Examples of org.carrot2.util.attribute.AttributeDescriptor

org.carrot2.util.resource.DirLocator
Represents an occurrence of a {@link SpriteReferenceDirective} in a specific CSS file.

    /**
     * Discovers labels for clusters.
     */
    void buildLabels(LingoProcessingContext context, ITermWeighting termWeighting)
    {
        final PreprocessingContext preprocessingContext = context.preprocessingContext;
        final VectorSpaceModelContext vsmContext = context.vsmContext;
        final DoubleMatrix2D reducedTdMatrix = context.reducedVsmContext.baseMatrix;
        final int [] wordsStemIndex = preprocessingContext.allWords.stemIndex;
        final int [] labelsFeatureIndex = preprocessingContext.allLabels.featureIndex;
        final int [] mostFrequentOriginalWordIndex = preprocessingContext.allStems.mostFrequentOriginalWordIndex;

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      private final MutableCharArray tempCharSequence;
      private final Class<?> tokenFilterClass;


      private ChineseTokenizer() throws Exception {
        this.tempCharSequence = new MutableCharArray(new char[0]);


        // As Smart Chinese is not available during compile time,
        // we need to resort to reflection.
        final Class<?> tokenizerClass = ReflectionUtils.classForName(
            "org.apache.lucene.analysis.cn.smart.SentenceTokenizer", false);

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    // is not affected by the test stopwords and stoplabels.
    ILexicalData lexicalData = preprocessing.lexicalDataFactory
        .getLexicalData(LanguageCode.MALTESE);


    for (String word : wordsToCheck.split(",")) {
      if (!lexicalData.isCommonWord(new MutableCharArray(word))
          && !lexicalData.isStopLabel(word)) {
        clusters.add(new Cluster(word));
      }
    }
  }

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        if (context.hasLabels())
        {
            // Term-document matrix building and reduction
            final VectorSpaceModelContext vsmContext = new VectorSpaceModelContext(
                context);
            final ReducedVectorSpaceModelContext reducedVsmContext = new ReducedVectorSpaceModelContext(
                vsmContext);
            LingoProcessingContext lingoContext = new LingoProcessingContext(
                reducedVsmContext);


            matrixBuilder.buildTermDocumentMatrix(vsmContext);

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        // Further processing only if there are words to process
        clusters = Lists.newArrayList();
        if (context.hasLabels())
        {
            // Term-document matrix building and reduction
            final VectorSpaceModelContext vsmContext = new VectorSpaceModelContext(
                context);
            final ReducedVectorSpaceModelContext reducedVsmContext = new ReducedVectorSpaceModelContext(
                vsmContext);
            LingoProcessingContext lingoContext = new LingoProcessingContext(
                reducedVsmContext);

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     * Discovers labels for clusters.
     */
    void buildLabels(LingoProcessingContext context, ITermWeighting termWeighting)
    {
        final PreprocessingContext preprocessingContext = context.preprocessingContext;
        final VectorSpaceModelContext vsmContext = context.vsmContext;
        final DoubleMatrix2D reducedTdMatrix = context.reducedVsmContext.baseMatrix;
        final int [] wordsStemIndex = preprocessingContext.allWords.stemIndex;
        final int [] labelsFeatureIndex = preprocessingContext.allLabels.featureIndex;
        final int [] mostFrequentOriginalWordIndex = preprocessingContext.allStems.mostFrequentOriginalWordIndex;
        final int [][] phrasesWordIndices = preprocessingContext.allPhrases.wordIndices;

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        final Map<String, AttributeEditorInfo> editorInfos = Maps.newHashMap();


        int maxColumns = 1;
        for (String key : sortedKeys)
        {
            final AttributeDescriptor descriptor = attributeDescriptors.get(key);


            IAttributeEditor editor = null;
            try
            {
                editor = EditorFactory.getEditorFor(this.componentClazz, descriptor);
                final AttributeEditorInfo info = editor.init(bindable, descriptor,
                    globalEventsProvider, currentValues);


                editorInfos.put(key, info);
                maxColumns = Math.max(maxColumns, info.columns);
            }
            catch (EditorNotFoundException ex)
            {
                Utils.logError("No editor for attribute: "
                    + descriptor.key + " (class: " + descriptor.type + ")", false);


                /*
                 * Skip editor.
                 */
                editor = null;
            }


            editors.put(key, editor);
        }


        /*
         * Prepare the layout for this editor.
         */
        final GridLayout layout = GUIFactory.zeroMarginGridLayout();
        layout.makeColumnsEqualWidth = false;


        layout.numColumns = maxColumns;
        this.setLayout(layout);


        /*
         * Create visual components for editors.
         */
        final GridDataFactory labelFactory = GridDataFactory.fillDefaults().span(
            maxColumns, 1);


        boolean firstEditor = true;
        for (String key : sortedKeys)
        {
            final AttributeDescriptor descriptor = attributeDescriptors.get(key);
            final IAttributeEditor editor = editors.get(key);
            final AttributeEditorInfo editorInfo = editorInfos.get(key);


            if (editor == null)
            {

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          }
        },
        
        // Using the class loader directly because this time we want to omit the prefix 
        new ClassLoaderLocator(core.getResourceLoader().getClassLoader())));
    
    this.controller.init(initAttributes);
    this.idFieldName = core.getSchema().getUniqueKeyField().getName();


    // Make sure the requested Carrot2 clustering algorithm class is available

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    @Override
    protected IResource getXsltResource()
    {
        if (solrXsltAdapter == null) {
            return new ClassResource(SolrDocumentSource.class, "solr-to-c2.xsl");
        } else {
            return solrXsltAdapter; 
        }
    }

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                    .defaultLanguage(LanguageCode.ENGLISH);




                    File resourcesDir = new File(environment.configFile(), "carrot2/resources");


                    ResourceLookup resourceLookup = new ResourceLookup(new DirLocator(resourcesDir));


                    DefaultLexicalDataFactoryDescriptor.attributeBuilder(attributes)
                    .mergeResources(true);
                    LexicalDataLoaderDescriptor.attributeBuilder(attributes)
                    .resourceLookup(resourceLookup);

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