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A multidimensional, type-agnostic image processing library.
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/*
 * #%L
 * ImgLib2: a general-purpose, multidimensional image processing library.
 * %%
 * Copyright (C) 2009 - 2018 Tobias Pietzsch, Stephan Preibisch, Stephan Saalfeld,
 * John Bogovic, Albert Cardona, Barry DeZonia, Christian Dietz, Jan Funke,
 * Aivar Grislis, Jonathan Hale, Grant Harris, Stefan Helfrich, Mark Hiner,
 * Martin Horn, Steffen Jaensch, Lee Kamentsky, Larry Lindsey, Melissa Linkert,
 * Mark Longair, Brian Northan, Nick Perry, Curtis Rueden, Johannes Schindelin,
 * Jean-Yves Tinevez and Michael Zinsmaier.
 * %%
 * Redistribution and use in source and binary forms, with or without
 * modification, are permitted provided that the following conditions are met:
 * 
 * 1. Redistributions of source code must retain the above copyright notice,
 *    this list of conditions and the following disclaimer.
 * 2. Redistributions in binary form must reproduce the above copyright notice,
 *    this list of conditions and the following disclaimer in the documentation
 *    and/or other materials provided with the distribution.
 * 
 * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
 * AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
 * IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
 * ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR CONTRIBUTORS BE
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 * ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
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package net.imglib2.neighborsearch;

import net.imglib2.EuclideanSpace;
import net.imglib2.RealLocalizable;
import net.imglib2.Sampler;

/**
 * Radius neighbor search in an Euclidean space. The interface describes
 * implementations that perform the search for a specified reference location
 * and radius, and provide access to the data, location, and distance of the
 * found neighbors until the next search is performed. For every search, the
 * user can choose whether the found neighbors are returned in arbitrary order
 * or sorted by distance to the reference location.
 * 
 * In a multi-threaded application, each thread will need its own
 * {@link RadiusNeighborSearch}.
 * 
 * @author Tobias Pietzsch
 */
public interface RadiusNeighborSearch< T > extends EuclideanSpace
{
	/**
	 * Perform neighbor search within a radius about a reference coordinate. A
	 * point is considered within radius if its distance to the reference is
	 * smaller or equal the radius.
	 * 
	 * @param reference
	 *            the reference coordinate.
	 * @param radius
	 *            the radius about the reference coordinate that should be
	 *            searched for neighbors.
	 * @param sortResults
	 *            whether the results should be ordered by ascending distances
	 *            to reference.
	 */
	public void search( final RealLocalizable reference, final double radius, final boolean sortResults );

	/**
	 * Get the number of points found within radius after a
	 * {@link #search(RealLocalizable, double, boolean)}.
	 * 
	 * @return the number of points found within radius after a
	 *         {@link #search(RealLocalizable, double, boolean)}.
	 */
	public int numNeighbors();

	/**
	 * Access the data of the i^th neighbor within radius. If
	 * {@code sortResults} was set to true, neighbors are ordered by square
	 * Euclidean distance to the reference. Data is accessed through a
	 * {@link Sampler} that guarantees write access if the underlying data set
	 * is writable.
	 */
	public Sampler< T > getSampler( final int i );

	/**
	 * Access the position of the i^th neighbor within
	 * radius. If {@code sortResults} was set to true, neighbors are ordered by
	 * square Euclidean distance to the reference.
	 */
	public RealLocalizable getPosition( final int i );

	/**
	 * Access the square Euclidean distance between the reference location as
	 * used for the last search and the i^th neighbor. If
	 * {@code sortResults} was set to true, neighbors are ordered by square
	 * Euclidean distance to the reference.
	 */
	public double getSquareDistance( final int i );

	/**
	 * Access the Euclidean distance between the reference location as used for
	 * the last search and the i^th neighbor.
	 */
	public double getDistance( final int i );
}