typescript 36 lines · 6 steps

A weighted moving average in TypeScript

Smooth a series of timestamped readings by averaging each point with its recent neighbors, giving newer samples more weight.

Explained by highlit

Intermediate moving-average sliding-window smoothing weighting

1interface Reading {
2  timestamp: number;
3  value: number;
4}
5 
6export function weightedMovingAverage(
7  readings: readonly Reading[],
8  windowSize: number,
9): Reading[] {
10  if (windowSize < 1) {
11    throw new RangeError(`windowSize must be >= 1, got ${windowSize}`);
12  }
13 
14  const smoothed: Reading[] = [];
15 
16  for (let i = 0; i < readings.length; i++) {
17    const start = Math.max(0, i - windowSize + 1);
18    const window = readings.slice(start, i + 1);
19 
20    let weightedSum = 0;
21    let weightTotal = 0;
22 
23    window.forEach((reading, offset) => {
24      const weight = offset + 1;
25      weightedSum += reading.value * weight;
26      weightTotal += weight;
27    });
28 
29    smoothed.push({
30      timestamp: readings[i].timestamp,
31      value: weightedSum / weightTotal,
32    });
33  }
34 
35  return smoothed;
36}

01 / 01

STEP 01

Walkthrough

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Three takeaways

1A sliding window that grows from the array start avoids special-casing the first few elements.
2Linear weights let recent samples dominate without discarding older context entirely.
3Validating inputs up front turns silent nonsense into a clear, actionable error.

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