refactor: rename project from Predix to NexQuant

Rename all source files, scripts, tests, documentation, and configuration from Predix/predix to NexQuant/nexquant across the entire codebase.
2026-08-07 12:07:43 +00:00 · 2026-05-09 17:48:22 +02:00
parent 70029b4577
commit 9d6c6d1d5f
92 changed files with 3690 additions and 1015 deletions
@@ -0,0 +1,111 @@
+#!/usr/bin/env python
+"""One strategy runner — standalone, called from parent script."""
+import json, sys, pandas as pd, subprocess, tempfile, numpy as np
+from pathlib import Path
+
+sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
+from rdagent.components.backtesting.vbt_backtest import backtest_signal
+
+if len(sys.argv) < 2:
+    print("Usage: python nexquant_rebacktest_one.py <strategy_json_path>")
+    sys.exit(1)
+
+strat_path = Path(sys.argv[1])
+data = json.loads(strat_path.read_text())
+
+OHLCV = Path("git_ignore_folder/factor_implementation_source_data/intraday_pv.h5")
+FACTORS_DIR = Path("results/factors/values")
+
+fmap = {p.stem: str(p) for p in FACTORS_DIR.glob("*.parquet")}
+
+names = data.get("factor_names", [])
+code = data.get("code", "")
+name = data.get("strategy_name", strat_path.stem)
+
+if not names or not code:
+    print(json.dumps({"status": "skipped", "reason": "no factors/code"}))
+    sys.exit(0)
+
+# Load close
+ohlcv = pd.read_hdf(str(OHLCV), key="data")
+close = ohlcv["$close"].dropna()
+if isinstance(close.index, pd.MultiIndex):
+    close = close.droplevel(-1)
+close = close.astype(float).sort_index()
+
+# Load factors
+series = {}
+for fn in names:
+    fp = fmap.get(fn) or fmap.get(fn.replace("/", "_")[:150])
+    if fp:
+        try:
+            s = pd.read_parquet(fp).iloc[:, 0]
+            series[fn] = s
+        except Exception:
+            pass
+
+if len(series) < 2:
+    print(json.dumps({"status": "skipped", "reason": f"only {len(series)} factors loaded"}))
+    sys.exit(0)
+
+df = pd.DataFrame(series).sort_index()
+if isinstance(df.index, pd.MultiIndex):
+    df = df.droplevel(-1)
+
+df_1m = df.reindex(close.index).ffill()
+valid = df_1m.notna().any(axis=1)
+if valid.sum() < 1000:
+    print(json.dumps({"status": "skipped", "reason": f"only {valid.sum()} valid bars"}))
+    sys.exit(0)
+
+ca = close.loc[valid]
+fa = df_1m.loc[valid]
+
+# Execute
+try:
+    with tempfile.TemporaryDirectory() as td:
+        tdp = Path(td)
+        fa.to_parquet(str(tdp / "factors.parquet"))
+        ca.to_pickle(str(tdp / "close.pkl"))
+        exec_script = (
+            "import sys, os\n"
+            "sys.stdout = open(os.devnull, 'w')\n"
+            "sys.stderr = open(os.devnull, 'w')\n"
+            "import pandas as pd, numpy as np\n"
+            "factors = pd.read_parquet('factors.parquet')\n"
+            "close = pd.read_pickle('close.pkl')\n"
+            "df = factors\n"
+            + code +
+            "\nif 'signal' not in dir():\n"
+            "    raise SystemExit(1)\n"
+            "pd.Series(signal).fillna(0).to_pickle('signal.pkl')\n"
+        )
+        (tdp / "run.py").write_text(exec_script)
+        r = subprocess.run(
+            ["python", "run.py"],
+            capture_output=True, text=True, timeout=60, cwd=str(tdp),
+            stdin=subprocess.DEVNULL,
+        )
+        if r.returncode != 0:
+            print(json.dumps({"status": "code_failed", "stderr": r.stderr[:500]}))
+            sys.exit(1)
+        sig = pd.read_pickle(tdp / "signal.pkl")
+except Exception as e:
+    print(json.dumps({"status": "code_failed", "error": str(e)[:500]}))
+    sys.exit(1)
+
+sig = sig.reindex(ca.index).ffill().fillna(0)
+result = backtest_signal(ca, sig, txn_cost_bps=2.14)
+
+# Return result as JSON
+output = {
+    "status": "ok",
+    "sharpe": result.get("sharpe"),
+    "max_drawdown": result.get("max_drawdown"),
+    "win_rate": result.get("win_rate"),
+    "n_trades": result.get("n_trades"),
+    "total_return": result.get("total_return"),
+    "monthly_return_pct": result.get("monthly_return_pct"),
+    "annualized_return": result.get("annualized_return"),
+}
+print(json.dumps(output))