class DataWranglerTest(unittest.TestCase):
def __init__(self, *args, **kwargs):
super(DataWranglerTest, self).__init__(*args, **kwargs)
self.dw = None
self.simulator = None
def test_1d(self):
for interp in range(1, 4):
self.simulator = Simulator(populate_simulation(1, interp))
self.simulator.initialize()
self.dw = self.simulator.data_wrangler()
print("\n", self.dw.lvl0IonDensity())
print("\n", self.dw.lvl0BulkVelocity())
print("\n", self.dw.lvl0PopDensity())
print("\n", self.dw.lvl0PopFluxes())
print("\n", self.dw.lvl0EM())
for pop, particles in self.dw.getPatchLevel(
0).getParticles().items():
for key, patches in particles.items():
for patch in patches:
self.assertTrue(isinstance(patch.lower, np.ndarray))
self.assertTrue(isinstance(patch.upper, np.ndarray))
self.simulator = None
def tearDown(self):
del self.dw
if self.simulator is not None:
self.simulator.reset()
class SimulatorRefinedParticleNbr(unittest.TestCase):
def __init__(self, *args, **kwargs):
super(SimulatorRefinedParticleNbr, self).__init__(*args, **kwargs)
with open(os.path.join(project_root, "res/amr/splitting.yml"), 'r') as stream:
try:
self.yaml_root = yaml.safe_load(stream)
except yaml.YAMLError as exc:
print(exc)
sys.exit(1)
# while splitting particles may leave the domain area
# so we remove the particles from the border cells of each patch
def _less_per_dim(self, dim, refined_particle_nbr, patch):
if dim == 1:
return refined_particle_nbr * 2
cellNbr = patch.upper - patch.lower + 1
if dim == 2:
return refined_particle_nbr * ((cellNbr[0] * 2 + (cellNbr[1] * 2)))
raise ValueError("Unhandled dimension for function")
def _check_deltas_and_weights(self, dim, interp, refined_particle_nbr):
yaml_dim = self.yaml_root["dimension_" + str(dim)]
yaml_interp = yaml_dim["interp_" + str(interp)]
yaml_n_particles = yaml_interp["N_particles_" + str(refined_particle_nbr)]
yaml_delta = [float(s) for s in str(yaml_n_particles["delta"]).split(" ")]
yaml_weight = [float(s) for s in str(yaml_n_particles["weight"]).split(" ")]
splitter_t = splitter_type(dim, interp, refined_particle_nbr)
np.testing.assert_allclose(yaml_delta, splitter_t.delta)
np.testing.assert_allclose(yaml_weight, splitter_t.weight)
def _do_dim(self, dim, min_diff, max_diff):
from pyphare.pharein.simulation import valid_refined_particle_nbr
for interp in range(1, 4):
prev_split_particle_max = 0
for refined_particle_nbr in valid_refined_particle_nbr[dim][interp]:
self._check_deltas_and_weights(dim, interp, refined_particle_nbr)
simInput = NoOverwriteDict({"refined_particle_nbr": refined_particle_nbr})
self.simulator = Simulator(populate_simulation(dim, interp, **simInput))
self.simulator.initialize()
dw = self.simulator.data_wrangler()
max_per_pop = 0
leaving_particles = 0
for pop, particles in dw.getPatchLevel(1).getParticles().items():
per_pop = 0
for key, patches in particles.items():
for patch in patches:
leaving_particles += self._less_per_dim(dim, refined_particle_nbr, patch)
per_pop += patch.data.size()
max_per_pop = max(max_per_pop, per_pop)
prev_min_diff = prev_split_particle_max * min_diff
# while splitting particles may leave the domain area
# so we remove the particles from the border cells of each patch
self.assertTrue(
max_per_pop > prev_min_diff - (leaving_particles)
)
if prev_split_particle_max > 0:
prev_max_diff = prev_min_diff * dim * max_diff
self.assertTrue(max_per_pop < prev_max_diff)
prev_split_particle_max = max_per_pop
self.simulator = None
""" 1d
refine 10 cells in 1d, ppc 100
10 * 2 * ppc = 200
10 * 3 * ppc = 300 300 / 200 = 1.5
10 * 4 * ppc = 400 500 / 400 = 1.33
10 * 5 * ppc = 500 500 / 400 = 1.25
taking the minimul diff across permutations
current to previous should be at least this times bigger
"""
PREVIOUS_ITERATION_MIN_DIFF_1d = 1.25
PREVIOUS_ITERATION_MAX_DIFF_1d = 1.50
def test_1d(self):
This = type(self)
self._do_dim(1, This.PREVIOUS_ITERATION_MIN_DIFF_1d, This.PREVIOUS_ITERATION_MAX_DIFF_1d)
""" 2d
refine 10x10 cells in 2d, ppc 100
10 * 10 * 4 * ppc = 400
10 * 10 * 8 * ppc = 800 800 / 400 = 1.5
10 * 10 * 9 * ppc = 900 900 / 800 = 1.125
"""
PREVIOUS_ITERATION_MIN_DIFF_2d = 1.125
PREVIOUS_ITERATION_MAX_DIFF_2d = 1.50
def test_2d(self):
This = type(self)
self._do_dim(2, This.PREVIOUS_ITERATION_MIN_DIFF_2d, This.PREVIOUS_ITERATION_MAX_DIFF_2d)
def tearDown(self):
# needed in case exception is raised in test and Simulator
# not reset properly
if self.simulator is not None:
self.simulator.reset()