本文整理汇总了Java中org.apache.commons.math3.ml.neuralnet.SquareNeighbourhood.VON_NEUMANN属性的典型用法代码示例。如果您正苦于以下问题：Java SquareNeighbourhood.VON_NEUMANN属性的具体用法？Java SquareNeighbourhood.VON_NEUMANN怎么用？Java SquareNeighbourhood.VON_NEUMANN使用的例子？那么恭喜您, 这里精选的属性代码示例或许可以为您提供帮助。您也可以进一步了解该属性所在类org.apache.commons.math3.ml.neuralnet.SquareNeighbourhood的用法示例。
在下文中一共展示了SquareNeighbourhood.VON_NEUMANN属性的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: testMinimalNetworkSize1
@Test(expected=NumberIsTooSmallException.class)
public void testMinimalNetworkSize1() {
final FeatureInitializer[] initArray = { init };
new NeuronSquareMesh2D(1, false,
2, false,
SquareNeighbourhood.VON_NEUMANN,
initArray);
}
示例2: testMinimalNetworkSize2
@Test(expected=NumberIsTooSmallException.class)
public void testMinimalNetworkSize2() {
final FeatureInitializer[] initArray = { init };
new NeuronSquareMesh2D(2, false,
0, false,
SquareNeighbourhood.VON_NEUMANN,
initArray);
}
示例3: testSerialize
@Test
public void testSerialize()
throws IOException,
ClassNotFoundException {
final FeatureInitializer[] initArray = { init };
final NeuronSquareMesh2D out = new NeuronSquareMesh2D(4, false,
3, true,
SquareNeighbourhood.VON_NEUMANN,
initArray);
final ByteArrayOutputStream bos = new ByteArrayOutputStream();
final ObjectOutputStream oos = new ObjectOutputStream(bos);
oos.writeObject(out);
final ByteArrayInputStream bis = new ByteArrayInputStream(bos.toByteArray());
final ObjectInputStream ois = new ObjectInputStream(bis);
final NeuronSquareMesh2D in = (NeuronSquareMesh2D) ois.readObject();
for (Neuron nOut : out.getNetwork()) {
final Neuron nIn = in.getNetwork().getNeuron(nOut.getIdentifier());
// Same values.
final double[] outF = nOut.getFeatures();
final double[] inF = nIn.getFeatures();
Assert.assertEquals(outF.length, inF.length);
for (int i = 0; i < outF.length; i++) {
Assert.assertEquals(outF[i], inF[i], 0d);
}
// Same neighbours.
final Collection<Neuron> outNeighbours = out.getNetwork().getNeighbours(nOut);
final Collection<Neuron> inNeighbours = in.getNetwork().getNeighbours(nIn);
Assert.assertEquals(outNeighbours.size(), inNeighbours.size());
for (Neuron oN : outNeighbours) {
Assert.assertTrue(inNeighbours.contains(in.getNetwork().getNeuron(oN.getIdentifier())));
}
}
}