Examples of DoubleVector

JSci.maths.vectors.DoubleVector
de.jungblut.math.DoubleVector
de.lmu.ifi.dbs.elki.data.DoubleVector
A DoubleVector is to store real values approximately as double values. @author Arthur Zimek @apiviz.landmark
edu.ucla.sspace.vector.DoubleVector
An generalized interface for vectors. This interface allows implementations to implement the vector with any kind of underlying data type, but the input and output data types must be doubles.
Methods which modify the state of a {@code Vector} are optional.Implementations that are not modifiable should throw an {@code UnsupportedOperationException} if such methods are called. These methods aremarked as "optional" in the specification for the interface. @author Keith Stevens
moa.core.DoubleVector
org.apache.hama.commons.math.DoubleVector
Vector with doubles. Some of the operations are mutable, unlike the apply and math functions, they return a fresh instance every time.
org.apache.hama.ml.math.DoubleVector
Vector with doubles. Some of the operations are mutable, unlike the apply and math functions, they return a fresh instance every time.
org.neo4j.graphalgo.impl.util.MatrixUtil.DoubleVector
org.renjin.sexp.DoubleVector
weka.core.matrix.DoubleVector
A vector specialized on doubles. @author Yong Wang @version $Revision: 1.4 $

Examples of edu.ucla.sspace.vector.DoubleVector

            if (clusterAssignment.get(row).assignments().length == 0)
                continue;                
            int assignment = clusterAssignment.get(row).assignments()[0];                
            clusterSize[assignment]++;


            DoubleVector contextVector = contexts.getRowVector(row);
            VectorMath.add(meanSenseVectors[assignment], contextVector);
        }
        
        // For each of the clusters with more than 2% of the contexts, generage
        // an average sense vectors.  For those clusters with less than that

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Examples of edu.ucla.sspace.vector.DoubleVector

        // Setup the best cost and index for the best cost.
        double bestTotal = totalCost;
        int bestDeltaIndex = -1;


        // Get the current vector.
        DoubleVector vector = matrix.get(currentVectorIndex);


        // Get the base cost for removing the data point from the current
        // cluster.
        double baseE1Delta = 0;
        double baseI1Delta = 0;

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Examples of edu.ucla.sspace.vector.DoubleVector

            for (int i = 0; i < rows; ++i) {
                LOG.fine("computing affinity for row " + i);
                MultiMap<Double,Integer> neighborMap = rc.getMostSimilar(
                        input, i, numNearestNeighbors, edgeSim);


                DoubleVector row = input.getRowVector(i);
                for (int n : neighborMap.values()) {
                    double edgeWeight = kernelSim.sim(
                            row, input.getRowVector(n));
                    affMatrixWriter.printf("%d %d %f\n", i+1 ,n+1, edgeWeight);
                }

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Examples of edu.ucla.sspace.vector.DoubleVector


    /**
     * {@inheritDoc}
     */
    public synchronized int addColumn(Vector col) {
        DoubleVector column = Vectors.asDouble(col);
        if (isFinished)
            throw new IllegalStateException(
                "Cannot add columns to a MatrixBuilder that is finished");
        if (column instanceof SparseVector) {
            SparseVector s = (SparseVector)column;
            for (int r : s.getNonZeroIndices()) {
                // NB: Matlab sparse format is in [row col val] format
                //
                // NOTE: Matlab indices start at 1, not 0, so update all the
                // column and column values to be Matlab formatted.
                addEntry(r + 1, curColumn + 1, column.get(r));
            }
        }
        else {
            for (int r = 0; r < column.length(); ++r) {
                double d = column.get(r);
                if (d != 0d) {
                    // NOTE: Matlab indices start at 1, not 0, so update all
                    // the row and column values to be Matlab formatted.
                    addEntry(r + 1, curColumn + 1, d);
                }

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Examples of edu.ucla.sspace.vector.DoubleVector


            if (!focusWord.equals(IteratorFactory.EMPTY_TOKEN)) {
                // Incorporate the context into the semantic vector for the
                // focus word.  If the focus word has no semantic vector yet,
                // create a new one, as determined by the index builder.
                DoubleVector meaning = termHolographs.get(focusWord);
                if (meaning == null) {
                    meaning = new DenseVector(indexVectorSize);
                    documentVectors.put(focusWord, meaning);
                }
                updateMeaning(meaning, prevWords, nextWords);
            }


            prevWords.offer(focusWord);
            if (prevWords.size() > 1)
                prevWords.remove();
        }


        // Add the local cached semantics to the global term semantics.
        for (Map.Entry<String, DoubleVector> entry :
                documentVectors.entrySet()) {
            synchronized (entry.getKey()) {
                // Get the global semantic representation of each word.  If it
                // does not currently exist, then just put the local copies
                // representation, otherwise add the local copy to the global
                // version.
                DoubleVector existingVector =
                    termHolographs.get(entry.getKey());
                if (existingVector == null)
                    termHolographs.put(entry.getKey(), entry.getValue());
                else
                    VectorMath.add(existingVector, entry.getValue());

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Examples of edu.ucla.sspace.vector.DoubleVector

                               Queue<String> nextWords) {
        // Generate the semantics of the context using summation of index
        // vectors.
        if (semanticType == SemanticType.COMPOSITE ||
            semanticType == SemanticType.CONTEXT) {
            DoubleVector context = new DenseVector(indexVectorSize);


            // Sum the words prior to the focus word, skipping filtered tokens.
            for (String term: prevWords) {
                if (term.equals(IteratorFactory.EMPTY_TOKEN))
                    continue;
                VectorMath.add(context, vectorMap.get(term));
            }


            // Sum the words after the focus word, skipping filtered tokens.
            for (String term: nextWords) {
                if (term.equals(IteratorFactory.EMPTY_TOKEN))
                    continue;
                VectorMath.add(context, vectorMap.get(term));
            }


            // Normalize the context vector and add it to the meaning.
            normalize(context);
            VectorMath.add(meaning, context);
        }


        // Generate the semantics of the ordering using circular convolution of
        // n-grams.
        if (semanticType == SemanticType.COMPOSITE ||
            semanticType == SemanticType.ORDERING) {
            DoubleVector order = groupConvolution(prevWords, nextWords);


            // Normalize the order vector and add it to the meaning.
            normalize(order);
            VectorMath.add(meaning, order);
        }

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Examples of edu.ucla.sspace.vector.DoubleVector

     * @return The semantic vector generated from the circular convolution.
     */
    private DoubleVector groupConvolution(Queue<String> prevWords,
                                          Queue<String> nextWords) {
        // Generate an empty DoubleVector to hold the convolution.
        DoubleVector result = new DenseVector(indexVectorSize);


        // Do the convolutions starting at index 0.
        String prevWord = prevWords.peek();
        DoubleVector tempConvolution;
        if (!prevWord.equals(IteratorFactory.EMPTY_TOKEN)) {
            tempConvolution =
                convolute(vectorMap.get(prevWords.peek()), placeHolder);
            VectorMath.add(result, tempConvolution);
        } else

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Examples of edu.ucla.sspace.vector.DoubleVector

        // Use the Fast Fourier Transform on each vector.
        FastFourierTransform.transform(left);
        FastFourierTransform.transform(right);


        // Multiply the two together.
        DoubleVector result = VectorMath.multiply(left, right);


        // The inverse transform completes the convolution.
        FastFourierTransform.backtransform(result);
        return result;
    }

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Examples of edu.ucla.sspace.vector.DoubleVector

     * @param orderVector The ordering of values to be used.
     * 
     * @return The shuffled version of {@code data}.
     */
    private DoubleVector changeVector(DoubleVector data, int[] orderVector) {
        DoubleVector result = new DenseVector(indexVectorSize);
        for (int i = 0; i < indexVectorSize; i++)
            result.set(i, data.get(orderVector[i]));
        return result;
    }

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Examples of edu.ucla.sspace.vector.DoubleVector

            PrintWriter pw = new PrintWriter(output);
            // Count the number of non-zero values in the matrix
            int nonZero = 0;
            int rows = matrix.rows();
            for (int i = 0; i < rows; ++i) {
                DoubleVector v = matrix.getRowVector(i);
                if (v instanceof SparseVector) 
                    nonZero += ((SparseVector)v).getNonZeroIndices().length;
                else {
                    for (int col = 0; col < v.length(); ++col) {
                        if (v.get(col) != 0) 
                            nonZero++;
                    }
                }
            }
            // Write the header: rows cols non-zero
            pw.println(matrix.rows() + " " + matrix.columns() + " " + nonZero);
            for (int row = 0; row < rows; ++row) {
                StringBuilder sb = new StringBuilder(nonZero / rows);
                // NOTE: the columns in CLUTO start at 1, not 0, so increment
                // one to each of the columns
                DoubleVector v = matrix.getRowVector(row);
                if (v instanceof SparseVector) {
                    int[] nzIndices = ((SparseVector)v).getNonZeroIndices();
                    for (int nz : nzIndices) {
                        sb.append(nz + 1).append(" ").
                            append(v.get(nz)).append(" ");
                    }
                }
                else {
                    for (int col = 0; col < v.length(); ++col) {
                        double d = v.get(col);
                        if (d != 0) 
                            sb.append(col+1).append(" ").append(d).append(" ");
                    }
                }
                pw.println(sb.toString());

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