def test_parse_artifact_path_config(base_config, test_data_dir):
artifact_path = test_data_dir / 'artifact.hdf'
base_config.update({'input_data': {
'artifact_path': str(artifact_path)
}}, **metadata(str(Path('/'))))
assert parse_artifact_path_config(base_config) == str(artifact_path)
def test_prevalence_multiple_sequelae(base_config, base_plugins, disease,
base_data, test_prevalence_level):
year_start = base_config.time.start.year
year_end = base_config.time.end.year
healthy = BaseDiseaseState('healthy')
sequela = dict()
for i, p in enumerate(test_prevalence_level):
data_funcs = base_data(p)
data_funcs.update({'disability_weight': lambda _, __: 0.0})
sequela[i] = DiseaseState('sequela' + str(i),
get_data_functions=data_funcs)
model = DiseaseModel(disease,
initial_state=healthy,
states=[healthy, sequela[0], sequela[1], sequela[2]])
base_config.update({'population': {
'population_size': 100000
}}, **metadata(__file__))
simulation = InteractiveContext(components=[TestPopulation(), model],
configuration=base_config,
plugin_configuration=base_plugins)
error_message = "initial sequela status of simulants should be matched to the prevalence data."
assert np.allclose([
get_test_prevalence(simulation, 'sequela0'),
get_test_prevalence(simulation, 'sequela1'),
get_test_prevalence(simulation, 'sequela2')
], test_prevalence_level, .02), error_message
def test_parse_artifact_path_relative(base_config, test_data_dir):
base_config.update(
{'input_data': {
'artifact_path': '../../test_data/artifact.hdf'
}}, **metadata(__file__))
assert parse_artifact_path_config(base_config) == str(test_data_dir /
'artifact.hdf')
def test_parse_artifact_path_config_fail_relative(base_config):
base_config.update(
{'input_data': {
'artifact_path': './not_an_artifact.hdf'
}}, **metadata(__file__))
with pytest.raises(FileNotFoundError):
parse_artifact_path_config(base_config)
def test_parse_artifact_path_config_fail(base_config):
artifact_path = Path(__file__).parent / 'not_an_artifact.hdf'
base_config.update({'input_data': {
'artifact_path': str(artifact_path)
}}, **metadata(str(Path('/'))))
with pytest.raises(FileNotFoundError):
parse_artifact_path_config(base_config)
def test_get_age_bins(builder, base_config, age_start, exit_age,
result_age_end_values, result_age_start_values):
base_config.update(
{'population': {
'age_start': age_start,
'exit_age': exit_age
}}, **metadata(__file__))
builder.configuration = base_config
df = get_age_bins(builder)
assert set(df.age_end) == result_age_end_values
assert set(df.age_start) == result_age_start_values
def test_dwell_time(assign_cause_mock, base_config, base_plugins, disease,
base_data):
time_step = 10
assign_cause_mock.side_effect = lambda population, *args: pd.DataFrame(
{'condition_state': 'healthy'}, index=population.index)
base_config.update(
{
'time': {
'step_size': time_step
},
'population': {
'population_size': 10
}
}, **metadata(__file__))
healthy_state = BaseDiseaseState('healthy')
data_function = base_data(0)
data_function['dwell_time'] = lambda _, __: pd.Timedelta(days=28)
data_function['disability_weight'] = lambda _, __: 0.0
event_state = DiseaseState('event', get_data_functions=data_function)
done_state = BaseDiseaseState('sick')
healthy_state.add_transition(event_state)
event_state.add_transition(done_state)
model = DiseaseModel(disease,
initial_state=healthy_state,
states=[healthy_state, event_state, done_state])
simulation = InteractiveContext(components=[TestPopulation(), model],
configuration=base_config,
plugin_configuration=base_plugins)
# Move everyone into the event state
simulation.step()
event_time = simulation._clock.time
assert np.all(simulation.get_population()[disease] == 'event')
simulation.step()
simulation.step()
# Not enough time has passed for people to move out of the event state, so they should all still be there
assert np.all(simulation.get_population()[disease] == 'event')
simulation.step()
# Now enough time has passed so people should transition away
assert np.all(simulation.get_population()[disease] == 'sick')
assert np.all(simulation.get_population().event_event_time ==
pd.to_datetime(event_time))
assert np.all(simulation.get_population().event_event_count == 1)
def test_prevalence_birth_prevalence_initial_assignment(
base_config, base_plugins, disease):
healthy = BaseDiseaseState('healthy')
data_funcs = {
'prevalence': lambda _, __: 1,
'birth_prevalence': lambda _, __: 0.5,
'disability_weight': lambda _, __: 0
}
with_condition = DiseaseState('with_condition',
get_data_functions=data_funcs)
model = DiseaseModel(disease,
initial_state=healthy,
states=[healthy, with_condition])
base_config.update(
{
'population': {
'population_size': 1000,
'age_start': 0,
'age_end': 5
}
}, **metadata(__file__))
simulation = InteractiveContext(components=[TestPopulation(), model],
configuration=base_config,
plugin_configuration=base_plugins)
# prevalence should be used for assigning initial status at sim start
assert np.isclose(get_test_prevalence(simulation, "with_condition"), 1)
# birth prevalence should be used for assigning initial status to newly-borns on time steps
simulation._clock.step_forward()
simulation.simulant_creator(1000,
population_configuration={
'age_start': 0,
'age_end': 0,
'sim_state': 'time_step'
})
assert np.isclose(get_test_prevalence(simulation, "with_condition"), 0.75,
0.01)
# and prevalence should be used for ages not start = end = 0
simulation._clock.step_forward()
simulation.simulant_creator(1000,
population_configuration={
'age_start': 0,
'age_end': 5,
'sim_state': 'time_step'
})
assert np.isclose(get_test_prevalence(simulation, "with_condition"), 0.83,
0.01)
def test_prevalence_single_state_with_migration(base_config, base_plugins,
disease, base_data,
test_prevalence_level):
"""
Test the prevalence for the single state over newly migrated population.
Start with the initial population, check the prevalence for initial assignment.
Then add new simulants and check whether the initial status is
properly assigned to new simulants based on the prevalence data and pre-existing simulants status
"""
year_start = base_config.time.start.year
year_end = base_config.time.end.year
healthy = BaseDiseaseState('healthy')
data_funcs = base_data(test_prevalence_level)
data_funcs.update({'disability_weight': lambda _, __: 0.0})
sick = DiseaseState('sick', get_data_functions=data_funcs)
model = DiseaseModel(disease,
initial_state=healthy,
states=[healthy, sick])
base_config.update({'population': {
'population_size': 50000
}}, **metadata(__file__))
simulation = InteractiveContext(components=[TestPopulation(), model],
configuration=base_config,
plugin_configuration=base_plugins)
error_message = "initial status of simulants should be matched to the prevalence data."
assert np.isclose(get_test_prevalence(simulation, 'sick'),
test_prevalence_level, 0.01), error_message
simulation._clock.step_forward()
assert np.isclose(get_test_prevalence(simulation, 'sick'),
test_prevalence_level, .01), error_message
simulation.simulant_creator(50000,
population_configuration={
'age_start': 0,
'age_end': 5,
'sim_state': 'time_step'
})
assert np.isclose(get_test_prevalence(simulation, 'sick'),
test_prevalence_level, .01), error_message
simulation._clock.step_forward()
simulation.simulant_creator(50000,
population_configuration={
'age_start': 0,
'age_end': 5,
'sim_state': 'time_step'
})
assert np.isclose(get_test_prevalence(simulation, 'sick'),
test_prevalence_level, .01), error_message
def base_config():
config = build_simulation_configuration()
config.update(
{
'time': {
'start': {
'year': 1990,
},
'end': {
'year': 2010
},
'step_size': 30.5
}
}, **metadata(__file__))
return config
def test_FertilityDeterministic(config):
pop_size = config.population.population_size
annual_new_simulants = 1000
step_size = config.time.step_size
num_days = 100
config.update({
'fertility': {
'number_of_new_simulants_each_year': annual_new_simulants
}
}, **metadata(__file__))
components = [TestPopulation(), FertilityDeterministic()]
simulation = InteractiveContext(components=components, configuration=config)
num_steps = simulation.run_for(duration=pd.Timedelta(days=num_days))
pop = simulation.get_population()
assert num_steps == num_days // step_size
assert np.all(pop.alive == 'alive')
assert int(num_days * annual_new_simulants / utilities.DAYS_PER_YEAR) == len(pop.age) - pop_size
def test_dwell_time_with_mortality(base_config, base_plugins, disease):
year_start = base_config.time.start.year
year_end = base_config.time.end.year
time_step = 10
pop_size = 100
base_config.update(
{
'time': {
'step_size': time_step
},
'population': {
'population_size': pop_size
}
}, **metadata(__file__))
healthy_state = BaseDiseaseState('healthy')
mort_get_data_funcs = {
'dwell_time':
lambda _, __: pd.Timedelta(days=14),
'excess_mortality_rate':
lambda _, __: build_table(0.7, year_start - 1, year_end),
'disability_weight':
lambda _, __: 0.0
}
mortality_state = DiseaseState('event',
get_data_functions=mort_get_data_funcs)
done_state = BaseDiseaseState('sick')
healthy_state.add_transition(mortality_state)
mortality_state.add_transition(done_state)
model = DiseaseModel(disease,
initial_state=healthy_state,
states=[healthy_state, mortality_state, done_state])
mortality = Mortality()
simulation = InteractiveContext(
components=[TestPopulation(), model, mortality],
configuration=base_config,
plugin_configuration=base_plugins)
# Move everyone into the event state
simulation.step()
assert np.all(simulation.get_population()[disease] == 'event')
simulation.step()
# Not enough time has passed for people to move out of the event state, so they should all still be there
assert np.all(simulation.get_population()[disease] == 'event')
simulation.step()
# Make sure some people have died and remained in event state
assert (simulation.get_population()['alive'] == 'alive').sum() < pop_size
assert ((simulation.get_population()['alive'] == 'dead').sum() == (
simulation.get_population()[disease] == 'event').sum())
# enough time has passed so living people should transition away to sick
assert ((simulation.get_population()['alive'] == 'alive').sum() == (
simulation.get_population()[disease] == 'sick').sum())
