assertTrue(rule.isTarget(1, 30, 1)); // 1:30 on Sunday (actually Monday morning)
        assertTrue(rule.isTarget(2, 0, 1)); // 2:00 on Sunday (actually Monday morning)

        // Outside range
        assertFalse(rule.isTarget(21, 59, 1)); // 21:59 on Sunday
        assertFalse(rule.isTarget(2, 1, 1)); // 2:01 on Sunday (actually Monday morning)
    }

    @Test
    public void test_intervalRule_isTarget_specificDays() {

   * #transform} methods all return {@link Double#NaN}. The {@link #inverse} method returns the same
   * instance.
   */
  public static LinearTransformation forNaN() {
    return NaNLinearTransformation.INSTANCE;
  }

  /** Returns whether this is a vertical transformation. */
  public abstract boolean isVertical();

   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link
   * Double#NEGATIVE_INFINITY}, or {@link Double#NaN}) then the result is {@link
   * LinearTransformation#forNaN()}.
   *
   * @throws IllegalStateException if the dataset is empty or contains a single pair of values, or
   *     both the {@code x} and {@code y} dataset have zero population variance
   */

   *
   * <p>If the dataset contains any non-finite values ({@link Double#POSITIVE_INFINITY}, {@link
   * Double#NEGATIVE_INFINITY}, or {@link Double#NaN}) then the result is {@link
   * LinearTransformation#forNaN()}.
   *
   * @throws IllegalStateException if the dataset is empty or contains a single pair of values, or
   *     both the {@code x} and {@code y} dataset must have zero population variance
   */

    assertThrows(IllegalArgumentException.class, () -> LinearTransformation.horizontal(Double.NaN));
  }

  public void testForNaN() {
    LinearTransformation transformation = LinearTransformation.forNaN();
    assertLinearTransformationNaN(transformation);
  }

    assertThrows(IllegalArgumentException.class, () -> LinearTransformation.horizontal(Double.NaN));
  }

  public void testForNaN() {
    LinearTransformation transformation = LinearTransformation.forNaN();
    assertLinearTransformationNaN(transformation);
  }

Since p = 1 mod 4, we can't use the exponentiation by (p + 1) / 4 like // for the other primes. Instead, implement a variation of Tonelli–Shanks. // The constant-time implementation is adapted from Thomas Pornin's ecGFp5. // // https://github.com/pornin/ecgfp5/blob/82325b965/rust/src/field.rs#L337-L385 // p = q*2^n + 1 with q odd -> q = 2^128 - 1 and n = 96 // g^(2^n) = 1 -> g = 11 ^ q (where 11 is the smallest non-square) // GG[j] = g^(2^j) for j = 0 to n-1 p224GGOnce.Do(func() { p224GG = new([...

    assertThat(transformation.inverse().inverse()).isSameInstanceAs(transformation);
  }

  /**
   * Asserts that {@code transformation} behaves as expected for {@link
   * LinearTransformation#forNaN}.
   */
  static void assertLinearTransformationNaN(LinearTransformation transformation) {
    assertThat(transformation.isHorizontal()).isFalse();
    assertThat(transformation.isVertical()).isFalse();

    assertThat(transformation.inverse().inverse()).isSameInstanceAs(transformation);
  }

  /**
   * Asserts that {@code transformation} behaves as expected for {@link
   * LinearTransformation#forNaN}.
   */
  static void assertLinearTransformationNaN(LinearTransformation transformation) {
    assertThat(transformation.isHorizontal()).isFalse();
    assertThat(transformation.isVertical()).isFalse();

Since p = 1 mod 4, we can't use the exponentiation by (p + 1) / 4 like // for the other primes. Instead, implement a variation of Tonelli–Shanks. // The constant-time implementation is adapted from Thomas Pornin's ecGFp5. // // https://github.com/pornin/ecgfp5/blob/82325b965/rust/src/field.rs#L337-L385 // p = q*2^n + 1 with q odd -> q = 2^128 - 1 and n = 96 // g^(2^n) = 1 -> g = 11 ^ q (where 11 is the smallest non-square) // GG[j] = g^(2^j) for j = 0 to n-1 p224GGOnce.Do(func() { p224GG = new([...