"Add Windows installer and driver training rewards"

src/training_logic.js

@@ -0,0 +1,113 @@
+export function normalizeTrainingState(training, { uid }) {
+  const source = training && typeof training === "object" ? training : {};
+  const goals = Array.isArray(source.goals)
+    ? source.goals
+        .map((goal) => ({
+          id: String(goal?.id || uid("goal")),
+          driverId: String(goal?.driverId || ""),
+          title: String(goal?.title || "").trim(),
+          reward: String(goal?.reward || "").trim(),
+          targetLaps: Math.max(1, Math.round(Number(goal?.targetLaps || 0) || 0)),
+          createdAt: String(goal?.createdAt || new Date().toISOString()),
+          claimedAt: goal?.claimedAt ? String(goal.claimedAt) : "",
+        }))
+        .filter((goal) => goal.driverId && goal.targetLaps > 0)
+    : [];
+
+  return { goals };
+}
+
+export function getDriverTrainingLaps(state, driverId) {
+  const laps = [];
+  Object.entries(state?.resultsBySession || {}).forEach(([sessionId, result]) => {
+    (Array.isArray(result?.passings) ? result.passings : []).forEach((passing) => {
+      const lapMs = Number(passing?.lapMs || 0);
+      if (
+        String(passing?.driverId || "") === String(driverId || "") &&
+        passing?.validLap !== false &&
+        lapMs > 500
+      ) {
+        laps.push({
+          sessionId,
+          timestamp: Number(passing.timestamp || 0) || 0,
+          lapMs,
+        });
+      }
+    });
+  });
+  return laps.sort((left, right) => left.timestamp - right.timestamp);
+}
+
+function percentile(values, ratio) {
+  if (!values.length) return 0;
+  const sorted = [...values].sort((left, right) => left - right);
+  const index = Math.min(sorted.length - 1, Math.max(0, Math.round((sorted.length - 1) * ratio)));
+  return sorted[index];
+}
+
+export function buildDriverTrainingStats(state, driverId) {
+  const laps = getDriverTrainingLaps(state, driverId);
+  const lapTimes = laps.map((lap) => lap.lapMs);
+  const recentLapTimes = lapTimes.slice(-30);
+  const totalLaps = laps.length;
+  const bestLapMs = totalLaps ? Math.min(...lapTimes) : 0;
+  const averageLapMs = totalLaps ? Math.round(lapTimes.reduce((sum, value) => sum + value, 0) / totalLaps) : 0;
+  const recentAverageMs = recentLapTimes.length
+    ? Math.round(recentLapTimes.reduce((sum, value) => sum + value, 0) / recentLapTimes.length)
+    : 0;
+  const recentP10Ms = percentile(recentLapTimes, 0.1);
+  const recentP90Ms = percentile(recentLapTimes, 0.9);
+  const consistencySpreadPct = recentAverageMs
+    ? ((recentP90Ms - recentP10Ms) / recentAverageMs) * 100
+    : 0;
+
+  return {
+    totalLaps,
+    totalSessions: new Set(laps.map((lap) => lap.sessionId)).size,
+    bestLapMs,
+    averageLapMs,
+    recentAverageMs,
+    consistencySpreadPct,
+    recentLapCount: recentLapTimes.length,
+    lastLapAt: laps.at(-1)?.timestamp || 0,
+  };
+}
+
+export function buildTrainingRecommendation(stats) {
+  if (!stats || stats.totalLaps < 10) {
+    return {
+      level: "baseline",
+      titleKey: "training.plan_baseline_title",
+      bodyKey: "training.plan_baseline_body",
+      targetLapMs: 0,
+    };
+  }
+
+  if (stats.recentLapCount >= 10 && stats.consistencySpreadPct > 8) {
+    return {
+      level: "consistency",
+      titleKey: "training.plan_consistency_title",
+      bodyKey: "training.plan_consistency_body",
+      targetLapMs: Math.round(stats.bestLapMs * 1.08),
+    };
+  }
+
+  return {
+    level: "progression",
+    titleKey: "training.plan_progression_title",
+    bodyKey: "training.plan_progression_body",
+    targetLapMs: Math.round(stats.bestLapMs * 1.05),
+  };
+}
+
+export function getTrainingGoalProgress(goal, stats) {
+  const targetLaps = Math.max(1, Number(goal?.targetLaps || 1));
+  const currentLaps = Math.max(0, Number(stats?.totalLaps || 0));
+  return {
+    currentLaps,
+    targetLaps,
+    remainingLaps: Math.max(0, targetLaps - currentLaps),
+    percent: Math.min(100, Math.max(0, (currentLaps / targetLaps) * 100)),
+    reached: currentLaps >= targetLaps,
+  };
+}