Merge pull request #188 from MaxGhenis/MaxGhenis/issue100

changelog_entry.yaml

@@ -0,0 +1,4 @@
+- bump: patch
+  changes:
+    fixed:
+      - FutureWarning issue with bools and enums.

policyengine_core/enums/enum.py

@@ -1,110 +1,79 @@
 from __future__ import annotations
-
 import enum
 from typing import Union
-
-import numpy
-
+import numpy as np
 from .config import ENUM_ARRAY_DTYPE
 from .enum_array import EnumArray
 
-import warnings
-
-warnings.simplefilter("ignore", category=FutureWarning)
-
 
 class Enum(enum.Enum):
     """
     Enum based on `enum34 <https://pypi.python.org/pypi/enum34/>`_, whose items
     have an index.
     """
 
-    # Tweak enums to add an index attribute to each enum item
     def __init__(self, name: str) -> None:
-        # When the enum item is initialized, self._member_names_ contains the
-        # names of the previously initialized items, so its length is the index
-        # of this item.
+        """
+        Initialize an Enum item with a name and an index.
+
+        The index is automatically assigned based on the order of the Enum items.
+        """
         self.index = len(self._member_names_)
 
-    # Bypass the slow Enum.__eq__
     __eq__ = object.__eq__
-
-    # In Python 3, __hash__ must be defined if __eq__ is defined to stay
-    # hashable.
     __hash__ = object.__hash__
 
     @classmethod
-    def encode(
-        cls,
-        array: Union[
-            EnumArray,
-            numpy.int_,
-            numpy.float_,
-            numpy.object_,
-        ],
-    ) -> EnumArray:
+    def encode(cls, array: Union[EnumArray, np.ndarray]) -> EnumArray:
         """
-        Encode a string numpy array, an enum item numpy array, or an int numpy
-        array into an :any:`EnumArray`. See :any:`EnumArray.decode` for
-        decoding.
-
-        :param numpy.ndarray array: Array of string identifiers, or of enum
-                                    items, to encode.
+        Encode an array of enum items or string identifiers into an EnumArray.
 
-        :returns: An :any:`EnumArray` encoding the input array values.
-        :rtype: :any:`EnumArray`
+        Args:
+            array: The input array to encode. Can be an EnumArray, a NumPy array
+                of enum items, or a NumPy array of string identifiers.
 
-        For instance:
+        Returns:
+            An EnumArray containing the encoded values.
 
-        >>> string_identifier_array = asarray(['free_lodger', 'owner'])
-        >>> encoded_array = HousingOccupancyStatus.encode(string_identifier_array)
-        >>> encoded_array[0]
-        2  # Encoded value
+        Examples:
+            >>> string_array = np.array(["ITEM_1", "ITEM_2", "ITEM_3"])
+            >>> encoded_array = MyEnum.encode(string_array)
+            >>> encoded_array
+            EnumArray([1, 2, 3], dtype=int8)
 
-        >>> free_lodger = HousingOccupancyStatus.free_lodger
-        >>> owner = HousingOccupancyStatus.owner
-        >>> enum_item_array = asarray([free_lodger, owner])
-        >>> encoded_array = HousingOccupancyStatus.encode(enum_item_array)
-        >>> encoded_array[0]
-        2  # Encoded value
+            >>> item_array = np.array([MyEnum.ITEM_1, MyEnum.ITEM_2, MyEnum.ITEM_3])
+            >>> encoded_array = MyEnum.encode(item_array)
+            >>> encoded_array
+            EnumArray([1, 2, 3], dtype=int8)
         """
         if isinstance(array, EnumArray):
             return array
 
-        if isinstance(array == 0, bool):
+        if array.dtype.kind == "b":
+            # Convert boolean array to string array
             array = array.astype(str)
 
-        # String array
-        if isinstance(array, numpy.ndarray) and array.dtype.kind in {"U", "S"}:
-            array = numpy.select(
+        if array.dtype.kind in {"U", "S"}:
+            # String array
+            indices = np.select(
                 [array == item.name for item in cls],
                 [item.index for item in cls],
-            ).astype(ENUM_ARRAY_DTYPE)
-
-        # Enum items arrays
-        elif isinstance(array, numpy.ndarray) and array.dtype.kind == "O":
-            # Ensure we are comparing the comparable. The problem this fixes:
-            # On entering this method "cls" will generally come from
-            # variable.possible_values, while the array values may come from
-            # directly importing a module containing an Enum class. However,
-            # variables (and hence their possible_values) are loaded by a call
-            # to load_module, which gives them a different identity from the
-            # ones imported in the usual way.
-            #
-            # So, instead of relying on the "cls" passed in, we use only its
-            # name to check that the values in the array, if non-empty, are of
-            # the right type.
-            if len(array) > 0 and cls.__name__ is array[0].__class__.__name__:
-                cls = array[0].__class__
-            if array[0].__class__.__name__ != "bytes":
-                array = numpy.select(
-                    [array == item for item in cls],
-                    [item.index for item in cls],
-                ).astype(ENUM_ARRAY_DTYPE)
-            else:
-                array = numpy.select(
-                    [array.astype(str) == item.name for item in cls],
-                    [item.index for item in cls],
-                ).astype(ENUM_ARRAY_DTYPE)
-
-        return EnumArray(array, cls)
+            )
+        elif array.dtype.kind == "O":
+            # Enum items array
+            if len(array) > 0:
+                first_item = array[0]
+                if cls.__name__ == type(first_item).__name__:
+                    # Use the same Enum class as the array items
+                    cls = type(first_item)
+            indices = np.select(
+                [array == item for item in cls],
+                [item.index for item in cls],
+            )
+        elif array.dtype.kind in {"i", "u"}:
+            # Integer array
+            indices = array
+        else:
+            raise ValueError(f"Unsupported array dtype: {array.dtype}")
+
+        return EnumArray(indices.astype(ENUM_ARRAY_DTYPE), cls)