/*
 * Encog(tm) Core v3.4 - Java Version
 * http://www.heatonresearch.com/encog/
 * https://github.com/encog/encog-java-core
 
 * Copyright 2008-2016 Heaton Research, Inc.
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 *   
 * For more information on Heaton Research copyrights, licenses 
 * and trademarks visit:
 * http://www.heatonresearch.com/copyright
 */
package org.encog.neural.som.training.basic.neighborhood;

/**
 * Defines how a neighborhood function should work in competitive training. This
 * is most often used in the training process for a self-organizing map. This
 * function determines to what degree the training should take place on a
 * neuron, based on its proximity to the "winning" neuron.
 * 
 * @author jheaton
 * 
 */
public interface NeighborhoodFunction {

	/**
	 * Determine how much the current neuron should be affected by training
	 * based on its proximity to the winning neuron.
	 * 
	 * @param currentNeuron
	 *            THe current neuron being evaluated.
	 * @param bestNeuron
	 *            The winning neuron.
	 * @return The ratio for this neuron's adjustment.
	 */
	double function(int currentNeuron, int bestNeuron);

	/**
	 * @return The radius.
	 */
	double getRadius();

	/**
	 * Set the radius.
	 * @param radius The new radius.
	 */
	void setRadius(double radius);

}