public void testAnalyze() {
BasicNetwork network = EncogUtility.simpleFeedForward(2, 2, 0, 1, false);
double[] weights = new double[network.encodedArrayLength()];
EngineArray.fill(weights, 1.0);
network.decodeFromArray(weights);
AnalyzeNetwork analyze = new AnalyzeNetwork(network);
Assert.assertEquals(weights.length, analyze.getWeightsAndBias().getSamples());
Assert.assertEquals(3, analyze.getBias().getSamples());
Assert.assertEquals(6, analyze.getWeights().getSamples());
}
public void testFactoryFeedforward() {
String architecture = "?:B->TANH->3->LINEAR->?:B";
MLMethodFactory factory = new MLMethodFactory();
BasicNetwork network =
(BasicNetwork) factory.create(MLMethodFactory.TYPE_FEEDFORWARD, architecture, 1, 4);
Assert.assertTrue(network.isLayerBiased(0));
Assert.assertFalse(network.isLayerBiased(1));
Assert.assertTrue(network.isLayerBiased(2));
Assert.assertEquals(3, network.getLayerCount());
Assert.assertTrue(network.getActivation(0) instanceof ActivationLinear);
Assert.assertTrue(network.getActivation(1) instanceof ActivationTANH);
Assert.assertTrue(network.getActivation(2) instanceof ActivationLinear);
Assert.assertEquals(18, network.encodedArrayLength());
Assert.assertEquals(1, network.getLayerNeuronCount(0));
Assert.assertEquals(3, network.getLayerNeuronCount(1));
Assert.assertEquals(4, network.getLayerNeuronCount(2));
}