How to use

PointerDensityHierarchyRepresentationResult

in

de.lmu.ifi.dbs.elki.algorithm.clustering.hierarchical

/**
 * Constructor.
 *
 * @param pointerresult Hierarchical result
 */
public Instance(PointerHierarchyRepresentationResult pointerresult) {
 this.ids = pointerresult.topologicalSort();
 this.pi = pointerresult.getParentStore();
 this.lambda = pointerresult.getParentDistanceStore();
 this.pointerresult = pointerresult;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  this.coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
}

/**
 * Run the algorithm
 *
 * @param db Database
 * @param relation Relation
 * @return Clustering hierarchy
 */
public PointerDensityHierarchyRepresentationResult run(Database db, Relation<O> relation) {
 final DistanceQuery<O> distQ = db.getDistanceQuery(relation, getDistanceFunction());
 final KNNQuery<O> knnQ = db.getKNNQuery(distQ, minPts);
 // We need array addressing later.
 final ArrayDBIDs ids = DBIDUtil.ensureArray(relation.getDBIDs());
 // 1. Compute the core distances
 // minPts + 1: ignore query point.
 final WritableDoubleDataStore coredists = computeCoreDists(ids, knnQ, minPts);
 final int numedges = ids.size() - 1;
 DoubleLongHeap heap = new DoubleLongMinHeap(numedges);
 // 2. Build spanning tree.
 FiniteProgress mprog = LOG.isVerbose() ? new FiniteProgress("Computing minimum spanning tree (n-1 edges)", numedges, LOG) : null;
 PrimsMinimumSpanningTree.processDense(ids,//
   new HDBSCANAdapter(ids, coredists, distQ), //
   new HeapMSTCollector(heap, mprog, LOG));
 LOG.ensureCompleted(mprog);
 // Storage for pointer representation:
 WritableDBIDDataStore pi = DataStoreUtil.makeDBIDStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC);
 WritableDoubleDataStore lambda = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC, Double.POSITIVE_INFINITY);
 convertToPointerRepresentation(ids, heap, pi, lambda);
 return new PointerDensityHierarchyRepresentationResult(ids, pi, lambda, coredists);
}

/**
 * Run the algorithm
 *
 * @param db Database
 * @param relation Relation
 * @return Clustering hierarchy
 */
public PointerDensityHierarchyRepresentationResult run(Database db, Relation<O> relation) {
 final DistanceQuery<O> distQ = db.getDistanceQuery(relation, getDistanceFunction());
 final KNNQuery<O> knnQ = db.getKNNQuery(distQ, minPts);
 // We need array addressing later.
 final ArrayDBIDs ids = DBIDUtil.ensureArray(relation.getDBIDs());
 // 1. Compute the core distances
 // minPts + 1: ignore query point.
 final WritableDoubleDataStore coredists = computeCoreDists(ids, knnQ, minPts);
 final int numedges = ids.size() - 1;
 DoubleLongHeap heap = new DoubleLongMinHeap(numedges);
 // 2. Build spanning tree.
 FiniteProgress mprog = LOG.isVerbose() ? new FiniteProgress("Computing minimum spanning tree (n-1 edges)", numedges, LOG) : null;
 PrimsMinimumSpanningTree.processDense(ids, //
   new HDBSCANAdapter(ids, coredists, distQ), //
   new HeapMSTCollector(heap, mprog, LOG));
 LOG.ensureCompleted(mprog);
 // Storage for pointer representation:
 WritableDBIDDataStore pi = DataStoreUtil.makeDBIDStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC);
 WritableDoubleDataStore lambda = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC, Double.POSITIVE_INFINITY);
 convertToPointerRepresentation(ids, heap, pi, lambda);
 return new PointerDensityHierarchyRepresentationResult(ids, pi, lambda, distQ.getDistanceFunction().isSquared(), coredists);
}

/**
 * Constructor.
 *
 * @param pointerresult Hierarchical result
 */
public Instance(PointerHierarchyRepresentationResult pointerresult) {
 this.ids = pointerresult.topologicalSort();
 this.pi = pointerresult.getParentStore();
 this.lambda = pointerresult.getParentDistanceStore();
 this.pointerresult = pointerresult;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  this.coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
}

/**
 * Run the algorithm
 *
 * @param db Database
 * @param relation Relation
 * @return Clustering hierarchy
 */
public PointerDensityHierarchyRepresentationResult run(Database db, Relation<O> relation) {
 final DistanceQuery<O> distQ = db.getDistanceQuery(relation, getDistanceFunction());
 final KNNQuery<O> knnQ = db.getKNNQuery(distQ, minPts);
 // We need array addressing later.
 final ArrayDBIDs ids = DBIDUtil.ensureArray(relation.getDBIDs());
 // 1. Compute the core distances
 // minPts + 1: ignore query point.
 final WritableDoubleDataStore coredists = computeCoreDists(ids, knnQ, minPts);
 final int numedges = ids.size() - 1;
 DoubleLongHeap heap = new DoubleLongMinHeap(numedges);
 // 2. Build spanning tree.
 FiniteProgress mprog = LOG.isVerbose() ? new FiniteProgress("Computing minimum spanning tree (n-1 edges)", numedges, LOG) : null;
 PrimsMinimumSpanningTree.processDense(ids, //
   new HDBSCANAdapter(ids, coredists, distQ), //
   new HeapMSTCollector(heap, mprog, LOG));
 LOG.ensureCompleted(mprog);
 // Storage for pointer representation:
 WritableDBIDDataStore pi = DataStoreUtil.makeDBIDStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC);
 WritableDoubleDataStore lambda = DataStoreUtil.makeDoubleStorage(ids, DataStoreFactory.HINT_HOT | DataStoreFactory.HINT_STATIC, Double.POSITIVE_INFINITY);
 convertToPointerRepresentation(ids, heap, pi, lambda);
 return new PointerDensityHierarchyRepresentationResult(ids, pi, lambda, distQ.getDistanceFunction().isSquared(), coredists);
}

/**
 * Constructor.
 *
 * @param pointerresult Hierarchical result
 */
public Instance(PointerHierarchyRepresentationResult pointerresult) {
 this.ids = pointerresult.topologicalSort();
 this.pi = pointerresult.getParentStore();
 this.lambda = pointerresult.getParentDistanceStore();
 this.pointerresult = pointerresult;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  this.coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
}

return new PointerDensityHierarchyRepresentationResult(ids, pi, lambda, coredists);

/**
 * Constructor.
 *
 * @param pointerresult Hierarchical result
 */
public Instance(PointerHierarchyRepresentationResult pointerresult) {
 this.ids = pointerresult.topologicalSort();
 this.pi = pointerresult.getParentStore();
 this.lambda = pointerresult.getParentDistanceStore();
 this.pointerresult = pointerresult;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  this.coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
}

return new PointerDensityHierarchyRepresentationResult(ids, pi, lambda, distQ.getDistanceFunction().isSquared(), coredists);

/**
 * Constructor.
 *
 * @param pointerresult Hierarchical result
 */
public Instance(PointerHierarchyRepresentationResult pointerresult) {
 this.ids = pointerresult.topologicalSort();
 this.pi = pointerresult.getParentStore();
 this.lambda = pointerresult.getParentDistanceStore();
 this.pointerresult = pointerresult;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  this.coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
}

return new PointerDensityHierarchyRepresentationResult(ids, pi, lambda, distQ.getDistanceFunction().isSquared(), coredists);

/**
 * Constructor.
 *
 * @param pointerresult Hierarchical result
 */
public Instance(PointerHierarchyRepresentationResult pointerresult) {
 this.ids = pointerresult.topologicalSort();
 this.pi = pointerresult.getParentStore();
 this.lambda = pointerresult.getParentDistanceStore();
 this.pointerresult = pointerresult;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  this.coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
}

@Override
public Clustering<DendrogramModel> run(Database database) {
 PointerHierarchyRepresentationResult pointerresult = algorithm.run(database);
 DBIDs ids = pointerresult.getDBIDs();
 DBIDDataStore pi = pointerresult.getParentStore();
 DoubleDataStore lambda = pointerresult.getParentDistanceStore();
 DoubleDataStore coredist = null;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
 Clustering<DendrogramModel> result = extractClusters(ids, pi, lambda, coredist);
 result.addChildResult(pointerresult);
 return result;
}

@Override
public Clustering<DendrogramModel> run(Database database) {
 PointerHierarchyRepresentationResult pointerresult = algorithm.run(database);
 DBIDs ids = pointerresult.getDBIDs();
 DBIDDataStore pi = pointerresult.getParentStore();
 DoubleDataStore lambda = pointerresult.getParentDistanceStore();
 DoubleDataStore coredist = null;
 if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
  coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
 }
 Clustering<DendrogramModel> result = extractClusters(ids, pi, lambda, coredist);
 result.addChildResult(pointerresult);
 return result;
}

@Override
public void processNewResult(ResultHierarchy hier, Result newResult) {
 ArrayList<PointerHierarchyRepresentationResult> hrs = ResultUtil.filterResults(hier, newResult, PointerHierarchyRepresentationResult.class);
 for(PointerHierarchyRepresentationResult pointerresult : hrs) {
  DBIDs ids = pointerresult.getDBIDs();
  DBIDDataStore pi = pointerresult.getParentStore();
  DoubleDataStore lambda = pointerresult.getParentDistanceStore();
  DoubleDataStore coredist = null;
  if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
   coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
  }
  Clustering<DendrogramModel> result = inner.extractClusters(ids, pi, lambda, coredist);
  pointerresult.addChildResult(result);
 }
}

@Override
public void processNewResult(ResultHierarchy hier, Result newResult) {
 ArrayList<PointerHierarchyRepresentationResult> hrs = ResultUtil.filterResults(hier, newResult, PointerHierarchyRepresentationResult.class);
 for(PointerHierarchyRepresentationResult pointerresult : hrs) {
  DBIDs ids = pointerresult.getDBIDs();
  DBIDDataStore pi = pointerresult.getParentStore();
  DoubleDataStore lambda = pointerresult.getParentDistanceStore();
  DoubleDataStore coredist = null;
  if(pointerresult instanceof PointerDensityHierarchyRepresentationResult) {
   coredist = ((PointerDensityHierarchyRepresentationResult) pointerresult).getCoreDistanceStore();
  }
  Clustering<DendrogramModel> result = inner.extractClusters(ids, pi, lambda, coredist);
  pointerresult.addChildResult(result);
 }
}