def data():
result, _ = compute_figure_data(nr=default_nr,
GC_max=default_GC_max,
psi_coord=x_id(),
grid_layouts=grid_layout_set,
opt_set=opt_set)
return result
def compute_figure_data(*,
nr,
GC_max,
psi_coord=x_id(),
grid_layouts=(x_id(), x_p2(), x_log_of_pn(n=1)),
opt_set=({
'n_iters': 1
}, ),
mixing_ratios_g_kg=default_mixing_ratios_g_kg):
setup = Setup(nr=nr, mixing_ratios_g_kg=mixing_ratios_g_kg)
with parallel_backend('threading', n_jobs=-2):
results = Parallel(verbose=10)(
delayed(analysis)(setup, grid_layout, psi_coord, options, GC_max)
for grid_layout in grid_layouts for options in deepcopy(opt_set))
cases = {}
for result in results:
case = Case(result)
if case.grid_layour_str not in cases:
cases[case.grid_layour_str] = case
def make_data(setup, grid, opts):
options = Options(**opts)
simulation = Simulation(setup=setup,
grid_layout=grid,
psi_coord=x_id(),
opts=options,
GC_max=default_GC_max)
result = {"wall_time": []}
last_step = 0
for n_steps in simulation.out_steps:
steps = n_steps - last_step
wall_time_per_timestep = simulation.step(steps)
last_step += steps
result['wall_time'].append(wall_time_per_timestep)
return result
from MPyDATA_examples.Olesik_et_al_2020.physics.East_and_Marshall_1954 import SizeDistribution
from MPyDATA.arakawa_c.discretisation import discretised_analytical_solution
import pint
from matplotlib import pyplot
import numpy as np
from MPyDATA_examples.Olesik_et_al_2020.coordinates import x_id, x_log_of_pn, x_p2
import pytest
def diff(x):
return np.diff(x.magnitude) * x.units
@pytest.mark.parametrize("grid", [x_id(), x_log_of_pn(r0=1), x_p2()])
@pytest.mark.parametrize("coord", [x_id(), x_log_of_pn(r0=1), x_p2()])
def test_size_distribution(grid, coord, plot=False):
# Arrange
si = pint.UnitRegistry()
sd = SizeDistribution(si)
n_unit = si.centimetres**-3 / si.micrometre
r_unit = si.micrometre
# Act
x = grid.x(np.linspace(1, 18, 100)) * r_unit
dx_dr = coord.dx_dr
numpdfx = x[1:] - diff(x) / 2
pdf_t = lambda r: sd.pdf(r * r_unit).to(n_unit).magnitude / dx_dr(
r * r_unit).magnitude
numpdfy = discretised_analytical_solution(rh=x.magnitude,
pdf_t=pdf_t) * n_unit
from MPyDATA_examples.Olesik_et_al_2020.simulation import Simulation
from MPyDATA_examples.Olesik_et_al_2020.setup import Setup, default_nr, default_GC_max
from MPyDATA_examples.Olesik_et_al_2020.coordinates import x_id, x_log_of_pn, x_p2
from MPyDATA_examples.Olesik_et_al_2020.analysis import compute_figure_data
from MPyDATA.options import Options
import pytest
import numpy as np
setup = Setup()
grid_layout_set = (x_id(), x_p2(), x_log_of_pn(r0=1, n=1))
opt_set = ({
'n_iters': 1
}, {
'n_iters': 2,
'flux_corrected_transport': True
}, {
'n_iters': 3,
'third_order_terms': True,
'infinite_gauge': True,
'flux_corrected_transport': True
})
@pytest.fixture(scope='module')
def data():
result, _ = compute_figure_data(nr=default_nr,
GC_max=default_GC_max,
psi_coord=x_id(),
grid_layouts=grid_layout_set,
opt_set=opt_set)
return result
from MPyDATA_examples.Olesik_et_al_2020.coordinates import x_id, x_log_of_pn, x_p2
import pint
import pytest
si = pint.UnitRegistry()
@pytest.mark.parametrize("k", [0, 1, 2, 3])
@pytest.mark.parametrize(
"coord", [x_id(), x_log_of_pn(r0=1 * si.um, n=1),
x_p2()])
def test_moment_of_r_integral(k, coord):
# Arrange
r0 = 2 * si.um
r1 = 4 * si.um
# Act
integral = coord.moment_of_r_integral(
coord.x(r1), k) - coord.moment_of_r_integral(coord.x(r0), k)
# Assert
if coord.__class__ == x_id:
assert integral.check(f'[length]**{k+1}')
elif coord.__class__ == x_p2:
assert integral.check(f'[length]**{k+2}')
elif coord.__class__ == x_log_of_pn:
assert integral.check(f'[length]**{k}')
from MPyDATA_examples.Olesik_et_al_2020.simulation import Simulation
from MPyDATA_examples.Olesik_et_al_2020.setup import Setup, default_nr, default_GC_max
from MPyDATA_examples.Olesik_et_al_2020.coordinates import x_id, x_log_of_pn, x_p2
from MPyDATA_examples.Olesik_et_al_2020.analysis import compute_figure_data
from MPyDATA.options import Options
import pytest
import numpy as np
grid_layout_set = (x_id(), x_p2(), x_log_of_pn(n=1))
opt_set = (
{'n_iters': 1},
{'n_iters': 2, 'flux_corrected_transport': True},
{'n_iters': 3, 'third_order_terms': True, 'infinite_gauge': True, 'flux_corrected_transport': True}
)
@pytest.fixture(scope='module')
def data():
result, _ = compute_figure_data(nr=default_nr, GC_max=default_GC_max, psi_coord=x_id(),
grid_layouts=grid_layout_set,
opt_set=opt_set)
return result
@pytest.mark.parametrize("psi_coord", [x_id(), x_p2(), x_log_of_pn(n=1)])
@pytest.mark.parametrize("grid_layout", [x_id(), x_p2(), x_log_of_pn(n=3)])
@pytest.mark.parametrize("flux_corrected_transport", [False, True])
def test_init(grid_layout, psi_coord, flux_corrected_transport):
# Arrange
opts = Options(flux_corrected_transport=flux_corrected_transport)
setup = Setup()