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) {

        assertEquals(0, new BigDecimal("0.01").compareTo(BigDecimalConversionUtil.toBigDecimal(Double.valueOf(0.01D))));
        assertEquals(0, new BigDecimal("0.001").compareTo(BigDecimalConversionUtil.toBigDecimal(Double.valueOf(0.001D))));
        assertEquals(0, new BigDecimal("0.0001").compareTo(BigDecimalConversionUtil.toBigDecimal(Double.valueOf(0.0001D))));

    final double slope;
    final double yIntercept;

    @LazyInit @Nullable LinearTransformation inverse;

    RegularLinearTransformation(double slope, double yIntercept) {
      this.slope = slope;
      this.yIntercept = yIntercept;
      this.inverse = null; // to be lazily initialized
    }

    RegularLinearTransformation(double slope, double yIntercept, LinearTransformation inverse) {

        case HALF_UP:
          return Double.MAX_VALUE * sign(x);
        case FLOOR:
          return (roundArbitrarily == Double.POSITIVE_INFINITY)
              ? Double.MAX_VALUE
              : Double.NEGATIVE_INFINITY;
        case CEILING:
          return (roundArbitrarily == Double.POSITIVE_INFINITY)
              ? Double.POSITIVE_INFINITY
              : -Double.MAX_VALUE;
        case UP:

    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) {

          .toString();
    }
  }

  double sumOfProductsOfDeltas() {
    return sumOfProductsOfDeltas;
  }

  private static double ensurePositive(double value) {
    if (value > 0.0) {
      return value;
    } else {
      return Double.MIN_VALUE;
    }
  }

  private static double ensureInUnitRange(double value) {
    if (value >= 1.0) {
      return 1.0;
    }

    for (double positiveValue : POSITIVE_FINITE_DOUBLE_CANDIDATES) {
      assertThat(DoubleUtils.ensureNonNegative(positiveValue)).isEqualTo(positiveValue);
      assertThat(DoubleUtils.ensureNonNegative(-positiveValue)).isEqualTo(0.0);
    }
    assertThat(DoubleUtils.ensureNonNegative(Double.POSITIVE_INFINITY)).isPositiveInfinity();
    assertThat(DoubleUtils.ensureNonNegative(Double.NEGATIVE_INFINITY)).isEqualTo(0.0);

            long timeEnd = measureEqualsTime(baseAuth, endAuth, TIMING_ITERATIONS);

            // Calculate relative timing differences
            double maxTime = Math.max(Math.max(timeStart, timeMiddle), timeEnd);
            double minTime = Math.min(Math.min(timeStart, timeMiddle), timeEnd);
            double timingRatio = (maxTime - minTime) / maxTime;

            // Timing differences should be minimal (within tolerance)

   * 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

    public void setAvailable_PercentileRanks(double[] values) {
        setAvailable_PercentileRanks(values, null);
    }

    public void setAvailable_PercentileRanks(double[] values, ConditionOptionCall<PercentileRanksAggregationBuilder> opLambda) {
        setAvailable_PercentileRanks("available", values, opLambda);
    }

    public void setAvailable_PercentileRanks(String name, double[] values,