/** Specifies the computation of quartiles (i.e. 4-quantiles). */
  public static Scale quartiles() {
    return scale(4);
  }

  /** Specifies the computation of percentiles (i.e. 100-quantiles). */
  public static Scale percentiles() {
    return scale(100);
  }

  /**
   * Specifies the computation of q-quantiles.
   *

    }
  },
  ;

  /**
   * Calculates a single quantile. Equivalent to {@code
   * Quantiles.scale(scale).index(index).computeInPlace(dataset)}.
   */
  abstract double singleQuantile(int index, int scale, double[] dataset);

  /**
   * Calculates multiple quantiles. Equivalent to {@code
   * Quantiles.scale(scale).indexes(indexes).computeInPlace(dataset)}.
   */
  abstract Map<Integer, Double> multipleQuantiles(

    }
  },
  ;

  /**
   * Calculates a single quantile. Equivalent to {@code
   * Quantiles.scale(scale).index(index).computeInPlace(dataset)}.
   */
  abstract double singleQuantile(int index, int scale, double[] dataset);

  /**
   * Calculates multiple quantiles. Equivalent to {@code
   * Quantiles.scale(scale).indexes(indexes).computeInPlace(dataset)}.
   */
  abstract Map<Integer, Double> multipleQuantiles(

  public void testScale_zero() {
    assertThrows(IllegalArgumentException.class, () -> Quantiles.scale(0));
  }

  public void testScale_negative() {
    assertThrows(IllegalArgumentException.class, () -> Quantiles.scale(-4));
  }

  public void testScale_index_negative() {
    Quantiles.Scale intermediate = Quantiles.scale(10);
    assertThrows(IllegalArgumentException.class, () -> intermediate.index(-1));
  }

  public void testScale_zero() {
    assertThrows(IllegalArgumentException.class, () -> Quantiles.scale(0));
  }

  public void testScale_negative() {
    assertThrows(IllegalArgumentException.class, () -> Quantiles.scale(-4));
  }

  public void testScale_index_negative() {
    Quantiles.Scale intermediate = Quantiles.scale(10);
    assertThrows(IllegalArgumentException.class, () -> intermediate.index(-1));
  }

      Map<Integer, Double> quantiles = algorithm.multipleQuantiles(indexes, 100, dataset.clone());
      assertWithMessage("Wrong keys from %s", algorithm)
          .that(quantiles.keySet())
          .isEqualTo(indexes);
      for (int i : indexes) {
        assertWithMessage("Mismatch between %s and %s at %s", algorithm, REFERENCE_ALGORITHM, i)
            .that(quantiles.get(i))
            .isWithin(ALLOWED_ERROR)

      Map<Integer, Double> quantiles = algorithm.multipleQuantiles(indexes, 100, dataset.clone());
      assertWithMessage("Wrong keys from %s", algorithm)
          .that(quantiles.keySet())
          .isEqualTo(indexes);
      for (int i : indexes) {
        assertWithMessage("Mismatch between %s and %s at %s", algorithm, REFERENCE_ALGORITHM, i)
            .that(quantiles.get(i))
            .isWithin(ALLOWED_ERROR)

    *   `tf.einsum()`raises `ValueError` for unsupported equations like
        `"ii->"`.
    *   Add DCT-I and IDCT-I in `tf.signal.dct` and `tf.signal.idct`.
    *   Add LU decomposition op.
    *   Add quantile loss to gradient boosted trees in estimator.
    *   Add `round_mode` to `QuantizeAndDequantizeV2` op to select rounding
        algorithm.
    *   Add `unicode_encode`, `unicode_decode`, `unicode_decode_with_offsets`,