Nothing
test_that("create_data_nuggets compresses and preserves total weight", {
set.seed(1)
x <- rbind(matrix(rnorm(100 * 4, 0), ncol = 4),
matrix(rnorm(100 * 4, 5), ncol = 4))
dn <- create_data_nuggets(x, max_nuggets = 30, seed = 1)
expect_s3_class(dn, "data_nugget")
expect_lte(length(dn$weights), 30)
expect_equal(sum(dn$weights), nrow(x)) # weights partition the data
expect_equal(ncol(dn$centers), ncol(x))
expect_true(all(dn$weights >= 1))
})
test_that("small samples fall back to one-nugget-per-observation", {
x <- matrix(rnorm(20 * 3), ncol = 3)
dn <- create_data_nuggets(x, seed = 1) # n = 20 <= 50
expect_equal(length(dn$weights), 20)
})
test_that("nugget feature weights rank signal above noise", {
set.seed(2)
signal <- c(rnorm(60, 0), rnorm(60, 6)) # separates two groups
noise <- rnorm(120)
x <- cbind(signal = signal, noise = noise)
dn <- create_data_nuggets(x, max_nuggets = 20, seed = 2)
fw <- nugget_feature_weights(dn, "between")
expect_gt(fw["signal"], fw["noise"])
expect_true(all(fw >= 0))
})
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