def resolve_hands(p, g):
"""Check who has strongest hand and divide the pot accordingly
:param p: List of players to resolve the winner
:param g: Game object
:return:
"""
# take five additional cards from the deck
# add them to users hand
for c in range(5):
new_card = g.deck.draw_card()
for player in p:
player.hand.add_card(new_card)
# sort the hands
for pl in p:
pl.hand.sort()
print("Resolving player hands")
g.render_game()
# get the absolute score of the hand and the best five cards
results = []
for player in p:
results.append(Game.score(player.hand))
for i in range(g.p.__len__()):
print(g.p[i].name, "has", g.name_of_hand(results[i][0]))
# select the winner
winners = Game.determine_winner(results)
# award the pot to the winner
if winners.__len__() > 1:
# split the pot
print("No winner - split the pot")
g.split_the_pot()
else:
print(p[winners[0]].name, "has taken the pot")
print(p[winners[0]].name, "gained", min(p[winners[0]].bet * 2, g.pot))
g.player_won(p[winners[0]])
def main(p1, p2, num_of_games, num_of_chips):
import time
start_time = time.time()
# [0] player1 won accumulator, [1] player2 won accumulator
stats = [0, 0]
game_lengths_won_by_p1 = [0]
game_lengths_won_by_p2 = [0]
# successful bluff is when p1 is when SB goes all-in, and opponent folds, but would have won if called
bluffs_p1 = [0, 0]
bluffs_p2 = [0, 0]
if "n" in [p1, p2]:
neural_npc = NeuralNetworkNPC()
else:
neural_npc = None
if "q" in [p1, p2]:
q_table_npc = QtableNPC()
else:
q_table_npc = None
for games in range(num_of_games):
# q - indicate q-table, indicate
game = Game(player_types[p1],
player_types[p1],
player_types[p2],
player_types[p2],
bank=num_of_chips)
if random() > 0.5:
game.end_round()
game_length = 0
while not game.done:
if game.a_player().bank <= 0 or game.na_player().bank <= 0:
game.done = True
break
else:
game.render_game()
print(game.p[game.turn].name + " is small blind")
print("Placing blinds")
game.place_blinds()
game.render_game()
game.players_draw_cards()
current_player_index = game.turn
result = small_blind(game.p[game.turn],
game,
neural_model_npc=neural_npc,
q_table_npc=q_table_npc)
game.next_player()
if result:
result = big_blind(game.p[game.turn],
game,
neural_model_npc=neural_npc,
q_table_npc=q_table_npc)
if result:
resolve_hands(game.p, game)
else:
# bluff?
results = []
community_cards = []
for i in range(5):
community_cards.append(game.deck.draw_card())
for ep in game.p:
hand = copy.deepcopy(ep.hand)
hand.cards.extend(community_cards)
hand.sort()
results.append(Game.score(hand))
# select the winner
winners = Game.determine_winner(results)
if winners[0] == current_player_index:
if current_player_index == 0:
bluffs_p1[0] += 1
else:
bluffs_p2[0] += 1
if current_player_index == 0:
bluffs_p1[1] += 1
else:
bluffs_p2[1] += 1
game.opponent_folded(game.na_player())
else:
game.opponent_folded(game.a_player())
game.new_step()
print()
game_length += 1
# region End game
if game.done:
if game.p[0].bank > game.p[1].bank:
stats[0] += 1
game_lengths_won_by_p1.append(game_length)
else:
stats[1] += 1
game_lengths_won_by_p2.append(game_length)
for pl in game.p:
pl.bank += pl.bet
pl.bet = 0
if game.a_player().bank <= 0:
pl = game.na_player()
else:
pl = game.a_player()
s = pl.name + " has won the game with "
s += str(pl.bank) + " coins"
print(s)
print('\n')
# endregion
print(stats)
print("In total: Player1[" + player_types[p1] + "] has won " +
str(stats[0]))
print("In total: Player2[" + player_types[p2] + "] has won " +
str(stats[1]))
if len(game_lengths_won_by_p1) > 1:
print("Average game length when Player1[" + player_types[p1] +
"] has won " + str(
round(
sum(game_lengths_won_by_p1) /
len(game_lengths_won_by_p1), 2)))
if len(game_lengths_won_by_p2) > 1:
print("Average game length when Player2[" + player_types[p2] +
"] has won " + str(
round(
sum(game_lengths_won_by_p2) /
len(game_lengths_won_by_p2), 2)))
print("Successful bluffs by Player1[" + player_types[p1] + "] " +
str(bluffs_p1[0]) + " / " + str(bluffs_p1[1]))
print("Successful bluffs by Player2[" + player_types[p2] + "] " +
str(bluffs_p2[0]) + " / " + str(bluffs_p2[1]))
print("time elapsed: {:.2f}s".format(time.time() - start_time))