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# Copyright 2018 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
A board is a NxN numpy array.
A Coordinate is a tuple index into the board.
A Move is a (Coordinate c | None).
A PlayerMove is a (Color, Move) tuple
(0, 0) is considered to be the upper left corner of the board, and (18, 0) is the lower left.
"""
from collections import namedtuple, defaultdict
import copy
import itertools
from typing import Iterable, Sequence, Dict, Tuple, Set, Optional
import numpy as np
import os
import coords
import zobrist
N = int(os.environ.get('BOARD_SIZE', 9)) # was 19
zobrist_hasher = zobrist.ZobristHash(N)
# Position.score() switches from Tromp to Benson after this, for speed reasons
NUM_MOVES_BEFORE_BENSON = N * N // 2 # this is sensitive to go.N. 40 for 9x9
# Represent a board as a numpy array, with 0 empty, 1 is black, -1 is white.
# This means that swapping colors is as simple as multiplying array by -1.
WHITE, EMPTY, BLACK, FILL, KO, UNKNOWN = range(-1, 5)
def color_str(color: int) -> str:
if color == WHITE:
return 'WHITE'
if color == BLACK:
return 'BLACK'
if color == EMPTY:
return 'EMPTY'
return str(color)
# Represents "group not found" in the LibertyTracker object
MISSING_GROUP_ID = -1
ALL_COORDS = [(i, j) for i in range(N) for j in range(N)]
EMPTY_BOARD = np.zeros([N, N], dtype=np.int8)
def _check_bounds(c):
return 0 <= c[0] < N and 0 <= c[1] < N
NEIGHBORS = {(x, y): list(filter(_check_bounds, [
(x+1, y), (x-1, y), (x, y+1), (x, y-1)])) for x, y in ALL_COORDS}
DIAGONALS = {(x, y): list(filter(_check_bounds, [
(x+1, y+1), (x+1, y-1), (x-1, y+1), (x-1, y-1)])) for x, y in ALL_COORDS}
class IllegalMove(Exception):
pass
class PlayerMove(namedtuple('PlayerMove', ['color', 'move'])):
pass
class PositionWithContext(namedtuple('SgfPosition', ['position', 'next_move', 'result'])):
pass
def place_stones(board, color, stones):
for s in stones:
board[s] = color
def replay_position(position, result, initial_position=None):
"""
Wrapper for a go.Position which replays its history.
# Assumes an empty start position! (i.e. no handicap, and history must be exhaustive.)
Result must be passed in, since a resign cannot be inferred from position
history alone.
for position_w_context in replay_position(position):
print(position_w_context.position)
"""
pos = initial_position
if pos is None:
pos = Position(komi=position.komi)
assert position.n == len(position.recent), "Position history is incomplete"
for player_move in position.recent[pos.n:]:
color, next_move = player_move
yield PositionWithContext(pos, next_move, result)
pos = pos.play_move(next_move, color=color)
def find_reached(board: np.ndarray, c: Tuple) -> Tuple[set, set]:
""" find the chain c is in, as well as the boundary around it """
color = board[c]
chain = {c}
boundary = set()
frontier = [c]
while frontier:
current = frontier.pop()
chain.add(current)
for n in NEIGHBORS[current]:
if board[n] == color:
if n not in chain:
frontier.append(n)
else:
boundary.add(n)
return chain, boundary
def find_maximal_region_with_no(board: np.ndarray, c: Tuple, color_bound) -> Tuple[set, set]:
""" similar to find_reached, assume color_bound is black, find maximal region starting from c,
reachable thru empty or white stones
"""
assert board[c] != color_bound
chain = {c}
border = set()
frontier = [c]
while frontier:
current = frontier.pop()
chain.add(current)
for n in NEIGHBORS[current]:
if board[n] != color_bound:
if n not in chain:
frontier.append(n)
else:
border.add(n)
return chain, border
def is_koish(board, c):
'Check if c is surrounded on all sides by 1 color, and return that color'
if board[c] != EMPTY:
return None
neighbors = {board[n] for n in NEIGHBORS[c]}
if len(neighbors) == 1 and EMPTY not in neighbors:
return list(neighbors)[0]
else:
return None
def is_eyeish(board, c):
'Check if c is an eye, for the purpose of restricting MC rollouts.'
# pass is fine.
if c is None:
return
color = is_koish(board, c)
if color is None:
return None
diagonal_faults = 0
diagonals = DIAGONALS[c]
if len(diagonals) < 4:
diagonal_faults += 1
for d in diagonals:
if not board[d] in (color, EMPTY):
diagonal_faults += 1
if diagonal_faults > 1:
return None
else:
return color
class Group(namedtuple('Group', ['id', 'stones', 'liberties', 'color'])):
"""
stones: a frozenset of Coordinates belonging to this group
liberties: a frozenset of Coordinates that are empty and adjacent to this group.
color: color of this group
"""
def __eq__(self, other):
return self.stones == other.stones and self.liberties == other.liberties and self.color == other.color
class LibertyTracker():
@staticmethod
def from_board(board: np.ndarray) -> 'LibertyTracker':
board = np.copy(board)
curr_group_id = 0
lib_tracker = LibertyTracker()
for color in (WHITE, BLACK):
while color in board:
curr_group_id += 1
found_color = np.where(board == color)
coord = found_color[0][0], found_color[1][0]
chain, reached = find_reached(board, coord)
liberties = frozenset(r for r in reached if board[r] == EMPTY)
new_group = Group(curr_group_id, frozenset(chain), liberties, color)
lib_tracker.groups[curr_group_id] = new_group
for s in chain:
lib_tracker.group_index[s] = curr_group_id
place_stones(board, FILL, chain)
lib_tracker.max_group_id = curr_group_id
liberty_counts = np.zeros([N, N], dtype=np.uint8)
for group in lib_tracker.groups.values():
num_libs = len(group.liberties)
for s in group.stones:
liberty_counts[s] = num_libs
lib_tracker.liberty_cache = liberty_counts
return lib_tracker
def __init__(self, group_index=None, groups=None, liberty_cache=None, max_group_id=1):
# group_index: a NxN numpy array of group_ids. -1 means no group
# groups: a dict of group_id to groups
# liberty_cache: a NxN numpy array of liberty counts
self.group_index = group_index if group_index is not None else -np.ones([N, N], dtype=np.int32) # type: np.ndarray
self.groups = groups or {} # type: Dict[int, Group]
self.liberty_cache = liberty_cache if liberty_cache is not None else np.zeros([N, N], dtype=np.uint8) # type: np.ndarray
self.max_group_id = max_group_id
def __deepcopy__(self, memodict={}):
new_group_index = np.copy(self.group_index)
new_lib_cache = np.copy(self.liberty_cache)
# shallow copy
new_groups = copy.copy(self.groups)
return LibertyTracker(new_group_index, new_groups, liberty_cache=new_lib_cache, max_group_id=self.max_group_id)
def add_stone(self, color, c) -> set:
assert self.group_index[c] == MISSING_GROUP_ID
captured_stones = set()
opponent_neighboring_group_ids = set()
friendly_neighboring_group_ids = set()
empty_neighbors = set()
for n in NEIGHBORS[c]:
neighbor_group_id = self.group_index[n]
if neighbor_group_id != MISSING_GROUP_ID:
neighbor_group = self.groups[neighbor_group_id]
if neighbor_group.color == color:
friendly_neighboring_group_ids.add(neighbor_group_id)
else:
opponent_neighboring_group_ids.add(neighbor_group_id)
else:
empty_neighbors.add(n)
new_group = self._merge_from_played(
color, c, empty_neighbors, friendly_neighboring_group_ids)
# new_group becomes stale as _update_liberties and
# _handle_captures are called; must refetch with self.groups[new_group.id]
for group_id in opponent_neighboring_group_ids:
neighbor_group = self.groups[group_id]
if len(neighbor_group.liberties) == 1:
captured = self._capture_group(group_id)
captured_stones.update(captured)
else:
self._update_liberties(group_id, remove={c})
self._handle_captures(captured_stones)
# suicide is illegal
if len(self.groups[new_group.id].liberties) == 0:
raise IllegalMove("Move at {} would commit suicide!\n".format(c))
return captured_stones
def _merge_from_played(self, color, played, libs, other_group_ids):
stones = {played}
liberties = set(libs)
for group_id in other_group_ids:
other = self.groups.pop(group_id)
stones.update(other.stones)
liberties.update(other.liberties)
if other_group_ids:
liberties.remove(played)
assert stones.isdisjoint(liberties)
self.max_group_id += 1
result = Group(
self.max_group_id,
frozenset(stones),
frozenset(liberties),
color)
self.groups[result.id] = result
for s in result.stones:
self.group_index[s] = result.id
self.liberty_cache[s] = len(result.liberties)
return result
def _capture_group(self, group_id):
dead_group = self.groups.pop(group_id)
for s in dead_group.stones:
self.group_index[s] = MISSING_GROUP_ID
self.liberty_cache[s] = 0
return dead_group.stones
def _update_liberties(self, group_id, add=set(), remove=set()):
group = self.groups[group_id]
new_libs = (group.liberties | add) - remove
self.groups[group_id] = Group(
group_id, group.stones, new_libs, group.color)
new_lib_count = len(new_libs)
for s in self.groups[group_id].stones:
self.liberty_cache[s] = new_lib_count
def _handle_captures(self, captured_stones):
for s in captured_stones:
for n in NEIGHBORS[s]:
group_id = self.group_index[n]
if group_id != MISSING_GROUP_ID:
self._update_liberties(group_id, add={s})
class Region(namedtuple('Region', ['id', 'stones', 'liberties', 'chains', 'color'])):
"""
stones: a frozenset of Coordinates belonging to this region
liberties: subset of area that are empty
chains: enclosing chains
color: empty if all empty, otherwise color of the opponent
"""
def __eq__(self, other):
return self.stones == other.stones and self.liberties == other.liberties and \
self.chains == other.chains and self.color == other.color
class BensonAnalyzer:
""" Benson's algorithm to determine pass-alive chains
Let X be the set of all Black chains and R be the set of all Black-enclosed regions of X.
Then Benson's algorithm requires iteratively applying the following two steps until neither
is able to remove any more chains or regions:
Remove from X all Black chains with less than two vital Black-enclosed regions in R, where a Black-enclosed region
is **vital** to a Black chain in X if *all* its empty intersections are also liberties of the chain.
Remove from R all Black-enclosed regions with a surrounding stone in a chain not in X.
The final set X is the set of all unconditionally alive Black chains.
- is it easy to incrementally update its status?
"""
def __init__(self, board: np.ndarray, color_bound):
""" color_bound: if black, we analyze black chains & black-"enclosed" regions.
"""
self.region_index = -np.ones([N, N], dtype=np.int32) # type: np.ndarray
self.regions = dict() # type: Dict[int, Region]
self.max_region_id = 0
self.lib_tracker = LibertyTracker.from_board(board)
self._find_enclosed_regions(board, color_bound)
self.color_bound = color_bound
def _find_enclosed_regions(self, board, color_bound):
"""
Black-enclosed regions: start from empty spots, find the max region (include white) that's surrounded by black
or wall. This is similar to a chain, just that it's the maximal region of empty+white
"""
board = np.copy(board)
lib_tracker = self.lib_tracker
curr_region_id = 0
for color in (EMPTY,):
while color in board:
curr_region_id += 1
found_color = np.where(board == color)
coord = found_color[0][0], found_color[1][0]
region, reached = find_maximal_region_with_no(board, coord, color_bound)
liberties = frozenset(r for r in region if board[r] == EMPTY)
# reached -> set of bordering chains
chains = frozenset(lib_tracker.group_index[s] for s in reached)
assert all(lib_tracker.groups[i].color == color_bound for i in chains)
# region color indicates presence of enemy stone
region_color = -color_bound if len(liberties) < len(region) else color
new_region = Region(curr_region_id, frozenset(region), liberties, chains, region_color)
self.regions[curr_region_id] = new_region
for s in region:
self.region_index[s] = curr_region_id
place_stones(board, FILL, region)
self.max_region_id = curr_region_id
@staticmethod
def from_board(board: np.ndarray, color_bound) -> 'BensonAnalyzer':
return BensonAnalyzer(board, color_bound)
def eliminate(self) -> Tuple[Set[int], Iterable[Region]]:
""" find pass-alive chains for color, using Benson's algorithm.
Note we use regions returned for scoring purposes. They need to be what Benson's original algo specifies.
regions are mainly black-enclosed regions, but could be a big neighboring white region (side-by-side)
"""
chains_current = set(idx for idx, chain in self.lib_tracker.groups.items() if chain.color == self.color_bound)
regions_current = [r for r in self.regions.values()]
for i in range(100):
# print(f'Benson iter {i}: %d chains, %d regions' % (len(chains_current), len(regions_current)))
num_vital_regions = defaultdict(int)
for region in regions_current:
# see which chains this is vital for
for chain_idx in region.chains:
chain = self.lib_tracker.groups[chain_idx]
if len(chain.liberties) < len(region.liberties):
continue
if region.liberties.issubset(chain.liberties):
num_vital_regions[chain_idx] += 1
# see if it has at least two (small) vital regions
chains_pruned = set(idx for idx in chains_current if num_vital_regions[idx] >= 2)
# prune regions
regions_pruned = [r for r in regions_current if all(chain_idx in chains_pruned for chain_idx in r.chains)]
if len(chains_pruned) == 0:
return chains_pruned, []
if len(chains_pruned) == len(chains_current) and len(regions_pruned) == len(regions_current):
return chains_pruned, regions_pruned
chains_current, regions_current = chains_pruned, regions_pruned
def remove_non_vital_regions(self):
""" remove regions that are not vital to any safe chain.
This just establish eye-space better
"""
# regions_final = [r for r in regions_pruned if r.id in vital_regions]
# regions_nonvital = [r for r in regions_pruned if r.id not in vital_regions]
# if regions_nonvital:
# print('final regions: removed %d of %d' % (len(regions_nonvital), len(regions_pruned)))
# print('\t#opp stones: %s' % [len(r.stones) - len(r.liberties) for r in regions_nonvital])
class BensonScoreDetail(namedtuple('BensonScoreDetail', ['score', 'final', 'black_area', 'white_area'])):
""" This counts unconditional live areas correctly; for everything else, it resorts to Tromp scoring.
Note: when final=True, we are sure of the winner, but score might not be exact, since the game may not
have finished (but won't affect final winner). score sign should be correct.
score has komi baked in
"""
pass
class Position:
def __init__(self, board=None, n=0, komi=5.5, caps=(0, 0),
lib_tracker=None, ko=None, recent=tuple(),
board_deltas=None, to_play=BLACK, zobrist_hash=None):
"""
board: a numpy array
n: an int representing moves played so far
komi: a float, representing points given to the second player.
caps: a (int, int) tuple of captures for B, W.
lib_tracker: a LibertyTracker object
ko: a Move
recent: a tuple of PlayerMoves, such that recent[-1] is the last move.
board_deltas: a np.array of shape (n, go.N, go.N) representing changes
made to the board at each move (played move and captures).
Should satisfy next_pos.board - next_pos.board_deltas[0] == pos.board
to_play: BLACK or WHITE
"""
assert type(recent) is tuple
self.board = board if board is not None else np.copy(EMPTY_BOARD)
# With a full history, self.n == len(self.recent) == num moves played
self.n = n
self.komi = komi
self.caps = caps
self.lib_tracker = lib_tracker or LibertyTracker.from_board(self.board)
self.ko = ko
self.recent = recent # type: Sequence[PlayerMove]
self.board_deltas = board_deltas if board_deltas is not None else np.zeros([
0, N, N], dtype=np.int8)
self.to_play = to_play
if zobrist_hash is None:
self.zobrist_hash = zobrist_hasher.EMPTY_BOARD_HASH if board is None else zobrist_hasher.board_hash(board)
else:
self.zobrist_hash = zobrist_hash
def __deepcopy__(self, memodict={}):
new_board = np.copy(self.board)
new_lib_tracker = copy.deepcopy(self.lib_tracker)
return Position(new_board, self.n, self.komi, self.caps, new_lib_tracker, self.ko, self.recent,
self.board_deltas, self.to_play, self.zobrist_hash)
def __str__(self, colors=True):
if colors:
pretty_print_map = {
WHITE: '\x1b[0;31;47mO',
EMPTY: '\x1b[0;31;43m.',
BLACK: '\x1b[0;31;40mX',
FILL: '#',
KO: '*',
}
else:
pretty_print_map = {
WHITE: 'O',
EMPTY: '.',
BLACK: 'X',
FILL: '#',
KO: '*',
}
board = np.copy(self.board)
captures = self.caps
if self.ko is not None:
place_stones(board, KO, [self.ko])
raw_board_contents = []
for i in range(N):
row = [' ']
for j in range(N):
appended = '<' if (self.recent and (i, j) ==
self.recent[-1].move) else ' '
row.append(pretty_print_map[board[i, j]] + appended)
if colors:
row.append('\x1b[0m')
raw_board_contents.append(''.join(row))
row_labels = ['%2d' % i for i in range(N, 0, -1)]
annotated_board_contents = [''.join(r) for r in zip(
row_labels, raw_board_contents, row_labels)]
header_footer_rows = [
' ' + ' '.join('ABCDEFGHJKLMNOPQRST'[:N]) + ' ']
annotated_board = '\n'.join(itertools.chain(
header_footer_rows, annotated_board_contents, header_footer_rows))
details = "\nMove: {}. Captures X: {} O: {}\n".format(
self.n, *captures)
return annotated_board + details
def is_move_suicidal(self, move):
potential_libs = set()
for n in NEIGHBORS[move]:
neighbor_group_id = self.lib_tracker.group_index[n]
if neighbor_group_id == MISSING_GROUP_ID:
# at least one liberty after playing here, so not a suicide
return False
neighbor_group = self.lib_tracker.groups[neighbor_group_id]
if neighbor_group.color == self.to_play:
potential_libs |= neighbor_group.liberties
elif len(neighbor_group.liberties) == 1:
# would capture an opponent group if they only had one lib.
return False
# it's possible to suicide by connecting several friendly groups
# each of which had one liberty.
potential_libs -= set([move])
return not potential_libs
def is_move_legal(self, move):
'Checks that a move is on an empty space, not on ko, and not suicide'
if move is None:
return True
if self.board[move] != EMPTY:
return False
if move == self.ko:
return False
if self.is_move_suicidal(move):
return False
return True
def all_legal_moves(self) -> np.ndarray:
""" Returns a np.array of size go.N**2 + 1, with 1 = legal, 0 = illegal """
# by default, every move is legal
legal_moves = np.ones([N, N], dtype=np.int8)
# ...unless there is already a stone there
legal_moves[self.board != EMPTY] = 0
# calculate which spots have 4 stones next to them
# padding is because the edge always counts as a lost liberty.
adjacent = np.ones([N + 2, N + 2], dtype=np.int8)
adjacent[1:-1, 1:-1] = np.abs(self.board)
num_adjacent_stones = (adjacent[:-2, 1:-1] + adjacent[1:-1, :-2] +
adjacent[2:, 1:-1] + adjacent[1:-1, 2:])
# Surrounded spots are those that are empty and have 4 adjacent stones.
surrounded_spots = np.multiply(
(self.board == EMPTY),
(num_adjacent_stones == 4))
# Such spots are possibly illegal, unless they are capturing something.
# Iterate over and manually check each spot.
for coord in np.transpose(np.nonzero(surrounded_spots)):
if self.is_move_suicidal(tuple(coord)):
legal_moves[tuple(coord)] = 0
# ...and retaking ko is always illegal
if self.ko is not None:
legal_moves[self.ko] = 0
# and pass is always legal
return np.concatenate([legal_moves.ravel(), [1]])
def pass_move(self, mutate=False) -> 'Position':
pos = self if mutate else copy.deepcopy(self)
pos.n += 1
pos.recent += (PlayerMove(pos.to_play, None),)
pos.board_deltas = np.concatenate((
np.zeros([1, N, N], dtype=np.int8),
pos.board_deltas[:6]))
pos.to_play *= -1
pos.ko = None
return pos
def flip_playerturn(self, mutate=False):
pos = self if mutate else copy.deepcopy(self)
pos.ko = None
pos.to_play *= -1
return pos
def get_liberties(self):
return self.lib_tracker.liberty_cache
def play_move(self, c: Optional[Tuple], color=None, mutate=False) -> 'Position':
"""
color=None means the next player
# Obeys CGOS Rules of Play. In short:
# No suicides
# Chinese/area scoring
# Positional superko (this is very crudely approximate at the moment.)
"""
if color is None:
color = self.to_play
if c is None:
pos = self.pass_move(mutate=mutate)
return pos
pos = self if mutate else copy.deepcopy(self)
if not self.is_move_legal(c):
raise IllegalMove("{} move at {} is illegal: \n{}".format(
"Black" if self.to_play == BLACK else "White",
coords.to_gtp(c), self))
potential_ko = is_koish(self.board, c)
place_stones(pos.board, color, [c])
captured_stones = pos.lib_tracker.add_stone(color, c)
place_stones(pos.board, EMPTY, captured_stones)
opp_color = color * -1
new_board_delta = np.zeros([N, N], dtype=np.int8)
new_board_delta[c] = color
place_stones(new_board_delta, color, captured_stones)
if len(captured_stones) == 1 and potential_ko == opp_color:
new_ko = list(captured_stones)[0]
else:
new_ko = None
if pos.to_play == BLACK:
new_caps = (pos.caps[0] + len(captured_stones), pos.caps[1])
else:
new_caps = (pos.caps[0], pos.caps[1] + len(captured_stones))
pos.n += 1
pos.caps = new_caps
pos.ko = new_ko
pos.recent += (PlayerMove(color, c),)
pos.zobrist_hash = zobrist_hasher.hash_after_move(self, c, captured_stones)
# keep a rolling history of last 7 deltas - that's all we'll need to
# extract the last 8 board states.
pos.board_deltas = np.concatenate((
new_board_delta.reshape(1, N, N),
pos.board_deltas[:6]))
pos.to_play *= -1
return pos
def is_game_over(self):
return (len(self.recent) >= 2 and
self.recent[-1].move is None and
self.recent[-2].move is None)
def score_tromp(self, mask: np.array = None) -> float:
"""Return score from B perspective. If W is winning, score is negative.
score = 0 could happen if komi is integer
"""
working_board = np.copy(self.board)
return self._score_board(working_board, mask=mask)
def _score_board(self, working_board, mask: np.array = None):
""" mask: when present, restrict scoring to area where mask != 0.
Note coloring remains the same (the entire board is used)
"""
while EMPTY in working_board:
unassigned_spaces = np.where(working_board == EMPTY)
c = unassigned_spaces[0][0], unassigned_spaces[1][0]
territory, borders = find_reached(working_board, c)
border_colors = set(working_board[b] for b in borders)
X_border = BLACK in border_colors
O_border = WHITE in border_colors
if X_border and not O_border:
territory_color = BLACK
elif O_border and not X_border:
territory_color = WHITE
else:
territory_color = UNKNOWN # dame, or seki
place_stones(working_board, territory_color, territory)
if mask is not None:
mask = mask[:N*N].reshape((N, N))
working_board[mask == 0] = 0
return np.count_nonzero(working_board == BLACK) - np.count_nonzero(working_board == WHITE) - self.komi
def score(self) -> float:
""" score has komi baked in """
if self.n < NUM_MOVES_BEFORE_BENSON:
# Pass-alive typically happens later in game. Use Tromp which is faster
return self.score_tromp()
score_detail = self._benson_analysis()
return score_detail.score
def score_benson(self) -> BensonScoreDetail:
return self._benson_analysis()
def _benson_analysis(self) -> BensonScoreDetail:
""" based on Benson's algo: this method will remove dead stones in pass-alive area
It also indicates whether winner is final: either all area is settled, or that winner's margin is large enough
"""
working_board = np.copy(self.board)
# first, mark pass-alive area
area_passalive = [0, 0] # black live, white live
num_removed = [0, 0] # white dead in black area, black dead in white area
for icolor, color in enumerate((BLACK, WHITE)):
analyzer = BensonAnalyzer(self.board, color)
chain_ids, regions = analyzer.eliminate()
num_dead_stones = 0
for region in regions: # region is black-enclosed, but could be completely owned by white
num_opp_stones = len(region.stones) - len(region.liberties)
if num_opp_stones >= 4 and len(region.liberties) >= 2:
# heuristics: consider 3 white stones not survivable in a black pass-alive area
# Either white region (with 2 potential eyes), or white could survive, consider it unsettled
continue
num_dead_stones += num_opp_stones
place_stones(working_board, color, region.stones)
area_passalive[icolor] += len(region.stones)
num_removed[icolor] = num_dead_stones
for chain_id in chain_ids:
chain = analyzer.lib_tracker.groups[chain_id]
assert chain.color == color
area_passalive[icolor] += len(chain.stones)
# see if we know the winner regardless of unsettled area
num_unsettled = N * N - sum(area_passalive)
advantage = area_passalive[0] - area_passalive[1] - self.komi
game_over = abs(advantage) > num_unsettled or num_unsettled == 0
# everything else, use Tromp scoring
score = self._score_board(working_board)
# this should always hold: when game_over, score should always have the right sign as winner
# if game_over:
# assert np.sign(advantage) == np.sign(score)
# if game_over:
# print('benson scoring: advantage=%.1f, unsettled area=%d, game over' % (advantage, num_unsettled))
# if sum(num_removed) > 0:
# print(f'score_benson: removed %s dead stones from pass-alive area -> %.1f' % (num_removed, score))
return BensonScoreDetail(score, game_over, area_passalive[0], area_passalive[1])
def result(self):
score = self.score()
if score > 0:
return 1
elif score < 0:
return -1
else:
return 0
def result_string(self):
score = self.score()
if score > 0:
return 'B+' + '%.1f' % score
elif score < 0:
return 'W+' + '%.1f' % abs(score)
else:
return 'DRAW'