Fix broadcasting of index with the same values but different names

tests/test_base.py

@@ -1575,6 +1575,28 @@ class TestReshapeFns:
                 )
             )
 
+        broadcasted = reshape_fns.broadcast(
+            pd.DataFrame([[1, 2, 3]], columns=pd.Index(['a', 'b', 'c'], name='i1')),
+            pd.DataFrame([[4, 5, 6]], columns=pd.Index(['a', 'b', 'c'], name='i2')),
+            index_from='stack',
+            columns_from='stack',
+            drop_duplicates=True,
+            drop_redundant=True,
+            ignore_sr_names=True
+        )
+        pd.testing.assert_frame_equal(
+            broadcasted[0],
+            pd.DataFrame([[1, 2, 3]], columns=pd.MultiIndex.from_tuples([
+                ('a', 'a'), ('b', 'b'), ('c', 'c')
+            ], names=['i1', 'i2']))
+        )
+        pd.testing.assert_frame_equal(
+            broadcasted[1],
+            pd.DataFrame([[4, 5, 6]], columns=pd.MultiIndex.from_tuples([
+                ('a', 'a'), ('b', 'b'), ('c', 'c')
+            ], names=['i1', 'i2']))
+        )
+
     def test_broadcast_keep(self):
         # 1d
         to_broadcast = 0, a1, a2, sr_none, sr1, sr2

vectorbt/base/reshape_fns.py

@@ -221,7 +221,7 @@ def broadcast_index(args: tp.Sequence[tp.AnyArray],
                 if checks.is_pandas(arg):
                     index = index_fns.get_index(arg, axis)
                     if last_index is not None:
-                        if not pd.Index.equals(index, last_index):
+                        if not checks.is_index_equal(index, last_index):
                             index_conflict = True
                     last_index = index
                     continue
@@ -241,18 +241,17 @@ def broadcast_index(args: tp.Sequence[tp.AnyArray],
                         if new_index is None:
                             new_index = index
                         else:
+                            if checks.is_index_equal(index, new_index):
+                                continue
                             if index_from.lower() == 'strict':
                                 # If pandas objects have different index/columns, raise an exception
-                                if not pd.Index.equals(index, new_index):
-                                    raise ValueError(
-                                        f"Broadcasting {index_str} is not allowed when {index_str}_from=strict")
+                                raise ValueError(
+                                    f"Broadcasting {index_str} is not allowed when {index_str}_from=strict")
                             # Broadcasting index must follow the rules of a regular broadcasting operation
                             # https://docs.scipy.org/doc/numpy/user/basics.broadcasting.html#general-broadcasting-rules
                             # 1. rule: if indexes are of the same length, they are simply stacked
                             # 2. rule: if index has one element, it gets repeated and then stacked
 
-                            if pd.Index.equals(index, new_index):
-                                continue
                             if len(index) != len(new_index):
                                 if len(index) > 1 and len(new_index) > 1:
                                     raise ValueError("Indexes could not be broadcast together")