Refactored

a_player.py

@@ -1,4 +1,5 @@
 import numpy as np
+from state import f_state_slices
 
 
 class APlayer(object):
@@ -14,17 +15,11 @@ class APlayer(object):
 	def set_debug(self, with_debug):
 		pass
 
-	@staticmethod
-	def get_potential_moves(state: np.array) -> np.array:
-		st = state.reshape(state.size)
-		indices = [idx for idx, s in enumerate(st) if '-' in s]
-		return np.array(indices)
-
 	def move(self, state: np.array):
 		return state, False
 
-	def state_from_move(self, state: np.array, field):
-		state.reshape(state.size)[field] = self.mark
+	def to_state(self, state: np.array, move):
+		state.reshape(state.size)[move] = self.mark
 		return state
 
 	def reward(self, value):
@@ -33,39 +28,10 @@ class APlayer(object):
 	def new_game(self):
 		pass
 
-	@staticmethod
-	def f_state_slices():
-		nr = 3
-		nc = 3
-		result = []
-		# Create row finishing states
-		d1 = ()
-		d2_r = ()
-		for r in range(0, nr):
-			d1 += (r,)
-		for c in range(0, nc):
-			d2 = (c,) * nc
-			result.append((d1, d2))
-
-		# Create column finishing states
-		for c in range(0, nc):
-			d2 = (c,) * nc
-			result.append((d2, d1))
-		for c in range(0, nc):
-			d2_r += (nc - c - 1,)
-
-		# Create diagonal finishing states #1
-		result.append((d1, d1))
-
-		# Create diagonal finishing states #2
-		result.append((d1, d2_r))
-
-		return result
-
 	def has_won(self, state: np.array):
 		result = False
 		ref = [self.mark, self.mark, self.mark]
-		for f_state_slice in APlayer.f_state_slices():
+		for f_state_slice in f_state_slices():
 			if np.all(state[f_state_slice] == ref):
 				result = True
 				break