Example usage for com.google.common.collect Multiset elementSet

Introduction

In this page you can find the example usage for com.google.common.collect Multiset elementSet.

Prototype

Set<E> elementSet();

Source Link

Document

Returns the set of distinct elements contained in this multiset.

Usage

From source file:nl.knaw.huygens.facetedsearch.AbstractSolrServer.java

private Map<String, Integer> getTermCountMap(Multiset<String> terms) {
    Map<String, Integer> termCountMap = Maps.newHashMap();
    for (String term : terms.elementSet()) {
        termCountMap.put(term, terms.count(term));
    }/*from ww w  .  j av  a  2 s . c o m*/
    return termCountMap;
}

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From source file:com.memonews.mahout.sentiment.SentimentModelHelper.java

Vector encodeFeatureVector(final File file, final Multiset<String> overallCounts) throws IOException {
    final Multiset<String> words = ConcurrentHashMultiset.create();

    final BufferedReader reader = Files.newReader(file, Charsets.UTF_8);
    try {/*from w ww .ja  va 2s  .  c om*/
        countWords(analyzer, words, reader, overallCounts);
    } finally {
        Closeables.closeQuietly(reader);
    }

    final Vector v = new RandomAccessSparseVector(FEATURES);
    bias.addToVector("", 1, v);
    for (final String word : words.elementSet()) {
        encoder.addToVector(word, Math.log1p(words.count(word)), v);
    }

    return v;
}

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From source file:org.dllearner.utilities.examples.AutomaticNegativeExampleFinderSPARQL2.java

private SortedSet<OWLIndividual> negativeExamplesBySiblingClasses(Multiset<OWLClass> positiveExamplesTypes,
        int cnt, int totalCnt) {
    logger.info("Applying sibling classes strategy...");
    SortedSet<OWLIndividual> negExamples = new TreeSet<>();

    // for each type of the positive examples
    for (OWLClass nc : positiveExamplesTypes.elementSet()) {
        int frequency = positiveExamplesTypes.count(nc);

        // get sibling classes
        Set<OWLClass> siblingClasses = sr.getSiblingClasses(nc);
        siblingClasses = filterByNamespace(siblingClasses);
        logger.info("Sibling classes: " + siblingClasses);

        int limit = (int) Math
                .ceil(((double) frequency / positiveExamplesTypes.size()) / siblingClasses.size() * cnt);

        // get instances for each sibling class
        for (OWLClass siblingClass : siblingClasses) {
            SortedSet<OWLIndividual> individuals = sr.getIndividualsExcluding(siblingClass, nc, totalCnt);
            individuals.removeAll(negExamples);
            SetManipulation.stableShrink(individuals, limit);
            negExamples.addAll(individuals);
        }// ww w. j  ava  2 s . c  o  m
    }
    negExamples = SetManipulation.stableShrink(negExamples, cnt);
    logger.info("Negative examples(" + negExamples.size() + "): " + negExamples);
    return negExamples;
}

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From source file:org.sonar.server.component.ws.ComponentAppAction.java

private void appendIssuesAggregation(JsonWriter json, RulesAggregation rulesAggregation,
        Multiset<String> severitiesAggregation) {
    json.name("severities").beginArray();
    for (String severity : severitiesAggregation.elementSet()) {
        json.beginArray().value(severity)
                .value(i18n.message(UserSession.get().locale(), "severity." + severity, null))
                .value(severitiesAggregation.count(severity)).endArray();
    }/*w ww .  j  a va 2 s . c  o m*/
    json.endArray();

    json.name("rules").beginArray();
    for (RulesAggregation.Rule rule : rulesAggregation.rules()) {
        json.beginArray().value(rule.ruleKey().toString()).value(rule.name())
                .value(rulesAggregation.countRule(rule)).endArray();
    }
    json.endArray();
}

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From source file:org.dllearner.utilities.examples.AutomaticNegativeExampleFinderSPARQL2.java

private SortedSet<OWLIndividual> negativeExamplesBySuperClasses(Multiset<OWLClass> positiveExamplesTypes,
        Set<OWLIndividual> negativeExamples, int cnt, int totalCnt) {
    logger.info("Applying super class strategy...");
    SortedSet<OWLIndividual> negExamples = new TreeSet<>();
    //for each type of the positive examples
    for (OWLClass nc : positiveExamplesTypes.elementSet()) {
        int frequency = positiveExamplesTypes.count(nc);
        //get super classes
        Set<OWLClassExpression> superClasses = sr.getSuperClasses(nc);
        superClasses.remove(df.getOWLThing());
        //               superClasses.remove(Thing.instance);
        superClasses.remove(df.getOWLClass(OWLRDFVocabulary.RDFS_RESOURCE.getIRI()));
        superClasses = filterByNamespace(superClasses);
        logger.info("Super classes: " + superClasses);

        int limit = (int) Math
                .ceil(((double) frequency / positiveExamplesTypes.size()) / superClasses.size() * cnt);
        //get instances for each super class
        for (OWLClassExpression superClass : superClasses) {
            SortedSet<OWLIndividual> individuals = sr.getIndividualsExcluding(superClass, nc, totalCnt);
            individuals.removeAll(negativeExamples);
            individuals.removeAll(negExamples);
            SetManipulation.stableShrink(individuals, limit);
            negExamples.addAll(individuals);
        }/*w  w w.  j av a  2 s. c o m*/
    }
    negExamples = SetManipulation.stableShrink(negExamples, cnt);
    logger.info("Negative examples(" + negExamples.size() + "): " + negExamples);
    return negExamples;
}

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From source file:org.splevo.jamopp.vpm.analyzer.programdependency.JaMoPPProgramDependencyVPMAnalyzer.java

private void printStatistics(Multiset<DependencyType> statistics) {
    StringBuilder builder = new StringBuilder();
    builder.append("Statistics:");
    for (DependencyType type : statistics.elementSet()) {
        builder.append("\n");
        builder.append(type + "\t" + statistics.count(type));
    }//from   w  ww. j  a va2s.co m
    logger.debug(builder.toString());
}

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From source file:bacter.model.ACGLikelihoodBeagle.java

/**
 * Set leaf partials in a Beagle instance
 *
 * @param beagle beagle instance object/*from  ww w .  j  a  va  2 s . c  o  m*/
 * @param patterns leaf state patterns
 */
protected void setPartials(Beagle beagle, Multiset<int[]> patterns) {
    for (Node node : acg.getExternalNodes()) {
        Alignment data = dataInput.get();
        int nStates = data.getDataType().getStateCount();
        double[] partials = new double[patterns.elementSet().size() * nStates * siteModel.getCategoryCount()];
        int k = 0;
        int iTaxon = alignment.getTaxonIndex(node.getID());
        for (int[] pattern : patterns.elementSet()) {
            int code = pattern[iTaxon];
            boolean[] stateSet = alignment.getDataType().getStateSet(code);
            for (int iState = 0; iState < nStates; iState++) {
                partials[k++] = (stateSet[iState] ? 1.0 : 0.0);
            }
        }

        int n = patterns.elementSet().size() * siteModel.getCategoryCount();
        for (int cIdx = 1; cIdx < siteModel.getCategoryCount(); cIdx++) {
            System.arraycopy(partials, 0, partials, n * cIdx, n);
        }

        beagle.setTipPartials(node.getNr(), partials);
    }
}

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From source file:bacter.model.ACGLikelihood.java

/**
 * Set leaf states in a likelihood core.
 * /*from   ww w.  j  ava2  s.  co m*/
 * @param lhc       likelihood core object
 * @param patterns  leaf state patterns
 */
void setStates(LikelihoodCore lhc, Multiset<int[]> patterns) {

    for (Node node : acg.getExternalNodes()) {
        int[] states = new int[patterns.size()];
        int taxon = alignment.getTaxonIndex(node.getID());
        int i = 0;
        for (int[] pattern : patterns.elementSet()) {
            int code = pattern[taxon];
            int[] statesForCode = alignment.getDataType().getStatesForCode(code);
            if (statesForCode.length == 1)
                states[i] = statesForCode[0];
            else
                states[i] = code; // Causes ambiguous states to be ignored.

            i += 1;
        }
        lhc.setNodeStates(node.getNr(), states);
    }
}

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From source file:bacter.model.ACGLikelihoodBeagle.java

/**
 * Set leaf states in a Beagle instance// w w w  . j av  a2s. co m
 * 
 * @param beagle beagle instance object
 * @param patterns leaf state patterns
 */
void setStates(Beagle beagle, Multiset<int[]> patterns) {

    for (Node node : acg.getExternalNodes()) {
        int[] states = new int[patterns.size()];
        int taxon = alignment.getTaxonIndex(node.getID());
        int i = 0;
        for (int[] pattern : patterns.elementSet()) {
            //                int code = pattern[taxon];
            //                int[] statesForCode = alignment.getDataType().getStatesForCode(code);
            //                if (statesForCode.length==1)
            //                    states[i] = statesForCode[0];
            //                else
            //                    states[i] = code; // Causes ambiguous states to be ignored.
            states[i] = pattern[taxon];

            i += 1;
        }
        beagle.setTipStates(node.getNr(), states);
    }
}

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From source file:net.shipilev.elections.cikrf.Parser.java

private void printSummaries(PrintWriter pw, String label, SummaryData data, List<String> key) {
    pw.printf("**** Summary for %s (aggregate over %s):\n", label, key.toString());
    Multiset<Metric> set = data.get(key);
    if (set == null || set.isEmpty()) {
        pw.println("No data.");
    } else {/*from  w  ww.j  a v a  2  s  . c o m*/
        for (Metric s : set.elementSet()) {
            pw.printf("%15d : %s\n", set.count(s), s.getLabel());
        }
    }
    pw.printf("\n");
    pw.flush();
}

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