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"))))
})
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