Nothing
test_that("`score_apd_pca_numeric` fails when model has no pcs argument", {
expect_snapshot(error = TRUE,
score_apd_pca_numeric(mtcars, mtcars)
)
})
test_that("`score` fails when predictors only contain factors", {
model <- apd_pca(~., iris)
expect_snapshot(error = TRUE,
score(model, iris$Species)
)
})
test_that("`score` fails when predictors are vectors", {
object <- iris
expect_snapshot(error = TRUE,
score(object)
)
})
test_that("`score_apd_pca_numeric` pcs output matches `stats::predict` output", {
model <- apd_pca(mtcars %>% dplyr::slice(1:15))
predictors <- as.matrix(mtcars %>% dplyr::slice(16:30))
expected <- stats::predict(model$pcs, predictors)
expected <- as.data.frame(expected[, 1:model$num_comp, drop = FALSE])
# Select columns of the form PC{number}
actual_output <- score_apd_pca_numeric(model, predictors) %>%
dplyr::select(dplyr::matches("^PC\\d+$"))
# Data frame method
expect_equal(ignore_attr = TRUE,
actual_output,
expected
)
})
test_that("`score` pcs output matches `stats::predict` output", {
model <- apd_pca(mtcars %>% dplyr::slice(1:15))
predictors <- as.matrix(mtcars %>% dplyr::slice(16:30))
expected <- stats::predict(model$pcs, predictors)
expected <- as.data.frame(expected[, 1:model$num_comp, drop = FALSE])
# Select columns of the form PC{number}
actual_output <- score(model, predictors) %>%
dplyr::select(dplyr::matches("^PC\\d+$"))
# Data frame method
expect_equal(ignore_attr = TRUE,
actual_output,
expected
)
})
test_that("`score_apd_pca_bridge` output is correct", {
model <- apd_pca(mtcars %>% dplyr::slice(1:15))
predictors <- as.matrix(mtcars %>% dplyr::slice(16:30))
expected <- stats::predict(model$pcs, predictors)
expected <- as.data.frame(expected[, 1:model$num_comp, drop = FALSE])
# Select columns of the form PC{number}
actual_output <- score_apd_pca_bridge("numeric", model, predictors) %>%
dplyr::select(dplyr::matches("^PC\\d+$"))
# Data frame method
expect_equal(ignore_attr = TRUE,
actual_output,
expected
)
})
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