one more check for clusters to ensure we fail if clusters is not a ve…

…ctor

packages/rOpenScPCA/R/evaluate-clusters.R

@@ -208,6 +208,7 @@ calculate_stability <- function(
 
   # check clusters and matrix compatibility
   stopifnot(
+    "The provided clusters variable must be a vector" = is.factor(clusters) || is.vector(clusters),
     "The number of rows in the matrix must equal the length of the clusters vector." =
       nrow(pca_matrix) == length(clusters)
   )
@@ -229,8 +230,11 @@ calculate_stability <- function(
           dplyr::slice(1) |>
           dplyr::select(!c("cell_id", "cluster")) |>
           dplyr::mutate(
-            replicate = i, # define this variable here to ensure it's numeric
-            ari = ari
+            # define this variable here to ensure it's numeric
+            replicate = i,
+            ari = ari,
+            # ensure these columns come first
+            .before = "algorithm"
           )
 
         return(ari_df)

packages/rOpenScPCA/tests/testthat/test-evaluate-clusters.R

@@ -94,6 +94,28 @@ test_that("calculate_stability errors as expected", {
   })
 
   expect_error({
+    # cluster_df not a vector
     calculate_stability(test_mat, cluster_df)
   })
+
+
+  # the next test ensures we fail even if the length of clusters
+  # is the same as the nrow in test_mat
+
+  # make it smaller for test
+  test_mat_small <- test_mat[1:5, ]
+
+  # make df with same length as rows in test_mat
+  bad_df <- data.frame(
+    cluster = sample(1:2, nrow(test_mat_small), replace = T),
+    cell_id = rownames(test_mat_small),
+    col1 = 1,
+    col2 = 1,
+    col3 = 1
+  )
+
+  expect_error({
+    # cluster_df not a vector, even though df length matches test mat
+    calculate_stability(test_mat_small, bad_df)
+  })
 })