/* * 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.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]); } }