Nothing
test_that("Can generate categorical variables with multiple levels.", {
SIM <- datasim_make(x ~ categorical(n, c("one", "two", "three")))
DF <- take_sample(SIM, n=99)
expect_true(all(DF$x %in% c("one", "two", "three")))
})
test_that("Relative probabilities work with categorical generation.", {
D <- datasim_make(x ~ categorical(n, c(one=1, two=2, three=3)))
S <- take_sample(D, n=6000)
# There should be about one-third as many "one"s and "three"s
# The following are just rough checks but are pretty safe
expect_true(sum(S$x=="one") < 1500)
expect_true(sum(S$x=="three") > 2500)
})
test_that("Relative probabilities work with categorical generation.", {
D <- datasim_make(x ~ categorical(n, c("one", "two", "three"), exact=TRUE))
S <- take_sample(D, n=6000)
# There should be about one-third as many "one"s and "three"s
# The following are just rough checks but are pretty safe
expect_true(sum(S$x=="one") == 2000)
expect_true(sum(S$x=="three") == 2000)
})
test_that("rounding works", {
D <- datasim_make(x ~ round(runif(n, 0,10)))
S <- take_sample(D, n = 100)
expect_equal(S$x, round(S$x))
})
test_that("Translation from categorical to numerical works.", {
D <- datasim_make(
g ~ categorical(n, c("A", "B", "C")),
y ~ cat2value(g, A=1, B=2, C=10)
)
Samp <- take_sample(D, n=100)
Summary <- Samp |> dplyr::summarize(m = mean(y), .by = g) |> dplyr::arrange(g)
expect_equal(Summary$m, c(1,2,10))
} )
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