Update SciPy minimize tests

tests/firedrake/adjoint/test_optimisation.py

@@ -121,13 +121,8 @@ def _simple_helmholz_model(V, source):
     return u
 
 
-@pytest.mark.parametrize(
-    "riesz_representation",
-    [None,
-     "l2",
-     pytest.param("H1", marks=pytest.mark.xfail(reason="H1 is the wrong norm for this problem"))])
 @pytest.mark.skipcomplex
-def test_simple_inversion(riesz_representation):
+def test_simple_inversion():
     """Test inversion of source term in helmholze eqn."""
     mesh = UnitIntervalMesh(10)
     V = FunctionSpace(mesh, "CG", 1)
@@ -141,7 +136,7 @@ def test_simple_inversion(riesz_representation):
 
     # now rerun annotated model with zero source
     source = Function(V)
-    c = Control(source, riesz_map=riesz_representation)
+    c = Control(source, riesz_map="l2")
     u = _simple_helmholz_model(V, source)
 
     J = assemble(1e6 * (u - u_ref)**2*dx)
@@ -151,6 +146,44 @@ def test_simple_inversion(riesz_representation):
     assert_allclose(x.dat.data, source_ref.dat.data, rtol=1e-2)
 
 
+@pytest.mark.skipcomplex
+def test_simple_inversion_scipy_riesz_map_ignored():
+    mesh = UnitIntervalMesh(10)
+    V = FunctionSpace(mesh, "CG", 1)
+    source_ref = Function(V)
+    x = SpatialCoordinate(mesh)
+    source_ref.interpolate(cos(pi*x**2))
+
+    # compute reference solution
+    with stop_annotating():
+        u_ref = _simple_helmholz_model(V, source_ref)
+
+    class Counter:
+        def __init__(self):
+            self._n = 0
+
+        def __call__(self, xk):
+            self._n += 1
+
+        @property
+        def n(self):
+            return self._n
+
+    iterations = {}
+    for riesz_map in ("l2", "L2", "H1"):
+        source = Function(V)
+        u = _simple_helmholz_model(V, source)
+        J = assemble(1e6 * (u - u_ref)**2*dx)
+        c = Control(source, riesz_map=riesz_map)
+        rf = ReducedFunctional(J, c)
+        cb = Counter()
+        x = minimize(rf, callback=cb)
+        assert_allclose(x.dat.data, source_ref.dat.data, rtol=1e-2)
+        iterations[riesz_map] = cb.n
+    # Should always take the same number of iterations
+    assert len(set(iterations.values())) == 1
+
+
 @pytest.mark.parametrize("minimize", [minimize_tao_lmvm,
                                       minimize_tao_nls])
 @pytest.mark.parametrize("riesz_representation", [None, "l2", "L2", "H1"])