#13 Add mixins

Author: pockerman

src/utils/mixins.py

@@ -0,0 +1,82 @@
+"""
+Various mixin classes to use for simplifying  code
+"""
+
+import numpy as np
+from typing import TypeVar, Any
+
+QTable = TypeVar('QTable')
+Hierarchy = TypeVar('Hierarchy')
+
+
+class WithHierarchyTable(object):
+
+    def __init__(self) -> None:
+        self.table = {}
+        self.iterators = []
+
+    def add_hierarchy(self, key: str, hierarchy: Hierarchy) -> None:
+        """
+        Add a hierarchy for the given key
+        :param key: The key to attach the Hierarchy
+        :param hierarchy: The hierarchy to attach
+        :return: None
+        """
+        self.table[key] = hierarchy
+
+    def reset_iterators(self):
+        """
+            Reinitialize the iterators in the table
+            :return:
+        """
+
+        # fill in the iterators
+        self.iterators = [iter(self.table[item]) for item in self.table]
+
+    def finished(self) -> bool:
+        """
+        Returns true if the action has exhausted all its
+        transforms
+        :return:
+        """
+        exhausted = True
+
+        for item in self.table:
+            if not self.table[item].is_exhausted():
+                return False
+
+        return exhausted
+
+
+class WithQTableMixin(object):
+    """
+    Helper class to associate a q_table with an algorithm
+     if this is needed.
+    """
+    def __init__(self):
+        # the table representing the q function
+        # client code should choose the type of
+        # the table
+        self.q_table: QTable = None
+
+
+class WithMaxActionMixin(object):
+    """
+    The class WithMaxActionMixin.
+    """
+
+    def __init__(self):
+        super(WithMaxActionMixin, self).__init__()
+        self.q_table: QTable = None
+
+    def max_action(self, state: Any, n_actions: int) -> int:
+        """
+        Return the action index that presents the maximum
+        value at the given state
+        :param state: state index
+        :param n_actions: Total number of actions allowed
+        :return: The action that corresponds to the maximum value
+        """
+        values = np.array(self.q_table[state, a] for a in range(n_actions))
+        action = np.argmax(values)
+        return int(action)