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Updated documentation and added a docstring to the newly created tests

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Luis Aleixo 2023-01-30 16:30:31 +01:00
parent eed3629dd5
commit 6197e3962f
2 changed files with 6 additions and 2 deletions
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4
caimira/docs/full_diameter_dependence.rst
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@ -314,8 +314,8 @@ CO\ :sub:`2` Concentration
The estimate of the concentration of CO\ :sub:`2` in a given room to indicate the air quality is given by the same approach as for the long-range virus concentration,
:math:`C_{\mathrm{LR}}(t, D)`, where :math:`C_0(D)` is considered to be the background (outdoor) CO\ :sub:`2` concentration (:meth:`caimira.models.CO2ConcentrationModel.CO2_atmosphere_concentration`).
Note that in order to calculate the CO\ :sub:`2` concentration one should use the concentration method defined in the superclass - :meth:`caimira.models._ConcentrationModelBase.concentration` - for a dedicated :class:`caimira.models.CO2ConcentrationModel` scenario.
A fraction of 4.2% of the exhalation rate of the defined activity was considered as the supplied to the room (:meth:`caimira.models.CO2ConcentrationModel.CO2_fraction_exhaled`).
In order to compute the CO\ :sub:`2` concentration one should then simply use the :meth:`caimira.models.CO2ConcentrationModel.concentration` method.
A fraction of 4.2% of the exhalation rate of the defined activity was considered as supplied to the room (:meth:`caimira.models.CO2ConcentrationModel.CO2_fraction_exhaled`).
Note still that nothing depends on the aerosol diameter :math:`D` in this case (no particles are involved) - hence in this class all parameters are constant w.r.t :math:`D`.

4
caimira/tests/models/test_concentration_model.py
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@ -179,6 +179,8 @@ def test_integrated_concentration(simple_conc_model):
npt.assert_almost_equal(c1, c2 + c3, decimal=15)
# The expected numbers were obtained via the quad integration of the
# normed_integrated_concentration method with 0 (start) and 2 (stop) as limits.
@pytest.mark.parametrize([
"known_min_background_concentration",
"expected_normed_integrated_concentration"],
@ -206,6 +208,8 @@ def test_normed_integrated_concentration_with_background_concentration(
npt.assert_almost_equal(known_conc_model.normed_integrated_concentration(0, 2), expected_normed_integrated_concentration)
# The expected numbers were obtained via the quad integration of the
# normed_integrated_concentration method with 0 (start) and 2 (stop) as limits.
@pytest.mark.parametrize([
"known_removal_rate",
"known_min_background_concentration",