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

Example 61 with Clustering

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

the class ExternalClustering method attachToRelation.

/**
 * Build a clustering from the file result.
 *
 * @param database Database
 * @param r Result to attach to
 * @param assignment Cluster assignment
 * @param name Name
 */
private void attachToRelation(Database database, Relation<?> r, IntArrayList assignment, ArrayList<String> name) {
    DBIDs ids = r.getDBIDs();
    if (!(ids instanceof ArrayDBIDs)) {
        throw new AbortException("External clusterings can only be used with static DBIDs.");
    }
    Int2IntOpenHashMap sizes = new Int2IntOpenHashMap();
    for (IntListIterator it = assignment.iterator(); it.hasNext(); ) {
        sizes.addTo(it.nextInt(), 1);
    }
    Int2ObjectOpenHashMap<ArrayModifiableDBIDs> cids = new Int2ObjectOpenHashMap<>(sizes.size());
    for (ObjectIterator<Int2IntMap.Entry> it = sizes.int2IntEntrySet().fastIterator(); it.hasNext(); ) {
        Int2IntMap.Entry entry = it.next();
        cids.put(entry.getIntKey(), DBIDUtil.newArray(entry.getIntValue()));
    }
    {
        DBIDArrayIter it = ((ArrayDBIDs) ids).iter();
        for (int i = 0; i < assignment.size(); i++) {
            cids.get(assignment.getInt(i)).add(it.seek(i));
        }
    }
    String nam = FormatUtil.format(name, " ");
    String snam = nam.toLowerCase().replace(' ', '-');
    Clustering<ClusterModel> result = new Clustering<>(nam, snam);
    for (ObjectIterator<Int2ObjectMap.Entry<ArrayModifiableDBIDs>> it = cids.int2ObjectEntrySet().fastIterator(); it.hasNext(); ) {
        Int2ObjectMap.Entry<ArrayModifiableDBIDs> entry = it.next();
        boolean noise = entry.getIntKey() < 0;
        result.addToplevelCluster(new Cluster<>(entry.getValue(), noise, ClusterModel.CLUSTER));
    }
    database.getHierarchy().add(r, result);
}

Example 62 with Clustering

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

the class ByLabelHierarchicalClustering method run.

/**
 * Run the actual clustering algorithm.
 *
 * @param relation The data input to use
 */
public Clustering<Model> run(Relation<?> relation) {
    HashMap<String, DBIDs> labelmap = new HashMap<>();
    ModifiableDBIDs noiseids = DBIDUtil.newArray();
    Clustering<Model> clustering = new Clustering<>("By Label Hierarchical Clustering", "bylabel-clustering");
    for (DBIDIter iditer = relation.iterDBIDs(); iditer.valid(); iditer.advance()) {
        final Object val = relation.get(iditer);
        if (val == null) {
            noiseids.add(iditer);
            continue;
        }
        String label = val.toString();
        assign(labelmap, label, iditer);
    }
    ArrayList<Cluster<Model>> clusters = new ArrayList<>(labelmap.size());
    for (Entry<String, DBIDs> entry : labelmap.entrySet()) {
        DBIDs ids = entry.getValue();
        if (ids instanceof DBID) {
            noiseids.add((DBID) ids);
            continue;
        }
        Cluster<Model> clus = new Cluster<Model>(entry.getKey(), ids, ClusterModel.CLUSTER);
        clusters.add(clus);
    }
    for (Cluster<Model> cur : clusters) {
        boolean isrootcluster = true;
        for (Cluster<Model> oth : clusters) {
            if (oth != cur && oth.getName().startsWith(cur.getName())) {
                clustering.addChildCluster(oth, cur);
                if (LOG.isDebuggingFiner()) {
                    LOG.debugFiner(oth.getName() + " is a child of " + cur.getName());
                }
                isrootcluster = false;
            }
        }
        if (isrootcluster) {
            clustering.addToplevelCluster(cur);
        }
    }
    // Collected noise IDs.
    if (noiseids.size() > 0) {
        Cluster<Model> c = new Cluster<Model>("Noise", noiseids, ClusterModel.CLUSTER);
        c.setNoise(true);
        clustering.addToplevelCluster(c);
    }
    return clustering;
}

Example 63 with Clustering

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

the class EvaluateDaviesBouldin method processNewResult.

@Override
public void processNewResult(ResultHierarchy hier, Result result) {
    List<Clustering<?>> crs = Clustering.getClusteringResults(result);
    if (crs.isEmpty()) {
        return;
    }
    Database db = ResultUtil.findDatabase(hier);
    Relation<? extends NumberVector> rel = db.getRelation(this.distanceFunction.getInputTypeRestriction());
    for (Clustering<?> c : crs) {
        evaluateClustering(db, (Relation<? extends NumberVector>) rel, c);
    }
}

Example 64 with Clustering

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

the class EvaluateSilhouette method processNewResult.

@Override
public void processNewResult(ResultHierarchy hier, Result result) {
    List<Clustering<?>> crs = Clustering.getClusteringResults(result);
    if (crs.isEmpty()) {
        return;
    }
    Database db = ResultUtil.findDatabase(hier);
    Relation<O> rel = db.getRelation(distance.getInputTypeRestriction());
    DistanceQuery<O> dq = db.getDistanceQuery(rel, distance);
    for (Clustering<?> c : crs) {
        evaluateClustering(db, rel, dq, c);
    }
}

Example 65 with Clustering

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

the class EvaluateSimplifiedSilhouette method processNewResult.

@Override
public void processNewResult(ResultHierarchy hier, Result result) {
    List<Clustering<?>> crs = Clustering.getClusteringResults(result);
    if (crs.isEmpty()) {
        return;
    }
    Database db = ResultUtil.findDatabase(hier);
    Relation<? extends NumberVector> rel = db.getRelation(this.distance.getInputTypeRestriction());
    for (Clustering<?> c : crs) {
        evaluateClustering(db, rel, c);
    }
}