public void Init(int[] layers)
{
var neurons = new INeuron[layers.Length][];
_inputValues = new double[layers[0]];
for (var i = 0; i < layers.Length; i++)
{
var layerSize = layers[i];
neurons[i] = new INeuron[layerSize];
for (var j = 0; j < layerSize; j++)
{
INeuron neuron;
if (i == 0)
{
neuron = new InputNeuron();
_inputNeurons.Add(neuron);
}
else if (i < layers.Length - 1)
{
neuron = new FunctionNeuronProcess(_layerFunc);
}
else
{
neuron = new OutputNeuron(_outputFunc);
_outputNeurons.Add(neuron);
}
neurons[i][j] = neuron;
_network.AddNeuron(neuron);
if (i > 0)
{
for (var k = 0; k < layers[i - 1]; k++)
{
var synapse = new Synapse(neurons[i - 1][k], neuron);
synapse.Weight = 1;
_synapses.Add(synapse);
_network.AddSynapse(synapse);
}
}
}
}
}
static void BasicTest()
{
var inputNeuron = new InputNeuron();
var calcNeuron1 = new FunctionNeuronProcess(ds => ds * 2);
var calcNeuron2 = new FunctionNeuronProcess(ds => ds * 2);
var outputNeuron = new OutputNeuron(ds => ds * 2);
var network = new NeuronalNetwork();
network.AddNeuron(inputNeuron);
network.AddNeuron(calcNeuron1);
network.AddNeuron(calcNeuron2);
network.AddNeuron(outputNeuron);
var synapse11 = network.CreateSynapse(inputNeuron, calcNeuron1);
var synapse12 = network.CreateSynapse(inputNeuron, calcNeuron2);
var synapse21 = network.CreateSynapse(calcNeuron1, outputNeuron);
var synapse22 = network.CreateSynapse(calcNeuron2, outputNeuron);
synapse11.Weight = 2;
synapse12.Weight = 2;
synapse21.Weight = 2;
synapse22.Weight = 2;
Console.WriteLine("Write any Value");
var input = string.Empty;
do
{
network.Reset();
Console.Write("> ");
input = Console.ReadLine();
if (double.TryParse(input, out double value))
{
inputNeuron.Value = value;
Console.Write("Calculating..");
network.FeedForward();
Console.WriteLine("Finished. Result: " + outputNeuron.Value);
}
} while (input != string.Empty);
}
