Improve training statistics, achievements and stable pace audio

server/public_training_profile.js

@@ -107,12 +107,12 @@ function buildPublicTrainingProfile(state, shareToken, updatedAt, sinceTimestamp
 }
 
 function buildPublicTimingChannelStats(state, classDriverIds) {
-  const splitTimes = [];
+  const splits = [];
   const pitTimes = [];
   Object.values(state?.resultsBySession || {}).forEach((result) => {
     (Array.isArray(result?.splits) ? result.splits : []).forEach((split) => {
       const splitMs = Math.round(Number(split?.splitMs || 0) || 0);
-      if (classDriverIds.has(String(split?.driverId || "")) && splitMs > 0) splitTimes.push(splitMs);
+      if (classDriverIds.has(String(split?.driverId || "")) && splitMs > 0) splits.push({ splitMs, timestamp: Number(split?.timestamp || 0) });
     });
     (Array.isArray(result?.pitStops) ? result.pitStops : []).forEach((stop) => {
       const pitStopMs = Math.round(Number(stop?.pitStopMs || 0) || 0);
@@ -122,10 +122,19 @@ function buildPublicTimingChannelStats(state, classDriverIds) {
   const average = (values) => values.length
     ? Math.round(values.reduce((sum, value) => sum + value, 0) / values.length)
     : 0;
+  splits.sort((left, right) => left.timestamp - right.timestamp);
+  const splitTimes = splits.map((split) => split.splitMs);
+  let runningBestSplitMs = 0;
+  let latestSplitGainMs = 0;
+  splits.forEach((split) => {
+    if (runningBestSplitMs && split.splitMs < runningBestSplitMs) latestSplitGainMs = runningBestSplitMs - split.splitMs;
+    if (!runningBestSplitMs || split.splitMs < runningBestSplitMs) runningBestSplitMs = split.splitMs;
+  });
   return {
     splitCount: splitTimes.length,
     bestSplitMs: splitTimes.length ? Math.min(...splitTimes) : 0,
     averageSplitMs: average(splitTimes),
+    latestSplitGainMs,
     pitStopCount: pitTimes.length,
     totalPitMs: pitTimes.reduce((sum, value) => sum + value, 0),
     bestPitStopMs: pitTimes.length ? Math.min(...pitTimes) : 0,
@@ -217,12 +226,41 @@ function buildPublicTrainingStats(laps) {
     .slice(0, 30);
   const bestLapMs = lapTimes.length ? Math.min(...lapTimes) : 0;
   const controlTargetMs = bestLapMs ? Math.round(bestLapMs * 1.08) : 0;
-  let controlledLapStreak = 0;
-  for (let index = lapTimes.length - 1; index >= 0; index -= 1) {
-    if (!controlTargetMs || lapTimes[index] > controlTargetMs) break;
-    controlledLapStreak += 1;
-  }
   const stints = splitPublicTrainingStints(laps);
+  const summarizeStints = (items) => {
+    let controlledLapStreak = 0;
+    let outlierLaps = 0;
+    let strongFinishStints = 0;
+    let cleanFiveMinuteStints = 0;
+    let completedFiveMinuteStints = 0;
+    items.forEach((stint) => {
+      let currentStreak = 0;
+      const values = stint.laps.filter((lap) => !lap.excludedFromPace).map((lap) => lap.lapMs);
+      values.forEach((lapMs) => {
+        currentStreak = controlTargetMs && lapMs <= controlTargetMs ? currentStreak + 1 : 0;
+        controlledLapStreak = Math.max(controlledLapStreak, currentStreak);
+      });
+      const medianMs = percentile(values, 0.5);
+      const stintOutliers = values.filter((lapMs) => medianMs && lapMs > medianMs * 1.15).length;
+      outlierLaps += stintOutliers;
+      const comparisonSize = values.length >= 6 ? Math.max(3, Math.floor(values.length / 3)) : 0;
+      const startPaceMs = comparisonSize ? average(values.slice(0, comparisonSize)) : 0;
+      const endPaceMs = comparisonSize ? average(values.slice(-comparisonSize)) : 0;
+      if (comparisonSize && endPaceMs <= startPaceMs * 1.01) strongFinishStints += 1;
+      const fiveMinuteResult = getPublicBestDurationResult([stint], 5 * 60 * 1000);
+      if (fiveMinuteResult) completedFiveMinuteStints += 1;
+      if (!stintOutliers && fiveMinuteResult) cleanFiveMinuteStints += 1;
+    });
+    return { controlledLapStreak, outlierLaps, strongFinishStints, cleanFiveMinuteStints, completedFiveMinuteStints };
+  };
+  const stintSummary = summarizeStints(stints);
+  const today = new Date();
+  const todayKey = [today.getFullYear(), String(today.getMonth() + 1).padStart(2, "0"), String(today.getDate()).padStart(2, "0")].join("-");
+  const todayStintSummary = summarizeStints(splitPublicTrainingStints(laps.filter((lap) => {
+    const date = new Date(lap.timestamp);
+    const dateKey = [date.getFullYear(), String(date.getMonth() + 1).padStart(2, "0"), String(date.getDate()).padStart(2, "0")].join("-");
+    return !Number.isNaN(date.getTime()) && dateKey === todayKey;
+  })));
   const bestThreeConsecutive = getPublicBestConsecutiveLaps(stints, 3);
   const bestFiveMinuteResult = getPublicBestDurationResult(stints, 5 * 60 * 1000);
 
@@ -240,7 +278,16 @@ function buildPublicTrainingStats(laps) {
     previousConsistencySpreadPct,
     consistencyTrendPct: trendSampleReady ? previousConsistencySpreadPct - consistencySpreadPct : 0,
     trendSampleReady,
-    controlledLapStreak,
+    controlZoneMinMs: bestLapMs,
+    controlZoneMaxMs: controlTargetMs,
+    controlledLapStreak: stintSummary.controlledLapStreak,
+    outlierLaps: stintSummary.outlierLaps,
+    strongFinishStints: stintSummary.strongFinishStints,
+    cleanFiveMinuteStints: stintSummary.cleanFiveMinuteStints,
+    todayControlledLapStreak: todayStintSummary.controlledLapStreak,
+    todayStrongFinishStints: todayStintSummary.strongFinishStints,
+    todayCleanFiveMinuteStints: todayStintSummary.cleanFiveMinuteStints,
+    todayCompletedFiveMinuteStints: todayStintSummary.completedFiveMinuteStints,
     dailySummaries,
     stintCount: stints.length,
     bestThreeConsecutive,
@@ -259,6 +306,8 @@ function buildPublicTrainingAchievements(stats) {
     ["days_3", Number(stats.trainingDays || 0), 3],
     ["days_10", Number(stats.trainingDays || 0), 10],
     ["controlled_5", Number(stats.controlledLapStreak || 0), 5],
+    ["strong_finish", Number(stats.strongFinishStints || 0), 1],
+    ["clean_five_minute", Number(stats.cleanFiveMinuteStints || 0), 1],
     ["five_minute", stats.bestFiveMinuteResult ? 1 : 0, 1],
   ];
   return definitions.map(([id, current, target]) => ({