Prepare source-only public release for develop.

Add cluster audit pipeline, united EA updates, brochure generators, and publication hygiene (gitignore, MT5 path desensitization, pre-upload scan). Remove tracked reports, models, and binary artifacts from the repo.

Co-authored-by: Cursor <cursoragent@cursor.com>

backtesting/MT5/cluster_audit/scoring.py

@@ -0,0 +1,126 @@
+"""Strategy scoring — requires ~1 trade per calendar day over the backtest period."""
+
+from __future__ import annotations
+
+from datetime import date, datetime
+
+from .backtest_core import BacktestReport
+
+DEFAULT_TRADES_PER_DAY = 1.0
+
+
+def period_days(start: date | datetime | str, end: date | datetime | str) -> int:
+    if isinstance(start, str):
+        start = datetime.fromisoformat(start)
+    if isinstance(end, str):
+        end = datetime.fromisoformat(end)
+    if isinstance(start, datetime):
+        start = start.date()
+    if isinstance(end, datetime):
+        end = end.date()
+    return max(1, (end - start).days)
+
+
+def min_trades_for_period(days: int, trades_per_day: float = DEFAULT_TRADES_PER_DAY) -> int:
+    return max(30, int(days * trades_per_day))
+
+
+def trades_per_day(report: BacktestReport, days: int) -> float:
+    if report.total_trades == 0 or days <= 0:
+        return 0.0
+    return report.total_trades / days
+
+
+def winning_months_pct(report: BacktestReport) -> float:
+    if not report.monthly_returns:
+        return 0.0
+    vals = list(report.monthly_returns.values())
+    return 100.0 * sum(1 for v in vals if v > 0) / len(vals)
+
+
+def score_report(
+    report: BacktestReport,
+    period_days_count: int,
+    trades_per_day_target: float = DEFAULT_TRADES_PER_DAY,
+) -> float:
+    """Higher is better. Hard-fails below activity + profit gates."""
+    min_t = min_trades_for_period(period_days_count, trades_per_day_target)
+    t = report.total_trades
+    tpd = trades_per_day(report, period_days_count)
+
+    if t < min_t or tpd < trades_per_day_target:
+        return float("-inf")
+
+    if report.net_profit <= 0 or report.profit_factor < 1.05:
+        return float("-inf")
+
+    win_mo = winning_months_pct(report) / 100.0
+    activity = min(tpd / (trades_per_day_target * 1.5), 1.0)
+    pf = min(report.profit_factor, 4.0) / 4.0
+    wr = min(report.win_rate, 70.0) / 70.0
+
+    return (
+        report.sharpe * 0.25
+        + (report.net_profit / 2000.0) * 0.18
+        - report.max_drawdown_pct * 0.10
+        + activity * 0.22
+        + win_mo * 0.12
+        + pf * 0.08
+        + wr * 0.05
+    )
+
+
+def score_label(
+    score: float,
+    trades: int,
+    period_days_count: int,
+    trades_per_day_target: float = DEFAULT_TRADES_PER_DAY,
+) -> str:
+    min_t = min_trades_for_period(period_days_count, trades_per_day_target)
+    tpd = trades / period_days_count if period_days_count else 0
+    if trades < min_t:
+        return f"N/A ({trades}<{min_t}, need {trades_per_day_target:.1f}/day)"
+    if tpd < trades_per_day_target:
+        return f"N/A ({tpd:.2f}/day < {trades_per_day_target:.1f}/day)"
+    if score == float("-inf"):
+        return "N/A (fails profit gates)"
+    return f"{score:.2f}"
+
+
+def acceptance(
+    report: BacktestReport,
+    period_days_count: int,
+    trades_per_day_target: float = DEFAULT_TRADES_PER_DAY,
+) -> tuple[bool, list[str]]:
+    min_t = min_trades_for_period(period_days_count, trades_per_day_target)
+    tpd = trades_per_day(report, period_days_count)
+    issues: list[str] = []
+
+    if report.total_trades < min_t:
+        issues.append(f"trades={report.total_trades} need >={min_t} ({trades_per_day_target:.1f}/day x {period_days_count}d)")
+    if tpd < trades_per_day_target:
+        issues.append(f"trades/day={tpd:.2f} need >={trades_per_day_target:.1f}")
+    if report.net_profit <= 0:
+        issues.append(f"net=${report.net_profit:.0f} not positive")
+    if report.profit_factor < 1.15:
+        issues.append(f"pf={report.profit_factor:.2f} need >=1.15")
+    if report.sharpe < 0.3:
+        issues.append(f"sharpe={report.sharpe:.2f} need >=0.30")
+    if report.max_drawdown_pct > 25:
+        issues.append(f"dd={report.max_drawdown_pct:.1f}% too high")
+
+    win_mo = winning_months_pct(report)
+    if win_mo < 45:
+        issues.append(f"winning_months={win_mo:.0f}% need >=45%")
+
+    return len(issues) == 0, issues
+
+
+def format_quality_line(report: BacktestReport, period_days_count: int) -> str:
+    tpd = trades_per_day(report, period_days_count)
+    return (
+        f"net=${report.net_profit:.0f} sharpe={report.sharpe:.2f} "
+        f"trades={report.total_trades} ({tpd:.2f}/day) pf={report.profit_factor:.2f} "
+        f"wr={report.win_rate:.0f}% win_mo={winning_months_pct(report):.0f}% "
+        f"dd={report.max_drawdown_pct:.1f}%"
+    )