Merge pull request #169 from tidymodels/fix160

Author: EmilHvitfeldt

R/k_means.R

@@ -250,7 +250,37 @@ check_args.k_means <- function(object) {
 #' @keywords internal
 #' @export
 .k_means_fit_clustMixType <- function(x, k, ...) {
-  res <- clustMixType::kproto(x, k, ...)
+  res <- tryCatch(
+    clustMixType::kproto(x, k, ...),
+    error = function(cnd) {
+      if (grepl("No factor variables", cnd$message)) {
+        cli::cli_abort(
+          c(
+            "Engine `clustMixType` requires both numeric and categorical \\
+          predictors.",
+          "x" = "Only numeric predictors where used.",
+          "i" = "Try using the `stats` engine with \\
+          {.code mod %>% set_engine(\"stats\")}."
+          ),
+          call = call("fit")
+        )
+      }
+      if (grepl("No numeric variables", cnd$message)) {
+        cli::cli_abort(
+          c(
+            "Engine `clustMixType` requires both numeric and categorical \\
+          predictors.",
+          "x" = "Only categorical predictors where used.",
+          "i" = "Try using the `klaR` engine with \\
+          {.code mod %>% set_engine(\"klaR\")}."
+          ),
+          call = call("fit")
+        )
+      }
+      stop(cnd)
+    }
+  )
+
   new_order <- unique(res$cluster)
   res$cluster <- order(new_order)[res$cluster]
   res$centers <- res$centers[new_order, , drop = FALSE]

tests/testthat/_snaps/k_means-clustMixType.md

@@ -0,0 +1,21 @@
+# modifies errors about suggested other models
+
+    Code
+      k_means(num_clusters = 3) %>% set_engine("clustMixType") %>% fit(~., data = mtcars)
+    Condition
+      Error in `fit()`:
+      ! Engine `clustMixType` requires both numeric and categorical predictors.
+      x Only numeric predictors where used.
+      i Try using the `stats` engine with `mod %>% set_engine("stats")`.
+
+---
+
+    Code
+      k_means(num_clusters = 3) %>% set_engine("clustMixType") %>% fit(~., data = data.frame(
+        letters, LETTERS))
+    Condition
+      Error in `fit()`:
+      ! Engine `clustMixType` requires both numeric and categorical predictors.
+      x Only categorical predictors where used.
+      i Try using the `klaR` engine with `mod %>% set_engine("klaR")`.
+

tests/testthat/test-k_means-clustMixType.R

@@ -97,3 +97,22 @@ test_that("extract_cluster_assignment() works", {
     expected
   )
 })
+
+test_that("modifies errors about suggested other models", {
+  skip_if_not_installed("clustMixType")
+
+  expect_snapshot(
+    error = TRUE,
+    k_means(num_clusters = 3) %>%
+      set_engine("clustMixType") %>%
+      fit(~., data = mtcars)
+  )
+
+  expect_snapshot(
+    error = TRUE,
+    k_means(num_clusters = 3) %>%
+      set_engine("clustMixType") %>%
+      fit(~., data = data.frame(letters, LETTERS))
+  )
+})
+