Add observation_function for full custom control over the observation

Lets a game define how its state becomes an observation as a plain
Python function (module:attr), used identically by GameEnvironment
(training) and TrainedPolicy (inference) instead of two independently
maintained encoding paths. Removes the egocentric/egocentric_player/
egocentric_radius flags — cropping is now something an
observation_function does itself by calling egocentric_board(), and
extras_size is discovered from one sampled observation instead of
being configured via observe_state_sizes.

docs/introduction.rst

@@ -100,9 +100,10 @@ matters.
 
 **Observation design** determines what information is available to the
 agent. If you leave a character out of the ``character_set``, the agent
-will not distinguish it from empty space. If the game module defines a
-``get_state()`` function, the agent also receives those computed values
-as part of its observation. The consequences of these choices for what
+will not distinguish it from empty space. If you list keys in
+``observe_state``, the agent also receives those computed values as part
+of its observation — or, for full control, an ``observation_function`` can
+replace the encoding entirely. The consequences of these choices for what
 the agent can learn are reasonably predictable — and making and checking
 those predictions is exactly the kind of reasoning the tool is designed
 to support.