--- name: "mlpack_tree_CoverTree" section: "3" platform: "linux" package: "mlpack-doc" version: "1.0.10-1" release: "Debian 8 (Jessie)" platforms: ["linux"] url: "https://new.carta.tech/mlpack_tree_CoverTree" --- # mlpack\_tree\_CoverTree(3) A cover tree is a tree specifically designed to speed up nearest-neighbor computation in high-dimensional spaces. ## NAME mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \> - A cover tree is a tree specifically designed to speed up nearest-neighbor computation in high-dimensional spaces. ## SYNOPSIS ### Classes class **DualTreeTraverser**\ *A dual-tree cover tree traverser; see dual\_tree\_traverser.hpp.* class **SingleTreeTraverser**\ *A single-tree cover tree traverser; see single\_tree\_traverser.hpp for implementation.* ### Public Types typedef arma::mat **Mat**\ ### Public Member Functions **CoverTree** (const arma::mat &**dataset**, const double **base**=2.0, MetricType \***metric**=NULL)\ *Create the cover tree with the given dataset and given base.* **CoverTree** (const arma::mat &**dataset**, MetricType &**metric**, const double **base**=2.0)\ *Create the cover tree with the given dataset and the given instantiated metric.* **CoverTree** (const arma::mat &**dataset**, const double **base**, const size\_t pointIndex, const int **scale**, **CoverTree** \***parent**, const double **parentDistance**, arma::Col\< size\_t \> &indices, arma::vec &distances, size\_t nearSetSize, size\_t &farSetSize, size\_t &usedSetSize, MetricType &**metric**=NULL)\ *Construct a child cover tree node.* **CoverTree** (const arma::mat &**dataset**, const double **base**, const size\_t pointIndex, const int **scale**, **CoverTree** \***parent**, const double **parentDistance**, const double **furthestDescendantDistance**, MetricType \***metric**=NULL)\ *Manually construct a cover tree node; no tree assembly is done in this constructor, and children must be added manually (use* **Children()***).* **CoverTree** (const **CoverTree** &other)\ *Create a cover tree from another tree.* **~CoverTree** ()\ *Delete this cover tree node and its children.* double **Base** () const \ *Get the base.* double & **Base** ()\ *Modify the base; don't do this, you'll break everything.* void **Centroid** (arma::vec ¢roid) const \ *Get the centroid of the node and store it in the given vector.* const **CoverTree** & **Child** (const size\_t index) const \ *Get a particular child node.* **CoverTree** & **Child** (const size\_t index)\ *Modify a particular child node.* const std::vector\< **CoverTree** \* \> & **Children** () const \ *Get the children.* std::vector\< **CoverTree** \* \> & **Children** ()\ *Modify the children manually (maybe not a great idea).* const arma::mat & **Dataset** () const \ *Get a reference to the dataset.* size\_t **Descendant** (const size\_t index) const \ *Get the index of a particular descendant point.* size\_t **DistanceComps** () const \ size\_t & **DistanceComps** ()\ double **FurthestDescendantDistance** () const \ *Get the distance from the center of the node to the furthest descendant.* double & **FurthestDescendantDistance** ()\ *Modify the distance from the center of the node to the furthest descendant.* double **FurthestPointDistance** () const \ *Get the distance to the furthest point. This is always 0 for cover trees.* bool **IsLeaf** () const \ double **MaxDistance** (const **CoverTree** \*other) const \ *Return the maximum distance to another node.* double **MaxDistance** (const **CoverTree** \*other, const double distance) const \ *Return the maximum distance to another node given that the point-to-point distance has already been calculated.* double **MaxDistance** (const arma::vec &other) const \ *Return the maximum distance to another point.* double **MaxDistance** (const arma::vec &other, const double distance) const \ *Return the maximum distance to another point given that the distance from the center to the point has already been calculated.* MetricType & **Metric** () const \ *Get the instantiated metric.* double **MinDistance** (const **CoverTree** \*other) const \ *Return the minimum distance to another node.* double **MinDistance** (const **CoverTree** \*other, const double distance) const \ *Return the minimum distance to another node given that the point-to-point distance has already been calculated.* double **MinDistance** (const arma::vec &other) const \ *Return the minimum distance to another point.* double **MinDistance** (const arma::vec &other, const double distance) const \ *Return the minimum distance to another point given that the distance from the center to the point has already been calculated.* double **MinimumBoundDistance** () const \ *Get the minimum distance from the center to any bound edge (this is the same as furthestDescendantDistance).* size\_t **NumChildren** () const \ *Get the number of children.* size\_t **NumDescendants** () const \ *Get the number of descendant points.* size\_t **NumPoints** () const \ **CoverTree** \* **Parent** () const \ *Get the parent node.* **CoverTree** \*& **Parent** ()\ *Modify the parent node.* double **ParentDistance** () const \ *Get the distance to the parent.* double & **ParentDistance** ()\ *Modify the distance to the parent.* size\_t **Point** () const \ *Get the index of the point which this node represents.* size\_t **Point** (const size\_t) const \ *For compatibility with other trees; the argument is ignored.* **math::Range** **RangeDistance** (const **CoverTree** \*other) const \ *Return the minimum and maximum distance to another node.* **math::Range** **RangeDistance** (const **CoverTree** \*other, const double distance) const \ *Return the minimum and maximum distance to another node given that the point-to-point distance has already been calculated.* **math::Range** **RangeDistance** (const arma::vec &other) const \ *Return the minimum and maximum distance to another point.* **math::Range** **RangeDistance** (const arma::vec &other, const double distance) const \ *Return the minimum and maximum distance to another point given that the point-to-point distance has already been calculated.* int **Scale** () const \ *Get the scale of this node.* int & **Scale** ()\ *Modify the scale of this node. Be careful...* const StatisticType & **Stat** () const \ *Get the statistic for this node.* StatisticType & **Stat** ()\ *Modify the statistic for this node.* std::string **ToString** () const \ *Returns a string representation of this object.* ### Static Public Member Functions static bool **HasSelfChildren** ()\ *Returns true: this tree does have self-children.* ### Private Member Functions void **ComputeDistances** (const size\_t pointIndex, const arma::Col\< size\_t \> &indices, arma::vec &distances, const size\_t pointSetSize)\ *Fill the vector of distances with the distances between the point specified by pointIndex and each point in the indices array.* void **CreateChildren** (arma::Col\< size\_t \> &indices, arma::vec &distances, size\_t nearSetSize, size\_t &farSetSize, size\_t &usedSetSize)\ *Create the children for this node.* void **MoveToUsedSet** (arma::Col\< size\_t \> &indices, arma::vec &distances, size\_t &nearSetSize, size\_t &farSetSize, size\_t &usedSetSize, arma::Col\< size\_t \> &childIndices, const size\_t childFarSetSize, const size\_t childUsedSetSize)\ size\_t **PruneFarSet** (arma::Col\< size\_t \> &indices, arma::vec &distances, const double bound, const size\_t nearSetSize, const size\_t pointSetSize)\ void **RemoveNewImplicitNodes** ()\ *Take a look at the last child (the most recently created one) and remove any implicit nodes that have been created.* size\_t **SortPointSet** (arma::Col\< size\_t \> &indices, arma::vec &distances, const size\_t childFarSetSize, const size\_t childUsedSetSize, const size\_t farSetSize)\ *Assuming that the list of indices and distances is sorted as \[ childFarSet \| childUsedSet \| farSet \| usedSet \], resort the sets so the organization is \[ childFarSet \| farSet \| childUsedSet \| usedSet \].* size\_t **SplitNearFar** (arma::Col\< size\_t \> &indices, arma::vec &distances, const double bound, const size\_t pointSetSize)\ *Split the given indices and distances into a near and a far set, returning the number of points in the near set.* ### Private Attributes double **base**\ *The base used to construct the tree.* std::vector\< **CoverTree** \* \> **children**\ *The list of children; the first is the self-child.* const arma::mat & **dataset**\ *Reference to the matrix which this tree is built on.* size\_t **distanceComps**\ double **furthestDescendantDistance**\ *Distance to the furthest descendant.* bool **localMetric**\ *Whether or not we need to destroy the metric in the destructor.* MetricType \* **metric**\ *The metric used for this tree.* size\_t **numDescendants**\ *The number of descendant points.* **CoverTree** \* **parent**\ *The parent node (NULL if this is the root of the tree).* double **parentDistance**\ *Distance to the parent.* size\_t **point**\ *Index of the point in the matrix which this node represents.* int **scale**\ *Scale level of the node.* StatisticType **stat**\ *The instantiated statistic.* ## Detailed Description ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\>class mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \> A cover tree is a tree specifically designed to speed up nearest-neighbor computation in high-dimensional spaces. Each non-leaf node references a point and has a nonzero number of children, including a 'self-child' which references the same point. A leaf node represents only one point. The tree can be thought of as a hierarchy with the root node at the top level and the leaf nodes at the bottom level. Each level in the tree has an assigned 'scale' i. The tree follows these three conditions: - • nesting: the level C\_i is a subset of the level C\_{i - 1}. - • covering: all node in level C\_{i - 1} have at least one node in the level C\_i with distance less than or equal to b^i (exactly one of these is a parent of the point in level C\_{i - 1}. - • separation: all nodes in level C\_i have distance greater than b^i to all other nodes in level C\_i. The value 'b' refers to the base, which is a parameter of the tree. These three properties make the cover tree very good for fast, high-dimensional nearest-neighbor search. The theoretical structure of the tree contains many 'implicit' nodes which only have a 'self-child' (a child referencing the same point, but at a lower scale level). This practical implementation only constructs explicit nodes -- non-leaf nodes with more than one child. A leaf node has no children, and its scale level is INT\_MIN. For more information on cover trees, see ``` @inproceedings{ author = {Beygelzimer, Alina and Kakade, Sham and Langford, John}, title = {Cover trees for nearest neighbor}, booktitle = {Proceedings of the 23rd International Conference on Machine Learning}, series = {ICML '06}, year = {2006}, pages = {97--104] } ``` For information on runtime bounds of the nearest-neighbor computation using cover trees, see the following paper, presented at NIPS 2009: ``` @inproceedings{ author = {Ram, P., and Lee, D., and March, W.B., and Gray, A.G.}, title = {Linear-time Algorithms for Pairwise Statistical Problems}, booktitle = {Advances in Neural Information Processing Systems 22}, editor = {Y. Bengio and D. Schuurmans and J. Lafferty and C.K.I. Williams and A. Culotta}, pages = {1527--1535}, year = {2009} } ``` The **CoverTree** class offers three template parameters; a custom metric type can be used with MetricType (this class defaults to the L2-squared metric). The root node's point can be chosen with the RootPointPolicy; by default, the **FirstPointIsRoot** policy is used, meaning the first point in the dataset is used. The StatisticType policy allows you to define statistics which can be gathered during the creation of the tree. **Template Parameters:** *MetricType* Metric type to use during tree construction. \ *RootPointPolicy* Determines which point to use as the root node. \ *StatisticType* Statistic to be used during tree creation. Definition at line 103 of file cover\_tree.hpp. ## Member Typedef Documentation ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> typedef arma::mat mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Mat Definition at line 106 of file cover\_tree.hpp. ## Constructor & Destructor Documentation ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::CoverTree (const arma::mat &dataset, const doublebase = `2.0`, MetricType \*metric = `NULL`) Create the cover tree with the given dataset and given base. The dataset will not be modified during the building procedure (unlike **BinarySpaceTree**). The last argument will be removed in mlpack 1.1.0 (see #274 and #273). **Parameters:** *dataset* Reference to the dataset to build a tree on. \ *base* Base to use during tree building (default 2.0). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::CoverTree (const arma::mat &dataset, MetricType &metric, const doublebase = `2.0`) Create the cover tree with the given dataset and the given instantiated metric. Optionally, set the base. The dataset will not be modified during the building procedure (unlike **BinarySpaceTree**). **Parameters:** *dataset* Reference to the dataset to build a tree on. \ *metric* Instantiated metric to use during tree building. \ *base* Base to use during tree building (default 2.0). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::CoverTree (const arma::mat &dataset, const doublebase, const size\_tpointIndex, const intscale, CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*parent, const doubleparentDistance, arma::Col\< size\_t \> &indices, arma::vec &distances, size\_tnearSetSize, size\_t &farSetSize, size\_t &usedSetSize, MetricType &metric = `NULL`) Construct a child cover tree node. This constructor is not meant to be used externally, but it could be used to insert another node into a tree. This procedure uses only one vector for the near set, the far set, and the used set (this is to prevent unnecessary memory allocation in recursive calls to this constructor). Therefore, the size of the near set, far set, and used set must be passed in. The near set will be entirely used up, and some of the far set may be used. The value of usedSetSize will be set to the number of points used in the construction of this node, and the value of farSetSize will be modified to reflect the number of points in the far set *after* the construction of this node. If you are calling this manually, be careful that the given scale is as small as possible, or you may be creating an implicit node in your tree. **Parameters:** *dataset* Reference to the dataset to build a tree on. \ *base* Base to use during tree building. \ *pointIndex* Index of the point this node references. \ *scale* Scale of this level in the tree. \ *parent* Parent of this node (NULL indicates no parent). \ *parentDistance* Distance to the parent node. \ *indices* Array of indices, ordered \[ nearSet \| farSet \| usedSet \]; will be modified to \[ farSet \| usedSet \]. \ *distances* Array of distances, ordered the same way as the indices. These represent the distances between the point specified by pointIndex and each point in the indices array. \ *nearSetSize* Size of the near set; if 0, this will be a leaf. \ *farSetSize* Size of the far set; may be modified (if this node uses any points in the far set). \ *usedSetSize* The number of points used will be added to this number. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::CoverTree (const arma::mat &dataset, const doublebase, const size\_tpointIndex, const intscale, CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*parent, const doubleparentDistance, const doublefurthestDescendantDistance, MetricType \*metric = `NULL`) Manually construct a cover tree node; no tree assembly is done in this constructor, and children must be added manually (use **Children()**). This constructor is useful when the tree is being 'imported' into the **CoverTree** class after being created in some other manner. **Parameters:** *dataset* Reference to the dataset this node is a part of. \ *base* Base that was used for tree building. \ *pointIndex* Index of the point in the dataset which this node refers to. \ *scale* Scale of this node's level in the tree. \ *parent* Parent node (NULL indicates no parent). \ *parentDistance* Distance to parent node point. \ *furthestDescendantDistance* Distance to furthest descendant point. \ *metric* Instantiated metric (optional). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::CoverTree (const CoverTree\< MetricType, RootPointPolicy, StatisticType \> &other) Create a cover tree from another tree. Be careful! This may use a lot of memory and take a lot of time. **Parameters:** *other* Cover tree to copy from. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::~CoverTree () Delete this cover tree node and its children. ## Member Function Documentation ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Base () const` [inline]` Get the base. Definition at line 262 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::base. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Base ()` [inline]` Modify the base; don't do this, you'll break everything. Definition at line 264 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::base. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> void mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Centroid (arma::vec ¢roid) const` [inline]` Get the centroid of the node and store it in the given vector. Definition at line 343 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::dataset, and mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::point. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> const CoverTree& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Child (const size\_tindex) const` [inline]` Get a particular child node. Definition at line 238 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::children. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> CoverTree& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Child (const size\_tindex)` [inline]` Modify a particular child node. Definition at line 240 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::children. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> const std::vector\& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Children () const` [inline]` Get the children. Definition at line 246 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::children. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> std::vector\& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Children ()` [inline]` Modify the children manually (maybe not a great idea). Definition at line 248 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::children. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> void mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::ComputeDistances (const size\_tpointIndex, const arma::Col\< size\_t \> &indices, arma::vec &distances, const size\_tpointSetSize)` [private]` Fill the vector of distances with the distances between the point specified by pointIndex and each point in the indices array. The distances of the first pointSetSize points in indices are calculated (so, this does not necessarily need to use all of the points in the arrays). **Parameters:** *pointIndex* Point to build the distances for. \ *indices* List of indices to compute distances for. \ *distances* Vector to store calculated distances in. \ *pointSetSize* Number of points in arrays to calculate distances for. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> void mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::CreateChildren (arma::Col\< size\_t \> &indices, arma::vec &distances, size\_tnearSetSize, size\_t &farSetSize, size\_t &usedSetSize)` [private]` Create the children for this node. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> const arma::mat& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Dataset () const` [inline]` Get a reference to the dataset. Definition at line 227 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::dataset. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Descendant (const size\_tindex) const Get the index of a particular descendant point. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::DistanceComps () const` [inline]` Definition at line 479 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::distanceComps. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::DistanceComps ()` [inline]` Definition at line 480 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::distanceComps. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::FurthestDescendantDistance () const` [inline]` Get the distance from the center of the node to the furthest descendant. Definition at line 332 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::furthestDescendantDistance. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::FurthestDescendantDistance ()` [inline]` Modify the distance from the center of the node to the furthest descendant. Definition at line 336 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::furthestDescendantDistance. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::FurthestPointDistance () const` [inline]` Get the distance to the furthest point. This is always 0 for cover trees. Definition at line 329 of file cover\_tree.hpp. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> static bool mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::HasSelfChildren ()` [inline]`, ` [static]` Returns true: this tree does have self-children. Definition at line 316 of file cover\_tree.hpp. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> bool mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::IsLeaf () const` [inline]` Definition at line 234 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::children. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MaxDistance (const CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*other) const Return the maximum distance to another node. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MaxDistance (const CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*other, const doubledistance) const Return the maximum distance to another node given that the point-to-point distance has already been calculated. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MaxDistance (const arma::vec &other) const Return the maximum distance to another point. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MaxDistance (const arma::vec &other, const doubledistance) const Return the maximum distance to another point given that the distance from the center to the point has already been calculated. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> MetricType& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Metric () const` [inline]` Get the instantiated metric. Definition at line 346 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::metric. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MinDistance (const CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*other) const Return the minimum distance to another node. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MinDistance (const CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*other, const doubledistance) const Return the minimum distance to another node given that the point-to-point distance has already been calculated. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MinDistance (const arma::vec &other) const Return the minimum distance to another point. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MinDistance (const arma::vec &other, const doubledistance) const Return the minimum distance to another point given that the distance from the center to the point has already been calculated. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MinimumBoundDistance () const` [inline]` Get the minimum distance from the center to any bound edge (this is the same as furthestDescendantDistance). Definition at line 340 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::furthestDescendantDistance. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> void mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MoveToUsedSet (arma::Col\< size\_t \> &indices, arma::vec &distances, size\_t &nearSetSize, size\_t &farSetSize, size\_t &usedSetSize, arma::Col\< size\_t \> &childIndices, const size\_tchildFarSetSize, const size\_tchildUsedSetSize)` [private]` ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::NumChildren () const` [inline]` Get the number of children. Definition at line 243 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::children. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::NumDescendants () const Get the number of descendant points. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::NumPoints () const` [inline]` Definition at line 235 of file cover\_tree.hpp. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> CoverTree\* mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Parent () const` [inline]` Get the parent node. Definition at line 319 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::parent. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> CoverTree\*& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Parent ()` [inline]` Modify the parent node. Definition at line 321 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::parent. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::ParentDistance () const` [inline]` Get the distance to the parent. Definition at line 324 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::parentDistance. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::ParentDistance ()` [inline]` Modify the distance to the parent. Definition at line 326 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::parentDistance. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Point () const` [inline]` Get the index of the point which this node represents. Definition at line 230 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::point. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Point (const size\_t) const` [inline]` For compatibility with other trees; the argument is ignored. Definition at line 232 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::point. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::PruneFarSet (arma::Col\< size\_t \> &indices, arma::vec &distances, const doublebound, const size\_tnearSetSize, const size\_tpointSetSize)` [private]` ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> math::Range mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::RangeDistance (const CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*other) const Return the minimum and maximum distance to another node. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> math::Range mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::RangeDistance (const CoverTree\< MetricType, RootPointPolicy, StatisticType \> \*other, const doubledistance) const Return the minimum and maximum distance to another node given that the point-to-point distance has already been calculated. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> math::Range mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::RangeDistance (const arma::vec &other) const Return the minimum and maximum distance to another point. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> math::Range mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::RangeDistance (const arma::vec &other, const doubledistance) const Return the minimum and maximum distance to another point given that the point-to-point distance has already been calculated. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> void mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::RemoveNewImplicitNodes ()` [private]` Take a look at the last child (the most recently created one) and remove any implicit nodes that have been created. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> int mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Scale () const` [inline]` Get the scale of this node. Definition at line 257 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::scale. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> int& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Scale ()` [inline]` Modify the scale of this node. Be careful... Definition at line 259 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::scale. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::SortPointSet (arma::Col\< size\_t \> &indices, arma::vec &distances, const size\_tchildFarSetSize, const size\_tchildUsedSetSize, const size\_tfarSetSize)` [private]` Assuming that the list of indices and distances is sorted as \[ childFarSet \| childUsedSet \| farSet \| usedSet \], resort the sets so the organization is \[ childFarSet \| farSet \| childUsedSet \| usedSet \]. The size\_t parameters specify the sizes of each set in the array. Only the ordering of the indices and distances arrays will be modified (not their actual contents). The size of any of the four sets can be zero and this method will handle that case accordingly. **Parameters:** *indices* List of indices to sort. \ *distances* List of distances to sort. \ *childFarSetSize* Number of points in child far set (childFarSet). \ *childUsedSetSize* Number of points in child used set (childUsedSet). \ *farSetSize* Number of points in far set (farSet). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::SplitNearFar (arma::Col\< size\_t \> &indices, arma::vec &distances, const doublebound, const size\_tpointSetSize)` [private]` Split the given indices and distances into a near and a far set, returning the number of points in the near set. The distances must already be initialized. This will order the indices and distances such that the points in the near set make up the first part of the array and the far set makes up the rest: \[ nearSet \| farSet \]. **Parameters:** *indices* List of indices; will be reordered. \ *distances* List of distances; will be reordered. \ *bound* If the distance is less than or equal to this bound, the point is placed into the near set. \ *pointSetSize* Size of point set (because we may be sorting a smaller list than the indices vector will hold). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> const StatisticType& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Stat () const` [inline]` Get the statistic for this node. Definition at line 267 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::stat. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> StatisticType& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Stat ()` [inline]` Modify the statistic for this node. Definition at line 269 of file cover\_tree.hpp. References mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::stat. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> std::string mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::ToString () const Returns a string representation of this object. ## Member Data Documentation ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::base` [private]` The base used to construct the tree. Definition at line 362 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Base(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> std::vector\ mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::children` [private]` The list of children; the first is the self-child. Definition at line 356 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Child(), mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Children(), mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::IsLeaf(), and mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::NumChildren(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> const arma::mat& mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::dataset` [private]` Reference to the matrix which this tree is built on. Definition at line 350 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Centroid(), and mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Dataset(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::distanceComps` [private]` Definition at line 483 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::DistanceComps(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::furthestDescendantDistance` [private]` Distance to the furthest descendant. Definition at line 377 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::FurthestDescendantDistance(), and mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::MinimumBoundDistance(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> bool mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::localMetric` [private]` Whether or not we need to destroy the metric in the destructor. Definition at line 380 of file cover\_tree.hpp. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> MetricType\* mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::metric` [private]` The metric used for this tree. Definition at line 383 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Metric(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::numDescendants` [private]` The number of descendant points. Definition at line 368 of file cover\_tree.hpp. ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> CoverTree\* mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::parent` [private]` The parent node (NULL if this is the root of the tree). Definition at line 371 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Parent(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> double mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::parentDistance` [private]` Distance to the parent. Definition at line 374 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::ParentDistance(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> size\_t mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::point` [private]` Index of the point in the matrix which this node represents. Definition at line 353 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Centroid(), and mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Point(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> int mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::scale` [private]` Scale level of the node. Definition at line 359 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Scale(). ### template\, typename RootPointPolicy = FirstPointIsRoot, typename StatisticType = EmptyStatistic\> StatisticType mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::stat` [private]` The instantiated statistic. Definition at line 365 of file cover\_tree.hpp. Referenced by mlpack::tree::CoverTree\< MetricType, RootPointPolicy, StatisticType \>::Stat(). ## Author Generated automatically by Doxygen for MLPACK from the source code.