def appendScenarioData(scenario_lst):
for scenario in scenario_lst:
df = df.append(scenario.toDict(), ignore_index=True)
df.to_csv(out_path, index=False)
log.printString('\t- Dataframe has been successfully printed\n',
log_path,
access='a')
def performDecision( current_scenario, cardDeck, firstTurn=False, log_str='' ):
# Initialize Variables
playerTurn = True
printLog = False
# New Scenario
if firstTurn:
# Deal cards to Player, Dealer and Player
current_scenario.dealCard(cardDeck)
current_scenario.dealCard(cardDeck, player=False)
current_scenario.dealCard(cardDeck)
# Make decision based on playerHand
current_scenario.makeDecision()
log_str += '\tcurrent scenario:\n' + log.logDict(current_scenario.toDict(), buffer='\t')
new_scenario = current_scenario.copy()
playerTurn = new_scenario.processDecision(cardDeck)
scenario_lst = []
if playerTurn and current_scenario.decision == 4: # Split
scenario_0 = current_scenario[0]
scenario_1 = current_scenario[1]
"""
current_scenario = [scenario_0, performDecision(scenario_0.copy())]
scenario_1.TotalCount = current_scenario[-1].TotalCount
card = cardDeck.dealCard()
scenario_1['PlayerHand'].append(card)
current_scenario = [current_scenario[0]] + performDecision(current_scenario[0]) + [current_scenario[1]] + performDecision(current_scenario[1])
"""
elif playerTurn:
scenario_lst = performDecision(new_scenario.copy(), cardDeck, log_str=log_str, firstTurn=False) + [current_scenario.copy()]
elif not playerTurn:
printLog = True
scenario_lst = [current_scenario.copy()]
log_str += '\tPlayer\'s turn has ended\n'
if printLog:
log.printString(log_str, log_path, access='a', buffer=True)
return scenario_lst
def performAction(model, current_scenario, cardDeck):
printLog = False
current_scenario.dealCard(cardDeck, player=True)
current_scenario.dealCard(cardDeck, player=False)
current_scenario.dealCard(cardDeck, player=True)
log_str = 'The Player has received 2 cards and the Dealer has received 1:\n' + log.logDict(
current_scenario.toDict()) + '\n'
prediction = model.predict(prepTrainData(current_scenario))
log_str += '\n=========================\nPrediction:\t' + str(
prediction) + '\nDecide Action:\t' + str(
decideAction(prediction)) + '\n=========================\n'
current_scenario.importDecision(decideAction(prediction), cardDeck)
new_scenario = current_scenario.copy()
playerTurn = new_scenario.processDecision(cardDeck)
log_str += 'The Player decision has been processed:\n' + log.logDict(
current_scenario.toDict()) + '\n'
scenario_lst = []
if playerTurn and current_scenario.decision == 4: # Split
scenario_0 = current_scenario[0]
scenario_1 = current_scenario[1]
elif playerTurn:
scenario_lst = performAction(model, new_scenario.copy(),
cardDeck) + [current_scenario.copy()]
elif not playerTurn:
printLog = True
# Deal cards to dealer
while current_scenario.getHandValue(cardDeck, player=False) < 17:
current_scenario.dealCard(cardDeck, player=False)
scenario_lst = [new_scenario.copy()]
if printLog:
log.printString(log_str, log_path, access='a')
return scenario_lst
def getOutcome(scenario, cardDeck):
if scenario.getHandValue(cardDeck, player=True) > 21: # Player busts: Loss
return -1
elif scenario.getHandValue(cardDeck, player=False) > 21: # Dealer busts: Win
return 1
elif scenario.getHandValue(cardDeck, player=True) > scenario.getHandValue(cardDeck, player=False): # Player beats dealer: Win
return 1
elif scenario.getHandValue(cardDeck, player=True) < scenario.getHandValue(cardDeck, player=False): # Dealer beats player: Loss
return -1
elif scenario.getHandValue(cardDeck, player=True) == scenario.getHandValue(cardDeck, player=False):
return 0
else:
print(scenario.toDict())
raise Exception('Outcome undetermined: ' + log.logDict(scenario.toDict()) + '\n')
def playIteration( cardDeck, TotalCount ):
df = pd.DataFrame()
scenarios = []
log_str = ''
current_scenario = scenario(count=TotalCount, dealercard=0, playerhandvalue=0,
numaces=0, numplayercards=0, dec=0, winloss=-999,
correctdecision=[0,0,0,0], playerhand=[], dealerhand=[])
scenario_lst = performDecision(current_scenario, cardDeck, firstTurn=True)
if isinstance(scenario_lst[0], scenario):
# Dealer gets second card
scenario_lst[0].dealCard(cardDeck, player=False)
while scenario_lst[0].getHandValue(cardDeck, player=False) < 17:
scenario_lst[0].dealCard(cardDeck, player=False)
for i in range(1, len(scenario_lst)):
scenario_lst[i].DealerHand = scenario_lst[0].DealerHand
output = getCorrectDecision(scenario_lst[0], cardDeck)
scenarios = scenarios + output
else:
raise Exception('performDecision returned incorrect data type: list<list>\n')
for s in scenarios:
if DEBUG:
df = df.append(s.toDict(), ignore_index=True)
else:
log_str += '\tPlayerHand and DealerHand fields have been removed\n'
df = df.append(s.toDict(), ignore_index=True)
log.printString(log_str, log_path, access='a')
return df
def generateCorrectDecision(self, last_scenario, cardDeck):
self.getHandValue(cardDeck) # update PlayerHandValue
if self.PlayerHandValue >= 20: # Player Busts
self.CorrectDecision = [0, 1, 0, 0]
elif last_scenario != None and last_scenario.PlayerHandValue > 21 and len(
self.PlayerHand) + 1 == len(
last_scenario.PlayerHand
): # Not Last Scenario and Player Busts Next
self.CorrectDecision = [0, 1, 0, 0]
# Not Last Scenario, Player Double Down and Lose to Dealer
elif last_scenario == None and self.getHandValue(
cardDeck, player=False) > 21: # Dealer Busts and Last Scenario
self.CorrectDecision = [0, 1, 0, 0]
elif dd_allow and last_scenario != None and last_scenario.getHandValue(
cardDeck, player=False
) > 21 and self.NumPlayerCards == 3: # Dealer Busts, not Last Scenario, and 2 cards
self.CorrectDecision = [1, 0, 1, 0]
elif last_scenario != None and last_scenario.getHandValue(
cardDeck, player=False
) > 21 and self.NumPlayerCards == 3: # Dealer Busts, not Last Scenario, and 2 cards
self.CorrectDecision = [1, 0, 0, 0]
elif last_scenario != None and last_scenario.getHandValue(
cardDeck, player=False
) > 21: # Dealer Busts, not Last Scenario, and not 2 cards
self.CorrectDecision = [
0, 1, 0, 0
] if self.decision == 0 else self.toCorrectDecision()
elif last_scenario == None and self.getHandValue(
cardDeck, player=False
) > self.PlayerHandValue: # Dealer beats player and Last Scenario
self.CorrectDecision = [1, 0, 0, 0]
elif last_scenario != None and last_scenario.getHandValue(
cardDeck, player=False
) > last_scenario.PlayerHandValue: # Dealer beats player and Not last Scenario
self.CorrectDecision = [
1, 0, 0, 0
] if self.decision == 0 else self.toCorrectDecision(self.decision)
elif last_scenario == None and self.PlayerHandValue == self.getHandValue(
cardDeck, player=False
) and self.PlayerHand != 20: # Dealer ties player and Last Scenario
self.CorrectDecision = [1, 0, 0, 0]
elif last_scenario != None and last_scenario.PlayerHandValue == last_scenario.getHandValue(
cardDeck, player=False
) and self.PlayerHand != 20: # Dealer ties Player and Not Last Scenario
self.CorrectDecision = [
1, 0, 0, 0
] if self.decision == 0 else self.toCorrectDecision(self.decision)
elif last_scenario == None and self.PlayerHandValue > self.getHandValue(
cardDeck,
player=False): # Dealer loses Player and Last Scenario
self.CorrectDecision = [
0, 1, 0, 0
] if self.decision == 0 else self.toCorrectDecision(self.decision)
elif dd_allow and last_scenario != None and last_scenario.PlayerHandValue > last_scenario.getHandValue(
cardDeck, player=False
) and self.NumPlayerCards == 3: # Dealer loses Player, Not Last Scenario and 2 cards
self.CorrectDecision = [1, 0, 1, 0]
elif last_scenario != None and last_scenario.PlayerHandValue > last_scenario.getHandValue(
cardDeck, player=False
) and self.NumPlayerCards == 3: # Dealer loses Player, Not Last Scenario and 2 cards
self.CorrectDecision = [1, 0, 0, 0]
elif last_scenario != None and self.PlayerHandValue > self.getHandValue(
cardDeck, player=False
): # Dealer loses Player, Not Last Scenario and not 2 cards
self.CorrectDecision = [0, 1, 0, 0]
else:
log.printString(
str(self.toDict()) + '\n',
'C:/Users/akami/Documents/GitHub/Projects/BlackJackNeuralNetwork/Log/MissingScenario.log',
access='a',
buffer=True)
model.add(Dense(2, activation='sigmoid')) # final layer
# model.add(Dense(1, activation='sigmoid')) # final layer
model.compile(loss='binary_crossentropy', optimizer='sgd')
log_str += 'Neural Network has been built\n'
else:
model = keras.models.load_model(
'C:/Users/akami/Documents/GitHub/Projects/BlackJackNeuralNetwork/TrainingData/GenerationFiles/ModelFiles/epoch_'
+ str(epoch_num) + '.h5')
model.fit(train_X, train_Y, epochs=32, batch_size=256, verbose=1)
model.save(
'C:/Users/akami/Documents/GitHub/Projects/BlackJackNeuralNetwork/TrainingData/GenerationFiles/ModelFiles/epoch_'
+ str(epoch_num) + '.h5')
log_str += 'Neural Network has been trained\nThere will be ' + str(
num_scenario) + ' ran\n===============================\n\n'
log.printString(log_str, log_path, access='w')
cardDeck = CardDeck(num_decks)
TotalCount = 0
scenarios = []
df_out = pd.DataFrame()
for i in range(num_scenario):
log_str = 'Scenario ' + str(
i) + ':\n==============================================\n'
if (cardDeck.NumDeck * 52) - cardDeck.currentCard >= 20:
cardDeck.shuffleCards()
TotalCount = 0
log_str += '\t- Deck Shuffled\n'
df = pd.read_csv(
'C:/Users/akami/Documents/GitHub/Projects/BlackJackNeuralNetwork/TrainingData/Corpus/Log/Generation_Performance.csv',
dtype=str)
df = df.append(dic, ignore_index=True)
else:
df = pd.DataFrame.from_dict(dic)
df.to_csv(
'C:/Users/akami/Documents/GitHub/Projects/BlackJackNeuralNetwork/TrainingData/Corpus/Log/Generation_Performance.csv',
index=False,
)
start_time = time.time()
Log.printString('The Script has started at ' +
str(time.asctime(time.localtime())) + '\n',
log_path,
access="w",
buffer=True)
epoch_win = []
df_training = pd.DataFrame()
for path in glob.glob(os.path.join(input_dir, 'epoch_*.csv')):
df_temp = pd.read_csv(path, dtype=str)
num_games = len(df_temp)
log_str = 'File: ' + path + '\n\tLength: ' + str(num_games) + '\n'
df_temp.WinLoss = df_temp.WinLoss.astype(float).astype(int)
calc_win = len(df_temp[df_temp.WinLoss > 0]) / (
len(df_temp[df_temp.WinLoss > 0]) + len(df_temp[df_temp.WinLoss < 0]))
print(df_temp.WinLoss.value_counts())
if DEBUG:
df = df.append(s.toDict(), ignore_index=True)
else:
log_str += '\tPlayerHand and DealerHand fields have been removed\n'
df = df.append(s.toDict(), ignore_index=True)
log.printString(log_str, log_path, access='a')
return df
# =============================================
# Main
# =============================================
if __name__ == "__main__":
start_time = time.time()
log.printString('Training Started at ' + str(time.asctime(time.localtime())) + '\n', log_path, access='w', buffer=True)
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: