expected_df_both <- data.frame(
y = y,
x1 = c(3L, 2L, NA_integer_, 2L, 3L, 3L),
x2 = as.integer(c(4, 4, 4, 2, 2, 4))
)
expected_tbl_both <- as_tibble(expected_df_both)
expected_x1_df_fact <- data.frame(y, x1 = c(3L, 2L, NA_integer_, 2L, 3L, 3L), x2)
expected_x1_df_char <- data.frame(
y,
x1 = as.integer(c(3, 2, NA, 2, 3, 3)),
x2,
stringsAsFactors = FALSE
)
expected_x1_tbl_char <- tibble(y, x1 = as.integer(c(3, 2, NA, 2, 3, 3)), x2)
expected_x1_tbl_fact <- tibble(
y,
x1 = as.integer(c(3, 2, NA, 2, 3, 3)),
x2 = factor(x2)
)
test_df <- data.frame(
y = y[seq(5)],
x1 = c(NA, NA, "a", "b", "b"),
x2 = c("d", NA, NA, "c", "c")
)
encoded_test <- data.frame(
y = y[seq(5)],
x1 = c(NA, NA, 3, 2, 2),
x2 = c(2, NA, NA, 4, 4)
)
test_that("catto_freq(): multiple data.frame training columns.", {
both_encoded <- check_x1_x2(catto_freq, "data.frame")
for (m in both_encoded) expect_equal(m, cattonum_df(expected_df_both))
})
test_that("catto_freq(): multiple tibble training columns.", {
both_encoded <- check_x1_x2(catto_freq, "tibble")
for (m in both_encoded) expect_equal(m, cattonum_df(expected_tbl_both))
})
test_that("catto_freq(): one data.frame training column.", {
one_encoded <- check_x1(catto_freq, "data.frame")
num_tests <- length(one_encoded)
for (i in seq(from = 1, to = num_tests / 2)) {
expect_equal(one_encoded[[i]], cattonum_df(expected_x1_df_fact))
}
for (i in seq(from = num_tests / 2 + 1, to = num_tests)) {
expect_equal(one_encoded[[i]], cattonum_df(expected_x1_df_char))
}
})
test_that("catto_freq: one tibble training column.", {
one_encoded <- check_x1(catto_freq, "tibble")
num_tests <- length(one_encoded)
for (i in seq(from = 1, to = num_tests / 2)) {
expect_equal(one_encoded[[i]], cattonum_df(expected_x1_tbl_fact))
}
for (i in seq(from = num_tests / 2 + 1, to = num_tests)) {
expect_equal(one_encoded[[i]], cattonum_df(expected_x1_tbl_char))
}
})
test_that("catto_freq() correctly encodes test data.", {
expect_equal(
catto_freq(df_fact, test = test_df),
cattonum_df2(train = expected_df_both, test = encoded_test)
)
})
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