правки по графикам

src/pages/workouts/components/NormalizedPower.ts

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+/**
+ * Computes Normalized Power (NP) over a slice of a workout, matching the
+ * canonical Strava/TrainingPeaks algorithm and tolerating uneven sample dt.
+ *
+ * Exponential 4th-power smoothing with a 30 s time constant; points with
+ * null power or non-finite timestamps are skipped, as are samples with
+ * non-positive dt. Returns null when fewer than 2 valid points exist.
+ *
+ * @param times timestamps (ISO strings or ms numbers), 1 Hz
+ * @param powers power in watts, null where the sensor has no data
+ * @param startIdx inclusive start index
+ * @param endIdx exclusive end index
+ */
+export function normalizedPower(
+  times: Array<string | number>,
+  powers: Array<number | null>,
+  startIdx: number,
+  endIdx: number,
+): number | null {
+  const tau = 30;
+  const end = Math.min(endIdx, times.length, powers.length);
+  const start = Math.max(0, startIdx);
+
+  // Collect valid points: finite timestamp + non-null power.
+  const t: number[] = [];
+  const p: number[] = [];
+  for (let i = start; i < end; i++) {
+    const raw = times[i];
+    const ms =
+      typeof raw === "number" && Number.isFinite(raw)
+        ? raw
+        : Number(new Date(raw as string));
+    const w = powers[i];
+    if (!Number.isFinite(ms) || w === null || !Number.isFinite(w)) {
+      continue;
+    }
+    t.push(ms);
+    p.push(w);
+  }
+
+  const n = p.length;
+  if (n < 2) {
+    return null;
+  }
+
+  // Exponential smoothing of p^4; the last sample has no forward dt, so its
+  // 4th power is added to the sum as its own smoothing value.
+  let sm = Math.pow(p[0], 4);
+  let sum = sm;
+  let count = 1;
+  for (let i = 1; i < n; i++) {
+    const dt = (t[i] - t[i - 1]) / 1000;
+    if (dt <= 0) {
+      continue;
+    }
+    sm = sm + (Math.pow(p[i], 4) - sm) * (1 - Math.exp(-dt / tau));
+    sum += sm;
+    count += 1;
+  }
+
+  return Math.pow(sum / count, 0.25);
+}