Examples with DoubleDBIDPair de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDPair used on opensource projects

Example 1 with DoubleDBIDPair

use of de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDPair in project elki by elki-project.

the class MaterializeKNNAndRKNNPreprocessor method affectedRkNN.

/**
 * Extracts and removes the DBIDs in the given collections.
 *
 * @param extract a list of lists of DistanceResultPair to extract
 * @param remove the ids to remove
 * @return the DBIDs in the given collection
 */
protected ArrayDBIDs affectedRkNN(List<? extends Collection<DoubleDBIDPair>> extract, DBIDs remove) {
    HashSetModifiableDBIDs ids = DBIDUtil.newHashSet();
    for (Collection<DoubleDBIDPair> drps : extract) {
        for (DoubleDBIDPair drp : drps) {
            ids.add(drp);
        }
    }
    ids.removeDBIDs(remove);
    // Convert back to array
    return DBIDUtil.newArray(ids);
}

Example 2 with DoubleDBIDPair

use of de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDPair in project elki by elki-project.

the class MaterializeKNNAndRKNNPreprocessor method objectsRemoved.

@Override
protected void objectsRemoved(DBIDs ids) {
    StepProgress stepprog = getLogger().isVerbose() ? new StepProgress(3) : null;
    // For debugging: valid DBIDs still in the database.
    final DBIDs valid = DBIDUtil.ensureSet(distanceQuery.getRelation().getDBIDs());
    ArrayDBIDs aids = DBIDUtil.ensureArray(ids);
    // delete the materialized (old) kNNs and RkNNs
    getLogger().beginStep(stepprog, 1, "New deletions ocurred, remove their materialized kNNs and RkNNs.");
    // Temporary storage of removed lists
    List<KNNList> kNNs = new ArrayList<>(ids.size());
    List<TreeSet<DoubleDBIDPair>> rkNNs = new ArrayList<>(ids.size());
    for (DBIDIter iter = aids.iter(); iter.valid(); iter.advance()) {
        kNNs.add(storage.get(iter));
        for (DBIDIter it = storage.get(iter).iter(); it.valid(); it.advance()) {
            if (!valid.contains(it) && !ids.contains(it)) {
                LOG.warning("False kNN: " + it);
            }
        }
        storage.delete(iter);
        rkNNs.add(materialized_RkNN.get(iter));
        for (DoubleDBIDPair it : materialized_RkNN.get(iter)) {
            if (!valid.contains(it) && !ids.contains(it)) {
                LOG.warning("False RkNN: " + it);
            }
        }
        materialized_RkNN.delete(iter);
    }
    // Keep only those IDs not also removed
    ArrayDBIDs kNN_ids = affectedkNN(kNNs, aids);
    ArrayDBIDs rkNN_ids = affectedRkNN(rkNNs, aids);
    // update the affected kNNs and RkNNs
    getLogger().beginStep(stepprog, 2, "New deletions ocurred, update the affected kNNs and RkNNs.");
    // Recompute the kNN for affected objects (in rkNN lists)
    {
        List<? extends KNNList> kNNList = knnQuery.getKNNForBulkDBIDs(rkNN_ids, k);
        int i = 0;
        for (DBIDIter reknn = rkNN_ids.iter(); reknn.valid(); reknn.advance(), i++) {
            if (kNNList.get(i) == null && !valid.contains(reknn)) {
                LOG.warning("BUG in online kNN/RkNN maintainance: " + DBIDUtil.toString(reknn) + " no longer in database.");
                continue;
            }
            assert (kNNList.get(i) != null);
            storage.put(reknn, kNNList.get(i));
            for (DoubleDBIDListIter it = kNNList.get(i).iter(); it.valid(); it.advance()) {
                materialized_RkNN.get(it).add(makePair(it, reknn));
            }
        }
    }
    // remove objects from RkNNs of objects (in kNN lists)
    {
        SetDBIDs idsSet = DBIDUtil.ensureSet(ids);
        for (DBIDIter nn = kNN_ids.iter(); nn.valid(); nn.advance()) {
            TreeSet<DoubleDBIDPair> rkNN = materialized_RkNN.get(nn);
            for (Iterator<DoubleDBIDPair> it = rkNN.iterator(); it.hasNext(); ) {
                if (idsSet.contains(it.next())) {
                    it.remove();
                }
            }
        }
    }
    // inform listener
    getLogger().beginStep(stepprog, 3, "New deletions ocurred, inform listeners.");
    fireKNNsRemoved(ids, rkNN_ids);
    getLogger().ensureCompleted(stepprog);
}

Example 3 with DoubleDBIDPair

use of de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDPair in project elki by elki-project.

the class HilOut method innerScan.

/**
 * innerScan function calculates new upper and lower bounds and inserts the
 * points of the neighborhood the bounds are based on in the NN Set
 *
 * @param i position in pf of the feature for which the bounds should be
 *        calculated
 * @param maxcount maximal size of the neighborhood
 */
private void innerScan(HilbertFeatures hf, final int i, final int maxcount) {
    // Get only once for performance
    final O p = hf.relation.get(hf.pf[i].id);
    int a = i, b = i;
    int level = h, levela = h, levelb = h;
    // Explore up to "maxcount" neighbors in this pass
    for (int count = 0; count < maxcount; count++) {
        // Neighbor to explore
        final int c;
        if (a == 0) {
            // At left end, explore right
            // assert (b < capital_n - 1);
            levelb = Math.min(levelb, hf.pf[b].level);
            b++;
            c = b;
        } else if (b >= capital_n - 1) {
            // At right end, explore left
            // assert (a > 0);
            a--;
            levela = Math.min(levela, hf.pf[a].level);
            c = a;
        } else if (hf.pf[a - 1].level >= hf.pf[b].level) {
            // Prefer higher level
            a--;
            levela = Math.min(levela, hf.pf[a].level);
            c = a;
        } else {
            // assert (b < capital_n - 1);
            levelb = Math.min(levelb, hf.pf[b].level);
            b++;
            c = b;
        }
        if (!hf.pf[i].nn_keys.contains(hf.pf[c].id)) {
            // hf.distcomp ++;
            hf.pf[i].insert(hf.pf[c].id, distq.distance(p, hf.pf[c].id), k);
            if (hf.pf[i].nn.size() == k) {
                if (hf.pf[i].sum_nn < omega_star) {
                    // stop = true
                    break;
                }
                final int mlevel = Math.max(levela, levelb);
                if (mlevel < level) {
                    level = mlevel;
                    final double delta = hf.minDistLevel(hf.pf[i].id, level);
                    if (delta >= hf.pf[i].nn.peek().doubleValue()) {
                        // stop = true
                        break;
                    }
                }
            }
        }
    }
    double br = hf.boxRadius(i, a - 1, b + 1);
    double newlb = 0.0;
    double newub = 0.0;
    for (ObjectHeap.UnsortedIter<DoubleDBIDPair> iter = hf.pf[i].nn.unsortedIter(); iter.valid(); iter.advance()) {
        DoubleDBIDPair entry = iter.get();
        newub += entry.doubleValue();
        if (entry.doubleValue() <= br) {
            newlb += entry.doubleValue();
        }
    }
    if (newlb > hf.pf[i].lbound) {
        hf.pf[i].lbound = newlb;
    }
    if (newub < hf.pf[i].ubound) {
        hf.pf[i].ubound = newub;
    }
}

Example 4 with DoubleDBIDPair

use of de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDPair in project elki by elki-project.

the class LinearWeightedExtendedNeighborhood method getWeightedNeighbors.

@Override
public Collection<DoubleDBIDPair> getWeightedNeighbors(DBIDRef reference) {
    ModifiableDBIDs seen = DBIDUtil.newHashSet();
    List<DoubleDBIDPair> result = new ArrayList<>();
    // Add starting object
    result.add(DBIDUtil.newPair(computeWeight(0), reference));
    seen.add(reference);
    // Extend.
    DBIDs cur = DBIDUtil.deref(reference);
    for (int i = 1; i <= steps; i++) {
        final double weight = computeWeight(i);
        // Collect newly discovered IDs
        ModifiableDBIDs add = DBIDUtil.newHashSet();
        for (DBIDIter iter = cur.iter(); iter.valid(); iter.advance()) {
            for (DBIDIter iter2 = inner.getNeighborDBIDs(iter).iter(); iter2.valid(); iter2.advance()) {
                // Seen before?
                if (seen.contains(iter2)) {
                    continue;
                }
                add.add(iter2);
                result.add(DBIDUtil.newPair(weight, iter2));
            }
        }
        if (add.size() == 0) {
            break;
        }
        cur = add;
    }
    return result;
}

Example 5 with DoubleDBIDPair

use of de.lmu.ifi.dbs.elki.database.ids.DoubleDBIDPair in project elki by elki-project.

the class OUTRES method subsetNeighborhoodQuery.

/**
 * Refine neighbors within a subset.
 *
 * @param neighc Neighbor candidates
 * @param dbid Query object
 * @param df distance function
 * @param adjustedEps Epsilon range
 * @param kernel Kernel
 * @return Neighbors of neighbor object
 */
private DoubleDBIDList subsetNeighborhoodQuery(DoubleDBIDList neighc, DBIDRef dbid, PrimitiveDistanceFunction<? super V> df, double adjustedEps, KernelDensityEstimator kernel) {
    ModifiableDoubleDBIDList n = DBIDUtil.newDistanceDBIDList(neighc.size());
    V query = kernel.relation.get(dbid);
    for (DoubleDBIDListIter neighbor = neighc.iter(); neighbor.valid(); neighbor.advance()) {
        DoubleDBIDPair p = neighbor.getPair();
        double dist = df.distance(query, kernel.relation.get(p));
        if (dist <= adjustedEps) {
            n.add(dist, p);
        }
    }
    return n;
}