test_that("check_top_N returns expected result ",{
data(sim_FS)
data(sim_Scores)
set.seed(21)
rowscore <- calc_rowscore(
FS = sim_FS,
input_score = sim_Scores,
meta_feature = NULL,
method = "ks_pval",
alternative = "less",
weights = NULL
)
# Re-order rowscore in a decreasing order (from highest to lowest values)
# This comes in handy when doing the top-N evaluation of
# top N 'best' features
rowscore <- rowscore[order(rowscore, decreasing=TRUE)]
top_N_index <- check_top_N(
rowscore = rowscore,
top_N = 7,
search_start = NULL,
feature_names = rownames(sim_FS)
)
expect_type(top_N_index, "integer")
expect_length(top_N_index, 7L)
expect_identical(top_N_index, c(8L, 9L, 10L, 6L, 948L, 706L, 995L))
})
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