static buildSmoothedHistogram()

in src/engine/loaders/voltools.js [172:228]
52 lines of code
14 McCabe index (conditional complexity)

  static buildSmoothedHistogram(histSrc, histDst, numEntries, gaussSigma) {
    // check args
    const ERR_NO_SRC = -1;
    const ERR_NO_DST = -2;
    const ERR_SRC_DST_DIF_LEN = -3;
    const ERR_SRC_LEN_NOT_MATCH = -4;
    const ERR_SIGMA_RANGE = -5;
    if (histSrc === null) {
      return ERR_NO_SRC;
    }
    if (histDst === null) {
      return ERR_NO_DST;
    }
    if (histSrc.length !== histDst.length) {
      return ERR_SRC_DST_DIF_LEN;
    }
    if (histSrc.length !== numEntries) {
      return ERR_SRC_LEN_NOT_MATCH;
    }
    const SIGMA_MIN = 0.0;
    const SIGMA_MAX = 64.0;
    if (gaussSigma < SIGMA_MIN || gaussSigma > SIGMA_MAX) {
      return ERR_SIGMA_RANGE;
    }

    const SIZE_DIV = 60;
    let windowSize = Math.floor(numEntries / SIZE_DIV);
    // avoid too large neighbourhood window size
    const SIZE_LARGE = 32;
    if (windowSize > SIZE_LARGE) {
      windowSize = SIZE_LARGE;
    }

    for (let i = 0; i < numEntries; i++) {
      let sum = 0.0;
      let sumKoef = 0.0;
      for (let j = -windowSize; j <= +windowSize; j++) {
        // t in [-1..+1]
        let t = j / windowSize;
        // t in [0..1]
        t = t >= 0.0 ? t : -t;
        let idx = i + j;
        idx = idx >= 0 ? idx : 0;
        idx = idx < numEntries ? idx : numEntries - 1;
        const val = histSrc[idx];
        const koef = Math.exp(-t * gaussSigma);
        sum += val * koef;
        sumKoef += koef;
      } // for j around neighbourhood
      // divide by window range
      // sum /= (2 * windowSize + 1);
      // normalize average
      sum /= sumKoef;
      histDst[i] = Math.floor(sum);
    } // for i all entries
    return 1;
  } // buildSmoothedHistogram