def _test_dump_diags(self, dim, **simInput):
test_id = self.ddt_test_id()
for key in ["cells", "dl", "boundary_types"]:
simInput[key] = [simInput[key] for d in range(dim)]
for interp in range(1, 4):
local_out = f"{out}_dim{dim}_interp{interp}_mpi_n_{cpp.mpi_size()}_id{test_id}"
simInput["diag_options"]["options"]["dir"] = local_out
simulation = ph.Simulation(**simInput)
self.assertTrue(len(simulation.cells) == dim)
dump_all_diags(setup_model().populations)
self.simulator = Simulator(
simulation).initialize().advance().reset()
self.assertTrue(
any([
diagInfo.quantity.endswith("tags")
for diagInfo in ph.global_vars.sim.diagnostics
]))
checks = 0
found = 0
for diagInfo in ph.global_vars.sim.diagnostics:
h5_filepath = os.path.join(local_out,
h5_filename_from(diagInfo))
self.assertTrue(os.path.exists(h5_filepath))
h5_file = h5py.File(h5_filepath, "r")
self.assertTrue("0.0000000000"
in h5_file[h5_time_grp_key]) # init dump
n_patches = len(
list(h5_file[h5_time_grp_key]["0.0000000000"]
["pl0"].keys()))
if h5_filepath.endswith("tags.h5"):
found = 1
hier = hierarchy_from(h5_filename=h5_filepath)
patches = hier.level(0).patches
tag_found = 0
for patch in patches:
self.assertTrue(len(patch.patch_datas.items()))
for qty_name, pd in patch.patch_datas.items():
self.assertTrue((pd.dataset[:] >= 0).all())
self.assertTrue((pd.dataset[:] < 2).all())
tag_found |= (pd.dataset[:] == 1).any()
checks += 1
self.assertEqual(found, 1)
self.assertEqual(tag_found, 1)
self.assertEqual(checks, n_patches)
self.simulator = None
ph.global_vars.sim = None
def _test_dump_diags(self, dim, **simInput):
test_id = self.ddt_test_id()
# configure simulation dim sized values
for key in ["cells", "dl", "boundary_types"]:
simInput[key] = [simInput[key] for d in range(dim)]
b0 = [[10 for i in range(dim)], [19 for i in range(dim)]]
simInput["refinement_boxes"] = {"L0": {"B0": b0}}
for interp in range(1, 4):
print("_test_dump_diags dim/interp:{}/{}".format(dim, interp))
local_out = f"{out}_dim{dim}_interp{interp}_mpi_n_{cpp.mpi_size()}_id{test_id}"
simInput["diag_options"]["options"]["dir"] = local_out
simulation = ph.Simulation(**simInput)
self.assertTrue(len(simulation.cells) == dim)
dump_all_diags(setup_model().populations)
self.simulator = Simulator(simulation).initialize().advance()
for diagInfo in ph.global_vars.sim.diagnostics:
# diagInfo.quantity starts with a / this interferes with os.path.join, hence [1:]
h5_filename = os.path.join(local_out, (diagInfo.quantity + ".h5").replace('/', '_')[1:])
print("h5_filename", h5_filename)
h5_file = h5py.File(h5_filename, "r")
self.assertTrue("t0.000000" in h5_file) # init dump
self.assertTrue("t0.000100" in h5_file)
self.assertTrue("pl1" in h5_file["t0.000100"])
self.assertFalse("pl0" in h5_file["t0.000100"])
self.assertTrue("t0.001000" in h5_file) # advance dump
# SEE https://github.com/PHAREHUB/PHARE/issues/275
if dim == 1: # REMOVE WHEN PHARESEE SUPPORTS 2D
self.assertTrue(os.path.exists(h5_filename))
hier = hierarchy_from(h5_filename=h5_filename)
if h5_filename.endswith("domain.h5"):
for patch in hier.level(0).patches:
for qty_name, pd in patch.patch_datas.items():
splits = pd.dataset.split(ph.global_vars.sim)
self.assertTrue(splits.size() == pd.dataset.size() * 2)
print("splits.iCell", splits.iCells)
print("splits.delta", splits.deltas)
print("splits.weight", splits.weights)
print("splits.charge", splits.charges)
print("splits.v", splits.v)
self.simulator = None
ph.global_vars.sim = None
def dup(dic):
dic = NoOverwriteDict(dic)
dic.update(diags.copy())
dic.update(
{"diags_fn": lambda model: dump_all_diags(model.populations)})
return dic
def test_twice_register(self):
simulation = ph.Simulation(**simArgs.copy())
model = setup_model()
dump_all_diags(model.populations) # first register
self.assertRaises(RuntimeError, dump_all_diags, model.populations)
def _test_dump_diags(self, dim, **simInput):
test_id = self.ddt_test_id()
# configure simulation dim sized values
for key in ["cells", "dl", "boundary_types"]:
simInput[key] = [simInput[key] for d in range(dim)]
b0 = [[10 for i in range(dim)], [19 for i in range(dim)]]
simInput["refinement_boxes"] = {"L0": {"B0": b0}}
py_attrs = [
f"{dep}_version" for dep in ["samrai", "highfive", "pybind"]
]
py_attrs += ["git_hash"]
for interp in range(1, 4):
print("test_dump_diags dim/interp:{}/{}".format(dim, interp))
local_out = f"{out}_dim{dim}_interp{interp}_mpi_n_{cpp.mpi_size()}_id{test_id}"
simInput["diag_options"]["options"]["dir"] = local_out
simulation = ph.Simulation(**simInput)
self.assertTrue(len(simulation.cells) == dim)
dump_all_diags(setup_model().populations)
self.simulator = Simulator(
simulation).initialize().advance().reset()
refined_particle_nbr = simulation.refined_particle_nbr
self.assertTrue(
any([
diagInfo.quantity.endswith("domain")
for diagInfo in ph.global_vars.sim.diagnostics
]))
particle_files = 0
for diagInfo in ph.global_vars.sim.diagnostics:
h5_filepath = os.path.join(local_out,
h5_filename_from(diagInfo))
self.assertTrue(os.path.exists(h5_filepath))
h5_file = h5py.File(h5_filepath, "r")
self.assertTrue("0.0000000000"
in h5_file[h5_time_grp_key]) # init dump
self.assertTrue(
"0.0010000000"
in h5_file[h5_time_grp_key]) # first advance dump
h5_py_attrs = h5_file["py_attrs"].attrs.keys()
for py_attr in py_attrs:
self.assertIn(py_attr, h5_py_attrs)
hier = hierarchy_from(h5_filename=h5_filepath)
if h5_filepath.endswith("domain.h5"):
particle_files += 1
self.assertTrue("pop_mass" in h5_file.attrs)
if "protons" in h5_filepath:
self.assertTrue(h5_file.attrs["pop_mass"] == 1)
elif "alpha" in h5_filepath:
self.assertTrue(h5_file.attrs["pop_mass"] == 4)
else:
raise RuntimeError("Unknown population")
self.assertGreater(len(hier.level(0).patches), 0)
for patch in hier.level(0).patches:
self.assertTrue(len(patch.patch_datas.items()))
for qty_name, pd in patch.patch_datas.items():
splits = pd.dataset.split(ph.global_vars.sim)
self.assertTrue(splits.size() > 0)
self.assertTrue(pd.dataset.size() > 0)
self.assertTrue(
splits.size() == pd.dataset.size() *
refined_particle_nbr)
self.assertEqual(particle_files,
ph.global_vars.sim.model.nbr_populations())
self.simulator = None
ph.global_vars.sim = None
def test_restarts(self, dim, interp, simInput):
print(f"test_restarts dim/interp:{dim}/{interp}")
simput = copy.deepcopy(simInput)
for key in ["cells", "dl", "boundary_types"]:
simput[key] = [simput[key]] * dim
if "refinement" not in simput:
b0 = [[10 for i in range(dim)], [19 for i in range(dim)]]
simput["refinement_boxes"] = {"L0": {"B0": b0}}
else: # https://github.com/LLNL/SAMRAI/issues/199
# tagging can handle more than one timestep as it does not
# appear subject to regridding issues, so we make more timesteps
# to confirm simulations are still equivalent
simput["time_step_nbr"] = 10
# if restart time exists it "loads" from restart file
# otherwise just saves restart files based on timestamps
assert "restart_time" not in simput["restart_options"]
simput["interp_order"] = interp
time_step = simput["time_step"]
time_step_nbr = simput["time_step_nbr"]
restart_idx = 4
restart_time = time_step * restart_idx
timestamps = [time_step * restart_idx, time_step * time_step_nbr]
# first simulation
local_out = f"{out}/test/{dim}/{interp}/mpi_n/{cpp.mpi_size()}/id{self.ddt_test_id()}"
simput["restart_options"]["dir"] = local_out
simput["diag_options"]["options"]["dir"] = local_out
ph.global_vars.sim = None
ph.global_vars.sim = ph.Simulation(**simput)
assert "restart_time" not in ph.global_vars.sim.restart_options
model = setup_model()
dump_all_diags(model.populations, timestamps=np.array(timestamps))
Simulator(ph.global_vars.sim).run().reset()
self.register_diag_dir_for_cleanup(local_out)
diag_dir0 = local_out
# second restarted simulation
local_out = f"{local_out}_n2"
simput["diag_options"]["options"]["dir"] = local_out
simput["restart_options"]["restart_time"] = restart_time
ph.global_vars.sim = None
ph.global_vars.sim = ph.Simulation(**simput)
assert "restart_time" in ph.global_vars.sim.restart_options
model = setup_model()
dump_all_diags(model.populations, timestamps=np.array(timestamps))
Simulator(ph.global_vars.sim).run().reset()
self.register_diag_dir_for_cleanup(local_out)
diag_dir1 = local_out
def check(qty0, qty1, checker):
checks = 0
for ilvl, lvl0 in qty0.patch_levels.items():
patch_level1 = qty1.patch_levels[ilvl]
for p_idx, patch0 in enumerate(lvl0):
patch1 = patch_level1.patches[p_idx]
for pd_key, pd0 in patch0.patch_datas.items():
pd1 = patch1.patch_datas[pd_key]
self.assertNotEqual(id(pd0), id(pd1))
checker(pd0, pd1)
checks += 1
return checks
def check_particles(qty0, qty1):
return check(
qty0, qty1,
lambda pd0, pd1: self.assertEqual(pd0.dataset, pd1.dataset))
def check_field(qty0, qty1):
return check(
qty0, qty1, lambda pd0, pd1: np.testing.assert_equal(
pd0.dataset[:], pd1.dataset[:]))
def count_levels_and_patches(qty):
n_levels = len(qty.patch_levels)
n_patches = 0
for ilvl, lvl in qty.patch_levels.items():
n_patches += len(qty.patch_levels[ilvl].patches)
return n_levels, n_patches
n_quantities_per_patch = 20
pops = model.populations
for time in timestamps:
checks = 0
run0 = Run(diag_dir0)
run1 = Run(diag_dir1)
checks += check_particles(run0.GetParticles(time, pops),
run1.GetParticles(time, pops))
checks += check_field(run0.GetB(time), run1.GetB(time))
checks += check_field(run0.GetE(time), run1.GetE(time))
checks += check_field(run0.GetNi(time), run1.GetNi(time))
checks += check_field(run0.GetVi(time), run1.GetVi(time))
for pop in pops:
checks += check_field(run0.GetFlux(time, pop),
run1.GetFlux(time, pop))
checks += check_field(run0.GetN(time, pop),
run1.GetN(time, pop))
n_levels, n_patches = count_levels_and_patches(run0.GetB(time))
self.assertEqual(n_levels, 2) # at least 2 levels
self.assertGreaterEqual(n_patches,
n_levels) # at least one patch per level
self.assertEqual(checks, n_quantities_per_patch * n_patches)
