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Improve readability of tests; adding 2 end-to-end tests (on infection probability)

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This commit is contained in:
Nicolas Mounet 2020-11-09 18:32:56 +01:00
parent ddbfbf2631
commit 6dacddedbe
1 changed files with 42 additions and 8 deletions
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50
cara/tests/test_known_quantities.py
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@ -299,13 +299,20 @@ def test_windowopening(time, expected_value):
def build_hourly_dependent_model(month, intervals_open=((7.5, 8.5),),
intervals_presence_infected=((0, 4), (5, 7.5)),refine=False):
if refine:
times_refined = tuple(np.linspace(0.,24,241))
temperatures_refined = tuple(np.hstack([[v]*10 for v in data.GenevaTemperatures_hourly[month].values]))
outside_temp=models.PiecewiseConstant(times_refined,temperatures_refined)
intervals_presence_infected=((0, 4), (5, 7.5)),
artificial_refinement=False,
temperatures=data.GenevaTemperatures_hourly):
if artificial_refinement:
# 5-fold increase of number of times, WITHOUT interpolation
# (hence transparent for the results)
refine_factor = 2
times_refined = tuple(np.linspace(0.,24,
refine_factor*len(temperatures[month].values)+1))
temperatures_refined = tuple(np.hstack([[v]*refine_factor
for v in temperatures[month].values]))
outside_temp = models.PiecewiseConstant(times_refined,temperatures_refined)
else:
outside_temp=data.GenevaTemperatures_hourly[month]
outside_temp = temperatures[month]
model = models.Model(
room=models.Room(volume=75),
@ -435,11 +442,38 @@ def test_concentrations_hourly_dep_adding_artificial_transitions(month_temp_item
@pytest.mark.parametrize(
"time",
list(np.random.random_sample(20)*24.)+list(np.arange(0,24.5,0.5)),
list(np.random.random_sample(10)*24.)+list(np.arange(0,24.5,0.5)),
)
def test_concentrations_refine_times(time):
month = 'Jan'
m1 = build_hourly_dependent_model(month,intervals_open=((0, 24),))
m2 = build_hourly_dependent_model(month,intervals_open=((0, 24),),refine=True)
m2 = build_hourly_dependent_model(month,intervals_open=((0, 24),),
artificial_refinement=True)
npt.assert_allclose(m1.concentration(time), m2.concentration(time), rtol=1e-8)
@pytest.mark.parametrize(
"month, expected_r0",
[
['Jan', 91.06953],
['Jun', 99.46692],
],
)
def test_r0_hourly_dep(month,expected_r0):
m = build_hourly_dependent_model(month,intervals_open=((0,24),),
intervals_presence_infected=((8,12),(13,17)))
p = m.infection_probability()
npt.assert_allclose(p, expected_r0)
@pytest.mark.parametrize(
"month, expected_r0",
[
['Jan', 91.19912],
['Jun', 99.59226],
],
)
def test_r0_hourly_dep_refined(month,expected_r0):
m = build_hourly_dependent_model(month,intervals_open=((0,24),),
intervals_presence_infected=((8,12),(13,17)),
temperatures=data.GenevaTemperatures)
p = m.infection_probability()
npt.assert_allclose(p, expected_r0)