| """Generate synthetic 1h bars + 8h funding for harness smoke tests. |
| |
| Layout matches crypto_eval.data.load_local exactly: |
| <out>/bars_BTCUSDT_1h.parquet (UTC DatetimeIndex, OHLCV) |
| <out>/funding_BTCUSDT.parquet (UTC DatetimeIndex, funding_rate) |
| <out>/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") |
|
|
