assertEquals("00", Hexdump.toHexString(data1, 0, 2)); // 2 chars = 1 byte
        assertEquals("000", Hexdump.toHexString(data1, 0, 3)); // 3 chars = 1.5 bytes (rounds up to 2)
        assertEquals("0001", Hexdump.toHexString(data1, 0, 4)); // 4 chars = 2 bytes
        assertEquals("000102", Hexdump.toHexString(data1, 0, 6)); // 6 chars = 3 bytes
        assertEquals("00010203", Hexdump.toHexString(data1, 0, 8)); // 8 chars = 4 bytes

-rw-rw-rw-   1 spark spark       4956 2019-05-04 01:36 s3a://testbucket/wordcount/part-00000
-rw-rw-rw-   1 spark spark       5616 2019-05-04 01:36 s3a://testbucket/wordcount/part-00001

none;\n}\n\n.toast {\n  -ms-flex-preferred-size: 350px;\n  flex-basis: 350px;\n  max-width: 350px;\n  font-size: 0.875rem;\n  background-color: rgba(255, 255, 255, 0.85);\n  background-clip: padding-box;\n  border: 1px solid rgba(0, 0, 0, 0.1);\n  box-shadow: 0 0.25rem 0.75rem rgba(0, 0, 0, 0.1);\n  opacity: 0;\n  border-radius: 0.25rem;\n}\n\n.toast:not(:last-child) {\n  margin-bottom: 0.75rem;\n}\n\n.toast.showing {\n  opacity: 1;\n}\n\n.toast.show {\n  display: block;\n  opacity: 1;\n}\n\n.toast.hide {\n ...

  }

  /** Tests that we always get a non-negative optimal size. */
  public void testOptimalSize() {
    for (int n = 1; n < 1000; n++) {
      for (double fpp = Double.MIN_VALUE; fpp < 1.0; fpp += 0.001) {
        assertTrue(BloomFilter.optimalNumOfBits(n, fpp) >= 0);
      }
    }

    // some random values
    Random random = new Random(0);
    for (int repeats = 0; repeats < 10000; repeats++) {

          Doubles.asList(
              -Double.MIN_VALUE,
              -Double.MIN_NORMAL,
              -1,
              -20,
              Double.NaN,
              Double.NEGATIVE_INFINITY,
              -0.001));

  public void testFuzzyEqualsFinite() {
    for (double a : FINITE_DOUBLE_CANDIDATES) {
      for (double b : FINITE_DOUBLE_CANDIDATES) {
        for (double tolerance : FINITE_TOLERANCE_CANDIDATES) {

    assertThat(Doubles.constrainToRange(1.0, 1.0, 5.0)).isEqualTo(1.0);
    assertThat(Doubles.constrainToRange(1.0, 3.0, 5.0)).isEqualTo(3.0);
    assertThat(Doubles.constrainToRange(0.0, -5.0, -1.0)).isEqualTo(-1.0);
    assertThat(Doubles.constrainToRange(5.0, 2.0, 2.0)).isEqualTo(2.0);
    assertThrows(IllegalArgumentException.class, () -> Doubles.constrainToRange(1.0, 3.0, 2.0));
  }

 *   <dt>An IPv6 "IPv4 compatible" (or "compat") address, {@code "::192.168.0.1"}.
 *   <dd>{@code 00 00 00 00 00 00 00 00 00 00 00 00 c0 a8 00 01}
 *   <dt>An IPv6 "IPv4 mapped" address, {@code "::ffff:192.168.0.1"}.
 *   <dd>{@code 00 00 00 00 00 00 00 00 00 00 ff ff c0 a8 00 01}
 * </dl>
 *
 * <p>A few notes about IPv6 "IPv4 mapped" addresses and their observed use in Java.
 *

  }

  /**
   * Maximum allowed false positive probability of detecting a hash flooding attack given random
   * input.
   */
  @VisibleForTesting(
      )
  static final double HASH_FLOODING_FPP = 0.001;

  /**
   * Maximum allowed length of a hash table bucket before falling back to a j.u.LinkedHashSet based
   * implementation. Experimentally determined.
   */
  private static final int MAX_HASH_BUCKET_LENGTH = 9;

        public int hunds;
        /**
         * The time zone offset from UTC in minutes.
         */
        public int timezone;
        /**
         * The time interval for each tick of the clock in 0.0001 seconds.
         */
        public int tinterval;
        /**
         * The current day of the month (1-31).
         */
        public int day;
        /**
         * The current month (1-12).

  }

  /** Tests that we always get a non-negative optimal size. */
  public void testOptimalSize() {
    for (int n = 1; n < 1000; n++) {
      for (double fpp = Double.MIN_VALUE; fpp < 1.0; fpp += 0.001) {
        assertTrue(BloomFilter.optimalNumOfBits(n, fpp) >= 0);
      }
    }

    // some random values
    Random random = new Random(0);
    for (int repeats = 0; repeats < 10000; repeats++) {