The aim of this function is to provide users with a quick and easy graphing function that makes best use of the data, whatever its composition. Users can also tailor the plot according to their preferences regarding node size, colour, and shape. The function also supports visualisation of network measures such as centrality.

autographr(
  object,
  layout = "stress",
  labels = TRUE,
  node_color = NULL,
  node_group = NULL,
  node_shape = NULL,
  node_size = NULL,
  edge_color = NULL,
  ...
)

Arguments

object

A migraph-consistent object.

layout

An igraph layout algorithm, currently defaults to 'stress'.

labels

Logical, whether to print node names as labels if present.

node_color

Node variable in quotation marks to be used for coloring the nodes. It is easiest if this is added as a node attribute to the graph before plotting.

node_group

Node variable in quotation marks to be used for drawing convex but also concave hulls around clusters of nodes. These groupings will be labelled with the categories of the variable passed.

node_shape

Character string in quotation marks referring to the name of a node attribute already present in the graph to be used for the shapes of the nodes. Shapes follow the ordering "circle", "square", "triangle", so this aesthetic should be used for a variable with only a few categories.

node_size

Node variable in quotation marks to be used for the size of the nodes. This can be any continuous variable on the nodes of the network. Since this function expects this to be an existing variable, it is recommended to calculate all node-related statistics prior to using this function.

edge_color

Tie variable in quotation marks to be used for coloring the nodes. It is easiest if this is added as an edge or tie attribute to the graph before plotting.

...

Extra arguments.

See also

Other mapping: layouts

Examples

ison_adolescents %>% 
  mutate(shape = rep(c("circle", "square"), times = 4)) %>%
  mutate(color = rep(c("blue", "red"), times = 4)) %>% 
  autographr(node_shape = "shape", node_color = "color")

autographr(ison_karateka, node_size = 8)

ison_adolescents %>% 
  mutate(high_degree = node_is_max(node_degree())) %>% 
  activate(edges) %>% 
  mutate(high_betweenness = tie_is_max(tie_betweenness(ison_adolescents))) %>% 
  autographr(node_color = "high_degree", edge_color = "high_betweenness")