def test_underflow(self):
np.seterr(all='raise') # TODO: use with construct
norm_factor = 1e10
scale = 1e-13
sut = Exponential(norm_factor, scale)
x = 5e-10
value = sut.size_distribution(x)
assert value != 0
def test_size_distribution_n_part(self, scale):
# Arrange
scale = 1
n_part = 256
sut = Exponential(n_part, scale)
# Act
m, dm = np.linspace(0, 5, 10000, retstep=True)
sd = sut.size_distribution(m)
# Assert
assert_approx_equal(np.sum(sd) * dm, n_part, 2)
def test_coalescence():
# TODO: np.random.RandomState in backend?
# Arrange
v_min = 4.186e-15
v_max = 4.186e-12
n_sd = 2**13
steps = [0, 30, 60]
X0 = 4 / 3 * 3.14 * 30.531e-6**3
n_part = 2**23 # [m-3]
dv = 1e6 # [m3]
dt = 1 # [s]
norm_factor = n_part * dv
kernel = Golovin(b=1.5e3) # [s-1]
spectrum = Exponential(norm_factor=norm_factor, scale=X0)
particles = Particles(n_sd=n_sd, dt=dt, backend=backend)
particles.set_mesh_0d(dv=dv)
particles.set_environment(Box, {})
v, n = constant_multiplicity(n_sd, spectrum, (v_min, v_max))
particles.create_state_0d(n=n, extensive={'volume': v}, intensive={})
particles.add_dynamic(SDM, {"kernel": kernel})
states = {}
# Act
for step in steps:
particles.run(step - particles.n_steps)
states[particles.n_steps] = copy.deepcopy(particles.state)
# Assert
x_max = 0
for state in states.values():
assert x_max < state.max('volume')
x_max = state.max('volume')
class SetupA:
x_min = phys.volume(radius=10 * si.micrometres) # not given in the paper
x_max = phys.volume(radius=100 * si.micrometres) # not given in the paper
n_sd = 2 ** 13
n_part = 2 ** 23 / si.metre**3
X0 = 4 / 3 * np.pi * 30.531e-6 ** 3
dv = 1e6 * si.metres**3
norm_factor = n_part * dv
rho = 1000 * si.kilogram / si.metre**3
dt = 1 * si.seconds
seed = 44
steps = [0, 1200, 2400, 3600]
kernel = Golovin(b=1.5e3 / si.second)
spectrum = Exponential(norm_factor=norm_factor, scale=X0)
backend = Default
# TODO: rename?
# TODO: as backend method?
def check(self, state, step):
check_LWC = 1e-3 * si.kilogram / si.metre**3
check_ksi = self.n_part * self.dv / self.n_sd
# multiplicities
if step == 0:
np.testing.assert_approx_equal(np.amin(state['n']), np.amax(state['n']), 1)
np.testing.assert_approx_equal(state['n'][0], check_ksi, 1)
# liquid water content
LWC = self.rho * np.dot(state['n'], state['volume']) / self.dv
np.testing.assert_approx_equal(LWC, check_LWC, 3)