info.debatty.java.graphs

Class Graph<T>

java.lang.Object

info.debatty.java.graphs.Graph<T>

Type Parameters:

T - The class of the node, used when getting a node

All Implemented Interfaces:

Serializable

public class Graph<T>
extends Object
implements Serializable

k-nn graph, represented as a mapping node => neighborlist.

Author:

Thibault Debatty

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static int	DEFAULT_K Number of edges per node.
static double	DEFAULT_SEARCH_EXPANSION Fast search: expansion parameter.
static int	DEFAULT_SEARCH_RANDOM_JUMPS Fast search: number of random jumps per node (to simulate small world graph).
static double	DEFAULT_SEARCH_SPEEDUP Fast search: speedup compared to exhaustive search.
static int	DEFAULT_UPDATE_DEPTH Fast add or remove node: depth of search to update the graph.

Constructor Summary

Constructors

Constructor and Description
Graph() Initialize an empty graph with k = 10.
Graph(Graph<T> origin) Copy constructor.
Graph(int k) Initialize an empty graph, and set k (number of edges per node).

Method Summary

Methods

Modifier and Type	Method and Description
int	add(T new_node) Add a node to the online graph using exhaustive search approach.
int	compare(Graph<T> other) Count the number of edges/neighbors that are the same (based on similarity) in both graphs.
ArrayList<Graph<T>>	connectedComponents() Split the graph in connected components (usually you will first prune the graph to remove "weak" edges).
boolean	containsKey(T node)
Iterable<Map.Entry<T,NeighborList>>	entrySet()
boolean	equals(Object obj)
void	fastAdd(T node) Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al.
void	fastAdd(T node, double speedup) Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al.
void	fastAdd(T new_node, double speedup, int long_jumps, double expansion) Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al.
void	fastAdd(T new_node, double speedup, int long_jumps, double expansion, int update_depth, StatisticsContainer stats) Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al.
void	fastRemove(T node_to_remove) Remove a node from the graph (and update the graph) using fast approximate algorithm.
void	fastRemove(T node_to_remove, int update_depth, StatisticsContainer stats) Remove a node from the graph (and update the graph) using fast approximate algorithm.
NeighborList	fastSearch(T query, int k) Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al.
NeighborList	fastSearch(T query, int k, double speedup) Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al.
NeighborList	fastSearch(T query, int k, double speedup, int long_jumps, double expansion) Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al.
NeighborList	fastSearch(T query, int k, double speedup, int long_jumps, double expansion, StatisticsContainer stats) Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al.
LinkedList<T>	findNeighbors(LinkedList<T> starting_points, int depth) Recursively search neighbors of neighbors, up to a given depth.
T	first() Get the first node in the graph.
HashMap<T,NeighborList>	getHashMap() Get the underlying hash map that stores the nodes and associated neighborlists.
int	getK() Get k (the number of edges per node).
NeighborList	getNeighbors(T node) Get the neighborlist of this node.
Iterable<T>	getNodes()
SimilarityInterface<T>	getSimilarity() Get the similarity measure.
int	hashCode()
void	prune(double threshold) Remove from the graph all edges with a similarity lower than threshold.
NeighborList	put(T node, NeighborList neighborlist)
NeighborList	search(T query, int k) Multi-thread exhaustive search.
void	setK(int k) Set k (the number of edges per node).
void	setSimilarity(SimilarityInterface<T> similarity) Set the similarity measure used to build or search the graph.
int	size()
ArrayList<Graph<T>>	stronglyConnectedComponents() Computes the strongly connected sub-graphs (where every node is reachable from every other node) using Tarjan's algorithm, which has computation cost O(n).
String	toString()
void	writeGEXF(String filename) Writes the graph as a GEXF file (to be used in Gephi, for example).

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Field Detail

DEFAULT_K

public static final int DEFAULT_K

Number of edges per node.

See Also:

Constant Field Values

DEFAULT_SEARCH_SPEEDUP

public static final double DEFAULT_SEARCH_SPEEDUP

Fast search: speedup compared to exhaustive search.

See Also:

Constant Field Values

DEFAULT_SEARCH_EXPANSION

public static final double DEFAULT_SEARCH_EXPANSION

Fast search: expansion parameter.

See Also:

Constant Field Values

DEFAULT_SEARCH_RANDOM_JUMPS

public static final int DEFAULT_SEARCH_RANDOM_JUMPS

Fast search: number of random jumps per node (to simulate small world graph).

See Also:

Constant Field Values

DEFAULT_UPDATE_DEPTH

public static final int DEFAULT_UPDATE_DEPTH

Fast add or remove node: depth of search to update the graph.

See Also:

Constant Field Values

Constructor Detail

Graph

public Graph(Graph<T> origin)

Copy constructor.

Parameters:

origin -

Graph

public Graph(int k)

Initialize an empty graph, and set k (number of edges per node). Default k is 10.

Parameters:

k -

Graph

public Graph()

Initialize an empty graph with k = 10.

Method Detail

getSimilarity

public final SimilarityInterface<T> getSimilarity()

Get the similarity measure.

Returns:

setSimilarity

public final void setSimilarity(SimilarityInterface<T> similarity)

Set the similarity measure used to build or search the graph.

Parameters:

similarity -

getK

public final int getK()

Get k (the number of edges per node).

Returns:

setK

public final void setK(int k)

Set k (the number of edges per node). The existing graph will not be modified.

Parameters:

k -

getNeighbors

public final NeighborList getNeighbors(T node)

Get the neighborlist of this node.

Parameters:

node -

Returns:

the neighborlist of this node

first

public final T first()
              throws NoSuchElementException

Get the first node in the graph.

Returns:

The first node in the graph

Throws:

NoSuchElementException - if the graph is empty...

prune

public final void prune(double threshold)

Remove from the graph all edges with a similarity lower than threshold.

Parameters:

threshold -

connectedComponents

public final ArrayList<Graph<T>> connectedComponents()

Split the graph in connected components (usually you will first prune the graph to remove "weak" edges).

Returns:

stronglyConnectedComponents

public final ArrayList<Graph<T>> stronglyConnectedComponents()

Computes the strongly connected sub-graphs (where every node is reachable from every other node) using Tarjan's algorithm, which has computation cost O(n).

Returns:

put

public final NeighborList put(T node,
               NeighborList neighborlist)

Parameters:

node -

neighborlist -

Returns:

containsKey

public final boolean containsKey(T node)

Parameters:

node -

Returns:

size

public final int size()

Returns:

entrySet

public final Iterable<Map.Entry<T,NeighborList>> entrySet()

Returns:

getNodes

public final Iterable<T> getNodes()

Returns:

findNeighbors

public final LinkedList<T> findNeighbors(LinkedList<T> starting_points,
                          int depth)

Recursively search neighbors of neighbors, up to a given depth.

Parameters:

starting_points -

depth -

Returns:

getHashMap

public final HashMap<T,NeighborList> getHashMap()

Get the underlying hash map that stores the nodes and associated neighborlists.

Returns:

search

public final NeighborList search(T query,
                  int k)
                          throws InterruptedException,
                                 ExecutionException

Multi-thread exhaustive search.

Parameters:

query -

k -

Returns:

Throws:

InterruptedException - if thread is interrupted

ExecutionException - if thread cannot complete

fastSearch

public final NeighborList fastSearch(T query,
                      int k)

Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al. Default speedup is 4.

Parameters:

query -

k - search K neighbors

Returns:

See Also:

Fast Online k-nn Graph Building

fastSearch

public final NeighborList fastSearch(T query,
                      int k,
                      double speedup)

Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al.

Parameters:

query -

k - search k neighbors

speedup - speedup for searching (> 1, default 4)

Returns:

See Also:

Fast Online k-nn Graph Building

fastSearch

public final NeighborList fastSearch(T query,
                      int k,
                      double speedup,
                      int long_jumps,
                      double expansion)

Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al.

Parameters:

query -

k -

speedup -

long_jumps -

expansion -

Returns:

See Also:

Fast Online k-nn Graph Building

fastSearch

public final NeighborList fastSearch(T query,
                      int k,
                      double speedup,
                      int long_jumps,
                      double expansion,
                      StatisticsContainer stats)

Approximate fast graph based search, as published in "Fast Online k-nn Graph Building" by Debatty et al.

Parameters:

query - query point

k - number of neighbors to find (the K from K-nn search)

speedup - (default: 4.0)

long_jumps - (default: 2)

expansion - (default: 1.2)

stats -

Returns:

See Also:

Fast Online k-nn Graph Building

writeGEXF

public final void writeGEXF(String filename)
                     throws FileNotFoundException,
                            IOException

Writes the graph as a GEXF file (to be used in Gephi, for example).

Parameters:

filename -

Throws:

FileNotFoundException - if filename is invalid

IOException - if cannot write to file

add

public final int add(T new_node)

Add a node to the online graph using exhaustive search approach. Adding a node requires to compute the similarity between the new node and every other node in the graph...

Parameters:

new_node -

Returns:

fastAdd

public final void fastAdd(T node)

Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al. Default speedup is 4 compared to exhaustive search.

Parameters:

node -

fastAdd

public final void fastAdd(T node,
           double speedup)

Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al. Uses default number of long jumps (2) and default expansion (1.2).

Parameters:

node -

speedup -

fastAdd

public final void fastAdd(T new_node,
           double speedup,
           int long_jumps,
           double expansion)

Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al.

Parameters:

new_node -

speedup - compared to exhaustive search

long_jumps -

expansion -

fastAdd

public final void fastAdd(T new_node,
           double speedup,
           int long_jumps,
           double expansion,
           int update_depth,
           StatisticsContainer stats)

Add a node to the online graph, using approximate online graph building algorithm presented in "Fast Online k-nn Graph Building" by Debatty et al.

Parameters:

new_node -

speedup - compared to exhaustive search

long_jumps -

expansion -

update_depth -

stats -

fastRemove

public final void fastRemove(T node_to_remove)

Remove a node from the graph (and update the graph) using fast approximate algorithm.

Parameters:

node_to_remove -

fastRemove

public final void fastRemove(T node_to_remove,
              int update_depth,
              StatisticsContainer stats)

Remove a node from the graph (and update the graph) using fast approximate algorithm.

Parameters:

node_to_remove -

update_depth -

stats -

compare

public final int compare(Graph<T> other)

Count the number of edges/neighbors that are the same (based on similarity) in both graphs.

Parameters:

other -

Returns:

toString

public final String toString()

Overrides:

toString in class Object

hashCode

public int hashCode()

Overrides:

hashCode in class Object

equals

public boolean equals(Object obj)

Overrides:

equals in class Object