*
     * Consequently:
     * 1. If the previous mean is finite and the new value is non-finite then the new mean is that
     *    value (whether it is NaN or infinity).
     * 2. If the new value is finite and the previous mean is non-finite then the mean is unchanged
     *    (whether it is NaN or infinity).
     * 3. If both the previous mean and the new value are non-finite and...

                }
            }
        }
    }


    protected void initProtocolVersions ( String minStr, String maxStr ) {
        DialectVersion min = ( minStr != null && !minStr.isEmpty() ) ? DialectVersion.valueOf(minStr) : null;
        DialectVersion max = ( maxStr != null && !maxStr.isEmpty() ) ? DialectVersion.valueOf(maxStr) : null;
        initProtocolVersions(min, max);
    }

          -20,
          Double.NaN,
          Double.NEGATIVE_INFINITY,
          -0.001);

  public void testFuzzyEqualsFinite() {
    for (double a : FINITE_DOUBLE_CANDIDATES) {
      for (double b : FINITE_DOUBLE_CANDIDATES) {
        for (double tolerance : FINITE_TOLERANCE_CANDIDATES) {
          assertEquals(Math.abs(a - b) <= tolerance, DoubleMath.fuzzyEquals(a, b, tolerance));
        }
      }
    }
  }

        fractionalBuilder.add(x);
      }
    }
    FRACTIONAL_DOUBLE_CANDIDATES = fractionalBuilder.build();
    FINITE_DOUBLE_CANDIDATES =
        Iterables.concat(FRACTIONAL_DOUBLE_CANDIDATES, INTEGRAL_DOUBLE_CANDIDATES);
    POSITIVE_FINITE_DOUBLE_CANDIDATES =
        Iterables.filter(
            FINITE_DOUBLE_CANDIDATES,
            new Predicate<Double>() {
              @Override

    assertThat(TWO_VALUES_STATS.mean()).isWithin(ALLOWED_ERROR).of(TWO_VALUES_MEAN);
    // For datasets of many double values created from an array, we test many combinations of finite
    // and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      double mean = Stats.of(values.asArray()).mean();
      if (values.hasAnyNaN()) {
        assertWithMessage("mean of " + values).that(mean).isNaN();

        .isWithin(ALLOWED_ERROR)
        .of(MANY_VALUES_MEAN);
    // For datasets of many double values created from an iterable, we test many combinations of
    // finite and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      StatsAccumulator accumulator = new StatsAccumulator();
      StatsAccumulator accumulatorByAddAllStats = new StatsAccumulator();

  /**
   * Helper class for testing with non-finite values. {@link #ALL_MANY_VALUES} gives a number of
   * instances with many combinations of finite and non-finite values. All have {@link
   * #MANY_VALUES_COUNT} values. If all the values are finite then the mean is {@link
   * #MANY_VALUES_MEAN} and the sum-of-squares-of-deltas is {@link
   * #MANY_VALUES_SUM_OF_SQUARES_OF_DELTAS}. The smallest and largest finite values are always

        }

        public boolean isTarget(final int hours, final int minutes, final int day) {
            if (!reverse) {
                return compareTime(fromHours, fromMinutes, hours, minutes) >= 0 && compareTime(hours, minutes, toHours, toMinutes) >= 0
                        && isInDays(day);
            }
            if ((compareTime(hours, minutes, toHours, toMinutes) >= 0 && isInDays(day + 1))

  }

  static boolean isNormal(double d) {
    return getExponent(d) >= MIN_EXPONENT;
  }

  /*
   * Returns x scaled by a power of 2 such that it is in the range [1, 2). Assumes x is positive,
   * normal, and finite.
   */
  static double scaleNormalize(double x) {
    long significand = doubleToRawLongBits(x) & SIGNIFICAND_MASK;
    return longBitsToDouble(significand | ONE_BITS);
  }

  static double bigToDouble(BigInteger x) {

   * 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