def test_predictor(self):
""" Integral regression test of integrator algorithm using CE/CM. """
settings = opendeplete.Settings()
settings.dt_vec = [0.75, 0.75]
settings.output_dir = self.results
op = dummy_geometry.DummyGeometry(settings)
# Perform simulation using the predictor algorithm
opendeplete.predictor(op, print_out=False)
# Load the files
res = results.read_results(settings.output_dir + "/results.h5")
_, y1 = utilities.evaluate_single_nuclide(res, "1", "1")
_, y2 = utilities.evaluate_single_nuclide(res, "1", "2")
# Mathematica solution
s1 = [2.46847546272295, 0.986431226850467]
s2 = [4.11525874568034, -0.0581692232513460]
tol = 1.0e-13
self.assertLess(np.absolute(y1[1] - s1[0]), tol)
self.assertLess(np.absolute(y2[1] - s1[1]), tol)
self.assertLess(np.absolute(y1[2] - s2[0]), tol)
self.assertLess(np.absolute(y2[2] - s2[1]), tol)
def test_cecm(self):
""" Integral regression test of integrator algorithm using CE/CM. """
settings = opendeplete.Settings()
settings.dt_vec = [0.75, 0.75]
settings.output_dir = self.results
op = dummy_geometry.DummyGeometry(settings)
# Perform simulation using the MCNPX/MCNP6 algorithm
opendeplete.cecm(op, print_out=False)
# Load the files
res = results.read_results(settings.output_dir + "/results.h5")
_, y1 = utilities.evaluate_single_nuclide(res, "1", "1")
_, y2 = utilities.evaluate_single_nuclide(res, "1", "2")
# Mathematica solution
s1 = [1.86872629872102, 1.395525772416039]
s2 = [2.18097439443550, 2.69429754646747]
tol = 1.0e-13
self.assertLess(np.absolute(y1[1] - s1[0]), tol)
self.assertLess(np.absolute(y2[1] - s1[1]), tol)
self.assertLess(np.absolute(y1[2] - s2[0]), tol)
self.assertLess(np.absolute(y2[2] - s2[1]), tol)
def test_evaluate_eigenvalue(self):
""" Tests evaluating eigenvalue
"""
# Load the reference
res = results.read_results("test/test_reference.h5")
x, y = utilities.evaluate_eigenvalue(res)
x_ref = [0.0, 1296000.0, 2592000.0, 3888000.0]
y_ref = [
1.1921984510699268, 1.1809789004827738, 1.1930669366462165,
1.2102186170751308
]
np.testing.assert_array_equal(x, x_ref)
np.testing.assert_array_equal(y, y_ref)
def test_evaluate_single_nuclide(self):
""" Tests evaluating single nuclide utility code.
"""
# Load the reference
res = results.read_results("test/test_reference.h5")
x, y = utilities.evaluate_single_nuclide(res, "1", "Xe135")
x_ref = [0.0, 1296000.0, 2592000.0, 3888000.0]
y_ref = [
6.6747328233649218e+08, 3.5519326338509556e+14,
3.5965291907016744e+14, 3.3660528631036400e+14
]
np.testing.assert_array_equal(x, x_ref)
np.testing.assert_array_equal(y, y_ref)
def test_evaluate_eigenvalue(self):
""" Tests evaluating eigenvalue
"""
# Load the reference
res = results.read_results("test/test_reference.h5")
x, y = utilities.evaluate_eigenvalue(res)
x_ref = [0.0, 1296000.0, 2592000.0, 3888000.0]
y_ref = [
1.1921986054449838, 1.1712785643938586, 1.1927099024502694,
1.2269183590698847
]
np.testing.assert_array_equal(x, x_ref)
np.testing.assert_array_equal(y, y_ref)
def test_evaluate_single_nuclide(self):
""" Tests evaluating single nuclide utility code.
"""
# Load the reference
res = results.read_results("test/test_reference.h5")
x, y = utilities.evaluate_single_nuclide(res, "1", "Xe135")
x_ref = [0.0, 1296000.0, 2592000.0, 3888000.0]
y_ref = [
6.6747328233649218e+08, 3.5519299354458244e+14,
3.4599104054580338e+14, 3.3821165110278112e+14
]
np.testing.assert_array_equal(x, x_ref)
np.testing.assert_array_equal(y, y_ref)
def test_evaluate_reaction_rate(self):
""" Tests evaluating reaction rate utility code.
"""
# Load the reference
res = results.read_results("test/test_reference.h5")
x, y = utilities.evaluate_reaction_rate(res, "1", "Xe135", "(n,gamma)")
x_ref = [0.0, 1296000.0, 2592000.0, 3888000.0]
xe_ref = np.array([
6.6747328233649218e+08, 3.5519326338509556e+14,
3.5965291907016744e+14, 3.3660528631036400e+14
])
r_ref = np.array([
4.0643678160858948e-05, 3.7482633215418289e-05,
3.6235405850442806e-05, 3.7149949868282194e-05
])
np.testing.assert_array_equal(x, x_ref)
np.testing.assert_array_equal(y, xe_ref * r_ref)
def test_evaluate_reaction_rate(self):
""" Tests evaluating reaction rate utility code.
"""
# Load the reference
res = results.read_results("test/test_reference.h5")
x, y = utilities.evaluate_reaction_rate(res, "1", "Xe135", "(n,gamma)")
x_ref = [0.0, 1296000.0, 2592000.0, 3888000.0]
xe_ref = np.array([
6.6747328233649218e+08, 3.5519299354458244e+14,
3.4599104054580338e+14, 3.3821165110278112e+14
])
r_ref = np.array([
4.0643598574337784e-05, 4.1457730544386974e-05,
3.4121248544056681e-05, 3.9204686657643301e-05
])
np.testing.assert_array_equal(x, x_ref)
np.testing.assert_array_equal(y, xe_ref * r_ref)
def test_full(self):
"""
This test runs a complete OpenMC simulation and tests the outputs.
It will take a while.
"""
n_rings = 2
n_wedges = 4
# Load geometry from example
geometry, lower_left, upper_right = \
example_geometry.generate_problem(n_rings=n_rings, n_wedges=n_wedges)
# Create dt vector for 3 steps with 15 day timesteps
dt1 = 15 * 24 * 60 * 60 # 15 days
dt2 = 1.5 * 30 * 24 * 60 * 60 # 1.5 months
N = np.floor(dt2 / dt1)
dt = np.repeat([dt1], N)
# Create settings variable
settings = opendeplete.OpenMCSettings()
settings.chain_file = "chains/chain_simple.xml"
settings.openmc_call = "openmc"
settings.openmc_npernode = 2
settings.particles = 100
settings.batches = 100
settings.inactive = 40
settings.lower_left = lower_left
settings.upper_right = upper_right
settings.entropy_dimension = [10, 10, 1]
settings.round_number = True
settings.constant_seed = 1
joule_per_mev = 1.6021766208e-13
settings.power = 2.337e15 * 4 * joule_per_mev # MeV/second cm from CASMO
settings.dt_vec = dt
settings.output_dir = "test_full"
op = opendeplete.OpenMCOperator(geometry, settings)
# Perform simulation using the predictor algorithm
opendeplete.integrator.predictor(op)
# Load the files
res_test = results.read_results(settings.output_dir + "/results.h5")
# Load the reference
res_old = results.read_results("test/test_reference.h5")
# Assert same mats
for mat in res_old[0].mat_to_ind:
self.assertIn(mat,
res_test[0].mat_to_ind,
msg="Cell " + mat + " not in new results.")
for nuc in res_old[0].nuc_to_ind:
self.assertIn(nuc,
res_test[0].nuc_to_ind,
msg="Nuclide " + nuc + " not in new results.")
for mat in res_test[0].mat_to_ind:
self.assertIn(mat,
res_old[0].mat_to_ind,
msg="Cell " + mat + " not in old results.")
for nuc in res_test[0].nuc_to_ind:
self.assertIn(nuc,
res_old[0].nuc_to_ind,
msg="Nuclide " + nuc + " not in old results.")
for mat in res_test[0].mat_to_ind:
for nuc in res_test[0].nuc_to_ind:
_, y_test = utilities.evaluate_single_nuclide(
res_test, mat, nuc)
_, y_old = utilities.evaluate_single_nuclide(res_old, mat, nuc)
# Test each point
tol = 1.0e-6
correct = True
for i, ref in enumerate(y_old):
if ref != y_test[i]:
if ref != 0.0:
if np.abs(y_test[i] - ref) / ref > tol:
correct = False
else:
correct = False
self.assertTrue(correct,
msg="Discrepancy in mat " + mat + " and nuc " +
nuc + "\n" + str(y_old) + "\n" + str(y_test))
def test_save_results(self):
""" Test data save module """
stages = 3
comm = MPI.COMM_WORLD
np.random.seed(comm.rank)
# Mock geometry
op = MagicMock()
vol_dict = {}
full_burn_dict = {}
j = 0
for i in range(comm.size):
vol_dict[str(2 * i)] = 1.2
vol_dict[str(2 * i + 1)] = 1.2
full_burn_dict[str(2 * i)] = j
full_burn_dict[str(2 * i + 1)] = j + 1
j += 2
burn_list = [str(i) for i in range(2 * comm.rank, 2 * comm.rank + 2)]
nuc_list = ["na", "nb"]
op.get_results_info.return_value = vol_dict, nuc_list, burn_list, full_burn_dict
# Construct x
x1 = []
x2 = []
for i in range(stages):
x1.append([np.random.rand(2), np.random.rand(2)])
x2.append([np.random.rand(2), np.random.rand(2)])
# Construct r
cell_dict = {s: i for i, s in enumerate(burn_list)}
r1 = ReactionRates(cell_dict, {"na": 0, "nb": 1}, {"ra": 0, "rb": 1})
r1.rates = np.random.rand(2, 2, 2)
rate1 = []
rate2 = []
for i in range(stages):
rate1.append(copy.deepcopy(r1))
r1.rates = np.random.rand(2, 2, 2)
rate2.append(copy.deepcopy(r1))
r1.rates = np.random.rand(2, 2, 2)
# Create global terms
eigvl1 = np.random.rand(stages)
eigvl2 = np.random.rand(stages)
seed1 = [np.random.randint(100) for i in range(stages)]
seed2 = [np.random.randint(100) for i in range(stages)]
eigvl1 = comm.bcast(eigvl1, root=0)
eigvl2 = comm.bcast(eigvl2, root=0)
seed1 = comm.bcast(seed1, root=0)
seed2 = comm.bcast(seed2, root=0)
t1 = [0.0, 1.0]
t2 = [1.0, 2.0]
integrator.save_results(op, x1, rate1, eigvl1, seed1, t1, 0)
integrator.save_results(op, x2, rate2, eigvl2, seed2, t2, 1)
# Load the files
res = results.read_results("results.h5")
for i in range(stages):
for mat_i, mat in enumerate(burn_list):
for nuc_i, nuc in enumerate(nuc_list):
self.assertEqual(res[0][i, mat, nuc], x1[i][mat_i][nuc_i])
self.assertEqual(res[1][i, mat, nuc], x2[i][mat_i][nuc_i])
np.testing.assert_array_equal(res[0].rates[i][mat, nuc, :],
rate1[i][mat, nuc, :])
np.testing.assert_array_equal(res[1].rates[i][mat, nuc, :],
rate2[i][mat, nuc, :])
np.testing.assert_array_equal(res[0].k, eigvl1)
np.testing.assert_array_equal(res[0].seeds, seed1)
np.testing.assert_array_equal(res[0].time, t1)
np.testing.assert_array_equal(res[1].k, eigvl2)
np.testing.assert_array_equal(res[1].seeds, seed2)
np.testing.assert_array_equal(res[1].time, t2)
# Delete files
MPI.COMM_WORLD.barrier()
if MPI.COMM_WORLD.rank == 0:
os.remove("results.h5")