KAHAN {
      @Override
      double mean(double[] values) {
        double sum = 0.0;
        double c = 0.0;
        for (double value : values) {
          double y = value - c;
          double t = sum + y;
          c = (t - sum) - y;
          sum = t;
        }
        return sum / values.length;
      }
    },
    KNUTH {
      @Override
      double mean(double[] values) {
        double mean = values[0];

import static com.google.common.base.Preconditions.checkArgument;
import static java.lang.Double.MAX_EXPONENT;
import static java.lang.Double.MIN_EXPONENT;
import static java.lang.Double.POSITIVE_INFINITY;
import static java.lang.Double.doubleToRawLongBits;
import static java.lang.Double.isNaN;
import static java.lang.Double.longBitsToDouble;
import static java.lang.Math.getExponent;
import static java.lang.Math.max;

   */
  abstract double singleQuantile(int index, int scale, double[] dataset);

  /**
   * Calculates multiple quantiles. Equivalent to {@code
   * Quantiles.scale(scale).indexes(indexes).computeInPlace(dataset)}.
   */
  abstract Map<Integer, Double> multipleQuantiles(
      Collection<Integer> indexes, int scale, double[] dataset);

  static double getMinValue(double[] array, int from) {

import jsinterop.annotations.JsPackage;

/** Web specializations for {@link Doubles} methods. */
public abstract class DoublesMethodsForWeb {

  @JsMethod(name = "Math.min", namespace = JsPackage.GLOBAL)
  public static native double min(double... array);

  @JsMethod(name = "Math.max", namespace = JsPackage.GLOBAL)
  public static native double max(double... array);

 *
 * @author Louis Wasserman
 */
public class DoubleMathRoundingBenchmark {
  private static final double[] doubleInIntRange = new double[ARRAY_SIZE];
  private static final double[] doubleInLongRange = new double[ARRAY_SIZE];
  private static final double[] positiveDoubles = new double[ARRAY_SIZE];

  @Param({"DOWN", "UP", "FLOOR", "CEILING", "HALF_EVEN", "HALF_UP", "HALF_DOWN"})
  RoundingMode mode;

    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);

  private static final double ALLOWED_ERROR = 1.0e-10;
  private static final QuantilesAlgorithm REFERENCE_ALGORITHM = QuantilesAlgorithm.SORTING;
  private static final Set<QuantilesAlgorithm> NON_REFERENCE_ALGORITHMS =
      Sets.difference(
          ImmutableSet.copyOf(QuantilesAlgorithm.values()), ImmutableSet.of(REFERENCE_ALGORITHM));

  private double[] dataset;

  @Override
  protected void setUp() {

  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 class MultipleSetContainsBenchmark {

  @Param({"0.0", "0.1", "0.7", "1.0"})
  double emptySetProportion;

  @Param({"0.0", "0.1", "0.7", "1.0"})
  double singletonSetProportion;

  @Param({"0.2", "0.8"})
  double hitRate;

  static final Object PRESENT = new Object();
  static final Object ABSENT = new Object();

    for (int i = 0; i < reps; i++) {
      String unused = interner.intern(Double.toHexString(Math.random()));
    }
    return reps;
  }

  @Benchmark
  int strongInterner(int reps) {
    Interner<String> interner = Interners.newStrongInterner();
    for (int i = 0; i < reps; i++) {
      String unused = interner.intern(Double.toHexString(Math.random()));
    }
    return reps;
  }

  @Benchmark