# Tests for the as_ conversion methods mat1 <- matrix(c(0,1,0,0,1,0,1,0,0,1,0,1,0,0,0,0),4,4, byrow = TRUE) rownames(mat1) <- LETTERS[1:4] colnames(mat1) <- LETTERS[1:4] mat2 <- matrix(c(0,1,0,0,2,0,3,0,0,4,0,5,0,0,0,0),4,4, byrow = TRUE) rownames(mat2) <- LETTERS[1:4] colnames(mat2) <- LETTERS[1:4] # Unweighted test data1 <- dplyr::arrange(data.frame(from = c("A","B","B","C","C"), to = c("B","C","A","D","B")), from, to) # Weighted test data2 <- data1 data2$weight <- 1:5 # Data 3: misnamed weight col data3 <- data1 data3$hello <- 1:5 test_that("as_edgelist converts correctly", { expect_s3_class(as_edgelist(as_igraph(data2)), "tbl_df") expect_equal(as_edgelist(as_igraph(data2)), dplyr::as_tibble(data2)) expect_equal(as_edgelist(as_igraph(data1)), dplyr::as_tibble(data1)) expect_equal(as_edgelist(as_tidygraph(data2)), dplyr::as_tibble(data2)) expect_equal(as_edgelist(as_tidygraph(data1)), dplyr::as_tibble(data1)) expect_equal(as_edgelist(as_network(data1)), dplyr::as_tibble(data1)) expect_equal(as_edgelist(as_network(data2)), dplyr::as_tibble(data2)) }) test_that("data frame converted to matrix correctly",{ expect_equal(as_matrix(data1), mat1) expect_equal(as_matrix(data2), mat2) }) test_that("as_matrix converts correctly",{ expect_vector(as_matrix(mat1)) expect_vector(as_matrix(ison_southern_women)) expect_vector(ison_southern_women %>% as_matrix()) expect_vector(ison_southern_women %>% as_matrix()) expect_equal(as_matrix(as_network(ison_southern_women)), as_matrix(ison_southern_women)) }) test_that("as_igraph converts correctly",{ expect_s3_class(as_igraph(mat1), "igraph") expect_s3_class(as_igraph(ison_southern_women), "igraph") expect_s3_class(as_igraph(as_network(ison_southern_women)), "igraph") expect_error(as_igraph(data3, weight = T)) expect_equal(igraph::vcount(as_igraph(as_network(data2))), igraph::vcount(as_igraph(data2))) # NB: ordering of edges is a little different when converting from network # to igraph. Should not matter though. }) test_that("as_tidygraph converts correctly",{ expect_s3_class(as_tidygraph(mat1), "tbl_graph") expect_s3_class(as_tidygraph(ison_southern_women), "tbl_graph") expect_s3_class(as_tidygraph(as_network(mat1)), "tbl_graph") expect_s3_class(as_tidygraph(as_network(ison_southern_women)), "tbl_graph") }) test_that("as_network converts correctly",{ expect_s3_class(as_network(mat1), "network") expect_s3_class(as_network(ison_southern_women), "network") expect_equal(as_network(as_network(data2)), as_network(data2)) expect_equal(as_network(as_igraph(ison_southern_women)), as_network(ison_southern_women)) expect_equal(igraph::vcount(as_igraph(as_network(dplyr::as_tibble(data2)))), igraph::vcount(as_igraph(as_network(data2)))) expect_equal(is_directed(ison_southern_women), is_directed(as_network(ison_southern_women))) expect_equal(is_directed(ison_southern_women), is_directed(as_network(ison_southern_women))) # NB: ordering of edges is a little different when converting from network # to igraph. Should not matter though. }) # test conversion of siena objects # test_that("as_tidygraph.siena converts correctly", { # expect_equal(net_nodes(as_igraph(sienadata)), net_nodes(as_matrix(sienadata))) # expect_equal(net_nodes(as_igraph(sienadata)), length(sienadata[["nodeSets"]][["Actors"]])) # }) test_that("conversion of diff_model object works correctly", { skip_on_cran() skip_on_ci() diff <- play_diffusion(ison_brandes) tidy_diff <- as_tidygraph(diff) expect_values(net_nodes(tidy_diff), net_nodes(ison_brandes)) expect_values(net_ties(tidy_diff), net_ties(ison_brandes)) expect_values(net_nodes(tidy_diff), max(diff$I)) })