Fixed bug with copied data instead of using UMAP.

fdc/fdc.py

@@ -55,16 +55,13 @@ class Clustering:
             data = data.reshape((data.shape[0], 1))
 
         # do UMAP if needed (e.g. data has more than 2 features)
-        if data.shape[1] > self.max_components:
-            data_embedded = umap.UMAP(
-                n_neighbors=self.UMAP_neb
-                , min_dist=self.min_dist_UMAP
-                , n_components=self.max_components
-                , metric=self.metric
-                , random_state=42
-                ).fit_transform(data)
-        else:
-            data_embedded = data
+        data_embedded = umap.UMAP(
+            n_neighbors=self.UMAP_neb
+            , min_dist=self.min_dist_UMAP
+            , n_components=self.max_components
+            , metric=self.metric
+            , random_state=42
+            ).fit_transform(data)
 
         # normalize the data
         for n in range(data_embedded.shape[1]):