BUG: Fix handling of non-empty ndarrays

2 files changed, 17 insertions, 11 deletions

diff --git a/numpy/lib/index_tricks.py b/numpy/lib/index_tricks.py
index 2bb11bf1e..752407f18 100644
--- a/numpy/lib/index_tricks.py
+++ b/numpy/lib/index_tricks.py
@@ -72,10 +72,12 @@ def ix_(*args):
     out = []
     nd = len(args)
     for k, new in enumerate(args):
-        # Explicitly type empty sequences to avoid float default
-        new = asarray(new, dtype=None if new else _nx.intp)
-        if (new.ndim != 1):
+        new = asarray(new)
+        if new.ndim != 1:
             raise ValueError("Cross index must be 1 dimensional")
+        if new.size == 0:
+            # Explicitly type empty arrays to avoid float default
+            new = new.astype(_nx.intp)
         if issubdtype(new.dtype, _nx.bool_):
             new, = new.nonzero()
         new.shape = (1,)*k + (new.size,) + (1,)*(nd-k-1)
diff --git a/numpy/lib/tests/test_index_tricks.py b/numpy/lib/tests/test_index_tricks.py
index fc3b90900..0e3c98ee1 100644
--- a/numpy/lib/tests/test_index_tricks.py
+++ b/numpy/lib/tests/test_index_tricks.py
@@ -171,17 +171,21 @@ class TestIndexExpression(TestCase):
 
 class TestIx_(TestCase):
     def test_regression_1(self):
-        # Empty inputs create ouputs of indexing type, gh-5804
-        a, = np.ix_(range(0, 0))
-        assert_equal(a.dtype, np.intp)
+        # Test empty inputs create ouputs of indexing type, gh-5804
+        # Test both lists and arrays
+        for func in (range, np.arange):
+            a, = np.ix_(func(0))
+            assert_equal(a.dtype, np.intp)
 
     def test_shape_and_dtype(self):
         sizes = (4, 5, 3, 2)
-        arrays = np.ix_(*[range(sz) for sz in sizes])
-        for k, (a, sz) in enumerate(zip(arrays, sizes)):
-            assert_equal(a.shape[k], sz)
-            assert_(all(sh == 1 for j, sh in enumerate(a.shape) if j != k))
-            assert_(np.issubdtype(a.dtype, int))
+        # Test both lists and arrays
+        for func in (range, np.arange):
+            arrays = np.ix_(*[func(sz) for sz in sizes])
+            for k, (a, sz) in enumerate(zip(arrays, sizes)):
+                assert_equal(a.shape[k], sz)
+                assert_(all(sh == 1 for j, sh in enumerate(a.shape) if j != k))
+                assert_(np.issubdtype(a.dtype, int))
 
     def test_bool(self):
         bool_a = [True, False, True, True]