Revert get draws kwargs (#326)

    Category: bugfix
    JIRA issue: MIC-4615

Changes and notes

The get_draws_kwargs argument was erroneously merged into main in #312 but should be removed because it's never used.

CHANGELOG.rst

@@ -1,3 +1,7 @@
+**4.1.4 - 01/11/24**
+
+ - Remove erroneously merged get_draws_kwargs argument
+
 **4.1.3 - 01/09/24**
 
  - Update PyPI to 2FA with trusted publisher

docs/source/tutorials/pulling_data.rst

@@ -379,8 +379,7 @@ To use:
                 'parameters': {
                     'entity': ModelableEntity, 
                     'measure': str, 
-                    'location': str, 
-                    'get_draws_kwargs': inspect._empty,
+                    'location': str,
                         },
                 'return': pd.DataFrame, },
              get_population_structure: {

src/vivarium_inputs/core.py

@@ -22,7 +22,7 @@
 from vivarium_inputs.mapping_extension import AlternativeRiskFactor, HealthcareEntity
 
 
-def get_data(entity, measure: str, location: Union[str, int], **get_draws_kwargs):
+def get_data(entity, measure: str, location: Union[str, int]):
     measure_handlers = {
         # Cause-like measures
         "incidence_rate": (get_incidence_rate, ("cause", "sequela")),
@@ -78,7 +78,7 @@ def get_data(entity, measure: str, location: Union[str, int], **get_draws_kwargs
     location_id = (
         utility_data.get_location_id(location) if isinstance(location, str) else location
     )
-    data = handler(entity, location_id, **get_draws_kwargs)
+    data = handler(entity, location_id)
 
     if measure in [
         "structure",
@@ -217,9 +217,9 @@ def get_deaths(entity: Cause, location_id: int) -> pd.DataFrame:
 
 
 def get_exposure(
-    entity: Union[RiskFactor, AlternativeRiskFactor], location_id: int, **get_draws_kwargs
+    entity: Union[RiskFactor, AlternativeRiskFactor], location_id: int
 ) -> pd.DataFrame:
-    data = extract.extract_data(entity, "exposure", location_id, **get_draws_kwargs)
+    data = extract.extract_data(entity, "exposure", location_id)
     data = data.drop("modelable_entity_id", "columns")
 
     if entity.name in EXTRA_RESIDUAL_CATEGORY:

src/vivarium_inputs/extract.py

@@ -21,7 +21,7 @@
 
 
 def extract_data(
-    entity, measure: str, location_id: int, validate: bool = True, **get_draws_kwargs
+    entity, measure: str, location_id: int, validate: bool = True
 ) -> Union[pd.Series, pd.DataFrame]:
     """Check metadata for the requested entity-measure pair. Pull raw data from
     GBD. The only filtering that occurs is by applicable measure id, metric id,
@@ -94,7 +94,7 @@ def extract_data(
 
     try:
         main_extractor, additional_extractors = extractors[measure]
-        data = main_extractor(entity, location_id, **get_draws_kwargs)
+        data = main_extractor(entity, location_id)
     except (
         ValueError,
         AssertionError,
@@ -176,10 +176,10 @@ def extract_deaths(entity: Cause, location_id: int) -> pd.DataFrame:
 
 
 def extract_exposure(
-    entity: Union[RiskFactor, AlternativeRiskFactor], location_id: int, **get_draws_kwargs
+    entity: Union[RiskFactor, AlternativeRiskFactor], location_id: int
 ) -> pd.DataFrame:
     if entity.kind == "risk_factor":
-        data = gbd.get_exposure(entity.gbd_id, location_id, **get_draws_kwargs)
+        data = gbd.get_exposure(entity.gbd_id, location_id)
         allowable_measures = [
             MEASURES["Proportion"],
             MEASURES["Continuous"],

src/vivarium_inputs/interface.py

@@ -9,9 +9,7 @@
 from vivarium_inputs.globals import Population
 
 
-def get_measure(
-    entity: ModelableEntity, measure: str, location: str, **get_draws_kwargs
-) -> pd.DataFrame:
+def get_measure(entity: ModelableEntity, measure: str, location: str) -> pd.DataFrame:
     """Pull GBD data for measure and entity and prep for simulation input,
     including scrubbing all GBD conventions to replace IDs with meaningful
     values or ranges and expanding over all demographic dimensions. To pull data
@@ -55,7 +53,7 @@ def get_measure(
         Dataframe standardized to the format expected by `vivarium` simulations.
 
     """
-    data = core.get_data(entity, measure, location, **get_draws_kwargs)
+    data = core.get_data(entity, measure, location)
     data = utilities.scrub_gbd_conventions(data, location)
     validation.validate_for_simulation(data, entity, measure, location)
     data = utilities.split_interval(data, interval_column="age", split_column_prefix="age")