Package ch.akuhn.matrix

Examples of ch.akuhn.matrix.SymmetricMatrix

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    }
    public Mds(DenseMatrix dissimilarities, Points initial, 
            Function fConfigDist, Function fWeights, Function fDtarget) {
        len = dissimilarities.rowCount();
        Dtarget = dissimilarities;
        config_dist = new SymmetricMatrix(len);
        this.pos = initial == null ? new Points(len) : initial;
        this.gradient = new Points(len);
        f_config_dist = fConfigDist;
        f_weights = fWeights;
        f_dtarget = fDtarget;
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        //double this_weight;
        //double local_weight_power = 0.;
        //double local_within_between = 1.;

        this.weights = new SymmetricMatrix(Dtarget.rowCount());
        for (int i = 0; i < Dtarget.rowCount(); i++) {
            for (int j = 0; j < i; j++) {
                this.weights.put(i,j, f_weights.apply(this.Dtarget.get(i,j)));
            }
        }
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            constructCloserThanEpsilonNeighborhoodGraph();
        }
    }
   
    private void constructCloserThanEpsilonNeighborhoodGraph() {
        graph = new SymmetricMatrix(n);
        graph.fill(Double.POSITIVE_INFINITY);
        for (int i = 0; i < n; i++) {
            for (int j = 0; j < i; j++) {
                if (dist(i,j) < e) graph.put(i, j, e);
            }
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            }
        }
    }
   
    private void constructKayNearestNeighborhoodGraph() {
        graph = new SymmetricMatrix(n);
        graph.fill(Double.POSITIVE_INFINITY);
        for (int i = 0; i < n; i++) {
            double[] data = new double[n];
            for (int j = 0; j < n; j++) data[j] = dist(i,j);
            int[] index = indicesOfMinima(data, k+1);
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Related Classes of ch.akuhn.matrix.SymmetricMatrix

  • ch.akuhn.isomap.Isomap
  • ch.akuhn.org.ggobi.plugins.ggvis.Mds
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