CODEWITHSUNDEEP
rdata-visualizationigraph
stats_noob
stats_noob

Reputation: 5935

Connecting All Nodes Together on a Graph

I have the following network graph:

library(tidyverse)
library(igraph)


set.seed(123)
n=5
data = tibble(d = paste(1:n))

relations = data.frame(tibble(
  from = sample(data$d),
  to = lead(from, default=from[1]),
))

graph = graph_from_data_frame(relations, directed=T, vertices = data) 

V(graph)$color <- ifelse(data$d == relations$from[1], "red", "orange")

plot(graph, layout=layout.circle, edge.arrow.size = 0.2)

enter image description here

I want to connect each Node to every Node on this graph - I can do this manually by redefining the "relations" data frame:

relations_1 = data.frame("from" = c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,4,5,5,5,5), "to" = c(2,3,4,5,1,3,4,5,1,2,4,5,1,2,3,5,1,2,3,4))

Then, I can re-run the network graph:

graph = graph_from_data_frame(relations_1, directed=T, vertices = data) 

V(graph)$color <- ifelse(data$d == relations_1$from[1], "red", "orange")

plot(graph, layout=layout.circle, edge.arrow.size = 0.2)

enter image description here

Thank you!

Upvotes: 3

Views: 623

Answers (3)

ThomasIsCoding
ThomasIsCoding

Reputation: 102710

If you depart from graph, you can try the following code using add_edges + get.adjacency

graph %>%
    add_edges(c(t(which(`diag<-`(get.adjacency(., sparse = FALSE), 1) != 1, arr.ind = TRUE))))

which adds all missing edges while retaining the attributes from your original graph object, and you will see

enter image description here

Upvotes: 1

Stefano Barbi
Stefano Barbi

Reputation: 3194

An solution using igraph::make_full_graph:

relations %>%
  with(union(from,to)) %>%
  {
    G <- make_full_graph(length(.), directed = TRUE)
    V(G)$name <- .
    G
  }

enter image description here

Upvotes: 2

Lennyy
Lennyy

Reputation: 6132

You could just update relations using complete, and than filter out the rows where from is equal to to, which gives arrows from a node to itself.

relations <- relations %>% 
  complete(from, to) %>% 
  dplyr::filter(from != to)

Upvotes: 2

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