info.debatty.java.graphs

Class Graph<T>

java.lang.Object

java.util.AbstractMap<K,V>

java.util.HashMap<Node<T>,NeighborList>

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

Type Parameters:

T - The type of nodes value

All Implemented Interfaces:

Serializable, Cloneable, Map<Node<T>,NeighborList>

public class Graph<T>
extends HashMap<Node<T>,NeighborList>

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

Author:

Thibault Debatty

See Also:

Serialized Form

Nested Class Summary

Nested classes/interfaces inherited from class java.util.AbstractMap

AbstractMap.SimpleEntry<K,V>, AbstractMap.SimpleImmutableEntry<K,V>

Constructor Summary

Constructors

Constructor and Description
Graph()
Graph(int n)

Method Summary

Methods

Modifier and Type	Method and Description
ArrayList<Graph<T>>	connectedComponents() Split the graph in connected components (usually you will first prune the graph to remove "weak" edges).
NeighborList	get(Node node) Get the neighborlist of this node
void	prune(double threshold) Remove from the graph all edges with a similarity lower than threshold
NeighborList	search(T query, int K, SimilarityInterface<T> similarity_measure, int max_similarities) Perform approximate k-nn search on this graph.
NeighborList	search(T query, int K, SimilarityInterface<T> similarity_measure, int max_similarities, int search_depth, double expansion) Implementation of Graph Nearest Neighbor Search (GNNS) algorithm from paper "Fast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph" by Hajebi et al.
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).
void	writeGEXF(String filename) Writes the graph as a GEXF file (to be used in Gephi, for example)

Methods inherited from class java.util.HashMap

clear, clone, containsKey, containsValue, entrySet, get, isEmpty, keySet, put, putAll, remove, size, values

Methods inherited from class java.util.AbstractMap

equals, hashCode, toString

Methods inherited from class java.lang.Object

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

Methods inherited from interface java.util.Map

equals, hashCode

Constructor Detail

Graph

public Graph(int n)

Graph

public Graph()

Method Detail

get

public NeighborList get(Node node)

Get the neighborlist of this node

Parameters:

node -

Returns:

the neighborlist of this node

prune

public void prune(double threshold)

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

Parameters:

threshold -

connectedComponents

public ArrayList<Graph<T>> connectedComponents()

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

Returns:

stronglyConnectedComponents

public 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:

search

public NeighborList search(T query,
                  int K,
                  SimilarityInterface<T> similarity_measure,
                  int max_similarities)

Perform approximate k-nn search on this graph.

Parameters:

query -

K - search K neighbors

similarity_measure -

max_similarities - perform max max_similarities similarity computations

Returns:

search

public NeighborList search(T query,
                  int K,
                  SimilarityInterface<T> similarity_measure,
                  int max_similarities,
                  int search_depth,
                  double expansion)

Implementation of Graph Nearest Neighbor Search (GNNS) algorithm from paper "Fast Approximate Nearest-Neighbor Search with k-Nearest Neighbor Graph" by Hajebi et al. The algorithm is basically a best-first search method with random starting points.

Parameters:

query - query point

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

max_similarities - max similarities to compute

search_depth - number of greedy steps (default: 100)

similarity_measure - similarity measure

expansion - (default: 1.01)

Returns:

writeGEXF

public 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

IOException