* infinite {@code double} values are considered infinitely far away. For example, 2^2000 is not
   * representable as a double, but {@code roundToDouble(BigDecimal.valueOf(2).pow(2000), HALF_UP)}
   * will return {@code Double.MAX_VALUE}, not {@code Double.POSITIVE_INFINITY}.
   *
   * <p>For the case of {@link RoundingMode#HALF_EVEN}, this implementation uses the IEEE 754

     */
    private double calculateSuccessRate() {
        long total = totalRequests.get();
        if (total == 0) {
            return 100.0;
        }
        return (totalSuccesses.get() * 100.0) / total;
    }

    /**
     * Calculate availability
     *
     * @return availability as percentage (0-100)
     */
    private double calculateAvailability() {

          } else {
            diff[k] += 1;
          }
        }
      }
      // measure probability and assert it's within margin of error
      for (int j = 0; j < hashBits; j++) {
        double prob = (double) diff[j] / (double) (diff[j] + same[j]);
        assertThat(prob).isWithin(epsilon).of(0.50d);
      }
    }
  }

  /**

  public void testCheckNonNegative_zeroDouble() {
    MathPreconditions.checkNonNegative("double", 0d);
  }

  public void testCheckNonNegative_maxDouble() {
    MathPreconditions.checkNonNegative("double", Double.MAX_VALUE);
  }

  public void testCheckNonNegative_minDouble() {
    MathPreconditions.checkNonNegative("double", Double.MIN_VALUE);
  }

  public void testCheckNonNegative_positiveDouble() {

     */
    public double getAverageReadLatencyMicros() {
        long reads = rdmaReads.get();
        if (reads == 0) {
            return 0.0;
        }
        return totalReadTime.get() / (double) reads / 1000.0; // Convert to microseconds
    }

    /**
     * Calculate average write latency in microseconds
     *
     * @return average write latency
     */
    public double getAverageWriteLatencyMicros() {

    assertThat(ONE_VALUE_PAIRED_STATS.populationCovariance()).isEqualTo(0.0);
    assertThat(createSingleStats(Double.POSITIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NEGATIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NaN, 1.23).populationCovariance()).isNaN();
    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())

    assertThat(ONE_VALUE_PAIRED_STATS.populationCovariance()).isEqualTo(0.0);
    assertThat(createSingleStats(Double.POSITIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NEGATIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NaN, 1.23).populationCovariance()).isNaN();
    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())

    double expectedReportedFpp = (double) knownNumberOfFalsePositives / numInsertions;
    double actualReportedFpp = bf.expectedFpp();
    assertThat(actualReportedFpp).isWithin(0.00033).of(expectedReportedFpp);
  }

  /** Sanity checking with many combinations of false positive rates and expected insertions */
  public void testBasic() {
    for (double fpr = 0.0000001; fpr < 0.1; fpr *= 10) {

    }

    public void formatRate(MessageBuilder builder, double rate) {
        // Handle invalid rates gracefully (including negative values)
        if (Double.isNaN(rate) || Double.isInfinite(rate) || rate < 0) {
            builder.append("? B/s");
            return;
        }

        ScaleUnit unit = ScaleUnit.getScaleUnit(Math.round(rate));
        double scaledRate = rate / unit.bytes();

      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =
          createPartitionedFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES, 2);
      double populationCovariance = accumulator.populationCovariance();
      double populationCovarianceByAddAllPartitionedPairedStats =
          accumulatorByAddAllPartitionedPairedStats.populationCovariance();
      if (values.hasAnyNonFinite()) {