def test_fake_numba():
# Arrange
sut = DimensionalAnalysis()
# Act & Assert
assert hasattr(Formulae().saturation_vapour_pressure.pvs_Celsius,
"py_func")
with sut:
assert not hasattr(
Formulae().saturation_vapour_pressure.pvs_Celsius, "py_func")
assert hasattr(Formulae().saturation_vapour_pressure.pvs_Celsius,
"py_func")
def __init__(self,
w_avg: float,
N_STP: float,
r_dry: float,
mass_of_dry_air: float,
coord: str = 'VolumeLogarithm'):
self.formulae = Formulae(
saturation_vapour_pressure='AugustRocheMagnus',
condensation_coordinate=coord)
self.p0 = 1000 * si.hectopascals
self.RH0 = .98
self.kappa = .2 # TODO #441
self.T0 = 300 * si.kelvin
self.z_half = 150 * si.metres
pvs = self.formulae.saturation_vapour_pressure.pvs_Celsius(self.T0 -
const.T0)
self.q0 = const.eps / (self.p0 / self.RH0 / pvs - 1)
self.w_avg = w_avg
self.r_dry = r_dry
self.N_STP = N_STP
self.n_in_dv = N_STP / const.rho_STP * mass_of_dry_air
self.mass_of_dry_air = mass_of_dry_air
self.n_output = 500
self.rtol_x = condensation.default_rtol_x
self.rtol_thd = condensation.default_rtol_thd
self.coord = 'volume logarithm'
self.dt_cond_range = condensation.default_cond_range
def test___str__():
# Arrange
sut = Formulae()
# Act
result = str(sut)
# Assert
assert len(result) > 0
def __init__(self, backend, n_sd=0, formulae=None):
if formulae is None:
formulae = Formulae()
Core.__init__(self, n_sd, backend(formulae))
self.core = self
self.environment = DummyEnvironment()
self.environment.register(self)
self.req_attr = {'n': Multiplicities(self), 'cell id': CellID(self)}
self.particles = None
def __init__(self, n_sd, backend, formulae=Formulae()):
assert inspect.isclass(backend)
self.formulae = formulae
self.core = Core(n_sd, backend(formulae))
self.req_attr = {
'n': Multiplicities(self),
'volume': Volume(self),
'cell id': CellID(self)
}
self.aerosol_radius_threshold = 0
self.condensation_params = None
def test_pvs():
with DimensionalAnalysis():
# Arrange
formulae = Formulae()
si = constants.si
sut = formulae.saturation_vapour_pressure.pvs_Celsius
T = 300 * si.kelvins
# Act
pvs = sut(T)
# Assert
assert pvs.units == si.hectopascals
def test_analytic_solution_underflow(x):
# Arrange
formulae = Formulae()
b = 1.5e3
x_0 = formulae.trivia.volume(radius=30.531e-6)
N_0 = 2 ** 23
sut = Golovin(b)
# Act
value = sut.analytic_solution(x=x, t=1200, x_0=x_0, N_0=N_0)
# Assert
assert np.all(np.isfinite(value))
def test_lv():
with DimensionalAnalysis():
# Arrange
si = constants.si
T = 300 * si.kelvins
formulae = Formulae()
sut = formulae.latent_heat.lv
# Act
latent_heat = sut(T)
# Assert
assert latent_heat.check('[energy]/[mass]')
def test_r_cr():
with DimensionalAnalysis():
# Arrange
si = constants.si
formulae = Formulae()
sut = formulae.hygroscopicity.r_cr
kp = .5
rd = .1 * si.micrometre
T = 300 * si.kelvins
sgm = constants.sgm
# Act
r_cr = sut(kp, rd**3, T, sgm)
# Assert
assert r_cr.to_base_units().units == si.metres
def __init__(self, settings, backend=CPU):
dt_output = settings.total_time / settings.n_steps # TODO #334 overwritten in jupyter example
self.n_substeps = 1 # TODO #334 use condensation substeps
while (dt_output / self.n_substeps >= settings.dt_max):
self.n_substeps += 1
self.formulae = Formulae(condensation_coordinate=settings.coord, saturation_vapour_pressure='AugustRocheMagnus')
self.bins_edges = self.formulae.trivia.volume(settings.r_bins_edges)
builder = Builder(backend=backend, n_sd=settings.n_sd, formulae=self.formulae)
builder.set_environment(Parcel(
dt=dt_output / self.n_substeps,
mass_of_dry_air=settings.mass_of_dry_air,
p0=settings.p0,
q0=settings.q0,
T0=settings.T0,
w=settings.w,
z0=settings.z0
))
environment = builder.core.environment
builder.add_dynamic(AmbientThermodynamics())
condensation = Condensation(
kappa=settings.kappa,
adaptive=settings.adaptive,
rtol_x=settings.rtol_x,
rtol_thd=settings.rtol_thd,
dt_cond_range=settings.dt_cond_range
)
builder.add_dynamic(condensation)
products = [
PySDM_products.ParticlesWetSizeSpectrum(v_bins=self.formulae.trivia.volume(settings.r_bins_edges)),
PySDM_products.CondensationTimestepMin(),
PySDM_products.CondensationTimestepMax(),
PySDM_products.RipeningRate()
]
attributes = environment.init_attributes(
n_in_dv=settings.n,
kappa=settings.kappa,
r_dry=settings.r_dry
)
self.core = builder.build(attributes, products)
self.n_steps = settings.n_steps
def test_toms748(fun):
sut = toms748_solve if 'NUMBA_DISABLE_JIT' in os.environ else toms748_solve.py_func
a = -.5
b = .5
rtol = 1e-6
wt = Formulae().trivia.within_tolerance
actual, iters = sut(f2, (),
ax=a,
bx=b,
fax=f2(a),
fbx=f2(b),
max_iter=10,
rtol=rtol,
within_tolerance=wt)
expected = toms748(f2, a, b)
np.testing.assert_almost_equal(actual, expected)
def test_coalescence(backend, croupier, adaptive):
if backend == ThrustRTC and croupier == 'local': # TODO #358
return
if backend == ThrustRTC and adaptive and croupier == 'global': # TODO #329
return
# Arrange
formulae = Formulae(seed=256)
n_sd = 2**14
steps = [0, 100, 200]
X0 = formulae.trivia.volume(radius=30.531e-6)
n_part = 2**23 / si.metre**3
dv = 1e6 * si.metres**3
dt = 1 * si.seconds
norm_factor = n_part * dv
rho = 1000 * si.kilogram / si.metre**3
kernel = Golovin(b=1.5e3) # [s-1]
spectrum = Exponential(norm_factor=norm_factor, scale=X0)
builder = Builder(n_sd=n_sd, backend=backend(formulae=formulae))
builder.set_environment(Box(dt=dt, dv=dv))
attributes = {}
attributes['volume'], attributes['n'] = ConstantMultiplicity(
spectrum).sample(n_sd)
builder.add_dynamic(
Coalescence(kernel, croupier=croupier, adaptive=adaptive))
particulator = builder.build(attributes)
volumes = {}
# Act
for step in steps:
particulator.run(step - particulator.n_steps)
check(n_part, dv, n_sd, rho, particulator.attributes, step)
volumes[particulator.
n_steps] = particulator.attributes['volume'].to_ndarray()
# Assert
x_max = 0
for volume in volumes.values():
assert x_max < np.amax(volume)
x_max = np.amax(volume)
def test_equilibrate_pH_non_trivial(init_conc, env_T):
equilibria = {
'water':
Equilibrium.from_string(f"H2O = H+ + OH-; {K_H2O / M / M}"),
'ammonia':
Equilibrium.from_string(
f"NH3 + H2O = NH4+ + OH-; {EQUILIBRIUM_CONST['K_NH3'].at(env_T) / M}"
),
'sulfonic_first':
Equilibrium.from_string(
f"H2SO3(aq) = H+ + HSO3-; {EQUILIBRIUM_CONST['K_SO2'].at(env_T) / M}"
),
'sulfonic_second':
Equilibrium.from_string(
f"HSO3- = H+ + SO3-2; {EQUILIBRIUM_CONST['K_HSO3'].at(env_T) / M}"
),
'carbonic_first':
Equilibrium.from_string(
f"H2CO3(aq) = H+ + HCO3-; {EQUILIBRIUM_CONST['K_CO2'].at(env_T) / M}"
),
'carbonic_second':
Equilibrium.from_string(
f"HCO3- = H+ + CO3-2; {EQUILIBRIUM_CONST['K_HCO3'].at(env_T) / M}"
)
}
substances = [
Species.from_formula(f) for f in
'H2O OH- H+ NH3 NH4+ H2CO3(aq) HCO3- CO3-2 H2SO3(aq) HSO3- SO3-2'.
split()
]
eqsys = EqSystem(equilibria.values(), substances)
x, sol, sane = eqsys.root(init_conc)
assert sol['success'] and sane
H_idx = 2
assert substances[H_idx].name == 'H+'
expected_pH = -np.log10(x[H_idx])
eqs = {}
for key in EQUILIBRIUM_CONST.keys():
eqs[key] = np.full(1, EQUILIBRIUM_CONST[key].at(env_T))
actual_pH = np.empty(1)
formulae = Formulae()
ChemistryMethods.equilibrate_H_body(
within_tolerance=formulae.trivia.within_tolerance,
pH2H=formulae.trivia.pH2H,
H2pH=formulae.trivia.H2pH,
N_mIII=np.full(1, init_conc['NH3'] * 1e3),
N_V=np.full(1, init_conc['HNO3(aq)'] * 1e3),
C_IV=np.full(1, init_conc['H2CO3(aq)'] * 1e3),
S_IV=np.full(1, init_conc['H2SO3(aq)'] * 1e3),
S_VI=np.full(1, init_conc['HSO4-'] * 1e3),
K_HNO3=eqs['K_HNO3'].data,
K_HCO3=eqs['K_HCO3'].data,
K_HSO3=eqs['K_HSO3'].data,
K_HSO4=eqs['K_HSO4'].data,
K_CO2=eqs['K_CO2'].data,
K_NH3=eqs['K_NH3'].data,
K_SO2=eqs['K_SO2'].data,
cell_id=np.zeros(1, dtype=int),
# output
do_chemistry_flag=np.empty(1),
pH=actual_pH,
# params
H_min=formulae.trivia.pH2H(aqueous_chemistry.default_pH_max),
H_max=formulae.trivia.pH2H(aqueous_chemistry.default_pH_min),
ionic_strength_threshold=aqueous_chemistry.
default_ionic_strength_threshold,
rtol=aqueous_chemistry.default_pH_rtol)
np.testing.assert_allclose(actual_pH[0], expected_pH, rtol=1e-5)
from PySDM.physics.aqueous_chemistry.support import M, EquilibriumConsts
from PySDM.physics.constants import ROOM_TEMP, K_H2O
from PySDM.physics.formulae import Formulae
from PySDM.backends.numba.impl._chemistry_methods import ChemistryMethods
from PySDM.dynamics import aqueous_chemistry
from chempy import Equilibrium
from chempy.equilibria import EqSystem
from chempy.chemistry import Species
import numpy as np
import pytest
from collections import defaultdict
formulae = Formulae()
EQUILIBRIUM_CONST = EquilibriumConsts(formulae).EQUILIBRIUM_CONST
class Test_pH:
@staticmethod
def test_equilibrate_pH_pure_water():
# Arrange
eqs = {}
for key in EQUILIBRIUM_CONST.keys():
eqs[key] = np.full(1, EQUILIBRIUM_CONST[key].at(ROOM_TEMP))
# Act
result = np.empty(1)
ChemistryMethods.equilibrate_H_body(
within_tolerance=formulae.trivia.within_tolerance,
pH2H=formulae.trivia.pH2H,
H2pH=formulae.trivia.H2pH,