/// <summary>
/// Connects two neurons.
/// </summary>
/// <param name="neuron1">First neuron, cannot be OutputNeuron.</param>
/// <param name="neuron2">Second neuron, cannot be InputNeuron.</param>
/// <returns>InputLink of seocnd neuron.</returns>
private Neuron.InputLink Connect(Neuron neuron1, Neuron neuron2)
{
if (neuron1.Type == NeuronType.OutputNeuron)
{
throw new NeuralNetworkException("Output neuron cannot have output links");
}
if (neuron2.Type == NeuronType.InputNeuron)
{
throw new NeuralNetworkException("Input neuron cannot have input links");
}
Neuron.InputLink newInputLink = new Neuron.InputLink(neuron1, 0.0);
neuron2.InputLinks.Add(newInputLink);
neuron1.OutputLinks.Add(neuron2);
// since network structure changed, neurons have to be sorted
this.SortNeurons();
return(newInputLink);
}
/// <summary>
/// Loads neural network from txt file.
/// </summary>
/// <param name="filename">Name of the file.</param>
/// <returns>Neural network loaded from the file.</returns>
#pragma warning disable SA1204 // Static elements should appear before instance elements
public static NeuralNetwork LoadFromFile(string filename)
#pragma warning restore SA1204 // Static elements should appear before instance elements
{
// object which will be returned
NeuralNetwork loadedNetwork = new NeuralNetwork();
using (StreamReader reader = new StreamReader(filename))
{
// loading network properties
loadedNetwork.Id = int.Parse(reader.ReadLine().Split(' ')[1]);
// loading extra properties
while (true)
{
string nextLine = reader.ReadLine();
// list of properties ends with empty line
if (nextLine == null || nextLine == string.Empty)
{
break;
}
loadedNetwork.ExtraProperties.Add(nextLine.Split(' ')[0], nextLine.Split(' ')[1]);
}
// first pass, loading list of neurons and creating them
while (true)
{
string nextLine = reader.ReadLine();
// checking if list has ended
if (nextLine == null || nextLine == string.Empty)
{
break;
}
// skipping lines with weights
if (nextLine.StartsWith(" "))
{
continue;
}
// creating new neuron
Neuron newNeuron = null;
string[] neuronHeader = nextLine.Split(' ');
switch (neuronHeader[0])
{
case "Input": newNeuron = loadedNetwork.AddInputNeuron(string.Empty); break;
case "Hidden": newNeuron = loadedNetwork.AddHiddenNeuron(string.Empty); break;
case "Output": newNeuron = loadedNetwork.AddOutputNeuron(string.Empty); break;
}
newNeuron.Id = int.Parse(neuronHeader[1]);
newNeuron.Name = neuronHeader[2];
}
// reset position to the beginning of the file
reader.DiscardBufferedData();
reader.BaseStream.Seek(0, SeekOrigin.Begin);
// skipping network parameters and empty line in the beginning
while (true)
{
string nextLine = reader.ReadLine();
if (nextLine == string.Empty)
{
break;
}
}
// second pass, loading neurons
while (true)
{
// cheking if list has ended
string nextLine = reader.ReadLine();
if (nextLine == null || nextLine == string.Empty)
{
break;
}
// finding neuron
string[] neuronHeader = nextLine.Split(' ');
int neuronId = int.Parse(neuronHeader[1]);
Neuron neuron = loadedNetwork.GetNeuronById(neuronId);
// loading weights and bias
while (true)
{
string[] weightOrBiasLine = reader.ReadLine().Trim().Split(' ');
string label = weightOrBiasLine[0];
double value = double.Parse(weightOrBiasLine[1]);
if (label == "w")
{
int connection = int.Parse(weightOrBiasLine[2]);
Neuron anotherNeuron = loadedNetwork.GetNeuronById(connection);
Neuron.InputLink newInputLink = loadedNetwork.Connect(anotherNeuron, neuron);
newInputLink.Weight = value;
}
else if (label == "b")
{
neuron.Bias = value;
break; // line with bias is the last line of the neuron
}
}
}
}
return(loadedNetwork);
}
