def move_one_piece(old_x, old_y, new_x, new_y, context):
# Memorize the old piece.
piece = model.global_game_board_state[old_x][old_y]
# Remove the old piece.
model.global_game_board_state[old_x][old_y] = 0
# Place the piece to new location.
model.global_game_board_state[new_x][new_y] = piece
# Increase the score and taken moves for each side.
if model.global_game_board_state[new_x][new_y] == 1:
gameboard.update_moves_taken_for('black')
elif model.global_game_board_state[new_x][new_y] == 2:
gameboard.update_moves_taken_for('white')
gameboard.update_game_score()
# Log the movement information.
messages = []
if model.global_game_board_state[new_x][new_y] == 1:
messages.append("Black made movement as the following:")
elif model.global_game_board_state[new_x][new_y] == 2:
messages.append("White made movement as the following:")
messages.append("STD From : " +
str(chiens_board_representation_output[old_x][old_y]))
messages.append("STD To : " +
str(chiens_board_representation_output[new_x][new_y]))
messages.append("From : (" + str(old_x) + "," + str(old_y) + ")")
messages.append("To : (" + str(new_x) + "," + str(new_y) + ")")
context.log(messages)
def move_three_pieces(old_x1, old_y1, new_x1, new_y1, old_x2, old_y2, new_x2,
new_y2, old_x3, old_y3, new_x3, new_y3, context):
# Memorize the old pieces.
piece1 = model.global_game_board_state[old_x1][old_y1]
piece2 = model.global_game_board_state[old_x2][old_y2]
piece3 = model.global_game_board_state[old_x3][old_y3]
# Remove the old pieces.
model.global_game_board_state[old_x1][old_y1] = 0
model.global_game_board_state[old_x2][old_y2] = 0
model.global_game_board_state[old_x3][old_y3] = 0
# Place the pieces to new location.
model.global_game_board_state[new_x1][new_y1] = piece1
model.global_game_board_state[new_x2][new_y2] = piece2
model.global_game_board_state[new_x3][new_y3] = piece3
# Increase the score and taken moves for each side.
if model.global_game_board_state[new_x1][new_y1] == 1:
gameboard.update_moves_taken_for('black')
elif model.global_game_board_state[new_x1][new_y1] == 2:
gameboard.update_moves_taken_for('white')
gameboard.update_game_score()
# Log the movement information.
messages = []
if model.global_game_board_state[new_x1][new_y1] == 1:
messages.append("Black made movement as the following:")
elif model.global_game_board_state[new_x1][new_y1] == 2:
messages.append("White made movement as the following:")
messages.append("STD From : " +
str(chiens_board_representation_output[old_x1][old_y1]) +
', ' +
str(chiens_board_representation_output[old_x2][old_y2]) +
', ' +
str(chiens_board_representation_output[old_x3][old_y3]))
messages.append("STD To : " +
str(chiens_board_representation_output[new_x1][new_y1]) +
', ' +
str(chiens_board_representation_output[new_x2][new_y2]) +
', ' +
str(chiens_board_representation_output[new_x3][new_y3]))
messages.append("From : (" + str(old_x1) + "," + str(old_y1) + ")" + " " +
"(" + str(old_x2) + "," + str(old_y2) + ")" + " " + "(" +
str(old_x3) + "," + str(old_y3) + ")")
messages.append("To : (" + str(new_x1) + "," + str(new_y1) + ")" + " " +
"(" + str(new_x2) + "," + str(new_y2) + ")" + " " + "(" +
str(new_x3) + "," + str(new_y3) + ")")
context.log(messages)
def ai_calculation_thread(context, color):
try:
# ================ ================ An Empty State Initialization ================ ================
new_state = [[-9, -9, -9, -9, 0, 0, 0, 0, 0],
[-9, -9, -9, 0, 0, 0, 0, 0, 0],
[-9, -9, 0, 0, 0, 0, 0, 0,
0], [-9, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, -9],
[0, 0, 0, 0, 0, 0, 0, -9, -9],
[0, 0, 0, 0, 0, 0, -9, -9, -9],
[0, 0, 0, 0, 0, -9, -9, -9, -9]]
# ================ ================ AI Search to Get Next Move & State ================ ================
new_move_and_state = ai_search.get_next_move_and_state_from_ai_search(
color, model.global_game_board_state,
model.global_game_play_state[color]['moves_taken'], context)
new_move = new_move_and_state[0]
new_state = new_move_and_state[1]
# ================ ================ Print & Log Movement ================ ================
print_and_log_move_tuple(context, color, new_move)
# ================ ================ Update the Global State ================ ================
model.global_game_board_state = copy.deepcopy(new_state)
# Increase the score and taken moves for each side.
gameboard.update_game_score()
if 'black' == color:
gameboard.update_moves_taken_for('black')
elif 'white' == color:
gameboard.update_moves_taken_for('white')
# ================ ================ Prolog for GUI ================ ================
# Update the game graphic
context.update_canvas()
# Update gameboard after movement.
gameboard.update_gui_game_panel(context)
# AI finishes a turn.
model.update_turn_state(context)
except Exception:
print("RuntimeError from ai_calculation_thread.")
def move_3_to_1_or_3_to_2_sumito(old_x1, old_y1, new_x1, new_y1, old_x2,
old_y2, new_x2, new_y2, old_x3, old_y3,
new_x3, new_y3, context):
# Get the clicked position.
clicked_position = get_the_differences_from_sets_for_sumitos(
{(new_x1, new_y1), (new_x2, new_y2), (new_x3, new_y3)},
{(old_x1, old_y1), (old_x2, old_y2), (old_x3, old_y3)})
clicked_x = clicked_position[0]
clicked_y = clicked_position[1]
# Get the moved position.
moved_position = get_the_differences_from_sets_for_sumitos(
{(old_x1, old_y1), (old_x2, old_y2), (old_x3, old_y3)},
{(new_x1, new_y1), (new_x2, new_y2), (new_x3, new_y3)})
removed_x = moved_position[0]
removed_y = moved_position[1]
# Store 3 advanced coordinates for piece advancement.
advanced_coordinates = []
# Find out the directions and populate advanced_coordinates.
if removed_y == clicked_y:
if clicked_x > removed_x:
advanced_coordinates.append((clicked_x + 1, clicked_y))
advanced_coordinates.append((clicked_x + 2, clicked_y))
advanced_coordinates.append((clicked_x + 3, clicked_y))
elif clicked_x < removed_x:
advanced_coordinates.append((clicked_x - 1, clicked_y))
advanced_coordinates.append((clicked_x - 2, clicked_y))
advanced_coordinates.append((clicked_x - 3, clicked_y))
elif removed_x == clicked_x:
if clicked_y > removed_y:
advanced_coordinates.append((clicked_x, clicked_y + 1))
advanced_coordinates.append((clicked_x, clicked_y + 2))
advanced_coordinates.append((clicked_x, clicked_y + 3))
elif clicked_y < removed_y:
advanced_coordinates.append((clicked_x, clicked_y - 1))
advanced_coordinates.append((clicked_x, clicked_y - 2))
advanced_coordinates.append((clicked_x, clicked_y - 3))
else:
if clicked_x > removed_x:
advanced_coordinates.append((clicked_x + 1, clicked_y - 1))
advanced_coordinates.append((clicked_x + 2, clicked_y - 2))
advanced_coordinates.append((clicked_x + 3, clicked_y - 3))
elif clicked_x < removed_x:
advanced_coordinates.append((clicked_x - 1, clicked_y + 1))
advanced_coordinates.append((clicked_x - 2, clicked_y + 2))
advanced_coordinates.append((clicked_x - 3, clicked_y + 3))
# Find whether this is 3 to 1 or 3 to 2 sumito.
# A set will be generated: ((x1, y1, x2, y2, x3, y3))
all_3_to_1_sumitos_set = rules.generate_all_3_to_1_legal_sumitos(
old_x1, old_y1, old_x2, old_y2, old_x3, old_y3)
all_3_to_2_sumitos_set = rules.generate_all_3_to_2_legal_sumitos(
old_x1, old_y1, old_x2, old_y2, old_x3, old_y3)
new_coordinates_set_1 = set()
new_coordinates_set_1.add((new_x1, new_y1, new_x2, new_y2, new_x3, new_y3))
new_coordinates_set_2 = set()
new_coordinates_set_2.add((new_x1, new_y1, new_x3, new_y3, new_x2, new_y2))
new_coordinates_set_3 = set()
new_coordinates_set_3.add((new_x2, new_y2, new_x1, new_y1, new_x3, new_y3))
new_coordinates_set_4 = set()
new_coordinates_set_4.add((new_x2, new_y2, new_x3, new_y3, new_x1, new_y1))
new_coordinates_set_5 = set()
new_coordinates_set_5.add((new_x3, new_y3, new_x2, new_y2, new_x1, new_y1))
new_coordinates_set_6 = set()
new_coordinates_set_6.add((new_x3, new_y3, new_x1, new_y1, new_x2, new_y2))
# 1. 3 to 1 sumito.
if all_3_to_1_sumitos_set != set() and \
(all_3_to_1_sumitos_set.issuperset(new_coordinates_set_1)
or all_3_to_1_sumitos_set.issuperset(new_coordinates_set_2)
or all_3_to_1_sumitos_set.issuperset(new_coordinates_set_3)
or all_3_to_1_sumitos_set.issuperset(new_coordinates_set_4)
or all_3_to_1_sumitos_set.issuperset(new_coordinates_set_5)
or all_3_to_1_sumitos_set.issuperset(new_coordinates_set_6)
):
# Memorize the opponent piece.
piece_opponent = model.global_game_board_state[clicked_x][clicked_y]
# Memorize the old pieces.
piece1 = model.global_game_board_state[old_x1][old_y1]
piece2 = model.global_game_board_state[old_x2][old_y2]
piece3 = model.global_game_board_state[old_x3][old_y3]
# Remove the old pieces.
model.global_game_board_state[old_x1][old_y1] = 0
model.global_game_board_state[old_x2][old_y2] = 0
model.global_game_board_state[old_x3][old_y3] = 0
# Place the pieces to new location.
model.global_game_board_state[new_x1][new_y1] = piece1
model.global_game_board_state[new_x2][new_y2] = piece2
model.global_game_board_state[new_x3][new_y3] = piece3
# Place the opponent piece to the advanced position.
if (rules.is_the_position_inside_of_the_board(
[advanced_coordinates[0]])):
adv_x = advanced_coordinates[0][0]
adv_y = advanced_coordinates[0][1]
model.global_game_board_state[adv_x][adv_y] = piece_opponent
# 2. 3 to 2 sumito (Normal descriptive statements omitted for computing efficiency).
elif all_3_to_2_sumitos_set != set() and \
(all_3_to_2_sumitos_set.issuperset(new_coordinates_set_1)
or all_3_to_2_sumitos_set.issuperset(new_coordinates_set_2)
or all_3_to_2_sumitos_set.issuperset(new_coordinates_set_3)
or all_3_to_2_sumitos_set.issuperset(new_coordinates_set_4)
or all_3_to_2_sumitos_set.issuperset(new_coordinates_set_5)
or all_3_to_2_sumitos_set.issuperset(new_coordinates_set_6)
):
# Memorize the opponent pieces.
piece_opponent_1 = model.global_game_board_state[clicked_x][clicked_y]
piece_opponent_2 = model.global_game_board_state[
advanced_coordinates[0][0]][advanced_coordinates[0][1]]
# Memorize the old pieces.
piece1 = model.global_game_board_state[old_x1][old_y1]
piece2 = model.global_game_board_state[old_x2][old_y2]
piece3 = model.global_game_board_state[old_x3][old_y3]
# Remove the old pieces.
model.global_game_board_state[old_x1][old_y1] = 0
model.global_game_board_state[old_x2][old_y2] = 0
model.global_game_board_state[old_x3][old_y3] = 0
# Place the pieces to new location.
model.global_game_board_state[new_x1][new_y1] = piece1
model.global_game_board_state[new_x2][new_y2] = piece2
model.global_game_board_state[new_x3][new_y3] = piece3
# Place the opponent piece 1 to the advanced position.
if (rules.is_the_position_inside_of_the_board(
[advanced_coordinates[0]])):
adv_x_1 = advanced_coordinates[0][0]
adv_y_1 = advanced_coordinates[0][1]
model.global_game_board_state[adv_x_1][adv_y_1] = piece_opponent_1
# Place the opponent piece 2 to the advanced position.
if (rules.is_the_position_inside_of_the_board(
[advanced_coordinates[1]])):
adv_x_2 = advanced_coordinates[1][0]
adv_y_2 = advanced_coordinates[1][1]
model.global_game_board_state[adv_x_2][adv_y_2] = piece_opponent_2
# Increase the score and taken moves for each side.
if model.global_game_board_state[new_x1][new_y1] == 1:
gameboard.update_moves_taken_for('black')
elif model.global_game_board_state[new_x1][new_y1] == 2:
gameboard.update_moves_taken_for('white')
gameboard.update_game_score()
# Log the movement information.
messages = []
if model.global_game_board_state[new_x1][new_y1] == 1:
messages.append("Black made movement (SUMITO!):")
elif model.global_game_board_state[new_x1][new_y1] == 2:
messages.append("White made movement (SUMITO!):")
messages.append("STD From : " +
str(chiens_board_representation_output[old_x1][old_y1]) +
', ' +
str(chiens_board_representation_output[old_x2][old_y2]) +
', ' +
str(chiens_board_representation_output[old_x3][old_y3]))
messages.append("STD To : " +
str(chiens_board_representation_output[new_x1][new_y1]) +
', ' +
str(chiens_board_representation_output[new_x2][new_y2]) +
', ' +
str(chiens_board_representation_output[new_x3][new_y3]))
messages.append("From : (" + str(old_x1) + "," + str(old_y1) + ")" + " " +
"(" + str(old_x2) + "," + str(old_y2) + ")" + " " + "(" +
str(old_x3) + "," + str(old_y3) + ")")
messages.append("To : (" + str(new_x1) + "," + str(new_y1) + ")" + " " +
"(" + str(new_x2) + "," + str(new_y2) + ")" + " " + "(" +
str(new_x3) + "," + str(new_y3) + ")")
context.log(messages)
def move_2_to_1_sumito(old_x1, old_y1, new_x1, new_y1, old_x2, old_y2, new_x2,
new_y2, context):
# Get the clicked position.
clicked_position = get_the_differences_from_sets_for_sumitos(
{(new_x1, new_y1), (new_x2, new_y2)}, {(old_x1, old_y1),
(old_x2, old_y2)})
clicked_x = clicked_position[0]
clicked_y = clicked_position[1]
# Get the moved position.
moved_position = get_the_differences_from_sets_for_sumitos(
{(old_x1, old_y1), (old_x2, old_y2)}, {(new_x1, new_y1),
(new_x2, new_y2)})
removed_x = moved_position[0]
removed_y = moved_position[1]
# Store 2 advanced coordinates for piece advancement.
advanced_coordinates = []
# Find out the directions and populate advanced_coordinates.
if removed_y == clicked_y:
if clicked_x > removed_x:
advanced_coordinates.append((clicked_x + 1, clicked_y))
advanced_coordinates.append((clicked_x + 2, clicked_y))
elif clicked_x < removed_x:
advanced_coordinates.append((clicked_x - 1, clicked_y))
advanced_coordinates.append((clicked_x - 2, clicked_y))
elif removed_x == clicked_x:
if clicked_y > removed_y:
advanced_coordinates.append((clicked_x, clicked_y + 1))
advanced_coordinates.append((clicked_x, clicked_y + 2))
elif clicked_y < removed_y:
advanced_coordinates.append((clicked_x, clicked_y - 1))
advanced_coordinates.append((clicked_x, clicked_y - 2))
else:
if clicked_x > removed_x:
advanced_coordinates.append((clicked_x + 1, clicked_y - 1))
advanced_coordinates.append((clicked_x + 2, clicked_y - 2))
elif clicked_x < removed_x:
advanced_coordinates.append((clicked_x - 1, clicked_y + 1))
advanced_coordinates.append((clicked_x - 2, clicked_y + 2))
# Memorize the opponent piece.
piece_opponent = model.global_game_board_state[clicked_x][clicked_y]
# Memorize the old pieces.
piece1 = model.global_game_board_state[old_x1][old_y1]
piece2 = model.global_game_board_state[old_x2][old_y2]
# Remove the old pieces.
model.global_game_board_state[old_x1][old_y1] = 0
model.global_game_board_state[old_x2][old_y2] = 0
# Place the pieces to new location.
model.global_game_board_state[new_x1][new_y1] = piece1
model.global_game_board_state[new_x2][new_y2] = piece2
# Place the opponent piece to the advanced position.
if (rules.is_the_position_inside_of_the_board([advanced_coordinates[0]])):
adv_x = advanced_coordinates[0][0]
adv_y = advanced_coordinates[0][1]
model.global_game_board_state[adv_x][adv_y] = piece_opponent
# Increase the score and taken moves for each side.
if model.global_game_board_state[new_x1][new_y1] == 1:
gameboard.update_moves_taken_for('black')
elif model.global_game_board_state[new_x1][new_y1] == 2:
gameboard.update_moves_taken_for('white')
gameboard.update_game_score()
# Log the movement information.
messages = []
if model.global_game_board_state[new_x1][new_y1] == 1:
messages.append("Black made movement (SUMITO!):")
elif model.global_game_board_state[new_x1][new_y1] == 2:
messages.append("White made movement (SUMITO!):")
messages.append("STD From : " +
str(chiens_board_representation_output[old_x1][old_y1]) +
', ' +
str(chiens_board_representation_output[old_x2][old_y2]))
messages.append("STD To : " +
str(chiens_board_representation_output[new_x1][new_y1]) +
', ' +
str(chiens_board_representation_output[new_x2][new_y2]))
messages.append("From : (" + str(old_x1) + "," + str(old_y1) + ")" + " " +
"(" + str(old_x2) + "," + str(old_y2) + ")")
messages.append("To : (" + str(new_x1) + "," + str(new_y1) + ")" + " " +
"(" + str(new_x2) + "," + str(new_y2) + ")")
context.log(messages)