tests/testthat/test-communities.R

In igraph: Network Analysis and Visualization

test_that("community detection functions work", {
  set.seed(42)

  F <- list(
    "cluster_edge_betweenness", "cluster_fast_greedy",
    "cluster_label_prop", "cluster_leading_eigen",
    "cluster_louvain", "cluster_spinglass", "cluster_walktrap"
  )
  if (has_glpk()) F <- c(F, list("cluster_optimal"))

  karate <- make_graph("Zachary")

  for (f in F) {
    f <- get(f)
    comm <- f(karate)

    expect_that(
      modularity(comm),
      equals(modularity(karate, membership(comm)))
    )

    cc <- communities(comm)
    expect_true(all(!duplicated(unlist(cc))))
    expect_true(all(unlist(cc) <= vcount(karate) & unlist(cc) >= 1))
    expect_that(length(comm), equals(max(membership(comm))))
  }

  fc <- cluster_fast_greedy(karate)
  m1 <- modularity(karate, cut_at(fc, no = 1))
  m2 <- modularity(karate, cut_at(fc, no = 2))
  m3 <- modularity(karate, cut_at(fc, no = 3))
  m4 <- modularity(karate, cut_at(fc, no = 4))
  expect_that(m1, equals(0))
  expect_that(m2, equals(0.3717948718))
  expect_that(m3, equals(0.3806706114))
  expect_that(m4, equals(0.3759861933))

  cr <- crossing(fc, karate)
  expect_that(cr, equals(c(
    TRUE, TRUE, TRUE, FALSE, FALSE, FALSE, TRUE,
    TRUE, FALSE, FALSE, TRUE, TRUE, TRUE,
    FALSE, TRUE, TRUE, FALSE, FALSE, FALSE, FALSE,
    FALSE, TRUE, FALSE, TRUE, FALSE, FALSE,
    TRUE, TRUE, TRUE, FALSE, TRUE, FALSE,
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
    TRUE, TRUE, FALSE, FALSE, FALSE, FALSE,
    FALSE, FALSE, TRUE, FALSE, FALSE, FALSE,
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
    FALSE, FALSE, FALSE, FALSE, FALSE, FALSE,
    FALSE, FALSE, FALSE, FALSE
  )))
})

test_that("creating communities objects works", {
  set.seed(42)

  karate <- make_graph("Zachary")

  membership <- sample(1:2, vcount(karate), replace = TRUE)
  mod <- modularity(karate, membership)
  comm <- make_clusters(
    algorithm = "random", membership = membership,
    modularity = mod
  )

  expect_that(as.vector(membership(comm)), equals(membership))
  expect_that(modularity(comm), equals(mod))
  expect_that(algorithm(comm), equals("random"))
})

test_that("communities function works", {
  skip_if_no_glpk()
  g <- make_graph("Zachary")
  oc <- cluster_optimal(g)
  gr <- communities(oc)
  expect_that(
    gr,
    equals(structure(
      list(
        `1` = c(
          1L, 2L, 3L, 4L, 8L, 12L, 13L, 14L, 18L,
          20L, 22L
        ),
        `2` = c(5L, 6L, 7L, 11L, 17L),
        `3` = c(
          9L, 10L, 15L,
          16L, 19L, 21L, 23L, 27L, 30L, 31L, 33L, 34L
        ),
        `4` = c(
          24L, 25L,
          26L, 28L, 29L, 32L
        )
      ),
      .Dim = 4L,
      .Dimnames = list(c(
        "1", "2",
        "3", "4"
      ))
    ))
  )

  g <- make_ring(5) + make_ring(5)
  V(g)$name <- letters[1:10]
  oc <- cluster_optimal(g)
  gr <- communities(oc)
  expect_that(gr, equals(structure(
    list(
      `1` = letters[1:5],
      `2` = letters[6:10]
    ),
    .Dim = 2L,
    .Dimnames = list(c("1", "2"))
  )))
})