Example usage for java.util.stream Collectors groupingBy

List of usage examples for java.util.stream Collectors groupingBy

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Introduction

In this page you can find the example usage for java.util.stream Collectors groupingBy.

Prototype

public static <T, K> Collector<T, ?, Map<K, List<T>>> groupingBy(Function<? super T, ? extends K> classifier)

Source Link

Document

Returns a Collector implementing a "group by" operation on input elements of type T , grouping elements according to a classification function, and returning the results in a Map .

Usage

From source file:org.obiba.mica.dataset.rest.entity.StudyEntitiesCountService.java

/**
 * Parse the RQL query and translate each node as a Opal query wrapped in a {@link StudyEntitiesCountQuery}.
 *
 * @param query// w w w  .  j av a2s.c  o  m
 * @param entityType
 * @return
 */
public List<StudyEntitiesCountQuery> newQueries(String query, String entityType) {
    RQLCriteriaOpalConverter converter = applicationContext.getBean(RQLCriteriaOpalConverter.class);
    converter.parse(query);
    Map<BaseStudy, List<RQLCriterionOpalConverter>> studyConverters = converter.getCriterionConverters()
            .stream().filter(c -> !c.hasMultipleStudyTables()) // TODO include Dataschema variables
            .collect(Collectors.groupingBy(c -> c.getVariableReferences().getStudy()));

    return studyConverters.keySet().stream()
            .map(study -> newQuery(entityType, study, studyConverters.get(study))).collect(Collectors.toList());
}

From source file:de.wpsverlinden.dupfind.DupeFinder.java

public Collection<List<FileEntry>> getDupeEntries() {
    Map<String, List<FileEntry>> dupeMap = fileIndex.values().parallelStream()
            .collect(Collectors.groupingBy((e) -> e.getSize() + "-" + e.getHash()));
    return dupeMap.values();
}

From source file:edu.washington.gs.skyline.model.quantification.GroupComparisonDataSet.java

public LinearFitResult calculateFoldChange(String label) {
    List<Replicate> replicates = removeIncompleteReplicates(label, this.replicates);
    if (replicates.size() == 0) {
        return null;
    }//  w  w  w .j a  v a2 s .  c o m
    List<Replicate> summarizedRows;
    if (replicates.stream().anyMatch(row -> null != row.getBioReplicate())) {
        Map<Pair<Boolean, Object>, List<Replicate>> groupedByBioReplicate = replicates.stream().collect(
                Collectors.groupingBy(replicate -> Pair.of(replicate.isControl(), replicate.bioReplicate)));
        summarizedRows = new ArrayList<>();
        for (Map.Entry<Pair<Boolean, Object>, List<Replicate>> entry : groupedByBioReplicate.entrySet()) {
            Double log2Abundance = calculateMean(entry.getValue().stream()
                    .map(replicateData -> replicateData.getLog2Abundance(label)).collect(Collectors.toList()));
            if (log2Abundance == null) {
                continue;
            }
            Replicate combinedReplicate = new Replicate(entry.getKey().getLeft(), entry.getKey().getValue());
            ResultFileData resultFileData = combinedReplicate.ensureResultFileData();
            resultFileData.setTransitionAreas(label,
                    TransitionAreas.fromMap(Collections.singletonMap("", Math.pow(2.0, log2Abundance))));
            if (getNormalizationMethod() instanceof NormalizationMethod.RatioToLabel) {
                TransitionAreas denominator = TransitionAreas.fromMap(Collections.singletonMap("", 1.0));
                resultFileData.setTransitionAreas(
                        ((NormalizationMethod.RatioToLabel) getNormalizationMethod()).getIsotopeLabelTypeName(),
                        denominator);
            }
            summarizedRows.add(combinedReplicate);
        }
    } else {
        summarizedRows = replicates;
    }

    List<Double> abundances = summarizedRows.stream()
            .map(replicateData -> replicateData.getLog2Abundance(label)).collect(Collectors.toList());
    List<Integer> features = Collections.nCopies(summarizedRows.size(), 0);
    List<Integer> runs = IntStream.range(0, summarizedRows.size()).boxed().collect(Collectors.toList());
    List<Integer> subjects = IntStream.range(0, summarizedRows.size()).boxed().collect(Collectors.toList());
    List<Boolean> subjectControls = summarizedRows.stream().map(Replicate::isControl)
            .collect(Collectors.toList());
    FoldChangeDataSet foldChangeDataSet = new FoldChangeDataSet(abundances, features, runs, subjects,
            subjectControls);
    DesignMatrix designMatrix = DesignMatrix.getDesignMatrix(foldChangeDataSet, false);
    LinearFitResult linearFitResult = designMatrix.performLinearFit().get(0);
    return linearFitResult;
}

From source file:ch.wisv.areafiftylan.seats.service.SeatServiceImpl.java

@Override
public SeatmapResponse getAllSeats() {
    List<Seat> all = seatRepository.findAll();

    Map<String, List<Seat>> seatMapGroups = all.stream().collect(Collectors.groupingBy(Seat::getSeatGroup));

    return new SeatmapResponse(seatMapGroups);
}

From source file:tds.assessment.services.impl.AssessmentWindowServiceImpl.java

@Override
@Cacheable(CacheType.LONG_TERM)// w  ww  .j a  v  a2  s . c  o  m
public Map<String, List<AssessmentWindow>> findAssessmentWindowsForAssessmentIds(final String clientName,
        final String... assessmentIds) {
    List<AssessmentWindow> assessmentWindows = assessmentWindowQueryRepository
            .findAssessmentWindowsForAssessmentIds(clientName, assessmentIds);
    return assessmentWindows.stream().collect(Collectors.groupingBy(AssessmentWindow::getAssessmentKey));
}

From source file:com.pscnlab.train.services.impls.TrainPeopleServiceImpl.java

@Override
public Map<Integer, List<TrainPeople>> findMapByTrainIds(List<Integer> es) {
    List<TrainPeople> trainPeoples = this.findListByTrainIds(es);
    if (CollectionUtils.isEmpty(trainPeoples)) {
        return Collections.EMPTY_MAP;
    }//w ww  . j av a2 s  . co  m
    return trainPeoples.stream().collect(Collectors.groupingBy(TrainPeople::getUuidTrain));
}

From source file:br.com.Summoner.core.base.cartas.monk.MonkCard.java

public static void GeraEstatisca(StringBuilder strbOut) {

    strbOut.append("\r\n");
    strbOut.append("\r\n");
    strbOut.append(" Estatsticas de Combo Humano ");
    strbOut.append("\r\n");
    strbOut.append("\r\n");

    Comparator<MonkComboResult> byCombo = (e1, e2) -> e2.ComboCriatura.compareTo(e1.ComboCriatura);
    CombosRealizados = CombosRealizados.stream()
            .filter(c -> c.ComboCriatura != null && c.ComboCriatura.length() > 1).sorted(byCombo)
            .collect(Collectors.toList());

    Map<String, List<MonkComboResult>> combosRealizados;
    combosRealizados = CombosRealizados.stream()
            .collect(Collectors.groupingBy(classifier -> classifier.ComboCriatura));

    for (Map.Entry<String, List<MonkComboResult>> entry : combosRealizados.entrySet()) {
        strbOut.append(" Combo Realizado:\t").append(entry.getKey()).append("\tQuantidade:\t")
                .append(entry.getValue().size()).append("\r\n");
    }// www. ja v  a  2  s  .  c om

    //        for (MonkComboResult comboResult : CombosRealizados) {
    //
    //            if (comboResult.ComboRealizado.length() > 1) {
    //                strbOut.append(" Combo Realizado - ").append(comboResult.ComboRealizado).append("\r\n");
    //                strbOut.append(" Combo Utilizado - ").append(comboResult.ComboCartaUtilizado == null ? "" : comboResult.ComboCartaUtilizado).append("\r\n");
    //                strbOut.append("\r\n");
    //            }
    //            for (MonkMonsterCombo combo : comboResult.CombosCarta)
    //            {
    //                strbOut.append(" Combo - ").append(combo.CombinacaoCombo);
    //                strbOut.append("\r\n");
    //            }
    //            strbOut.append("\r\n");
    //            strbOut.append("\r\n");
    //        }
    strbOut.append("\r\n");
    strbOut.append("\r\n");

}

From source file:edu.brandeis.wisedb.scheduler.experiments.SkewDistributionExperiment.java

public static void calculateBurn(int samples) throws Exception {
    TightenableSLA sla = PercentSLA.nintyTenSLA();
    //TightenableSLA sla = new SimpleLatencyModelSLA(9 * 60 * 1000, 1);
    //TightenableSLA sla = PerQuerySLA.getLatencyTimesN(2.0);
    //TightenableSLA sla = new AverageLatencyModelSLA(7 * 60 * 1000, 1);
    QueryTimePredictor qtp = new QueryTimePredictor();

    File f = new File("distSkew.csv");
    if (f.exists())
        f.delete();// w  ww.ja  v a 2s. c  o m

    try (Trainer t = new Trainer("distSkew.csv", sla)) {
        t.train(2000, 12);
    }

    DTSearcher dt = new DTSearcher("distSkew.csv", qtp, sla);
    AStarGraphSearch astar = new AStarGraphSearch(new UnassignedQueryTimeHeuristic(qtp), sla, qtp);
    //FirstFitDecreasingGraphSearch astar = new FirstFitDecreasingGraphSearch(sla, qtp);

    ChiSquareTest cst = new ChiSquareTest();
    ChiSquaredDistribution cqd = new ChiSquaredDistribution(qtp.QUERY_TYPES.length - 1);
    double[] expceted = Arrays.stream(qtp.QUERY_TYPES).mapToDouble(i -> 20.0 / (qtp.QUERY_TYPES.length))
            .toArray();

    System.out.println("Chi\tDT\tOpt");

    for (int i = 0; i < samples; i++) {
        Set<ModelQuery> smp = ModelWorkloadGenerator.randomQueries(20);

        // reject samples that don't have at least one of each query type
        long repr = smp.stream().mapToInt(q -> q.getType()).distinct().count();
        if (repr != qtp.QUERY_TYPES.length) {
            i--;
            continue;
        }

        Map<Integer, List<ModelQuery>> groups = smp.stream().collect(Collectors.groupingBy(q -> q.getType()));

        long obs[] = Arrays.stream(qtp.QUERY_TYPES).mapToLong(v -> groups.get(v).size()).toArray();

        double chi = cst.chiSquare(expceted, obs);
        chi = cqd.cumulativeProbability(chi);

        Cost dtCost = dt.getCostForQueries(smp, sla);
        Cost optCost = astar.getCostForQueries(smp, sla);

        System.out.println(chi + "\t" + dtCost.getTotalCost() + "\t" + optCost.getTotalCost());
    }

}

From source file:org.wallerlab.yoink.density.service.density.DensityVectorBasedCalculator.java

/**
 * calculate the density of a point from molecules
 * /*  ww w  . ja  va 2s.c  om*/
 * @param currentCoord
 *            -{@link org.wallerlab.yoink.api.model.molecular.Coord}
 * @param molecules
 *            -a Set of molecules
 *            {@link org.wallerlab.yoink.api.model.molecular.Molecule}
 * @return the density of a point from molecules
 */
public Double calculate(Coord currentCoord, Set<Molecule> molecules) {
    // long starting = System.currentTimeMillis();
    // get all atoms
    List<Atom> atoms = new ArrayList<Atom>();
    for (Molecule molecule : molecules) {
        atoms.addAll(molecule.getAtoms());
    }
    // group atoms by element type
    Map<Element, List<Atom>> atomMap = atoms.stream()
            .collect(Collectors.groupingBy(atom -> atom.getElementType()));
    double density = loopOverEveryElement(currentCoord, atomMap);
    // if the density is too small, zero or close to zero, take the default
    // density value.
    density = Math.max(density, Constants.DENSITY_DEFAULT);
    // System.out.println("starting to ending (millseconds): "
    // + (System.currentTimeMillis() - starting));
    return density;
}

From source file:org.ng200.openolympus.services.ContestService.java

public Instant getContestEndIncludingAllTimeExtensions(final Contest contest) {
    return contest.getStartTime().toInstant().plusMillis(contest.getDuration())
            .plusMillis(this.contestTimeExtensionRepository.findByContest(contest).stream()
                    .collect(Collectors.groupingBy(timeExtension -> timeExtension.getContest())).values()
                    .stream()//ww  w  . j ava2s  .  c  o  m
                    .map(group -> group.stream().map(timeExtension -> timeExtension.getDuration())
                            .reduce((l, r) -> l + r))
                    .max((l, r) -> l.orElse(0l).compareTo(r.orElse(0l))).orElse(Optional.of(0l)).orElse(0l));
}