def execute(self):
if self.__on_init() == False:
self.__running = False
champfactory = ChampionFactory()
## Simulates champion select:
comp_champ = champfactory.create_champion('viking', self.__comp_rect,
self.__ground)
player_champ = champfactory.create_champion('samurai',
self.__player_rect,
self.__ground)
self.__computer = Computer(champion=comp_champ)
self.__player = Player(champion=player_champ, name="Player1")
self.__computer.setRival(self.__player.getChampion())
self.__player.setRival(self.__computer.getChampion())
clock = pygame.time.Clock()
while (self.__running):
if not USE_PYGAME_CLOCK:
clock.tick(PYGAME_FPS)
else:
clock.tick()
self.__on_loop()
self.__on_render()
for event in pygame.event.get():
self.__on_event(event)
self.__on_cleanup()
def cal(phase):
result = 0
for value in phase:
A = Computer(program, [value, result])
A.execute()
result = A.outputs[0]
return result
def add_product():
""" Adds a product to products """
content = request.json
try:
id = None
type = None
product = None
if content["type"] == AbstractProduct.CELLPHONE_TYPE:
cellphone = Cellphone(content['name'], content['price'],
content['cost'], content["date_stocked"],
content["date_sold"], content["is_sold"],
content["camera"], content["security"],
content["screen_body_ratio"])
prod_manager.add_product(cellphone)
id = cellphone.get_id()
type = cellphone.get_type()
product = cellphone
elif content["type"] == AbstractProduct.COMPUTER_TYPE:
computer = Computer(content["name"], content["price"],
content["cost"], content["date_stocked"],
content["date_sold"], content["is_sold"],
content["graphics_card"], content["case"],
content["memory_type"])
prod_manager.add_product(computer)
id = computer.get_id()
type = computer.get_type()
product = computer
print("id = ", id)
print("type = ", type)
print("prod = ", product.to_dict())
response = app.response_class(status=200)
except ValueError as e:
response = app.response_class(response=str(e), status=400)
return response
def part2(file):
debug = True
buffer = deque()
def chr_output(value):
buffer.append(chr(value))
def chr_input():
return ord(buffer.popleft())
program = parse_program(file)
computer = Computer(program, int_input, chr_output)
computer.run()
view = list(map(str.strip, ''.join(buffer).strip().split('\n')))
height = len(view)
width = len(view[0])
robot = find_robot(view)
steps = build_steps(robot, view)
actions, procedures = compact(steps)[-1]
actions = ','.join('ABC'[i] for i in actions) + '\n'
buffer.clear()
buffer.extend(actions)
for procedure in procedures:
buffer.extend(procedure + '\n')
buffer.extend(('y' if debug else 'n') + '\n')
map_buffer = [[]]
map_buffer_offset = height + 7
def map_output(value):
nonlocal map_buffer
nonlocal map_buffer_offset
if value > 255:
print(value)
return
c = chr(value)
if map_buffer_offset > 0:
sys.stdout.write(c)
if c == '\n':
map_buffer_offset -= 1
return
map_buffer[-1].append(c)
if c == '\n':
map_buffer.append([])
return
if len(map_buffer) > height:
cur_buffer, map_buffer = map_buffer[:-1], map_buffer[-1:]
sys.stdout.write(''.join(''.join(s) for s in cur_buffer))
computer = Computer(program, chr_input, map_output)
computer.set(0, 2)
computer.run()
def main(player_first = True):
WIDTH = 3
HEIGHT = 3
board = Board(WIDTH, HEIGHT)
interaction = Interaction(WIDTH, HEIGHT)
computer = Computer()
turn = 'X'
if player_first:
computer_tile = 'O'
else:
computer_tile = 'X'
while board.get_winner() is None and not board.is_cat_game():
if turn == computer_tile:
x, y = computer.get_move(board, computer_tile)
board.place_tile(turn, x, y)
else:
x, y = interaction.get_move(turn, board)
board.place_tile(turn, x, y)
if turn == 'X':
turn = 'O'
else:
turn = 'X'
if board.is_cat_game():
interaction.display_cat_game(board)
else:
interaction.display_winner(board, board.get_winner() != computer_tile)
def __init__(self, addr, program, network):
self._addr = addr
self._computer = Computer(program, self._processInput, self._output)
self._network = network
self._processing = None
self._write_buffer = []
self._inputMode = 0
def run():
pile = Deck.standard_deck()
pile.shuffle()
player_hand = Hand("Player")
computer_hand = Hand("Computer")
player = Player()
computer = Computer()
while not player.stopped:
if player_stops():
player.stop()
else:
player.draw(player_hand, pile)
print(player_hand)
if RuleSet.sums_to_21(player_hand) or RuleSet.is_bust(player_hand):
break
print("---------")
print("Total: {0}".format(player_hand.sum()))
computer.play(computer_hand, pile, player_hand)
print("\n=== WINNER ===")
print("---------")
winning_hand = RuleSet().determine_winner(computer_hand, player_hand)
if RuleSet.sums_to_21(winning_hand):
print("{0} got 21".format(winning_hand.holder))
else:
print("{0} won ({1})".format(winning_hand.holder, winning_hand.sum()))
def __init__(self, computer, resource_response):
ip = computer.ip_address
port = computer.port
Computer.__init__(self, ip, port)
self.resource_response = resource_response
self.task_to_solve = None
self.work_response = None
def intcode(library, program):
""" Create an IntCode Computer """
computer = Computer(library, program)
computer.flash_memory()
return computer
def main():
# updated input
input = "1,0,0,3,1,1,2,3,1,3,4,3,1,5,0,3,2,1,9,19,1,10,19,23,2,9,23,27,1,6,27,31,2,31,9,35,1,5,35,39,1,10,39,43,1,10,43,47,2,13,47,51,1,10,51,55,2,55,10,59,1,9,59,63,2,6,63,67,1,5,67,71,1,71,5,75,1,5,75,79,2,79,13,83,1,83,5,87,2,6,87,91,1,5,91,95,1,95,9,99,1,99,6,103,1,103,13,107,1,107,5,111,2,111,13,115,1,115,6,119,1,6,119,123,2,123,13,127,1,10,127,131,1,131,2,135,1,135,5,0,99,2,14,0,0"
inputList = [int(d) for d in input.split(",")]
# part A
inputA = inputList.copy()
inputA[1] = 12
inputA[2] = 2
computerA = Computer(inputA)
outputA = computerA.run()
print(f"Part a: {next(outputA)[0]}")
# part B
for noun, verb in product(range(0, 100), range(0, 100)):
inputB = inputList.copy()
inputB[1] = noun
inputB[2] = verb
outputB = Computer(inputB).run()
if next(outputB)[0] == 19690720:
print(
f"noun is {noun}, verb is {verb}, the number seeked (100*noun + verb) is: {100*noun + verb}"
)
break
def game():
board = [i for i in range(10)]
print("Press 0 at any time to quit")
h = input("If you want to go first enter X, otherwise enter O ")
c = 'O'
if h == "0":
quit()
elif h.upper() == "O":
h, c = 'O', "X"
else:
h = "X"
comp = Computer(c, h)
# Human move if Human is X
if h == "X":
print_board(board)
board = m(board, h)
while board is not 0:
# Computer move
board = comp.make_move(board)
if board == 0:
break
# Human move
board = m(board, h)
def solve_part_one() -> int:
"""Uncomment the `print` statements to see how the beam looks on a plane."""
with open("19_input", "r") as f:
program: List[int] = [int(code) for code in f.read().split(",")]
x_min = 0
x_max = 50 # excluding x_max
y_min = 0
y_max = 50 # excluding y_max
affected_field_count = 0
for y in range(y_min, y_max):
# print(f"{y}: ", end="")
for x in range(x_min, x_max):
drone = Computer(opcodes=program.copy(), inputs=[x, y])
drone.solve()
# drone.inputs will contain the output of the program;
# 0 - no effect, 1 - affected field
affected_field_count += drone.inputs[-1]
# print("." if drone.inputs[-1] == 0 else "#", end="")
# print()
return affected_field_count
def engine_stop(self, engine_id):
"""Stop a specific engine"""
# delete computer information in db
DrQueueComputer.delete_from_db(engine_id)
# shutdown computer
self.ip_client.shutdown(engine_id)
return True
def part2(state):
TARGET = 19690720
for noun, verb in itertools.product(range(100), repeat=2):
comp = Computer(state, mem_override={1: noun, 2: verb})
comp.run()
if comp.mem0 == TARGET:
return 100 * noun + verb
def build_computer(cpu, ram, motherboard):
computer = Computer()
computer.motherboard = motherboard
computer.cpu = cpu
computer.ram = ram
return computer
def mouse_clicked(self, evt):
if evt.y <= 0:
return
for i in range(len(self.SQUARE_COORDINATES)):
if ((evt.x <= self.SQUARE_COORDINATES[i]['bottom_right_corner_x'])
and (evt.y <=
self.SQUARE_COORDINATES[i]['bottom_right_corner_y'])):
self.draw_text(i, self.SQUARE_COORDINATES[i]['letter_x'],
self.SQUARE_COORDINATES[i]['letter_y'])
break
if self.game_has_a_winner():
messagebox.showinfo('The Xs win!', 'The Xs win!')
self.reset()
return
elif self.game_is_a_draw():
messagebox.showinfo('Draw', 'This game is a draw')
self.reset()
return
computer = Computer(self.squares)
messagebox.showinfo('Computer Message', computer.message())
i = computer.square()
self.draw_text(i, self.SQUARE_COORDINATES[i]['letter_x'],
self.SQUARE_COORDINATES[i]['letter_y'])
if self.game_has_a_winner():
messagebox.showinfo('The Os win!', 'The Os win!')
self.reset()
elif self.game_is_a_draw():
messagebox.showinfo('Draw', 'This game is a draw')
self.reset()
def get_intersection(code):
computer = Computer(code, [])
computer.run()
x = 0
y = 0
sum_alignment = 0
items = defaultdict(list)
for ascii_item in computer.get_whole_output():
if ascii_item == 10:
y += 1
print()
else:
x += 1
items[y].append(ascii_item)
print(chr(ascii_item), end='')
# check for intersections
sum_alignment = 0
num_intersections = 0
for x in range(len(items[0])):
for y in range(len(items.keys())):
if x > 0 and x < len(items[0]) - 1:
if y > 0 and y < len(items.keys()) - 1:
if chr(items[y][x]) == '#' and chr(
items[y - 1][x]) == '#' and chr(
items[y + 1][x]) == '#' and chr(
items[y][x - 1]) == '#' and chr(
items[y][x + 1]) == '#':
num_intersections += 1
sum_alignment += x * y
print("Star 1: Sum of alignment:", sum_alignment)
def __init__(self):
"""Initialize the board as a nested array, specifying four tiles
in the middle"""
self.grid = Grid(600, 600, 100)
self.WIDTH = self.grid.SPACING * 0.85
self.HEIGHT = self.grid.SPACING * 0.85
self.computer = Computer(self)
self.row = self.grid.HEIGHT // self.grid.SPACING
self.col = self.grid.WIDTH // self.grid.SPACING
self.full_tile = self.row * self.col
self.full = False
self.tile = [[0] * self.col for i in range(self.row)]
# Initialize starting four tiles.
# 1 stands for black tile
# 2 stands for white tile
self.tile[self.row // 2 - 1][self.col // 2 - 1] = 2
self.tile[self.row // 2][self.col // 2] = 2
self.tile[self.row // 2 - 1][self.col // 2] = 1
self.tile[self.row // 2][self.col // 2 - 1] = 1
self.black_tile = 2
self.white_tile = 2
self.counter = 1 # Indicate whether player or AI's turn
self.legal_move = False
self.flip_tiles = []
self.interval = 2000
self.over = False
self.text_position_x = self.grid.WIDTH / 2 - 100
self.text_position_y = self.grid.HEIGHT / 2
def main():
to_guess = input("Numero a adivinar: ")
computer = Computer(to_guess)
while computer.game.check_win():
computer.play()
print("\nNumero adivinado por la computadora: ",computer.getNumber())
print("Se ha terminado en ",computer.game.get_tries()," intentos")
class TestComputer(unittest.TestCase):
WIDTH = 3
HEIGHT = 3
def setUp(self):
self.computer = Computer()
self.board = Board(self.WIDTH, self.HEIGHT)
def update_board_to(self, new_board):
for y in range(0, self.HEIGHT):
for x in range(0, self.WIDTH):
tile = new_board[y][x] # Swap to match
if tile is not '-':
self.board.place_tile(tile, x, y)
def assert_board(self, board, tile, expected_move):
self.update_board_to(board)
move = self.computer.get_move(self.board, tile)
self.assertEqual(move, expected_move)
def test_win(self):
self.assert_board([['X', 'O', 'X'], ['X', 'O', 'X'], ['-', '-', 'O']],
'X', (0, 2))
def test_stop_loss(self):
self.assert_board([['X', 'O', 'X'], ['X', '-', 'O'], ['-', '-', 'O']],
'O', (0, 2))
def test_beat_trap(self):
self.update_board_to([['X', '-', '-'], ['-', 'O', '-'],
['-', '-', 'X']])
move = self.computer.get_move(self.board, 'O')
self.assertNotEqual(move, (0, 2))
self.assertNotEqual(move, (2, 0))
def check_events(screen, settings, chessmans, chessboard):
'''
检查输入输出状态
:param screen:界面引用
:param settings:游戏设置
:param chessmans:棋子group
:param chessboard:棋盘
:return:
'''
for event in pygame.event.get():
if event.type in (pygame.QUIT, ): #pygame.KEYDOWN
sys.exit()
elif settings.player_round and event.type == pygame.MOUSEBUTTONDOWN:
mouse_x, mouse_y = pygame.mouse.get_pos()
return put_chessman(screen, settings.player_color,
[mouse_x, mouse_y], settings, chessmans,
chessboard)
elif settings.player_round == False:
computer = Computer(settings, chessboard)
# # if(color_num==1):
computer_act_list = computer.max_min_search(
settings, computer.root, 2)
# print(computer_act_list)
computer_act = random.choice(computer_act_list)
print(computer_act)
return put_chessman(screen, settings.computer_color, computer_act,
settings, chessmans, chessboard)
return None
def main(player_first=True):
WIDTH = 3
HEIGHT = 3
board = Board(WIDTH, HEIGHT)
interaction = Interaction(WIDTH, HEIGHT)
computer = Computer()
turn = 'X'
if player_first:
computer_tile = 'O'
else:
computer_tile = 'X'
while board.get_winner() is None and not board.is_cat_game():
if turn == computer_tile:
x, y = computer.get_move(board, computer_tile)
board.place_tile(turn, x, y)
else:
x, y = interaction.get_move(turn, board)
board.place_tile(turn, x, y)
if turn == 'X':
turn = 'O'
else:
turn = 'X'
if board.is_cat_game():
interaction.display_cat_game(board)
else:
interaction.display_winner(board, board.get_winner() != computer_tile)
def run_until(x, y, target_output, program):
while True:
comp = Computer(program, input=(x, y))
comp.run()
if comp.collect() == target_output:
return x
x += 1
def part1():
lines = read_file_lines()
program = [int(code) for code in lines[0].split(',')]
computer = Computer(program)
computer.run()
out = computer.send_output()
print(len([x for x in out[2:-1:3] if x == 2]))
def main():
audit_data = []
config_profile_mapping = config_profile_map()
client = JamfApi()
response = client.jamf_call(
method='get',
path='/computers',
)
computer_ids = [x.get('id', {}) for x in response.json().get('computers', {})]
for computer_id in computer_ids:
response = client.jamf_call(
method='get',
path=f"/computers/id/{computer_id}",
)
computer = Computer(response.json().get('computer'))
configuration_profile_ids = [x.get('id') for x in computer.configuration_profiles()]
for configuration_profile_id in configuration_profile_ids:
if configuration_profile_id in config_profile_mapping.keys():
audit_data.append(f"{computer.serial_number()},{config_profile_mapping[configuration_profile_id]}")
for line in audit_data:
print(line)
print(len(audit_data))
def part2():
ascii_answer = "A,B,B,A,C,B,C,C,B,A\n" + \
"R,10,R,8,L,10,L,10\n" + \
"R,8,L,6,L,6\n" + \
"L,10,R,10,L,6\n" + \
"n\n"
raw_answer = [ord(c) for c in ascii_answer]
print(raw_answer)
code = parse_input("input.txt")
code[0] = 2
computer = Computer(code)
output = computer.run_on_input(raw_answer)
as_ascii = [chr(n) for n in output[:-1]]
rows = "".join(as_ascii).split("\n")
for y, r in enumerate(rows):
for x, c in enumerate(r):
print(c, end="")
print()
print("Answer to Part 2: ", output[-1])
def part1():
code = parse_input("input.txt")
computer = Computer(code)
output = computer.run_on_input([])
as_ascii = [chr(n) for n in output]
rows = "".join(as_ascii).split("\n")
grid = defaultdict(lambda: ".")
scaffolding = set()
for y, r in enumerate(rows):
for x, c in enumerate(r):
grid[(x, y)] = c
if c == '#':
scaffolding.add((x, y))
# print(c, end="")
# print()
intersections = set()
a1 = 0
for c in scaffolding:
if all(a in scaffolding for a in get_adjacent(*c)):
intersections.add(c)
grid[c] = "0"
a1 += c[0] * c[1]
print_grid(grid)
print("Answer to Part 1: ", a1)
def test_play_ok(self):
juego = Computer()
self.assertTrue(juego.play())
self.assertFalse(juego.error)
self.assertTrue(juego.loop_bien)
self.assertTrue(juego.loop_regular)
self.assertTrue(juego.loop_general)
def feedback(data, permutation):
e_out = 0
a_queue = deque([permutation[0], e_out])
b_queue = deque([permutation[1]])
c_queue = deque([permutation[2]])
d_queue = deque([permutation[3]])
e_queue = deque([permutation[4]])
a = Computer(data.copy()).run(a_queue)
b = Computer(data.copy()).run(b_queue)
c = Computer(data.copy()).run(c_queue)
d = Computer(data.copy()).run(d_queue)
e = Computer(data.copy()).run(e_queue)
while True:
b_queue.append(next(a, None))
c_queue.append(next(b, None))
d_queue.append(next(c, None))
e_queue.append(next(d, None))
try:
e_out = next(e)
a_queue.append(e_out)
except:
break
return e_out
def test_all_legal_moves():
"""Test all_legal_moves method.
When the game is initialized, there are four legal moves
for either black or white tile"""
tile = Tile()
computer = Computer(tile)
legal_move = computer.all_legal_moves()
assert legal_move == [(2, 3), (3, 2), (4, 5), (5, 4)]
def main():
f = open("input.txt")
s = f.readline()
memory = list(map(int, s.split(",")))
c = Computer(memory, 12, 2)
c.execute()
print(c.read(0))
def __init__(self, program):
self.com = Computer(program)
self.graph = {}
self.buffer = ''
self.x = self.y = 0
self.c_x = self.c_y = 0
self.im = Image.new('RGB', (50, 50))
self.direc = [0,-1]
def intcode(library, program):
""" Create an IntCode Computer """
computer = Computer(library, program)
computer.flash_memory()
computer.halt_condition = True
return computer
def content():
data = request.form['data']
ass = Assembler(data)
ass.gen_bin_instructions()
c = Computer()
program_start, end = ass.load(c.ram)
c.run(program_start)
return jsonify({
'assembler': ass.show_ins_table(),
'run': c.ram.show_relevant(program_start, end),
'storage': show_bin_rep(data)
})
def main():
player = Player()
computer = Computer()
print("Welcome to Simple Turn Based Game")
print("Featuring a simple A.I.\n")
while 1:
while 1:
print("Press q to quit at any time\n")
# Give player choices
print("1. Weak Attack")
print("2. Strong Attack")
print("3. Heal")
print("4. Improve Attack")
print("5. Improve Defense")
print("6. Show Health\n")
choice = input(": ")
print()
if choice == 'q':
print("Exiting...")
return
elif choice == '1':
computer.atked_weak()
break
elif choice == '2':
computer.atked_strong()
break
elif choice == '3':
player.heal()
break
elif choice == '4':
computer.imp_player_atk()
break
elif choice == '5':
player.imp_def()
break
elif choice == '6':
win_cond(player, computer)
else:
print("That is not an option.\n")
print()
if win_cond(player, computer):
return
print()
# AI's turn
computer.move(player.hp)
if win_cond(player, computer):
return
print("\n")
def __init__(self):
self.board = Board()
self.bag = Bag()
self.dict = utility.get_dictionary()
self.user = User(self.bag)
self.computer = Computer(self.bag)
self.moves_log = []
class TestComputer(unittest.TestCase):
WIDTH = 3
HEIGHT = 3
def setUp(self):
self.computer = Computer()
self.board = Board(self.WIDTH, self.HEIGHT)
def update_board_to(self, new_board):
for y in range(0, self.HEIGHT):
for x in range(0, self.WIDTH):
tile = new_board[y][x] # Swap to match
if tile is not '-':
self.board.place_tile(tile, x, y)
def assert_board(self, board, tile, expected_move):
self.update_board_to(board)
move = self.computer.get_move(self.board, tile)
self.assertEqual(move, expected_move)
def test_win(self):
self.assert_board(
[['X', 'O', 'X'],
['X', 'O', 'X'],
['-', '-', 'O']],
'X', (0, 2))
def test_stop_loss(self):
self.assert_board(
[['X', 'O', 'X'],
['X', '-', 'O'],
['-', '-', 'O']],
'O', (0, 2))
def test_beat_trap(self):
self.update_board_to(
[['X', '-', '-'],
['-', 'O', '-'],
['-', '-', 'X']])
move = self.computer.get_move(self.board, 'O')
self.assertNotEqual(move, (0, 2))
self.assertNotEqual(move, (2, 0))
def identify_computer(self, engine_id, cache_time):
"""Gather information about computer"""
# look if engine info is already stored
engine = DrQueueComputer.query_db(engine_id)
now = int(time.time())
# check existence and age of info
if (engine != None) and (now <= engine["date"] + cache_time):
print ("DEBUG: Engine %i was found in DB" % engine_id)
# store new info
else:
print ("DEBUG: Engine %i was not found in DB" % engine_id)
# run command only on specific computer
dview = self.ip_client[engine_id]
dview.block = True
dview.execute(
"import DrQueue\nfrom DrQueue import Computer as DrQueueComputer\nengine = DrQueueComputer("
+ str(engine_id)
+ ")"
)
engine = dview["engine"]
engine["date"] = int(time.time())
DrQueueComputer.store_db(engine)
return engine
def __init__(self, humanBoard, computerBoard, humanScore, computerScore,
humanIsFirstPlayer, humanIsNext, diceQueue, didLoad):
self.human = Human(humanScore)
self.computer = Computer(computerScore)
self.diceQueue = diceQueue
self.humanIsFirstPlayer = humanIsFirstPlayer
self.humanIsNext = humanIsNext
self.exitCode = 0
self.board = Board(humanBoard, computerBoard)
self.turnCount = 0
self.returnList = [False, 0, 0]
if didLoad:
self.resumeRound()
else:
self.newRound()
class TableWindow(QWidget):
"""
Визуализира играта.
"""
def __init__(self):
super(TableWindow, self).__init__()
self.cols = []
self.pc = Computer("B")
self.vsPC = True
self.win_dialog = WinDialog()
self.compuret_win = ComputerWinDialog()
self.first_player_time = Timer()
self.first_player_time.start()
self.col_one_edit = QTextEdit()
self.col_one_edit.setReadOnly(True)
self.col_two_edit = QTextEdit()
self.col_two_edit.setReadOnly(True)
self.col_three_edit = QTextEdit()
self.col_three_edit.setReadOnly(True)
self.col_four_edit = QTextEdit()
self.col_four_edit.setReadOnly(True)
self.col_five_edit = QTextEdit()
self.col_five_edit.setReadOnly(True)
self.col_six_edit = QTextEdit()
self.col_six_edit.setReadOnly(True)
self.col_seven_edit = QTextEdit()
self.col_seven_edit.setReadOnly(True)
self.col_eight_edit = QTextEdit()
self.col_eight_edit.setReadOnly(True)
self.col_nine_edit = QTextEdit()
self.col_nine_edit.setReadOnly(True)
self.col_ten_edit = QTextEdit()
self.col_ten_edit.setReadOnly(True)
self.col_one_edit = QTextEdit()
self.col_one_edit.setReadOnly(True)
label_on_turn = QLabel()
label_on_turn.setText("On turn:")
self.player = QLabel()
self.player.setText("R")
self.player_time = QLabel()
self.player_time.setText("Time player R:")
self.player_game_time = QLabel()
self.player_game_time.setText(" ")
self.adding_to_vector()
self.onTurn = 1
self.t = Table()
self.read_table()
firstButton = QPushButton("&")
firstButton.setFocusPolicy(Qt.NoFocus)
firstButton.clicked.connect(self.first_button_clicked)
secondButton = QPushButton("&")
secondButton.setFocusPolicy(Qt.NoFocus)
secondButton.clicked.connect(self.second_button_clicked)
thirdButton = QPushButton("&")
thirdButton.setFocusPolicy(Qt.NoFocus)
thirdButton.clicked.connect(self.third_button_clicked)
fourthButton = QPushButton("&")
fourthButton.setFocusPolicy(Qt.NoFocus)
fourthButton.clicked.connect(self.fourth_button_clicked)
fifthButton = QPushButton("&")
fifthButton.setFocusPolicy(Qt.NoFocus)
fifthButton.clicked.connect(self.fifth_button_clicked)
sixthButton = QPushButton("&")
sixthButton.setFocusPolicy(Qt.NoFocus)
sixthButton.clicked.connect(self.sixth_button_clicked)
seventhButton = QPushButton("&")
seventhButton.setFocusPolicy(Qt.NoFocus)
seventhButton.clicked.connect(self.seventh_button_clicked)
eighthButton = QPushButton("&")
eighthButton.setFocusPolicy(Qt.NoFocus)
eighthButton.clicked.connect(self.eighth_button_clicked)
ninthButton = QPushButton("&")
ninthButton.setFocusPolicy(Qt.NoFocus)
ninthButton.clicked.connect(self.ninth_button_clicked)
tenthButton = QPushButton("&")
tenthButton.setFocusPolicy(Qt.NoFocus)
tenthButton.clicked.connect(self.tenth_button_clicked)
layout = QGridLayout()
layout.addWidget(firstButton, 0, 0)
layout.addWidget(secondButton, 0, 1)
layout.addWidget(thirdButton, 0, 2)
layout.addWidget(fourthButton, 0, 3)
layout.addWidget(fifthButton, 0, 4)
layout.addWidget(sixthButton, 0, 5)
layout.addWidget(seventhButton, 0, 6)
layout.addWidget(eighthButton, 0, 7)
layout.addWidget(ninthButton, 0, 8)
layout.addWidget(tenthButton, 0, 9)
layout.addWidget(self.col_one_edit, 1, 0)
layout.addWidget(self.col_two_edit, 1, 1)
layout.addWidget(self.col_three_edit, 1, 2)
layout.addWidget(self.col_four_edit, 1, 3)
layout.addWidget(self.col_five_edit, 1, 4)
layout.addWidget(self.col_six_edit, 1, 5)
layout.addWidget(self.col_seven_edit, 1, 6)
layout.addWidget(self.col_eight_edit, 1, 7)
layout.addWidget(self.col_nine_edit, 1, 8)
layout.addWidget(self.col_ten_edit, 1, 9)
layout.addWidget(label_on_turn, 2, 0)
layout.addWidget(self.player, 2, 1)
layout.addWidget(self.player_time, 2, 2)
layout.addWidget(self.player_game_time, 2, 3)
self.setLayout(layout)
self.setWindowTitle("Connect Four")
self.resize(550, 450)
def adding_to_vector(self):
"""Добавя бутоните към масив от позициите
на който може да се постави елемента"""
self.cols.append(self.col_one_edit)
self.cols.append(self.col_two_edit)
self.cols.append(self.col_three_edit)
self.cols.append(self.col_four_edit)
self.cols.append(self.col_five_edit)
self.cols.append(self.col_six_edit)
self.cols.append(self.col_seven_edit)
self.cols.append(self.col_eight_edit)
self.cols.append(self.col_nine_edit)
self.cols.append(self.col_ten_edit)
def read_table(self):
"""Прочита таблицата от Table и я попълва в UI-a.
Ако има победител, пуска нов прозер.
"""
result = ""
i = 0
for col in self.cols:
for j in range(0, len(self.t.matrix)):
result += self.t.matrix[j][i] + "\n-\n"
i += 1
col.setText(result)
result = ""
if self.t.has_winner():
if self.t.get_winner() == Table.RED:
print(self.first_player_time.stop())
self.player_game_time.setText(str(self.first_player_time.stop()))
self.win_dialog.show()
else:
self.compuret_win.show()
def first_button_clicked(self):
"""Метод, който се извиква при натискането на първия бутон.
Извършва ход в играта на позиция 0.
"""
if self.onTurn == 1:
self.t.commit_turn(0, "R")
self.first_player_time.sleep()
if self.vsPC:
pos = self.pc.get_turn(self.t.matrix)
self.t.commit_turn(pos, "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(0, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def second_button_clicked(self):
"""Метод, който се извиква при натискането на втория бутон.
Извършва ход в играта на позиция 1.
"""
if self.onTurn == 1:
self.t.commit_turn(1, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(1, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def third_button_clicked(self):
"""Метод, който се извиква при натискането на третия бутон.
Извършва ход в играта на позиция 2.
"""
if self.onTurn == 1:
self.t.commit_turn(2, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(2, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def fourth_button_clicked(self):
"""Метод, който се извиква при натискането на четвътия бутон.
Извършва ход в играта на позиция 3.
"""
if self.onTurn == 1:
self.t.commit_turn(3, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(3, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def fifth_button_clicked(self):
"""Метод, който се извиква при натискането на петия бутон.
Извършва ход в играта на позиция 4.
"""
if self.onTurn == 1:
self.t.commit_turn(4, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(4, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def sixth_button_clicked(self):
"""Метод, който се извиква при натискането на шестия бутон.
Извършва ход в играта на позиция 5.
"""
if self.onTurn == 1:
self.t.commit_turn(5, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(5, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def seventh_button_clicked(self):
"""Метод, който се извиква при натискането на седмия бутон.
Извършва ход в играта на позиция 6.
"""
if self.onTurn == 1:
self.t.commit_turn(6, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(6, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def eighth_button_clicked(self):
"""Метод, който се извиква при натискането на осмият бутон.
Извършва ход в играта на позиция 7.
"""
if self.onTurn == 1:
self.t.commit_turn(7, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(7, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def ninth_button_clicked(self):
"""Метод, който се извиква при натискането на деветия бутон.
Извършва ход в играта на позиция 8.
"""
if self.onTurn == 1:
self.t.commit_turn(8, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(8, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def tenth_button_clicked(self):
"""Метод, който се извиква при натискането на десетия бутон.
Извършва ход в играта на позиция 9.
"""
if self.onTurn == 1:
self.t.commit_turn(9, "R")
self.first_player_time.sleep()
if self.vsPC:
self.t.commit_turn(self.pc.get_turn(
self.t.matrix), "B")
self.first_player_time.start()
else:
self.onTurn = 2
self.player.setText("B")
else:
self.t.commit_turn(9, "B")
self.player.setText("R")
self.onTurn = 1
self.first_player_time.start()
self.read_table()
def __init__(self):
super(TableWindow, self).__init__()
self.cols = []
self.pc = Computer("B")
self.vsPC = True
self.win_dialog = WinDialog()
self.compuret_win = ComputerWinDialog()
self.first_player_time = Timer()
self.first_player_time.start()
self.col_one_edit = QTextEdit()
self.col_one_edit.setReadOnly(True)
self.col_two_edit = QTextEdit()
self.col_two_edit.setReadOnly(True)
self.col_three_edit = QTextEdit()
self.col_three_edit.setReadOnly(True)
self.col_four_edit = QTextEdit()
self.col_four_edit.setReadOnly(True)
self.col_five_edit = QTextEdit()
self.col_five_edit.setReadOnly(True)
self.col_six_edit = QTextEdit()
self.col_six_edit.setReadOnly(True)
self.col_seven_edit = QTextEdit()
self.col_seven_edit.setReadOnly(True)
self.col_eight_edit = QTextEdit()
self.col_eight_edit.setReadOnly(True)
self.col_nine_edit = QTextEdit()
self.col_nine_edit.setReadOnly(True)
self.col_ten_edit = QTextEdit()
self.col_ten_edit.setReadOnly(True)
self.col_one_edit = QTextEdit()
self.col_one_edit.setReadOnly(True)
label_on_turn = QLabel()
label_on_turn.setText("On turn:")
self.player = QLabel()
self.player.setText("R")
self.player_time = QLabel()
self.player_time.setText("Time player R:")
self.player_game_time = QLabel()
self.player_game_time.setText(" ")
self.adding_to_vector()
self.onTurn = 1
self.t = Table()
self.read_table()
firstButton = QPushButton("&")
firstButton.setFocusPolicy(Qt.NoFocus)
firstButton.clicked.connect(self.first_button_clicked)
secondButton = QPushButton("&")
secondButton.setFocusPolicy(Qt.NoFocus)
secondButton.clicked.connect(self.second_button_clicked)
thirdButton = QPushButton("&")
thirdButton.setFocusPolicy(Qt.NoFocus)
thirdButton.clicked.connect(self.third_button_clicked)
fourthButton = QPushButton("&")
fourthButton.setFocusPolicy(Qt.NoFocus)
fourthButton.clicked.connect(self.fourth_button_clicked)
fifthButton = QPushButton("&")
fifthButton.setFocusPolicy(Qt.NoFocus)
fifthButton.clicked.connect(self.fifth_button_clicked)
sixthButton = QPushButton("&")
sixthButton.setFocusPolicy(Qt.NoFocus)
sixthButton.clicked.connect(self.sixth_button_clicked)
seventhButton = QPushButton("&")
seventhButton.setFocusPolicy(Qt.NoFocus)
seventhButton.clicked.connect(self.seventh_button_clicked)
eighthButton = QPushButton("&")
eighthButton.setFocusPolicy(Qt.NoFocus)
eighthButton.clicked.connect(self.eighth_button_clicked)
ninthButton = QPushButton("&")
ninthButton.setFocusPolicy(Qt.NoFocus)
ninthButton.clicked.connect(self.ninth_button_clicked)
tenthButton = QPushButton("&")
tenthButton.setFocusPolicy(Qt.NoFocus)
tenthButton.clicked.connect(self.tenth_button_clicked)
layout = QGridLayout()
layout.addWidget(firstButton, 0, 0)
layout.addWidget(secondButton, 0, 1)
layout.addWidget(thirdButton, 0, 2)
layout.addWidget(fourthButton, 0, 3)
layout.addWidget(fifthButton, 0, 4)
layout.addWidget(sixthButton, 0, 5)
layout.addWidget(seventhButton, 0, 6)
layout.addWidget(eighthButton, 0, 7)
layout.addWidget(ninthButton, 0, 8)
layout.addWidget(tenthButton, 0, 9)
layout.addWidget(self.col_one_edit, 1, 0)
layout.addWidget(self.col_two_edit, 1, 1)
layout.addWidget(self.col_three_edit, 1, 2)
layout.addWidget(self.col_four_edit, 1, 3)
layout.addWidget(self.col_five_edit, 1, 4)
layout.addWidget(self.col_six_edit, 1, 5)
layout.addWidget(self.col_seven_edit, 1, 6)
layout.addWidget(self.col_eight_edit, 1, 7)
layout.addWidget(self.col_nine_edit, 1, 8)
layout.addWidget(self.col_ten_edit, 1, 9)
layout.addWidget(label_on_turn, 2, 0)
layout.addWidget(self.player, 2, 1)
layout.addWidget(self.player_time, 2, 2)
layout.addWidget(self.player_game_time, 2, 3)
self.setLayout(layout)
self.setWindowTitle("Connect Four")
self.resize(550, 450)
def openlog(self, file):
"""Open logfile and write header."""
logfile = open(file, "ab")
logfile.write("Log started at " + strftime("%a, %d %b %Y %H:%M:%S", localtime()) + ".\n")
logfile.write("Running on " + DrQueueComputer.get_hostname() + " under " + DrQueueComputer.get_os() + ".\n\n")
return logfile
def main(args):
print('starting..!.')
# get all the relevant data from the preprocessing
X_train, y_train, X_test, y_test, num_splits, tunned_parameters, random_state = args
# multiprocessing dose not update the seed - so we make sure its random
np.random.seed(random_state)
# shuffle to introduce randomness in the smaller samples
X_train, y_train = shuffle(X_train, y_train)
# init paramters to make code more readable
num_test_samples = len(y_test)
num_dimensions = len(X_train[0])
max_iterations = 3000
range_of_samples_to_check = 1000
num_training_samples = len(y_train)
#final_points = [2000, 4000, 6000, 8000, num_training_samples] # for PCA
final_points = [2000, 6000, num_training_samples] # without PCA
num_splits -= len(final_points) # since we add the final points by hand
# in each itreation we use different amount of data to see how the model improvese with increased data
total_amount_of_data = [int(range_of_samples_to_check / num_splits) for i in range(num_splits)]
total_amount_of_data_intervals = np.cumsum(total_amount_of_data).tolist()
# we add final points to show that the model has converged
total_amount_of_data_intervals += final_points
print('total_amount_of_data_intervals', total_amount_of_data_intervals)
# make the two computer centers that run the program
computer_1 = Computer()
computer_2 = Computer()
# container for the accuricies
accuracies_distributed, accuracies_single, accuracies_central = [], [], []
# container for the weights
distributed_weights, single_weights, central_weights = {}, {}, {}
loop_start_time = time.time()
for loop_num, n in enumerate(total_amount_of_data_intervals):
# split the data differently according to if it is odd or even
if n % 2 == 0:
m = int(n / 2)
else:
# if odd, we add one ovservation to ensure that there is the same amount of
# observations in both places.
m = int((n + 1) / 2)
# init the computer before distributed run
computer_1.cost = 999999999 # due to minimization
computer_1.num_data_points = m
computer_1.is_first_run = True
computer_1.is_cost_small_enough = False
computer_2.cost = 999999999 # due to minimization
computer_2.num_data_points = m
computer_2.is_first_run = True
computer_2.is_cost_small_enough = False
learning_rate =tunned_parameters['distributed'][str(n)]['learning_rate']
weight_decay = tunned_parameters['distributed'][str(n)]['weight_decay']
Gamma = lambda x: np.sign(x)*(abs(x) - weight_decay)
theta = np.zeros(num_dimensions)
for i in range(max_iterations):
is_converged_computer_1, computer_1_gradient, computer_1_cost_small_enough = computer_1.get_gradients(X_train[:m], y_train[:m], theta)
is_converged_computer_2, computer_2_gradient, computer_2_cost_small_enough = computer_2.get_gradients(X_train[m:2*m], y_train[m:2*m], theta)
total_gradients = computer_1_gradient + computer_2_gradient
if is_converged_computer_1:
# if either of the computers has converge we stopp
print('distributed converge')
theta = computer_1_gradient
break
elif is_converged_computer_2:
print('distributed converge2')
theta = computer_2_gradient
break
elif computer_1_cost_small_enough:
print('distributed cost1')
theta = computer_1_gradient
break
elif computer_2_cost_small_enough:
print('distributed cost2')
theta = computer_2_gradient
break
else:
theta = Gamma(theta - learning_rate * total_gradients)
if i == max_iterations - 1:
print('distributed maxItr')
# Evaluate the model -- check for error rate
total_correct_distributed = 0
for i in range(num_test_samples):
prediction = np.sign(np.dot(theta, X_test[i]))
if prediction == y_test[i]:
total_correct_distributed += 1
distributed_weights[str(n)] = theta
accuracies_distributed.append(1 - total_correct_distributed / num_test_samples)
############## If only one computer did the analysis on there own data ############################
# initalize the data center
computer_1.cost = 999999999 # due to minimization
computer_1.num_data_points = m
computer_1.is_first_run = True
computer_1.is_cost_small_enough = False
learning_rate = tunned_parameters['single'][str(n)]['learning_rate']
weight_decay = tunned_parameters['single'][str(n)]['weight_decay']
Gamma = lambda x: np.sign(x) * (abs(x) - weight_decay)
theta = np.zeros(num_dimensions)
for i in range(max_iterations):
is_converged, gradient, is_cost_small_enough = computer_1.get_gradients(X_train[:m], y_train[:m], theta)
if is_converged:
print('single converge')
theta = gradient
break
elif is_cost_small_enough:
theta = gradient
print('single cost')
break
else:
theta = Gamma(theta - learning_rate * gradient)
if i == max_iterations - 1:
print('single maxItr')
# Evaluate the model -- check for error rate
total_correct_single = 0
for i in range(num_test_samples):
prediction = np.sign(np.dot(theta, X_test[i]))
if prediction == y_test[i]:
total_correct_single += 1
single_weights[str(n)] = theta
accuracies_single.append(1 - total_correct_single / num_test_samples)
############ If all data was at a centeralized location ###########################################
# initalize the data center
theta = np.zeros(num_dimensions)
computer_1.cost = 999999999 # due to minimization
computer_1.num_data_points = 2*m
computer_1.is_first_run = True
computer_1.is_cost_small_enough = False
learning_rate = tunned_parameters['central'][str(n)]['learning_rate']
weight_decay = tunned_parameters['central'][str(n)]['weight_decay']
Gamma = lambda x: np.sign(x) * (abs(x) - weight_decay)
for i in range(max_iterations):
is_converged, gradient, is_cost_small_enough = computer_1.get_gradients(X_train[:2*m], y_train[:2*m], theta )
if is_converged:
theta = gradient
print('central converge')
break
elif is_cost_small_enough:
theta = gradient
print('central cost')
break
else:
theta = Gamma(theta - learning_rate * gradient)
if i == max_iterations - 1:
print('central maxItr')
# Evaluate the model -- check for error rate
total_correct_all_data = 0
for i in range(num_test_samples):
prediction = np.sign(np.dot(theta, X_test[i]))
if prediction == y_test[i]:
total_correct_all_data += 1
central_weights[str(n)] = theta
accuracies_central.append(1 - total_correct_all_data / num_test_samples)
print('loop {} out of {}, time from first loop: {}'.format(loop_num, len(total_amount_of_data_intervals), time.time() - loop_start_time))
print('Leaving..!.1')
return (
{
'distributed':np.array(accuracies_distributed),
'single':np.array(accuracies_single),
'central_all_data':np.array(accuracies_central),
'total_amount_of_data_intervals':np.array(total_amount_of_data_intervals)},
{
'distributed': distributed_weights,
'single': single_weights,
'central':central_weights}
)
import pygame
from console import Console
from computer import Computer
from level import Screen
from pygame.locals import *
pygame.init()
screen = pygame.display.set_mode((1024,768))
spaceConsole = Console()
spaceComputer = Computer()
oxigen = 25
testStates = [["close",1],["open",0]]
testTransitions = {"open":("close","capsule","open")}
testObjects = {oxigen, "capsule"}
testScreen = Screen(testObjects,testStates,testTransitions)
while 1:
line = spaceConsole.update()
if line is not None:
line = line.lower()
spaceComputer.processString(line,testScreen)
print testScreen.getState()
pygame.display.flip()
class Game:
def __init__(self):
self.board = Board()
self.bag = Bag()
self.dict = utility.get_dictionary()
self.user = User(self.bag)
self.computer = Computer(self.bag)
self.moves_log = []
def get_user_letters(self):
''' Return the list of user's Letters
@return: the list of user's Letters.
'''
return self.user.get_letters()
def get_computer_letters(self):
''' Return the list of computer's Letters
@return: the list of computer's Letters.
'''
return self.computer.get_letters()
def get_user(self):
return self.user
def get_computer(self):
return self.computer
def computer_make_move(self):
return self.computer.make_move(self.board,
self.dict,
self.moves_log)
def get_players_char_letters(self, player):
'''
Return the list of letters the given player currently has.
@param player: string indicating the player ('user' or 'computer')
@return: the list of letters.
'''
letters = []
lts = getattr(self, player).get_letters()
for l in lts:
letters.append(l.get_character())
return letters
def user_swap_letters(self, letters):
''' Return the given list of Letters to the bag, and take
the same amount of letters from the bag.
@param letters: the list of letters to put back.
@return: True if it is possible, otherwise False.
'''
res = self.user.swap_letters(self.bag, letters)
return res
def computer_swap_letters(self):
''' Return the an amount of Letters to the bag, and take
the same amount of letters from the bag.
@return: True if it is possible, otherwise False.
'''
amount = random.randint(1, 7)
res = self.computer.swap_letters(self.bag, amount)
return res
class Tournament(object):
#----------------------------------------------------------------------------------------------------
# Function Name: __init__
# Purpose: To initialize the object
# Parameters:
# The human board
# The computer board
# The human score
# The computer score
# The humanIsFirstPlayer flag
# The humanIsNext flag
# The list of loaded dice rolls
# The didLoad flag
# Return Value: none
# Local Variables:
# All the same variables initializing the classes data members
# Algorithm:
# 1. Set up all the parameters as object data member
# 2. If the user is loading a game, resume around, if not then start a new one
#----------------------------------------------------------------------------------------------------
def __init__(self, humanBoard, computerBoard, humanScore, computerScore,
humanIsFirstPlayer, humanIsNext, diceQueue, didLoad):
self.human = Human(humanScore)
self.computer = Computer(computerScore)
self.diceQueue = diceQueue
self.humanIsFirstPlayer = humanIsFirstPlayer
self.humanIsNext = humanIsNext
self.exitCode = 0
self.board = Board(humanBoard, computerBoard)
self.turnCount = 0
self.returnList = [False, 0, 0]
if didLoad:
self.resumeRound()
else:
self.newRound()
#----------------------------------------------------------------------------------------------------
# Function Name: newRound
# Purpose: To start a new round
# Parameters: none
# Return Value: none
# Local Variables:
# numSquares - The number of squares that the user would like
# cround - An instance of a round to be played
# Algorithm:
# 1. Get the number of squares that the user would like to have
# 2. Reset the boards with the new amount of squares
# 3. Choose the first player
# 4. Begin a new round
#----------------------------------------------------------------------------------------------------
def newRound(self):
numSquares = self.getNumSquares()
self.board.resetBoards(numSquares)
self.chooseFirstPlayer()
self.returnList[2] = 0
cround = cRound(self.board, self.human, self.computer, self.turnCount,
self.humanIsNext, self.humanIsFirstPlayer, self.diceQueue,
self.returnList)
cround.play()
self.askToPlayAgain()
self.subsequentRound()
#----------------------------------------------------------------------------------------------------
# Function Name: resumeRound
# Purpose: To resume a round
# Parameters: none
# Return Value: none
# Local Variables:
# cround - An instance of a round to be played
# Algorithm:
# 1. Set the turn count to an arbitrary large number
# 2. Set the handicap square in the return list to 0
# 3. Play a round with loaded data
# 4. Ask the player if they would like to play again
# 5. If so, begin a another round
#----------------------------------------------------------------------------------------------------
def resumeRound(self):
self.turnCount = 4
self.returnList[2] = 0
cround = cRound(self.board, self.human, self.computer, self.turnCount,
self.humanIsNext, self.humanIsFirstPlayer, self.diceQueue,
self.returnList)
cround.play()
self.askToPlayAgain()
self.subsequentRound()
#----------------------------------------------------------------------------------------------------
# Function Name: subsequentRound
# Purpose: To start a subsequent round
# Parameters: none
# Return Value: none
# Local Variables:
# numSquares - The number of squares that the user would like
# cround - An instance of a round to be played
# Algorithm:
# 1. Set the turncount to 0
# 2. Get the number of squares from the suer
# 3. Reset the boards using the new numSquares
# 4. Compute and apply the handicap
# 5. Choose the first player
# 6. Play a round
# 7. Ask if the user wants to play another round
# 8. If so, then recurse
#----------------------------------------------------------------------------------------------------
def subsequentRound(self):
self.turnCount = 0
numSquares = self.getNumSquares()
self.board.resetBoards(numSquares)
self.computeHandicap()
self.chooseFirstPlayer()
cround = cRound(self.board, self.human, self.computer, self.turnCount,
self.humanIsNext, self.humanIsFirstPlayer, self.diceQueue,
self.returnList)
cround.play()
self.askToPlayAgain()
self.subsequentRound()
#----------------------------------------------------------------------------------------------------
# Function Name: getNumSquares
# Purpose: To retrieve the number of board squares from the user
# Parameters: none
# Return Value: squares - the desired number of squares
# Local Variables:
# squares - the desired number of squares
# Algorithm:
# 1. Ask for the user's validated input
# 2. Return their input
#----------------------------------------------------------------------------------------------------
def getNumSquares(self):
squares = Interface.validateRange(
"How many squares would you like to use? (9, 10, or 11): ",
9, 11)
return squares
#----------------------------------------------------------------------------------------------------
# Function Name: computeHandicap
# Purpose: To compute and apply the handicap from the previous round
# Parameters: none
# Return Value: none
# Local Variables:
# ones - the ones place value from the winning score
# tens - the tens place value from the winning score
# handicapSquare - the square to be handicapped
# boardSize - the size of the game board
# Algorithm:
# 1. Compute which square is the handicapped one
# 2. If the square is out of the bounds of the game board, then make it
# the largest square on the gameboard
# 3. Set the handicap square in the return list to be sent to round
# 4. Apply the handicap
#----------------------------------------------------------------------------------------------------
def computeHandicap(self):
ones = self.returnList[1]%10
tens = int(self.returnList[1]/10)
handicapSquare = ones + tens
boardSize = len(self.board.humanBoard)
if handicapSquare > boardSize:
handicapSquare = boardSize
self.returnList[2] = handicapSquare
self.applyHandicap(handicapSquare)
#----------------------------------------------------------------------------------------------------
# Function Name: applyHandicap
# Purpose: To correctly apply the handicap
# Parameters: The handicapSquare
# Return Value: none
# Local Variables: none
# Algorithm:
# 1. If the human own and is the first player, give handicap to Computer
# 2. If human won and was not the first player, give human the handicap
# 3. If computer won and was the first player, give human the handicap
# 4. If computer won ans was not the first player, give computer the handicap
#----------------------------------------------------------------------------------------------------
def applyHandicap(self, handicapSquare):
if self.returnList[0] and self.humanIsFirstPlayer:
Interface.printMsg("The Computer gets a handicap.")
self.board.computerBoard[handicapSquare-1] = "*"
if self.returnList[0] and not self.humanIsFirstPlayer:
Interface.printMsg("You get a handicap.")
self.board.humanBoard[handicapSquare-1] = "*"
if not self.returnList[0] and not self.humanIsFirstPlayer:
Interface.printMsg("You get a handicap.")
self.board.humanBoard[handicapSquare-1] = "*"
if not self.returnList[0] and self.humanIsFirstPlayer:
Interface.printMsg("The Computer gets a handicap.")
self.board.computerBoard[handicapSquare-1] = "*"
#----------------------------------------------------------------------------------------------------
# Function Name: chooseFirstPlayer
# Purpose: To choose the first player
# Parameters: none
# Return Value: none
# Local Variables:
# humanRoll - the human's roll
# computerRoll - the computer's roll
# Algorithm:
# 1. If the dice queue has contents in it then:
# a. Load the humanRoll from dice queue
# b. Pop that roll from the queue
# c. Load the computer roll from the dice queue
# d. Pop that roll from the queue
# 3. Otherwise:
# a. Generate a random roll for the human
# b. Generate a random roll for the computer
# 4. If the human roll is greater than computer roll, then set
# humanIsFirstPlayer and humanIsNext to 1
# 5. If the human roll is less than the computer roll then set
# humanIsFirstPlayer and humanIsNext to 0
# 6. If the rolls are equal, then recurse
#----------------------------------------------------------------------------------------------------
def chooseFirstPlayer(self):
if self.diceQueue:
Interface.printMsg("You are rolling...")
humanRoll = self.diceQueue[0][0] + self.diceQueue[0][1]
self.diceQueue.pop(0)
Interface.printMsg("You rolled " + repr(humanRoll))
Interface.printMsg("The Computer is rolling...")
computerRoll = self.diceQueue[0][0] + self.diceQueue[0][1]
Interface.printMsg("The Computer rolled " + repr(computerRoll))
self.diceQueue.pop(0)
else:
Interface.printMsg("You are rolling...")
humanRoll = self.human.rollDice()
Interface.printMsg("You rolled " + repr(humanRoll))
Interface.printMsg("The Computer is rolling...")
computerRoll = self.computer.rollDice()
Interface.printMsg("The Computer rolled " + repr(computerRoll))
if humanRoll > computerRoll:
Interface.printMsg("You go first!")
self.humanIsFirstPlayer = 1
self.humanIsNext = 1
elif humanRoll < computerRoll:
Interface.printMsg("The Computer goes first!")
self.humanIsFirstPlayer = 0
self.humanIsNext = 0
else:
Interface.printMsg("It was a tie!")
self.chooseFirstPlayer()
#----------------------------------------------------------------------------------------------------
# Function Name: askToPlayAgain
# Purpose: To see if the user would like to play another round
# Parameters: none
# Return Value: True if they will play again
# Local Variables:
# willPlay - a flag indicating if the user will play another round
# Algorithm:
# 1. Get the user's input on whether they will play again or not
# 2. If they want to play again, return true
# 3. Otherwise terminate the program
#----------------------------------------------------------------------------------------------------
def askToPlayAgain(self):
willPlay = Interface.validateBoolean("Would you like to play another round? (y/n): ")
if willPlay:
return True
self.terminate()
#----------------------------------------------------------------------------------------------------
# Function Name: terminate
# Purpose: To display the winner and terminate the program
# Parameters: none
# Return Value: none
# Local Variables: none
# Algorithm:
# 1. Infer and display the winner of the tournament
# 2. Exit the program
#----------------------------------------------------------------------------------------------------
def terminate(self):
print "\n\n"
print ("\tHuman: " + repr(self.human.score) +
"\t\tComputer: " + repr(self.computer.score))
print "\n\n"
if self.computer.score < self.human.score:
print "\tYou won the tournament!"
if self.computer.score > self.human.score:
print "\tThe Computer won the tournament!"
if self.computer.score == self.human.score:
print "\tThe tournament was a draw!"
print "\n\n"
print "Program is terminating."
sys.exit()
class ComputerTest(unittest.TestCase):
def setUp(self):
self.pc = Computer("B")
def test_potential_enemy_win_horizontal(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "R", "R", "R", "E", "E", "E"]
]
self.assertEqual(self.pc.potential_enemy_win_horizontal(
matrix), (3, 4))
def test_potential_enemy_win_horizontal_not_win(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "R", "R", "E", "E", "E", "E"]
]
self.assertEqual(self.pc.potential_enemy_win_horizontal(
matrix), (-1, -1))
def test_potential_enemy_win_horizontal_not_win_v2(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "R", "B", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"]
]
self.assertEqual(self.pc.potential_enemy_win_horizontal(
matrix), (-1, -1))
def test_potential_enemy_win_vertical(self):
matrix = [
["E", "E", "E", "R", "E", "E", "E"],
["E", "E", "E", "R", "E", "E", "E"],
["E", "E", "E", "R", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"]
]
self.assertEqual(self.pc.potential_enemy_win_vertical(matrix), (3, 3))
def test_potential_enemy_win_vertical_not_win(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "R", "E", "E", "E"],
["E", "E", "E", "R", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"]
]
self.assertEqual(self.pc.potential_enemy_win_vertical(
matrix), (-1, -1))
def test_potential_player_win_horizontal(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "B", "B", "B", "E", "E"],
["R", "E", "E", "E", "E", "E", "E"],
["E", "R", "E", "R", "B", "B", "E"]
]
self.assertEqual(self.pc.potential_player_win_horizontal(
matrix), (1, 5))
def test_potential_player_not_win_horizontal(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "B", "B", "E", "E", "E"],
["R", "E", "E", "E", "E", "E", "E"],
["E", "R", "E", "R", "B", "B", "E"]
]
self.assertEqual(self.pc.potential_player_win_horizontal(
matrix), (-1, -1))
def test_potential_player_win_first_diagonal(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "B", "B", "R", "E", "E"],
["R", "E", "E", "B", "E", "E", "E"],
["E", "B", "E", "R", "B", "B", "E"]
]
self.assertEqual(self.pc.potential_player_win_first_diagonal(
matrix), (0, 1))
def test_potential_player_not_win_first_diagonal(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"]
]
self.assertEqual(self.pc.potential_player_win_first_diagonal(
matrix), (-1, -1))
def test_get_turn_with_series_of_two_vertical(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "R", "E", "E"],
["E", "E", "E", "E", "R", "E", "E"]
]
self.assertEqual(self.pc.get_turn_with_series_of_two_vertical(
matrix), (1, 4))
def test_get_turn_with_series_of_two_horizontal(self):
matrix = [
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "E", "E", "E", "E"],
["E", "E", "E", "R", "R", "E", "E"]
]
self.assertEqual(self.pc.get_turn_with_series_of_two_horizontal(
matrix), (3, 2))
def setUp(self):
self.pc = Computer("B")
def main(args):
print('starting..!.')
# get all the relevant data from the preprocessing
X, y, num_splits, random_state = args
# shuffle the data so we get different data for each run of this program
# Then the program us run multiple times to get a good esitmate
# multiprocessing dose not do different seed, so we take a random number to start different seeds
np.random.seed(random_state)
X, y = shuffle(X, y)
# init parameters to make code more readable
max_iterations = 3000
num_samples = len(y)
num_dimensions = len(X[0])
range_of_samples_to_check = 1000 # since the model converges on very few images
# in each itreation we use different amount of data to see how the model improvese with increased data
total_amount_of_data = [int(range_of_samples_to_check/num_splits) for i in range(num_splits)]
total_amount_of_data_in_intervals = np.cumsum(total_amount_of_data).tolist()
# we add points to show that the model has converged
#total_amount_of_data_in_intervals += [2000, 4000, 6000, 8000, num_samples] # PCA
total_amount_of_data_in_intervals += [2000, 6000, num_samples]
# initialize dictonaries that contain information from the cross validation
distributed_solution = {}
single_solution = {}
all_data_solution = {}
splited_data_intervals = []
for n in total_amount_of_data_in_intervals:
distributed_solution[n] = {'weight_decays': [], 'learning_rates': [], 'error_rates':[]}
single_solution[n] = {'weight_decays': [], 'learning_rates': [], 'error_rates':[]}
all_data_solution[n] = {'weight_decays': [], 'learning_rates': [], 'error_rates':[]}
if n % 2 == 0:
m = int(n / 2)
splited_data_intervals.append(m)
else:
# if odd, we make the first data set have 1 more record than the second
m = int((n + 1) / 2)
splited_data_intervals.append(m)
# make the two computer centers that run the program
computer_1 = Computer()
computer_2 = Computer()
loop_start_time = time.time()
# tune the weight decay and learning rate with grid search and 5 fold cross validation
learning_rates = [0.1, 0.05, 0.01, 0.005, 0.0001, 0.00005, 10**(-5), 5*10**(-6)]
#weight_decays = [1.5, 1.0, 0.5, 0.1, 0.01]
for splited_index, n in enumerate(total_amount_of_data_in_intervals):
all_results_for_each_n_distributed = []
all_results_for_each_n_single = []
all_results_for_each_n_central = []
half_data = splited_data_intervals[splited_index] # !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!
if n < 360:
weight_decays = [15, 10, 5, 1, 0.01, 10**(-5), 10**(-10), 10**(-20)]
else:
weight_decay = [10**(-5), 10**(-10), 10**(-20)]
for weight_decay in weight_decays:
Gamma = lambda x: np.sign(x) * (abs(x) - weight_decay)
for learning_rate in learning_rates:
# initalize lists to gather errors from the cross validation
error_rates_distributed = []
error_rates_single = []
error_rates_central = []
kf = KFold(n_splits = 5)
for train_index, test_index in kf.split(X[:2*half_data]):
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
num_test_samples = len(y_test)
m = int(len(y_train) / 2)
# now we perform the distributed lasso regression
# initalize for the distributed algorithm
computer_1.cost = 999999999 # due to minimization
computer_1.num_data_points = m
computer_1.is_first_run = True
computer_1.is_cost_small_enough = False
computer_2.cost = 999999999 # due to minimization
computer_2.num_data_points = m
computer_2.is_first_run = True
computer_2.is_cost_small_enough = False
theta = np.zeros(num_dimensions)
for i in range(max_iterations):
is_converged_computer_1, computer_1_gradient, computer_1_cost_small_enough = computer_1.get_gradients(X_train[:m], y_train[:m], theta )
is_converged_computer_2, computer_2_gradient, computer_2_cost_small_enough = computer_2.get_gradients(X_train[m:2*m], y_train[m:2*m], theta )
total_gradients = computer_1_gradient + computer_2_gradient
if is_converged_computer_1:
theta = computer_1_gradient
# if either of the computers has converge we stopp
break
elif is_converged_computer_2:
theta = computer_2_gradient
break
elif computer_1_cost_small_enough:
theta = computer_1_gradient
break
elif computer_2_cost_small_enough:
theta = computer_2_gradient
break
else:
theta = Gamma(theta - learning_rate * total_gradients)
# Evaluate the model -- check for error rate
total_correct_distributed = 0
for i in range(num_test_samples):
prediction = np.sign(np.dot(theta, X_test[i]))
if prediction == y_test[i]:
total_correct_distributed += 1
error_rates_distributed.append(1 - total_correct_distributed / num_test_samples)
############ If all data was at a centeralized location ###########################################
computer_1.num_data_points = 2 * m
computer_1.cost = 999999999
computer_1.is_first_run = True
computer_1.is_cost_small_enough = False
theta = np.zeros(num_dimensions)
for i in range(max_iterations):
is_converged, gradient, is_cost_small_enough = computer_1.get_gradients(X_train[:2*m], y_train[:2*m], theta)
if is_converged:
theta = gradient
print('converge all', (learning_rate, weight_decay))
break
elif is_cost_small_enough:
theta = gradient
print('cost all', (learning_rate, weight_decay))
break
else:
theta = Gamma(theta - learning_rate * gradient)
# Evaluate the model -- check for error rate
total_correct_all_data = 0
for i in range(num_test_samples):
prediction = np.sign(np.dot(theta, X_test[i]))
if prediction == y_test[i]:
total_correct_all_data += 1
error_rates_central.append(1 - total_correct_all_data / num_test_samples)
############## If only one computer did the analysis on there own data ############################
# we do another cross validation so that the ratio between training and testing is the same as for the other models
kf = KFold(n_splits = 5)
for train_index, test_index in kf.split(X[:half_data]):
X_train, X_test = X[train_index], X[test_index]
y_train, y_test = y[train_index], y[test_index]
num_test_samples = len(y_test)
m = int(len(y_train) )
computer_1.cost = 999999999
computer_1.num_data_points = m
computer_1.is_first_run = True
computer_1.is_cost_small_enough = False
theta = np.zeros(num_dimensions)
for i in range(max_iterations):
is_converged, gradient, is_cost_small_enough = computer_1.get_gradients(X_train[:m], y_train[:m], theta)
if is_converged:
theta = gradient
break
elif is_cost_small_enough:
theta = gradient
break
else:
theta = Gamma(theta - learning_rate * gradient)
# Evaluate the model -- check for error rate
total_correct_single = 0
for i in range(num_test_samples):
prediction = np.sign(np.dot(theta, X_test[i]))
if prediction == y_test[i]:
total_correct_single += 1
error_rates_single.append(1 - total_correct_single / num_test_samples)
# After cross validation is finsihed for a pair of weight decay and learning rate we save the results
# we use tuples so we can find the min error rate, and at the same time have the correct weight decay and learning rate
all_results_for_each_n_distributed.append((np.mean(error_rates_distributed), weight_decay, learning_rate))
all_results_for_each_n_single.append((np.mean(error_rates_single), weight_decay, learning_rate))
all_results_for_each_n_central.append((np.mean(error_rates_central), weight_decay, learning_rate))
print('all_results_for_each_n_central', all_results_for_each_n_central)
error_rate, weight_decay, learning_rate = min(all_results_for_each_n_distributed)
distributed_solution[n]['weight_decays'].append(weight_decay)
distributed_solution[n]['learning_rates'].append(learning_rate)
distributed_solution[n]['error_rates'].append(error_rate)
error_rate, weight_decay, learning_rate = min(all_results_for_each_n_single)
single_solution[n]['error_rates'].append(error_rate)
single_solution[n]['weight_decays'].append(weight_decay)
single_solution[n]['learning_rates'].append(learning_rate)
error_rate, weight_decay, learning_rate = min(all_results_for_each_n_central)
all_data_solution[n]['error_rates'].append(error_rate)
all_data_solution[n]['weight_decays'].append(weight_decay)
all_data_solution[n]['learning_rates'].append(learning_rate)
print('\n{} out of {} total loop time: {}'.format(splited_index, len(total_amount_of_data_in_intervals), time.time() - loop_start_time), flush = True)
#print('distributed_solution[n]', distributed_solution[n]['error_rates'])
#print('single_solution[n]', single_solution[n])
#print('all_data_solution[n]', all_data_solution[n], flush = True)
#print('len(distributed_solution[n][error_rates])', len(distributed_solution[n]['error_rates']))
#print('distributed_solution[n][error_rates]', distributed_solution[n]['error_rates'])
print('Leaving..!.1')
return (distributed_solution, single_solution, all_data_solution)
def setUp(self):
self.computer = Computer()
self.board = Board(self.WIDTH, self.HEIGHT)
