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

  private static 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);
  }

   * each other or identical non-finite values.
   */
  private static final Correspondence<Double, Double> QUANTILE_CORRESPONDENCE =
      Correspondence.from(
          new BinaryPredicate<Double, Double>() {
            @Override
            public boolean apply(@Nullable Double actual, @Nullable Double expected) {
              // Test for equality to allow non-finite values to match; otherwise, use the finite

   * each other or identical non-finite values.
   */
  private static final Correspondence<Double, Double> QUANTILE_CORRESPONDENCE =
      Correspondence.from(
          new BinaryPredicate<Double, Double>() {
            @Override
            public boolean apply(@Nullable Double actual, @Nullable Double expected) {
              // Test for equality to allow non-finite values to match; otherwise, use the finite

  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,

      Double[] suffix = {86.0, 99.0};
      Double[] all = concat(concat(prefix, elements), suffix);
      return makeArray(all).subArray(2, elements.length + 2).asList();
    }
  }

  @J2ktIncompatible
  @GwtIncompatible // used only from suite
  @AndroidIncompatible
  private static Double[] concat(Double[] a, Double[] b) {
    return ObjectArrays.concat(a, b, Double.class);
  }

  @Param QuantilesAlgorithm algorithm;

  private final double[][] datasets = new double[0x100][];

  @BeforeExperiment
  void setUp() {
    Random rng = new Random();
    for (int i = 0; i < 0x100; i++) {
      datasets[i] = new double[datasetSize];
      for (int j = 0; j < datasetSize; j++) {
        datasets[i][j] = rng.nextDouble();
      }
    }
  }

  private double[] dataset(int i) {

  @Param QuantilesAlgorithm algorithm;

  private final double[][] datasets = new double[0x100][];

  @BeforeExperiment
  void setUp() {
    Random rng = new Random();
    for (int i = 0; i < 0x100; i++) {
      datasets[i] = new double[datasetSize];
      for (int j = 0; j < datasetSize; j++) {
        datasets[i][j] = rng.nextDouble();
      }
    }
  }

  private double[] dataset(int i) {

 *
 * @author Louis Wasserman
 */
@NullUnmarked
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;

    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) {

          .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;
    }