Changed type of short range presence and added tests

cara/models.py

@@ -673,6 +673,7 @@ class Expiration(_ExpirationBase):
         return self.cn * (volume(self.diameter) *
                 (1 - mask.exhale_efficiency(self.diameter))) * 1e-12
 
+    @cached()
     def jet_origin_concentration(self):
         def volume(d):
             return (np.pi * d**3) / 6.
@@ -1075,7 +1076,7 @@ class ConcentrationModel:
 @dataclass(frozen=True)
 class ShortRangeModel:
     #: Short range interactions
-    presence: typing.List[Interval]
+    presence: typing.List[SpecificInterval]
 
     #: Expiration type
     expirations: typing.List[Expiration]

cara/tests/models/test_short_range_model.py

@@ -0,0 +1,78 @@
+import typing
+from unicodedata import decimal
+
+import numpy as np
+import pytest
+
+from cara import models
+from cara.models import ShortRangeModel
+from cara.apps.calculator.model_generator import build_expiration
+from cara.monte_carlo.data import dilution_factor, short_range_expiration_distributions
+
+
+@pytest.fixture
+def concentration_model():
+    return models.ConcentrationModel(
+        room=models.Room(volume=75),
+        ventilation=models.AirChange(
+            active=models.SpecificInterval(present_times=((8.5, 12.5), (13.5, 17.5))),
+            air_exch=30.,
+        ),
+        infected=models.InfectedPopulation(
+            number=1,
+            virus=models.Virus.types['SARS_CoV_2'],
+            presence=models.SpecificInterval(present_times=((8.5, 12.5), (13.5, 17.5))),
+            mask=models.Mask.types['No mask'],
+            activity=models.Activity.types['Light activity'],
+            expiration=build_expiration({'Speaking': 0.33, 'Breathing': 0.67}).build_model(250000),
+            host_immunity=0.,
+        ),
+        evaporation_factor=0.3,
+    )
+
+
+activities = ['Breathing', 'Speaking', 'Shouting']
+
+
+@pytest.fixture
+def presences():
+    return [models.SpecificInterval((10.5, 11.0)),
+        models.SpecificInterval((14.5, 15.0)),
+        models.SpecificInterval((16.5, 17.5)),]
+
+
+@pytest.fixture
+def expirations():
+    return [short_range_expiration_distributions[activity] for activity in activities]
+
+
+@pytest.fixture
+def dilutions():
+    return dilution_factor(activities=activities,
+                        distance=np.random.uniform(0.5, 1.5, 250000))
+
+
+def test_short_range_model_ndarray(concentration_model, presences, expirations, dilutions):
+    model = ShortRangeModel(presences, expirations, dilutions)
+    assert isinstance(model._normed_concentration(concentration_model, 10.75), np.ndarray)
+    assert isinstance(model.short_range_concentration(concentration_model, 14.75), np.ndarray)
+    assert isinstance(model.normed_exposure_between_bounds(concentration_model, 16.6, 17.7), np.ndarray) 
+
+
+@pytest.mark.parametrize(
+    "time, expected_sr_normed_concentration, expected_concentration", [
+        [10.75, 1.1066751695e-07, 110.66751695458098],
+        [14.75, 3.451543659539623e-07, 345.15431668253206],
+        [16.75, 3.433877350917482e-07, 343.38772746180666],
+    ]
+)
+def test_short_range_model(time, expected_sr_normed_concentration, expected_concentration, 
+                        concentration_model, presences, expirations, dilutions):
+    
+    model = ShortRangeModel(presences, expirations, dilutions)
+    np.testing.assert_almost_equal(
+        model._normed_concentration(concentration_model, time).mean(), expected_sr_normed_concentration
+    )
+    np.testing.assert_almost_equal(
+        model.short_range_concentration(concentration_model, time).mean(), expected_concentration, decimal=0
+    )