assertThat(ONE_VALUE_PAIRED_STATS.populationCovariance()).isWithin(0.0).of(0.0);
    assertThat(createSingleStats(Double.POSITIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NEGATIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NaN, 1.23).populationCovariance()).isNaN();
    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())

    assertThat(ONE_VALUE_PAIRED_STATS.populationCovariance()).isWithin(0.0).of(0.0);
    assertThat(createSingleStats(Double.POSITIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NEGATIVE_INFINITY, 1.23).populationCovariance()).isNaN();
    assertThat(createSingleStats(Double.NaN, 1.23).populationCovariance()).isNaN();
    assertThat(TWO_VALUES_PAIRED_STATS.populationCovariance())

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 datasets of many double values created from an iterable, we test many combinations of
    // finite and non-finite values:
    for (ManyValues values : ALL_MANY_VALUES) {
      StatsAccumulator accumulator = new StatsAccumulator();
      StatsAccumulator accumulatorByAddAllStats = new StatsAccumulator();
      accumulator.addAll(values.asIterable());
      for (double value : values.asIterable()) {

        .expect(1L, 1L, 2L, 3L);
  }

  public void testFlatMapToDouble_nullStream() {
    SpliteratorTester.ofDouble(
            () ->
                CollectSpliterators.flatMapToDouble(
                    Arrays.spliterator(new Double[] {1.0, 0.0, 1.0, 2.0, 3.0}),
                    (Double i) -> i == 0.0 ? null : DoubleStream.of(i).spliterator(),
                    Spliterator.SIZED | Spliterator.DISTINCT | Spliterator.NONNULL,

    in.put(Number.class, 0);
    in.put(Double.class, Math.PI);
    ClassToInstanceMap<Number> map = ImmutableClassToInstanceMap.copyOf(in);
    assertEquals(2, map.size());

    Number zero = map.getInstance(Number.class);
    assertEquals(0, zero);

    Double pi = map.getInstance(Double.class);
    assertEquals(Math.PI, pi, 0.0);

      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =
          createPartitionedFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES, 2);
      double populationCovariance = accumulator.populationCovariance();
      double populationCovarianceByAddAllPartitionedPairedStats =
          accumulatorByAddAllPartitionedPairedStats.populationCovariance();
      if (values.hasAnyNonFinite()) {

      PairedStatsAccumulator accumulatorByAddAllPartitionedPairedStats =
          createPartitionedFilledPairedStatsAccumulator(values.asIterable(), OTHER_MANY_VALUES, 2);
      double populationCovariance = accumulator.populationCovariance();
      double populationCovarianceByAddAllPartitionedPairedStats =
          accumulatorByAddAllPartitionedPairedStats.populationCovariance();
      if (values.hasAnyNonFinite()) {

    Random random = new Random();
    int warmupPermits = 10;
    double[] coldFactorsToTest = {2.0, 3.0, 10.0};
    double[] qpsToTest = {4.0, 2.0, 1.0, 0.5, 0.1};
    for (int trial = 0; trial < 100; trial++) {
      for (double coldFactor : coldFactorsToTest) {
        for (double qps : qpsToTest) {
          // If warmupPermits = maxPermits - thresholdPermits then

    in.put(Number.class, 0);
    in.put(Double.class, Math.PI);
    ClassToInstanceMap<Number> map = ImmutableClassToInstanceMap.copyOf(in);
    assertEquals(2, map.size());

    Number zero = map.getInstance(Number.class);
    assertEquals(0, zero);

    Double pi = map.getInstance(Double.class);
    assertEquals(Math.PI, pi, 0.0);