org.openimaj.knn.InternalNearestNeighbours Maven / Gradle / Ivy
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* Copyright (c) 2011, The University of Southampton and the individual contributors.
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package org.openimaj.knn;
/**
* Interface for K-nearest-neighbour implementations that are able to search
* directly using an indexed item of their own internal data as the query.
*
* @author Jonathon Hare ([email protected])
*
* @param
* The type of distances measured (usually an array type)
*/
public interface InternalNearestNeighbours {
/**
* Search for the nearest neighbour to each of the N queries (given by their
* index in this nearest neighbours object), and return the index of each
* nearest neighbour and the respective distance.
*
* This method should not return the same index as the query (i.e.
* technically it should find the second-nearest-neighbour)
*
* For efficiency, to use this method, you need to pre-construct the arrays
* for storing the results outside of the method and pass them in as
* arguments.
*
* @param qus
* An array of N query vectors
* @param nnIndices
* The return N-dimensional array for holding the indices of the
* nearest neighbour of each respective query.
* @param nnDistances
* The return N-dimensional array for holding the distances of
* the nearest neighbour to each respective query.
*/
public abstract void searchNN(final int[] qus, int[] nnIndices, DISTANCES nnDistances);
/**
* Search for the K nearest neighbours to each of the N queries, and return
* the indices of each nearest neighbour and their respective distances.
*
* This method should not return the same index as the query (i.e.
* technically it should find the second-nearest-neighbour as the first
* returned value)
*
* For efficiency, to use this method, you need to pre-construct the arrays
* for storing the results outside of the method and pass them in as
* arguments.
*
* @param qus
* An array of N query indices
* @param K
* the number of neighbours to find
* @param nnIndices
* The return N*K-dimensional array for holding the indices of
* the K nearest neighbours of each respective query.
* @param nnDistances
* The return N*K-dimensional array for holding the distances of
* the nearest neighbours of each respective query.
*/
public abstract void searchKNN(final int[] qus, int K, int[][] nnIndices, DISTANCES[] nnDistances);
}