Concatenate list of arrays instead of vstack

1 files changed, 4 insertions, 3 deletions

diff --git a/tree.py b/tree.py
index 64e9d21..9f67b0b 100644
--- a/tree.py
+++ b/tree.py
@@ -202,7 +202,7 @@ def bestsplit(x, y, min_leaf) -> None:
     # twee "x rows" arrays we moeten returnen, en welke split value het beste
     # was natuurlijk.
 
-    # Hieren stoppen we (rows for children, delta_i, split value, col will be added later)
+    # Hieren stacken we arrays onder (rows for children, delta_i, split value, col will be added later)
     best_array = np.zeros((split_points.shape[0], x.shape[0] + 3), dtype='float64')
     # print(f"{best_array=}")
     # Stop wanneer de array met split points leeg is
@@ -255,7 +255,7 @@ def exhaustive_split_search(rows, classes, min_leaf):
     print("\t\t->entering exhaustive split search")
     # We hebben enumerate nodig, want we willen weten op welke col
     # (age,married,house,income,gender) we een split doen
-    exhaustive_best_array = np.zeros((1, rows.shape[0] + 3), dtype='float64')
+    exhaustive_best_array = []
     print(f"Rows:\n{rows},\n Classes:\n{classes}")
     for i, col in enumerate(rows.transpose()):
         # calculate the best split for the col that satisfies the min_leaf
@@ -263,7 +263,8 @@ def exhaustive_split_search(rows, classes, min_leaf):
         best_array_for_col = bestsplit(col, classes, min_leaf)
         # add col number to rows
         best_array_for_col[:,-1] = i
-        exhaustive_best_array = np.vstack((exhaustive_best_array, best_array_for_col))
+        exhaustive_best_array.append(best_array_for_col)
+    exhaustive_best_array = np.concatenate(exhaustive_best_array)
     print("The array with exhaustive splits is\n", exhaustive_best_array)
     print("\t\t->returning from exhaustive split search")
     return exhaustive_best_array