STY, TST: fix formatting and add tests for other dtypes, unaligned data

2 files changed, 19 insertions, 3 deletions

diff --git a/numpy/core/src/common/cblasfuncs.c b/numpy/core/src/common/cblasfuncs.c
index c46843d63..39572fed4 100644
--- a/numpy/core/src/common/cblasfuncs.c
+++ b/numpy/core/src/common/cblasfuncs.c
@@ -197,7 +197,7 @@ _bad_strides(PyArrayObject *ap)
         if ((strides[i] < 0) || (strides[i] % itemsize) != 0) {
             return 1;
         }
-        if ((strides[i] == 0 && dims[i] >1)) {
+        if ((strides[i] == 0 && dims[i] > 1)) {
             return 1;
         }
     }
diff --git a/numpy/core/tests/test_multiarray.py b/numpy/core/tests/test_multiarray.py
index 703edb190..b64b70a94 100644
--- a/numpy/core/tests/test_multiarray.py
+++ b/numpy/core/tests/test_multiarray.py
@@ -2714,10 +2714,11 @@ class TestMethods(object):
             assert_equal(func(edf.T, edf), edtdf)
 
     @pytest.mark.parametrize('func', (np.dot, np.matmul))
-    def test_no_dgemv(self, func):
+    @pytest.mark.parametrize('dtype', 'ifdFD')
+    def test_no_dgemv(self, func, dtype):
         # check vector arg for contiguous before gemv
         # gh-12156
-        a = np.arange(8.0).reshape(2, 4)
+        a = np.arange(8.0, dtype=dtype).reshape(2, 4)
         b = np.broadcast_to(1., (4, 1))
         ret1 = func(a, b)
         ret2 = func(a, b.copy())
@@ -2727,6 +2728,21 @@ class TestMethods(object):
         ret2 = func(b.T.copy(), a.T)
         assert_equal(ret1, ret2)
 
+        # check for unaligned data
+        dt = np.dtype(dtype)
+        a = np.zeros(8 * dt.itemsize // 2 + 1, dtype='int16')[1:].view(dtype)
+        a = a.reshape(2, 4)
+        b = a[0]
+        # make sure it is not aligned
+        assert_(a.__array_interface__['data'][0] % dt.itemsize != 0)
+        ret1 = func(a, b)
+        ret2 = func(a.copy(), b.copy())
+        assert_equal(ret1, ret2)
+
+        ret1 = func(b.T, a.T)
+        ret2 = func(b.T.copy(), a.T.copy())
+        assert_equal(ret1, ret2)
+
     def test_dot(self):
         a = np.array([[1, 0], [0, 1]])
         b = np.array([[0, 1], [1, 0]])