changed termination

EA/constants.py

@@ -7,7 +7,7 @@
 DECKSIZE = 40
 CROSSOVER_RATE = 0.1
 MUTATION_RATE = 0.2
-NUMBER_OF_GENERATIONS = 200
+NUMBER_OF_GENERATIONS = 400
 MATCHES_PER_OPPONENT = '50'  # must be string!
 CARD_POOL = read_card_pool('../AER-POOL-1.txt')
 CARD_POOL_SIZE = len(CARD_POOL)
@@ -18,4 +18,5 @@
 OPPONENTS = ["GB-sealed-opponent.dck", "UWg-sealed-opponent.dck", "UW-sealed-opponent.dck", "BGw-sealed-opponent.dck"]
 EXPERIMENT_TIMESTAMP = datetime.datetime.now().strftime("%d%m%H%M")
 EXPERIMENT_FOLDER = "results/" + EXPERIMENT_TIMESTAMP
+TERMINATION_TRESHOLD = 65
 # CARDS = read_cards_json()

EA/fitness.py

@@ -12,6 +12,9 @@ def build_cmd(candidate_name, opponent_name, nr_matches):
 
 
 def evaluate_deck_by_wins(individual):
+
+    number_of_matches = len(ct.OPPONENTS) * ct.MATCHES_PER_OPPONENT
+
     decklist = genome_to_decklist(individual)
     filename = "candidate.dck"
     write_decklist(ct.CARD_DIRECTORY + filename, decklist)
@@ -25,5 +28,5 @@ def evaluate_deck_by_wins(individual):
                 result = line.split(' ')
         wins += int(result[3])
         p.wait()
-    fitness = wins
+    fitness = (wins / float(number_of_matches)) * 100
     return fitness,  # MUST BE TUPLE!

EA/logger.py

@@ -1,5 +1,3 @@
-import datetime
-
 import matplotlib
 
 import constants as ct
@@ -10,12 +8,8 @@
 
 
 def log_experiment(top_list, median_list, worst_list, global_maximum, time_to_complete, alpha_deck):
-    matches_per_generation = int(ct.MATCHES_PER_OPPONENT) * len(ct.OPPONENTS)
     log_name = ct.EXPERIMENT_TIMESTAMP + '.txt'
     graph_name = ct.EXPERIMENT_TIMESTAMP + '.png'
-    top_list[:] = [(x / float(matches_per_generation)) * 100 for x in top_list]
-    median_list[:] = [(x / float(matches_per_generation)) * 100 for x in median_list]
-    worst_list[:] = [(x / float(matches_per_generation)) * 100 for x in worst_list]
     write_log(top_list, median_list, worst_list, global_maximum, time_to_complete, alpha_deck, log_name)
     write_graph(top_list, median_list, worst_list, graph_name)
     send_mail(['[email protected]', '[email protected]'],

EA/main.py

@@ -103,21 +103,24 @@ def main():
         card_location = ct.EXPERIMENT_FOLDER + "/" + str(gen)
         os.makedirs(card_location)
 
-        counter = 0
-        for solution in population:  # TODO: use enumerate()?
-            write_decklist(card_location + "/" + str(counter) + '.dck', genome_to_decklist(solution))
-            counter += 1
+        for i, solution in enumerate(population):
+            write_decklist(card_location + "/" + str(i) + '.dck', genome_to_decklist(solution))
         fitness_list = [x[0] for x in fits]
         maximum = max(fitness_list)
 
         strongest_individual = tools.selBest(population, k=1)
 
+        median_score = median(fitness_list)
+
         if maximum >= global_maximum:
             global_maximum = maximum
             alpha_deck = strongest_individual
 
+        if median_score >= 65:
+            break
+
         top_list.append(maximum)
-        median_list.append(median(fitness_list))
+        median_list.append(median_score)
         worst_list.append(min(fitness_list))
 
     runtime = (time.time() - start_time)