Test improvements

tests/regression/test_adjoint_reverse_over_forward.py

@@ -121,7 +121,7 @@ def test_subfunction(idx):
 
     with reverse_over_forward():
         u = Function(space, name="u")
-        u.sub(idx).interpolate(-2 * X[0])
+        u.sub(idx).interpolate(X[0] - 0.5)
         u_ref = u.copy(deepcopy=True)
         zeta = Function(space, name="zeta")
         zeta.sub(idx).interpolate(X[0])
@@ -140,7 +140,7 @@ def test_subfunction(idx):
 
 @pytest.mark.skipcomplex
 def test_interpolate():
-    mesh = UnitSquareMesh(10, 10)
+    mesh = UnitIntervalMesh(10)
     X = SpatialCoordinate(mesh)
     space_a = FunctionSpace(mesh, "Lagrange", 1)
     space_b = FunctionSpace(mesh, "Lagrange", 2)
@@ -162,9 +162,33 @@ def test_interpolate():
         assemble(6 * inner(u_ref * zeta, test_a) * dx).dat.data_ro)
 
 
+@pytest.mark.skipcomplex
+def test_interpolate_expr():
+    mesh = UnitIntervalMesh(10)
+    X = SpatialCoordinate(mesh)
+    space_a = FunctionSpace(mesh, "Lagrange", 1)
+    space_b = FunctionSpace(mesh, "Lagrange", 2)
+    test_a = TestFunction(space_a)
+
+    with reverse_over_forward():
+        u = Function(space_a, name="u").interpolate(X[0] - 0.5)
+        u_ref = u.copy(deepcopy=True)
+        zeta = Function(space_a, name="zeta").interpolate(X[0])
+        u.block_variable.tlm_value = zeta.copy(deepcopy=True)
+
+        v = Function(space_b, name="v").interpolate(-3 * u)
+        J = assemble(v ** 3 * dx)
+
+    _ = compute_gradient(J.block_variable.tlm_value, Control(u))
+    adj_value = u.block_variable.adj_value
+    assert np.allclose(
+        adj_value.dat.data_ro,
+        assemble(-162 * inner(u_ref * zeta, test_a) * dx).dat.data_ro)
+
+
 @pytest.mark.skipcomplex
 def test_project():
-    mesh = UnitSquareMesh(10, 10)
+    mesh = UnitIntervalMesh(10)
     X = SpatialCoordinate(mesh)
     space_a = FunctionSpace(mesh, "Lagrange", 1)
     space_b = FunctionSpace(mesh, "Discontinuous Lagrange", 0)