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A fct that plot a visNetwork plot of a adjacency matrix or an Sbm fit from the sbm package.

Usage

# S3 method for SimpleSBM_fit
visSbm(
  x,
  labels = "default",
  node_names = NULL,
  directed = "default",
  settings = list()
)

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

Value

a visNetwork visual of the x object

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")
  )
)