def retrieve_clp_typecheck(
model: type[Model],
parameters: ParameterGroup,
clp_labels: dict[str, list[str] | list[list[str]]],
reduced_clp_labels: dict[str, list[str] | list[list[str]]],
reduced_clps: dict[str, list[np.ndarray]],
data: dict[str, xr.Dataset],
) -> dict[str, list[np.ndarray]]:
assert isinstance(parameters, ParameterGroup)
assert isinstance(reduced_clps, dict)
assert all(
isinstance(dataset_clps, list)
for dataset_clps in reduced_clps.values())
assert all(
[isinstance(index_clps, np.ndarray) for index_clps in dataset_clps]
for dataset_clps in reduced_clps.values())
assert isinstance(data, dict)
assert all(isinstance(label, str) for label in data)
assert all(isinstance(dataset, xr.Dataset) for dataset in data.values())
assert isinstance(clp_labels, dict)
assert isinstance(reduced_clp_labels, dict)
assert all(
isinstance(dataset_clp_labels, list)
for dataset_clp_labels in reduced_clp_labels.values())
assert all([[isinstance(label, str) for label in index_labels]
for index_labels in dataset_clp_labels]
for dataset_clp_labels in reduced_clp_labels.values())
if model.index_dependent():
for dataset_clp_labels in clp_labels.values():
assert all(
isinstance(index_label, list)
for index_label in dataset_clp_labels)
assert all([isinstance(label, str) for label in index_label]
for index_label in dataset_clp_labels)
assert all([
isinstance(index_labels, list)
for index_labels in dataset_clp_labels
] for dataset_clp_labels in reduced_clp_labels.values())
else:
for dataset_clp_labels in clp_labels.values():
assert all(isinstance(label, str) for label in dataset_clp_labels)
model.retrieve_clp_function_called = True
return reduced_clps
def additional_penalty_typecheck(
model: type[Model],
parameters: ParameterGroup,
clp_labels: dict[str, list[str] | list[list[str]]],
clps: dict[str, list[np.ndarray]],
matrices: dict[str, np.ndarray | list[np.ndarray]],
data: dict[str, xr.Dataset],
group_tolerance: float,
) -> np.ndarray:
assert isinstance(parameters, ParameterGroup)
assert isinstance(group_tolerance, float)
assert isinstance(clps, dict)
assert all(
isinstance(dataset_clps, list) for dataset_clps in clps.values())
assert all(
[isinstance(index_clps, np.ndarray) for index_clps in dataset_clps]
for dataset_clps in clps.values())
assert isinstance(data, dict)
assert all(isinstance(label, str) for label in data)
assert all(isinstance(dataset, xr.Dataset) for dataset in data.values())
assert isinstance(clp_labels, dict)
assert isinstance(matrices, dict)
if model.index_dependent():
for dataset_clp_labels in clp_labels.values():
assert all(
isinstance(index_label, list)
for index_label in dataset_clp_labels)
assert all([isinstance(label, str) for label in index_label]
for index_label in dataset_clp_labels)
for matrix in matrices.values():
assert isinstance(matrix, list)
assert all(
isinstance(index_matrix, np.ndarray)
for index_matrix in matrix)
else:
for dataset_clp_labels in clp_labels.values():
assert all(isinstance(label, str) for label in dataset_clp_labels)
for matrix in matrices.values():
assert isinstance(matrix, np.ndarray)
model.additional_penalty_function_called = True
return np.asarray([0.1])
def constrain_matrix_function_typecheck(
model: type[Model],
label: str,
parameters: ParameterGroup,
clp_labels: list[str],
matrix: np.ndarray,
index: float,
):
assert isinstance(label, str)
assert isinstance(parameters, ParameterGroup)
assert isinstance(clp_labels, list)
assert all(isinstance(clp_label, str) for clp_label in clp_labels)
assert isinstance(matrix, np.ndarray)
if model.index_dependent():
assert isinstance(index, float)
else:
assert index is None
model.constrain_matrix_function_called = True
return (clp_labels, matrix)