| Modifier and Type | Class and Description |
|---|---|
class |
AbstractMTreeFactory<O,D extends NumberDistance<D,?>,N extends AbstractMTreeNode<O,D,N,E>,E extends MTreeEntry,I extends AbstractMTree<O,D,N,E,S> & Index,S extends MTreeSettings<O,D,N,E>>
Abstract factory for various MTrees
|
| Modifier and Type | Method and Description |
|---|---|
void |
AbstractMTreeNode.adjustEntry(E entry,
DBID routingObjectID,
double parentDistance,
AbstractMTree<O,D,N,E,?> mTree)
Adjusts the parameters of the entry representing this node (e.g. after
insertion of new objects).
|
double |
AbstractMTreeNode.coveringRadius(DBID routingObjectID,
AbstractMTree<O,D,N,E,?> mTree)
Determines and returns the covering radius of this node.
|
void |
AbstractMTreeNode.integrityCheck(AbstractMTree<O,D,N,E,?> mTree,
E entry)
Tests this node (for debugging purposes).
|
protected void |
AbstractMTreeNode.integrityCheckParameters(E parentEntry,
N parent,
int index,
AbstractMTree<O,D,N,E,?> mTree)
Tests, if the parameters of the entry representing this node, are correctly
set.
|
| Modifier and Type | Class and Description |
|---|---|
class |
AbstractMkTree<O,D extends NumberDistance<D,?>,N extends AbstractMTreeNode<O,D,N,E>,E extends MTreeEntry,S extends MTreeSettings<O,D,N,E>>
Abstract class for all M-Tree variants supporting processing of reverse
k-nearest neighbor queries by using the k-nn distances of the entries, where
k is less than or equal to the given parameter.
|
class |
AbstractMkTreeUnified<O,D extends NumberDistance<D,?>,N extends AbstractMTreeNode<O,D,N,E>,E extends MTreeEntry,S extends MkTreeSettings<O,D,N,E>>
Abstract class for all M-Tree variants supporting processing of reverse
k-nearest neighbor queries by using the k-nn distances of the entries, where
k is less than or equal to the given parameter.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MkAppTree<O,D extends NumberDistance<D,?>>
MkAppTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k < kmax.
|
class |
MkAppTreeIndex<O,D extends NumberDistance<D,?>>
MkAppTree used as database index.
|
| Modifier and Type | Method and Description |
|---|---|
void |
MkAppTreeNode.adjustEntry(MkAppEntry entry,
DBID routingObjectID,
double parentDistance,
AbstractMTree<O,D,MkAppTreeNode<O,D>,MkAppEntry,?> mTree)
Adjusts the parameters of the entry representing this node.
|
protected void |
MkAppTreeNode.integrityCheckParameters(MkAppEntry parentEntry,
MkAppTreeNode<O,D> parent,
int index,
AbstractMTree<O,D,MkAppTreeNode<O,D>,MkAppEntry,?> mTree) |
| Modifier and Type | Class and Description |
|---|---|
class |
MkCoPTree<O,D extends NumberDistance<D,?>>
MkCopTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k < kmax.
|
class |
MkCoPTreeIndex<O,D extends NumberDistance<D,?>>
MkCoPTree used as database index.
|
| Modifier and Type | Method and Description |
|---|---|
void |
MkCoPTreeNode.adjustEntry(MkCoPEntry entry,
DBID routingObjectID,
double parentDistance,
AbstractMTree<O,D,MkCoPTreeNode<O,D>,MkCoPEntry,?> mTree) |
protected void |
MkCoPTreeNode.integrityCheckParameters(MkCoPEntry parentEntry,
MkCoPTreeNode<O,D> parent,
int index,
AbstractMTree<O,D,MkCoPTreeNode<O,D>,MkCoPEntry,?> mTree) |
| Modifier and Type | Class and Description |
|---|---|
class |
MkMaxTree<O,D extends NumberDistance<D,?>>
MkMaxTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k <= k_max.
|
class |
MkMaxTreeIndex<O,D extends NumberDistance<D,?>>
MkMax tree
|
| Modifier and Type | Method and Description |
|---|---|
void |
MkMaxTreeNode.adjustEntry(MkMaxEntry entry,
DBID routingObjectID,
double parentDistance,
AbstractMTree<O,D,MkMaxTreeNode<O,D>,MkMaxEntry,?> 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 void |
MkMaxTreeNode.integrityCheckParameters(MkMaxEntry parentEntry,
MkMaxTreeNode<O,D> parent,
int index,
AbstractMTree<O,D,MkMaxTreeNode<O,D>,MkMaxEntry,?> mTree)
Calls the super method and tests if the k-nearest neighbor distance of this
node is correctly set.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MkTabTree<O,D extends NumberDistance<D,?>>
MkTabTree is a metrical index structure based on the concepts of the M-Tree
supporting efficient processing of reverse k nearest neighbor queries for
parameter k < kmax.
|
class |
MkTabTreeIndex<O,D extends NumberDistance<D,?>>
MkTabTree used as database index.
|
| Modifier and Type | Method and Description |
|---|---|
void |
MkTabTreeNode.adjustEntry(MkTabEntry entry,
DBID routingObjectID,
double parentDistance,
AbstractMTree<O,D,MkTabTreeNode<O,D>,MkTabEntry,?> mTree) |
protected void |
MkTabTreeNode.integrityCheckParameters(MkTabEntry parentEntry,
MkTabTreeNode<O,D> parent,
int index,
AbstractMTree<O,D,MkTabTreeNode<O,D>,MkTabEntry,?> mTree)
Tests, if the parameters of the entry representing this node, are correctly
set.
|
| Modifier and Type | Class and Description |
|---|---|
class |
MTree<O,D extends NumberDistance<D,?>>
MTree is a metrical index structure based on the concepts of the M-Tree.
|
class |
MTreeIndex<O,D extends NumberDistance<D,?>>
Class for using an m-tree as database index.
|
| Modifier and Type | Field and Description |
|---|---|
protected AbstractMTree<O,D,?,?,?> |
MetricalIndexRangeQuery.index
The index to use
|
protected AbstractMTree<O,DoubleDistance,?,?,?> |
DoubleDistanceMetricalIndexRangeQuery.index
The index to use
|
protected AbstractMTree<O,D,?,?,?> |
MetricalIndexKNNQuery.index
The index to use
|
protected AbstractMTree<O,DoubleDistance,?,?,?> |
DoubleDistanceMetricalIndexKNNQuery.index
The index to use
|
| Modifier and Type | Method and Description |
|---|---|
static <O,D extends NumberDistance<D,?>> |
MTreeQueryUtil.getKNNQuery(AbstractMTree<O,D,?,?,?> tree,
DistanceQuery<O,D> distanceQuery,
Object... hints)
Get an RTree knn query, using an optimized double implementation when
possible.
|
static <O,D extends NumberDistance<D,?>> |
MTreeQueryUtil.getRangeQuery(AbstractMTree<O,D,?,?,?> tree,
DistanceQuery<O,D> distanceQuery,
Object... hints)
Get an RTree knn query, using an optimized double implementation when
possible.
|
| Constructor and Description |
|---|
DoubleDistanceMetricalIndexKNNQuery(AbstractMTree<O,DoubleDistance,?,?,?> index,
DistanceQuery<O,DoubleDistance> distanceQuery,
PrimitiveDoubleDistanceFunction<? super O> distf)
Constructor.
|
DoubleDistanceMetricalIndexRangeQuery(AbstractMTree<O,DoubleDistance,?,?,?> index,
DistanceQuery<O,DoubleDistance> distanceQuery,
PrimitiveDoubleDistanceFunction<? super O> distf)
Constructor.
|
MetricalIndexKNNQuery(AbstractMTree<O,D,?,?,?> index,
DistanceQuery<O,D> distanceQuery)
Constructor.
|
MetricalIndexRangeQuery(AbstractMTree<O,D,?,?,?> index,
DistanceQuery<O,D> distanceQuery)
Constructor.
|
| Modifier and Type | Method and Description |
|---|---|
IndexTreePath<E> |
MinimumEnlargementInsert.choosePath(AbstractMTree<O,D,N,E,?> tree,
E object) |
IndexTreePath<E> |
MTreeInsert.choosePath(AbstractMTree<O,D,N,E,?> tree,
E object)
Choose the subpath to insert into.
|
private IndexTreePath<E> |
MinimumEnlargementInsert.choosePath(AbstractMTree<O,D,N,E,?> tree,
E object,
IndexTreePath<E> subtree)
Chooses the best path of the specified subtree for insertion of the given
object.
|
| Modifier and Type | Method and Description |
|---|---|
(package private) Assignments<E> |
MTreeSplit.balancedPartition(AbstractMTree<O,D,N,E,?> tree,
N node,
DBID routingObject1,
DBID routingObject2)
Creates a balanced partition of the entries of the specified node.
|
(package private) Assignments<E> |
MTreeSplit.balancedPartition(AbstractMTree<O,D,N,E,?> tree,
N node,
int routingEntNum1,
int routingEntNum2,
double[] distanceMatrix)
Creates a balanced partition of the entries of the specified node.
|
protected double[] |
MTreeSplit.computeDistanceMatrix(AbstractMTree<O,D,N,E,?> tree,
N node)
Compute the pairwise distances in the given node.
|
abstract Assignments<E> |
MTreeSplit.split(AbstractMTree<O,D,N,E,?> tree,
N node)
Returns the assignments of this split.
|
Assignments<E> |
RandomSplit.split(AbstractMTree<O,D,N,E,?> tree,
N node)
Selects two objects of the specified node to be promoted and stored into
the parent node.
|
Assignments<E> |
MMRadSplit.split(AbstractMTree<O,D,N,E,?> tree,
N node)
Selects two objects of the specified node to be promoted and stored into
the parent node.
|
Assignments<E> |
MLBDistSplit.split(AbstractMTree<O,D,N,E,?> tree,
N node)
Selects the second object of the specified node to be promoted and stored
into the parent node and partitions the entries according to the M_LB_DIST
strategy.
|
Assignments<E> |
MRadSplit.split(AbstractMTree<O,D,N,E,?> tree,
N node)
Selects two objects of the specified node to be promoted and stored into
the parent node.
|
| Modifier and Type | Field and Description |
|---|---|
protected AbstractMTree<?,D,N,E,?> |
TreeSphereVisualization.Instance.tree
The tree we visualize
|
| Modifier and Type | Method and Description |
|---|---|
static boolean |
TreeSphereVisualization.canVisualize(AbstractMTree<?,?,?,?,?> tree)
Test for a visualizable index in the context's database.
|
static double |
TreeSphereVisualization.getLPNormP(AbstractMTree<?,?,?,?,?> tree)
Get the "p" value of an Lp norm.
|
private void |
TreeSphereVisualization.Instance.visualizeMTreeEntry(SVGPlot svgp,
Element layer,
Projection2D proj,
AbstractMTree<?,D,N,E,?> mtree,
E entry,
int depth)
Recursively draw the MBR rectangles.
|
){kind=link}