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jrmaddisonjrmaddison
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Test improvements
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‎tests/regression/test_adjoint_reverse_over_forward.py‎

Lines changed: 41 additions & 26 deletions
Original file line numberDiff line numberDiff line change
@@ -35,16 +35,18 @@ def test_assembly():
3535
test = TestFunction(space)
3636

3737
with reverse_over_forward():
38-
u = Function(space, name="u").interpolate(X[0])
38+
u = Function(space, name="u").interpolate(X[0] - 0.5)
39+
u_ref = u.copy(deepcopy=True)
3940
zeta = Function(space, name="zeta").interpolate(X[0])
4041
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
4142

42-
J = assemble(u * u * dx)
43+
J = assemble((u ** 3) * dx)
4344

4445
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
4546
adj_value = u.block_variable.adj_value
46-
assert np.allclose(adj_value.dat.data_ro,
47-
assemble(2 * inner(zeta, test) * dx).dat.data_ro)
47+
assert np.allclose(
48+
adj_value.dat.data_ro,
49+
assemble(6 * inner(u_ref * zeta, test) * dx).dat.data_ro)
4850

4951

5052
@pytest.mark.skipcomplex
@@ -72,16 +74,18 @@ def test_function_assignment():
7274

7375
with reverse_over_forward():
7476
u = Function(space, name="u").interpolate(X[0] - 0.5)
77+
u_ref = u.copy(deepcopy=True)
7578
zeta = Function(space, name="zeta").interpolate(X[0])
7679
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
7780

7881
v = Function(space, name="v").assign(u)
79-
J = assemble(v * v * dx)
82+
J = assemble((v ** 3) * dx)
8083

8184
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
8285
adj_value = u.block_variable.adj_value
83-
assert np.allclose(adj_value.dat.data_ro,
84-
assemble(2 * inner(zeta, test) * dx).dat.data_ro)
86+
assert np.allclose(
87+
adj_value.dat.data_ro,
88+
assemble(6 * inner(u_ref * zeta, test) * dx).dat.data_ro)
8589

8690

8791
@pytest.mark.skipcomplex
@@ -94,15 +98,17 @@ def test_function_assignment_expr():
9498
with reverse_over_forward():
9599
u = Function(space, name="u").interpolate(X[0] - 0.5)
96100
zeta = Function(space, name="zeta").interpolate(X[0])
101+
u_ref = u.copy(deepcopy=True)
97102
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
98103

99104
v = Function(space, name="v").assign(-3 * u)
100-
J = assemble(v * v * dx)
105+
J = assemble((v ** 3) * dx)
101106

102107
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
103108
adj_value = u.block_variable.adj_value
104-
assert np.allclose(adj_value.dat.data_ro,
105-
assemble(18 * inner(zeta, test) * dx).dat.data_ro)
109+
assert np.allclose(
110+
adj_value.dat.data_ro,
111+
assemble(-162 * inner(u_ref * zeta, test) * dx).dat.data_ro)
106112

107113

108114
@pytest.mark.skipcomplex
@@ -116,18 +122,20 @@ def test_subfunction(idx):
116122
with reverse_over_forward():
117123
u = Function(space, name="u")
118124
u.sub(idx).interpolate(-2 * X[0])
125+
u_ref = u.copy(deepcopy=True)
119126
zeta = Function(space, name="zeta")
120127
zeta.sub(idx).interpolate(X[0])
121128
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
122129

123130
v = Function(space, name="v")
124131
v.sub(idx).assign(u.sub(idx))
125-
J = assemble(u.sub(idx) * v.sub(idx) * dx)
132+
J = assemble((u.sub(idx) ** 2) * v.sub(idx) * dx)
126133

127134
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
128135
adj_value = u.block_variable.adj_value
129-
assert np.allclose(adj_value.sub(idx).dat.data_ro,
130-
assemble(2 * inner(zeta[idx], test[idx]) * dx).dat.data_ro[idx])
136+
assert np.allclose(
137+
adj_value.sub(idx).dat.data_ro,
138+
assemble(6 * inner(u_ref[idx] * zeta[idx], test[idx]) * dx).dat.data_ro[idx])
131139

132140

133141
@pytest.mark.skipcomplex
@@ -140,16 +148,18 @@ def test_interpolate():
140148

141149
with reverse_over_forward():
142150
u = Function(space_a, name="u").interpolate(X[0] - 0.5)
151+
u_ref = u.copy(deepcopy=True)
143152
zeta = Function(space_a, name="zeta").interpolate(X[0])
144153
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
145154

146155
v = Function(space_b, name="v").interpolate(u)
147-
J = assemble(v * v * dx)
156+
J = assemble(v ** 3 * dx)
148157

149158
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
150159
adj_value = u.block_variable.adj_value
151-
assert np.allclose(adj_value.dat.data_ro,
152-
assemble(2 * inner(zeta, test_a) * dx).dat.data_ro)
160+
assert np.allclose(
161+
adj_value.dat.data_ro,
162+
assemble(6 * inner(u_ref * zeta, test_a) * dx).dat.data_ro)
153163

154164

155165
@pytest.mark.skipcomplex
@@ -162,16 +172,18 @@ def test_project():
162172

163173
with reverse_over_forward():
164174
u = Function(space_a, name="u").interpolate(X[0] - 0.5)
175+
u_ref = u.copy(deepcopy=True)
165176
zeta = Function(space_a, name="zeta").interpolate(X[0])
166177
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
167178

168179
v = Function(space_b, name="v").project(u)
169-
J = assemble(v * v * dx)
180+
J = assemble(v ** 3 * dx)
170181

171182
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
172183
adj_value = u.block_variable.adj_value
173-
assert np.allclose(adj_value.dat.data_ro,
174-
assemble(2 * inner(Function(space_b).project(zeta), test_a) * dx).dat.data_ro)
184+
assert np.allclose(
185+
adj_value.dat.data_ro,
186+
assemble(6 * inner(Function(space_b).project(u_ref) * Function(space_b).project(zeta), test_a) * dx).dat.data_ro)
175187

176188

177189
@pytest.mark.skipcomplex
@@ -183,6 +195,7 @@ def test_project_overwrite():
183195

184196
with reverse_over_forward():
185197
u = Function(space, name="u").interpolate(X[0] - 0.5)
198+
u_ref = u.copy(deepcopy=True)
186199
zeta = Function(space, name="zeta").interpolate(X[0])
187200
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
188201

@@ -194,12 +207,13 @@ def test_project_overwrite():
194207
-2 * zeta.dat.data_ro)
195208
assert np.allclose(w.block_variable.tlm_value.dat.data_ro,
196209
-2 * zeta.dat.data_ro)
197-
J = assemble(w * w * dx)
210+
J = assemble(w ** 3 * dx)
198211

199212
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
200213
adj_value = u.block_variable.adj_value
201-
assert np.allclose(adj_value.dat.data_ro,
202-
assemble(8 * inner(zeta, test) * dx).dat.data_ro)
214+
assert np.allclose(
215+
adj_value.dat.data_ro,
216+
assemble(-48 * inner(u_ref * zeta, test) * dx).dat.data_ro)
203217

204218

205219
@pytest.mark.skipcomplex
@@ -217,12 +231,13 @@ def test_supermesh_project():
217231
u.block_variable.tlm_value = zeta.copy(deepcopy=True)
218232

219233
v = Function(space_b, name="v").project(u)
220-
J = assemble(v * v * dx)
234+
J = assemble(v ** 2 * dx)
221235

222236
_ = compute_gradient(J.block_variable.tlm_value, Control(u))
223237
adj_value = u.block_variable.adj_value
224-
assert np.allclose(adj_value.dat.data_ro,
225-
assemble(2 * inner(Function(space_a).project(Function(space_b).project(zeta)), test_a) * dx).dat.data_ro)
238+
assert np.allclose(
239+
adj_value.dat.data_ro,
240+
assemble(2 * inner(Function(space_a).project(Function(space_b).project(zeta)), test_a) * dx).dat.data_ro)
226241

227242

228243
@pytest.mark.skipcomplex
@@ -238,7 +253,7 @@ def test_dirichletbc():
238253
bc = DirichletBC(space, u, "on_boundary")
239254

240255
v = project(Constant(0.0), space, bcs=bc)
241-
J = assemble(v * v * v * dx)
256+
J = assemble(v ** 3 * dx)
242257

243258
J_hat = ReducedFunctional(J, Control(u))
244259
assert taylor_test(J_hat, u, zeta, dJdm=J.block_variable.tlm_value) > 1.9

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