Examples with BiclusterWithInversionsModel de.lmu.ifi.dbs.elki.data.model.BiclusterWithInversionsModel used on opensource projects

Example 1 with BiclusterWithInversionsModel

use of de.lmu.ifi.dbs.elki.data.model.BiclusterWithInversionsModel in project elki by elki-project.

the class ChengAndChurch method biclustering.

@Override
public Clustering<BiclusterWithInversionsModel> biclustering() {
    double[][] mat = RelationUtil.relationAsMatrix(relation, rowIDs);
    BiclusterCandidate cand = new BiclusterCandidate(getRowDim(), getColDim());
    Clustering<BiclusterWithInversionsModel> result = new Clustering<>("Cheng-and-Church", "Cheng and Church Biclustering");
    ModifiableDBIDs noise = DBIDUtil.newHashSet(relation.getDBIDs());
    FiniteProgress prog = LOG.isVerbose() ? new FiniteProgress("Extracting Cluster", n, LOG) : null;
    for (int i = 0; i < n; i++) {
        cand.reset();
        multipleNodeDeletion(mat, cand);
        if (LOG.isVeryVerbose()) {
            LOG.veryverbose("Residue after Alg 2: " + cand.residue + " " + cand.rowcard + "x" + cand.colcard);
        }
        singleNodeDeletion(mat, cand);
        if (LOG.isVeryVerbose()) {
            LOG.veryverbose("Residue after Alg 1: " + cand.residue + " " + cand.rowcard + "x" + cand.colcard);
        }
        nodeAddition(mat, cand);
        if (LOG.isVeryVerbose()) {
            LOG.veryverbose("Residue after Alg 3: " + cand.residue + " " + cand.rowcard + "x" + cand.colcard);
        }
        cand.maskMatrix(mat, dist);
        BiclusterWithInversionsModel model = new BiclusterWithInversionsModel(colsBitsetToIDs(cand.cols), rowsBitsetToIDs(cand.irow));
        final ArrayDBIDs cids = rowsBitsetToIDs(cand.rows);
        noise.removeDBIDs(cids);
        result.addToplevelCluster(new Cluster<>(cids, model));
        if (LOG.isVerbose()) {
            LOG.verbose("Score of bicluster " + (i + 1) + ": " + cand.residue + "\n");
            LOG.verbose("Number of rows: " + cand.rowcard + "\n");
            LOG.verbose("Number of columns: " + cand.colcard + "\n");
        // LOG.verbose("Total number of masked values: " + maskedVals.size() +
        // "\n");
        }
        LOG.incrementProcessed(prog);
    }
    // Add a noise cluster, full-dimensional.
    if (!noise.isEmpty()) {
        long[] allcols = BitsUtil.ones(getColDim());
        BiclusterWithInversionsModel model = new BiclusterWithInversionsModel(colsBitsetToIDs(allcols), DBIDUtil.EMPTYDBIDS);
        result.addToplevelCluster(new Cluster<>(noise, true, model));
    }
    LOG.ensureCompleted(prog);
    return result;
}