context("Simulations")
n <- 300
d <- 10
test_that("Fat Tails", {
result <- lol.sims.fat_tails(n, d)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
pr <- c(0.8, 0.2)
result <- lol.sims.fat_tails(n, d, priors=pr)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_error(lol.sims.fat_tails(n, d, priors=c(0.9, 0.2)))
})
test_that("Mean Diff", {
result <- lol.sims.mean_diff(n, d)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
pr <- c(0.8, 0.2)
result <- lol.sims.mean_diff(n, d, priors=pr)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_error(lol.sims.mean_diff(n, d, priors=c(0.9, 0.2)))
})
test_that("Toeplitz", {
result <- lol.sims.toep(n, d)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
pr <- c(0.8, 0.2)
result <- lol.sims.toep(n, d, priors=pr)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_error(lol.sims.toep(n, d, priors=c(0.9, 0.2)))
})
test_that("Quadratic Discriminant Toeplitz", {
result <- lol.sims.qdtoep(n, d)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
pr <- c(0.8, 0.2)
result <- lol.sims.qdtoep(n, d, priors=pr)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_error(lol.sims.qdtoep(n, d, priors=c(0.9, 0.2)))
})
test_that("Random Trunk", {
result <- lol.sims.rtrunk(n, d)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
pr <- c(0.8, 0.2)
result <- lol.sims.rtrunk(n, d, priors=pr)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_error(lol.sims.rtrunk(n, d, priors=c(0.9, 0.2)))
result <- lol.sims.rtrunk(n, d, K=3)
expect_equal(length(unique(result$Y)), 3)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
})
test_that("Cigar", {
result <- lol.sims.cigar(n, d)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
pr <- c(0.8, 0.2)
result <- lol.sims.cigar(n, d, priors=pr)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_error(lol.sims.cigar(n, d, priors=c(0.9, 0.2)))
})
test_that("XOR", {
result <- lol.sims.xor2(n, d)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
pr <- c(0.8, 0.2)
result <- lol.sims.xor2(n, d, priors=pr)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_error(lol.sims.xor2(n, d, priors=c(0.9, 0.2)))
})
test_that("Rotation", {
pr <- c(0.8, 0.2)
result <- lol.sims.mean_diff(n, d, md=3, priors=pr, rotate=TRUE)
expect_equal(mean(result$Y == 1), pr[1], tolerance=0.05)
expect_equal(mean(result$Y == 2), pr[2], tolerance=0.05)
expect_equal(length(result$Y), n)
expect_equal(dim(result$X), c(n, d))
result <- lol.sims.cigar(n, d, rotate=TRUE)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
result <- lol.sims.fat_tails(n, d, rotate=TRUE)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
result <- lol.sims.toep(n, d, rotate=TRUE)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
result <- lol.sims.qdtoep(n, d, rotate=TRUE)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
result <- lol.sims.rtrunk(n, d, rotate=TRUE)
expect_equal(dim(result$X)[1], n)
expect_equal(dim(result$X)[2], d)
expect_equal(length(result$Y), n)
})
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