def _load_ensemble_parameters(ensemble, workspace):
parameters = _utils.load_parameters(workspace)
ensemble_parameters = {}
for input_record in ensemble.input:
record_name = input_record.record
record_source = input_record.source.split(".")
assert len(record_source) == 2
assert record_source[0] == "stochastic"
parameter_group_name = record_source[1]
ensemble_parameters[parameter_group_name] = parameters[parameter_group_name]
return ensemble_parameters
def sample_record(workspace, parameter_group_name, record_name, ensemble_size):
parameters = _utils.load_parameters(workspace)
if parameter_group_name not in parameters:
raise ValueError(
f"No parameter group found named: {parameter_group_name}")
distribution = parameters[parameter_group_name]
ert3.storage.add_variables(
workspace,
record_name,
[distribution.sample() for _ in range(ensemble_size)],
)
def _load_ensemble_parameters(
ensemble: ert3.config.EnsembleConfig,
workspace: pathlib.Path,
) -> Mapping[str, ert3.stats.Distribution]:
parameters = _utils.load_parameters(workspace)
ensemble_parameters = {}
for input_record in ensemble.input:
record_name = input_record.record
record_source = input_record.source.split(".")
assert len(record_source) == 2
assert record_source[0] == "stochastic"
parameter_group_name = record_source[1]
ensemble_parameters[record_name] = parameters[parameter_group_name]
return ensemble_parameters
def sample_record(
workspace: Path,
parameter_group_name: str,
record_name: str,
ensemble_size: int,
experiment_name: Optional[str] = None,
) -> None:
parameters = _utils.load_parameters(workspace)
if parameter_group_name not in parameters:
raise ValueError(f"No parameter group found named: {parameter_group_name}")
distribution = parameters[parameter_group_name]
ensrecord = ert3.data.EnsembleRecord(
records=[distribution.sample() for _ in range(ensemble_size)]
)
ert3.storage.add_ensemble_record(
workspace=workspace,
record_name=record_name,
ensemble_record=ensrecord,
experiment_name=experiment_name,
)