return new ImmutableDoubleArray(new double[] {e0, e1, e2, e3});
  }

  /** Returns an immutable array containing the given values, in order. */
  public static ImmutableDoubleArray of(double e0, double e1, double e2, double e3, double e4) {
    return new ImmutableDoubleArray(new double[] {e0, e1, e2, e3, e4});
  }

      return LinearTransformation.vertical(xStats.mean());
    }
  }

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

  private static double ensureInUnitRange(double value) {
    return Doubles.constrainToRange(value, -1.0, 1.0);
  }

    for (double tolerance : TOLERANCE_CANDIDATES) {
      assertTrue(DoubleMath.fuzzyEquals(Double.NaN, Double.NaN, tolerance));
    }
  }

  public void testFuzzyEqualsZeroTolerance() {
    // make sure we test -0 tolerance
    for (double zero : Doubles.asList(0.0, -0.0)) {
      for (double a : ALL_DOUBLE_CANDIDATES) {
        for (double b : ALL_DOUBLE_CANDIDATES) {
          assertEquals(

  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,

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;

    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;