* Optional<Number>} (where {@code Number} is the desired output type) solves the problem:
   *
   * <pre>{@code
   * Optional<Number> optionalInt = (Optional) getSomeOptionalInt();
   * Number value = optionalInt.or(0.5); // fine
   *
   * FluentIterable<? extends Number> numbers = getSomeNumbers();
   * Optional<Number> first = (Optional) numbers.first();
   * Number value = first.or(0.5); // fine
   * }</pre>

            BloomFilterStrategies.MURMUR128_MITZ_32);

    // Insert "numInsertions" even numbers into the BF.
    for (int i = 0; i < numInsertions * 2; i += 2) {
      bf.put(Integer.toString(i));
    }
    assertApproximateElementCountGuess(bf, numInsertions);

    // Assert that the BF "might" have all of the even numbers.
    for (int i = 0; i < numInsertions * 2; i += 2) {
      assertTrue(bf.mightContain(Integer.toString(i)));

            BloomFilterStrategies.MURMUR128_MITZ_32);

    // Insert "numInsertions" even numbers into the BF.
    for (int i = 0; i < numInsertions * 2; i += 2) {
      bf.put(Integer.toString(i));
    }
    assertApproximateElementCountGuess(bf, numInsertions);

    // Assert that the BF "might" have all of the even numbers.
    for (int i = 0; i < numInsertions * 2; i += 2) {
      assertTrue(bf.mightContain(Integer.toString(i)));

    BigInteger result = randomPositiveBigInteger(numBits);
    return RANDOM_SOURCE.nextBoolean() ? result : result.negate();
  }

  /**
   * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of
   * lower magnitude.
   */
  static BigInteger randomBigInteger(int numBits) {
    while (true) {
      if (RANDOM_SOURCE.nextBoolean()) {

    BigInteger result = randomPositiveBigInteger(numBits);
    return RANDOM_SOURCE.nextBoolean() ? result : result.negate();
  }

  /**
   * Chooses a number in (-2^numBits, 2^numBits) at random, with density concentrated in numbers of
   * lower magnitude.
   */
  static BigInteger randomBigInteger(int numBits) {
    while (true) {
      if (RANDOM_SOURCE.nextBoolean()) {

                        ),
                        "price": {"title": "Price", "type": "number"},
                        "tax": IsDict(
                            {
                                "title": "Tax",
                                "anyOf": [{"type": "number"}, {"type": "null"}],
                            }
                        )
                        | IsDict(

                        ),
                        "price": {"title": "Price", "type": "number"},
                        "tax": IsDict(
                            {
                                "title": "Tax",
                                "anyOf": [{"type": "number"}, {"type": "null"}],
                            }
                        )
                        | IsDict(

                        ),
                        "price": {"title": "Price", "type": "number"},
                        "tax": IsDict(
                            {
                                "title": "Tax",
                                "anyOf": [{"type": "number"}, {"type": "null"}],
                            }
                        )
                        | IsDict(

                        ),
                        "price": {"title": "Price", "type": "number"},
                        "tax": IsDict(
                            {
                                "title": "Tax",
                                "anyOf": [{"type": "number"}, {"type": "null"}],
                            }
                        )
                        | IsDict(

   * keys and values without rehashing.
   *
   * <p>This method will soon be deprecated in favor of {@code
   * MultimapBuilder.hashKeys(expectedKeys).hashSetValues(expectedValuesPerKey).build()}.
   *
   * @param expectedKeys the expected number of distinct keys
   * @param expectedValuesPerKey the expected average number of values per key