| # SPDX-License-Identifier: LicenseRef-PolyForm-Noncommercial-1.0.0 (see LICENSE)
|
| """Compare what the indicator drew (DumpIndicator CSVs on MT5, Dump4 CSVs on MT4) with tests/reference.py, bar by bar.
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|
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| python3 tests/check_parity.py <dump dir> (needs numpy and pandas; looks in <dump dir>/dump)
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| python3 tests/check_parity.py <dump dir> --mt4 (the MT4 edition, dumps from the MT4 tester)
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| Buffers: b0 bullish arrow (at the low), b1 bearish arrow (at the high), b2/b3 bullish/bearish pattern bit masks.
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| Pass: the masks equal the reference exactly on every closed bar; the arrows are set on the same bars (on MT4 the
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| arrow sits a fraction of ATR away from the candle, so only where it is set is compared)."""
|
| import sys
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| from pathlib import Path
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|
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| import numpy as np
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| import pandas as pd
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|
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| sys.path.insert(0, str(Path(__file__).parent))
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| from reference import ALL, NP, run # noqa: E402
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|
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| NODOJI = tuple(i != 6 for i in range(NP))
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| # tag: (patterns on, closed bars scanned (InpHistory), DumpIndicator InpParams for MT5 in input order; groups count)
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| CONFIGS = {
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| "cd_default": (ALL, 2000, "s:Patterns|b:true|b:true|b:true|b:true|b:true|b:true|b:true|s:Display|i:2000|b:true|"
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| "c:6465062|c:4606690|i:7|s:Alerts|b:false|b:false|s:alert.wav|b:false|b:false"),
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| "cd_long": (NODOJI, 6000, "s:Patterns|b:true|b:true|b:true|b:false|b:true|b:true|b:true|s:Display|i:6000|b:true|"
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| "c:6465062|c:4606690|i:7|s:Alerts|b:false|b:false|s:alert.wav|b:false|b:false"),
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| }
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|
|
|
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| def num(col):
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| return pd.to_numeric(col, errors="coerce").to_numpy(float)
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|
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| def check(csv: Path, use, hist, mt4=False):
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| d = pd.read_csv(csv)
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| n = len(d)
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| # MT4 tester: the indicator was attached with far fewer than InpHistory bars, so it scans from bar 0 and keeps
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| # feeding, which is why the scan starts at bar 0 there
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| start = 0 if mt4 else max(0, n - 1 - hist)
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| o, h, l, c = (d[k].to_numpy(float)[start:n - 1] for k in ("open", "high", "low", "close"))
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| rows = run(o, h, l, c, use=use)
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| exp = {b: np.full(n, np.nan) for b in ("b0", "b1", "b2", "b3")}
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| for i, r in enumerate(rows):
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| k = start + i
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| mb = sum(1 << p for p, dr in r["ev"] if dr > 0)
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| ms = sum(1 << p for p, dr in r["ev"] if dr < 0)
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| if mb:
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| exp["b0"][k], exp["b2"][k] = l[i], mb
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| if ms:
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| exp["b1"][k], exp["b3"][k] = h[i], ms
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| ok, msgs = True, []
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| for b in exp:
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| if mt4 and b in ("b0", "b1"):
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| good = np.isnan(num(d[b])[:n - 1]) == np.isnan(exp[b][:n - 1])
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| else:
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| good = np.isclose(num(d[b])[:n - 1], exp[b][:n - 1], rtol=1e-12, atol=0, equal_nan=True)
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| ok &= bool(good.all())
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| msgs.append(f"{b} {'OK' if good.all() else f'{(~good).sum()} differ (first bar {int(np.flatnonzero(~good)[0])})'}")
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| npat = int(sum(1 for r in rows if r["ev"]))
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| return ok, f"{csv.stem:30} bars {n:>6} scanned {n - 1 - start:>5} pattern bars {npat:>5} " + " ".join(msgs)
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|
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| if __name__ == "__main__":
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| mt4 = "--mt4" in sys.argv
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| root = Path([a for a in sys.argv[1:] if a != "--mt4"][0])
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| allok, k = True, 0
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| for tag, (use, hist, _) in CONFIGS.items():
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| for f in sorted(root.glob(f"dump/{tag}_*.csv")):
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| ok, msg = check(f, use, hist, mt4)
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| allok &= ok
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| k += 1
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| print(("PASS " if ok else "FAIL ") + msg)
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| print(f"\n{'ALL PASS' if allok and k else 'FAILURES'} ({k} files)")
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| sys.exit(0 if allok and k else 1)
|
