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

Introduction

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

Prototype

Set<Entry<E>> entrySet();

Source Link

Document

Returns a view of the contents of this multiset, grouped into Multiset.Entry instances, each providing an element of the multiset and the count of that element.

Usage

From source file:com.cloudera.oryx.rdf.common.rule.NumericDecision.java

static List<Decision> numericDecisionsFromExamples(int featureNumber, Iterable<Example> examples,
        int suggestedMaxSplitCandidates) {
    Multiset<Float> sortedFeatureValueCounts = TreeMultiset.create();
    StorelessUnivariateStatistic mean = new Mean();
    int numExamples = 0;
    for (Example example : examples) {
        NumericFeature feature = (NumericFeature) example.getFeature(featureNumber);
        if (feature == null) {
            continue;
        }//from ww w  . j a  v  a 2s .  c  o  m
        numExamples++;
        float value = feature.getValue();
        sortedFeatureValueCounts.add(value, 1);
        mean.increment(value);
    }

    // Make decisions from split points that divide up input into roughly equal amounts of examples
    List<Decision> decisions = Lists.newArrayListWithExpectedSize(suggestedMaxSplitCandidates);
    int approxExamplesPerSplit = FastMath.max(1, numExamples / suggestedMaxSplitCandidates);
    int examplesInSplit = 0;
    float lastValue = Float.NaN;
    // This will iterate in order of value by nature of TreeMap
    for (Multiset.Entry<Float> entry : sortedFeatureValueCounts.entrySet()) {
        float value = entry.getElement();
        if (examplesInSplit >= approxExamplesPerSplit) {
            decisions.add(
                    new NumericDecision(featureNumber, (value + lastValue) / 2.0f, (float) mean.getResult()));
            examplesInSplit = 0;
        }
        examplesInSplit += entry.getCount();
        lastValue = value;
    }

    // The vital condition here is that if decision n decides an example is positive, then all subsequent
    // decisions in the list will also find it positive. So we need to order from highest threshold to lowest
    Collections.reverse(decisions);
    return decisions;
}

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From source file:com.textocat.textokit.commons.wfstore.DefaultWordformStoreBuilder.java

@Override
public DefaultWordformStore<TagType> build() {
    DefaultWordformStore<TagType> result = new DefaultWordformStore<TagType>();
    result.strKeyMap = Maps.newHashMapWithExpectedSize(strKeyMap.size());
    for (String wf : strKeyMap.keySet()) {
        Multiset<TagType> tagBag = strKeyMap.get(wf);
        int max = 0;
        TagType maxTag = null;// w ww  .j a va2s.co  m
        for (Multiset.Entry<TagType> tagEntry : tagBag.entrySet()) {
            if (tagEntry.getCount() > max) {
                max = tagEntry.getCount();
                maxTag = tagEntry.getElement();
            }
        }
        if (maxTag == null) {
            throw new IllegalStateException();
        }
        result.strKeyMap.put(wf, maxTag);
    }
    return result;
}

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From source file:org.lightjason.agentspeak.action.buildin.collection.list.CSymmetricDifference.java

@Override
public final IFuzzyValue<Boolean> execute(final IContext p_context, final boolean p_parallel,
        final List<ITerm> p_argument, final List<ITerm> p_return, final List<ITerm> p_annotation) {
    // create a multiset and counts the occurence of element -> on an odd number the element will be returned
    final Multiset<?> l_count = ConcurrentHashMultiset.create();
    CCommon.flatcollection(p_argument).parallel().forEach(i -> l_count.add(i.raw()));
    final List<?> l_result = l_count.entrySet().parallelStream().filter(i -> i.getCount() % 2 == 1)
            .collect(Collectors.toList());

    p_return.add(CRawTerm.from(p_parallel ? Collections.synchronizedList(l_result) : l_result));

    return CFuzzyValue.from(true);
}

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From source file:org.lightjason.agentspeak.action.builtin.collection.list.CSymmetricDifference.java

@Nonnull
@Override//from   ww  w.  ja v a  2 s . co m
public final IFuzzyValue<Boolean> execute(final boolean p_parallel, @Nonnull final IContext p_context,
        @Nonnull final List<ITerm> p_argument, @Nonnull final List<ITerm> p_return) {
    // create a multiset and counts the occurence of element -> on an odd number the element will be returned
    final Multiset<Object> l_count = ConcurrentHashMultiset.create();
    CCommon.flatten(p_argument).parallel().map(ITerm::raw).forEach(l_count::add);
    final List<Object> l_result = l_count.entrySet().parallelStream().filter(i -> i.getCount() % 2 == 1)
            .map(Multiset.Entry::getElement).collect(Collectors.toList());
    l_result.sort(Comparator.comparing(Object::hashCode));

    p_return.add(CRawTerm.from(p_parallel ? Collections.synchronizedList(l_result) : l_result));

    return CFuzzyValue.from(true);
}

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From source file:org.mule.runtime.extension.api.model.AbstractComplexModel.java

/**
 * Returns an immutable copy of the {@code values} collection, validating
 * that no items exist such that its name is repeated
 *
 * @param values     the collection to copy
 * @param identifier human friendly identifier of the {@code values} content
 * @param <T>        the generic type of the {@code values} items
 * @return an immutable copy of the {@code values}
 *///  w w  w.jav a 2  s.c o  m
protected <T extends NamedObject> List<T> unique(Collection<T> values, String identifier) {
    Multiset<String> names = HashMultiset.create();
    values.stream().map(NamedObject::getName).forEach(names::add);

    List<String> invalid = names.entrySet().stream().filter(entry -> entry.getCount() > 1)
            .map(Multiset.Entry::getElement).collect(Collectors.toList());

    if (!invalid.isEmpty()) {
        throw new IllegalModelDefinitionException(
                format("%s %s were defined multiple times", identifier, invalid));
    }

    return copyOf(values);
}

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From source file:edu.uw.cs.lil.tiny.parser.ccg.factoredlex.features.scorers.LexemeCooccurrenceScorer.java

private double score(List<String> tokens, Multiset<LogicalConstant> constants) {
    double totalScore = 0.0;
    int numConstants = 0;
    for (final Entry<LogicalConstant> entry : constants.entrySet()) {
        if (!LogicLanguageServices.isCoordinationPredicate(entry.getElement())) {
            numConstants += entry.getCount();
            for (final String word : tokens) {
                totalScore += indexScore(word, entry.getElement().getName()) * entry.getCount();
            }/*from  ww  w.j a v a2  s .  c o  m*/
        }
    }

    return totalScore / (tokens.size() * (numConstants + 1));
}

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From source file:com.b2international.snowowl.snomed.reasoner.server.diff.SourceConceptNamespaceAndModuleAssigner.java

@Override
public void allocateRelationshipIdsAndModules(Multiset<String> conceptIds,
        final SnomedEditingContext editingContext) {
    Multiset<String> reservedIdsByNamespace = HashMultiset.create();
    for (Multiset.Entry<String> conceptIdWithCount : conceptIds.entrySet()) {
        String namespace = SnomedIdentifiers.getNamespace(conceptIdWithCount.getElement());
        reservedIdsByNamespace.add(namespace, conceptIdWithCount.getCount());
    }/*from  w w  w .  ja  va  2s.c  o  m*/

    ISnomedIdentifierService identifierService = getServiceForClass(ISnomedIdentifierService.class);
    for (Multiset.Entry<String> namespaceWithCount : reservedIdsByNamespace.entrySet()) {
        Collection<String> reservedIds = identifierService.reserve(namespaceWithCount.getElement(),
                ComponentCategory.RELATIONSHIP, namespaceWithCount.getCount());
        this.reservedIds.addAll(reservedIds);
        namespaceToRelationshipIdMap.put(namespaceWithCount.getElement(), reservedIds.iterator());
    }

    for (String conceptId : conceptIds.elementSet()) {
        Concept concept = editingContext.lookup(conceptId, Concept.class);
        conceptIdToRelationshipModuleMap.put(conceptId, concept.getModule());
    }
}

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From source file:edu.cmu.lti.oaqa.baseqa.providers.ml.classifiers.WekaProvider.java

@Override
public void train(List<Map<String, Double>> X, List<String> Y, boolean crossValidation)
        throws AnalysisEngineProcessException {
    // create attribute (including label) info
    ArrayList<Attribute> attributes = new ArrayList<>();
    ClassifierProvider.featureNames(X).stream().map(Attribute::new).forEachOrdered(attributes::add);
    Attribute label = new Attribute("__label__", ClassifierProvider.labelNames(Y));
    attributes.add(label);//  w ww  .  j  av  a  2 s .  co  m
    String name = Files.getNameWithoutExtension(modelFile.getName());
    datasetSchema = new Instances(name, attributes, X.size());
    datasetSchema.setClass(label);
    // add instances
    Instances trainingInstances = new Instances(datasetSchema, X.size());
    if (balanceWeight) {
        Multiset<String> labelCounts = HashMultiset.create(Y);
        double maxCount = labelCounts.entrySet().stream().mapToInt(Multiset.Entry::getCount).max()
                .orElseThrow(AnalysisEngineProcessException::new);
        for (int i = 0; i < X.size(); i++) {
            String y = Y.get(i);
            double weight = maxCount / labelCounts.count(y);
            trainingInstances.add(newInstance(X.get(i), y, weight, trainingInstances));
        }
    } else {
        for (int i = 0; i < X.size(); i++) {
            trainingInstances.add(newInstance(X.get(i), Y.get(i), 1.0, trainingInstances));
        }
    }
    // training
    try {
        classifier = AbstractClassifier.forName(classifierName, options);
        classifier.buildClassifier(trainingInstances);
    } catch (Exception e) {
        throw new AnalysisEngineProcessException(e);
    }
    // write model and dataset schema
    try {
        SerializationHelper.write(modelFile.getAbsolutePath(), classifier);
        SerializationHelper.write(datasetSchemaFile.getAbsolutePath(), datasetSchema);
    } catch (Exception e) {
        throw new AnalysisEngineProcessException(e);
    }
    // backup training dataset as arff file
    if (datasetExportFile != null) {
        try {
            ArffSaver saver = new ArffSaver();
            saver.setInstances(trainingInstances);
            saver.setFile(datasetExportFile);
            saver.writeBatch();
        } catch (IOException e) {
            throw new AnalysisEngineProcessException(e);
        }
    }
    if (crossValidation) {
        try {
            Evaluation eval = new Evaluation(trainingInstances);
            Random rand = new Random();
            eval.crossValidateModel(classifier, trainingInstances, 10, rand);
            LOG.debug(eval.toSummaryString());
        } catch (Exception e) {
            throw new AnalysisEngineProcessException(e);
        }
    }
}

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From source file:bio.gcat.operation.analysis.BDAUsage.java

@Override
public Result analyse(Collection<Tuple> tuples, Object... values) {
    if (condenseTuples(tuples).isEmpty())
        return new SimpleResult(this, "No tuples.");
    else if (Tuple.tuplesLength(tuples) != 3)
        return new SimpleResult(this, "Only sequences with codons (tuples of length 3) are allowed.");

    bio.gcat.geneticcode.dich.ct.ClassTable classTable = AnalysisTool.getBDATool().getClassTable();
    if (classTable == null)
        return new SimpleResult(this, "No Binary Dichotomic Algorithm. Use BDA Tool to open / create BDAs.");
    HashMap<Codon, List<Object>> codonToClass = classTable.codon2class();

    Multiset<List<Object>> classCount = HashMultiset.create(tuples.stream()
            .map(tuple -> codonToClass.get(new Codon(tuple.toString()))).collect(Collectors.toList()));

    StringBuilder builder = new StringBuilder();
    for (Entry<List<Object>> count : classCount.entrySet())
        builder.append(count.getElement().mkString("", "", "") + ": " + count.getCount() + "<br/>");
    return new SimpleResult(this, builder.toString());
}

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From source file:edu.cmu.lti.oaqa.baseqa.answer.score.scorers.ConceptTypeAnswerScorer.java

@Override
public Map<String, Double> score(JCas jcas, Answer answer) {
    Set<CandidateAnswerOccurrence> caos = TypeUtil.getCandidateAnswerVariants(answer).stream()
            .map(TypeUtil::getCandidateAnswerOccurrences).flatMap(Collection::stream).collect(toSet());
    Multiset<String> ctypes = HashMultiset.create();
    caos.stream().map(TypeUtil::annotationOffset).map(offset2ctypes::get).forEach(ctypes::addAll);
    ImmutableMap.Builder<String, Double> feat2value = ImmutableMap.builder();
    for (Multiset.Entry<String> entry : ctypes.entrySet()) {
        String type = "ctype-" + entry.getElement();
        feat2value.put(type + "/ratio", Scorer.safeDividedBy(entry.getCount(), ctypes.size()));
        feat2value.put(type + "/binary", 1.0);
    }//from w w  w .j a va  2  s . co  m
    return feat2value.build();
}

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