"""Generate synthetic 1h bars + 8h funding for harness smoke tests. Layout matches crypto_eval.data.load_local exactly: /bars_BTCUSDT_1h.parquet (UTC DatetimeIndex, OHLCV) /funding_BTCUSDT.parquet (UTC DatetimeIndex, funding_rate) /manifest.json ({"outputs": {...}} placeholder) """ import json import sys from pathlib import Path import numpy as np import pandas as pd out = Path(sys.argv[1] if len(sys.argv) > 1 else "/tmp/synthdata") out.mkdir(parents=True, exist_ok=True) rng = np.random.default_rng(7) n = 20_000 idx = pd.date_range("2022-01-01", periods=n, freq="1h", tz="UTC") ret = rng.normal(0.0, 0.01, n) close = 30_000.0 * np.exp(np.cumsum(ret)) open_ = np.r_[close[0], close[:-1]] high = np.maximum(open_, close) * (1 + rng.uniform(0, 0.002, n)) low = np.minimum(open_, close) * (1 - rng.uniform(0, 0.002, n)) vol = rng.lognormal(8, 0.5, n) bars = pd.DataFrame( {"open": open_, "high": high, "low": low, "close": close, "volume": vol}, index=idx, ) bars.to_parquet(out / "bars_BTCUSDT_1h.parquet") fidx = idx[::8] funding = pd.DataFrame( {"funding_rate": rng.normal(1e-4, 2e-4, len(fidx))}, index=fidx ) funding.to_parquet(out / "funding_BTCUSDT.parquet") (out / "manifest.json").write_text(json.dumps({"outputs": {}}, indent=2)) print(f"synthetic data written to {out}: {n} bars, {len(fidx)} funding ticks")