public static void SaveNeuroNet(NeuroNet neuroNet, string filePath)
{
//Random random = new Random();
using (StreamWriter writer = new StreamWriter(filePath))
{
NeuroData.SaveNeuroData(neuroNet.neuroData, writer);
writer.WriteLine(neuroNet.neuroLayer.Length);
for (int i = 0; i < neuroNet.neuroLayer.Length; i++)
{
writer.WriteLine(neuroNet.neuroLayer[i].Neurons.Length);
}
for (int i = 0; i < neuroNet.neuroLayer.Length; i++)
{
for (int j = 0; j < neuroNet.neuroLayer[i].Neurons.Length; j++)
{
for (int k = 0; k < neuroNet.neuroLayer[i].Neurons[j].weights.Length; k++)
{
writer.WriteLine(neuroNet.neuroLayer[i].Neurons[j].weights[k]);
}
}
if (i < neuroNet.neuroLayer.Length - 1)
{
for (int k = 0; k < neuroNet.neuroLayer[i + 1].Neurons.Length; k++)
{
writer.WriteLine(neuroNet.neuroLayer[i].AdditionalNeuron.weights[k]);
}
}
}
}
}
public static NeuroNet CreateNeuroNet(int[] layers, NeuroData neuroData)
{
NeuroNet neuroNet = new NeuroNet();
neuroNet.neuroData = neuroData;
neuroNet.neuroLayer = new NeuroLayer[layers.Length];
neuroNet.SetData();
for (int i = 0; i < layers.Length; i++)
{
if (i < layers.Length - 1)
{
neuroNet.neuroLayer[i] = new NeuroLayer(layers[i], layers[i + 1]);
}
else
{
neuroNet.neuroLayer[i] = new NeuroLayer(layers[i], 0);
}
}
neuroNet.FullZeroingNeurons();
return(neuroNet);
}
public static NeuroNet LoadNeuroNet(string filePath)
{
NeuroNet neuroNet;
using (StreamReader reader = new StreamReader(filePath))
{
NeuroData neuroData = NeuroData.LoadNeuroData(reader);
int number_of_layers = Convert.ToInt32(reader.ReadLine());
int[] layers = new int[number_of_layers];
for (int i = 0; i < number_of_layers; i++)
{
layers[i] = Convert.ToInt32(reader.ReadLine());
}
neuroNet = NeuroNet.CreateNeuroNet(layers, neuroData);
for (int i = 0; i < neuroNet.neuroLayer.Length; i++)
{
for (int j = 0; j < neuroNet.neuroLayer[i].Neurons.Length; j++)
{
for (int k = 0; k < neuroNet.neuroLayer[i].Neurons[j].weights.Length; k++)
{
neuroNet.neuroLayer[i].Neurons[j].weights[k] = Convert.ToSingle(reader.ReadLine());
}
}
if (i < neuroNet.neuroLayer.Length - 1)
{
for (int k = 0; k < neuroNet.neuroLayer[i + 1].Neurons.Length; k++)
{
neuroNet.neuroLayer[i].AdditionalNeuron.weights[k] = Convert.ToSingle(reader.ReadLine());
}
}
}
}
return(neuroNet);
}
public static void SaveNeuroData(NeuroData neuroData, StreamWriter writer)
{
writer.WriteLine(neuroData.number_of_passes);
writer.WriteLine(neuroData.edukationK);
}