/*
* Encog(tm) Core v3.3 - Java Version
* http://www.heatonresearch.com/encog/
* https://github.com/encog/encog-java-core
* Copyright 2008-2014 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.activation;
import junit.framework.TestCase;
import org.encog.engine.network.activation.ActivationLinear;
import org.junit.Assert;
import org.junit.Test;
public class TestActivationLinear extends TestCase {
@Test
public void testLinear() throws Throwable
{
ActivationLinear activation = new ActivationLinear();
Assert.assertTrue(activation.hasDerivative());
ActivationLinear clone = (ActivationLinear)activation.clone();
Assert.assertNotNull(clone);
double[] input = { 1,2,3 };
activation.activationFunction(input,0,input.length);
Assert.assertEquals(1.0,input[0],0.1);
Assert.assertEquals(2.0,input[1],0.1);
Assert.assertEquals(3.0,input[2],0.1);
// test derivative, should throw an error
input[0] = activation.derivativeFunction(input[0],input[0]);
}
}