import java.util.Map;
import java.util.Random;
import java.util.Set;
import junit.framework.TestCase;

/**
 * Tests that the different algorithms benchmarked in {@link QuantilesBenchmark} are actually all
 * returning more-or-less the same answers.
 */
public class QuantilesAlgorithmTest extends TestCase {

  private static final Random RNG = new Random(82674067L);
  private static final int DATASET_SIZE = 1000;

        }
      }
    },
    RANDOM {
      @Override
      void arrange(List<Integer> list) {}
    };

    abstract void arrange(List<Integer> list);
  }

  private ImmutableList<Integer> input;

  @BeforeExperiment
  void setUp() {
    checkArgument(size > 0, "empty collection not supported");
    Set<Integer> set = new LinkedHashSet<>(size);

    Random random = new Random();

      nonnegative[i] = randomNonNegativeBigInteger(Long.SIZE - 1).longValue();
      longs[i] = RANDOM_SOURCE.nextLong();
      factorialArguments[i] = RANDOM_SOURCE.nextInt(30);
      binomialArguments[i][1] = RANDOM_SOURCE.nextInt(MathBenchmarking.biggestBinomials.length);
      int k = binomialArguments[i][1];
      binomialArguments[i][0] = RANDOM_SOURCE.nextInt(MathBenchmarking.biggestBinomials[k] - k) + k;
    }
  }

  @Benchmark

  @BeforeExperiment
  void setUp() {
    Random random = new Random(randomSeed);
    xInts = new int[SAMPLE_SIZE];
    yInts = new int[SAMPLE_SIZE];
    xLongs = new long[SAMPLE_SIZE];
    yLongs = new long[SAMPLE_SIZE];
    constant = new int[SAMPLE_SIZE];
    for (int i = 0; i < SAMPLE_SIZE; i++) {
      xInts[i] = random.nextInt(Integer.MAX_VALUE);
      yInts[i] = random.nextInt(Integer.MAX_VALUE);

   * [acquire(5), acquire(1)] takes exactly the same time as [acquire(2), acquire(3), acquire(1)].
   */
  public void testTimeToWarmUpIsHonouredEvenWithWeights() {
    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++) {

  int datasetSize;

  @Param QuantilesAlgorithm algorithm;

  private 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();
      }
    }
  }

// GenerateAccessKey returns a new access key generated randomly using
// the given io.Reader. If random is nil, crypto/rand.Reader is used.
// If length <= 0, the access key length is chosen automatically.
//
// GenerateAccessKey returns an error if length is too small for a valid
// access key.
func GenerateAccessKey(length int, random io.Reader) (string, error) {
	if random == nil {
		random = rand.Reader
	}
	if length <= 0 {

    if (TF_GetCode(status) != TF_OK) {
      TF_DeleteStatus(status);
      return "";
    }
    TF_DeleteStatus(status);

    // We add a random value into `test_dir` to ensures that two consecutive
    // runs are unlikely to clash.
    std::random_device rd;
    std::mt19937 gen(rd());
    std::uniform_int_distribution<> distribution;
    std::string rng_val = std::to_string(distribution(gen));

  // Use a statically configured random instance for all of the benchmarks
  private static final Random random = new Random(42);

  @Param({"10", "1000", "100000", "1000000"})
  private int size;

  @Param HashFunctionEnum hashFunctionEnum;

  private byte[] testBytes;

  @BeforeExperiment
  void setUp() {
    testBytes = new byte[size];
    random.nextBytes(testBytes);
  }

  @Benchmark

    treeMultiset = TreeMultiset.create();

    Random random = new Random();

    int sizeRemaining = size;

    // TODO(kevinb): generate better test contents for multisets
    for (int i = 0; sizeRemaining > 0; i++) {
      // The JVM will return interned values for small ints.
      Integer value = random.nextInt(1000) + 128;
      int count = Math.min(random.nextInt(10) + 1, sizeRemaining);
      sizeRemaining -= count;