*/
    public ScaleAndIndex index(int index) {
      return new ScaleAndIndex(scale, index);
    }

    /**
     * Specifies multiple quantile indexes to be calculated, each index being the k in the kth
     * q-quantile.
     *
     * @param indexes the quantile indexes, each of which must be in the inclusive range [0, q] for

    assertThat(dataset).usingExactEquality().containsExactlyElementsIn(SIXTEEN_SQUARES_DOUBLES);
  }

  public void testQuartiles_indexes_varargs_compute_doubleCollection() {
    assertThat(quartiles().indexes(1, 3).compute(SIXTEEN_SQUARES_DOUBLES))
        .comparingValuesUsing(QUANTILE_CORRESPONDENCE)
        .containsExactly(1, SIXTEEN_SQUARES_QUARTILE_1, 3, SIXTEEN_SQUARES_QUARTILE_3);
  }

    assertThat(dataset).usingExactEquality().containsExactlyElementsIn(SIXTEEN_SQUARES_DOUBLES);
  }

  public void testQuartiles_indexes_varargs_compute_doubleCollection() {
    assertThat(quartiles().indexes(1, 3).compute(SIXTEEN_SQUARES_DOUBLES))
        .comparingValuesUsing(QUANTILE_CORRESPONDENCE)
        .containsExactly(1, SIXTEEN_SQUARES_QUARTILE_1, 3, SIXTEEN_SQUARES_QUARTILE_3);
  }

    }
  },
  ;

  /**
   * 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(

      Map<Integer, Double> quantiles = algorithm.multipleQuantiles(indexes, 100, dataset.clone());
      assertWithMessage("Wrong keys from " + 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 " + 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)

import com.google.common.collect.ImmutableSet;
import com.google.common.collect.Range;
import java.util.Random;

/** Benchmarks some algorithms providing the same functionality as {@link Quantiles}. */
public class QuantilesBenchmark {

  private static final ContiguousSet<Integer> ALL_DECILE_INDEXES =
      ContiguousSet.create(Range.closed(0, 10), DiscreteDomain.integers());

import com.google.common.collect.ImmutableSet;
import com.google.common.collect.Range;
import java.util.Random;

/** Benchmarks some algorithms providing the same functionality as {@link Quantiles}. */
public class QuantilesBenchmark {

  private static final ContiguousSet<Integer> ALL_DECILE_INDEXES =
      ContiguousSet.create(Range.closed(0, 10), DiscreteDomain.integers());

				}
			}
		}
	}

	var memstats runtime.MemStats
	runtime.ReadMemStats(&memstats)

	gcStats := debug.GCStats{
		// If stats.PauseQuantiles is non-empty, ReadGCStats fills
		// it with quantiles summarizing the distribution of pause time.
		// For example, if len(stats.PauseQuantiles) is 5, it will be
		// filled with the minimum, 25%, 50%, 75%, and maximum pause times.
		PauseQuantiles: make([]time.Duration, 5),
	}