Error in `igraph::as.undirected(.data, edge.attr.comb = "first")`: unused argument (edge.attr.comb = "first")

test_that("is_ tests return correct values", {
#   dplyr::distinct(directed, weighted, twomode, multiplex, .keep_all = TRUE) |>
#   dplyr::select(dataset) |> unlist() |> unname()
#     testthat::test_that(paste(f, "works for", d), {
# dplyr::distinct(dplyr::across(dplyr::where(is.logical)), .keep_all = TRUE) |>
# benchmark <- function(functions, coercions, data){
#   if(missing(coercions)) coercions <- c("as_edgelist","as_igraph","as_matrix","as_network","as_tidygraph")
#   if(missing(data)) data <- "ison_adolescents"
#   isas <- expand.grid(functions, coercions, stringsAsFactors = FALSE)
#   isas <- paste0(isas$Var1, "(", isas$Var2, "(", data, "))")
#   out <- microbenchmark::microbenchmark(list = sapply(isas, function(x) x = eval(parse(text = x))), times = 1000)
# drill <- function(object, ..., which_summ = c("functions","coercions","data")){
#     tidyr::separate_wider_delim(expr, delim = "(", names = c("functions", "coercions", "data")) |>
#     dplyr::mutate(data = stringr::str_remove(data, "\\)\\)")) |>
#     dplyr::summarise(mean = mean(time), min = min(time), max = max(time)) |>

test_that("create filled graph works", {
#   expect_s3_class(create_nest(2,4, as = "igraph"), "igraph")
#   expect_s3_class(create_nest(2,4, as = "tidygraph"), "tbl_graph")
expect_true(is_directed(create_explicit(A -+ B, B -+ C, A +-+ C, D)))
expect_false(manynet::is_weighted(create_explicit(A -+ B, B -+ C, A +-+ C, D)))
expect_length(create_explicit(A -+ B, B -+ C, A +-+ C, D), 4)
expect_s3_class(create_explicit(A -+ B, B -+ C, A +-+ C, D, as = "igraph"),
expect_s3_class(create_explicit(A -+ B, B -+ C, A +-+ C, D, as = "tidygraph"),

dplyr::mutate(attribute = c("friend", "family", "friend", "friend", "family"))
c("friend", "family", "friend", "friend", "family"))),
south1 <- add_node_attribute(ison_southern_women, "Age", rep(25, 18))
south2 <- add_node_attribute(ison_southern_women, "Budget", rep(100, 14))
# Test error when wrong number of attributes
# Test error when different number of dimensions
test_that("mutate_ties and filter_ties works", {
orig <- ison_southern_women %>% mutate_ties(year = 1:89)
filt <- orig %>% activate(edges) %>% dplyr::filter(year > 5) %>% activate(nodes)
mutate_ties(year = sample(1:3, 178, replace = TRUE))
sum <- summarise_ties(orig, mean = mean(year))