def test_at_t_0(spectral_sampling, plot=False):
# Arrange
settings = Settings(n_sd=64, dt=1 * si.s, n_substep=1, spectral_sampling=spectral_sampling)
settings.t_max = 0
simulation = Simulation(settings)
# Act
output = simulation.run()
# Plot
if plot:
from matplotlib import pyplot
pyplot.step(
2e6 * settings.dry_radius_bins_edges[:-1],
output['dm_S_VI/dlog_10(dry diameter)'][-1]
)
pyplot.ylabel('dS(VI)/dlog_10(D)')
pyplot.xlabel('dry diameter [µm]')
pyplot.xscale('log')
pyplot.yscale('log')
pyplot.ylim([.01, 12])
pyplot.show()
# Assert
key = 'S_VI'
spectrum = output[f'dm_{key}/dlog_10(dry diameter)'][0][0]
peaks, props = find_peaks(spectrum)
assert len(peaks) == 1
assert 3 < np.amax(spectrum) < 5
def test_at_cloud_base():
# Arrange
settings = Settings(n_sd=50, dt=1 * si.s, n_substep=5)
settings.t_max = 196 * si.s
settings.output_interval = settings.dt
simulation = Simulation(settings)
# Act
output = simulation.run()
# Assert
assert round(output['z'][-1]) == (698 - 600) * si.m
np.testing.assert_allclose(output['p_env'][-1],
939 * si.mbar,
rtol=.005)
np.testing.assert_allclose(output['T_env'][-1],
284.2 * si.K,
rtol=.005)
np.testing.assert_allclose(
settings.formulae.state_variable_triplet.rho_of_rhod_qv(
rhod=output['rhod_env'][-1],
qv=output['qv_env'][-1] * si.g / si.kg),
1.15 * si.kg / si.m**3,
rtol=.005)
assert output['ql'][-2] < .00055
assert output['ql'][-1] > .0004
assert output['RH_env'][-1] > 100
assert output['RH_env'][-8] < 100
def test_at_t_0(spectral_sampling, plot=False):
# Arrange
settings = Settings(n_sd=64,
dt=1 * si.s,
n_substep=5,
spectral_sampling=spectral_sampling)
settings.t_max = 0
simulation = Simulation(settings)
# Act
output = simulation.run()
# Plot
if plot:
from matplotlib import pyplot
pyplot.step(2e6 * settings.dry_radius_bins_edges[:-1],
output['dm_S_VI/dlog_10(dry diameter)'][-1])
pyplot.ylabel('dS(VI)/dlog_10(D)')
pyplot.xlabel('dry diameter [µm]')
pyplot.xscale('log')
pyplot.yscale('log')
pyplot.ylim([.01, 12])
pyplot.show()
# Assert
key = 'S_VI'
# TODO #481 : better than >0 (we do have analytic formula)
assert (output[f'dm_{key}/dlog_10(dry diameter)'][0] > 0).any()
def test_at_1200m_above_cloud_base():
# Arrange
settings = Settings(n_sd=10, dt=1 * si.s, n_substep=5)
simulation = Simulation(settings)
# Act
output = simulation.run()
# Assert
np.testing.assert_allclose(output['z'][-1], (1.2 + .1) * si.km,
rtol=.005)
np.testing.assert_allclose(output['ql'][-1], 2.17, rtol=.02)
def test_at_t_0():
# Arrange
settings = Settings(n_sd=100, dt=1 * si.s, n_substep=5)
settings.t_max = 0
simulation = Simulation(settings)
specific_gravities = SpecificGravities(
simulation.particulator.formulae.constants)
# Act
output = simulation.run()
# Assert
np.testing.assert_allclose(output['RH'][0], 95)
np.testing.assert_allclose(output['gas_S_IV_ppb'][0], 0.2)
np.testing.assert_allclose(output['gas_N_mIII_ppb'][0], 0.1)
np.testing.assert_allclose(output['gas_H2O2_ppb'], 0.5)
np.testing.assert_allclose(output['gas_N_V_ppb'], 0.1)
np.testing.assert_allclose(output['gas_O3_ppb'], 50)
np.testing.assert_allclose(output['gas_C_IV_ppb'], 360 * 1000)
rtol = 0.15
mass_conc_SO4mm = 2
mass_conc_NH4p = 0.375
num_conc_SO4mm = mass_conc_SO4mm / Substance.from_formula(
"SO4").mass * si.gram / si.mole
num_conc_NH4p = mass_conc_NH4p / Substance.from_formula(
"NH4").mass * si.gram / si.mole
np.testing.assert_allclose(num_conc_NH4p, num_conc_SO4mm, rtol=.005)
mass_conc_H = num_conc_NH4p * Substance.from_formula(
"H").mass * si.gram / si.mole
np.testing.assert_allclose(
actual=np.asarray(output['q_dry']) * np.asarray(output['rhod']),
desired=mass_conc_NH4p + mass_conc_SO4mm + mass_conc_H,
rtol=rtol)
expected = {k: 0 for k in AQUEOUS_COMPOUNDS}
expected['S_VI'] = mass_conc_SO4mm * si.ug / si.m**3
expected['N_mIII'] = mass_conc_NH4p * si.ug / si.m**3
for key in expected:
mole_fraction = np.asarray(output[f"aq_{key}_ppb"])
convert_to(mole_fraction, 1 / PPB)
compound = AQUEOUS_COMPOUNDS[key][0] # sic!
np.testing.assert_allclose(
actual=(settings.formulae.trivia.mole_fraction_2_mixing_ratio(
mole_fraction,
specific_gravity=specific_gravities[compound]) *
np.asarray(output['rhod'])),
desired=expected[key],
rtol=rtol)
def example_output():
settings = Settings(n_sd=16, dt=1 * si.s, n_substep=5)
simulation = Simulation(settings)
output = simulation.run()
return output
def test_calc_ionic_strength(nt, n_sd):
formulae = Formulae()
const = formulae.constants
EQUILIBRIUM_CONST = EquilibriumConsts(formulae).EQUILIBRIUM_CONST
K = _K(NH3=EQUILIBRIUM_CONST["K_NH3"].at(const.ROOM_TEMP),
SO2=EQUILIBRIUM_CONST["K_SO2"].at(const.ROOM_TEMP),
HSO3=EQUILIBRIUM_CONST["K_HSO3"].at(const.ROOM_TEMP),
HSO4=EQUILIBRIUM_CONST["K_HSO4"].at(const.ROOM_TEMP),
HCO3=EQUILIBRIUM_CONST["K_HCO3"].at(const.ROOM_TEMP),
CO2=EQUILIBRIUM_CONST["K_CO2"].at(const.ROOM_TEMP),
HNO3=EQUILIBRIUM_CONST["K_HNO3"].at(const.ROOM_TEMP))
settings = Settings(dt=1, n_sd=n_sd, n_substep=5)
settings.t_max = nt * settings.dt
simulation = Simulation(settings)
simulation.run()
H = simulation.particulator.attributes['conc_N_mIII'].data
conc = {
'H+': H,
'N-3': simulation.particulator.attributes['conc_N_mIII'].data,
'N+5': simulation.particulator.attributes['conc_N_V'].data,
'S+4': simulation.particulator.attributes['conc_S_IV'].data,
'S+6': simulation.particulator.attributes['conc_S_VI'].data,
'C+4': simulation.particulator.attributes['conc_C_IV'].data,
}
alpha_C = (1 + K.CO2 / conc['H+'] + K.CO2 * K.HCO3 / conc['H+']**2)
alpha_S = (1 + K.SO2 / conc['H+'] + K.SO2 * K.HSO3 / conc['H+']**2)
alpha_N3 = (1 + conc['H+'] * K.NH3 / K_H2O)
alpha_N5 = (1 + K.HNO3 / conc['H+'])
actual = calc_ionic_strength(H=conc['H+'],
conc=_conc(
N_mIII=conc['N-3'],
N_V=conc['N+5'],
C_IV=conc['C+4'],
S_IV=conc['S+4'],
S_VI=conc['S+6'],
),
K=K)
expected = ionic_strength(
{
'H+':
conc['H+'] / const.rho_w,
'HCO3-':
K.CO2 / conc['H+'] * conc['C+4'] / alpha_C / const.rho_w,
'CO3-2':
K.CO2 / conc['H+'] * K.HCO3 / conc['H+'] * conc['C+4'] / alpha_C /
const.rho_w,
'HSO3-':
K.SO2 / conc['H+'] * conc['S+4'] / alpha_S / const.rho_w,
'SO3-2':
K.SO2 / conc['H+'] * K.HSO3 / conc['H+'] * conc['S+4'] / alpha_S /
const.rho_w,
'NH4+':
K.NH3 / K_H2O * conc['H+'] * conc['N-3'] / alpha_N3 / const.rho_w,
'NO3-':
K.HNO3 / conc['H+'] * conc['N+5'] / alpha_N5 / const.rho_w,
'HSO4-':
conc['H+'] * conc['S+6'] / (conc['H+'] + K.HSO4) / const.rho_w,
'SO4-2':
K.HSO4 * conc['S+6'] / (conc['H+'] + K.HSO4) / const.rho_w,
'OH-':
K_H2O / conc['H+'] / const.rho_w
},
warn=False) * const.rho_w
np.testing.assert_allclose(actual, expected, rtol=1e-15)
def test_calc_ionic_strength(nt, n_sd):
formulae = Formulae()
EQUILIBRIUM_CONST = EquilibriumConsts(formulae).EQUILIBRIUM_CONST
K_NH3 = EQUILIBRIUM_CONST["K_NH3"].at(ROOM_TEMP)
K_SO2 = EQUILIBRIUM_CONST["K_SO2"].at(ROOM_TEMP)
K_HSO3 = EQUILIBRIUM_CONST["K_HSO3"].at(ROOM_TEMP)
K_HSO4 = EQUILIBRIUM_CONST["K_HSO4"].at(ROOM_TEMP)
K_HCO3 = EQUILIBRIUM_CONST["K_HCO3"].at(ROOM_TEMP)
K_CO2 = EQUILIBRIUM_CONST["K_CO2"].at(ROOM_TEMP)
K_HNO3 = EQUILIBRIUM_CONST["K_HNO3"].at(ROOM_TEMP)
settings = Settings(dt=1, n_sd=n_sd, n_substep=5)
settings.t_max = nt * settings.dt
simulation = Simulation(settings)
simulation.run()
H = simulation.core.particles['conc_N_mIII'].data
conc = {
'H+': H,
'N-3': simulation.core.particles['conc_N_mIII'].data,
'N+5': simulation.core.particles['conc_N_V'].data,
'S+4': simulation.core.particles['conc_S_IV'].data,
'S+6': simulation.core.particles['conc_S_VI'].data,
'C+4': simulation.core.particles['conc_C_IV'].data,
}
alpha_C = (1 + K_CO2 / conc['H+'] + K_CO2 * K_HCO3 / conc['H+']**2)
alpha_S = (1 + K_SO2 / conc['H+'] + K_SO2 * K_HSO3 / conc['H+']**2)
alpha_N3 = (1 + conc['H+'] * K_NH3 / K_H2O)
alpha_N5 = (1 + K_HNO3 / conc['H+'])
actual = calc_ionic_strength(H=conc['H+'],
N_mIII=conc['N-3'],
N_V=conc['N+5'],
C_IV=conc['C+4'],
S_IV=conc['S+4'],
S_VI=conc['S+6'],
K_NH3=K_NH3,
K_SO2=K_SO2,
K_HSO3=K_HSO3,
K_HSO4=K_HSO4,
K_HCO3=K_HCO3,
K_CO2=K_CO2,
K_HNO3=K_HNO3)
expected = ionic_strength(
{
'H+':
conc['H+'] / rho_w,
'HCO3-':
K_CO2 / conc['H+'] * conc['C+4'] / alpha_C / rho_w,
'CO3-2':
K_CO2 / conc['H+'] * K_HCO3 / conc['H+'] * conc['C+4'] / alpha_C /
rho_w,
'HSO3-':
K_SO2 / conc['H+'] * conc['S+4'] / alpha_S / rho_w,
'SO3-2':
K_SO2 / conc['H+'] * K_HSO3 / conc['H+'] * conc['S+4'] / alpha_S /
rho_w,
'NH4+':
K_NH3 / K_H2O * conc['H+'] * conc['N-3'] / alpha_N3 / rho_w,
'NO3-':
K_HNO3 / conc['H+'] * conc['N+5'] / alpha_N5 / rho_w,
'HSO4-':
conc['H+'] * conc['S+6'] / (conc['H+'] + K_HSO4) / rho_w,
'SO4-2':
K_HSO4 * conc['S+6'] / (conc['H+'] + K_HSO4) / rho_w,
'OH-':
K_H2O / conc['H+'] / rho_w
},
warn=False) * rho_w
np.testing.assert_allclose(actual, expected, rtol=1e-15)
def test_calc_ionic_strength(nt, n_sd):
from chempy.electrolytes import ionic_strength
from PySDM_examples.Kreidenweis_et_al_2003 import Settings, Simulation
from PySDM.backends.numba.impl._chemistry_methods import calc_ionic_strength
from PySDM.physics.constants import rho_w, ROOM_TEMP
K_NH3 = EQUILIBRIUM_CONST["K_NH3"].at(ROOM_TEMP)
K_SO2 = EQUILIBRIUM_CONST["K_SO2"].at(ROOM_TEMP)
K_HSO3 = EQUILIBRIUM_CONST["K_HSO3"].at(ROOM_TEMP)
K_HSO4 = EQUILIBRIUM_CONST["K_HSO4"].at(ROOM_TEMP)
K_HCO3 = EQUILIBRIUM_CONST["K_HCO3"].at(ROOM_TEMP)
K_CO2 = EQUILIBRIUM_CONST["K_CO2"].at(ROOM_TEMP)
K_HNO3 = EQUILIBRIUM_CONST["K_HNO3"].at(ROOM_TEMP)
settings = Settings(dt=1, n_sd=n_sd, n_substep=5)
settings.t_max = nt * settings.dt
simulation = Simulation(settings)
simulation.run()
H = simulation.core.particles['conc_N_mIII'].data
conc = {
'H+': H,
'N-3': simulation.core.particles['conc_N_mIII'].data,
'N+5': simulation.core.particles['conc_N_V'].data,
'S+4': simulation.core.particles['conc_S_IV'].data,
'S+6': simulation.core.particles['conc_S_VI'].data,
'C+4': simulation.core.particles['conc_C_IV'].data,
}
alpha_C = (1 + K_CO2 / conc['H+'] + K_CO2 * K_HCO3 / conc['H+']**2)
alpha_S = (1 + K_SO2 / conc['H+'] + K_SO2 * K_HSO3 / conc['H+']**2)
alpha_N3 = (1 + conc['H+'] * K_NH3 / K_H2O)
alpha_N5 = (1 + K_HNO3 / conc['H+'])
actual = calc_ionic_strength(H=conc['H+'],
N_mIII=conc['N-3'],
N_V=conc['N+5'],
C_IV=conc['C+4'],
S_IV=conc['S+4'],
S_VI=conc['S+6'],
K_NH3=K_NH3,
K_SO2=K_SO2,
K_HSO3=K_HSO3,
K_HSO4=K_HSO4,
K_HCO3=K_HCO3,
K_CO2=K_CO2,
K_HNO3=K_HNO3)
expected = ionic_strength(
{
'H+':
conc['H+'] / rho_w,
'HCO3-':
K_CO2 / conc['H+'] * conc['C+4'] / alpha_C / rho_w,
'CO3-2':
K_CO2 / conc['H+'] * K_HCO3 / conc['H+'] * conc['C+4'] /
alpha_C / rho_w,
'HSO3-':
K_SO2 / conc['H+'] * conc['S+4'] / alpha_S / rho_w,
'SO3-2':
K_SO2 / conc['H+'] * K_HSO3 / conc['H+'] * conc['S+4'] /
alpha_S / rho_w,
'NH4+':
K_NH3 / K_H2O * conc['H+'] * conc['N-3'] / alpha_N3 / rho_w,
'NO3-':
K_HNO3 / conc['H+'] * conc['N+5'] / alpha_N5 / rho_w,
'HSO4-':
conc['H+'] * conc['S+6'] / (conc['H+'] + K_HSO4) / rho_w,
'SO4-2':
K_HSO4 * conc['S+6'] / (conc['H+'] + K_HSO4) / rho_w,
'OH-':
K_H2O / conc['H+'] / rho_w
},
warn=False) * rho_w
np.testing.assert_allclose(actual, expected, rtol=1e-15)