Java Code Examples for org.neuroph.core.NeuralNetwork#getLayers()

The following examples show how to use org.neuroph.core.NeuralNetwork#getLayers() . You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may check out the related API usage on the sidebar.
Example 1
Source File: NetworkUtils.java    From developerWorks with Apache License 2.0 6 votes vote down vote up 
/**
 * Returns a NxNxNxN style string showing the layer structure
 * of the specified network.
 * 
 * @param network
 * @return
 */
public static String getNetworkStructure(NeuralNetwork<BackPropagation> network) {
  StringBuilder sb = new StringBuilder();
  //
  // First the inputs
  if (network != null) {
    sb.append(network.getInputsCount());
    //
    // Now for the hidden layers
    for (Layer layer : network.getLayers()) {
      sb.append("x");
      sb.append(layer.getNeuronsCount());
    }
    //
    // Finally, the outputs
    sb.append("x");
    sb.append(network.getOutputsCount());
  }
  return sb.toString();
}
Example 2
Source File: NeuralNetworkCODEC.java    From NeurophFramework with Apache License 2.0 5 votes vote down vote up 
/**
 * Encode a network to an array.
 * @param network The network to encode.
 */
public static void network2array(NeuralNetwork network, double[] array) {
	int index = 0;

                List<Layer> layers = network.getLayers();
	for (Layer layer : layers) {
		for (Neuron neuron : layer.getNeurons()) {
			for (Connection connection : neuron.getOutConnections()) {
				array[index++] = connection.getWeight().getValue();
			}
		}
	}
}
Example 3
Source File: NeuralNetworkCODEC.java    From NeurophFramework with Apache License 2.0 5 votes vote down vote up 
/**
 * Decode a network from an array.
 * @param array The array used to decode.
 * @param network The network to decode into.
 */
public static void array2network(double[] array, NeuralNetwork network) {
	int index = 0;
               
               List<Layer> layers = network.getLayers();
               for (Layer layer : layers) {
		for (Neuron neuron : layer.getNeurons()) {
			for (Connection connection : neuron.getOutConnections()) {
				connection.getWeight().setValue(array[index++]);
				//connection.getWeight().setPreviousValue(array[index++]);
			}
		}
	}
}
Example 4
Source File: NeuralNetworkCODEC.java    From NeurophFramework with Apache License 2.0 5 votes vote down vote up 
/**
 * Determine the array size for the given neural network.
 * @param network The neural network to determine for.
 * @return The size of the array necessary to hold that network.
 */
public static int determineArraySize(NeuralNetwork network) {
	int result = 0;

               List<Layer> layers = network.getLayers();
	for (Layer layer : layers) {
		for (Neuron neuron : layer.getNeurons()) {
			result+=neuron.getOutConnections().size();
		}
	}
	return result;
}
Example 5
Source File: RandomizationSample.java    From NeurophFramework with Apache License 2.0 5 votes vote down vote up 
public static void printWeights(NeuralNetwork<?> neuralNet) {
    for (Layer layer : neuralNet.getLayers()) {
        for (Neuron neuron : layer.getNeurons()) {
            for (Connection connection : neuron.getInputConnections()) {
                System.out.print(connection.getWeight().value + " ");
            }
            System.out.println();
        }
    }
}
Example 6
Source File: WeightsRandomizer.java    From NeurophFramework with Apache License 2.0 4 votes vote down vote up 
/**
 * Iterates and randomizes all layers in specified network
 *
 * @param neuralNetwork neural network to randomize
 */
public void randomize(NeuralNetwork<?> neuralNetwork) {
    for (Layer layer : neuralNetwork.getLayers()) {
            randomize(layer);
    }       
}