/**
 * Copyright (C) 2017 Jan Schäfer (jansch@users.sourceforge.net)
 *
 * 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.
 */
package org.jskat.ai.nn.util;

public interface INeuralNetwork {

	/**
	 * Gets the average difference of all output neurons
	 *
	 * @return Average difference
	 */
	double getAvgDiff();

	/**
	 * Adjusts the weights of the net according inputs and desired outputs
	 *
	 * @param inputs
	 *            Input attributes
	 * @param outputs
	 *            Output attributes
	 * @return Average error
	 */
	double adjustWeights(double[] inputs, double[] outputs);

	/**
	 * Adjusts the weights of the net with a batch training set.
	 *
	 * @param inputs
	 *            Input attributes
	 * @param outputs
	 *            Output attributes
	 * @return Average error
	 */
	double adjustWeightsBatch(double[][] inputs, double[][] outputs);

	/**
	 * Resets the network, sets random values for all weights
	 */
	public abstract void resetNetwork();

	/**
	 * Gets the predicted outcome of a game according inputs
	 *
	 * @param inputs
	 *            Input attributes
	 * @return Predicted outcome
	 */
	public abstract double getPredictedOutcome(double[] inputs);

	/**
	 * Gets the number of iterations the NeuralNetwork was trained so far
	 *
	 * @return Number of iterations
	 */
	public abstract long getIterations();

	/**
	 * Save the network parameters to a file
	 *
	 * @param fileName
	 *            File name to save to
	 * @return TRUE if the saving was successful
	 */
	public abstract boolean saveNetwork(String fileName);

	/**
	 * Loads network parameters from a file
	 *
	 * @param fileName
	 *            File name to load from
	 * @param inputNeurons
	 *            Number of input neurons
	 * @param hiddenNeurons
	 *            Number of hidden neurons
	 * @param outputNeurons
	 *            Number of output neurons
	 */
	public abstract void loadNetwork(String fileName, int inputNeurons, int hiddenNeurons, int outputNeurons);
}