public void loadLVQNet(string path)
{
if (neuralReader.netConfigFound(path))
{
try
{
WeightsMatrix wm = neuralReader.readConfiguration(path);
lvqNet = new LVQNet(wm);
}
catch (Exception e) {
throw e;
}
}
}
public WeightsMatrix readConfiguration(string path)
{
WeightsMatrix wm;
string data = "";
try
{
System.IO.StreamReader reader = new System.IO.StreamReader(path);
data = reader.ReadToEnd();
reader.Close();
float[] weightsRow = new float[1];
ArrayList netConfigMatrix = new ArrayList();
string strctr = data.Substring(1, data.IndexOf("]", 0) - 1);
data = data.Substring(strctr.Length + 2);
ArrayList structure = new ArrayList();
int spaceindex = 0;
string s = "";
while (true)
{
spaceindex = strctr.IndexOf(" ", 0);
if (spaceindex == -1)
{
structure.Add(Convert.ToInt16(strctr));
break;
}
s = strctr.Substring(0, spaceindex);
structure.Add(Convert.ToInt16(s));
strctr = strctr.Substring(spaceindex, strctr.Length - spaceindex);
strctr = strctr.Trim();
}
netConfigMatrix.Add(structure);
string iw = data.Substring(1, data.IndexOf("]", 0) - 1);
data = data.Substring(iw.Length + 2);
double[,] IW = new double[Int32.Parse(structure[1].ToString()), Int32.Parse(structure[0].ToString())];
spaceindex = 0;
int semicolonindex = 0;
int rowCount = 0;
int columnCount = 0;
s = "";
int inputNeruronCount = int.Parse(structure[structure.Count - 2].ToString());
int inputNeruronIndex = 0;
while (inputNeruronIndex < inputNeruronCount)
{
semicolonindex = iw.IndexOf(";");
string w = "";
if (semicolonindex == -1)
{
w = iw.Substring(0).Trim();
}
else
{
w = iw.Substring(0, semicolonindex).Trim();
iw = iw.Substring(semicolonindex + 1);
}
for (int colCount = 0; columnCount < IW.GetLength(1); colCount++)
{
spaceindex = w.IndexOf(" ", 0);
if (spaceindex == -1)
{
IW[rowCount, colCount] = double.Parse(w);
break;
}
s = w.Substring(0, spaceindex);
IW[rowCount, colCount] = double.Parse(s);
w = w.Substring(spaceindex, w.Length - spaceindex).Trim();
}
rowCount++;
inputNeruronIndex++;
}
string lw = data.Substring(1, data.IndexOf("]", 0) - 1);
int[,] LW = new int[Int32.Parse(structure[2].ToString()), Int32.Parse(structure[1].ToString())];
spaceindex = 0;
semicolonindex = 0;
rowCount = 0;
columnCount = 0;
s = "";
int outputNeruronCount = int.Parse(structure[structure.Count - 1].ToString());
int outputNeruronIndex = 0;
while (outputNeruronIndex < outputNeruronCount)
{
semicolonindex = lw.IndexOf(";");
string w = "";
if (semicolonindex == -1)
{
w = lw.Substring(0).Trim();
}
else
{
w = lw.Substring(0, semicolonindex).Trim();
lw = lw.Substring(semicolonindex + 1);
}
for (int colCount = 0; columnCount < LW.GetLength(1); colCount++)
{
spaceindex = w.IndexOf(" ", 0);
if (spaceindex == -1)
{
LW[rowCount, colCount] = Int32.Parse(w);
break;
}
s = w.Substring(0, spaceindex);
LW[rowCount, colCount] = Int32.Parse(s);
w = w.Substring(spaceindex, w.Length - spaceindex).Trim();
}
rowCount++;
outputNeruronIndex++;
}
wm = new WeightsMatrix(IW, LW);
return(wm);
}
catch (Exception ioerror)
{
throw ioerror;
}
}
public LVQNet(WeightsMatrix wm)
{
layerOne = new HiddenLayer(wm.IW);
layerTwo = new OutputLayer(wm.LW);
}