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test.py

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+import warnings
+import numpy as np
+import pandas as pd
+import json
+
+# 抑制numpy的警告（由于数据中包含NaN值，这是正常的）
+warnings.filterwarnings("ignore", category=RuntimeWarning, module="numpy")
+np.seterr(all="ignore")  # 忽略numpy的浮点错误警告
+
+from data import load_data
+from factor_mining.gp_miner import GPMiner, GPConfig
+
+if __name__ == "__main__":
+    df = load_data("/Users/aszer/Documents/vscode/factorhack/ETH_USDT-1h.feather")
+    # 以4小时为周期重采样K线数据（假定有datetime索引，常见ohlcv列）
+    df = (
+        df.resample("4h")
+        .agg(
+            {
+                "open": "first",
+                "high": "max",
+                "low": "min",
+                "close": "last",
+                "volume": "sum",
+            }
+        )
+        .dropna()
+    )
+    df = df[df.index < '2023-01-01']
+    print("数据加载成功，前5行：")
+    print(df.head())
+    print(f"\n数据形状: {df.shape}")
+    print(f"数据列: {df.columns.tolist()}")
+    gp_config = GPConfig(
+        ret_horizon=48,
+        ic_window=120,
+        ic_method="spearman",
+        seed=None,
+        population_size=200,
+        generations=30,
+        tournament_size=5,
+        crossover_prob=0.9,
+        mutation_prob=0.05,
+        elitism=5,
+        max_depth_init=1,
+        max_depth=30,
+        complexity_penalty=0.001,
+    )
+    miner = GPMiner(config=gp_config)
+    res = miner.mine(df, ["open", "high", "low", "close", "volume"])
+    with open("gp_miner_result.txt", "w") as out_file:
+        for formula, ic_tuple in res:
+            # ic_tuple 是元组，取第一个元素作为IC值
+            ic = ic_tuple[0] if isinstance(ic_tuple, tuple) else ic_tuple
+            print(f"{formula.expression}, IC: {ic:.4f}")
+            # 将因子公式转换为字典并写入文件
+            out_file.write(json.dumps(formula.to_dict(), ensure_ascii=False))
+            out_file.write("\n")