def create_stgpr_version(path_to_config: str,
model_index_id: Optional[int] = None,
output_path: Optional[str] = None) -> int:
"""
Creates a new ST-GPR version (and model version) and adds it to
the database.
Args:
path_to_config: path to config CSV containing model parameters
model_index_id: index of config parameters to use, if config contains
multiple sets of model parameters
output_path: where to save files
Returns:
Created ST-GPR version ID
Raises:
ValueError: for config validation errors
"""
# Validate input.
config_exists = os.path.isfile(path_to_config)
config_is_csv = path_to_config.lower().endswith('.csv')
if not config_exists or not config_is_csv:
raise ValueError(
f'{path_to_config} is not a valid path to a config CSV')
with session_management.session_scope() as session:
# Call library function to create ST-GPR version.
return stgpr_version.create_stgpr_version(session, path_to_config,
model_index_id, output_path)
def get_parameters(stgpr_version_id: int) -> Dict[str, Any]:
"""
Pulls parameters associated with an ST-GPR version ID.
Args:
stgpr_version_id: the ID with which to pull parameters
Returns:
Dictionary of parameters for an ST-GPR run
Raises:
ValueError: if stgpr_version_id is not in the database
"""
with session_management.session_scope() as session:
# Validate input.
stgpr_version_validation.validate_stgpr_version_exists(
stgpr_version_id, session)
# Call library function to get parameters.
return parameters.get_parameters(session, stgpr_version_id)
def get_custom_stage_1_estimates(stgpr_version_id: int) -> pd.DataFrame:
"""
Pulls custom stage 1 data associated with an ST-GPR version ID.
Args:
stgpr_version_id: the ID with which to pull custom stage 1 estimates
Returns:
Dataframe of custom stage 1 estimates for an ST-GPR run or None if
there are no custom stage 1 estimates for the given ST-GPR version ID
Raises:
ValueError: if stgpr_version_id is not in the database
"""
with session_management.session_scope() as session:
# Validate input.
stgpr_version_validation.validate_stgpr_version_exists(
stgpr_version_id, session)
# Call library function to get parameters.
return stage_1.get_custom_stage_1_estimates(session, stgpr_version_id)
def create_model_version(
stgpr_version_id: int,
decomp_step: str,
gbd_round_id: int,
modelable_entity_id: Optional[int] = None,
covariate_id: Optional[int] = None,
epi_model_version_id: Optional[int] = None,
covariate_model_version_id: Optional[int] = None) -> int:
"""
Creates a new ST-GPR model version and adds it to the database.
Args:
stgpr_version_id: the ST-GPR version ID to link to this model version
decomp_step: the decomp step associated with this ST-GPR
gbd_round_id: the ID of the GBD round associated with this ST-GPR model
modelable_entity_id: the ME ID associated with this ST-GPR model
covariate_id: the covariate ID associated with this ST-GPR model
epi_model_version_id: the epi model version ID associated with this
ST-GPR model
covariate_model_version_id: the covariate model version ID associated
with this ST-GPR model
Returns:
Created model version ID
"""
with session_management.session_scope() as session:
# Validate input.
stgpr_version_validation.validate_stgpr_version_exists(
stgpr_version_id, session)
# Call library function to create model version.
return model_version.create_model_version(session, stgpr_version_id,
decomp_step, gbd_round_id,
modelable_entity_id,
covariate_id,
epi_model_version_id,
covariate_model_version_id)