Merge pull request #16 from tanaylab/fix@clustering-crashed-when-hclu…

…st_intra_clusters-was-TRUE-and-input-was-a-matrix

Fix: clustering crashed when `hclust_intra_clusters` was TRUE and inp…

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tglkmeans
 Title: Efficient Implementation of K-Means++ Algorithm
-Version: 0.5.4
+Version: 0.5.5
 Authors@R: c(
     person("Aviezer", "Lifshitz", , "[email protected]", role = c("aut", "cre")),
     person("Amos", "Tanay", role = "aut"),
@@ -26,6 +26,7 @@ Depends:
 Imports: 
     cli,
     doFuture,
+    doRNG,
     dplyr (>= 0.5.0),
     future,
     ggplot2 (>= 2.2.0),
@@ -56,5 +57,5 @@ Config/testthat/parallel: false
 Encoding: UTF-8
 NeedsCompilation: yes
 OS_type: unix
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1
 SystemRequirements: GNU make

NEWS.md

@@ -1,3 +1,7 @@
+# tglkmeans 0.5.5 
+
+* Fix: clustering crashed when `hclust_intra_clusters` was TRUE and input was a matrix. 
+
 # tglkmeans 0.5.4
 
 * Fixed usage of more than 2 cores when testing on CRAN. 

R/TGL_kmeans.R

@@ -215,6 +215,7 @@ TGL_kmeans_tidy <- function(df,
 
 add_data_to_km_object <- function(df, cluster, ids, id_column_name) {
     df %>%
+        as.data.frame() %>%
         # add the ids at id_column_name
         mutate(!!id_column_name := as.character(ids)) %>%
         left_join(cluster, by = id_column_name) %>%

R/intra_clustering.R

@@ -1,15 +1,22 @@
 hclust_every_cluster <- function(km, df, parallel = TRUE) {
-    all_hc <- df %>%
-        plyr::dlply(plyr::.(clust), function(x) {
-            ids <- x$id
-            hc <- as.matrix(x[, -1:-2]) %>%
-                t() %>%
-                tgs_cor(pairwise.complete.obs = TRUE, spearman = TRUE) %>%
-                tgs_dist() %>%
-                hclust(method = "ward.D2")
-            return(tibble(clust = x$clust[1], id = ids, intra_clust_order = hc$order))
-        }, .parallel = parallel) %>%
-        purrr::map_df(~.x)
+    doFuture::withDoRNG({
+        all_hc <- df %>%
+            plyr::dlply(plyr::.(clust), function(x) {
+                ids <- x$id
+                dist <- as.matrix(x[, -1:-2]) %>%
+                    t() %>%
+                    tgs_cor(pairwise.complete.obs = TRUE, spearman = TRUE) %>%
+                    tgs_dist()
+
+                if (length(dist) == 0 || any(is.na(dist))) {
+                    return(tibble(clust = x$clust[1], id = ids, intra_clust_order = 1:length(ids)))
+                }
+
+                hc <- hclust(dist, method = "ward.D2")
+                return(tibble(clust = x$clust[1], id = ids, intra_clust_order = hc$order))
+            }, .parallel = parallel) %>%
+            purrr::map_df(~.x)
+    })
 
     res <- df %>%
         select(id, clust) %>%