NerdCorner VAM: filter short climbs, opacity-encode confidence, add climbing time to tooltip

- Exclude per-activity VAM contributions where climbing_time_s < 10 min; short
  punchy efforts don't represent aerobic fitness and were skewing monthly averages
- Store climbing_time_s alongside climbing_vam_mh in metrics, detail JSON, and
  summary JSON so the frontend has the data to reason about confidence
- Accumulate total climbing time per period; opacity scales from 0.25 (10 min,
  minimum threshold) to 1.0 (≥ 1 h) so thin-evidence months read as faint dots
- Render VAM as dots only (no lines) since each period is an independent average,
  not a cumulative — lines implied continuity that isn't there
- Tooltip now shows "1060 m/h · 38 min climbing"

bincio/extract/metrics.py

@@ -65,6 +65,7 @@ class ComputedMetrics:
     best_efforts: Optional[list[list[float]]]
     best_climb_m: Optional[float]   # max net elevation gain in one contiguous window (cycling only)
     climbing_vam_mh: Optional[int]  # average VAM on ascending segments only (m/h)
+    climbing_time_s: Optional[int]  # total ascending seconds used to compute VAM
 
 
 def compute(activity: ParsedActivity) -> ComputedMetrics:
@@ -84,7 +85,8 @@ def compute(activity: ParsedActivity) -> ComputedMetrics:
     start_ll, end_ll = _endpoints(pts)
     mmp = compute_mmp(pts, activity.started_at)
     best_efforts, best_climb_m = compute_best_efforts(pts, activity.started_at, activity.sport)
-    climbing_vam_mh = compute_vam(pts, activity.started_at, activity.sport)
+    _vam = compute_vam(pts, activity.started_at, activity.sport)
+    climbing_vam_mh, climbing_time_s = _vam if _vam else (None, None)
 
     return ComputedMetrics(
         distance_m=distance_m,
@@ -107,6 +109,7 @@ def compute(activity: ParsedActivity) -> ComputedMetrics:
         best_efforts=best_efforts,
         best_climb_m=best_climb_m,
         climbing_vam_mh=climbing_vam_mh,
+        climbing_time_s=climbing_time_s,
     )
 
 
@@ -183,12 +186,13 @@ def _rolling_mean_ele(data: list[float], win: int) -> list[float]:
     return result
 
 
-def _vam_from_ele_1hz(ele_1hz: list[float]) -> Optional[int]:
+def _vam_from_ele_1hz(ele_1hz: list[float]) -> Optional[tuple[int, int]]:
     """Climbing VAM from a dense 1 Hz elevation array.
 
     Accumulates gain and time only on ascending seconds, identified by a 30 s
     forward-lookahead on the smoothed elevation signal.
-    Returns climbing_vam_mh (m/h), or None when there is too little climbing data.
+    Returns (climbing_vam_mh, climbing_time_s), or None when there is too little
+    climbing data.
     """
     n = len(ele_1hz)
     if n < 60:
@@ -206,7 +210,7 @@ def _vam_from_ele_1hz(ele_1hz: list[float]) -> Optional[int]:
             climbing_time += 1
 
     if climbing_time >= 60 and climbing_gain >= 5.0:
-        return round(climbing_gain * 3600.0 / climbing_time)
+        return round(climbing_gain * 3600.0 / climbing_time), climbing_time
     return None
 
 
@@ -233,11 +237,12 @@ def _build_ele_1hz(sparse: dict[int, Optional[float]]) -> Optional[list[float]]:
     return [e if e is not None else first_valid for e in ele_raw]
 
 
-def compute_vam(pts: list[DataPoint], started_at: datetime, sport: str) -> Optional[int]:
+def compute_vam(pts: list[DataPoint], started_at: datetime, sport: str) -> Optional[tuple[int, int]]:
     """Compute average climbing VAM (m/h) from DataPoints.
 
     Only computed for cycling, running, hiking, walking.
-    Returns None when the activity has insufficient climbing data.
+    Returns (climbing_vam_mh, climbing_time_s), or None when there is insufficient
+    climbing data.
     """
     if sport not in _VAM_SPORTS:
         return None
@@ -618,5 +623,5 @@ def _empty() -> ComputedMetrics:
         avg_cadence_rpm=None, avg_power_w=None, np_power_w=None, max_power_w=None,
         bbox=None, start_latlng=None, end_latlng=None,
         mmp=None, best_efforts=None, best_climb_m=None,
-        climbing_vam_mh=None,
+        climbing_vam_mh=None, climbing_time_s=None,
     )

bincio/extract/writer.py

@@ -102,6 +102,7 @@ def write_activity(
         "best_efforts": metrics.best_efforts,
         "best_climb_m": metrics.best_climb_m,
         "climbing_vam_mh": metrics.climbing_vam_mh,
+        "climbing_time_s": metrics.climbing_time_s,
         "laps": [_serialise_lap(lap) for lap in activity.laps],
         "timeseries_url": f"activities/{activity_id}.timeseries.json" if timeseries else None,
         "source": source,
@@ -259,6 +260,7 @@ def build_summary(
         "best_efforts": metrics.best_efforts,
         "best_climb_m": metrics.best_climb_m,
         "climbing_vam_mh": metrics.climbing_vam_mh,
+        "climbing_time_s": metrics.climbing_time_s,
         "source": _infer_source(activity),
         "privacy": privacy,
         "detail_url": f"activities/{activity_id}.json",

site/src/components/NerdCorner.svelte

@@ -56,14 +56,30 @@
   const _now         = new Date();
   const _currentYear = _now.getFullYear();
 
+  // Minimum climbing time per activity to count in the VAM chart (10 min).
+  const VAM_MIN_CLIMB_S = 600;
+  // Climbing time range for full confidence opacity (10 min → 1 h).
+  const VAM_OPACITY_MIN_S = 600;
+  const VAM_OPACITY_MAX_S = 3600;
+
+  function vamOpacity(climbTime: number | undefined): number {
+    if (!climbTime) return 0.25;
+    const t = Math.min(1, Math.max(0, (climbTime - VAM_OPACITY_MIN_S) / (VAM_OPACITY_MAX_S - VAM_OPACITY_MIN_S)));
+    return 0.25 + t * 0.75;
+  }
+
   function buildData(acts: ActivitySummary[], m: Metric, g: Granularity) {
     const curPeriod = g === 'week' ? weekOfYear(_now) : _now.getMonth() + 1;
-    const byYear    = new Map<number, Map<number, number>>();
-    const byYearCnt = new Map<number, Map<number, number>>();  // for VAM averaging
+    const byYear          = new Map<number, Map<number, number>>();
+    const byYearCnt       = new Map<number, Map<number, number>>();
+    const byYearClimbTime = new Map<number, Map<number, number>>();
 
     for (const act of acts) {
       if (!act.started_at) continue;
-      if (m === 'vam' && act.climbing_vam_mh == null) continue;
+      if (m === 'vam') {
+        if (act.climbing_vam_mh == null) continue;
+        if ((act.climbing_time_s ?? 0) < VAM_MIN_CLIMB_S) continue;
+      }
       const d   = new Date(act.started_at);
       const yr  = d.getFullYear();
       const per = g === 'week' ? weekOfYear(d) : d.getMonth() + 1;
@@ -77,6 +93,11 @@
       const ymc = byYearCnt.get(yr)!;
       ym.set(per,  (ym.get(per)  ?? 0) + val);
       ymc.set(per, (ymc.get(per) ?? 0) + 1);
+      if (m === 'vam') {
+        if (!byYearClimbTime.has(yr)) byYearClimbTime.set(yr, new Map());
+        const yct = byYearClimbTime.get(yr)!;
+        yct.set(per, (yct.get(per) ?? 0) + (act.climbing_time_s ?? 0));
+      }
     }
 
     // VAM: convert sums to averages
@@ -91,13 +112,17 @@
 
     const years  = [...byYear.keys()].sort();
     const maxPer = g === 'week' ? 52 : 12;
-    const rows: { year: string; period: number; value: number }[] = [];
+    const rows: { year: string; period: number; value: number; climbTime?: number }[] = [];
 
     for (const yr of years) {
       const pm    = byYear.get(yr)!;
+      const ct    = byYearClimbTime.get(yr);
       const limit = yr === _currentYear ? curPeriod : maxPer;
       for (let p = 1; p <= limit; p++) {
-        rows.push({ year: String(yr), period: p, value: pm.get(p) ?? 0 });
+        const row: { year: string; period: number; value: number; climbTime?: number } =
+          { year: String(yr), period: p, value: pm.get(p) ?? 0 };
+        if (ct?.has(p)) row.climbTime = ct.get(p);
+        rows.push(row);
       }
     }
 
@@ -173,28 +198,45 @@
       y: { label: yLabel, grid: true, zero: true },
       color: { domain: colorDomain, range: colorRange, legend: !cumulative },
       marks: [
-        ...(pastRows.length ? [
-          Plot.line(pastRows, {
-            x: 'period', y: 'value', stroke: 'year',
-            strokeWidth: 1.5, curve: 'monotone-x',
-          }),
-          Plot.dot(pastRows, {
-            x: 'period', y: 'value', fill: 'year', r: 2, fillOpacity: 0,
-            tip: true,
-            title: (d: any) => `${d.year}  ·  ${xLabel} ${d.period}\n${fmt(d.value)}`,
-          }),
-        ] : []),
-        ...(curRows.length ? [
-          Plot.line(curRows, {
-            x: 'period', y: 'value', stroke: 'year',
-            strokeWidth: 2.5, curve: 'monotone-x',
-          }),
-          Plot.dot(curRows, {
-            x: 'period', y: 'value', fill: 'year', r: 2, fillOpacity: 0,
-            tip: true,
-            title: (d: any) => `${d.year}  ·  ${xLabel} ${d.period}\n${fmt(d.value)}`,
-          }),
-        ] : []),
+        ...(m === 'vam' ? (() => {
+          // VAM: dots only, no lines — opacity encodes total climbing time in period.
+          const vamRows = [...pastRows, ...curRows].filter((r: any) => r.value > 0);
+          return vamRows.length ? [
+            Plot.dot(vamRows, {
+              x: 'period', y: 'value', fill: 'year',
+              r: 5,
+              fillOpacity: (d: any) => vamOpacity(d.climbTime),
+              tip: true,
+              title: (d: any) => {
+                const mins = d.climbTime ? `${Math.round(d.climbTime / 60)} min climbing` : '';
+                return `${d.year}  ·  ${xLabel} ${d.period}\n${fmt(d.value)}${mins ? '\n' + mins : ''}`;
+              },
+            }),
+          ] : [];
+        })() : [
+          ...(pastRows.length ? [
+            Plot.line(pastRows, {
+              x: 'period', y: 'value', stroke: 'year',
+              strokeWidth: 1.5, curve: 'monotone-x',
+            }),
+            Plot.dot(pastRows, {
+              x: 'period', y: 'value', fill: 'year', r: 2, fillOpacity: 0,
+              tip: true,
+              title: (d: any) => `${d.year}  ·  ${xLabel} ${d.period}\n${fmt(d.value)}`,
+            }),
+          ] : []),
+          ...(curRows.length ? [
+            Plot.line(curRows, {
+              x: 'period', y: 'value', stroke: 'year',
+              strokeWidth: 2.5, curve: 'monotone-x',
+            }),
+            Plot.dot(curRows, {
+              x: 'period', y: 'value', fill: 'year', r: 2, fillOpacity: 0,
+              tip: true,
+              title: (d: any) => `${d.year}  ·  ${xLabel} ${d.period}\n${fmt(d.value)}`,
+            }),
+          ] : []),
+        ]),
       ],
     });
     el.appendChild(chart);

site/src/lib/types.ts

@@ -67,6 +67,7 @@ export interface ActivitySummary {
   avg_power_w: number | null;
   mmp: MmpCurve | null;
   climbing_vam_mh?: number | null;
+  climbing_time_s?: number | null;
   source: string | null;
   privacy: Privacy;
   detail_url: string | null;