree,
# model = "poisson")
my_sbm_uni <- FungusTreeNetwork$sbmResults$tree_tree
node_names_uni <- list(FungusTreeNetwork$networks$tree_names)
visSbm(my_sbm_uni,
labels = c("Tree"),
node_names = node_names_uni,
settings = list(
edge_threshold = 0.01,
edge_color = "grey",
node_color = c("violet")
)
)