def find_puzzle_candidates(game: Game, scan_depth=SCAN_DEPTH) -> List[Puzzle]:
""" finds puzzle candidates from a chess game
"""
log(Color.DIM, "Scanning game for puzzles (depth: %d)..." % scan_depth)
prev_score = Cp(0)
puzzles = []
i = 0
node = game
while not node.is_end():
next_node = node.variation(0)
next_board = next_node.board()
cur_score = AnalysisEngine.best_move(next_board, scan_depth).score
board = node.board()
highlight_move = False
if should_investigate(prev_score, cur_score, board):
highlight_move = True
puzzle = Puzzle(
board,
next_node.move,
)
puzzles.append(puzzle)
log_move(board, next_node.move, cur_score, highlight=highlight_move)
prev_score = cur_score
node = next_node
i += 1
return puzzles
def _calculate_best_move(self, depth):
""" Find the best move from board position using multipv 1
"""
log(Color.BLACK, "Evaluating best move (depth %d)..." % depth)
best_move = AnalysisEngine.best_move(self.board, depth)
self.best_move = best_move.move
self.score = best_move.score
if self._num_legal_moves() == 1:
self.candidate_moves = [best_move]
self._log_move(self.best_move, self.score)
def _analyze_best_initial_move(self, depth) -> Move:
log(Color.BLACK, "Evaluating best initial move (depth %d)..." % depth)
best_move = AnalysisEngine.best_move(self.initial_board, depth)
if best_move.move:
self.analyzed_moves.append(best_move)
log_move(self.initial_board,
best_move.move,
best_move.score,
show_uci=True)
self.initial_score = best_move.score
return best_move.move