tests/testthat/test-mark_ties.R

In netrics: Many Ways to Measure and Classify Membership for Networks, Nodes, and Ties

tie_marks <- funs_objs[grepl("tie_is_", names(funs_objs))]
for(fn in names(tie_marks)) {
  for (ob in names(data_objs)) { 
    test_that(paste(fn, "works on", ob), {
      skip_if(grepl("tie_is_imbalanced", fn) && ob == "twomode")
      if(fn == "tie_is_path"){
        expect_s3_class(tie_marks[[fn]](data_objs[[ob]], 1, 2), "tie_mark")
      } else if(grepl("infected|recovered", fn)){
        if(ob == "diffusion")
        expect_s3_class(tie_marks[[fn]](data_objs[[ob]]), "tie_mark") else
          success("Only used for diffusion objects")
      } else if(grepl("max|min", fn)){
        skip_if_not(packageVersion("manynet") >= "1.7.3")
        expect_s3_class(tie_marks[[fn]](tie_by_degree(data_objs[[ob]])), "tie_mark")
      } else {
        expect_s3_class(tie_marks[[fn]](data_objs[[ob]]), "tie_mark")
      }
    })
  }
}

graph1 <- igraph::make_directed_graph(c(1,2,1,5,2,3,2,4,3,5,4,5,5,1))
graph2 <- igraph::make_undirected_graph(c(1,1,1,2,2,4,3,4,3,4))

test_that("tie_is_reciprocated works", {
  expect_length(tie_is_reciprocated(graph1), 7)
  expect_true(tie_is_reciprocated(graph1)[2], tie_is_reciprocated(graph1)[7])
})

test_that("tie_is_multiple works", {
  expect_true(tie_is_multiple(graph2)[5])
})

test_that("tie_is_loop works", {
  expect_true(tie_is_loop(graph2)[1])
  expect_false(tie_is_loop(graph2)[2], tie_is_loop(graph2)[3], tie_is_loop(graph2)[4])
})

test_that("tie_is_bridge works", {
  expect_equal(length(tie_is_bridge(graph1)), c(net_ties(graph1)))
})

test_that("tie_is_path works", {
  expect_equal(sum(tie_is_path(ison_adolescents, "Betty", "Alice")), 2)
})

test_that("tie_is_triangular works", {
  expect_equal(sum(tie_is_triangular(ison_adolescents)), 7)
  expect_output(print(tie_is_triangular(ison_adolescents)), "Betty-Sue")
})

test_that("directed triangle tie marks work", {
  acy_adol <- to_acyclic(ison_adolescents)
  expect_true(sum(tie_is_transitive(acy_adol)) >= 3)
  expect_true(sum(tie_is_triplet(acy_adol)) >= 3)
  expect_false(any(tie_is_cyclical(acy_adol)))
  expect_false(any(tie_is_simmelian(acy_adol)))
})

test_that("tie_is_max works", {
  skip_on_ci()
  skip_on_cran()
  expect_equal(length(tie_is_max(tie_by_betweenness(graph1))),
               c(net_ties(graph1)))
  expect_equal(sum(tie_is_max(tie_by_betweenness(graph1)) == TRUE), 1)
  expect_s3_class(tie_is_max(tie_by_betweenness(graph1)), "logical")
})

test_that("tie_is_min works", {
  skip_on_ci()
  skip_on_cran()
  expect_equal(length(tie_is_min(tie_by_betweenness(ison_brandes))),
               c(net_ties(ison_brandes)))
  expect_equal(sum(tie_is_min(tie_by_betweenness(ison_brandes)) == TRUE), 1)
  expect_s3_class(tie_is_min(tie_by_betweenness(ison_brandes)), "logical")
})

test_that("tie_is_feedback() mark functions work", {
  expect_equal(as.character(tie_is_feedback(ison_adolescents)),
               c("FALSE", "FALSE", "FALSE", "FALSE", "TRUE", "TRUE", "FALSE",
                 "TRUE", "FALSE", "FALSE"))
})