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

        final SortedMultiMap<Double,Map.Entry<DoubleVector,Set<String>>>
            mostSimilarPrincipleVectors = new BoundedSortedMultiMap
                <Double,Map.Entry<DoubleVector,Set<String>>>(k, false);        
        for (Map.Entry<DoubleVector,Set<String>> e : 
                 principleVectorToNearestTerms.asMap().entrySet()) { 
            DoubleVector pVec = e.getKey();
            double sim = Similarity.cosineSimilarity(v, pVec);
            mostSimilarPrincipleVectors.put(sim, e);
        }
        
        // Create a global map to store the results of the principle vectors'

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Examples of edu.ucla.sspace.vector.DoubleVector

    /**
     * {@inheritDoc}
     */
    public double getKMeansObjective() {
        // Note that the scaled vector handles any recursive scaling.
        DoubleVector centroid = new ScaledDoubleVector(
                matrixRowSums, 1/((double) dataMatrix.rows()));
        double score = 0;
        for (int r = 0; r < dataMatrix.rows(); ++r)
            score += VectorMath.dotProduct(
                    centroid, dataMatrix.getRowVector(r));

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Examples of edu.ucla.sspace.vector.DoubleVector

        DoubleVector[] centroids = new DoubleVector[numComparisons.length];
        int[] centroidSizes = new int[numComparisons.length];
        double intraClusterScore = 0;
        for (int i = 0; i < assignments.length; ++i) {
            int assignment = assignments[i];
            DoubleVector v = m.getRowVector(i);
            if (centroids[assignment] == null)
                centroids[assignment] = Vectors.copyOf(v);
            else {
                DoubleVector centroid = centroids[assignment];
                intraClusterScore += (centroidSizes[assignment] -
                                      VectorMath.dotProduct(v, centroid));
                VectorMath.add(centroid, v);
                numComparisons[assignment] += centroidSizes[assignment];
            }

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Examples of edu.ucla.sspace.vector.DoubleVector

    protected static int computeCut(Matrix matrix, 
                                    DoubleVector rho, 
                                    double rhoSum,
                                    DoubleVector matrixRowSums) {
        // Compute the conductance of the newly sorted matrix.
        DoubleVector x = new DenseVector(matrix.columns());
        DoubleVector y = matrixRowSums;
        VectorMath.subtract(y, x);


        // First compute x and y, which are summations of different cuts of the
        // matrix, starting with x being the first row and y being the summation
        // of all other rows.  While doing this, also compute different
        // summations of values in the rho vector using the same cut.
        VectorMath.add(x, matrix.getRowVector(0));
        double rhoX = rho.get(0);
        double rhoY = rhoSum - rho.get(0);


        // Compute the dot product between the first possible cut.
        double u = VectorMath.dotProduct(x, y); 


        // Find the current conductance for the cut, assume that this is the
        // best so far.
        double minConductance = u / Math.min(rhoX, rhoY);
        int cutIndex = 0;


        // Compute the other possible cuts, ignoring the last cut, which would
        // leave no data points in a partition.  The cut with the smallest
        // conductance is maintained.
        for (int i = 1; i < rho.length() - 2; ++i) {
            // Compute the new value of u, the denominator for computing the
            // conductance.
            DoubleVector vector = matrix.getRowVector(i);
            double xv = VectorMath.dotProduct(x, vector);
            double yv = VectorMath.dotProduct(y, vector);
            u = u - xv + yv + 1;


            // Shift over vectors from y to x.

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Examples of edu.ucla.sspace.vector.DoubleVector

     * This method also assumes that {@code matrix} is row based and iterates
     * over each of the values in the row before iterating over another row.
     */
    protected static DoubleVector computeMatrixTransposeV(Matrix matrix,
                                                          DoubleVector v) {
        DoubleVector newV = new DenseVector(matrix.columns());
        if (matrix instanceof SparseMatrix) {
            SparseMatrix smatrix = (SparseMatrix) matrix;
            for (int r = 0; r < smatrix.rows(); ++r) {
                SparseDoubleVector row = smatrix.getRowVector(r);
                int[] nonZeros = row.getNonZeroIndices();
                for (int c : nonZeros)
                    newV.add(c, row.get(c) * v.get(r));
            }
        } else {
            for (int r = 0; r < matrix.rows(); ++r)
                for (int c = 0; c < matrix.columns(); ++c)
                    newV.add(c, matrix.get(r, c) * v.get(r));
        }
        return newV;
    }

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Examples of edu.ucla.sspace.vector.DoubleVector

     * Compute the row sums of the values in {@code matrix} and returns the
     * values in a vector of length {@code matrix.columns()}.
     */
    protected static <T extends Matrix> DoubleVector computeMatrixRowSum(
            T matrix) {
        DoubleVector rowSums = new DenseVector(matrix.columns());
        for (int r = 0; r < matrix.rows(); ++r)
            VectorMath.add(rowSums, matrix.getRowVector(r));
        return rowSums;
    }

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Examples of edu.ucla.sspace.vector.DoubleVector

    @Test
    public void testGetRowVector() {
        Matrix baseMatrix = new ArrayMatrix(baseValues);
        Matrix maskedMatrix = new CellMaskedMatrix(baseMatrix, rowMap, colMap);
        for (int r = 0; r < maskedMatrix.rows(); ++r) {
            DoubleVector rowVector = maskedMatrix.getRowVector(r);
            assertEquals(4, rowVector.length());
            for (int c = 0; c < 4; ++c)
                assertEquals(getBaseValue(baseMatrix, r, c),
                             rowVector.get(c), .000001);
        }
    }

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Examples of edu.ucla.sspace.vector.DoubleVector

    @Test
    public void testGetColumnVector() {
        Matrix baseMatrix = new ArrayMatrix(baseValues);
        Matrix maskedMatrix = new CellMaskedMatrix(baseMatrix, rowMap, colMap);
        for (int c = 0; c < maskedMatrix.columns(); ++c) {
            DoubleVector colVector = maskedMatrix.getColumnVector(c);
            assertEquals(3, colVector.length());
            for (int r = 0; r < 3; ++r) 
                assertEquals(getBaseValue(baseMatrix, r, c),
                             colVector.get(r), .000002);
        }
    }

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Examples of edu.ucla.sspace.vector.DoubleVector


    @Test
    public void testSetRowVector() {
        Matrix baseMatrix = new ArrayMatrix(baseValues);
        Matrix maskedMatrix = new CellMaskedMatrix(baseMatrix, rowMap, colMap);
        DoubleVector row = new DenseVector(new double[]{1, 2, 3, 4});
        maskedMatrix.setRow(0, row);
        for (int i = 0; i < 4; i++)
            assertEquals(getBaseValue(baseMatrix, 0, i), row.get(i), .000001);
    }

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Examples of edu.ucla.sspace.vector.DoubleVector


    @Test
    public void testSetColumnVector() {
        Matrix baseMatrix = new ArrayMatrix(baseValues);
        Matrix maskedMatrix = new CellMaskedMatrix(baseMatrix, rowMap, colMap);
        DoubleVector col = new DenseVector(new double[] {1, 2, 3});
        maskedMatrix.setColumn(0, col);
        for (int i = 0; i < 3; i++)
            assertEquals(getBaseValue(baseMatrix, i, 0), col.get(i), .000001);
    }

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