3 files changed, 17 insertions, 6 deletions
diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py
index cb24eb24e..7776d7e76 100644
--- a/numpy/lib/arraysetops.py
+++ b/numpy/lib/arraysetops.py
@@ -97,10 +97,11 @@ def unique(ar, return_index=False, return_inverse=False, return_counts=False):
     """
     Find the unique elements of an array.
 
-    Returns the sorted unique elements of an array. There are two optional
+    Returns the sorted unique elements of an array. There are three optional
     outputs in addition to the unique elements: the indices of the input array
-    that give the unique values, and the indices of the unique array that
-    reconstruct the input array.
+    that give the unique values, the indices of the unique array that
+    reconstruct the input array, and the number of times each unique value
+    comes up in the input array.
 
     Parameters
     ----------
diff --git a/numpy/lib/stride_tricks.py b/numpy/lib/stride_tricks.py
index 0f46ed335..a5f247abf 100644
--- a/numpy/lib/stride_tricks.py
+++ b/numpy/lib/stride_tricks.py
@@ -60,9 +60,9 @@ def _broadcast_to(array, shape, subok, readonly):
     if any(size < 0 for size in shape):
         raise ValueError('all elements of broadcast shape must be non-'
                          'negative')
-    broadcast = np.nditer((array,), flags=['multi_index', 'zerosize_ok'],
-                          op_flags=['readonly'], itershape=shape, order='C'
-                          ).itviews[0]
+    broadcast = np.nditer(
+        (array,), flags=['multi_index', 'refs_ok', 'zerosize_ok'],
+        op_flags=['readonly'], itershape=shape, order='C').itviews[0]
     result = _maybe_view_as_subclass(array, broadcast)
     if not readonly and array.flags.writeable:
         result.flags.writeable = True
diff --git a/numpy/lib/tests/test_stride_tricks.py b/numpy/lib/tests/test_stride_tricks.py
index 0b73109bc..ef483921c 100644
--- a/numpy/lib/tests/test_stride_tricks.py
+++ b/numpy/lib/tests/test_stride_tricks.py
@@ -364,5 +364,15 @@ def test_writeable():
     assert_equal(result.flags.writeable, False)
 
 
+def test_reference_types():
+    input_array = np.array('a', dtype=object)
+    expected = np.array(['a'] * 3, dtype=object)
+    actual = broadcast_to(input_array, (3,))
+    assert_array_equal(expected, actual)
+
+    actual, _ = broadcast_arrays(input_array, np.ones(3))
+    assert_array_equal(expected, actual)
+
+
 if __name__ == "__main__":
     run_module_suite()