def __init__(self, cause, risk):
self.cause = EntityString(cause)
self.risk = EntityString(risk)
self.state_column = self.cause.name
self.state_id = self.cause.name
self.diseased_event_time_column = f'{self.cause.name}_event_time'
self.susceptible_event_time_column = f'susceptible_to_{self.cause.name}_event_time'
self.configuration_defaults = {
self.cause.name: RiskAttributableDisease.configuration_defaults['risk_attributable_disease']
}
def setup(self, builder):
self.risk = EntityString(
f'risk_factor.{project_globals.LBWSG_MODEL_NAME}')
self.exposure_distribution = LBWSGDistribution(builder)
# FIXME: These are not actual birth weights/gestational times, but the
# raw values that source pipelines. They should use different column
# names but that's too much to try to fix now. We didn't build the
# distribution class with clear enough boundaries to make the
# distinction.
created_columns = project_globals.LBWSG_COLUMNS
self.population_view = builder.population.get_view(created_columns +
['tracked'])
builder.population.initializes_simulants(
self.on_initialize_simulants,
creates_columns=created_columns,
requires_columns=['age', 'sex'])
self._raw_exposure = builder.value.register_value_producer(
f'{self.risk.name}.raw_exposure',
source=lambda index: self.population_view.get(index),
requires_columns=project_globals.LBWSG_COLUMNS)
self.exposure = builder.value.register_value_producer(
f'{self.risk.name}.exposure',
source=self._raw_exposure,
preferred_post_processor=self.exposure_distribution.
convert_to_categorical,
requires_values=f'{self.risk.name}.raw_exposure')
def __init__(self, risk: str):
"""
Parameters
----------
risk :
the type and name of a risk, specified as "type.name". Type is singular.
"""
self.risk = EntityString(risk)
self.configuration_defaults = {f'{self.risk.name}': Risk.configuration_defaults['risk']}
self.exposure_distribution = SimulationDistribution(self.risk)
self._sub_components = [self.exposure_distribution]
def __init__(self, target: str):
"""
Parameters
----------
target :
Type, name, and target rate of entity to be affected by risk factor,
supplied in the form "entity_type.entity_name.measure"
where entity_type should be singular (e.g., cause instead of causes).
"""
self.risk = EntityString(
f'risk_factor.low_birth_weight_and_short_gestation')
self.target = TargetString(target)
def __init__(self, builder):
self.risk = EntityString(
'risk_factor.low_birth_weight_and_short_gestation')
self.randomness = builder.randomness.get_stream(
f'{self.risk.name}.exposure')
self.categories_by_interval = get_categories_by_interval(
builder, self.risk)
self.intervals_by_category = self.categories_by_interval.reset_index(
).set_index('cat')
self.max_gt_by_bw, self.max_bw_by_gt = self._get_boundary_mappings()
self.exposure_parameters = builder.lookup.build_table(
get_exposure_data(builder, self.risk))
def __init__(self, risk: str):
"""
Parameters
----------
risk :
the type and name of a risk, specified as "type.name". Type is singular.
"""
self.risk = EntityString(risk)
self.configuration_defaults = {
'metrics': {
f'{self.risk.name}_observer':
RiskObserver.configuration_defaults['metrics']['risk_observer']
}
}
def __init__(self, builder):
self.risk = EntityString(
f'risk_factor.{project_globals.LBWSG_MODEL_NAME}')
self.randomness = builder.randomness.get_stream(
f'{self.risk.name}.exposure')
self.categories_by_interval = get_lbwsg_categories_by_interval(builder)
self.intervals_by_category = self.categories_by_interval.reset_index(
).set_index('cat')
self.max_gt_by_bw, self.max_bw_by_gt = self._get_boundary_mappings()
self.exposure_parameters = builder.lookup.build_table(
self.get_exposure_data(builder),
key_columns=['sex'],
parameter_columns=['age', 'year'])
def __init__(self, target: str):
"""
Parameters
----------
target :
Type, name, and target rate of entity to be affected by risk factor,
supplied in the form "entity_type.entity_name.measure"
where entity_type should be singular (e.g., cause instead of causes).
"""
self.risk = EntityString(
'risk_factor.low_birth_weight_and_short_gestation')
self.target = TargetString(target)
self.configuration_defaults = {
f'effect_of_{self.risk.name}_on_{self.target.name}': {
self.target.measure:
RiskEffect.configuration_defaults['effect_of_risk_on_target']
['measure']
}
}
def __init__(self, risk: str, target: str):
"""
Parameters
----------
risk :
Type and name of risk factor, supplied in the form
"risk_type.risk_name" where risk_type should be singular (e.g.,
risk_factor instead of risk_factors).
target :
Type, name, and target rate of entity to be affected by risk factor,
supplied in the form "entity_type.entity_name.measure"
where entity_type should be singular (e.g., cause instead of causes).
"""
self.risk = EntityString(risk)
self.target = TargetString(target)
self.configuration_defaults = {
f'effect_of_{self.risk.name}_on_{self.target.name}': {
self.target.measure: RiskEffect.configuration_defaults['effect_of_risk_on_target']['measure']
}
}
def __init__(self, risk, low, high):
self.risk = EntityString(risk)
self.low = int(low)
self.high = int(high)
self.exp = pd.Series()
def __init__(self):
self.risk = EntityString(
'risk_factor.low_birth_weight_and_short_gestation')
def test_EntityString_pass(s):
entity_type, entity_name = s.split('.')
r = EntityString(s)
assert r.type == entity_type
assert r.name == entity_name
def test_EntityString_fail(s):
with pytest.raises(ValueError):
EntityString(s)