edge_types function

Querying edge types

These functions lets the user query whether the edges in a graph is of a specific type. All functions return a logical vector giving whether each edge in the graph corresponds to the specific type.

edge_is_multiple()

edge_is_loop()

edge_is_mutual()

edge_is_from(from)

edge_is_to(to)

edge_is_between(from, to, ignore_dir = !graph_is_directed())

edge_is_incident(nodes)

edge_is_bridge()

edge_is_feedback_arc(weights = NULL, approximate = TRUE)

Arguments

• from, to, nodes: A vector giving node indices
• ignore_dir: Is both directions of the edge allowed
• weights: The weight of the edges to use for the calculation. Will be evaluated in the context of the edge data.
• approximate: Should the minimal set be approximated or exact

Returns

A logical vector of the same length as the number of edges in the graph

Functions

• edge_is_multiple(): Query whether each edge has any parallel siblings
• edge_is_loop(): Query whether each edge is a loop
• edge_is_mutual(): Query whether each edge has a sibling going in the reverse direction
• edge_is_from(): Query whether an edge goes from a set of nodes
• edge_is_to(): Query whether an edge goes to a set of nodes
• edge_is_between(): Query whether an edge goes between two sets of nodes
• edge_is_incident(): Query whether an edge goes from or to a set of nodes
• edge_is_bridge(): Query whether an edge is a bridge (ie. it's removal will increase the number of components in a graph)
• edge_is_feedback_arc(): Query whether an edge is part of the minimal feedback arc set (its removal together with the rest will break all cycles in the graph)

Examples

create_star(10, directed = TRUE, mutual = TRUE) %>%
  activate(edges) %>%
  sample_frac(0.7) %>%
  mutate(single_edge = !edge_is_mutual())