From 87ff8ac778a1f51a6fc20cfa14948aa21b09c006 Mon Sep 17 00:00:00 2001 From: Luis Aleixo Date: Mon, 16 Aug 2021 18:29:23 +0200 Subject: [PATCH] updated known quantities tests --- cara/tests/test_known_quantities.py | 32 ++++++++++++++--------------- 1 file changed, 16 insertions(+), 16 deletions(-) diff --git a/cara/tests/test_known_quantities.py b/cara/tests/test_known_quantities.py index 91454898..6f67b834 100644 --- a/cara/tests/test_known_quantities.py +++ b/cara/tests/test_known_quantities.py @@ -7,7 +7,7 @@ import cara.data as data def test_no_mask_superspeading_emission_rate(baseline_model): - expected_rate = 970. + expected_rate = 48500. npt.assert_allclose( [baseline_model.infected.emission_rate(t) for t in [0, 1, 4, 4.5, 5, 8, 9]], [0, expected_rate, expected_rate, 0, 0, expected_rate, 0], @@ -44,7 +44,7 @@ def test_concentrations(baseline_model): concentrations = [baseline_model.concentration(t) for t in ts] npt.assert_allclose( concentrations, - [0.000000e+00, 0.41611256, 1.3205628e-14, 0.41611256, 4.1909001e-28], + [0.000000e+00, 20.805628, 6.602814e-13, 20.805628, 2.09545e-26], rtol=1e-6 ) @@ -354,16 +354,16 @@ def build_exposure_model(concentration_model): ) -# expected quanta were computed with a trapezoidal integration, using +# expected exposure were computed with a trapezoidal integration, using # a mesh of 100'000 pts per exposed presence interval. @pytest.mark.parametrize( - "month, expected_quanta", + "month, expected_exposure", [ - ['1', 9.930854], - ['6', 37.962708], + ['1', 496.5427], + ['6', 1898.1354], ], ) -def test_quanta_hourly_dep(month,expected_quanta): +def test_exposure_hourly_dep(month,expected_exposure): m = build_exposure_model( build_hourly_dependent_model( month, @@ -371,20 +371,20 @@ def test_quanta_hourly_dep(month,expected_quanta): intervals_presence_infected=((8, 12), (13, 17)) ) ) - quanta = m.quanta_exposure() - npt.assert_allclose(quanta, expected_quanta) + exposure = m.exposure() + npt.assert_allclose(exposure, expected_exposure) -# expected quanta were computed with a trapezoidal integration, using +# expected exposure were computed with a trapezoidal integration, using # a mesh of 100'000 pts per exposed presence interval and 25 pts per hour # for the temperature discretization. @pytest.mark.parametrize( - "month, expected_quanta", + "month, expected_exposure", [ - ['1', 9.993842], - ['6', 40.151985], + ['1', 499.6921], + ['6', 2007.59925], ], ) -def test_quanta_hourly_dep_refined(month,expected_quanta): +def test_exposure_hourly_dep_refined(month,expected_exposure): m = build_exposure_model( build_hourly_dependent_model( month, @@ -393,5 +393,5 @@ def test_quanta_hourly_dep_refined(month,expected_quanta): temperatures=data.Temperatures, ) ) - quanta = m.quanta_exposure() - npt.assert_allclose(quanta, expected_quanta, rtol=0.02) + exposure = m.exposure() + npt.assert_allclose(exposure, expected_exposure, rtol=0.02)