tests/testthat/test-communities.R

test_that("community detection functions work", {
  withr::local_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_equal(
      modularity(comm),
      modularity(karate, membership(comm))
    )

    cc <- communities(comm)
    expect_true(all(!duplicated(unlist(cc))))
    expect_true(all(unlist(cc) <= vcount(karate) & unlist(cc) >= 1))
    expect_equal(length(comm), 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_equal(m1, 0)
  expect_equal(m2, 0.3717948718)
  expect_equal(m3, 0.3806706114)
  expect_equal(m4, 0.3759861933)

  cr <- crossing(fc, karate)
  expect_equal(cr, 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", {
  withr::local_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_equal(as.vector(membership(comm)), membership)
  expect_equal(modularity(comm), mod)
  expect_equal(algorithm(comm), "random")
})

test_that("communities function works", {
  skip_if_no_glpk()
  g <- make_graph("Zachary")
  oc <- cluster_optimal(g)
  gr <- communities(oc)
  expect_equal(
    gr,
    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_equal(gr, structure(list(`1` = letters[1:5], `2` = letters[6:10]), .Dim = 2L, .Dimnames = list(c("1", "2"))))
})
igraph/rigraph documentation built on Aug. 16, 2024, 1:38 p.m.