Package | Description |
---|---|
de.lmu.ifi.dbs.elki.algorithm |
Algorithms suitable as a task for the
KDDTask main routine. |
de.lmu.ifi.dbs.elki.algorithm.clustering |
Clustering algorithms.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation |
Correlation clustering algorithms
|
de.lmu.ifi.dbs.elki.algorithm.clustering.correlation.cash |
Helper classes for the
CASH algorithm. |
de.lmu.ifi.dbs.elki.algorithm.clustering.kmeans |
K-means clustering and variations.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace |
Axis-parallel subspace clustering algorithms
The clustering algorithms in this package are instances of both, projected clustering algorithms or
subspace clustering algorithms according to the classical but somewhat obsolete classification schema
of clustering algorithms for axis-parallel subspaces.
|
de.lmu.ifi.dbs.elki.algorithm.clustering.subspace.clique |
Helper classes for the
CLIQUE algorithm. |
de.lmu.ifi.dbs.elki.algorithm.outlier |
Outlier detection algorithms
|
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial |
Spatial outlier detection algorithms
|
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood |
Spatial outlier neighborhood classes
|
de.lmu.ifi.dbs.elki.algorithm.outlier.spatial.neighborhood.weighted |
Weighted Neighborhood definitions.
|
de.lmu.ifi.dbs.elki.algorithm.outlier.subspace |
Subspace outlier detection methods.
|
de.lmu.ifi.dbs.elki.algorithm.statistics |
Statistical analysis algorithms
The algorithms in this package perform statistical analysis of the data
(e.g. compute distributions, distance distributions etc.)
|
de.lmu.ifi.dbs.elki.application.jsmap |
JavaScript based map client - server architecture.
|
de.lmu.ifi.dbs.elki.application.visualization |
Visualization applications in ELKI.
|
de.lmu.ifi.dbs.elki.data |
Basic classes for different data types, database object types and label types.
|
de.lmu.ifi.dbs.elki.data.model |
Cluster models classes for various algorithms.
|
de.lmu.ifi.dbs.elki.data.type |
Data type information, also used for type restrictions.
|
de.lmu.ifi.dbs.elki.database |
ELKI database layer - loading, storing, indexing and accessing data
|
de.lmu.ifi.dbs.elki.database.datastore.memory |
Memory data store implementation for ELKI.
|
de.lmu.ifi.dbs.elki.database.ids |
Database object identification and ID group handling API.
|
de.lmu.ifi.dbs.elki.database.ids.generic |
Database object identification and ID group handling - generic implementations.
|
de.lmu.ifi.dbs.elki.database.ids.integer |
Integer-based DBID implementation --
do not use directly - always use
DBIDUtil . |
de.lmu.ifi.dbs.elki.database.query |
Database queries - computing distances, neighbors, similarities - API and general documentation.
|
de.lmu.ifi.dbs.elki.database.query.distance |
Prepared queries for distances.
|
de.lmu.ifi.dbs.elki.database.query.knn |
Prepared queries for k nearest neighbor (kNN) queries.
|
de.lmu.ifi.dbs.elki.database.relation |
Relations, materialized and virtual (views).
|
de.lmu.ifi.dbs.elki.distance.distancefunction |
Distance functions for use within ELKI.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.external |
Distance functions using external data sources.
|
de.lmu.ifi.dbs.elki.distance.distancefunction.subspace |
Distance functions based on subspaces.
|
de.lmu.ifi.dbs.elki.distance.similarityfunction |
Similarity functions.
|
de.lmu.ifi.dbs.elki.evaluation.roc |
Evaluation of rankings using ROC AUC (Receiver Operation Characteristics - Area Under Curve)
|
de.lmu.ifi.dbs.elki.index |
Index structure implementations
|
de.lmu.ifi.dbs.elki.index.preprocessed.knn |
Indexes providing KNN and rKNN data.
|
de.lmu.ifi.dbs.elki.index.preprocessed.localpca |
Index using a preprocessed local PCA.
|
de.lmu.ifi.dbs.elki.index.preprocessed.preference |
Indexes storing preference vectors.
|
de.lmu.ifi.dbs.elki.index.tree |
Tree-based index structures
|
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants |
M-Tree and variants.
|
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees |
Metrical index structures based on the concepts of the M-Tree
supporting processing of reverse k nearest neighbor queries by
using the k-nn distances of the entries.
|
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkapp | |
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkcop | |
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mkmax | |
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mktrees.mktab | |
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.mtree | |
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.query |
Classes for performing queries (knn, range, ...) on metrical trees.
|
de.lmu.ifi.dbs.elki.index.tree.metrical.mtreevariants.split |
Splitting strategies of nodes in an M-Tree (and variants).
|
de.lmu.ifi.dbs.elki.index.tree.query |
Classes related to generic tree queries.
|
de.lmu.ifi.dbs.elki.index.tree.spatial |
Tree-based index structures for spatial indexing.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.deliclu | |
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.query |
Queries on the R-Tree family of indexes: kNN and range queries.
|
de.lmu.ifi.dbs.elki.index.tree.spatial.rstarvariants.rstar | |
de.lmu.ifi.dbs.elki.index.vafile |
Vector Approximation File
|
de.lmu.ifi.dbs.elki.result |
Result types, representation and handling
|
de.lmu.ifi.dbs.elki.result.optics |
Result classes for OPTICS.
|
de.lmu.ifi.dbs.elki.result.outlier |
Outlier result classes
|
de.lmu.ifi.dbs.elki.result.textwriter |
Text serialization (CSV, Gnuplot, Console, ...)
|
de.lmu.ifi.dbs.elki.utilities.datastructures |
Basic memory structures such as heaps and object hierarchies.
|
de.lmu.ifi.dbs.elki.utilities.datastructures.arraylike |
Common API for accessing objects that are "array-like", including lists, numerical vectors, database vectors and arrays.
|
de.lmu.ifi.dbs.elki.utilities.exceptions |
Exception classes and common exception messages.
|
de.lmu.ifi.dbs.elki.visualization.visualizers.scatterplot |
Visualizers based on scatterplots.
|
Modifier and Type | Method and Description |
---|---|
CollectionResult<CTriple<DBID,DBID,Double>> |
MaterializeDistances.run(Database database,
Relation<O> relation)
Iterates over all points in the database.
|
CollectionResult<CTriple<DBID,DBID,Double>> |
MaterializeDistances.run(Database database,
Relation<O> relation)
Iterates over all points in the database.
|
Modifier and Type | Field and Description |
---|---|
private WritableDataStore<DBID> |
SLINK.pi
The values of the function Pi of the pointer representation.
|
Modifier and Type | Method and Description |
---|---|
private DBID |
DeLiClu.getStartObject(Relation<NV> relation)
Returns the id of the start object for the run method.
|
private DBID |
SLINK.lastObjectInCluster(DBID id,
D stopdist,
DataStore<DBID> pi,
DataStore<D> lambda) |
Modifier and Type | Method and Description |
---|---|
int |
SLINK.CompareByLambda.compare(DBID id1,
DBID id2) |
protected void |
AbstractProjectedDBSCAN.expandCluster(LocallyWeightedDistanceFunction.Instance<V> distFunc,
RangeQuery<V,DoubleDistance> rangeQuery,
DBID startObjectID,
FiniteProgress objprog,
IndefiniteProgress clusprog)
ExpandCluster function of DBSCAN.
|
protected void |
DBSCAN.expandCluster(Relation<O> relation,
RangeQuery<O,D> rangeQuery,
DBID startObjectID,
FiniteProgress objprog,
IndefiniteProgress clusprog)
DBSCAN-function expandCluster.
|
protected void |
SNNClustering.expandCluster(SimilarityQuery<O,IntegerDistance> snnInstance,
DBID startObjectID,
FiniteProgress objprog,
IndefiniteProgress clusprog)
DBSCAN-function expandCluster adapted to SNN criterion.
|
protected void |
OPTICS.expandClusterOrder(ClusterOrderResult<D> clusterOrder,
Database database,
RangeQuery<O,D> rangeQuery,
DBID objectID,
D epsilon,
FiniteProgress progress)
OPTICS-function expandClusterOrder.
|
protected void |
OPTICS.expandClusterOrderDouble(ClusterOrderResult<DoubleDistance> clusterOrder,
Database database,
RangeQuery<O,DoubleDistance> rangeQuery,
DBID objectID,
DoubleDistance epsilon,
FiniteProgress progress)
OPTICS-function expandClusterOrder.
|
protected ArrayModifiableDBIDs |
SNNClustering.findSNNNeighbors(SimilarityQuery<O,IntegerDistance> snnInstance,
DBID queryObject)
Returns the shared nearest neighbors of the specified query object in the
given database.
|
private DBID |
SLINK.lastObjectInCluster(DBID id,
D stopdist,
DataStore<DBID> pi,
DataStore<D> lambda) |
private void |
SLINK.step1(DBID newID)
First step: Initialize P(id) = id, L(id) = infinity.
|
private void |
SLINK.step2(DBID newID,
DBIDs processedIDs,
DistanceQuery<O,D> distFunc,
WritableDataStore<D> m)
Second step: Determine the pairwise distances from all objects in the
pointer representation to the new object with the specified id.
|
private void |
SLINK.step3(DBID newID,
DBIDs processedIDs,
WritableDataStore<D> m)
Third step: Determine the values for P and L
|
private void |
SLINK.step4(DBID newID,
DBIDs processedIDs)
Fourth step: Actualize the clusters if necessary
|
Modifier and Type | Method and Description |
---|---|
private Clustering<Model> |
SLINK.extractClusters_erich(DBIDs ids,
DataStore<DBID> pi,
DataStore<D> lambda,
int minclusters)
Extract all clusters from the pi-lambda-representation.
|
private Clustering<DendrogramModel<D>> |
SLINK.extractClusters(DBIDs ids,
DataStore<DBID> pi,
DataStore<D> lambda,
int minclusters)
Extract all clusters from the pi-lambda-representation.
|
private DBID |
SLINK.lastObjectInCluster(DBID id,
D stopdist,
DataStore<DBID> pi,
DataStore<D> lambda) |
private Cluster<DendrogramModel<D>> |
SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids,
Map<DBID,D> cluster_distances,
DataStore<DBID> pi,
DataStore<D> lambda,
ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier,
FiniteProgress progress) |
private Cluster<DendrogramModel<D>> |
SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids,
Map<DBID,D> cluster_distances,
DataStore<DBID> pi,
DataStore<D> lambda,
ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier,
FiniteProgress progress) |
private Cluster<DendrogramModel<D>> |
SLINK.root(Map<DBID,ModifiableDBIDs> cluster_ids,
Map<DBID,D> cluster_distances,
DataStore<DBID> pi,
DataStore<D> lambda,
ModifiableHierarchy<Cluster<DendrogramModel<D>>> hier,
FiniteProgress progress) |
Constructor and Description |
---|
ORCLUS.ORCLUSCluster(V o,
DBID id,
V factory)
Creates a new cluster containing the specified object o.
|
Modifier and Type | Field and Description |
---|---|
private Map<HyperBoundingBox,Map<DBID,Double>> |
CASHIntervalSplit.f_maxima
Caches maximum function values for given intervals, used for better split
performance.
|
private Map<HyperBoundingBox,Map<DBID,Double>> |
CASHIntervalSplit.f_minima
Caches minimum function values for given intervals, used for better split
performance.
|
Modifier and Type | Method and Description |
---|---|
protected double |
KMeansPlusPlusInitialMeans.initialWeights(double[] weights,
ArrayDBIDs ids,
DBID latest,
DistanceQuery<? super V,D> distQ)
Initialize the weight list.
|
protected double |
KMeansPlusPlusInitialMeans.updateWeights(double[] weights,
ArrayDBIDs ids,
DBID latest,
DistanceQuery<? super V,D> distQ)
Update the weight list.
|
protected double |
KMeansPlusPlusInitialMeans.updateWeights(double[] weights,
ArrayDBIDs ids,
DBID latest,
PrimitiveDoubleDistanceFunction<V> distF,
Relation<V> rel)
Update the weight list.
|
Modifier and Type | Method and Description |
---|---|
private Map<DBID,PROCLUS.PROCLUSCluster> |
PROCLUS.assignPoints(Map<DBID,Set<Integer>> dimensions,
Relation<V> database)
Assigns the objects to the clusters.
|
private Map<DBID,Set<Integer>> |
PROCLUS.findDimensions(DBIDs medoids,
Relation<V> database,
DistanceQuery<V,DoubleDistance> distFunc,
RangeQuery<V,DoubleDistance> rangeQuery)
Determines the set of correlated dimensions for each medoid in the
specified medoid set.
|
private Map<DBID,List<DistanceResultPair<DoubleDistance>>> |
PROCLUS.getLocalities(DBIDs medoids,
Relation<V> database,
DistanceQuery<V,DoubleDistance> distFunc,
RangeQuery<V,DoubleDistance> rangeQuery)
Computes the localities of the specified medoids: for each medoid m the
objects in the sphere centered at m with radius minDist are determined,
where minDist is the minimum distance between medoid m and any other medoid
m_i.
|
Modifier and Type | Method and Description |
---|---|
private Map<DBID,PROCLUS.PROCLUSCluster> |
PROCLUS.assignPoints(Map<DBID,Set<Integer>> dimensions,
Relation<V> database)
Assigns the objects to the clusters.
|
private ModifiableDBIDs |
PROCLUS.computeBadMedoids(Map<DBID,PROCLUS.PROCLUSCluster> clusters,
int threshold)
Computes the bad medoids, where the medoid of a cluster with less than the
specified threshold of objects is bad.
|
private double |
PROCLUS.evaluateClusters(Map<DBID,PROCLUS.PROCLUSCluster> clusters,
Map<DBID,Set<Integer>> dimensions,
Relation<V> database)
Evaluates the quality of the clusters.
|
private double |
PROCLUS.evaluateClusters(Map<DBID,PROCLUS.PROCLUSCluster> clusters,
Map<DBID,Set<Integer>> dimensions,
Relation<V> database)
Evaluates the quality of the clusters.
|
Modifier and Type | Method and Description |
---|---|
boolean |
CLIQUEUnit.addFeatureVector(DBID id,
V vector)
Adds the id of the specified feature vector to this unit, if this unit
contains the feature vector.
|
Modifier and Type | Field and Description |
---|---|
DBID |
HilOut.HilFeature.id
Object ID
|
Modifier and Type | Method and Description |
---|---|
private Heap<DoubleObjPair<DBID>> |
ABOD.calcDistsandNN(Relation<V> data,
KernelMatrix kernelMatrix,
int sampleSize,
DBIDRef aKey,
WritableDoubleDataStore dists) |
private Heap<DoubleObjPair<DBID>> |
ABOD.calcDistsandRNDSample(Relation<V> data,
KernelMatrix kernelMatrix,
int sampleSize,
DBIDRef aKey,
WritableDoubleDataStore dists) |
Modifier and Type | Method and Description |
---|---|
private void |
ABOD.generateExplanation(Relation<V> data,
DBID key,
DBIDs expList) |
protected void |
HilOut.HilFeature.insert(DBID id,
double dt,
int k)
insert function inserts a nearest neighbor into a features nn list and
its distance
|
private double |
HilOut.HilbertFeatures.maxDistLevel(DBID id,
int level)
maxDist function calculate the maximal Distance from Vector p to the
border of the corresponding r-region at the given level
|
private double |
HilOut.HilbertFeatures.minDistLevel(DBID id,
int level)
minDist function calculate the minimal Distance from Vector p to the
border of the corresponding r-region at the given level
|
Constructor and Description |
---|
HilOut.HilFeature(DBID id,
Heap<DoubleDistanceResultPair> nn)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
private Pair<DBID,Double> |
CTLuGLSBackwardSearchAlgorithm.singleIteration(Relation<V> relationx,
Relation<? extends NumberVector<?,?>> relationy)
Run a single iteration of the GLS-SOD modeling step
|
Modifier and Type | Method and Description |
---|---|
DBIDs |
AbstractPrecomputedNeighborhood.getNeighborDBIDs(DBID reference) |
DBIDs |
NeighborSetPredicate.getNeighborDBIDs(DBID reference)
Get the neighbors of a reference object for DBSCAN.
|
Modifier and Type | Method and Description |
---|---|
Collection<DoubleObjPair<DBID>> |
UnweightedNeighborhoodAdapter.getWeightedNeighbors(DBID reference) |
Collection<DoubleObjPair<DBID>> |
LinearWeightedExtendedNeighborhood.getWeightedNeighbors(DBID reference) |
Collection<DoubleObjPair<DBID>> |
WeightedNeighborSetPredicate.getWeightedNeighbors(DBID reference)
Get the neighbors of a reference object for DBSCAN.
|
Modifier and Type | Method and Description |
---|---|
Collection<DoubleObjPair<DBID>> |
UnweightedNeighborhoodAdapter.getWeightedNeighbors(DBID reference) |
Collection<DoubleObjPair<DBID>> |
LinearWeightedExtendedNeighborhood.getWeightedNeighbors(DBID reference) |
Collection<DoubleObjPair<DBID>> |
WeightedNeighborSetPredicate.getWeightedNeighbors(DBID reference)
Get the neighbors of a reference object for DBSCAN.
|
Modifier and Type | Method and Description |
---|---|
private List<DoubleDistanceResultPair> |
OUTRES.subsetNeighborhoodQuery(List<DistanceResultPair<DoubleDistance>> neighc,
DBID dbid,
PrimitiveDoubleDistanceFunction<? super V> df,
double adjustedEps,
OUTRES.KernelDensityEstimator kernel)
Refine neighbors within a subset.
|
Modifier and Type | Method and Description |
---|---|
private void |
DistanceStatisticsWithClasses.shrinkHeap(TreeSet<DoubleObjPair<DBID>> hotset,
int k) |
Modifier and Type | Method and Description |
---|---|
private DBID |
JSONWebServer.stringToDBID(String query)
Parse a string into a DBID.
|
Modifier and Type | Method and Description |
---|---|
protected void |
JSONWebServer.bundleToJSON(JSONBuffer re,
DBID id)
Serialize an object bundle to JSON.
|
Modifier and Type | Field and Description |
---|---|
protected HashMap<DBID,Double> |
KNNExplorer.ExplorerWindow.distancecache |
Modifier and Type | Method and Description |
---|---|
private Element |
KNNExplorer.ExplorerWindow.plotSeries(DBID idx,
int resolution)
Plot a single time series.
|
Modifier and Type | Method and Description |
---|---|
int |
VectorUtil.SortDBIDsBySingleDimension.compare(DBID id1,
DBID id2) |
Modifier and Type | Field and Description |
---|---|
private DBID |
MedoidModel.medoid
Cluster medoid
|
Modifier and Type | Method and Description |
---|---|
DBID |
MedoidModel.getMedoid() |
Modifier and Type | Method and Description |
---|---|
void |
MedoidModel.setMedoid(DBID medoid) |
Constructor and Description |
---|
MedoidModel(DBID medoid)
Constructor with medoid
|
Modifier and Type | Field and Description |
---|---|
static SimpleTypeInformation<DBID> |
TypeUtil.DBID
Database IDs
|
Modifier and Type | Method and Description |
---|---|
private void |
HashmapDatabase.doDelete(DBID id)
Removes the object with the specified id from this database.
|
void |
DatabaseEventManager.fireObjectInserted(DBID insertion)
Convenience method, calls
fireObjectChanged(insertion,
DataStoreEvent.Type.INSERT) . |
protected void |
DatabaseEventManager.fireObjectRemoved(DBID deletion)
Convenience method, calls
fireObjectChanged(deletion,
DataStoreEvent.Type.DELETE) . |
SingleObjectBundle |
AbstractDatabase.getBundle(DBID id) |
SingleObjectBundle |
Database.getBundle(DBID id)
Returns the DatabaseObject represented by the specified id.
|
private void |
HashmapDatabase.restoreID(DBID id)
Makes the given id reusable for new insertion operations.
|
Modifier and Type | Field and Description |
---|---|
private Map<DBID,Object[]> |
MapRecordStore.data
Storage Map
|
private Map<DBID,T> |
MapStore.data
Storage Map
|
Constructor and Description |
---|
MapRecordStore(int rlen,
Map<DBID,Object[]> data)
Constructor with existing data.
|
MapStore(Map<DBID,T> data)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
static DBID |
DBIDUtil.generateSingleDBID()
Generate a single DBID
|
DBID |
DBIDFactory.generateSingleDBID()
Generate a single DBID
|
DBID |
EmptyDBIDs.get(int i) |
DBID |
ArrayDBIDs.get(int i)
Get the i'th entry (starting at 0)
|
DBID |
DBIDRef.getDBID()
Get the referenced
DBID . |
DBID |
EmptyDBIDs.EmptyDBIDIterator.getDBID() |
DBID |
DBID.getDBID()
Deprecated.
When the object is known to be a DBID, the usage of this method
is pointless, therefore it is marked as deprecated to cause a
warning.
|
DBID |
DBIDIter.getDBID()
Get the referenced
DBID . |
DBID |
DBIDPair.getFirst()
Getter for first
|
DBID |
DBIDPair.getSecond()
Getter for second element in pair
|
static DBID |
DBIDUtil.importInteger(int id)
Import an Integer DBID.
|
DBID |
DBIDFactory.importInteger(int id)
Import an integer ID
|
DBID |
ArrayModifiableDBIDs.remove(int i)
Remove the i'th entry (starting at 0)
|
DBID |
ArrayModifiableDBIDs.set(int i,
DBID newval)
Replace the i'th entry (starting at 0)
|
Modifier and Type | Method and Description |
---|---|
ByteBufferSerializer<DBID> |
DBIDUtil.getDBIDSerializer()
Get a serializer for DBIDs
|
ByteBufferSerializer<DBID> |
DBIDFactory.getDBIDSerializer()
Get a serializer for DBIDs
|
ByteBufferSerializer<DBID> |
DBIDUtil.getDBIDSerializerStatic()
Get a serializer for DBIDs with static size
|
FixedSizeByteBufferSerializer<DBID> |
DBIDFactory.getDBIDSerializerStatic()
Get a serializer for DBIDs with static size
|
Class<? extends DBID> |
DBIDFactory.getTypeRestriction()
Get type restriction
|
Iterator<DBID> |
EmptyDBIDs.iterator() |
Iterator<DBID> |
DBIDs.iterator()
Deprecated.
Use
DBIDIter API instead. |
Modifier and Type | Method and Description |
---|---|
static void |
DBIDUtil.deallocateSingleDBID(DBID id)
Return a single DBID for reuse.
|
void |
DBIDFactory.deallocateSingleDBID(DBID id)
Return a single DBID for reuse.
|
DBID |
ArrayModifiableDBIDs.set(int i,
DBID newval)
Replace the i'th entry (starting at 0)
|
Modifier and Type | Method and Description |
---|---|
void |
ArrayModifiableDBIDs.sort(Comparator<? super DBID> comparator)
Sort the DBID set.
|
Modifier and Type | Field and Description |
---|---|
(package private) DBID |
DBIDIterAdapter.cur
Current DBID
|
Modifier and Type | Field and Description |
---|---|
(package private) Iterator<DBID> |
DBIDIterAdapter.iter
The real iterator
|
Modifier and Type | Method and Description |
---|---|
DBID |
UnmodifiableArrayDBIDs.get(int i) |
DBID |
MaskedDBIDs.DBIDItr.getDBID() |
DBID |
MaskedDBIDs.InvDBIDItr.getDBID() |
DBID |
DBIDIterAdapter.getDBID() |
DBID |
MaskedDBIDs.Itr.next() |
DBID |
MaskedDBIDs.InvItr.next() |
Modifier and Type | Method and Description |
---|---|
Iterator<DBID> |
UnmodifiableArrayDBIDs.iterator() |
Iterator<DBID> |
UnmodifiableDBIDs.iterator() |
Iterator<DBID> |
MergedDBIDs.iterator() |
Iterator<DBID> |
MaskedDBIDs.iterator() |
Modifier and Type | Method and Description |
---|---|
void |
GenericArrayModifiableDBIDs.sort(Comparator<? super DBID> comparator) |
Constructor and Description |
---|
DBIDIterAdapter(Iterator<DBID> iter)
Constructor.
|
Modifier and Type | Class and Description |
---|---|
(package private) class |
IntegerDBID
Database ID object.
|
Modifier and Type | Method and Description |
---|---|
DBID |
IntegerDBID.DynamicSerializer.fromByteBuffer(ByteBuffer buffer) |
DBID |
IntegerDBID.StaticSerializer.fromByteBuffer(ByteBuffer buffer) |
DBID |
ReusingDBIDFactory.generateSingleDBID() |
DBID |
SimpleDBIDFactory.generateSingleDBID() |
DBID |
TrivialDBIDFactory.generateSingleDBID() |
DBID |
TroveArrayDBIDs.get(int index) |
DBID |
IntegerArrayStaticDBIDs.get(int i) |
DBID |
IntegerDBID.get(int i) |
DBID |
IntegerDBIDRange.get(int i) |
DBID |
TroveArrayDBIDs.DBIDItr.getDBID() |
DBID |
IntegerArrayStaticDBIDs.DBIDItr.getDBID() |
DBID |
IntegerDBID.getDBID() |
DBID |
IntegerDBID.DBIDItr.getDBID() |
DBID |
IntegerDBIDRange.DBIDItr.getDBID() |
DBID |
TroveHashSetModifiableDBIDs.DBIDItr.getDBID() |
DBID |
SimpleDBIDFactory.importInteger(int id) |
DBID |
TrivialDBIDFactory.importInteger(int id) |
DBID |
IntegerArrayStaticDBIDs.Itr.next() |
DBID |
TroveIteratorAdapter.next() |
DBID |
IntegerDBID.Itr.next() |
DBID |
IntegerDBIDRange.Itr.next() |
DBID |
TroveArrayModifiableDBIDs.remove(int index) |
DBID |
TroveArrayModifiableDBIDs.set(int index,
DBID element) |
Modifier and Type | Method and Description |
---|---|
ByteBufferSerializer<DBID> |
SimpleDBIDFactory.getDBIDSerializer() |
ByteBufferSerializer<DBID> |
TrivialDBIDFactory.getDBIDSerializer() |
FixedSizeByteBufferSerializer<DBID> |
SimpleDBIDFactory.getDBIDSerializerStatic() |
FixedSizeByteBufferSerializer<DBID> |
TrivialDBIDFactory.getDBIDSerializerStatic() |
Class<? extends DBID> |
SimpleDBIDFactory.getTypeRestriction() |
Class<? extends DBID> |
TrivialDBIDFactory.getTypeRestriction() |
Iterator<DBID> |
TroveArrayDBIDs.iterator() |
Iterator<DBID> |
IntegerArrayStaticDBIDs.iterator() |
Iterator<DBID> |
IntegerDBID.iterator() |
Iterator<DBID> |
IntegerDBIDRange.iterator() |
Iterator<DBID> |
TroveHashSetModifiableDBIDs.iterator() |
Modifier and Type | Method and Description |
---|---|
void |
ReusingDBIDFactory.deallocateSingleDBID(DBID id) |
void |
SimpleDBIDFactory.deallocateSingleDBID(DBID id) |
void |
TrivialDBIDFactory.deallocateSingleDBID(DBID id) |
int |
IntegerDBID.DynamicSerializer.getByteSize(DBID object) |
int |
IntegerDBID.StaticSerializer.getByteSize(DBID object) |
DBID |
TroveArrayModifiableDBIDs.set(int index,
DBID element) |
void |
IntegerDBID.DynamicSerializer.toByteBuffer(ByteBuffer buffer,
DBID object) |
void |
IntegerDBID.StaticSerializer.toByteBuffer(ByteBuffer buffer,
DBID object) |
Modifier and Type | Method and Description |
---|---|
void |
TroveArrayModifiableDBIDs.sort(Comparator<? super DBID> comparator) |
Modifier and Type | Field and Description |
---|---|
(package private) DBID |
DoubleDistanceResultPair.id
Object ID
|
Modifier and Type | Method and Description |
---|---|
DBID |
DoubleDistanceResultPair.getDBID() |
DBID |
GenericDistanceResultPair.getDBID()
Getter for second element in pair
|
DBID |
DoubleDistanceResultPair.getSecond()
Deprecated.
Use
DoubleDistanceResultPair.getDBID() for clearness. |
Modifier and Type | Method and Description |
---|---|
void |
DistanceResultPair.setID(DBID second)
Setter for second
|
void |
DoubleDistanceResultPair.setID(DBID id) |
void |
GenericDistanceResultPair.setID(DBID second)
Setter for second
|
Constructor and Description |
---|
DoubleDistanceResultPair(double distance,
DBID id)
Constructor.
|
GenericDistanceResultPair(D first,
DBID second)
Canonical constructor
|
Modifier and Type | Method and Description |
---|---|
D |
SpatialDistanceQuery.minDist(SpatialComparable mbr,
DBID id)
Computes the minimum distance between the given MBR and the FeatureVector
object according to this distance function.
|
D |
SpatialPrimitiveDistanceQuery.minDist(SpatialComparable mbr,
DBID id) |
Constructor and Description |
---|
DBIDDistanceQuery(Relation<DBID> relation,
DBIDDistanceFunction<D> distanceFunction)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
DBID |
KNNUtil.DBIDView.get(int i) |
DBID |
KNNUtil.DBIDItr.getDBID() |
DBID |
KNNUtil.DBIDIterator.next() |
Modifier and Type | Method and Description |
---|---|
Iterator<DBID> |
KNNUtil.DBIDView.iterator() |
Modifier and Type | Method and Description |
---|---|
void |
KNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps)
Bulk query method configured by a map.
|
void |
PreprocessorKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) |
void |
LinearScanKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) |
void |
LinearScanPrimitiveDistanceKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) |
Modifier and Type | Method and Description |
---|---|
DBID |
DBIDView.get(DBIDRef id) |
Modifier and Type | Method and Description |
---|---|
SimpleTypeInformation<DBID> |
DBIDView.getDataTypeInformation() |
Modifier and Type | Method and Description |
---|---|
void |
DBIDView.set(DBIDRef id,
DBID val) |
Modifier and Type | Method and Description |
---|---|
<O extends DBID> |
AbstractDBIDDistanceFunction.instantiate(Relation<O> database) |
Modifier and Type | Method and Description |
---|---|
SimpleTypeInformation<DBID> |
AbstractDBIDDistanceFunction.getInputTypeRestriction() |
Modifier and Type | Method and Description |
---|---|
private void |
NumberDistanceParser.put(DBID id1,
DBID id2,
D distance,
Map<DBIDPair,D> cache)
Puts the specified distance value for the given ids to the distance cache.
|
Modifier and Type | Method and Description |
---|---|
double |
AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance.weightedDistance(DBID id1,
DBID id2,
BitSet weightVector)
Computes the weighted distance between the two specified vectors
according to the given preference vector.
|
double |
AbstractPreferenceVectorBasedCorrelationDistanceFunction.Instance.weightedPrefereneceVectorDistance(DBID id1,
DBID id2)
Computes the weighted distance between the two specified data vectors
according to their preference vectors.
|
Modifier and Type | Field and Description |
---|---|
protected Relation<? extends DBID> |
AbstractDBIDSimilarityFunction.database
The database we work on
|
Modifier and Type | Method and Description |
---|---|
D |
DBIDSimilarityFunction.similarity(DBID id1,
DBID id2)
Computes the similarity between two given DatabaseObjects according to this
similarity function.
|
Constructor and Description |
---|
AbstractDBIDSimilarityFunction(Relation<? extends DBID> database)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
Pair<D,DBID> |
ROC.DistanceResultAdapter.next() |
DoubleObjPair<DBID> |
ROC.OutlierScoreAdapter.next() |
Modifier and Type | Method and Description |
---|---|
static <C extends Comparable<? super C>> |
ROC.materializeROC(int size,
SetDBIDs ids,
Iterator<? extends PairInterface<C,DBID>> nei)
Compute a ROC curve given a set of positive IDs and a sorted list of
(comparable, ID)s, where the comparable object is used to decided when two
objects are interchangeable.
|
Modifier and Type | Method and Description |
---|---|
boolean |
AbstractIndex.delete(DBID id) |
boolean |
Index.delete(DBID id)
Deletes the specified object from this index.
|
void |
AbstractIndex.insert(DBID id) |
void |
Index.insert(DBID id)
Inserts the specified object into this index.
|
protected O |
AbstractRefiningIndex.refine(DBID id)
Refine a given object (and count the refinement!)
|
protected D |
AbstractRefiningIndex.AbstractRangeQuery.refine(DBID id,
O q)
Refinement distance computation.
|
protected D |
AbstractRefiningIndex.AbstractKNNQuery.refine(DBID id,
O q)
Refinement distance computation.
|
Modifier and Type | Method and Description |
---|---|
void |
AbstractRefiningIndex.AbstractKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) |
Modifier and Type | Method and Description |
---|---|
boolean |
MaterializeKNNPreprocessor.delete(DBID id) |
KNNResult<D> |
MaterializeKNNAndRKNNPreprocessor.getKNN(DBID id)
Returns the materialized kNNs of the specified id.
|
void |
MaterializeKNNPreprocessor.insert(DBID id) |
Modifier and Type | Method and Description |
---|---|
protected abstract Collection<DistanceResultPair<DoubleDistance>> |
AbstractFilteredPCAIndex.objectsForPCA(DBID id)
Returns the objects to be considered within the PCA for the specified query
object.
|
protected KNNResult<DoubleDistance> |
KNNQueryFilteredPCAIndex.objectsForPCA(DBID id) |
protected DistanceDBIDResult<DoubleDistance> |
RangeQueryFilteredPCAIndex.objectsForPCA(DBID id) |
Modifier and Type | Method and Description |
---|---|
private BitSet |
HiSCPreferenceVectorIndex.determinePreferenceVector(Relation<V> relation,
DBID id,
DBIDs neighborIDs,
StringBuffer msg)
Determines the preference vector according to the specified neighbor ids.
|
Modifier and Type | Field and Description |
---|---|
private DBID |
AbstractLeafEntry.id
Holds the id of the object (node or data object) represented by this entry.
|
Modifier and Type | Method and Description |
---|---|
DBID |
AbstractLeafEntry.getDBID() |
DBID |
LeafEntry.getDBID()
Get the DBID of this leaf entry.
|
Constructor and Description |
---|
AbstractLeafEntry(DBID id)
Provides a new AbstractEntry with the specified id.
|
Modifier and Type | Field and Description |
---|---|
private DBID |
MTreeDirectoryEntry.routingObjectID
The id of routing object of this entry.
|
Modifier and Type | Method and Description |
---|---|
DBID |
MTreeEntry.getRoutingObjectID()
Returns the id of the underlying database object of this entry, if this
entry is a leaf entry, the id of the routing object, otherwise.
|
DBID |
MTreeDirectoryEntry.getRoutingObjectID()
Returns the id of the routing object of this entry.
|
DBID |
MTreeLeafEntry.getRoutingObjectID()
Returns the id of the underlying data object of this entry.
|
Modifier and Type | Method and Description |
---|---|
void |
AbstractMTreeNode.adjustEntry(E entry,
DBID routingObjectID,
D parentDistance,
AbstractMTree<O,D,N,E> mTree)
Adjusts the parameters of the entry representing this node (e.g. after
insertion of new objects).
|
D |
AbstractMTreeNode.coveringRadius(DBID routingObjectID,
AbstractMTree<O,D,N,E> mTree)
Determines and returns the covering radius of this node.
|
protected abstract E |
AbstractMTree.createNewDirectoryEntry(N node,
DBID routingObjectID,
D parentDistance)
Creates a new directory entry representing the specified node.
|
private IndexTreePath<E> |
AbstractMTree.createNewRoot(N oldRoot,
N newNode,
DBID firstRoutingObjectID,
DBID secondRoutingObjectID)
Creates a new root node that points to the two specified child nodes and
return the path to the new root.
|
protected D |
AbstractMTree.distance(DBID id1,
DBID id2)
Returns the distance between the two specified ids.
|
protected D |
AbstractMTree.distance(DBID id1,
O o2)
Returns the distance between the given object and the id.
|
protected void |
AbstractMTree.doKNNQuery(DBID q,
KNNHeap<D> knnList)
Performs a k-nearest neighbor query for the given FeatureVector with the
given parameter k and the according distance function.
|
protected List<DistanceEntry<D,E>> |
AbstractMTree.getSortedEntries(N node,
DBID q)
Sorts the entries of the specified node according to their minimum distance
to the specified object.
|
void |
MTreeEntry.setRoutingObjectID(DBID objectID)
Sets the id of the underlying database object of this entry, if this entry
is a leaf entry, the id of the routing object, otherwise.
|
void |
MTreeDirectoryEntry.setRoutingObjectID(DBID objectID)
Sets the id of the routing object of this entry.
|
void |
MTreeLeafEntry.setRoutingObjectID(DBID objectID)
todo ok
|
Modifier and Type | Method and Description |
---|---|
protected void |
AbstractMTree.batchNN(N node,
DBIDs ids,
Map<DBID,KNNHeap<D>> knnLists)
Deprecated.
Change to use by-object NN lookups instead.
|
Constructor and Description |
---|
MTreeDirectoryEntry(DBID objectID,
D parentDistance,
Integer nodeID,
D coveringRadius)
Provides a new MTreeDirectoryEntry with the given parameters.
|
MTreeLeafEntry(DBID objectID,
D parentDistance)
Provides a new MTreeLeafEntry object with the given parameters.
|
Modifier and Type | Method and Description |
---|---|
protected abstract void |
AbstractMkTreeUnified.kNNdistanceAdjustment(E entry,
Map<DBID,KNNHeap<D>> knnLists)
Performs a distance adjustment in the subtree of the specified root entry.
|
Modifier and Type | Method and Description |
---|---|
void |
MkAppTreeNode.adjustEntry(MkAppEntry<D> entry,
DBID routingObjectID,
D parentDistance,
AbstractMTree<O,D,MkAppTreeNode<O,D>,MkAppEntry<D>> mTree)
Adjusts the parameters of the entry representing this node.
|
protected MkAppEntry<D> |
MkAppTree.createNewDirectoryEntry(MkAppTreeNode<O,D> node,
DBID routingObjectID,
D parentDistance)
Creates a new directory entry representing the specified node.
|
protected MkAppEntry<D> |
MkAppTreeIndex.createNewLeafEntry(DBID id,
O object,
D parentDistance)
Creates a new leaf entry representing the specified data object in the
specified subtree.
|
boolean |
MkAppTreeIndex.delete(DBID id)
Throws an UnsupportedOperationException since deletion of objects is not
yet supported by an M-Tree.
|
void |
MkAppTreeIndex.insert(DBID id) |
Modifier and Type | Method and Description |
---|---|
private void |
MkAppTree.adjustApproximatedKNNDistances(MkAppEntry<D> entry,
Map<DBID,KNNList<D>> knnLists)
Adjusts the knn distance in the subtree of the specified root entry.
|
private List<D> |
MkAppTree.getMeanKNNList(DBIDs ids,
Map<DBID,KNNList<D>> knnLists) |
Constructor and Description |
---|
MkAppDirectoryEntry(DBID objectID,
D parentDistance,
Integer nodeID,
D coveringRadius,
PolynomialApproximation approximation)
Provides a new MkCoPDirectoryEntry with the given parameters.
|
MkAppLeafEntry(DBID objectID,
D parentDistance,
PolynomialApproximation approximation)
Provides a new MkAppLeafEntry with the given parameters.
|
Modifier and Type | Method and Description |
---|---|
void |
MkCoPTreeNode.adjustEntry(MkCoPEntry<D> entry,
DBID routingObjectID,
D parentDistance,
AbstractMTree<O,D,MkCoPTreeNode<O,D>,MkCoPEntry<D>> mTree) |
protected MkCoPEntry<D> |
MkCoPTree.createNewDirectoryEntry(MkCoPTreeNode<O,D> node,
DBID routingObjectID,
D parentDistance)
Creates a new directory entry representing the specified node.
|
protected MkCoPEntry<D> |
MkCoPTreeIndex.createNewLeafEntry(DBID id,
O object,
D parentDistance)
Creates a new leaf entry representing the specified data object in the
specified subtree.
|
boolean |
MkCoPTreeIndex.delete(DBID id)
Throws an UnsupportedOperationException since deletion of objects is not
yet supported by an M-Tree.
|
void |
MkCoPTreeIndex.insert(DBID id) |
Modifier and Type | Method and Description |
---|---|
private void |
MkCoPTree.adjustApproximatedKNNDistances(MkCoPEntry<D> entry,
Map<DBID,KNNList<D>> knnLists)
Adjusts the knn distance in the subtree of the specified root entry.
|
Constructor and Description |
---|
MkCoPDirectoryEntry(DBID objectID,
D parentDistance,
Integer nodeID,
D coveringRadius,
ApproximationLine conservativeApproximation)
Provides a new MkCoPDirectoryEntry with the given parameters.
|
MkCoPLeafEntry(DBID objectID,
D parentDistance,
ApproximationLine conservativeApproximation,
ApproximationLine progressiveApproximation)
Provides a new MkCoPLeafEntry with the given parameters.
|
Modifier and Type | Method and Description |
---|---|
void |
MkMaxTreeNode.adjustEntry(MkMaxEntry<D> entry,
DBID routingObjectID,
D parentDistance,
AbstractMTree<O,D,MkMaxTreeNode<O,D>,MkMaxEntry<D>> mTree)
Calls the super method and adjust additionally the k-nearest neighbor
distance of this node as the maximum of the k-nearest neighbor distances of
all its entries.
|
protected MkMaxEntry<D> |
MkMaxTree.createNewDirectoryEntry(MkMaxTreeNode<O,D> node,
DBID routingObjectID,
D parentDistance) |
protected MkMaxLeafEntry<D> |
MkMaxTreeIndex.createNewLeafEntry(DBID id,
O object,
D parentDistance) |
boolean |
MkMaxTreeIndex.delete(DBID id)
Throws an UnsupportedOperationException since deletion of objects is not
yet supported by an M-Tree.
|
void |
MkMaxTreeIndex.insert(DBID id) |
Modifier and Type | Method and Description |
---|---|
protected void |
MkMaxTree.kNNdistanceAdjustment(MkMaxEntry<D> entry,
Map<DBID,KNNHeap<D>> knnLists)
Adjusts the knn distance in the subtree of the specified root entry.
|
Constructor and Description |
---|
MkMaxDirectoryEntry(DBID objectID,
D parentDistance,
Integer nodeID,
D coveringRadius,
D knnDistance)
Provides a new MkMaxDirectoryEntry with the given parameters.
|
MkMaxLeafEntry(DBID objectID,
D parentDistance,
D knnDistance)
Provides a new MkMaxLeafEntry with the given parameters.
|
Modifier and Type | Method and Description |
---|---|
void |
MkTabTreeNode.adjustEntry(MkTabEntry<D> entry,
DBID routingObjectID,
D parentDistance,
AbstractMTree<O,D,MkTabTreeNode<O,D>,MkTabEntry<D>> mTree) |
protected MkTabEntry<D> |
MkTabTree.createNewDirectoryEntry(MkTabTreeNode<O,D> node,
DBID routingObjectID,
D parentDistance)
Creates a new directory entry representing the specified node.
|
protected MkTabEntry<D> |
MkTabTreeIndex.createNewLeafEntry(DBID id,
O object,
D parentDistance)
Creates a new leaf entry representing the specified data object in the
specified subtree.
|
boolean |
MkTabTreeIndex.delete(DBID id)
Throws an UnsupportedOperationException since deletion of objects is not
yet supported by an M-Tree.
|
void |
MkTabTreeIndex.insert(DBID id) |
Modifier and Type | Method and Description |
---|---|
protected void |
MkTabTree.kNNdistanceAdjustment(MkTabEntry<D> entry,
Map<DBID,KNNHeap<D>> knnLists) |
Constructor and Description |
---|
MkTabDirectoryEntry(DBID objectID,
D parentDistance,
Integer nodeID,
D coveringRadius,
List<D> knnDistances)
Provides a new MkMaxDirectoryEntry with the given parameters.
|
MkTabLeafEntry(DBID objectID,
D parentDistance,
List<D> knnDistances)
Provides a new MkMaxLeafEntry with the given parameters.
|
Modifier and Type | Method and Description |
---|---|
protected MTreeEntry<D> |
MTree.createNewDirectoryEntry(MTreeNode<O,D> node,
DBID routingObjectID,
D parentDistance) |
protected MTreeEntry<D> |
MTreeIndex.createNewLeafEntry(DBID id,
O object,
D parentDistance) |
boolean |
MTreeIndex.delete(DBID id)
Throws an UnsupportedOperationException since deletion of objects is not
yet supported by an M-Tree.
|
void |
MTreeIndex.insert(DBID id) |
Modifier and Type | Method and Description |
---|---|
private void |
MetricalIndexRangeQuery.doRangeQuery(DBID o_p,
AbstractMTreeNode<O,D,?,?> node,
DBID q,
D r_q,
List<DistanceResultPair<D>> result)
Performs a range query on the specified subtree.
|
private void |
MetricalIndexRangeQuery.doRangeQuery(DBID o_p,
AbstractMTreeNode<O,D,?,?> node,
O q,
D r_q,
List<DistanceResultPair<D>> result)
Performs a range query on the specified subtree.
|
Modifier and Type | Method and Description |
---|---|
void |
MetricalIndexKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) |
Modifier and Type | Field and Description |
---|---|
private DBID |
Assignments.id1
The id of the first routing object.
|
private DBID |
Assignments.id2
The id of the second routing object.
|
Modifier and Type | Method and Description |
---|---|
DBID |
Assignments.getFirstRoutingObject()
Returns the id of the first routing object.
|
DBID |
Assignments.getSecondRoutingObject()
Returns the id of the second routing object.
|
Modifier and Type | Method and Description |
---|---|
(package private) Assignments<D,E> |
MTreeSplit.balancedPartition(N node,
DBID routingObject1,
DBID routingObject2,
DistanceQuery<O,D> distanceFunction)
Creates a balanced partition of the entries of the specified node.
|
Constructor and Description |
---|
Assignments(DBID id1,
DBID id2,
D firstCoveringRadius,
D secondCoveringRadius,
Set<E> firstAssignments,
Set<E> secondAssignments)
Provides an assignment during a split of an MTree node.
|
Modifier and Type | Field and Description |
---|---|
DBID |
GenericMTreeDistanceSearchCandidate.routingObjectID
The id of the routing object.
|
Constructor and Description |
---|
GenericMTreeDistanceSearchCandidate(D mindist,
Integer nodeID,
DBID routingObjectID)
Creates a new heap node with the specified parameters.
|
Constructor and Description |
---|
SpatialPointLeafEntry(DBID id,
double[] values)
Constructs a new LeafEntry object with the given parameters.
|
SpatialPointLeafEntry(DBID id,
NumberVector<?,?> vector)
Constructor from number vector
|
Modifier and Type | Method and Description |
---|---|
protected DeLiCluLeafEntry |
DeLiCluTreeIndex.createNewLeafEntry(DBID id)
Creates a new leaf entry representing the specified data object.
|
boolean |
DeLiCluTreeIndex.delete(DBID id)
Deletes the specified object from this index.
|
void |
DeLiCluTreeIndex.insert(DBID id)
Inserts the specified real vector object into this index.
|
List<TreeIndexPathComponent<DeLiCluEntry>> |
DeLiCluTreeIndex.setHandled(DBID id,
O obj)
Marks the specified object as handled and returns the path of node ids from
the root to the objects's parent.
|
Constructor and Description |
---|
DeLiCluLeafEntry(DBID id,
NumberVector<?,?> vector)
Constructs a new LeafEntry object with the given parameters.
|
Modifier and Type | Method and Description |
---|---|
protected void |
GenericRStarTreeKNNQuery.batchNN(AbstractRStarTreeNode<?,?> node,
Map<DBID,KNNHeap<D>> knnLists)
Performs a batch knn query.
|
protected void |
DoubleDistanceRStarTreeKNNQuery.batchNN(AbstractRStarTreeNode<?,?> node,
Map<DBID,KNNHeap<DoubleDistance>> knnLists)
Performs a batch knn query.
|
void |
GenericRStarTreeKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<D>> heaps) |
void |
DoubleDistanceRStarTreeKNNQuery.getKNNForBulkHeaps(Map<DBID,KNNHeap<DoubleDistance>> heaps) |
Modifier and Type | Method and Description |
---|---|
protected SpatialPointLeafEntry |
RStarTreeIndex.createNewLeafEntry(DBID id)
Create a new leaf entry.
|
boolean |
RStarTreeIndex.delete(DBID id)
Deletes the specified object from this index.
|
void |
RStarTreeIndex.insert(DBID id)
Inserts the specified reel vector object into this index.
|
Modifier and Type | Field and Description |
---|---|
protected DBID |
VectorApproximation.id
Object represented by this approximation
|
Modifier and Type | Method and Description |
---|---|
DBID |
VectorApproximation.getId() |
DBID |
PartialVAFile.PartialVACandidate.getId() |
Modifier and Type | Method and Description |
---|---|
VectorApproximation |
VAFile.calculateApproximation(DBID id,
V dv)
Calculate the VA file position given the existing borders.
|
protected VectorApproximation |
PartialVAFile.calculateFullApproximation(DBID id,
V dv)
Calculate the VA file position given the existing borders.
|
protected static VectorApproximation |
PartialVAFile.calculatePartialApproximation(DBID id,
NumberVector<?,?> dv,
List<DoubleObjPair<DAFile>> daFiles)
Calculate partial vector approximation
|
Constructor and Description |
---|
VectorApproximation(DBID id,
int[] approximation)
Constructor.
|
Modifier and Type | Method and Description |
---|---|
int |
OrderingFromDataStore.ImpliedComparator.compare(DBID id1,
DBID id2) |
int |
OrderingFromDataStore.DerivedComparator.compare(DBID id1,
DBID id2) |
private StringBuffer |
KMLOutputHandler.makeDescription(Collection<Relation<?>> relations,
DBID id)
Make an HTML description.
|
Modifier and Type | Field and Description |
---|---|
private DBID |
GenericClusterOrderEntry.objectID
The id of the entry.
|
private DBID |
DoubleDistanceClusterOrderEntry.objectID
The id of the entry.
|
private DBID |
GenericClusterOrderEntry.predecessorID
The id of the entry's predecessor.
|
private DBID |
DoubleDistanceClusterOrderEntry.predecessorID
The id of the entry's predecessor.
|
Modifier and Type | Method and Description |
---|---|
DBID |
ClusterOrderResult.PredecessorAdapter.get(DBIDRef objID) |
DBID |
GenericClusterOrderEntry.getID()
Returns the object id of this entry.
|
DBID |
DoubleDistanceClusterOrderEntry.getID()
Returns the object id of this entry.
|
DBID |
ClusterOrderEntry.getID()
Returns the object id of this entry.
|
DBID |
GenericClusterOrderEntry.getPredecessorID()
Returns the id of the predecessor of this entry if this entry has a
predecessor, null otherwise.
|
DBID |
DoubleDistanceClusterOrderEntry.getPredecessorID()
Returns the id of the predecessor of this entry if this entry has a
predecessor, null otherwise.
|
DBID |
ClusterOrderEntry.getPredecessorID()
Returns the id of the predecessor of this entry if this entry has a
predecessor, null otherwise.
|
Modifier and Type | Method and Description |
---|---|
SimpleTypeInformation<DBID> |
ClusterOrderResult.PredecessorAdapter.getDataTypeInformation() |
Modifier and Type | Method and Description |
---|---|
void |
ClusterOrderResult.add(DBID id,
DBID predecessor,
D reachability)
Add an object to the cluster order.
|
void |
ClusterOrderResult.PredecessorAdapter.set(DBIDRef id,
DBID val) |
Constructor and Description |
---|
DoubleDistanceClusterOrderEntry(DBID objectID,
DBID predecessorID,
double reachability)
Creates a new entry in a cluster order with the specified parameters.
|
GenericClusterOrderEntry(DBID objectID,
DBID predecessorID,
D reachability)
Creates a new entry in a cluster order with the specified parameters.
|
Modifier and Type | Method and Description |
---|---|
int |
OrderingFromRelation.ImpliedComparator.compare(DBID id1,
DBID id2) |
Modifier and Type | Method and Description |
---|---|
private void |
TextWriter.printObject(TextWriterStream out,
Database db,
DBID objID,
List<Relation<?>> ra) |
Modifier and Type | Method and Description |
---|---|
static DBID |
QuickSelect.median(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.median(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int begin,
int end)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.quantile(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
double quant)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.quantile(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int begin,
int end,
double quant)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.quickSelect(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int rank)
QuickSelect is essentially quicksort, except that we only "sort" that half
of the array that we are interested in.
|
Modifier and Type | Method and Description |
---|---|
private static void |
QuickSelect.insertionSort(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int start,
int end)
Sort a small array using repetitive insertion sort.
|
static DBID |
QuickSelect.median(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.median(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int begin,
int end)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.quantile(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
double quant)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.quantile(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int begin,
int end,
double quant)
Compute the median of an array efficiently using the QuickSelect method.
|
static DBID |
QuickSelect.quickSelect(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int rank)
QuickSelect is essentially quicksort, except that we only "sort" that half
of the array that we are interested in.
|
static void |
QuickSelect.quickSelect(ArrayModifiableDBIDs data,
Comparator<? super DBID> comparator,
int start,
int end,
int rank)
QuickSelect is essentially quicksort, except that we only "sort" that half
of the array that we are interested in.
|
Modifier and Type | Method and Description |
---|---|
DBID |
ArrayDBIDsAdapter.get(ArrayDBIDs array,
int off) |
Constructor and Description |
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ObjectNotFoundException(DBID id)
Object
|
Modifier and Type | Method and Description |
---|---|
protected Element |
TooltipScoreVisualization.makeTooltip(DBID id,
double x,
double y,
double dotsize) |
protected abstract Element |
AbstractTooltipVisualization.makeTooltip(DBID id,
double x,
double y,
double dotsize) |
protected Element |
TooltipStringVisualization.makeTooltip(DBID id,
double x,
double y,
double dotsize) |