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mypy errors - added some dummy variables to test_exposure_model.py

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This commit is contained in:
Luis Aleixo 2021-07-26 14:16:51 +02:00
parent 5983fca92e
commit 1803d4e919
1 changed files with 20 additions and 12 deletions
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32
cara/tests/models/test_exposure_model.py
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@ -17,10 +17,6 @@ class KnownConcentrations(models.ConcentrationModel):
which therefore doesn't need other components. Useful for testing.
"""
#def __init__(self, concentration_function: typing.Callable) -> None:
# self._func = concentration_function
concentration_function: typing.Callable
def infectious_virus_removal_rate(self, time: float) -> models._VectorisedFloat:
@ -58,23 +54,35 @@ populations = [
models.Activity(np.array([0.51,0.57]), 0.57),
),
]
dummyRoom = models.Room(50, 0.5)
dummyVentilation = models._VentilationBase()
dummyInfPopulation = models.InfectedPopulation(
number=1,
presence=halftime,
mask=models.Mask.types['Type I'],
activity=models.Activity.types['Standing'],
virus=models.Virus.types['SARS_CoV_2_B117'],
expiration=models.Expiration.types['Talking']
)
def known_concentrations(func):
return KnownConcentrations(dummyRoom, dummyVentilation, dummyInfPopulation, func)
@pytest.mark.parametrize(
"population, cm, f_dep, expected_exposure, expected_cumulated_exposure, expected_probability",[
[populations[1], KnownConcentrations(None, None, None, lambda t: 1.2), 1.,
[populations[1], known_concentrations(lambda t: 1.2), 1.,
np.array([14.4, 14.4]), np.array([3.44736/0.6, 3.20112/0.6]), np.array([99.6803184113, 99.5181053773])],
[populations[2], KnownConcentrations(None, None, None, lambda t: 1.2), 1.,
[populations[2], known_concentrations(lambda t: 1.2), 1.,
np.array([14.4, 14.4]), np.array([2.2032/0.6, 2.4624/0.6]), np.array([97.4574432074, 98.3493482895])],
[populations[0], KnownConcentrations(None, None, None,lambda t: np.array([1.2, 2.4])), 1.,
[populations[0], known_concentrations(lambda t: np.array([1.2, 2.4])), 1.,
np.array([14.4, 28.8]), np.array([2.4624/0.6, 4.9248/0.6]), np.array([98.3493482895, 99.9727534893])],
[populations[1], KnownConcentrations(None, None, None,lambda t: np.array([1.2, 2.4])), 1.,
[populations[1], known_concentrations(lambda t: np.array([1.2, 2.4])), 1.,
np.array([14.4, 28.8]), np.array([3.44736/0.6, 6.40224/0.6]), np.array([99.6803184113, 99.9976777757])],
[populations[0], KnownConcentrations(None, None, None,lambda t: 2.4), np.array([0.5, 1.]),
[populations[0], known_concentrations(lambda t: 2.4), np.array([0.5, 1.]),
28.8, np.array([4.104, 8.208]), np.array([98.3493482895, 99.9727534893])],
])
def test_exposure_model_ndarray(population, cm, f_dep,
@ -100,7 +108,7 @@ def test_exposure_model_ndarray(population, cm, f_dep,
@pytest.mark.parametrize("population", populations)
def test_exposure_model_ndarray_and_float_mix(population):
cm = KnownConcentrations(None, None, None, lambda t: 0 if np.floor(t) % 2 else np.array([1.2, 1.2]))
cm = known_concentrations(lambda t: 0 if np.floor(t) % 2 else np.array([1.2, 1.2]))
model = ExposureModel(cm, population)
expected_exposure = np.array([14.4, 14.4])
@ -114,8 +122,8 @@ def test_exposure_model_ndarray_and_float_mix(population):
@pytest.mark.parametrize("population", populations)
def test_exposure_model_compare_scalar_vector(population):
cm_scalar = KnownConcentrations(None, None, None,lambda t: 1.2)
cm_array = KnownConcentrations(None, None, None, lambda t: np.array([1.2, 1.2]))
cm_scalar = known_concentrations(lambda t: 1.2)
cm_array = known_concentrations(lambda t: np.array([1.2, 1.2]))
model_scalar = ExposureModel(cm_scalar, population)
model_array = ExposureModel(cm_array, population)
expected_exposure = 14.4