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Changed short range distance distribution to lognormal

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This commit is contained in:
Luis Aleixo 2022-03-22 14:52:50 +01:00
parent 75a7b75496
commit 2165c71bf5
3 changed files with 15 additions and 14 deletions
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2
cara/apps/calculator/model_generator.py
View file

@ -250,7 +250,7 @@ class FormData:
sr_presence=self.short_range_intervals()
sr_activities=self.short_range_activities()
short_range_expirations = tuple(short_range_expiration_distributions[activity] for activity in sr_activities)
dilutions=dilution_factor(activities=sr_activities, distance=np.random.uniform(0.5, 1.5, 250000))
dilutions=dilution_factor(activities=sr_activities)
else:
sr_presence=()
short_range_expirations=()

8
cara/monte_carlo/data.py
View file

@ -5,7 +5,7 @@ import numpy as np
from scipy import special as sp
import cara.monte_carlo as mc
from cara.monte_carlo.sampleable import Normal,LogNormal,LogCustomKernel,CustomKernel,Uniform
from cara.monte_carlo.sampleable import LogNormal,LogCustomKernel,CustomKernel,Uniform
sqrt2pi = np.sqrt(2.*np.pi)
@ -182,7 +182,11 @@ def expiration_distribution(
)
def dilution_factor(activities, distance, D=0.02):
def dilution_factor(activities):
D = 0.02
# From https://www.mdpi.com/1660-4601/17/4/1445/htm
distance = LogNormal(0.8542127255693238, 0.42755967248106513).generate_samples(250_000)
factors = []
for activity in activities:
u0 = 0.98 if activity == "Breathing" else 3.9

19
cara/tests/models/test_short_range_model.py
View file

@ -47,10 +47,7 @@ def expirations(presences) -> typing.Tuple[mc_models.Expiration, ...]:
@pytest.fixture
def dilutions(presences):
return dilution_factor(
activities=[activity for (activity, presence) in presences],
distance=np.random.uniform(0.5, 1.5, 250_000),
)
return dilution_factor(activities=[activity for (activity, presence) in presences])
def test_short_range_model_ndarray(concentration_model, presences, expirations, dilutions):
@ -64,9 +61,9 @@ def test_short_range_model_ndarray(concentration_model, presences, expirations,
@pytest.mark.parametrize(
"start, stop, expected_exposure", [
[8.5, 12.5, 5.844666077067048e-09],
[10.5, 11.0, 5.830120846251791e-09],
[10.6, 11.9, 4.6397748633454945e-09],
[8.5, 12.5, 5.963061627547172e-10],
[10.5, 11.0, 5.934552264225482e-10],
[10.6, 11.9, 4.709684623109963e-10],
]
)
def test_normed_exposure_between_bounds(
@ -76,15 +73,15 @@ def test_normed_exposure_between_bounds(
model = mc_models.ShortRangeModel(presences, expirations, dilutions)
model = model.build_model(250_000)
np.testing.assert_almost_equal(
model.normed_exposure_between_bounds(concentration_model, start, stop).mean(), expected_exposure
model.normed_exposure_between_bounds(concentration_model, start, stop).mean(), expected_exposure, decimal=10
)
@pytest.mark.parametrize(
"time, expected_sr_normed_concentration, expected_concentration", [
[10.75, 1.1670056689678455e-08, 11.67005668967846],
# [14.75, 3.6414877020308386e-06, 3641.4877020308395],
# [16.75, 1.973757599365769e-05, 19737.57599365769],
[10.75, 1.1670056689678455e-08, 1.1731466540816526],
# [14.75, 3.6414877020308386e-06, 474.36376505412574],
# [16.75, 1.973757599365769e-05, 2850.6219623225024],
]
)
def test_short_range_model(