Nothing
# generate toy dataset
seed <- as.numeric(format(Sys.time(), "%s"))
set.seed(seed); x <- .toySCE()
nk <- length(kids <- levels(x$cluster_id))
ns <- length(sids <- levels(x$sample_id))
ng <- length(gids <- levels(x$group_id))
test_that("pbMDS()", {
y <- x; class(y) <- "x"
expect_error(pbMDS(y))
y <- aggregateData(x)
expect_is(p <- pbMDS(y), "ggplot")
expect_true(nrow(p$data) == nk*ns)
expect_true(all(table(p$data$cluster_id) == ns))
expect_true(all(table(p$data$group_id) == ns*nk/ng))
cs1 <- x$group_id != gids[1] # remove group
cs2 <- x$sample_id != sids[1] # remove sample
cs3 <- x$cluster_id != kids[1] # remove cluster
cs4 <- cs1 & cs2 # remove sample in single group
cs5 <- cs1 & cs3 # remove cluster in single group
cs6 <- cs2 & cs3 # remove cluster-sample instance
for (cs in paste0("cs", seq_len(6)))
expect_silent(pbMDS(aggregateData(x[, get(cs)])))
})
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