List<String> docIds = Arrays.asList("doc1", "doc2", "doc3");
        List<Integer> indexes = Arrays.asList(1, 2, 3);
        RelevanceEvaluationResult result = RelevanceEvaluationResult.withRelevantDocs(docIds, indexes);

        assertTrue(result.isHasRelevantResults());
        assertEquals(docIds, result.getRelevantDocIds());
        assertEquals(indexes, result.getRelevantIndexes());
    }

    @Test

    ImmutableSet<Integer> indexes = ImmutableSet.of(50, 90, 99);
    Map<Integer, Double> referenceQuantiles =
        REFERENCE_ALGORITHM.multipleQuantiles(indexes, 100, dataset.clone());
    assertThat(referenceQuantiles.keySet()).isEqualTo(indexes);
    for (QuantilesAlgorithm algorithm : NON_REFERENCE_ALGORITHMS) {
      Map<Integer, Double> quantiles = algorithm.multipleQuantiles(indexes, 100, dataset.clone());

     * @param indexes the quantile indexes, each of which must be in the inclusive range [0, q] for
     *     q-quantiles; the order of the indexes is unimportant, duplicates will be ignored, and the
     *     set will be snapshotted when this method is called
     * @throws IllegalArgumentException if {@code indexes} is empty
     */
    public ScaleAndIndexes indexes(int... indexes) {
      return new ScaleAndIndexes(scale, indexes.clone());
    }

  TARGET {

    @Override
    double singleQuantile(int index, int scale, double[] dataset) {
      return Quantiles.scale(scale).index(index).computeInPlace(dataset);
    }

    @Override
    Map<Integer, Double> multipleQuantiles(
        Collection<Integer> indexes, int scale, double[] dataset) {
      return Quantiles.scale(scale).indexes(indexes).computeInPlace(dataset);
    }
  },
  ;

  /**

    ImmutableSet<Integer> indexes = ImmutableSet.of(50, 90, 99);
    Map<Integer, Double> referenceQuantiles =
        REFERENCE_ALGORITHM.multipleQuantiles(indexes, 100, dataset.clone());
    assertThat(referenceQuantiles.keySet()).isEqualTo(indexes);
    for (QuantilesAlgorithm algorithm : NON_REFERENCE_ALGORITHMS) {
      Map<Integer, Double> quantiles = algorithm.multipleQuantiles(indexes, 100, dataset.clone());

	}
	return indexes
}

func (schema *Schema) LookIndex(name string) *Index {
	if schema != nil {
		indexes := schema.ParseIndexes()
		for _, index := range indexes {
			if index.Name == name {
				return index
			}

			for _, field := range index.Fields {
				if field.Name == name {
					return index
				}
			}
		}
	}

	return nil
}

func parseFieldIndexes(field *Field) (indexes []Index, err error) {

    for (int index = 0; index <= 100; index++) {
      indexes.add(index);
      expectedBuilder.put(index, expectedLargeDatasetPercentile(index));
    }
    Random random = new Random(770683168895677741L);
    Collections.shuffle(indexes, random);
    assertThat(percentiles().indexes(Ints.toArray(indexes)).computeInPlace(dataset))
        .comparingValuesUsing(QUANTILE_CORRESPONDENCE)

    for (int index = 0; index <= 100; index++) {
      indexes.add(index);
      expectedBuilder.put(index, expectedLargeDatasetPercentile(index));
    }
    Random random = new Random(770683168895677741L);
    Collections.shuffle(indexes, random);
    assertThat(percentiles().indexes(Ints.toArray(indexes)).computeInPlace(dataset))
        .comparingValuesUsing(QUANTILE_CORRESPONDENCE)

  TARGET {

    @Override
    double singleQuantile(int index, int scale, double[] dataset) {
      return Quantiles.scale(scale).index(index).computeInPlace(dataset);
    }

    @Override
    Map<Integer, Double> multipleQuantiles(
        Collection<Integer> indexes, int scale, double[] dataset) {
      return Quantiles.scale(scale).indexes(indexes).computeInPlace(dataset);
    }
  },
  ;

  /**

                logger.debug("Failed to index from documents: index={}, documentCount={}", index, documents.length, e);
            }
            throw new SuggestIndexException("Failed to index from documents: index=" + index + ", documentCount=" + documents.length, e);
        }
    }

    /**
     * Indexes documents from an array of maps.
     *
     * @param index The index name