diff --git a/nutils/evaluable.py b/nutils/evaluable.py
index d00f83c6b..076b6d079 100644
--- a/nutils/evaluable.py
+++ b/nutils/evaluable.py
@@ -1753,7 +1753,7 @@ def __init__(self, args: typing.Tuple[Array, ...], args_idx: typing.Tuple[typing
         try:
             shape = tuple(lengths[i] for i in out_idx)
         except KeyError:
-            raise ValueError('Output axis {} is not listed in any of the arguments.'.format(', '.join(i for i in out_idx if i not in lengths)))
+            raise ValueError('Output axis {} is not listed in any of the arguments.'.format(', '.join(str(i) for i in out_idx if i not in lengths)))
         self.args = args
         self.args_idx = args_idx
         self.out_idx = out_idx
diff --git a/tests/test_evaluable.py b/tests/test_evaluable.py
index fda0dc645..f05065f23 100644
--- a/tests/test_evaluable.py
+++ b/tests/test_evaluable.py
@@ -68,8 +68,6 @@ def assertFunctionAlmostEqual(self, actual, desired, decimal):
             self.assertArrayAlmostEqual(actual.eval(**evalargs), desired, decimal)
         with self.subTest('simplified'):
             self.assertArrayAlmostEqual(actual.simplified.eval(**evalargs), desired, decimal)
-        with self.subTest('optimized'):
-            self.assertArrayAlmostEqual(actual.optimized_for_numpy.eval(**evalargs), desired, decimal)
         if actual.dtype != bool:
             with self.subTest('sparse'):
                 indices, values, shape = sparse.extract(evaluable.eval_sparse(actual, **evalargs))
diff --git a/tests/test_function.py b/tests/test_function.py
index e2f21baa5..d28554f4d 100644
--- a/tests/test_function.py
+++ b/tests/test_function.py
@@ -1187,11 +1187,11 @@ def test_lower(self):
         points = ref.getpoints('bezier', 4)
         coordinates = evaluable.constant(points.coords)
         lowerargs = function.LowerArgs.for_space('X', (self.checktransforms,), evaluable.Argument('ielem', (), int), coordinates)
-        lowered = self.basis.lower(lowerargs)
+        lowered = evaluable.compile(self.basis.lower(lowerargs), stats=False)
         with _builtin_warnings.catch_warnings():
             _builtin_warnings.simplefilter('ignore', category=evaluable.ExpensiveEvaluationWarning)
             for ielem in range(self.checknelems):
-                value = lowered.eval(ielem=ielem)
+                value = lowered(ielem=ielem)
                 if value.shape[0] == 1:
                     value = numpy.tile(value, (points.npoints, 1))
                 self.assertAllAlmostEqual(value, self.checkeval(ielem, points))
diff --git a/tests/test_sample.py b/tests/test_sample.py
index 186143db4..6a117022f 100644
--- a/tests/test_sample.py
+++ b/tests/test_sample.py
@@ -56,10 +56,11 @@ def test_get_evaluable_weights(self):
     def test_get_lower_args(self):
         assert len(self.desired_transform_chains) == len(self.desired_points) == self.desired_nelems
         args = self.sample.get_lower_args(evaluable.Argument('ielem', (), int))
+        args_points_shape = evaluable.compile(args.points_shape)
         for ielem, (desired_chains, desired_points) in enumerate(zip(self.desired_transform_chains, self.desired_points)):
             assert len(desired_chains) == len(desired_points) == len(self.desired_spaces)
             desired_shape = tuple(p.coords.shape[0] for p in desired_points)
-            actual_shape = tuple(n.__index__() for n in evaluable.Tuple(args.points_shape).eval(ielem=ielem))
+            actual_shape = tuple(n.__index__() for n in args_points_shape(ielem=ielem))
             self.assertEqual(actual_shape, desired_shape)
             offset = 0
             for space, desired_chain, desired_point in zip(self.desired_spaces, desired_chains, desired_points):