public static DataSection[] Parse(string fileName)
{
List<DataSection> dataSecList = new List<DataSection>();
using (StreamReader srIni = ZStreamReader.Open(fileName))
{
string line;
DataSection dataSec = null;
while ((line = srIni.ReadLine()) != null)
{
line.Trim();
if (line.StartsWith("["))
{
if (dataSec != null)
{
dataSecList.Add(dataSec);
}
string name = Regex.Replace(line, @"\[(.*?)\]", "$1");
dataSec = new DataSection(name);
}
else
{
if (line.Length > 0 &&
//igore comments
!line.StartsWith(";") &&
!line.StartsWith("C:", StringComparison.CurrentCultureIgnoreCase))
{
dataSec.AddData(line);
}
}
}
if (dataSec != null)
{
dataSecList.Add(dataSec);
}
}
return dataSecList.ToArray();
}
public InputTransform(DataSection dataSec)
{
string[] fields = dataSec.Name.Split(':');
this.inputID = int.Parse(fields[1]);
for (int i = 0; i < dataSec.Data.Length; i++)
{
if (dataSec.Data[i].StartsWith("Name="))
{
fields = dataSec.Data[i].Split('=');
this.ftrName = fields[1];
}
else if (dataSec.Data[i].StartsWith("Transform="))
{
fields = dataSec.Data[i].Split('=');
this.funcName = fields[1];
this.transformFunc = TransformFunction.Create(this.funcName, dataSec.Data, i + 1);
}
}
}
private static bool IsType(DataSection dataSec)
{
if (dataSec.Name.StartsWith("NeuralNet"))
{
return true;
}
return false;
}
private NNModelMSN(DataSection dataSec)
{
string[] fields;
for (int i = 0; i < dataSec.Data.Length; i++)
{
if (dataSec.Data[i].StartsWith("Layers="))
{
fields = dataSec.Data[i].Split('=');
this.cNodeLayer = int.Parse(fields[1]);
}
else if (dataSec.Data[i].StartsWith("Inputs="))
{
fields = dataSec.Data[i].Split('=');
this.cInputs = int.Parse(fields[1]);
}
}
}
public static bool IsType(DataSection dataSec)
{
if (dataSec.Name.StartsWith("Layer:"))
{
return true;
}
return false;
}
//construct a layer from data
public NodeLayer(DataSection dataSec)
{
string[] fields = dataSec.Name.Split(':');
this.layerID = int.Parse(fields[1]);
for (int i = 0; i < dataSec.Data.Length; i++)
{
if (dataSec.Data[i].StartsWith("nodes=", StringComparison.CurrentCultureIgnoreCase))
{
fields = dataSec.Data[i].Split('=');
this.cNodes = int.Parse(fields[1]);
}
}
nodes = new Node[this.cNodes];
outputs = new float[this.cNodes];
}
private float[] Weights; //Weights[0] is the bias
#endregion Fields
#region Constructors
//construct node from .ini configuration/description
public Node(DataSection dataSec)
{
string[] fields = dataSec.Name.Split(':');
this.layerID = int.Parse(fields[1]);
this.nodeID = int.Parse(fields[2]);
List<float> weightList = new List<float>();
List<int> idxList = new List<int>();
for (int i = 0; i < dataSec.Data.Length; i++)
{
if (dataSec.Data[i].StartsWith("Weight:"))
{
fields = dataSec.Data[i].Split(':');
fields = fields[1].Split('=');
idxList.Add(int.Parse(fields[0]));
weightList.Add(float.Parse(fields[1]));
}
else if (dataSec.Data[i].StartsWith("Type="))
{
fields = dataSec.Data[i].Split('=');
if (string.Compare(fields[1], "Tanh", StringComparison.CurrentCultureIgnoreCase) == 0)
{
this.transFunc = TransferFunction.Tanh;
}
else if (string.Compare(fields[1], "Sigmoid", StringComparison.CurrentCultureIgnoreCase) == 0)
{
this.transFunc = TransferFunction.Sigmoid;
}
else if (string.Compare(fields[1], "Linear", StringComparison.CurrentCultureIgnoreCase) == 0)
{
this.transFunc = TransferFunction.Linear;
}
else if (string.Compare(fields[1], "Logistic", StringComparison.CurrentCultureIgnoreCase) == 0)
{
this.IsLogistic = true;
}
}
}
this.Weights = new float[weightList.Count];
for (int i = 0; i < this.Weights.Length; i++)
{
this.Weights[idxList[i]] = weightList[i];
}
}