cess","chainable","emptyGet","raw","bulk","_key","rmsPrefix","rdashAlpha","fcamelCase","_all","letter","toUpperCase","camelCase","string","acceptData","owner","Data","uid","defineProperty","configurable","set","data","prop","hasData","dataPriv","dataUser","rbrace","rmultiDash","dataAttr","JSON","parse","removeData","_data","_removeData","attrs","dequeue","startLength","hooks","_queueHooks","unshift","stop","setter","clearQueue","tmp","count","defer","pnum","source","rcssNum","cssExpand","isAttac...

     *
     * @param dataset the dataset to do the calculation on, which must be non-empty, and which will
     *     be arbitrarily reordered by this method call
     * @return the quantile value
     */
    public double computeInPlace(double... dataset) {
      checkArgument(dataset.length > 0, "Cannot calculate quantiles of an empty dataset");
      if (containsNaN(dataset)) {

     */
    public void setEcsServiceName(final String ecsServiceName) {
        this.ecsServiceName = ecsServiceName;
    }

    /**
     * Set the ECS event dataset.
     * @param ecsEventDataset The ECS event dataset.
     */
    public void setEcsEventDataset(final String ecsEventDataset) {
        this.ecsEventDataset = ecsEventDataset;
    }

    long[] dataset = Longs.toArray(SIXTEEN_SQUARES_LONGS);
    assertThat(Quantiles.scale(10).index(1).compute(dataset))
        .isWithin(ALLOWED_ERROR)
        .of(SIXTEEN_SQUARES_DECILE_1);
    assertThat(dataset).asList().isEqualTo(SIXTEEN_SQUARES_LONGS);
  }

  public void testScale_index_compute_intVarargs() {
    int[] dataset = Ints.toArray(SIXTEEN_SQUARES_INTEGERS);

    long[] dataset = Longs.toArray(SIXTEEN_SQUARES_LONGS);
    assertThat(Quantiles.scale(10).index(1).compute(dataset))
        .isWithin(ALLOWED_ERROR)
        .of(SIXTEEN_SQUARES_DECILE_1);
    assertThat(dataset).asList().isEqualTo(SIXTEEN_SQUARES_LONGS);
  }

  public void testScale_index_compute_intVarargs() {
    int[] dataset = Ints.toArray(SIXTEEN_SQUARES_INTEGERS);

        setEncoding((String) src.get(ENCODING));
        final String dataStr = (String) src.get(DATA);
        if (dataStr != null) {
            try {
                setData(Base64Util.decode(dataStr));
            } catch (final Exception e) {
                throw new OpenSearchAccessException("data: " + dataStr, e);
            }
        }
    }

    /**

  SORTING {

    @Override
    double singleQuantile(int index, int scale, double[] dataset) {
      Arrays.sort(dataset);
      return singleQuantileFromSorted(index, scale, dataset);
    }

    @Override
    Map<Integer, Double> multipleQuantiles(
        Collection<Integer> indexes, int scale, double[] dataset) {
      Arrays.sort(dataset);
      ImmutableMap.Builder<Integer, Double> builder = ImmutableMap.builder();

   *
   * <p>This is guaranteed to return zero if the dataset contains a single pair of finite values. It
   * is not guaranteed to return zero when the dataset consists of the same pair of values multiple
   * times, due to numerical errors.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

   *
   * <p>This is guaranteed to return zero if the dataset contains only exactly one finite value. It
   * is not guaranteed to return zero when the dataset consists of the same value multiple times,
   * due to numerical errors. However, it is guaranteed never to return a negative result.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link

   *
   * <p>This is guaranteed to return zero if the dataset contains a single pair of finite values. It
   * is not guaranteed to return zero when the dataset consists of the same pair of values multiple
   * times, due to numerical errors.
   *
   * <h3>Non-finite values</h3>
   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link