more clear names for methods of Space (#181)

* rename Space.val_matches_space_definition -> contains; Space.is_point_in_space_shape -> valid_index
* rename valid_index -> is_valid_index

rl_coach/spaces.py

@@ -117,9 +117,10 @@ class Space(object):
             if type(self._high) == int or type(self._high) == float:
                 self._high = np.ones(self.shape)*self._high
 
-    def val_matches_space_definition(self, val: Union[int, float, np.ndarray]) -> bool:
+    def contains(self, val: Union[int, float, np.ndarray]) -> bool:
         """
-        Checks if the given value matches the space definition in terms of shape and values
+        Checks if value is contained by this space. The shape must match and
+        all of the values must be within the low and high bounds.
 
         :param val: a value to check
         :return: True / False depending on if the val matches the space definition
@@ -134,16 +135,16 @@ class Space(object):
             return False
         return True
 
-    def is_point_in_space_shape(self, point: np.ndarray) -> bool:
+    def is_valid_index(self, index: np.ndarray) -> bool:
         """
-        Checks if a given multidimensional point is within the bounds of the shape of the space
+        Checks if a given multidimensional index is within the bounds of the shape of the space
 
-        :param point: a multidimensional point
-        :return: True if the point is within the shape of the space. False otherwise
+        :param index: a multidimensional index
+        :return: True if the index is within the shape of the space. False otherwise
         """
-        if len(point) != self.num_dimensions:
+        if len(index) != self.num_dimensions:
             return False
-        if np.any(point < np.zeros(self.num_dimensions)) or np.any(point >= self.shape):
+        if np.any(index < np.zeros(self.num_dimensions)) or np.any(index >= self.shape):
             return False
         return True
 
@@ -160,6 +161,20 @@ class Space(object):
         else:
             return np.random.uniform(self.low, self.high, self.shape)
 
+    def val_matches_space_definition(self, val: Union[int, float, np.ndarray]) -> bool:
+        screen.warning(
+            "Space.val_matches_space_definition will be deprecated soon. Use "
+            "contains instead."
+        )
+        return self.contains(val)
+
+    def is_point_in_space_shape(self, point: np.ndarray) -> bool:
+        screen.warning(
+            "Space.is_point_in_space_shape will be deprecated soon. Use "
+            "is_valid_index instead."
+        )
+        return self.is_valid_index(point)
+
 
 class RewardSpace(Space):
     def __init__(self, shape: Union[int, np.ndarray], low: Union[None, int, float, np.ndarray]=-np.inf,