def test_spin_up(plot=False):
# Arrange
Setup.n_steps = 20
Setup.outfreq = 1
setup = Setup()
for key in setup.processes.keys():
setup.processes[key] = False
setup.processes["condensation"] = True
setup.processes["fluid advection"] = True
storage = DummyStorage()
simulation = Simulation(setup, storage)
simulation.reinit()
# Act
simulation.run()
# Plot
if plot:
levels = np.arange(setup.grid[1])
for step, datum in storage.profiles.items():
pyplot.plot(datum["qv"], levels, label=str(step))
pyplot.legend()
pyplot.show()
# Assert
step_num = len(storage.profiles) - 1
for step in range(step_num):
next = storage.profiles[step + Setup.outfreq]["qv"]
prev = storage.profiles[step]["qv"]
eps = 1e-5
assert ((prev + eps) >= next).all()
assert storage.profiles[step_num]["qv"][-1] < 7.
def test_environment(plot=False):
# Arrange
setup = Setup()
setup.n_steps = -1
simulation = Simulation(setup, None)
simulation.reinit()
# Act
simulation.run()
rhod = setup.backend.to_ndarray(simulation.particles.environment["rhod"]).reshape(setup.grid)
# Plot
if plot:
fig, ax = pyplot.subplots(1, 1)
plotter.image(ax, rhod, setup.size, label='rho_d [kg/m^3]')
pyplot.show()
# Assert - same in all columns
for column in range(setup.grid[0]):
np.testing.assert_array_equal(
rhod[column, :], rhod[0, :]
)
# Assert - decreasing with altitude
rhod_below = 2 * si.kilograms / si.metre**3
for level in range(setup.grid[1]):
rhod_above = rhod[0, level]
assert rhod_above < rhod_below
rhod_below = rhod_above
def test_single_timestep():
# Arrange
setup = Setup()
setup.n_steps = 1
simulation = Simulation(setup, DummyStorage())
simulation.reinit()
# Act
simulation.run()
def test_single_timestep():
# Arrange
Setup.n_steps = 1
Setup.outfreq = 1
setup = Setup()
for key in setup.processes.keys():
setup.processes[key] = True
setup.processes["condensation"] = True
setup.processes["relaxation"] = False
simulation = Simulation(setup, DummyStorage())
simulation.reinit()
# Act
simulation.run()
def test_export():
# Arrange
setup = Setup()
setup.n_steps = 1
setup.outfreq = 1
storage = Storage()
simulator = Simulation(setup, storage)
sut = netCDF(storage, setup, simulator)
controller = DummyController()
simulator.reinit()
simulator.run(controller)
# Act
sut.run(controller=controller)
def main():
setup = Setup()
setup.grid = (75, 75)
setup.steps = [1] + list(range(10, 100, 10)) #[100, 3600]
setup.processes = {
"advection": True,
"coalescence": True,
"condensation": True
}
setup.condensation_dt_max = .2
n_sd = range(50, 51, 10)
times = {}
for parallel in (False, ):
PySDM.backends.numba.conf.NUMBA_PARALLEL = parallel
reload_backend()
for method in ('local', ):
key = f"{method} (parallel={parallel})"
times[key] = []
for sd in n_sd:
setup.n_sd_per_gridbox = sd
storage = Storage()
simulation = Simulation(setup, storage)
# simulation.particles.croupier = method
stats = simulation.run()
times[key].append(stats.wall_times[-1])
from matplotlib import pyplot as plt
for method, t in times.items():
plt.plot(n_sd, t, label=method)
plt.legend()
plt.loglog()
plt.show()
def main():
with np.errstate(all='ignore'):
setup = Setup()
setup.n_sd_per_gridbox = 25
setup.grid = (25, 25)
setup.processes["coalescence"] = True
setup.processes["condensation"] = True
setup.condensation_rtol_lnv = 1e-8
setup.condensation_rtol_thd = 1e-8
setup.mpdata_iters = 2
storage = Storage()
simulation = Simulation(setup, storage)
simulation.reinit()
simulation.run()
def test_environment():
# Arrange
setup = Setup()
setup.n_steps = -1
simulation = Simulation(setup, None)
simulation.reinit()
# Act
simulation.run()
rhod = simulation.core.environment["rhod"].to_ndarray().reshape(setup.grid)
# Assert - same in all columns
for column in range(setup.grid[0]):
np.testing.assert_array_equal(rhod[column, :], rhod[0, :])
# Assert - decreasing with altitude
rhod_below = 2 * si.kilograms / si.metre**3
for level in range(setup.grid[1]):
rhod_above = rhod[0, level]
assert rhod_above < rhod_below
rhod_below = rhod_above
def test_initialisation(plot=False):
# TODO: seed as a part of setup?
setup = Setup()
setup.n_steps = -1
setup.grid = (10, 5)
setup.n_sd_per_gridbox = 2000
simulation = Simulation(setup, None)
n_bins = 32
n_levels = setup.grid[1]
n_cell = np.prod(np.array(setup.grid))
n_moments = 1
v_bins = np.logspace((np.log10(phys.volume(radius=setup.r_min))),
(np.log10(phys.volume(radius=10 * setup.r_max))),
num=n_bins,
endpoint=True)
r_bins = phys.radius(volume=v_bins)
histogram_dry = np.empty((len(r_bins) - 1, n_levels))
histogram_wet = np.empty_like(histogram_dry)
moment_0 = setup.backend.array(n_cell, dtype=int)
moments = setup.backend.array((n_moments, n_cell), dtype=float)
tmp = np.empty(n_cell)
simulation.reinit()
# Act (moments)
simulation.run()
particles = simulation.particles
environment = simulation.particles.environment
rhod = setup.backend.to_ndarray(environment["rhod"]).reshape(
setup.grid).mean(axis=0)
for i in range(len(histogram_dry)):
particles.state.moments(moment_0,
moments,
specs={},
attr_name='dry volume',
attr_range=(v_bins[i], v_bins[i + 1]))
particles.backend.download(moment_0, tmp)
histogram_dry[i, :] = tmp.reshape(
setup.grid).sum(axis=0) / (particles.mesh.dv * setup.grid[0])
particles.state.moments(moment_0,
moments,
specs={},
attr_name='volume',
attr_range=(v_bins[i], v_bins[i + 1]))
particles.backend.download(moment_0, tmp)
histogram_wet[i, :] = tmp.reshape(
setup.grid).sum(axis=0) / (particles.mesh.dv * setup.grid[0])
# Plot
if plot:
for level in range(0, n_levels):
color = str(.5 * (2 + (level / (n_levels - 1))))
pyplot.step(r_bins[:-1] * si.metres / si.micrometres,
histogram_dry[:, level] / si.metre**3 *
si.centimetre**3,
where='post',
color=color,
label="level " + str(level))
pyplot.step(r_bins[:-1] * si.metres / si.micrometres,
histogram_wet[:, level] / si.metre**3 *
si.centimetre**3,
where='post',
color=color,
linestyle='--')
pyplot.grid()
pyplot.xscale('log')
pyplot.xlabel('particle radius [µm]')
pyplot.ylabel('concentration per bin [cm^{-3}]')
pyplot.legend()
pyplot.show()
# Assert - location of maximum
for level in range(n_levels):
real_max = setup.spectrum_per_mass_of_dry_air.distribution_params[2]
idx_max_dry = np.argmax(histogram_dry[:, level])
idx_max_wet = np.argmax(histogram_wet[:, level])
assert r_bins[idx_max_dry] < real_max < r_bins[idx_max_dry + 1]
assert idx_max_dry < idx_max_wet
# Assert - total number
for level in reversed(range(n_levels)):
mass_conc_dry = np.sum(histogram_dry[:, level]) / rhod[level]
mass_conc_wet = np.sum(histogram_wet[:, level]) / rhod[level]
mass_conc_STP = setup.spectrum_per_mass_of_dry_air.norm_factor
assert .5 * mass_conc_STP < mass_conc_dry < 1.5 * mass_conc_STP
np.testing.assert_approx_equal(mass_conc_dry, mass_conc_wet)
# Assert - decreasing number density
total_above = 0
for level in reversed(range(n_levels)):
total_below = np.sum(histogram_dry[:, level])
assert total_below > total_above
total_above = total_below