1 files changed, 62 insertions, 4 deletions
diff --git a/test/test_backend.py b/test/test_backend.py
index 027c4cd..311c075 100644
--- a/test/test_backend.py
+++ b/test/test_backend.py
@@ -218,6 +218,8 @@ def test_empty_backend():
     with pytest.raises(NotImplementedError):
         nx.argmax(M)
     with pytest.raises(NotImplementedError):
+        nx.argmin(M)
+    with pytest.raises(NotImplementedError):
         nx.mean(M)
     with pytest.raises(NotImplementedError):
         nx.std(M)
@@ -264,12 +266,27 @@ def test_empty_backend():
         nx.device_type(M)
     with pytest.raises(NotImplementedError):
         nx._bench(lambda x: x, M, n_runs=1)
+    with pytest.raises(NotImplementedError):
+        nx.solve(M, v)
+    with pytest.raises(NotImplementedError):
+        nx.trace(M)
+    with pytest.raises(NotImplementedError):
+        nx.inv(M)
+    with pytest.raises(NotImplementedError):
+        nx.sqrtm(M)
+    with pytest.raises(NotImplementedError):
+        nx.isfinite(M)
+    with pytest.raises(NotImplementedError):
+        nx.array_equal(M, M)
+    with pytest.raises(NotImplementedError):
+        nx.is_floating_point(M)
 
 
 def test_func_backends(nx):
 
     rnd = np.random.RandomState(0)
     M = rnd.randn(10, 3)
+    SquareM = rnd.randn(10, 10)
     v = rnd.randn(3)
     val = np.array([1.0])
 
@@ -288,6 +305,7 @@ def test_func_backends(nx):
         lst_name = []
 
         Mb = nx.from_numpy(M)
+        SquareMb = nx.from_numpy(SquareM)
         vb = nx.from_numpy(v)
 
         val = nx.from_numpy(val)
@@ -467,6 +485,10 @@ def test_func_backends(nx):
         lst_b.append(nx.to_numpy(A))
         lst_name.append('argmax')
 
+        A = nx.argmin(Mb)
+        lst_b.append(nx.to_numpy(A))
+        lst_name.append('argmin')
+
         A = nx.mean(Mb)
         lst_b.append(nx.to_numpy(A))
         lst_name.append('mean')
@@ -529,7 +551,11 @@ def test_func_backends(nx):
 
         A = nx.where(Mb >= nx.stack([nx.linspace(0, 1, 10)] * 3, axis=1), Mb, 0.0)
         lst_b.append(nx.to_numpy(A))
-        lst_name.append('where')
+        lst_name.append('where (cond, x, y)')
+
+        A = nx.where(nx.from_numpy(np.array([True, False])))
+        lst_b.append(nx.to_numpy(nx.stack(A)))
+        lst_name.append('where (cond)')
 
         A = nx.copy(Mb)
         lst_b.append(nx.to_numpy(A))
@@ -550,15 +576,47 @@ def test_func_backends(nx):
 
         nx._bench(lambda x: x, M, n_runs=1)
 
+        A = nx.solve(SquareMb, Mb)
+        lst_b.append(nx.to_numpy(A))
+        lst_name.append('solve')
+
+        A = nx.trace(SquareMb)
+        lst_b.append(nx.to_numpy(A))
+        lst_name.append('trace')
+
+        A = nx.inv(SquareMb)
+        lst_b.append(nx.to_numpy(A))
+        lst_name.append('matrix inverse')
+
+        A = nx.sqrtm(SquareMb.T @ SquareMb)
+        lst_b.append(nx.to_numpy(A))
+        lst_name.append("matrix square root")
+
+        A = nx.concatenate([vb, nx.from_numpy(np.array([np.inf, np.nan]))], axis=0)
+        A = nx.isfinite(A)
+        lst_b.append(nx.to_numpy(A))
+        lst_name.append("isfinite")
+
+        assert not nx.array_equal(Mb, vb), "array_equal (shape)"
+        assert nx.array_equal(Mb, Mb), "array_equal (elements) - expected true"
+        assert not nx.array_equal(
+            Mb, Mb + nx.eye(*list(Mb.shape))
+        ), "array_equal (elements) - expected false"
+
+        assert nx.is_floating_point(Mb), "is_floating_point - expected true"
+        assert not nx.is_floating_point(
+            nx.from_numpy(np.array([0, 1, 2], dtype=int))
+        ), "is_floating_point - expected false"
+
         lst_tot.append(lst_b)
 
     lst_np = lst_tot[0]
     lst_b = lst_tot[1]
 
     for a1, a2, name in zip(lst_np, lst_b, lst_name):
-        if not np.allclose(a1, a2):
-            print('Assert fail on: ', name)
-        assert np.allclose(a1, a2, atol=1e-7)
+        np.testing.assert_allclose(
+            a2, a1, atol=1e-7, err_msg=f'ASSERT FAILED ON: {name}'
+        )
 
 
 def test_random_backends(nx):