tests/testthat/test_motif_census.R

In KevCaz/motifcensus: Count 3-nodes motifs for unipartite networks

# linear chain
mat_lc <- rbind(c(0, 1, 0), c(0, 0, 1), c(0, 0, 0))
mat_lc2 <- rbind(c(0, 1, 0), c(0, 0, 0), c(1, 0, 0))
# apparent competition
mat_ac <- rbind(c(0, 0, 0), c(1, 0, 0), c(1, 0, 0))
# exploitative competition
mat_ec <- rbind(c(0, 0, 0), c(0, 0, 0), c(1, 1, 0))
# omnivory
mat_om <- rbind(c(0, 0, 0), c(1, 0, 0), c(1, 1, 0))
mat_om2 <- rbind(c(0, 1, 1), c(0, 0, 1), c(0, 0, 0))
# circular
mat_ci <- rbind(c(0, 0, 1), c(1, 0, 0), c(0, 1, 0))
# 2 linear chain and one exploitative competition
mat_cb <- rbind(c(0, 0, 0, 0), c(0, 0, 0, 0), c(1, 1, 0, 0), c(0, 0, 1, 0))

test_that("expected error", {
  expect_error(motif_census(mat_lc[, -1], unidirectional = TRUE),
    "`mat` is not square",
    fixed = TRUE
  )
})


res_lc <- motif_census(t(mat_lc), unidirectional = TRUE)$positions_node
res_lc2 <- motif_census(mat_lc2, unidirectional = TRUE)$positions_node
res_ac <- motif_census(mat_ac, unidirectional = TRUE)$positions_node
res_ec <- motif_census(mat_ec, unidirectional = TRUE)$positions_node
res_om <- motif_census(mat_om, unidirectional = TRUE)$positions_node
res_om2 <- motif_census(mat_om2, unidirectional = TRUE)$positions_node
res_ci <- motif_census(mat_ci, unidirectional = TRUE)$positions_node
res_cb <- motif_census(mat_cb, unidirectional = TRUE)

test_that("position for unidirectional networks", {
  expect_equal(sum(res_lc), 3)
  expect_true(res_lc[1, 3] & res_lc[2, 2] & res_lc[3, 1])
  expect_equal(sum(res_lc2), 3)
  expect_true(res_lc2[3, 1] & res_lc2[1, 2] & res_lc2[2, 3])
  expect_equal(sum(res_ac), 3)
  expect_true(res_ac[1, 5] & res_ac[2, 4] & res_ac[3, 4])
  expect_equal(sum(res_ec), 3)
  expect_true(res_ec[1, 7] & res_ec[2, 7] & res_ec[3, 6])
  expect_equal(sum(res_om), 3)
  expect_true(res_om[1, 10] & res_om[2, 9] & res_om[3, 8])
  expect_equal(sum(res_om2), 3)
  expect_true(res_om2[1, 8] & res_om2[2, 9] & res_om2[3, 10])
  expect_equal(sum(res_ci), 3)
  expect_true(all(res_ci[, 11] == 1))

  cb_pos <- res_cb$positions_node
  expect_equal(sum(cb_pos), 9)
  expect_equal(sum(cb_pos[4, 1]), 2)
  expect_equal(sum(cb_pos[3, 2]), 2)
  expect_true(cb_pos[1, 3] & cb_pos[2, 3])
  expect_true(cb_pos[1, 7] & cb_pos[2, 7] & cb_pos[3, 6])

  expect_true(all(res_cb$positions == c(2, 2, 2, 0, 0, 1, 2, 0, 0, 0, 0)))
})

test_that("motifs for unidirectional networks", {
  expect_true(all(res_cb$species_motifs[, 1L] == c(1, 1, 2, 2)))
  expect_true(all(res_cb$motifs == c(2, 0, 1, 0, 0)))
})


test_that("positions for bidirectional networks", {
  expect_identical(motif_census(mat_ci), motif_census(t(mat_ci)))
})



test_that("triplet for 3 species networks", {
  expect_equal(motif_census_triplet(mat_lc)$mid, 17)
  expect_equal(motif_census_triplet(mat_lc2)$mid, 9)
  expect_equal(motif_census_triplet(mat_ac)$mid, 10)
  expect_equal(motif_census_triplet(mat_ec)$mid, 40)
  expect_equal(motif_census_triplet(mat_om)$mid, 42)
  expect_equal(motif_census_triplet(mat_om2)$mid, 21)
  expect_equal(motif_census_triplet(mat_ci)$mid, 38)
})

test_that("triplet for 4 species network", {
  expect_equal(motif_census_triplet(mat_cb)$mid, c(0, 34, 34, 40))
})