/*
 * Encog(tm) Core Unit Tests v3.0 - Java Version
 * http://www.heatonresearch.com/encog/
 * http://code.google.com/p/encog-java/
 
 * Copyright 2008-2011 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.
 *   
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 */
package org.encog.neural.networks.logic;

import junit.framework.TestCase;

import org.encog.ml.data.MLDataSet;
import org.encog.ml.data.basic.BasicMLDataSet;
import org.encog.ml.train.MLTrain;
import org.encog.neural.networks.BasicNetwork;
import org.encog.neural.networks.NetworkUtil;
import org.encog.neural.networks.XOR;
import org.encog.neural.networks.training.simple.TrainAdaline;
import org.encog.neural.pattern.ADALINEPattern;

public class TestADALINE extends TestCase {

	public void testAdalineNet() throws Throwable
	{
		ADALINEPattern pattern = new ADALINEPattern();
		pattern.setInputNeurons(2);
		pattern.setOutputNeurons(1);
		BasicNetwork network = (BasicNetwork)pattern.generate();
		
		// train it
		MLDataSet training = new BasicMLDataSet(XOR.XOR_INPUT,XOR.XOR_IDEAL);
		MLTrain train = new TrainAdaline(network,training,0.01);
		NetworkUtil.testTraining(train,0.01);
	}
	
}
