@GwtCompatible
@ElementTypesAreNonnullByDefault
final class Hashing {
  private Hashing() {}

  /*
   * These should be ints, but we need to use longs to force GWT to do the multiplications with
   * enough precision.
   */
  private static final long C1 = 0xcc9e2d51;
  private static final long C2 = 0x1b873593;

  /*
   * This method was rewritten in Java from an intermediate step of the Murmur hash function in

    List<Short> shorts = Arrays.asList((short) 0, (short) 1, (short) 2);
    List<Integer> ints = Arrays.asList(0, 1, 2);
    List<Float> floats = Arrays.asList((float) 0, (float) 1, (float) 2);
    List<Long> longs = Arrays.asList((long) 0, (long) 1, (long) 2);
    List<Double> doubles = Arrays.asList((double) 0, (double) 1, (double) 2);

    assertThat(Bytes.toArray(bytes)).isEqualTo(array);
    assertThat(Bytes.toArray(shorts)).isEqualTo(array);

   */
  protected void processRemaining(ByteBuffer bb) {
    Java8Compatibility.position(bb, bb.limit()); // move at the end
    Java8Compatibility.limit(bb, chunkSize + 7); // get ready to pad with longs
    while (bb.position() < chunkSize) {
      bb.putLong(0);
    }
    Java8Compatibility.limit(bb, chunkSize);
    Java8Compatibility.flip(bb);
    process(bb);
  }

  @Override
  @CanIgnoreReturnValue

    List<Short> shorts = Arrays.asList((short) 0, (short) 1, (short) 2);
    List<Integer> ints = Arrays.asList(0, 1, 2);
    List<Float> floats = Arrays.asList((float) 0, (float) 1, (float) 2);
    List<Long> longs = Arrays.asList((long) 0, (long) 1, (long) 2);
    List<Double> doubles = Arrays.asList((double) 0, (double) 1, (double) 2);

    assertThat(Bytes.toArray(bytes)).isEqualTo(array);
    assertThat(Bytes.toArray(shorts)).isEqualTo(array);

   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
   */
  public static Stats of(long... values) {
    StatsAccumulator accumulator = new StatsAccumulator();
    accumulator.addAll(values);
    return accumulator.snapshot();
  }

  /**

  }

  public void testToLong() {
    for (long a : UNSIGNED_INTS) {
      assertThat(UnsignedInts.toLong((int) a)).isEqualTo(a);
    }
  }

  public void testCompare() {
    for (long a : UNSIGNED_INTS) {
      for (long b : UNSIGNED_INTS) {
        int cmpAsLongs = Longs.compare(a, b);
        int cmpAsUInt = UnsignedInts.compare((int) a, (int) b);

   *
   * @param values a series of values, which will be converted to {@code double} values (this may
   *     cause loss of precision for longs of magnitude over 2^53 (slightly over 9e15))
   */
  public void addAll(long... values) {
    for (long value : values) {
      add(value);
    }
  }

  /**
   * Adds the given values to the dataset. The stream will be completely consumed by this method.

    List<Short> shorts = Arrays.asList((short) 0, (short) 1, (short) 2);
    List<Integer> ints = Arrays.asList(0, 1, 2);
    List<Float> floats = Arrays.asList((float) 0, (float) 1, (float) 2);
    List<Long> longs = Arrays.asList((long) 0, (long) 1, (long) 2);
    List<Double> doubles = Arrays.asList((double) 0, (double) 1, (double) 2);

    assertThat(Doubles.toArray(bytes)).isEqualTo(array);
    assertThat(Doubles.toArray(shorts)).isEqualTo(array);

          "Quantile indexes must be between 0 and the scale, which is " + scale);
    }
  }

  private static double[] longsToDoubles(long[] longs) {
    int len = longs.length;
    double[] doubles = new double[len];
    for (int i = 0; i < len; i++) {
      doubles[i] = longs[i];
    }
    return doubles;
  }

  private static double[] intsToDoubles(int[] ints) {
    int len = ints.length;

        .of(LONG_MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS / LONG_MANY_VALUES_COUNT);
    assertThat(LARGE_LONG_VALUES_STATS.populationVariance())
        .isWithin(ALLOWED_ERROR * Long.MAX_VALUE * Long.MAX_VALUE)
        .of(LARGE_LONG_VALUES_POPULATION_VARIANCE);
  }

  public void testPopulationStandardDeviation() {
    assertThrows(