def generateNNTrainingData(policy, state_potentials, new_training_title,
n_trials):
labelout = open("training/" + new_training_title, "a")
sys.stdout.write('Generating training data')
sys.stdout.flush()
for x in range(0, n_trials):
sheet, roll, n_rerolls = sample_gamespace(policy.choose_dice,
policy.choose_category)
opt_move = optimal_strategy.queryMove(state_potentials,
sheet.as_bitmask(),
roll.as_list(), n_rerolls)
labeled_one_hot = None
labelout.write(sheet.as_csv() + "," + roll.as_string() + "," +
str(n_rerolls) + ",")
try:
best_category = YahtzeeScoresheet.categories[opt_move]
labelout.write(best_category + ",")
labeled_one_hot = label.build_one_hot(opt_move, 13)
except (ValueError, TypeError) as e:
kept_dice = Roll(opt_move)
labelout.write("[" + kept_dice.as_string() + "],")
labeled_one_hot = label.find_macro(kept_dice, roll, sheet,
n_rerolls)
labelout.write(labeled_one_hot + "\n")
if x % 1000 == 0:
sys.stdout.write('.')
sys.stdout.flush()
labelout.close()
def generate_training_data(self, n_trials, all_data):
for x in range(0, n_trials):
current_line = ""
sheet, roll, n_rerolls = sample_gamespace(self.choose_dice,
self.choose_category)
opt_move = optimal_strategy.queryMove(self.state_potentials,
sheet.as_bitmask(),
roll.as_list(), n_rerolls)
labeled_one_hot = None
current_line = sheet.as_csv() + "," + roll.as_string() + "," + str(
n_rerolls) + ","
try: # assume in this situation you choose a category to score in
best_category = YahtzeeScoresheet.categories[opt_move]
current_line += best_category + ","
labeled_one_hot = label.build_one_hot(lookup_macro[opt_move],
10)
except (ValueError, TypeError) as e:
kept_dice = Roll(opt_move)
current_line += "[" + kept_dice.as_string() + "],"
labeled_one_hot = label.find_macro(kept_dice, roll, sheet,
n_rerolls)
current_line += labeled_one_hot + "\n"
all_data.append(current_line)