78 lines
2.6 KiB
Python
78 lines
2.6 KiB
Python
"""
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train_ftmo.py — FTMO 专属训练（跳过 forex，训练 metals_comm + index）
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奖励函数已切换为 FTMO 模式（ModelConfig.REWARD_MODE='ftmo'）：
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- 年化收益权重 0.60 → 0.75（提权 25%）
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- Calmar 权重 0.05 → 0.10（控制 MDD 贴近 10% Max Loss）
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- IC/Sortino/一致性等降权
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用法：
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python train_ftmo.py --offline
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"""
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import sys
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import time
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).parent))
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from config import Config
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from data_pipeline.fetcher import MT5DataFetcher
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from model_core.config import ModelConfig
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from main import train_group
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# 跳过已完成的 forex 组，训练其余组
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GROUPS_TO_TRAIN = ["metals_comm", "index"]
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def main():
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offline = "--offline" in sys.argv
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t0 = time.time()
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# 确认 FTMO 模式已激活
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print(f"\n{'='*60}")
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print(f" FTMO 专属因子训练")
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print(f"{'='*60}")
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print(f" 奖励模式: REWARD_MODE = '{ModelConfig.REWARD_MODE}'")
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if ModelConfig.REWARD_MODE != "ftmo":
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print(f" [警告] 当前不是 ftmo 模式，请检查 model_core/config.py")
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return
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print(f" 权重: ann_ret=0.75 calmar=0.10 sortino=0.05")
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print(f" 跳过: forex（已完成，Best=0.485，standard 模式）")
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print(f" 训练: {GROUPS_TO_TRAIN}")
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print(f" offline={offline} BARS_COUNT={Config.BARS_COUNT}")
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print(f" TRAIN_STEPS={ModelConfig.TRAIN_STEPS} BATCH_SIZE={ModelConfig.BATCH_SIZE}")
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print(f"{'='*60}")
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results = {}
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with MT5DataFetcher(offline=offline) as fetcher:
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for gname in GROUPS_TO_TRAIN:
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gsyms = Config.SYMBOL_GROUPS.get(gname, [])
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if not gsyms:
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print(f" [跳过] 组 {gname} 不存在")
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continue
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print(f"\n>>> 开始训练 [{gname}] 组: {gsyms}")
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eng = train_group(fetcher, gname, gsyms, offline)
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if eng is not None:
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results[gname] = {
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"score": eng.best_score,
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"formula": eng.best_formula,
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"readable": eng._decode_formula(eng.best_formula),
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}
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print(f"<<< [{gname}] 完成: score={eng.best_score:.4f}")
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print(f" {results[gname]['readable']}")
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else:
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print(f"<<< [{gname}] 失败")
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elapsed = time.time() - t0
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print(f"\n{'='*60}")
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print(f" FTMO 训练完成 耗时 {elapsed/3600:.2f}h")
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print(f"{'='*60}")
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for gname, r in results.items():
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print(f" [{gname:12s}] score={r['score']:.4f}")
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print(f" {r['readable']}")
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if __name__ == "__main__":
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main()
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