async def on_message(message):
pre = get_prefix
print (pre)
if message.author == client.user:
return
# handle help and all of the playbook interactions
response = plain_command_handler(message)
if response:
await message.channel.send(response)
return
response = embed_command_handler(message)
if response:
await message.channel.send(embed=response)
return
#list moves
move_list = get_moves(message)
if move_list:
await message.channel.send(move_list)
return
#remember generic ! should always be last in the tree
elif message.content.startswith("!"):
log_line = message.guild.name + "|" + message.channel.name + "|" + message.author.name + "|" + message.content
logger.info(log_line)
response = mad_parse(message)
if response: await message.channel.send(embed=response)
await client.process_commands(message)
def play():
''' play the game '''
orientation = {'N': 0, 'S': 180, 'E': 90, 'W': 270}
glide = 12
mm = 0
for move in moves.get_moves():
# who's moving
actor, direction = move.split(SEP)
f = F[actor]
if f.static : continue
if not f.alive: continue
has_weapon = False if f.weapon is None else True
print('-'*40)
print(mm:=mm+1, f, '->', direction)
# set angle
angle = orientation[direction]
f.setheading(angle)
if has_weapon:
f.weapon.setheading(angle)
# move
f_pos_old = tuptoint(f.position())
step = span/glide
for _ in range(glide):
f.forward(step)
if has_weapon:
f.weapon.forward(step)
f_pos_new = tuptoint(f.position())
# update board tracking
occupied = f_pos_new in F_Pos
update_position('old', f_pos_old, f, F_Pos)
update_position('new', f_pos_new, f, F_Pos)
# fight if occupied
if occupied:
print('someone here already -> ', F_Pos[f_pos_new][0])
normal_speed = f.speed()
ring, at, df = warmup(f_pos_new)
winner, loser = bell(angle, at, df, normal_speed)
final_rites(ring, loser)
if loser == f:
continue
# update weapons tracking dict
if has_weapon:
update_position('old', f_pos_old, f.weapon, W_Pos)
update_position('old', f_pos_new, f.weapon, W_Pos)
else:
# pick any weapons
if f_pos_new in W_Pos:
f.pick_weapon(W_Pos[f_pos_new])
f.weapon.forward(0) # so weapon shows atop
async def on_message(message):
if message.author == client.user:
return
# handle help and all of the playbook interactions
if message.content.startswith("!"):
response = plain_command_handler(message)
if response:
log_line = msg_log_line(message)
logger.info(log_line)
await message.channel.send(response)
return
response = embed_command_handler(message)
if response:
log_line = msg_log_line(message)
logger.info(log_line)
await message.channel.send(embed=response)
return
#answer a call for help
if message.content.startswith("!help"):
log_line = msg_log_line(message)
logger.info(log_line)
help_file = open("help", "r")
response = help_file.read()
await message.author.send(response)
await message.channel.send("I have sent help to your PMs.")
#list moves#
if message.content.startswith("!"):
move_list = get_moves(message)
if move_list:
await message.channel.send(move_list)
#remember generic ! should always be last in the tree#
else:
log_line = msg_log_line(message)
logger.info(log_line)
response = mad_parse(message)
if response:
logger.info(response)
(response, addendum) = response
# if addendum is not None: ##testing if going first made a difference
# await message.channel.send(content = addendum)
await message.channel.send(embed=response)
if addendum is not None:
await message.channel.send(content=addendum)
else:
logger.info('no match found for ' + message.content)
async def on_message(message):
if message.author == client.user:
return
lang = get_raw_lang(message)
# handle help and all of the playbook interactions
response = plain_command_handler(message, lang)
if response:
log_line = message.guild.name + "|" + message.channel.name + "|" + message.author.name + "|" + message.content
logger.info(log_line)
await message.channel.send(response)
return
response = embed_command_handler(message, lang)
if response:
log_line = message.guild.name + "|" + message.channel.name + "|" + message.author.name + "|" + message.content
logger.info(log_line)
await message.channel.send(embed=response)
return
#answer a call for help
if message.content.startswith("!help"):
log_line = message.guild.name + "|" + message.channel.name + "|" + message.author.name + "|" + message.content
logger.info(log_line)
help_file = open("help", "r")
response = help_file.read()
await message.author.send(response)
await message.channel.send("I have sent help to your PMs.")
#list moves#
move_list = get_moves(message, lang)
if move_list:
await message.channel.send(move_list)
#remember generic ! should always be last in the tree#
elif message.content.startswith("!"):
log_line = message.guild.name + "|" + message.channel.name + "|" + message.author.name + "|" + message.content
logger.info(log_line)
response = mad_parse(message)
if response:
logger.info(response)
await message.channel.send(embed=response)
else:
logger.info('no match found for ' + message.content)
def human_turn(playing_board, my_pieces, computer_pieces):
print_board(playing_board)
# Get a list of all the pieces that can be moved
edible = can_eat(playing_board, my_pieces, contents.WHITE, contents.BLACK)
# Print the list of pieces
print_pieces(edible[0])
# Get which piece the user wants to move
index = get_piece(edible[0])
# Get where the user would like to move that piece
print 'Please select where to move this piece to'
moves = get_moves(playing_board, index, contents.WHITE, contents.BLACK)
print_dct(moves)
move = get_move(moves)
# Make the move
make_move(playing_board, index, move, edible[1])
def __init__(self):
Character.__init__(self,
"The Maker",
5,
{"element": "???",
"quirk": "Flogna",
"form": "Ghost",
"gender": 0,
"orientation": 0},
{"HP": sys.maxint,
"MP": sys.maxint,
"Attack": sys.maxint,
"Defense": sys.maxint,
"Special": sys.maxint,
"Resistance": sys.maxint,
"Speed": sys.maxint,
"Luck": sys.maxint,
"Accuracy": sys.maxint,
"Evasion": sys.maxint},
dict([(x, 0) for x in get_moves().keys()]))
def __init__(self):
unsigned_moves = dict([(x, 0) for x in get_moves().keys()])
for signature in get_signatures().keys():
del unsigned_moves[signature]
Character.__init__(self,
"Mew",
5,
{"element": "Psychic",
"color": "magenta",
"quirk": "Synchronize",
"form": "Ghost",
"gender": 0,
"bio": "Because it can use all kinds of moves, many scientists believe Mew to be the ancestor of all Pokemon. Apparently, it appears only to those who are pure of heart and have a strong desire to see it."},
{"HP": 100,
"MP": 100,
"Attack": 100,
"Defense": 100,
"Special": 100,
"Resistance": 100,
"Speed": 100,
"Luck": 100},
unsigned_moves)
def a_star_sandbar(screen=[], old_loc=[], loop=False, frame_num=0, *args):
# Performs A* on the frog in order to get the player to the half-way point
# (the sandbar). Takes the screen and previous player's location, and
# returns the move or set of moves to make as well as the player's new position.
loc = old_loc
guide = set_guide(screen, loc)
loc = guide.pop()
dist = sandbar_distance(loc)
node = []
if frame_num:
# Dynamic nodes are made up of location, move that got there,
# the cost of the node (traveled + heuristic), the frame it
# came from, and the parent of the current node (implicit list).
node = [loc, None, dist, frame_num, None]
else:
# Nodes are made up of location, move that got there,
# the cost of the node (traveled + heuristic) and the
# parent node of the current one(they're implicitly linked).
node = [loc, None, dist, None]
frontier = priority_queue()
frontier.push(node, dist)
explored = []
move = 0
move_list = []
if frame_num:
while True:
if frontier.is_empty():
return None
parent_node = frontier.pop()
loc, move, this_cost, frame, grand_parent_node = parent_node
if loc in explored:
continue
if not sandbar_distance(loc):
while parent_node:
_, action, _, _, parent_node = parent_node
if not action == None:
if not loop:
move = action
else:
move_list.append(action)
if loop:
move_list.append(loc)
return move_list
else:
move = [move, loc]
return move
explored.append(loc)
for move in get_moves(guide, loc, frame):
action, new_loc = move
h_cost = sandbar_distance(new_loc)
new_cost = 1 + h_cost
next_frame = 5 + frame
child_node = [
new_loc, action, new_cost, next_frame, parent_node
]
if not ((new_loc in explored) or (new_loc in frontier)):
frontier.push(child_node, new_cost)
elif (new_loc in frontier):
frontier.push(child_node, new_cost)
else:
while True:
if frontier.is_empty():
return None
parent_node = frontier.pop()
loc, move, this_cost, grand_parent_node = parent_node
if loc in explored:
continue
if not sandbar_distance(loc):
while parent_node:
_, action, _, parent_node = parent_node
if not action == None:
if not loop:
move = action
else:
move_list.append(action)
if loop:
move_list.append(loc)
return move_list
else:
move = [move, loc]
return move
explored.append(loc)
for move in get_moves(guide, loc):
action, new_loc = move
h_cost = sandbar_distance(new_loc)
new_cost = 1 + h_cost
child_node = [new_loc, action, new_cost, parent_node]
if not ((new_loc in explored) or (new_loc in frontier)):
frontier.push(child_node, new_cost)
elif (new_loc in frontier):
frontier.push(child_node, new_cost)
def a_sure(screen=[], old_loc=[], loop=False, frame_num=0, *args):
# Takes the screen and the previous player's position as input
# and returns either the next move to make or the set of moves
# to make as well as the new position of the player.
loc = old_loc
guide = set_guide(screen, loc)
loc = guide.pop()
closest = [] # a list, with first element being h_cost, then the node
dist = goal_distance(loc, guide)
# Nodes are made up of location, move that got there,
# the cost of the node (traveled + heuristic), and the
# parent node of the current one (they're implicitly linked).
node = [loc, None, dist, None]
closest = [dist, node]
frontier = priority_queue()
frontier.push(node, dist)
explored = []
move = 0
move_list = []
while True:
if frontier.is_empty():
parent_node = closest[1]
while parent_node:
loc, action, _, parent_node = parent_node
if not action == None:
if not loop:
move = action
else:
move_list.append(action)
#print("a_sure: incomplete move: " + str(move) + " from distance " + str(goal_distance(loc, guide)))
if loop:
move_list.append(loc)
return move_list
else:
move = [move, loc]
return move
parent_node = frontier.pop()
loc, move, this_cost, grand_parent_node = parent_node
if loc in explored:
continue
if not goal_distance(loc, guide):
while parent_node:
loc, action, _, parent_node = parent_node
if not action == None:
if not loop:
move = action
else:
move_list.append(action)
#print("a_sure: complete move: " + str(move) + " from location: " + str(loc))
if loop:
move_list.append(loc)
return move_list
else:
move = [move, loc]
return move
explored.append(loc)
for new_move in get_moves(guide, loc, frame_num):
new_action, new_loc = new_move
# print("a_sure: new_action = " + str(new_action) + " new_loc = " + str(new_loc))
new_h_cost = goal_distance(new_loc, guide)
new_cost = 1 + new_h_cost
this_child_node = [new_loc, new_action, new_cost, parent_node]
if not ((new_loc in explored) or
(new_loc in frontier)) or (new_action == 0):
#print("a_sure: checked location: " + str(new_loc))
frontier.push(this_child_node, new_cost)
elif (new_loc in frontier):
#print("a_sure: re-entered location: " + str(new_loc))
frontier.push(this_child_node, new_cost)
if (new_h_cost < closest[0]):
closest = [new_h_cost, this_child_node]
elif (new_h_cost == closest[0]):
if (new_cost < closest[1][2]):
closest = [new_h_cost, this_child_node]
def alpha_beta_max(playing_board, comp_pieces, human_pieces, iteration, alpha,
beta):
# Get globals
global NODES_MADE
global MAX_PRUNES
# Find if this node is a terminal node
if is_terminal(playing_board, contents.BLACK):
return [comp_pieces, 1000, iteration]
if is_terminal(playing_board, contents.WHITE):
return [human_pieces, -1000, iteration]
# If this iteration is as far down as the tree should go
if iteration is 0:
# Get a utility of this node
utility = get_utility(comp_pieces, human_pieces, contents.BLACK)
return [comp_pieces, utility, iteration]
# Start the search!
smallest_value = -1000
potential_moves = list(comp_pieces)
# Find all the pieces that can be moved
edible = can_eat(playing_board, comp_pieces, contents.BLACK,
contents.WHITE)
# For each piece that can be moved
for i, piece in enumerate(edible[0]):
# Get the moves for that piece
all_moves_for_piece = get_moves(playing_board, piece, contents.BLACK,
contents.WHITE)
# If a piece has to be eaten
if edible[1] is True:
current_max = -1001
potential_eating_moves = None
# For all the moves that can be taken
for move in all_moves_for_piece:
# Accounts for the return of get_moves
if type(all_moves_for_piece[move]) is bool:
continue
# A new node was created
NODES_MADE += 1
# Find the new move
new_moves = list(comp_pieces)
piece_index = comp_pieces.index(piece)
new_moves[piece_index] = all_moves_for_piece[move]
# Get the utility of the node
eating_utility = get_utility(new_moves, human_pieces,
contents.BLACK)
# If this move is the best move so far
if eating_utility > current_max:
current_max = eating_utility
potential_eating_moves = list(new_moves)
# Return best move for eating
return [potential_eating_moves, current_max, iteration]
# If no piece can be eaten
for move in all_moves_for_piece:
# Accounts for the return of get_moves
if type(all_moves_for_piece[move]) is bool:
continue
# A new node was created
NODES_MADE += 1
# Find the new move
new_moves = list(comp_pieces)
new_moves[i] = all_moves_for_piece[move]
# Call the min player
minimum = alpha_beta_min(playing_board, new_moves, human_pieces,
iteration - 1, alpha, beta)
# Get the min utility
min_utility = minimum[1]
# If the min utility is a min value
if min_utility > smallest_value:
smallest_value = min_utility
potential_moves = list(new_moves)
# If the tree can be pruned
if smallest_value >= beta:
# Prune!
MAX_PRUNES += 1
return [list(new_moves), smallest_value, iteration]
# Fix alpha value
if alpha < smallest_value:
alpha = smallest_value
# If potential moves did not work out
if potential_moves is comp_pieces:
return [new_moves, smallest_value, iteration]
# If potential moves did work out
else:
return [potential_moves, smallest_value, iteration]
def alpha_beta_min(playing_board, comp_pieces, human_pieces, iteration, alpha,
beta):
# Get globals
global NODES_MADE
global MIN_PRUNES
# Find if this node is a terminal node
if is_terminal(playing_board, contents.WHITE):
return [human_pieces, -1000, iteration]
if is_terminal(playing_board, contents.BLACK):
return [comp_pieces, 1000, iteration]
# If this iteration is as far down as the tree should go
if iteration is 0:
# Get a utility of this node
utility = get_utility(human_pieces, comp_pieces, contents.WHITE)
return [human_pieces, utility, iteration]
# Start the search!
largest_value = 1000
potential_moves = list(human_pieces)
# Find all the pieces that can be moved
edible = can_eat(playing_board, human_pieces, contents.WHITE,
contents.BLACK)
# For each piece that can be moved
for i, piece in enumerate(edible[0]):
# Get the moves for that piece
all_moves_for_piece = get_moves(playing_board, piece, contents.WHITE,
contents.BLACK)
# If a piece has to be eaten
if edible[1] is True:
current_min = 1001
potential_eating_moves = None
# For all the moves that can be taken
for move in all_moves_for_piece:
# Accounts for the return of get_moves
if type(all_moves_for_piece[move]) is bool:
continue
# A new node was created
NODES_MADE += 1
# Check for a bad output
if piece in comp_pieces:
piece_index = comp_pieces.index(piece)
else:
continue
# Find the new move
new_moves = list(comp_pieces)
new_moves[piece_index] = all_moves_for_piece[move]
# Get the utility of the node
eating_utility = get_utility(new_moves, human_pieces,
contents.WHITE)
# If this move is the best move so far
if eating_utility < current_min:
current_min = eating_utility
potential_eating_moves = list(new_moves)
# Return best move for eating
return [potential_eating_moves, current_min, iteration]
# If no piece can be eaten
for move in all_moves_for_piece:
# Accounts for the return of get_moves
if type(all_moves_for_piece[move]) is bool:
continue
# A new node was created
NODES_MADE += 1
# Find the new move
new_moves = list(human_pieces)
new_moves[i] = all_moves_for_piece[move]
# Call the max player
maximum = alpha_beta_max(playing_board, comp_pieces, new_moves,
iteration - 1, alpha, beta)
# Get the max utility
max_utility = maximum[1]
# If the max utility is a max value
if max_utility < largest_value:
largest_value = max_utility
potential_moves = list(new_moves)
# If the tree can be pruned
if largest_value <= alpha:
# Prune!
MIN_PRUNES += 1
return [list(new_moves), largest_value, iteration]
# Fix beta value
if beta > largest_value:
beta = largest_value
# If potential moves did not work out
if potential_moves is comp_pieces:
return [new_moves, largest_value, iteration]
# If potential moves did work out
else:
return [potential_moves, largest_value, iteration]
import os
from sklearn.model_selection import train_test_split
from model import get_piece_moved, legal_start
from sklearn.linear_model import PassiveAggressiveClassifier
from sklearn.metrics import accuracy_score, confusion_matrix
import random
if __name__ == "__main__":
start = datetime(2018, 12, 8)
end = datetime(2021, 7, 7)
games = 500
print("gathering games")
white, black = get_moves('whoisis', start, end, games, split=True)
train, test = train_test_split(black)
train = black[:-len(black) // 9]
test = black[len(black) // 9:]
x_train = np.array([data[0] for data in train])
x_test = np.array([data[0] for data in test])
y_train = get_piece_moved([data[0] for data in train],
legal_start([data[2] for data in train], False))
y_test = get_piece_moved([data[0] for data in test],
legal_start([data[2] for data in test], False))
ans = []
for board in x_test:
ans.append(random.randint(0, 5))
