library(testthat)
library(recipes)
library(dplyr)
skip_if_not_installed("modeldata")
## -----------------------------------------------------------------------------
data(biomass, package = "modeldata")
biom_tr <- biomass %>%
dplyr::filter(dataset == "Training") %>%
dplyr::select(-dataset, -sample)
biom_te <- biomass %>%
dplyr::filter(dataset == "Testing") %>%
dplyr::select(-dataset, -sample, -HHV)
data(cells, package = "modeldata")
cell_tr <- cells %>%
dplyr::filter(case == "Train") %>%
dplyr::select(-case)
cell_te <- cells %>%
dplyr::filter(case == "Test") %>%
dplyr::select(-case, -class)
load(test_path("test_pls_new.RData"))
## -----------------------------------------------------------------------------
test_that("PLS, dense loadings", {
skip_if_not_installed("mixOmics")
rec <- recipe(HHV ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = "HHV", num_comp = 3)
rec <- prep(rec)
expect_equal(
names(rec$steps[[1]]$res),
c("mu", "sd", "coefs", "col_norms")
)
tr_new <- bake(rec, new_data = NULL, all_predictors())
expect_equal(tr_new, bm_pls_tr)
te_new <- bake(rec, biom_te)
expect_equal(te_new, bm_pls_te)
})
test_that("PLS, dense loadings, multiple outcomes", {
skip_if_not_installed("mixOmics")
rec <- recipe(HHV + carbon ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = c("HHV", "carbon"), num_comp = 3)
rec <- prep(rec)
expect_equal(
names(rec$steps[[1]]$res),
c("mu", "sd", "coefs", "col_norms")
)
tr_new <- bake(rec, new_data = NULL, all_predictors())
expect_equal(tr_new, bm_pls_multi_tr)
te_new <- bake(rec, biom_te %>% select(-carbon))
expect_equal(te_new, bm_pls_multi_te)
})
test_that("PLS, sparse loadings", {
skip_if_not_installed("mixOmics")
rec <- recipe(HHV ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = "HHV", num_comp = 3,
predictor_prop = 3 / 5)
rec <- prep(rec)
expect_equal(
names(rec$steps[[1]]$res),
c("mu", "sd", "coefs", "col_norms")
)
tr_new <- bake(rec, new_data = NULL, all_predictors())
expect_equal(tr_new, bm_spls_tr)
te_new <- bake(rec, biom_te)
expect_equal(te_new, bm_spls_te)
})
test_that("PLS, dense loadings, multiple outcomes", {
skip_if_not_installed("mixOmics")
rec <- recipe(HHV + carbon ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = c("HHV", "carbon"), num_comp = 3,
predictor_prop = 3 / 5)
rec <- prep(rec)
expect_equal(
names(rec$steps[[1]]$res),
c("mu", "sd", "coefs", "col_norms")
)
tr_new <- bake(rec, new_data = NULL, all_predictors())
expect_equal(tr_new, bm_spls_multi_tr)
te_new <- bake(rec, biom_te %>% select(-carbon))
expect_equal(te_new, bm_spls_multi_te)
})
## -----------------------------------------------------------------------------
test_that("PLS-DA, dense loadings", {
skip_if_not_installed("mixOmics")
rec <- recipe(class ~ ., data = cell_tr) %>%
step_pls(all_predictors(), outcome = "class", num_comp = 3)
rec <- prep(rec)
expect_equal(
names(rec$steps[[1]]$res),
c("mu", "sd", "coefs", "col_norms")
)
tr_new <- bake(rec, new_data = NULL, all_predictors())
expect_equal(tr_new, cell_plsda_tr)
te_new <- bake(rec, cell_te)
expect_equal(te_new, cell_plsda_te)
})
test_that("PLS-DA, dense loadings, multiple outcomes", {
skip_if_not_installed("mixOmics")
rec <- recipe(class + case ~ ., data = cells) %>%
step_pls(all_predictors(), outcome = c("class", "case"), num_comp = 3)
expect_snapshot(error = TRUE, prep(rec))
})
test_that("PLS-DA, sparse loadings", {
skip_if_not_installed("mixOmics")
rec <- recipe(class ~ ., data = cell_tr) %>%
step_pls(all_predictors(), outcome = "class", num_comp = 3,
predictor_prop = 50 / 56)
rec <- prep(rec)
expect_equal(
names(rec$steps[[1]]$res),
c("mu", "sd", "coefs", "col_norms")
)
tr_new <- bake(rec, new_data = NULL, all_predictors())
expect_equal(tr_new, cell_splsda_tr)
te_new <- bake(rec, cell_te)
expect_equal(te_new, cell_splsda_te)
})
test_that("PLS-DA, sparse loadings, multiple outcomes", {
skip_if_not_installed("mixOmics")
rec <- recipe(class + case ~ ., data = cells) %>%
step_pls(all_predictors(), outcome = c("class", "case"), num_comp = 3,
predictor_prop = 50 / 56)
expect_snapshot(error = TRUE, prep(rec))
})
## -----------------------------------------------------------------------------
test_that("No PLS", {
skip_if_not_installed("mixOmics")
rec <- recipe(class ~ ., data = cell_tr) %>%
step_pls(all_predictors(), outcome = "class", num_comp = 0)
rec <- prep(rec)
expect_null(
rec$steps[[1]]$res
)
pred_names <- summary(rec)$variable[summary(rec)$role == "predictor"]
tr_new <- bake(rec, new_data = NULL, all_predictors())
expect_equal(names(tr_new), pred_names)
te_new <- bake(rec, cell_te, all_predictors())
expect_equal(names(te_new), pred_names)
})
## -----------------------------------------------------------------------------
test_that("tidy method", {
skip_if_not_installed("mixOmics")
rec <- recipe(HHV ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = "HHV", num_comp = 3, id = "dork")
tidy_pre <- tidy(rec, number = 1)
exp_pre <- tibble::tribble(
~terms, ~value, ~component, ~id,
"all_predictors()", NA_real_, NA_character_, "dork"
)
expect_equal(tidy_pre, exp_pre)
rec <- prep(rec)
tidy_post <- tidy(rec, number = 1)
exp_post <-
tibble::tribble(
~terms, ~value, ~component, ~id,
"carbon", 0.82813459059393, "PLS1", "dork",
"carbon", 0.718469477422311, "PLS2", "dork",
"carbon", 0.476111929729498, "PLS3", "dork",
"hydrogen", -0.206963356355556, "PLS1", "dork",
"hydrogen", 0.642998926998282, "PLS2", "dork",
"hydrogen", 0.262836631090453, "PLS3", "dork",
"oxygen", -0.49241242430895, "PLS1", "dork",
"oxygen", 0.299176769170812, "PLS2", "dork",
"oxygen", 0.418081563632953, "PLS3", "dork",
"nitrogen", -0.122633995804743, "PLS1", "dork",
"nitrogen", -0.172719084680244, "PLS2", "dork",
"nitrogen", 0.642403301090588, "PLS3", "dork",
"sulfur", 0.11768677260853, "PLS1", "dork",
"sulfur", -0.217341766567037, "PLS2", "dork",
"sulfur", 0.521114256955661, "PLS3", "dork"
)
expect_equal(tidy_post, exp_post, tolerance = 0.01)
})
## -----------------------------------------------------------------------------
test_that("Deprecation warning", {
expect_snapshot(error = TRUE,
recipe(~ ., data = mtcars) %>%
step_pls(outcome = "mpg", preserve = TRUE)
)
})
test_that("print method", {
skip_if_not_installed("mixOmics")
rec <- recipe(HHV ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = "HHV", num_comp = 3, id = "dork")
expect_snapshot(print(rec))
rec <- prep(rec)
expect_snapshot(print(rec))
})
test_that("keep_original_cols works", {
skip_if_not_installed("mixOmics")
pls_rec <- recipe(HHV ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = "HHV", num_comp = 3, keep_original_cols = TRUE)
pls_trained <- prep(pls_rec)
pls_pred <- bake(pls_trained, new_data = biom_te, all_predictors())
expect_equal(
colnames(pls_pred),
c(
"carbon", "hydrogen", "oxygen", "nitrogen", "sulfur",
"PLS1", "PLS2", "PLS3"
)
)
})
test_that("can prep recipes with no keep_original_cols", {
skip_if_not_installed("mixOmics")
pls_rec <- recipe(HHV ~ ., data = biom_tr) %>%
step_pls(all_predictors(), outcome = "HHV", num_comp = 3)
pls_rec$steps[[1]]$keep_original_cols <- NULL
expect_snapshot(
pls_trained <- prep(pls_rec, training = biom_tr, verbose = FALSE)
)
expect_error(
pls_pred <- bake(pls_trained, new_data = biom_te, all_predictors()),
NA
)
})
test_that("empty selection prep/bake is a no-op", {
rec1 <- recipe(mpg ~ ., mtcars)
rec2 <- step_pls(rec1, outcome = "mpg")
rec1 <- prep(rec1, mtcars)
rec2 <- prep(rec2, mtcars)
baked1 <- bake(rec1, mtcars)
baked2 <- bake(rec2, mtcars)
expect_identical(baked1, baked2)
})
test_that("empty selection tidy method works", {
rec <- recipe(mpg ~ ., mtcars)
rec <- step_pls(rec, outcome = "mpg")
expect <- tibble(
terms = character(),
value = double(),
component = character(),
id = character()
)
expect_identical(tidy(rec, number = 1), expect)
rec <- prep(rec, mtcars)
expect_identical(tidy(rec, number = 1), expect)
})
test_that("empty printing", {
skip_if(packageVersion("rlang") < "1.0.0")
rec <- recipe(mpg ~ ., mtcars)
rec <- step_pls(rec, outcome = "mpg")
expect_snapshot(rec)
rec <- prep(rec, mtcars)
expect_snapshot(rec)
})
test_that("bake method errors when needed non-standard role columns are missing", {
skip_if_not_installed("mixOmics")
rec <- recipe(HHV ~ ., data = biom_tr) %>%
step_pls(carbon, outcome = "HHV", num_comp = 3) %>%
update_role(carbon, new_role = "potato") %>%
update_role_requirements(role = "potato", bake = FALSE)
rec <- prep(rec)
expect_error(bake(rec, new_data = biom_tr[, c(-1)]),
class = "new_data_missing_column")
})
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