FlatNetworkTest.java

/*
 * 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.flat;

import org.encog.EncogError;
import org.junit.Assert;
import org.junit.Test;

public class FlatNetworkTest {

    @Test(expected = EncogError.class)
    public void testDecodeNetworkThrowExceptionWhenWeightsSizesDiffer() throws Exception {

        FlatNetwork flatNetwork = new FlatNetwork(1, 2, 3, 4, true);

        flatNetwork.decodeNetwork(new double[]{1, 2, 3});
    }

    @Test(expected = NullPointerException.class)
    public void testDecodeNetworkThrowExceptionWhenNetworkIsUninitialized() throws Exception {

        FlatNetwork flatNetwork = new FlatNetwork();

        flatNetwork.decodeNetwork(new double[]{1, 2, 3});
    }

    @Test
    public void testDecodeNetwork() throws Exception {

        FlatNetwork flatNetwork = new FlatNetwork(1, 2, 3, 4, true);
        double[] weights = new double[29];
        for (int i = 0; i < 29; i++) {
            weights[i] = i;
        }

        flatNetwork.decodeNetwork(weights);

        Assert.assertArrayEquals(weights, flatNetwork.getWeights(), 0);
    }
}