def data(n_output, rtols, schemes, setups_num):
resultant_data = {}
for scheme in schemes:
resultant_data[scheme] = {}
if scheme == 'BDF':
for rtol in rtols:
resultant_data[scheme][rtol] = []
for settings_idx in range(setups_num):
settings = setups[settings_idx]
settings.n_output = n_output
simulation = Simulation(settings)
bdf.patch_core(simulation.core)
results = simulation.run()
for rtol in rtols:
resultant_data[scheme][rtol].append(results)
else:
for rtol in rtols:
resultant_data[scheme][rtol] = []
for settings_idx in range(setups_num):
settings = setups[settings_idx]
settings.rtol_x = rtol
settings.rtol_thd = rtol
settings.n_output = n_output
simulation = Simulation(settings, backend=CPU if scheme=='CPU' else GPU)
results = simulation.run()
resultant_data[scheme][rtol].append(results)
return resultant_data
def test_water_mass_conservation(settings_idx, mass_of_dry_air, scheme, coord):
# Arrange
assert scheme in ('BDF', 'CPU', 'GPU')
settings = Settings(
w_avg=setups[settings_idx].w_avg,
N_STP=setups[settings_idx].N_STP,
r_dry=setups[settings_idx].r_dry,
mass_of_dry_air=mass_of_dry_air,
coord=coord
)
settings.n_output = 50
settings.coord = coord
simulation = Simulation(settings, GPU if scheme == 'GPU' else CPU)
qt0 = settings.q0 + ql(simulation)
if scheme == 'BDF':
bdf.patch_core(simulation.core)
# Act
simulation.core.products['S_max'].get()
output = simulation.run()
# Assert
qt = simulation.core.environment["qv"].to_ndarray() + ql(simulation)
significant = 6 if scheme == 'GPU' else 14 # TODO #540
np.testing.assert_approx_equal(qt, qt0, significant)
if scheme != 'BDF':
assert simulation.core.products['S_max'].get() >= output['S'][-1]
def test_just_do_it(backend, scheme, adaptive):
# Arrange
if scheme == 'BDF' and (not adaptive or backend is GPU):
return
settings = Settings(dt_output=10 * si.second)
settings.adaptive = adaptive
if scheme == 'BDF':
settings.dt_max = settings.dt_output # TODO #334 'BDF')
elif not adaptive:
settings.dt_max = 1 * si.second
simulation = Simulation(settings, backend)
if scheme == 'BDF':
bdf.patch_core(simulation.core)
# Act
output = simulation.run()
r = np.array(output['r']).T * si.metres
n = settings.n / (settings.mass_of_dry_air * si.kilogram)
# Assert
condition = (r > 1 * si.micrometre)
NTOT = n_tot(n, condition)
N1 = NTOT[:int(1 / 3 * len(NTOT))]
N2 = NTOT[int(1 / 3 * len(NTOT)):int(2 / 3 * len(NTOT))]
N3 = NTOT[int(2 / 3 * len(NTOT)):]
n_unit = 1 / si.microgram
assert min(N1) == 0.0 * n_unit
assert .6 * n_unit < max(N1) < .8 * n_unit
assert .17 * n_unit < min(N2) < .18 * n_unit
assert .35 * n_unit < max(N2) < .41 * n_unit
assert .1 * n_unit < min(N3) < .11 * n_unit
assert .27 * n_unit < max(N3) < .4 * n_unit
# TODO #527
if backend is not GPU:
assert max(output['ripening_rate']) > 0
def test_water_mass_conservation(settings_idx, mass_of_dry_air, scheme, coord):
# Arrange
settings = Settings(w_avg=setups[settings_idx].w_avg,
N_STP=setups[settings_idx].N_STP,
r_dry=setups[settings_idx].r_dry,
mass_of_dry_air=mass_of_dry_air,
coord=coord)
settings.n_output = 50
settings.coord = coord
simulation = Simulation(settings)
qt0 = settings.q0 + ql(simulation)
assert scheme in ('BDF', 'default')
if scheme == 'BDF':
bdf.patch_core(simulation.core)
# Act
simulation.run()
# Assert
qt = simulation.core.environment["qv"].to_ndarray() + ql(simulation)
np.testing.assert_approx_equal(qt, qt0, 14)