Add files via upload

2026-08-22 05:18:04 +00:00 · 2025-11-14 23:16:51 +00:00
parent 8c9371683e
commit 53c7aa9182
85 changed files with 6789 additions and 0 deletions
@@ -0,0 +1,70 @@
+from __future__ import annotations
+
+import argparse
+from pathlib import Path
+from typing import List
+
+import pandas as pd
+from loguru import logger
+
+METRIC_COLS = [
+    "sharpe",
+    "ann_return",
+    "ann_vol",
+    "max_drawdown",
+    "expectancy",
+    "trades",
+    "win_rate",
+    "return_pct",
+    "rr",
+    "median_hold",
+    "symbol",
+    "source_file",
+]
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Compare zero-cost vs real-cost grid results.")
+    parser.add_argument("--zero", required=True, help="CSV from zero-cost grid run.")
+    parser.add_argument("--real", required=True, help="CSV from real-cost grid run.")
+    parser.add_argument("--out", default="data/grid/cost_comparison.csv", help="Output CSV path.")
+    parser.add_argument("--top", type=int, default=20, help="Print top-N rows with smallest Sharpe delta.")
+    args = parser.parse_args()
+
+    df_zero = pd.read_csv(args.zero)
+    df_real = pd.read_csv(args.real)
+
+    shared_cols = [c for c in df_zero.columns if c in df_real.columns]
+    if not shared_cols:
+        raise ValueError("No overlapping columns between zero and real CSVs.")
+
+    param_cols: List[str] = [c for c in shared_cols if c not in METRIC_COLS]
+    if not param_cols:
+        raise ValueError("Unable to infer parameter columns for join; ensure CSVs contain metrics from METRIC_COLS.")
+
+    z = df_zero.rename(columns={col: f"{col}_zero" for col in METRIC_COLS if col in df_zero.columns})
+    r = df_real.rename(columns={col: f"{col}_real" for col in METRIC_COLS if col in df_real.columns})
+
+    merged = z.merge(r, on=param_cols, how="inner", suffixes=("_zero", "_real"))
+    if merged.empty:
+        raise RuntimeError("Join result is empty; ensure both CSVs share the same parameter combinations.")
+
+    if "sharpe_zero" in merged.columns and "sharpe_real" in merged.columns:
+        merged["delta_sharpe"] = merged["sharpe_real"] - merged["sharpe_zero"]
+    if "ann_return_zero" in merged.columns and "ann_return_real" in merged.columns:
+        merged["delta_ann_return"] = merged["ann_return_real"] - merged["ann_return_zero"]
+    if "expectancy_zero" in merged.columns and "expectancy_real" in merged.columns:
+        merged["delta_expectancy"] = merged["expectancy_real"] - merged["expectancy_zero"]
+
+    out_path = Path(args.out)
+    out_path.parent.mkdir(parents=True, exist_ok=True)
+    merged.to_csv(out_path, index=False)
+    logger.info(f"Cost comparison saved to {out_path} (rows={len(merged)})")
+
+    if "delta_sharpe" in merged.columns:
+        top_df = merged.sort_values("delta_sharpe", ascending=False).head(args.top)
+        print(top_df[param_cols + ["sharpe_zero", "sharpe_real", "delta_sharpe"]].to_string(index=False))
+
+
+if __name__ == "__main__":
+    main()