feat: improve history overview visualization and data handling

- Added `safe_float` utility to enhance float handling in correlation calculations, preventing potential errors.
- Refactored lag correlation logic in `get_history_overview_viz_bundle` to utilize absolute values safely, improving accuracy in metric comparisons.
- Enhanced nutrition body merge logic to ensure proper date handling and data integrity, optimizing the retrieval of nutrition and weight logs.
- Introduced new functions in the frontend for processing lag details, improving the visualization of correlation data in the History page.

backend/data_layer/history_overview_viz.py

@@ -13,6 +13,7 @@ from data_layer.correlations import calculate_lag_correlation, calculate_top_dri
 from data_layer.fitness_viz import get_fitness_dashboard_viz_bundle
 from data_layer.nutrition_viz import get_nutrition_history_viz_bundle
 from data_layer.recovery_viz import get_recovery_dashboard_viz_bundle
+from data_layer.utils import safe_float
 
 
 def _take_kpis(tiles: Any, max_n: int = 4) -> List[Dict[str, Any]]:
@@ -90,11 +91,9 @@ def get_history_overview_viz_bundle(profile_id: str, days: int) -> Dict[str, Any
     c3_rhr = calculate_lag_correlation(profile_id, "load", "rhr", 14)
     c3 = None
     if c3_hrv and c3_rhr:
-        c3 = (
+        a1 = abs(safe_float(c3_hrv.get("correlation"), 0.0))
-            c3_hrv
+        a2 = abs(safe_float(c3_rhr.get("correlation"), 0.0))
-            if abs(float(c3_hrv.get("correlation") or 0)) >= abs(float(c3_rhr.get("correlation") or 0))
+        c3 = c3_hrv if a1 >= a2 else c3_rhr
-            else c3_rhr
-        )
         if c3 is c3_hrv:
             c3 = dict(c3)
             c3["metric"] = "HRV"

backend/data_layer/nutrition_body_merge.py

@@ -9,7 +9,7 @@ from __future__ import annotations
 from typing import Any, Dict, List, Optional
 
 from db import get_db, get_cursor, r2d
-from caliper_composition import compute_lean_fat_kg, nearest_weight_kg_from_map
+from caliper_composition import as_date, compute_lean_fat_kg, nearest_weight_kg_from_map
 
 
 def build_merged_daily_nutrition_body_rows(profile_id: str) -> List[Dict[str, Any]]:
@@ -20,21 +20,42 @@ def build_merged_daily_nutrition_body_rows(profile_id: str) -> List[Dict[str, An
     with get_db() as conn:
         cur = get_cursor(conn)
         cur.execute("SELECT * FROM nutrition_log WHERE profile_id=%s ORDER BY date", (profile_id,))
-        nutr = {r["date"]: r2d(r) for r in cur.fetchall()}
+        nutr: Dict[Any, Dict[str, Any]] = {}
+        for r in cur.fetchall():
+            rd = r2d(r)
+            dk = as_date(rd.get("date"))
+            if dk is not None:
+                nutr[dk] = rd
         cur.execute("SELECT date, weight FROM weight_log WHERE profile_id=%s ORDER BY date", (profile_id,))
-        wlog = {r["date"]: r["weight"] for r in cur.fetchall()}
+        wlog: Dict[Any, Any] = {}
+        for r in cur.fetchall():
+            rd = r2d(r)
+            dk = as_date(rd.get("date"))
+            if dk is not None:
+                wlog[dk] = rd["weight"]
         cur.execute(
             "SELECT date, lean_mass, body_fat_pct FROM caliper_log WHERE profile_id=%s ORDER BY date",
             (profile_id,),
         )
-        cals = sorted([r2d(r) for r in cur.fetchall()], key=lambda x: x["date"])
+        cals = [r2d(r) for r in cur.fetchall()]
+        cals = sorted(
+            [c for c in cals if as_date(c.get("date")) is not None],
+            key=lambda x: as_date(x["date"]),
+        )
 
-    all_dates = sorted(set(list(nutr.keys()) + list(wlog.keys())))
+    # Alle Keys sind datetime.date — vermeidet TypeError bei Vergleichen (str vs date)
+    all_dates = sorted(set(nutr.keys()) | set(wlog.keys()))
     mi = 0
     last_cal: Dict[str, Any] = {}
     cal_by_date: Dict[Any, Dict[str, Any]] = {}
     for d in all_dates:
-        while mi < len(cals) and cals[mi]["date"] <= d:
+        while mi < len(cals):
+            cd = as_date(cals[mi].get("date"))
+            if cd is None:
+                mi += 1
+                continue
+            if cd > d:
+                break
             last_cal = cals[mi]
             mi += 1
         if last_cal:

frontend/src/pages/History.jsx

@@ -1205,6 +1205,34 @@ function chartJsScatterPoints(payload) {
   return raw.map((p) => ({ x: Number(p.x), y: Number(p.y) }))
 }
 
+/** Backend metadata.lag_details: [{ lag, n_pairs, r }] — für Lag-Kurve L → r (C3: ggf. lag_details_hrv / lag_details_rhr) */
+function lagDetailsToCurve(meta) {
+  let ld = meta?.lag_details
+  if (!Array.isArray(ld) || ld.length === 0) {
+    const m = String(meta?.metric || '').toUpperCase()
+    if (m === 'HRV' && Array.isArray(meta?.lag_details_hrv)) ld = meta.lag_details_hrv
+    else if (m === 'RHR' && Array.isArray(meta?.lag_details_rhr)) ld = meta.lag_details_rhr
+    else {
+      const h = meta?.lag_details_hrv
+      const r = meta?.lag_details_rhr
+      const hl = Array.isArray(h) ? h.length : 0
+      const rl = Array.isArray(r) ? r.length : 0
+      if (hl >= rl && hl > 0) ld = h
+      else if (rl > 0) ld = r
+      else ld = []
+    }
+  }
+  if (!Array.isArray(ld) || ld.length === 0) return []
+  return ld
+    .map((d) => ({
+      lag: Number(d?.lag),
+      r: d?.r == null || d?.r === '' ? null : Number(d.r),
+      n_pairs: d?.n_pairs != null ? Number(d.n_pairs) : null,
+    }))
+    .filter((d) => Number.isFinite(d.lag) && d.r != null && Number.isFinite(d.r))
+    .sort((a, b) => a.lag - b.lag)
+}
+
 function driverBarFromStatus(st) {
   const s = String(st || '').toLowerCase()
   if (s.includes('hinder')) return { v: -1, fill: 'var(--danger)' }
@@ -1240,10 +1268,13 @@ function chartJsBarRows(payload, fallbackDrivers) {
 function CorrelationScatterTile({ title, accent, payload }) {
   const meta = payload?.metadata || {}
   const pts = chartJsScatterPoints(payload)
+  const curve = lagDetailsToCurve(meta)
   const hasChart = pts.length > 0 && meta.correlation != null
   const r = Number(meta.correlation)
   const strength =
     !Number.isFinite(r) ? 'bad' : Math.abs(r) >= 0.35 ? 'good' : Math.abs(r) >= 0.15 ? 'warn' : 'bad'
+  const bestLag = meta.best_lag_days != null ? Number(meta.best_lag_days) : null
+  const maxLagAxis = curve.length ? Math.max(14, ...curve.map((d) => d.lag), bestLag || 0) : 28
 
   return (
     <div
@@ -1257,12 +1288,76 @@ function CorrelationScatterTile({ title, accent, payload }) {
       <div style={{ fontSize: 11, fontWeight: 700, color: 'var(--text1)', marginBottom: 4 }}>{title}</div>
       <div style={{ fontSize: 10, color: 'var(--text3)', lineHeight: 1.35, marginBottom: 6 }}>
         r = {meta.correlation != null ? Number(meta.correlation).toFixed(3) : '—'}
-        {meta.best_lag_days != null ? ` · Lag ${meta.best_lag_days} T` : ''}
+        {meta.best_lag_days != null ? ` · bestes Lag ${meta.best_lag_days} T` : ''}
         {meta.metric ? ` · ${meta.metric}` : ''}
         {meta.confidence ? ` · ${meta.confidence}` : ''}
       </div>
       {!hasChart ? (
-        <div style={{ fontSize: 11, color: 'var(--text3)' }}>{meta.message || 'Keine Daten für diese Korrelation.'}</div>
+        <>
+          <div style={{ fontSize: 11, color: 'var(--text3)', marginBottom: curve.length ? 8 : 0 }}>
+            {meta.message || 'Keine Daten für diese Korrelation.'}
+          </div>
+          {curve.length > 0 && (
+            <div style={{ fontSize: 10, color: 'var(--text3)', marginBottom: 6 }}>
+              Lag-Sweep (kein Lag mit ≥15 Paaren): r über Lags — nur zur Einordnung.
+            </div>
+          )}
+          {curve.length > 0 && (
+            <ResponsiveContainer width="100%" height={120}>
+              <ComposedChart data={curve} margin={{ top: 4, right: 6, bottom: 4, left: -14 }}>
+                <CartesianGrid strokeDasharray="3 3" stroke="var(--border)" />
+                <XAxis dataKey="lag" type="number" domain={[0, maxLagAxis]} tick={{ fontSize: 9, fill: 'var(--text3)' }} label={{ value: 'Lag (T)', fontSize: 9, fill: 'var(--text3)', offset: -2 }} />
+                <YAxis dataKey="r" domain={[-1, 1]} tick={{ fontSize: 9, fill: 'var(--text3)' }} width={36} label={{ value: 'r', fontSize: 9, fill: 'var(--text3)', angle: -90 }} />
+                <ReferenceLine y={0} stroke="var(--text3)" strokeDasharray="4 4" />
+                <Tooltip
+                  contentStyle={{ background: 'var(--surface)', border: '1px solid var(--border)', borderRadius: 8, fontSize: 10 }}
+                  formatter={(v, _n, item) => [`r = ${Number(v).toFixed(3)}`, `Lag ${item?.payload?.lag} T · n = ${item?.payload?.n_pairs ?? '—'}`]}
+                />
+                <Line type="monotone" dataKey="r" stroke={accent} strokeWidth={2} dot={{ r: 3, fill: accent }} isAnimationActive={false} />
+              </ComposedChart>
+            </ResponsiveContainer>
+          )}
+        </>
+      ) : curve.length >= 1 ? (
+        <>
+          <div style={{ fontSize: 9, color: 'var(--text3)', marginBottom: 4 }}>
+            Kurve: Pearson-r je Lag (Tage); starker Punkt = gewähltes bestes Lag.
+          </div>
+          <ResponsiveContainer width="100%" height={132}>
+            <ComposedChart data={curve} margin={{ top: 4, right: 6, bottom: 4, left: -14 }}>
+              <CartesianGrid strokeDasharray="3 3" stroke="var(--border)" />
+              <XAxis dataKey="lag" type="number" domain={[0, maxLagAxis]} tick={{ fontSize: 9, fill: 'var(--text3)' }} />
+              <YAxis dataKey="r" domain={[-1, 1]} tick={{ fontSize: 9, fill: 'var(--text3)' }} width={36} />
+              <ReferenceLine y={0} stroke="var(--text3)" strokeDasharray="4 4" />
+              <Tooltip
+                contentStyle={{ background: 'var(--surface)', border: '1px solid var(--border)', borderRadius: 8, fontSize: 10 }}
+                formatter={(v, _n, item) => [`r = ${Number(v).toFixed(3)}`, `Lag ${item?.payload?.lag} T · n = ${item?.payload?.n_pairs ?? '—'}`]}
+              />
+              <Line
+                type="monotone"
+                dataKey="r"
+                stroke={accent}
+                strokeWidth={2}
+                isAnimationActive={false}
+                dot={(props) => {
+                  const { cx, cy, payload: pl } = props
+                  if (cx == null || cy == null || !pl) return null
+                  const isBest = bestLag != null && Number(pl.lag) === bestLag
+                  return (
+                    <circle
+                      cx={cx}
+                      cy={cy}
+                      r={isBest ? 6 : 3.5}
+                      fill={isBest ? 'var(--surface)' : accent}
+                      stroke={isBest ? accent : 'none'}
+                      strokeWidth={isBest ? 2.5 : 0}
+                    />
+                  )
+                }}
+              />
+            </ComposedChart>
+          </ResponsiveContainer>
+        </>
       ) : (
         <ResponsiveContainer width="100%" height={118}>
           <ScatterChart margin={{ top: 2, right: 4, bottom: 2, left: -18 }}>