take to_numpy before comparing actx's scalars

test/test_arraycontext.py

@@ -257,7 +257,7 @@ def test_actx_stack(actx_factory):
     ndofs = 5000
     args = [np.random.randn(ndofs) for i in range(10)]
 
-    assert_close_to_numpy(
+    assert_close_to_numpy_in_containers(
             actx, lambda _np, *_args: _np.stack(_args), args)
 
 
@@ -656,9 +656,8 @@ def test_container_arithmetic(actx_factory):
     bcast_result = ary_dof + bcast_dc_of_dofs
     bcast_dc_of_dofs + ary_dof
 
-    res = bcast_result.mass - 2*ary_of_dofs
-
-    assert np.linalg.norm(actx.to_numpy(res[0][0]) < 1e-8)
+    assert actx.to_numpy(actx.np.linalg.norm(bcast_result.mass
+                                             - 2*ary_of_dofs)) < 1e-8
 
     mock_gradient = MyContainerDOFBcast(
             name="yo",
@@ -670,9 +669,8 @@ def test_container_arithmetic(actx_factory):
     assert isinstance(grad_matvec_result.mass, DOFArray)
     assert grad_matvec_result.momentum.shape == (3,)
 
-    res = grad_matvec_result.mass - 3*ary_of_dofs**2
-
-    assert np.linalg.norm(actx.to_numpy(res[0][0]) < 1e-8)
+    assert actx.to_numpy(actx.np.linalg.norm(grad_matvec_result.mass
+                                             - 3*ary_of_dofs**2)) < 1e-8
 
     # }}}