refactor: proper classes for hanabi instances and games
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3 changed files with 338 additions and 9 deletions
33
constants.py
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33
constants.py
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# constants.py
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# some values shared by all (default) hanabi instances
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HAND_SIZES = {2: 5, 3: 5, 4: 4, 5: 4, 6: 3}
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NUM_STRIKES = 3
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COLOR_INITIALS = 'rygbp'
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PLAYER_NAMES = ["Alice", "Bob", "Cathy", "Donald", "Emily", "Frank"]
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#### hanab.live stuff
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# Id of no variant
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NO_VARIANT_ID = 0
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# a map (num_suits, num_dark_suits) -> variant id of a variant on hanab.live fitting that distribution
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VARIANT_IDS_STANDARD_DISTRIBUTIONS = {
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3: {
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0: 18 # 3 Suits
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},
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4: {
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0: 15 # 4 Suits
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},
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5: {
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0: 0, # No Variant
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1: 21 # Black (5 Suits)
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},
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6: {
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0: 1, # 6 Suits
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1: 2, # Black (6 Suits)
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2: 60, # Black & Gray
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}
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}
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280
hanabi.py
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280
hanabi.py
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from typing import Optional, List
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from enum import Enum
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import constants
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class DeckCard():
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def __init__(self, suitIndex: int, rank: int, deck_index=None):
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self.suitIndex: int = suitIndex
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self.rank: int = rank
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self.deck_index: Optional[int] = deck_index
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@staticmethod
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def from_json(deck_card):
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return DeckCard(**deck_card)
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def colorize(self):
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color = ["green", "blue", "magenta", "yellow", "white", "cyan"][self.suitIndex]
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return colored(str(self), color)
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def __eq__(self, other):
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return self.suitIndex == other.suitIndex and self.rank == other.rank
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def __repr__(self):
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return constants.COLOR_INITIALS[self.suitIndex] + str(self.rank)
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def __hash__(self):
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# should be injective enough, we never use cards with ranks differing by 1000
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return 1000 * self.suitIndex + self.rank
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class ActionType(Enum):
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Play = 0
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Discard = 1
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ColorClue = 2
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RankClue = 3
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EndGame = 4
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VoteTerminate = 5 ## hack: online, this is encoded as a 10
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class Action():
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def __init__(self, type_: ActionType, target: int, value: Optional[int] = None):
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self.type = type_
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self.target = target
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self.value = value
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@staticmethod
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def from_json(action):
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return Action(
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ActionType(action['type']),
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int(action['target']),
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action.get('value', None)
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)
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def __repr__(self):
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match self.type:
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case ActionType.Play:
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return "Play card {}".format(self.target)
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case ActionType.Discard:
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return "Discard card {}".format(self.target)
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case ActionType.ColorClue:
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return "Clue color {} to player {}".format(self.value, self.target)
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case ActionType.RankClue:
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return "Clue rank {} to player {}".format(self.value, self.target)
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case ActionType.EndGame:
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return "Player {} ends the game (code {})".format(self.target, self.value)
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case ActionType.VoteTerminate:
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return "Players vote to terminate the game (code {})".format(self.value)
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return "Undefined action"
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class HanabiInstance():
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def __init__(
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self,
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deck: List[DeckCard], # assumes a default deck, every suit has to be distributed either [1,1,1,2,2,3,3,4,4,5] or [1,2,3,4,5]
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num_players: int, # number of players that play this deck, in range [2,6]
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hand_size: Optional[int] = None, # number of cards that each player holds
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num_strikes: Optional[int] = None, # number of strikes that leads to game loss
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variant_id: Optional[int] = None # optional: variant id of hanab.live, useful if instance gets exported to be viewed in browser
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):
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assert(2 <= num_players <= 6)
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# defining properties
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self.deck = deck
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self.num_players = num_players
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self.hand_size = hand_size or constants.HAND_SIZES[self.num_players]
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self.num_strikes = num_strikes or constants.NUM_STRIKES
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# normalize deck indices
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for (idx, card) in enumerate(self.deck):
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card.deck_index = idx
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# deducable properties, to be calculated once
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self.num_suits = max(map(lambda c: c.suitIndex, deck)) + 1
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self.num_dark_suits = (len(deck) - 10 * self.num_suits) // (-5)
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self.player_names = constants.PLAYER_NAMES[:self.num_players]
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self.deck_size = len(self.deck)
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## maximum number of moves in any game that can achieve max score
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# each suit gives 15 moves, as we can play and discard 5 cards each and give 5 clues. dark suits only give 5 moves, since no discards are added
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# number of cards that remain in players hands after end of game. they cost 2 turns each, since we cannot discard them and also have one clue less
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# 8 clues at beginning, one further clue for each suit but one (the clue of the last 5 is never useful since it is gained in the extra-round)
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# subtract a further move for a second 5-clue that can't be used in 5 or 6-player games, since the extraround starts too soon
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self.max_winning_moves = 15 * self.num_suits - 10 * self.num_dark_suits \
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- 2 * self.num_players * (self.hand_size - 1) \
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+ 8 + (self.num_suits - 1) \
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+ (-1 if self.num_players >= 5 else 0)
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# TODO: set a meaningful default here for export?
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self._variant_id: Optional[int] = variant_id
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@property
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def num_dealt_cards(self):
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return self.num_players * self.hand_size
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@property
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def draw_pile_size(self):
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return self.deck_size - self.num_dealt_cards
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@property
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def variant_id(self):
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if self._variant_id is not None:
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return self._variant_id
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else:
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# ensure no key error can happen
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assert(self.is_standard())
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return constants.VARIANT_IDS_STANDARD_DISTRIBUTIONS[self.num_suits][self.num_dark_suits]
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# returns True if the instance has values matching hanabi-live rules
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# (i.e. standard + extra variants with 5 / 6 suits)
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def is_standard(self):
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return all([
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2 <= self.num_players <= 6,
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self.hand_size == constants.HAND_SIZES[self.num_players],
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self.num_strikes == constants.NUM_STRIKES,
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3 <= self.num_suits <= 6,
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0 <= self.num_dark_suits <= 2,
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4 <= self.num_suits - self.num_dark_suits or self.num_suits == 3
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# TODO: check that variant id matches deck distribution
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]
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)
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class GameState():
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def __init__(self, instance: HanabiInstance):
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# will not be modified
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self.instance = instance
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# dynamic game state
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self.progress = self.instance.num_players * self.instance.hand_size # index of next card to be drawn
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self.hands = [self.instance.deck[self.instance.hand_size * p : self.instance.hand_size * (p+1)] for p in range(0, self.instance.num_players)]
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self.stacks = [0 for i in range(0, self.instance.num_suits)]
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self.strikes = 0
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self.clues = 8
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self.turn = 0
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self.pace = self.instance.deck_size - 5 * self.instance.num_suits - self.instance.num_players * (self.instance.hand_size - 1)
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self.remaining_extra_turns = self.instance.num_players + 1
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self.trash = []
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# can be set to true if game is known to be in a lost state
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self.in_lost_state = False
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# will track replay as game progresses
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self.actions = []
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## Methods to control game state change
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def make_action(self, Action):
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match Action.ActionType:
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case ActionType.clue:
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self.clue()
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case ActionType.Play:
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self.play(action.target)
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def play(self, card_idx):
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card = self.instance.deck[card_idx]
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if card.rank == self.stacks[card.suitIndex] + 1:
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self.stacks[card.suitIndex] += 1
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if card.rank == 5 and self.clues != 8:
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self.clues += 1
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else:
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self.strikes += 1
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assert (self.strikes < instance.num_strikes)
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self.trash.append(instance.deck[card_idx])
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self.actions.append(Action(ActionType.Play, target=card_idx))
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self.__replace(card_idx)
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self.__make_turn()
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def discard(self, card_idx):
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assert(self.clues < 8)
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self.actions.append(Action(ActionType.Discard, target=card_idx))
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self.clues += 1
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self.pace -= 1
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self.trash.append(instance.deck[card_idx])
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self.__replace(card_idx)
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self.__make_turn()
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def clue(self):
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assert(self.clues > 0)
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self.actions.append(
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Action(
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ActionType.RankClue,
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target=(self.turn +1) % self.instance.num_players, # clue next plyaer
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value=self.hands[(self.turn +1) % self.instance.num_players][0].rank # clue index 0
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)
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)
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self.clues -= 1
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self.__make_turn()
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# Properties of GameState
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def is_over(self):
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return all(s == 5 for s in self.stacks) or (self.remaining_extra_turns == 0) or (self.is_known_lost())
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def is_won(self):
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return self.score == 5 * instance.num_suits
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def is_known_lost(self):
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return self.in_lost_state
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@property
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def score(self):
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return sum(self.stacks)
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@property
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def cur_hand(self):
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return self.hands[self.turn]
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# Utilities
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def holding_players(self, card):
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for (player, hand) in enumerate(self.hands):
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if card in hand:
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yield player
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def to_json(self):
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# ensure we have at least one action
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if len(self.actions) == 0:
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self.actions.append(Action(
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ActionType.EndGame,
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target=0
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)
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)
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return {
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"deck": instance.deck,
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"players": instance.players,
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"actions": self.actions,
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"first_player": 0,
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"options": {
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"variant": "No Variant",
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}
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}
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# Private helpers
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# increments turn counter and tracks extra round
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def __make_turn(self):
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assert(self.remaining_extra_turns > 0)
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self.turn = (self.turn + 1) % self.instance.num_players
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if self.progress == self.instance.deck_size:
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self.remaining_extra_turns -= 1
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# replaces the specified card (has to be in current player's hand) with the next card of the deck (if nonempty)
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def __replace(self, card_idx):
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idx_in_hand = next((i for (i, card) in enumerate(self.cur_hand) if card.deck_index == card_idx), None)
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assert(idx_in_hand is not None)
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for i in range(idx_in_hand, self.instance.hand_size - 1):
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self.cur_hand[i] = self.cur_hand[i + 1]
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if self.progress < self.instance.deck_size:
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self.cur_hand[self.instance.hand_size - 1] = self.instance.deck[self.progress]
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self.progress += 1
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@ -11,6 +11,7 @@ from threading import Lock
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from time import sleep, perf_counter
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from greedy_solver import GameState, GreedyStrategy
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from logger_setup import logger
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from deck_analyzer import analyze, InfeasibilityReason, InfeasibilityType
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MAX_PROCESSES=4
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@ -106,8 +107,14 @@ def get_decks_for_all_seeds():
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mutex = Lock()
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def solve_instance(num_players, deck):
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# first, sanity check on running out of pace
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result = analyze(deck, num_players)
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if result is not None:
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assert type(result) == InfeasibilityReason
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logger.info("found infeasible deck")
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return False, None, None
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for num_remaining_cards in [0, 5, 10, 20, 30]:
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# print("trying with {} greedy moves".format(num_greedy_moves))
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# logger.info("trying with {} remaining cards".format(num_remaining_cards))
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game = GameState(num_players, deck)
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strat = GreedyStrategy(game)
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@ -124,10 +131,11 @@ def solve_instance(num_players, deck):
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# now, apply sat solver
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if not game.is_over():
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logger.info("continuing greedy sol with SAT")
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solvable, sol = solve_sat(game)
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if solvable:
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return solvable, sol, num_remaining_cards
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logger.info("No success, reducing number of greedy moves, failed attempt was: {}".format(link(game.to_json())))
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return True, sol, num_remaining_cards
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logger.info("No success with {} remaining cards, reducing number of greedy moves, failed attempt was: {}".format(num_remaining_cards, link(game.to_json())))
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# print("Aborting trying with greedy strat")
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logger.info("Starting full SAT solver")
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game = GameState(num_players, deck)
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@ -143,17 +151,22 @@ def solve_seed(seed, num_players, deck_compressed, var_id):
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logger.info("Solved instance {} in {} seconds".format(seed, round(t1-t0, 2)))
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mutex.acquire()
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if solvable is not None:
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lcur = conn.cursor()
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lcur.execute("UPDATE seeds SET feasible = (%s) WHERE seed = (%s)", (solvable, seed))
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conn.commit()
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if solvable:
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if solvable == True:
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with open("remaining_cards.txt", "a") as f:
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f.write("Success with {} cards left in draw by greedy solver on seed {}: {}\n".format(num_remaining_cards, seed ,link(solution.to_json())))
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if not solvable:
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elif solvable == False:
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logger.info("seed {} was not solvable".format(seed))
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with open('infeasible_instances.txt', 'a') as f:
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f.write('{}-player, seed {:10}, {}\n'.format(num_players, seed, variant_name(var_id)))
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elif solvable is None:
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logger.info("seed {} skipped".format(seed))
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else:
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raise Exception("Programming Error")
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mutex.release()
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@ -164,6 +177,9 @@ def solve_unknown_seeds():
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cur.execute("SELECT seed, num_players, deck FROM seeds WHERE variant_id = (%s) AND feasible IS NULL AND deck IS NOT NULL", (var['id'],))
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res = cur.fetchall()
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# for r in res:
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# solve_seed(r[0], r[1], r[2], var['id'])
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with concurrent.futures.ProcessPoolExecutor(max_workers=MAX_PROCESSES) as executor:
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fs = [executor.submit(solve_seed, r[0], r[1], r[2], var['id']) for r in res]
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with alive_bar(len(res), title='Seed solving on {}'.format(var['name'])) as bar:
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