def test_web_download_data(webclient):
curve_conf = {
"population": 600000,
"N_init": 10,
"R": 1.2,
"intervention_start": 15,
"intervention_end": 25,
"intervention_decrease": 70.0,
"t_incubation": 5,
"t_infectious": 9,
"t_death": 32.0,
"mild_recovery": 11.0,
"bed_stay": 28.0,
"bed_rate": 0.2,
"bed_wait": 5,
"beta": 1.236,
"sigma": 1.1,
"gamma": 1.1,
}
sir_conf = {"t_max": 200, "dt": 1.0}
curve = arcovid19.load_infection_curve(**curve_conf)
expected = curve.do_SIR(**sir_conf)
data = {"model": "do_SIR"}
data.update(curve_conf)
data.update(sir_conf)
response = webclient.post("/download_model", data=data)
ectype = (
"application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
assert response.status_code == 200
assert response.headers["Content-Type"] == ectype
# validate result
result = pd.read_excel(io.BytesIO(response.data), sheet_name="Data")
result = result.set_index("ts")
# validate in the 8 decimal place
np.testing.assert_array_almost_equal(result, expected.df, decimal=8)
config = pd.read_excel(io.BytesIO(response.data), sheet_name="Config")
config = config.set_index("Attribute")
assert config.to_dict()["Value"] == data
def test_always_return_model_frame():
curve_conf = {
'population': 600000,
'N_init': 10,
'R': 1.2,
'intervention_start': 15.0,
'intervention_end': 25.0,
'intervention_decrease': 70.0,
't_incubation': 5.0,
't_infectious': 9.0
}
m_conf = {'t_max': 200.0, 'dt': 1.0}
curve = arcovid19.load_infection_curve(**curve_conf)
for mname in dir(curve):
method = getattr(curve, mname)
if mname.startswith("do_") and callable(method):
result = method(**m_conf)
assert isinstance(result, ModelResultFrame)
assert result.model_name == mname.split("_")[-1]
def test_SEIR_migration():
expected = pd.read_excel(TEST_DATA_PATH / "test_SEIR_migration.xlsx")
expected = expected.set_index("ts")
expected.index = expected.index.astype(float)
curve_conf = {
'population': 600000,
'N_init': 10,
'R': 1.2,
'intervention_start': 15.0,
'intervention_end': 25.0,
'intervention_decrease': 70.0,
't_incubation': 5.0,
't_infectious': 9.0
}
seir_conf = {'t_max': 200.0, 'dt': 1.0}
curve = arcovid19.load_infection_curve(**curve_conf)
result = curve.do_SEIR(**seir_conf)
np.testing.assert_array_almost_equal(result.df, expected, decimal=8)
assert result.model_name == "SEIR"
def test_SEIRF_plot_migration():
expected = pd.read_excel(TEST_DATA_PATH / "test_SEIRF_migration.xlsx")
expected = expected.set_index("ts")
expected.index = expected.index.astype(float)
curve_conf = {
'population': 600000,
'N_init': 10,
'R': 1.2,
'intervention_start': 15.0,
'intervention_end': 25.0,
'intervention_decrease': 70.0,
't_incubation': 5.0,
't_infectious': 9.0
}
sir_conf = {'t_max': 200.0, 'dt': 1.0}
curve = arcovid19.load_infection_curve(**curve_conf)
result = curve.do_SEIRF(**sir_conf)
fig, ax = plt.subplots()
result.plot(ax=ax, only=["S", "E", "I", "R", "F"], fill=True, log=True)
return fig