Package de.lmu.ifi.dbs.elki.database.ids

Examples of de.lmu.ifi.dbs.elki.database.ids.ArrayDBIDs

227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
  @Override
  protected void objectsRemoved(DBIDs ids) {
    StepProgress stepprog = getLogger().isVerbose() ? new StepProgress(3) : null;

    ArrayDBIDs aids = DBIDUtil.ensureArray(ids);
    // delete the materialized (old) kNNs and RkNNs
    if(stepprog != null) {
      stepprog.beginStep(1, "New deletions ocurred, remove their materialized kNNs and RkNNs.", getLogger());
    }
    List<List<DistanceResultPair<D>>> kNNs = new ArrayList<List<DistanceResultPair<D>>>(ids.size());
    List<List<DistanceResultPair<D>>> rkNNs = new ArrayList<List<DistanceResultPair<D>>>(ids.size());
    for(DBID id : aids) {
      kNNs.add(storage.get(id));
      storage.delete(id);
      rkNNs.add(new ArrayList<DistanceResultPair<D>>(materialized_RkNN.get(id)));
      materialized_RkNN.delete(id);
    }
    ArrayDBIDs kNN_ids = extractAndRemoveIDs(kNNs, aids);
    ArrayDBIDs rkNN_ids = extractAndRemoveIDs(rkNNs, aids);

    // update the affected kNNs and RkNNs
    if(stepprog != null) {
      stepprog.beginStep(2, "New deletions ocurred, update the affected kNNs and RkNNs.", getLogger());
    }
    // update the kNNs of the RkNNs
    List<List<DistanceResultPair<D>>> kNNList = knnQuery.getKNNForBulkDBIDs(rkNN_ids, k);
    for(int i = 0; i < rkNN_ids.size(); i++) {
      DBID id = rkNN_ids.get(i);
      storage.put(id, kNNList.get(i));
      for(DistanceResultPair<D> kNN : kNNList.get(i)) {
        Set<DistanceResultPair<D>> rknns = materialized_RkNN.get(kNN.getDBID());
        rknns.add(new GenericDistanceResultPair<D>(kNN.getDistance(), id));
      }
View Full Code Here
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
    MeanVariance ksize = new MeanVariance();
    if(logger.isVerbose()) {
      logger.verbose("Approximating nearest neighbor lists to database objects");
    }

    ArrayDBIDs aids = DBIDUtil.ensureArray(relation.getDBIDs());
    int minsize = (int) Math.floor(aids.size() / partitions);

    FiniteProgress progress = logger.isVerbose() ? new FiniteProgress("Processing partitions.", partitions, logger) : null;
    for(int part = 0; part < partitions; part++) {
      int size = (partitions * minsize + part >= aids.size()) ? minsize : minsize + 1;
      // Collect the ids in this node.
      ArrayModifiableDBIDs ids = DBIDUtil.newArray(size);
      for(int i = 0; i < size; i++) {
        assert (size * partitions + part < aids.size());
        ids.add(aids.get(i * partitions + part));
      }
      HashMap<DBIDPair, D> cache = new HashMap<DBIDPair, D>(size * size * 3 / 8);
      for(DBID id : ids) {
        KNNHeap<D> kNN = new KNNHeap<D>(k, distanceQuery.infiniteDistance());
        for(DBID id2 : ids) {
View Full Code Here
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
   */
  @Override
  protected void preprocess() {
    storage = DataStoreUtil.makeStorage(relation.getDBIDs(), DataStoreFactory.HINT_STATIC, List.class);

    ArrayDBIDs ids = DBIDUtil.ensureArray(relation.getDBIDs());
    FiniteProgress progress = getLogger().isVerbose() ? new FiniteProgress("Materializing k nearest neighbors (k=" + k + ")", ids.size(), getLogger()) : null;

    // Try bulk
    List<List<DistanceResultPair<D>>> kNNList = null;
    if(usebulk) {
      kNNList = knnQuery.getKNNForBulkDBIDs(ids, k);
      if(kNNList != null) {
        for(int i = 0; i < ids.size(); i++) {
          DBID id = ids.get(i);
          storage.put(id, kNNList.get(i));
          if(progress != null) {
            progress.incrementProcessed(getLogger());
          }
        }
View Full Code Here
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
   * @param ids the ids of the newly inserted objects
   */
  protected void objectsInserted(DBIDs ids) {
    StepProgress stepprog = getLogger().isVerbose() ? new StepProgress(3) : null;

    ArrayDBIDs aids = DBIDUtil.ensureArray(ids);
    // materialize the new kNNs
    if(stepprog != null) {
      stepprog.beginStep(1, "New insertions ocurred, materialize their new kNNs.", getLogger());
    }
    List<List<DistanceResultPair<D>>> kNNList = knnQuery.getKNNForBulkDBIDs(aids, k);
    for(int i = 0; i < aids.size(); i++) {
      DBID id = aids.get(i);
      storage.put(id, kNNList.get(i));
    }

    // update the affected kNNs
    if(stepprog != null) {
      stepprog.beginStep(2, "New insertions ocurred, update the affected kNNs.", getLogger());
    }
    ArrayDBIDs rkNN_ids = updateKNNsAfterInsertion(ids);

    // inform listener
    if(stepprog != null) {
      stepprog.beginStep(3, "New insertions ocurred, inform listeners.", getLogger());
    }
View Full Code Here
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
   *        materialized kNNs
   * @return the RkNNs of the specified ids, i.e. the kNNs which have been
   *         updated
   */
  private ArrayDBIDs updateKNNsAfterInsertion(DBIDs ids) {
    ArrayDBIDs rkNN_ids = DBIDUtil.newArray();
    DBIDs oldids = DBIDUtil.difference(relation.getDBIDs(), ids);
    for(DBID id1 : oldids) {
      List<DistanceResultPair<D>> kNNs = storage.get(id1);
      D knnDist = kNNs.get(kNNs.size() - 1).getDistance();
      // look for new kNNs
      List<DistanceResultPair<D>> newKNNs = new ArrayList<DistanceResultPair<D>>();
      KNNHeap<D> heap = null;
      for(DBID id2 : ids) {
        D dist = distanceQuery.distance(id1, id2);
        if(dist.compareTo(knnDist) <= 0) {
          if(heap == null) {
            heap = new KNNHeap<D>(k);
            heap.addAll(kNNs);
          }
          heap.add(dist, id2);
        }
      }
      if(heap != null) {
        newKNNs = heap.toSortedArrayList();
        storage.put(id1, newKNNs);
        rkNN_ids.add(id1);
      }
    }
    return rkNN_ids;
  }
View Full Code Here
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
   * @return the RkNNs of the specified ids, i.e. the kNNs which have been
   *         updated
   */
  private ArrayDBIDs updateKNNsAfterDeletion(DBIDs ids) {
    TreeSetModifiableDBIDs idsSet = DBIDUtil.newTreeSet(ids);
    ArrayDBIDs rkNN_ids = DBIDUtil.newArray();
    for(DBID id1 : relation.iterDBIDs()) {
      List<DistanceResultPair<D>> kNNs = storage.get(id1);
      for(DistanceResultPair<D> kNN : kNNs) {
        if(idsSet.contains(kNN.getDBID())) {
          rkNN_ids.add(id1);
          break;
        }
      }
    }

    // update the kNNs of the RkNNs
    List<List<DistanceResultPair<D>>> kNNList = knnQuery.getKNNForBulkDBIDs(rkNN_ids, k);
    for(int i = 0; i < rkNN_ids.size(); i++) {
      DBID id = rkNN_ids.get(i);
      storage.put(id, kNNList.get(i));
    }

    return rkNN_ids;
  }
View Full Code Here
301
302
303
304
305
306
307
308
309
310
311
    // update the affected kNNs
    if(stepprog != null) {
      stepprog.beginStep(2, "New deletions ocurred, update the affected kNNs.", getLogger());
    }
    ArrayDBIDs rkNN_ids = updateKNNsAfterDeletion(ids);

    // inform listener
    if(stepprog != null) {
      stepprog.beginStep(3, "New deletions ocurred, inform listeners.", getLogger());
    }
View Full Code Here
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
      // recompute lrds
      if(stepprog != null) {
        stepprog.beginStep(1, "Recompute LRDs.", logger);
      }
      ArrayDBIDs lrd_ids = DBIDUtil.ensureArray(DBIDUtil.union(insertions, updates2));
      List<List<DistanceResultPair<D>>> reachDistRKNNs = lofResult.getRkNNReach().getRKNNForBulkDBIDs(lrd_ids, k);
      ArrayDBIDs affected_lrd_id_candidates = mergeIDs(reachDistRKNNs, lrd_ids);
      ArrayDBIDs affected_lrd_ids = DBIDUtil.newArray(affected_lrd_id_candidates.size());
      WritableDataStore<Double> new_lrds = computeLRDs(affected_lrd_id_candidates, lofResult.getKNNReach());
      for(DBID id : affected_lrd_id_candidates) {
        Double new_lrd = new_lrds.get(id);
        Double old_lrd = lofResult.getLrds().get(id);
        if(old_lrd == null || !old_lrd.equals(new_lrd)) {
          lofResult.getLrds().put(id, new_lrd);
          affected_lrd_ids.add(id);
        }
      }

      // recompute lofs
      if(stepprog != null) {
        stepprog.beginStep(2, "Recompute LOFS.", logger);
      }
      List<List<DistanceResultPair<D>>> primDistRKNNs = lofResult.getRkNNRefer().getRKNNForBulkDBIDs(affected_lrd_ids, k);
      ArrayDBIDs affected_lof_ids = mergeIDs(primDistRKNNs, affected_lrd_ids, insertions, updates1);
      recomputeLOFs(affected_lof_ids, lofResult);

      // fire result changed
      if(stepprog != null) {
        stepprog.beginStep(3, "Inform listeners.", logger);
View Full Code Here
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
      // recompute lrds
      if(stepprog != null) {
        stepprog.beginStep(2, "Recompute LRDs.", logger);
      }
      ArrayDBIDs lrd_ids = DBIDUtil.ensureArray(updates2);
      List<List<DistanceResultPair<D>>> reachDistRKNNs = lofResult.getRkNNReach().getRKNNForBulkDBIDs(lrd_ids, k);
      ArrayDBIDs affected_lrd_id_candidates = mergeIDs(reachDistRKNNs, lrd_ids);
      ArrayDBIDs affected_lrd_ids = DBIDUtil.newArray(affected_lrd_id_candidates.size());
      WritableDataStore<Double> new_lrds = computeLRDs(affected_lrd_id_candidates, lofResult.getKNNReach());
      for(DBID id : affected_lrd_id_candidates) {
        Double new_lrd = new_lrds.get(id);
        Double old_lrd = lofResult.getLrds().get(id);
        if(!old_lrd.equals(new_lrd)) {
          lofResult.getLrds().put(id, new_lrd);
          affected_lrd_ids.add(id);
        }
      }

      // recompute lofs
      if(stepprog != null) {
        stepprog.beginStep(3, "Recompute LOFS.", logger);
      }
      List<List<DistanceResultPair<D>>> primDistRKNNs = lofResult.getRkNNRefer().getRKNNForBulkDBIDs(affected_lrd_ids, k);
      ArrayDBIDs affected_lof_ids = mergeIDs(primDistRKNNs, affected_lrd_ids, updates1);
      recomputeLOFs(affected_lof_ids, lofResult);

      // fire result changed
      if(stepprog != null) {
        stepprog.beginStep(4, "Inform listeners.", logger);
View Full Code Here
145
146
147
148
149
150
151
152
153
154
155
156
157
      for(int r = 0; r < phi; r++) {
        int end = (int) (part * r);
        if(r == phi - 1) {
          end = size;
        }
        ArrayDBIDs currange = DBIDUtil.newArray(phi + 1);
        for(int i = start; i < end; i++) {
          currange.add(axis.get(i).second);
        }
        start = end;
        dimranges.add(currange);
      }
      ranges.add(dimranges);
View Full Code Here
TOP

Related Classes of de.lmu.ifi.dbs.elki.database.ids.ArrayDBIDs

  • de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans.KMeansPlusPlusInitialMeans
  • de.lmu.ifi.dbs.elki.algorithm.outlier.AbstractAggarwalYuOutlier
  • de.lmu.ifi.dbs.elki.algorithm.outlier.GaussianUniformMixture
  • de.lmu.ifi.dbs.elki.algorithm.outlier.OnlineLOF$LOFKNNListener
  • de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuGLSBackwardSearchAlgorithm
  • de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.CTLuRandomWalkEC
  • de.lmu.ifi.dbs.elki.database.query.rknn.LinearScanRKNNQuery
  • de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNAndRKNNPreprocessor
  • de.lmu.ifi.dbs.elki.index.preprocessed.knn.MaterializeKNNPreprocessor
  • de.lmu.ifi.dbs.elki.index.preprocessed.knn.PartitionApproximationMaterializeKNNPreprocessor
    • Copyright © 2018 www.massapicom. All rights reserved.
    All source code are property of their respective owners. Java is a trademark of Sun Microsystems, Inc and owned by ORACLE Inc. Contact coftware#gmail.com.