/**
 * Copyright (C) 2001-2017 by RapidMiner and the contributors
 * 
 * Complete list of developers available at our web site:
 * 
 * http://rapidminer.com
 * 
 * This program is free software: you can redistribute it and/or modify it under the terms of the
 * GNU Affero General Public License as published by the Free Software Foundation, either version 3
 * of the License, or (at your option) any later version.
 * 
 * This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without
 * even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 * Affero General Public License for more details.
 * 
 * You should have received a copy of the GNU Affero General Public License along with this program.
 * If not, see http://www.gnu.org/licenses/.
*/
package com.rapidminer.tools.math.container;

import com.rapidminer.tools.container.Tupel;

import java.io.Serializable;
import java.util.Collection;


/**
 * This interface provides the methods for multidimensional data structures providing efficient
 * search in data space for the next k neighbors and its distances, or the next neighbors in a
 * specified distance. Also a mixed mode with distance but at least as many is supported.
 * 
 * @author Sebastian Land
 * 
 * @param <T>
 *            The type of the values stored within each point in data space
 */
public interface GeometricDataCollection<T extends Serializable> extends Serializable, Iterable<T> {

	/**
	 * This method has to be called in order to insert new values into the data structure
	 * 
	 * @param values
	 *            specifies the geometric coordinates in data space
	 * @param storeValue
	 *            specifies the value at the given point
	 */

	public abstract void add(double[] values, T storeValue);

	/**
	 * This method returns a collection of the stored data values from the k nearest sample points.
	 * 
	 * @param k
	 *            the number of neighbours
	 * @param values
	 *            the coordinate of the querry point in the sample dimension
	 */
	public abstract Collection<T> getNearestValues(int k, double[] values);

	/**
	 * This method returns a collection of data from the k nearest sample points. This collection
	 * consists of Tupels containing the distance from querrypoint to the samplepoint and in the
	 * second component the contained value of the sample point.
	 * 
	 * @param k
	 *            the number of neighbours
	 * @param values
	 *            the coordinate of the querry point in the sample dimension
	 */
	public abstract Collection<Tupel<Double, T>> getNearestValueDistances(int k, double[] values);

	/**
	 * This method returns a collection of data from all sample points inside the specified
	 * distance. This collection consists of Tupels containing the distance from querrypoint to the
	 * samplepoint and in the second component the contained value of the sample point.
	 * 
	 * @param values
	 *            the coordinate of the querry point in the sample dimension
	 */
	public abstract Collection<Tupel<Double, T>> getNearestValueDistances(double withinDistance, double[] values);

	/**
	 * This method returns a collection of data from all sample points inside the specified distance
	 * but at least k points. So the distance might be enlarged if density is to low. This
	 * collection consists of Tupels containing the distance from querrypoint to the samplepoint and
	 * in the second component the contained value of the sample point.
	 * 
	 * @param values
	 *            the coordinate of the querry point in the sample dimension
	 */
	public abstract Collection<Tupel<Double, T>> getNearestValueDistances(double withinDistance, int butAtLeastK,
			double[] values);

	/**
	 * This method has to return the number of stored data points.
	 */
	public abstract int size();

	/**
	 * This returns the index-th value added to this collection.
	 */
	public abstract T get(int index);
}