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@callstack/reassure-measure

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Performance measurement library for React and React Native

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/* Adapted from https://github.com/sharkdp/hyperfine/blob/3b0918511aee4d6f8860bb663cb7a7af57bc3814/src/outlier_detection.rs */ import * as math from 'mathjs'; // Minimum modified Z-score for a datapoint to be an outlier. Here, 1.4826 is a factor that // converts the MAD to an estimator for the standard deviation. The second factor is the number // of standard deviations. const OUTLIER_THRESHOLD = 1.4826 * 10; export function findOutliers(items) { if (items.length <= 1) { return { results: items, outliers: [] }; } const durations = items.map(({ duration }) => duration); // Compute the sample median and median absolute deviation (MAD) const median = math.median(durations); const mad = math.mad(durations); return items.reduce((acc, result) => { const modifiedZScore = (result.duration - median) / (mad > 0 ? mad : Number.EPSILON); // An outlier is a point that is larger than the modified Z-score threshold if (Math.abs(modifiedZScore) > OUTLIER_THRESHOLD) { acc.outliers.push(result); } else { acc.results.push(result); } return acc; }, { results: [], outliers: [] }); } //# sourceMappingURL=outlier-helpers.js.map