add distribution, boolean, and callable to Parameters

HARK/core.py

@@ -14,7 +14,7 @@
 from copy import copy, deepcopy
 from dataclasses import dataclass, field
 from time import time
-from typing import Any, Dict, List, NewType, Optional, Union
+from typing import Any, Dict, List, NewType, Optional, Union, Callable
 from warnings import warn
 
 import numpy as np
@@ -103,11 +103,11 @@ def __infer_dims__(
         """
         Infers the age-varying dimensions of a parameter.
 
-        If the parameter is a scalar, numpy array, or None, it is assumed to be
-        invariant over time. If the parameter is a list or tuple, it is assumed
-        to be varying over time. If the parameter is a list or tuple of length
-        greater than 1, the length of the list or tuple must match the
-        `_term_age` attribute of the Parameters object.
+        If the parameter is a scalar, numpy array, booleanm callable or None,
+        it is assumed to be invariant over time. If the parameter is a list or
+        tuple, it is assumed to be varying over time. If the parameter is a list
+        or tuple of length greater than 1, the length of the list or tuple must match
+        the `_term_age` attribute of the Parameters object.
 
         Parameters
         ----------
@@ -117,7 +117,9 @@ def __infer_dims__(
             value of parameter
 
         """
-        if isinstance(value, (int, float, np.ndarray, type(None))):
+        if isinstance(
+            value, (int, float, np.ndarray, type(None), Distribution, bool, Callable)
+        ):
             self.__add_to_invariant__(key)
             return value
         if isinstance(value, (list, tuple)):