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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