def test_basic_simulation_100_runs(data_api):
network, _ = np.createNetworkOfPopulation(
data_api.read_table("human/compartment-transition",
"compartment-transition"),
data_api.read_table("human/population", "population"),
data_api.read_table("human/commutes", "commutes"),
data_api.read_table("human/mixing-matrix", "mixing-matrix"),
data_api.read_table("human/infectious-compartments",
"infectious-compartments"),
data_api.read_table("human/infection-probability",
"infection-probability"),
data_api.read_table("human/initial-infections", "initial-infections"),
data_api.read_table("human/trials", "trials"),
data_api.read_table("human/start-end-date", "start-end-date"),
)
runs = []
rand = random.Random(1)
issues = []
for _ in range(100):
regions = rand.choices(list(network.graph.nodes()), k=1)
assert network.initialState[regions[0]][("[17,70)", "E")] == 0
df, new_issues = np.basicSimulationInternalAgeStructure(
network, {regions[0]: {
"[17,70)": 10.0
}}, numpy.random.default_rng(123))
result = calculateInfectiousOverTime(df, network.infectiousStates)
result.pop(
) # TODO: due to historical reasons we have to ignore the last entry
runs.append(result)
issues.extend(new_issues)
result = common.generateMeanPlot(runs)
_assert_baseline(result)
assert not issues
def test_basic_simulation_with_dampening(data_api):
network, _ = np.createNetworkOfPopulation(
data_api.read_table("human/compartment-transition",
"compartment-transition"),
data_api.read_table("human/population", "population"),
data_api.read_table("human/commutes", "commutes"),
data_api.read_table("human/mixing-matrix", "mixing-matrix"),
data_api.read_table("human/infectious-compartments",
"infectious-compartments"),
data_api.read_table("human/infection-probability",
"infection-probability"),
data_api.read_table("human/initial-infections", "initial-infections"),
data_api.read_table("human/trials", "trials"),
data_api.read_table("human/start-end-date", "start-end-date"),
data_api.read_table("human/movement-multipliers",
"movement-multipliers"),
)
df, issues = np.basicSimulationInternalAgeStructure(
network, {"S08000016": {
"[17,70)": 10.0
}}, numpy.random.default_rng(123))
result = calculateInfectiousOverTime(df, network.infectiousStates)
_assert_baseline(result)
assert not issues
def test_basic_simulation(data_api):
network = np.createNetworkOfPopulation(
data_api.read_table("human/compartment-transition"),
data_api.read_table("human/population"),
data_api.read_table("human/commutes"),
data_api.read_table("human/mixing-matrix"),
data_api.read_table("human/infectious-compartments"),
data_api.read_table("human/infection-probability"),
data_api.read_table("human/initial-infections"),
data_api.read_table("human/trials"),
)
result = calculateInfectiousOverTime(
np.basicSimulationInternalAgeStructure(
network, 200, {"S08000016": {
"[17,70)": 10.0
}}), network.infectiousStates)
_assert_baseline(result)