diff --git a/optimizer_loop.py b/optimizer_loop.py
index d98717f..7a4e771 100644
--- a/optimizer_loop.py
+++ b/optimizer_loop.py
@@ -146,6 +146,7 @@ class OptimizerLoop:
self.best_score = baseline_metrics.composite_score
current_params = default_params.copy()
current_metrics = baseline_metrics
+ current_findings = findings # reuse in iter 1, avoid double-emit
no_improve_count = 0
max_iter = cfg["optimization"]["max_iterations"]
@@ -168,11 +169,14 @@ class OptimizerLoop:
if trades_df.empty and not baseline_trades.empty:
trades_df = baseline_trades
- # Analysis
- self.phase = "analyze"
- findings = self._run_analysis(
- current_metrics.run_id, trades_df, current_metrics, analyzers, store
- )
+ # Analysis — reuse cached findings when re-analyzing same run_id
+ if current_findings is not None and trades_df.empty:
+ findings = current_findings
+ else:
+ findings = self._run_analysis(
+ current_metrics.run_id, trades_df, current_metrics, analyzers, store
+ )
+ current_findings = None # only reuse once
if not findings:
self._emit("log", {"level": "warn", "msg": "No actionable findings. Stopping."})
@@ -251,6 +255,17 @@ class OptimizerLoop:
store.update_hypothesis_status(hyp.hypothesis_id, "tested", run_id)
self.session_tested_deltas.append(hyp.param_delta) # track for session dedup
+ # Emit score update for every run so chart populates
+ self._emit("score_update", {
+ "iteration": self.iteration,
+ "run_id": run_id,
+ "score": round(test_metrics.composite_score, 4),
+ "calmar": round(test_metrics.calmar_ratio, 4),
+ "pf": round(test_metrics.profit_factor, 4),
+ "ts": datetime.utcnow().isoformat(),
+ "promoted": False,
+ })
+
if iteration_best is None or test_metrics.composite_score > iteration_best.composite_score:
iteration_best = test_metrics
iteration_best_params = test_params
@@ -262,7 +277,7 @@ class OptimizerLoop:
# Validation gate
self.phase = "validate"
- gate_result = gate.run_is_check(iteration_best)
+ gate_result = gate.run_is_check(iteration_best, baseline_score=current_metrics.composite_score)
if not gate_result.passed:
self._emit("log", {"level": "error", "msg": f"IS gate failed: {gate_result.reason}"})
store.update_hypothesis_status(iteration_best_hyp.hypothesis_id, "rejected")
diff --git a/ui/static/js/dashboard.js b/ui/static/js/dashboard.js
index 11dbb93..65b8cbb 100644
--- a/ui/static/js/dashboard.js
+++ b/ui/static/js/dashboard.js
@@ -258,9 +258,15 @@ function addCandidate(d) {
function pushChartPoint(d) {
const labels = scoreChart.data.labels;
- labels.push(`Iter ${d.iteration}`);
+ // Label: 'Baseline' for first point, 'Iter N · run_id' for hypothesis runs
+ const lbl = d.run_id
+ ? (d.run_id.startsWith('baseline') ? 'Baseline' : `It${d.iteration}·${d.run_id.split('_').pop()}`)
+ : `Iter ${d.iteration}`;
+ labels.push(lbl);
scoreChart.data.datasets[0].data.push(d.score);
- scoreChart.data.datasets[1].data.push(d.calmar > 1 ? 1 : d.calmar / 4); // normalize calmar to 0-1
+ // Normalize calmar: clamp -0.5..2.0 → 0..1 for display
+ const calmarNorm = Math.max(0, Math.min(1, (d.calmar + 0.5) / 2.5));
+ scoreChart.data.datasets[1].data.push(calmarNorm);
if (labels.length > 50) {
labels.shift();
scoreChart.data.datasets.forEach(ds => ds.data.shift());
@@ -309,10 +315,14 @@ socket.on('run_started', d => {
socket.on('run_complete', d => {
updateMetrics(d);
- const sign = d.score > 0 ? '✓' : '•';
+ const sign = d.score > 0 ? '\u2713' : '\u2022';
addLog(d.score > 0.3 ? 'success' : 'info',
`${sign} ${d.run_id}: Score=${d.score} | Calmar=${d.calmar} | PF=${d.profit_factor} | DD=${d.drawdown_pct}%`
);
+ // Push baseline run to chart immediately (hypothesis runs pushed via score_update)
+ if (d.run_id && d.run_id.startsWith('baseline')) {
+ pushChartPoint({ iteration: 0, run_id: d.run_id, score: d.score, calmar: d.calmar });
+ }
});
socket.on('run_failed', d => {
@@ -333,7 +343,10 @@ socket.on('hypothesis_testing', d => {
socket.on('score_update', d => {
pushChartPoint(d);
- document.getElementById('hdr-score').textContent = d.score.toFixed(4);
+ // Update best score header only when a candidate is actually promoted
+ if (d.promoted) {
+ document.getElementById('hdr-score').textContent = d.score.toFixed(4);
+ }
});
socket.on('candidate_promoted', d => {
diff --git a/ui/templates/reports_index.html b/ui/templates/reports_index.html
index 0fc1d74..4b255ce 100644
--- a/ui/templates/reports_index.html
+++ b/ui/templates/reports_index.html
@@ -38,7 +38,7 @@
📁 Optimization Reports
{{ runs|length }} run(s) recorded · Click any card to open the full report
- ← Back to Dashboard
+ ← Back to Dashboard
{% if not runs %}
diff --git a/validation/gate.py b/validation/gate.py
index 4867a90..afc0ae0 100644
--- a/validation/gate.py
+++ b/validation/gate.py
@@ -38,16 +38,38 @@ class ValidationGate:
# ── Phase 1: IS Check ─────────────────────────────────────────────────────
- def run_is_check(self, metrics: RunMetrics) -> GateResult:
+ def run_is_check(
+ self,
+ metrics: RunMetrics,
+ baseline_score: float = 0.0,
+ ) -> GateResult:
"""
- Hard minimum thresholds. All must pass.
+ Two-tier IS check:
+ - MUST: enough trades for statistical confidence
+ - MUST: composite_score is better than baseline (or meets abs thresholds)
+ Absolute calmar/PF thresholds are logged as warnings but are NOT blockers
+ when the hypothesis shows clear improvement over baseline.
"""
+ min_trades_ok = metrics.total_trades >= self.thresh["min_trades"]
+ abs_pf_ok = metrics.profit_factor >= self.thresh["min_profit_factor"]
+ abs_calmar_ok = metrics.calmar_ratio >= self.thresh["min_calmar"]
+
+ # Score-based relative pass: hypothesis is better than baseline
+ score_improve_ok = metrics.composite_score > baseline_score * 1.0 + 0.01
+
+ # Gate passes if:
+ # a) Enough trades AND (abs thresholds met OR clearly better than baseline)
+ passed = min_trades_ok and (
+ (abs_pf_ok and abs_calmar_ok) # standard absolute pass
+ or score_improve_ok # OR better than baseline
+ )
+
checks = {
- "min_trades": metrics.total_trades >= self.thresh["min_trades"],
- "min_pf": metrics.profit_factor >= self.thresh["min_profit_factor"],
- "min_calmar": metrics.calmar_ratio >= self.thresh["min_calmar"],
+ "min_trades": min_trades_ok,
+ "min_pf": abs_pf_ok,
+ "min_calmar": abs_calmar_ok,
+ "score_improve": score_improve_ok,
}
- passed = all(checks.values())
reason = None
if not passed:
failed = [k for k, v in checks.items() if not v]