GA基本正常

build_factory_data.py

@@ -0,0 +1,73 @@
+import json
+import os
+import pandas as pd
+from pathlib import Path
+
+
+def load_factory_mapping(year: int) -> dict:
+    path = os.path.join("data", str(year), "factory_mapping.json")
+    with open(path, "r", encoding="utf-8") as f:
+        return json.load(f)
+
+
+def load_model_params(year: int) -> dict:
+    path = os.path.join("data", str(year), "model_params.json")
+    with open(path, "r", encoding="utf-8") as f:
+        return json.load(f)
+
+def load_benchmark_factories(year: int) -> list[str]:
+    path = Path("data") / str(year) / "benchmark.csv"
+    encodings = ("utf-8", "utf-8-sig", "gbk")
+    last_error = None
+    df = None
+    for enc in encodings:
+        try:
+            df = pd.read_csv(path, encoding=enc)
+            break
+        except UnicodeDecodeError as exc:
+            last_error = exc
+            continue
+    if df is None:
+        raise last_error if last_error else FileNotFoundError(f"Missing {path}")
+    # Assume first column holds factory name (aligns with factory_mapping keys)
+    factory_col = df.columns[0]
+    return df[factory_col].astype(str).str.strip().unique().tolist()
+
+
+def build_factory_dataframe(year: int) -> pd.DataFrame:
+    mapping = load_factory_mapping(year)
+    params = load_model_params(year)
+    default_factor = params.get("factor_default", 1)
+    benchmark_factories = load_benchmark_factories(year)
+    rows = []
+    for cn_name in benchmark_factories:
+        code = mapping.get(cn_name)
+        if code is None:
+            raise KeyError(f"benchmark.csv中的工厂“{cn_name}”未在 factory_mapping.json 中找到映射。")
+        factor = params.get(f"factor_{code}", default_factor if default_factor is not None else 1)
+        rows.append(
+            {
+                "工厂中文名": cn_name,
+                "工厂英文名": code,
+                "工厂平均磨合系数": float(factor),
+                "最小误差": 1_000_000,
+            }
+        )
+    return pd.DataFrame(rows)
+
+
+def write_factory_csv(df: pd.DataFrame, year: int) -> str:
+    out_path = os.path.join("data", str(year), "factory_data.csv")
+    df.to_csv(out_path, index=False, encoding="utf-8-sig")
+    return out_path
+
+
+def main():
+    year = 2025
+    df = build_factory_dataframe(year)
+    out_path = write_factory_csv(df, year)
+    print(f"factory_data.csv generated at: {out_path}")
+
+
+if __name__ == "__main__":
+    main()