*/
  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) {

 * Double#doubleToRawLongBits}, which differs from both the primitive double {@code ==} operator and
 * from {@link Double#equals}, as if implemented by:
 *
 * <pre>{@code
 * static boolean bitEquals(double x, double y) {
 *   long xBits = Double.doubleToRawLongBits(x);
 *   long yBits = Double.doubleToRawLongBits(y);
 *   return xBits == yBits;
 * }
 * }</pre>
 *
 * @author Doug Lea
 * @author Martin Buchholz
 * @since 11.0
 */

 *
 * @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();

  private static final double[] VALUES = {
    Double.NEGATIVE_INFINITY,
    -Double.MAX_VALUE,
    (double) Long.MIN_VALUE,
    (double) Integer.MIN_VALUE,
    -Math.PI,
    -1.0,
    -Double.MIN_VALUE,
    -0.0,
    +0.0,
    Double.MIN_VALUE,
    1.0,
    Math.PI,
    (double) Integer.MAX_VALUE,
    (double) Long.MAX_VALUE,
    Double.MAX_VALUE,
    Double.POSITIVE_INFINITY,

    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

  }

  public void testMappingAnd_horizontal() {
    double x1 = 1.2;
    double xDelta = 3.4;
    double y = 5.6;
    LinearTransformation transformation = LinearTransformation.mapping(x1, y).and(x1 + xDelta, y);
    assertHorizontalLinearTransformation(transformation, y);
  }

  public void testMappingAnd_vertical() {
    double x = 1.2;
    double y1 = 3.4;
    double yDelta = 5.6;