Log.printString('\nEpoch Win totals for this generation: ' + str(epoch_win) +
'\n',
log_path,
access="a")
exportGenPerformance(gen_number, epoch_win)
print(epoch_win, '\n')
if gen_number >= 0:
df_training.to_csv(output_dir + 'Generation_' + str(gen_number) + '.csv',
index=False,
quotechar='"',
quoting=csv.QUOTE_NONNUMERIC)
else:
df_training.to_csv(output_dir + 'StartGeneration.csv',
index=False,
quotechar='"',
quoting=csv.QUOTE_NONNUMERIC)
if gen_number >= 0:
shutil.copyfile(
'C:/Users/akami/Documents/GitHub/Projects/BlackJackNeuralNetwork/TrainingData/GenerationFiles/ModelFiles/epoch_'
+ str(indexOfGreatest(epoch_win)) + '.h5',
'C:/Users/akami/Documents/GitHub/Projects/BlackJackNeuralNetwork/TrainingData/Corpus/ModelFiles/Generation_'
+ str(gen_number) + '.h5')
log_str = 'The Script has finished at ' + str(time.asctime(
time.localtime())) + '\nRuntime: ' + Log.secToHour(
time.time() - start_time, inLine=False)
log_str += 'Length of Output: ' + str(len(df_training)) + '\n'
Log.printString(log_str, log_path, access="a", buffer=True)
if last_scenario.WinLoss == 1:
log.printString('\tThis Scenario has won\n', log_path, access='a')
else:
log.printString('\tThis Scenario has lost\n', log_path, access='a')
scenarios = scenarios + output
log_str = 'Scenario ' + str(i) + ' has completed\n'
if wl_stats[0] + wl_stats[1] > 0:
log_str += '\t- The model has a win percentage of ' + str(
100 * wl_stats[0] / (wl_stats[0] + wl_stats[1])) + ' %\n'
log_str += '\t- Wins: ' + str(wl_stats[0]) + '\tLoses: ' + str(
wl_stats[1]) + '\tTies: ' + str(wl_stats[2])
log.printString('\t- ' + log_str + '\n', log_path, access='a')
df_out.to_csv(out_path, index=False)
script_end = time.time()
log_str = '\nScript has completed at ' + str(time.asctime(
time.localtime())) + '\nThe script took ' + str(
log.secToHour(script_end - script_start, inLine=True)) + '\n'
if wl_stats[0] + wl_stats[1] > 0:
log_str += 'The model has a win percentage of ' + str(
100 * wl_stats[0] / (wl_stats[0] + wl_stats[1])) + ' %\n'
else:
log_str += 'The model has a win percentage of 0%\n'
log_str += 'Wins: ' + str(wl_stats[0]) + '\tLoses: ' + str(
wl_stats[1]) + '\tTies: ' + str(wl_stats[2]) + '\n'
log.printString(log_str, log_path, access='a', buffer=True)
#print('Wins: ' + str(wl_stats[0]) + '\tLoses: ' + str(wl_stats[1]) + '\tTies: ' + str(wl_stats[2]) +'\n')
try:
os.remove(out_path)
except Exception as ex:
pass
df = pd.DataFrame()
cardDeck = CardDeck(num_deck)
TotalCount = 0
for i in range(num_training):
log.printString('\nTraining Number ' + str(i) + ':\n', log_path, access='a')
if (cardDeck.NumDeck * 52) - cardDeck.currentCard <= 20:
cardDeck.shuffleCards()
TotalCount = 0
df_out = playIteration( cardDeck, TotalCount )
TotalCount = df_out.iloc[0].TotalCount
df = df.append(df_out, ignore_index= True)
log.printString( log.logDf(df), log_path, access='a' )
df.to_csv(out_path, index= False)
end_time = time.time()
log_str = 'The Script has finished running at ' + str(time.asctime(time.localtime())) + '\nThe runtime was ' + log.secToHour( end_time - start_time, inLine= True) + '\n'
log_str += 'Win Percentage: ' + str(100 * wl_stats[0] / (wl_stats[0] + wl_stats[1])) + ' %\n'
log_str += 'Wins: ' + str(wl_stats[0]) + '\tLosses: ' + str(wl_stats[1]) + '\tTies: ' + str(wl_stats[2]) + '\n'
log.printString( log_str, log_path, access='a', buffer=True)
#print('Wins: ' + str(wl_stats[0]) + '\tLosses: ' + str(wl_stats[1]) + '\tTies: ' + str(wl_stats[2]) + '\n')