9e2fe0cae6
- Create python directory with data/, model/ subdirectories - Implement LinearEval(61072->1) model - Add config, constants, feature_extractor - Add tests with 4 passing test cases
47 lines
1.1 KiB
Python
47 lines
1.1 KiB
Python
"""Generate training data from PGN files"""
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import chess
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import chess.pgn
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import io
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from typing import List, Tuple
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from python.constants import TOTAL_FEATURES
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def parse_pgn(pgn_string: str) -> List[str]:
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"""
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Extract FENs from PGN string.
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Yields:
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FEN strings at key positions (start of each game, after each move)
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"""
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game = chess.pgn.read_string(pgn_string)
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# Yield opening position
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if game.board():
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yield game.board().fen()
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# Yield after each move
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for move in game.mainline_moves():
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board = game.board().copy()
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board.push(move)
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yield board.fen()
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def generate_data_from_pgn(pgn_text: str) -> Tuple[List[float], List[float]]:
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"""
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Generate (features, evaluation) pairs from PGN.
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For now, returns placeholder data.
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"""
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fen_list = list(parse_pgn(pgn_text))
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features_list = []
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evals_list = []
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for fen in fen_list:
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# TODO: Extract features
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features_list.append([0.0] * TOTAL_FEATURES)
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# TODO: Get evaluation from Stockfish
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evals_list.append(0.0)
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return features_list, evals_list
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