trivial

cobaya/theory.py

@@ -67,7 +67,7 @@ def __init__(self, info: TheoryDictIn = empty_dict,
                          standalone=standalone)
 
         # set to Provider instance before calculations
-        self.provider: Any = None
+        self.provider: Optional['Provider'] = None
         # Generate cache states, to avoid recomputing.
         # Default 3, but can be changed by sampler
         self.set_cache_size(3)
@@ -415,7 +415,7 @@ def __init__(self, model, requirement_providers: Dict[str, Theory]):
         self.requirement_providers = requirement_providers
         self.params = {}
 
-    def set_current_input_params(self, params):
+    def set_current_input_params(self, params: ParamValuesDict):
         self.params = params
 
     def get_param(self, param: Union[str, Iterable[str]]) -> Union[float, List[float]]:

cobaya/typing.py

@@ -152,7 +152,7 @@ def validate_type(expected_type: type, value: Any, path: str = ''):
 
     if expected_type is float:
         if not (isinstance(value, numbers.Real) or
-                (isinstance(value, np.ndarray) and value.shape == ())):
+                (isinstance(value, np.ndarray) and value.ndim == 0)):
             raise TypeError(f"{curr_path} must be a float, got {type(value).__name__}")
         return
 
@@ -218,7 +218,7 @@ def validate_type(expected_type: type, value: Any, path: str = ''):
 
         if issubclass(origin, Iterable):
             if isinstance(value, np.ndarray):
-                if not value.shape:
+                if value.ndim == 0:
                     raise TypeError(f"{curr_path} numpy array zero rank")
                 if len(args) == 1 and not np.issubdtype(value.dtype, args[0]):
                     raise TypeError(