I have a graph that contains 4 components of different cluster sizes.

I can see the details using the below code

cl <- components(graph1)

The details are looks like

$membership
ID_00104 ID_00136 ID_00169 ID_00178 ID_00180 ID_06663 ID_06791 ID_09099 ID_00910 ID_00790 ID_01013 ID_01130 ID_01260 ID_00394 ID_00860 ID_00959 ID_01222 ID_00288 ID_00324 ID_00663 ID_00846 ID_01047 ID_06781 ID_06786 
       1        2        2        3        4        1        1        1        2        3        4        4        4        4        4        4        4        4        4        4        4        4        4        4 

$csize
[1]  4  3  2 15

$no
[1] 4

I can also get the number of degree of a node using the below code

degree(graph1)

and the output is

ID_00104 ID_00136 ID_00169 ID_00178 ID_00180 ID_06663 ID_06791 ID_09099 ID_00910 ID_00790 ID_01013 ID_01130 ID_01260 ID_00394 ID_00860 ID_00959 ID_01222 ID_00288 ID_00324 ID_00663 ID_00846 ID_01047 ID_06781 ID_06786 
       3        2        2        1       14        1        1        1        2        1        1        1        1        1        1        1        1        1        1        1        1        1        1        1 

I can add all components (randomly choosing 2 nodes from 2 components) using the below code (solution from one of my previous

CodePudding user response：

Update

graph2 <- add.edges(
  graph1,
  combn(
    sapply(
      decompose(graph1),
      function(p) sample(names(V(p))[degree(p) == max(degree(p))], 1)
    ), 2
  ),
  weight = 0.01
)

plot(graph2, layout = layout_nicely(graph1))

gives

You can try

out <- combn(
  decompose(graph1),
  2,
  FUN = function(x) {
    add.edges(
      graph1,
      sapply(x, function(p) sample(names(V(p))[degree(p) == max(degree(p))], 1)),
      weight = 0.01
    )
  },
  simplify = FALSE
)

sapply(out,plot)