Added plotting of rewards

MutateActions/main.py

 from population import Population
 import time
 import matplotlib.pyplot as plt
+import pickle
 
 INCREASE_BY = 5
 BRAIN_SIZE = 50
 POP_SIZE = 50
-MUTATION_FACTOR = 0.1  # 0 <= x <= 1
+MUTATION_FACTOR = 0.2  # 0 <= x <= 1
 GAME_CANCELLED = False
-LOAD_BRAIN = True
+LOAD_BRAIN = False
 RENDER_BEST = False
+TEST_WALKER = True
+
+if TEST_WALKER:
+    LOAD_BRAIN = True
+
 
 if __name__ == '__main__':
     population = Population(POP_SIZE, BRAIN_SIZE,MUTATION_FACTOR, LOAD_BRAIN, RENDER_BEST)
 
+    rewards = []
+
+    if TEST_WALKER:
+        rewards = []
+        with open('rewards.p', 'rb') as fp:
+            rewards = pickle.load(fp)
+        plt.title(f'{POP_SIZE}, {MUTATION_FACTOR}')
+        plt.xlabel('Episodes')
+        plt.ylabel('Rewards')
+        plt.plot(rewards)
+        plt.savefig(f'./models/{POP_SIZE}, {MUTATION_FACTOR}.png')
+        plt.show()
+
     while GAME_CANCELLED is False:  # this is our game
+
         if population.all_players_finished():  # this is our genetic algorithm after one generation of players
             population.natural_selection()
             population.mutate_babies()
@@ -24,6 +44,12 @@ if __name__ == '__main__':
             print(f'Best Index: {population.best_walker_index}')
             print(f'Best Fitness: {population.fitnesses[population.best_walker_index]}')
             print(f'Max Steps: {population.max_steps}')
+
+            rewards.append(population.fitnesses[population.best_walker_index])
+
+            if population.gen % 10 == 0:
+                with open("rewards.p", 'wb') as fp:
+                    pickle.dump(rewards, fp)
         else:
             population.update()
         # time.sleep(0.1)