public void saveNetworkOnFile(string path)
{
// Delete the file if it exists.
if (File.Exists(path))
{
File.Delete(path);
}
FileStream fs = File.Create(path);
string netConfig = "";
netConfig += "Rho " + this.rho + "\r\n";
netConfig += "RhoInc " + this.rhoIncrement + "\r\n";
netConfig += "Alpha " + this.alpha + "\r\n";
netConfig += "Beta " + this.beta + "\r\n";
netConfig += "CC " + this.complementCoding + "\r\n";
netConfig += "F1 " + this.ARTModule.F1.Count + "\r\n";
netConfig += "MFCategoryCount " + this.mapField.getCategoryCount() + "\r\n";
for (int catIndex = 0; catIndex < this.mapField.getCategoryCount(); catIndex++)
{
MapFieldCategory cat = (MapFieldCategory)this.mapField.categories[catIndex];
netConfig += cat.getCode() + "\r\n";
netConfig += cat.getName() + "\r\n";
}
netConfig += "ContextCount " + this.ARTModule.contextField.Count + "\r\n";
ICollection contextKeys = this.ARTModule.contextField.Keys;
IEnumerator contextKeysEnum = contextKeys.GetEnumerator();
while (contextKeysEnum.MoveNext())
{
int contextKey = Int32.Parse(contextKeysEnum.Current.ToString());
netConfig += "Context " + contextKey + "\r\n";
LayerF2 F2 = ((LayerF2)this.ARTModule.contextField[contextKey]);
netConfig += "F2Count " + F2.Count + "\r\n";
for (int f2Index = 0; f2Index < F2.Count; f2Index++)
{
netConfig += "Prototype\r\n";
double [] prototype = ((F2Neuron)F2[f2Index]).getProtoTypeCluster();
for (int i = 0; i < prototype.Length; i++)
{
netConfig += prototype[i] + "\t";
}
netConfig += "\r\n";
netConfig += "tdConnWs\r\n";
SynapticConnection[] conns = ((F2Neuron)F2[f2Index]).getConnections();
for (int connIndex = 0; connIndex < conns.Length; connIndex++)
{
netConfig += ((SynapticConnection)conns[connIndex]).getWeight() + "\t";
}
netConfig += "\r\n";
netConfig += "CatCode\r\n";
//for (int f2Index = 0; f2Index < F2.Count; f2Index++)
{
MapFieldConnection mapFieldConn = ((F2Neuron)F2[f2Index]).getMapFieldConnection();
netConfig += mapFieldConn.getCategory().getCode() + "\r\n";
}
}
}
AddText(fs, netConfig);
fs.Close();
}
public object[,] getCluster(int contextCode, double[] I)
{
LayerF2 F2 = (LayerF2)contextField[contextCode];
object[,] cluster = new object[1, 2];
double[] T = new double[F2.Count];
double[] i = new double[I.Length * 2];
if (complementCoding)
{
i = new double[I.Length * 2];
i = complement(I);
}
else
{
i = new double[I.Length];
i = I;
}
T = F1.processInput(i, alpha, F2);
int repeatCount = 1;
Repeater: // Control shall come up here in case there are more than one members in T,
object[,] j_AND_Z_td_J = F2.processInput(T);
int j = (int)j_AND_Z_td_J[0, 0];
double[] Z_td_J = (double[])j_AND_Z_td_J[0, 1];
//Adaptation Phase
if (vigilancePass(i, Z_td_J))
{
cluster[0, 0] = Z_td_J;
cluster[0, 1] = j;
}
else
{
if (repeatCount <= T.Length)
{
T[j] = -1;
repeatCount++;
goto Repeater;
}
// MinDist F2Neuron does not resonate with this i, make a new category for it
else
{
double[] d = { -1.0 };
cluster[0, 0] = d;
cluster[0, 1] = -1;
}
}
return(cluster);
}
public MapFieldCategory recallCat(int contextCode, double[] Pattern) //THIS METHOD ASSUMES THAT EACH F2 NODE IS CONNECTED WITH ONLY ONE MAPFIELD NODE
{
ARTModule.reSetRho(rho);
LayerF2 contextNeurons = (LayerF2)ARTModule.contextField[contextCode];
object[,] artCluster = ARTModule.getCluster(contextCode, Pattern);
if ((int)artCluster[0, 1] == -1)
{
return(null);
}
else
{
F2Neuron f2Neuron = (F2Neuron)contextNeurons[(int)artCluster[0, 1]];
MapFieldConnection mfConn = f2Neuron.getMapFieldConnection();
return(mfConn.getCategory());
}
}
//public int recall(int contextCode, double[] Pattern) // THIS METHOD ASSUMES THAT EACH F2 NODE HAS CONNECTIONS WITH ALL MAPFIELD NODES
//{
// ARTModule.reSetRho(rho);
// int code = -1; // Don't Know
// LayerF2 contextNeurons = (LayerF2)ARTModule.contextField[contextCode];
// object [,]artCluster = ARTModule.getCluster(contextCode, Pattern);
// if ((int)artCluster[0, 1] == -1)
// code = -1;
// else
// {
// F2Neuron f2Neuron = (F2Neuron)contextNeurons[(int)artCluster[0, 1]];
// f2Neuron.getMapFieldConnections();
// ArrayList mapFieldConnections = f2Neuron.getMapFieldConnections();
// IEnumerator mapFieldConnEnum = mapFieldConnections.GetEnumerator();
// while (mapFieldConnEnum.MoveNext())
// {
// MapFieldConnection mapFieldConn = (MapFieldConnection)mapFieldConnEnum.Current;
// if (mapFieldConn.getWeight() == 1)
// {
// MapFieldCategory category = mapFieldConn.getCategory();
// code = category.getCode();
// //break;
// }
// }
// }
// // code = mapField.getAssociatedCategory(contextNeurons, (int)artCluster[0, 1]);
// return code;
//}
public int recall(int contextCode, double[] Pattern) //THIS METHOD ASSUMES THAT EACH F2 NODE IS CONNECTED WITH ONLY ONE MAPFIELD NODE
{
ARTModule.reSetRho(rho);
int code = -1; // Don't Know
LayerF2 contextNeurons = (LayerF2)ARTModule.contextField[contextCode];
object[,] artCluster = ARTModule.getCluster(contextCode, Pattern);
if ((int)artCluster[0, 1] == -1)
{
code = -1;
}
else
{
F2Neuron f2Neuron = (F2Neuron)contextNeurons[(int)artCluster[0, 1]];
MapFieldConnection mfConn = f2Neuron.getMapFieldConnection();
MapFieldCategory category = mfConn.getCategory();
code = category.getCode();
}
// code = mapField.getAssociatedCategory(contextNeurons, (int)artCluster[0, 1]);
return(code);
}
public double[] processInput(double[] i, double alpha, LayerF2 F2Neurons) // Orienting Subsystem
{
int f2index = 0;
double[] f1Output = new double[F2Neurons.Count];
while (f2index < F2Neurons.Count)
{
F2Neuron f2Neuron = (F2Neuron)F2Neurons[f2index];
int f1index = 0;
double[] z = new double[i.Length];
double I_FuzzyAND_Z = 0.0;
while (f1index < base.Count)
{
z[f1index] = f2Neuron.getWeight(f1index);
I_FuzzyAND_Z += Math.Min(z[f1index], i[f1index]);
f1index++;
}
f1Output[f2index++] = Math.Round((I_FuzzyAND_Z / (alpha + norm(z))), 4);
}
return(f1Output);
}
public object[,] feedInput(int contextCode, double[] I, int catCode)
{
object[,] output = new object[1, 2];
double[] z_td_J_new = new double[i.Length];
if (complementCoding)
{
i = complement(I);
}
else
{
i = I;
}
if (!contextField.ContainsKey(contextCode))
{
//Add Context Code
contextField.Add(contextCode, new LayerF2());
}
//Load Context
LayerF2 F2Neurons = (LayerF2)contextField[contextCode];
if (F2Neurons.Count == 0)
{
output[0, 1] = F2Neurons.AddF2Neuron(F1, i);
output[0, 0] = ((F2Neuron)F2Neurons[0]).getProtoTypeCluster();
}
else
{
double[] T = new double[F2Neurons.Count];
// Recognition Phase (Orientation Subsystem)
T = F1.processInput(i, alpha, F2Neurons);
int repeatCount = 1;
Repeater: // Control shall come up here in case there are more than one members in T,
object[,] j_AND_Z_td_J = F2Neurons.processInput(T);
int J = (int)j_AND_Z_td_J[0, 0];
double[] Z_td_J = (double[])j_AND_Z_td_J[0, 1];
//Adaptation Phase
if (vigilancePass(i, Z_td_J))
{
if (((F2Neuron)F2Neurons[J]).getMapFieldConnection().getCategory().getCode() == catCode)
{
z_td_J_new = F2Neurons.updateWeights(Z_td_J, i, J, beta);
output[0, 0] = z_td_J_new;
output[0, 1] = J;
}
else // invoke match tracking
{
double normIandZ = 0.0;
double normI = 0.0;
for (int index = 0; index < i.Length; index++)
{
normI += Math.Abs(i[index]);
normIandZ += Math.Abs((Math.Min(i[index], Z_td_J[index])));
}
double ro = Math.Round((normIandZ / normI), 4) + this.epsilon;
reSetRho(ro);
T[J] = -1;
repeatCount++;
goto Repeater;
}
}
else
{
if (repeatCount < T.Length)
{
T[J] = -1;
repeatCount++;
goto Repeater;
}
// MinDist F2Neuron does not resonate with this i, make a new category for it
else
{
if (CategoryCountLimit != -1 & F2Neurons.Count == CategoryCountLimit)
{
output[0, 1] = "-1";
output[0, 0] = i;
}
else
{
output[0, 1] = F2Neurons.AddF2Neuron(F1, i);
output[0, 0] = ((F2Neuron)F2Neurons[F2Neurons.Count - 1]).getProtoTypeCluster();
}
}
}
}
return(output);
}
public ConSelfARTMAP(string path)
{
string data = "";
if (netConfigFound(path))
{
try
{
System.IO.StreamReader reader = new System.IO.StreamReader(path);
data = reader.ReadToEnd();
reader.Close();
}
catch (Exception ioerror)
{
Console.Out.WriteLine(ioerror.ToString());
return;
} // cath ends
}
//if (data.Contains("Rho")) POCKET PC .NET DO NOT SUPPORT String.Contains() Method
{
float rho = float.Parse(data.Substring(4, data.IndexOf("\r") - (4)));
this.rho = rho;
data = data.Substring(data.IndexOf("\r") + 2);
}
{
float rhoIncrement = float.Parse(data.Substring(7, data.IndexOf("\r") - 7));
this.rhoIncrement = rhoIncrement;
data = data.Substring(data.IndexOf("\r") + 2);
}
//if (data.Contains("Alpha"))
{
float alpha = float.Parse(data.Substring(5, data.IndexOf("\r") - 5));
this.alpha = alpha;
data = data.Substring(data.IndexOf("\r") + 2);
}
//if (data.Contains("Beta"))
{
float beta = float.Parse(data.Substring(4, data.IndexOf("\r") - 4));
this.beta = beta;
data = data.Substring(data.IndexOf("\r") + 2);
}
//if (data.Contains("CC"))
bool CC = bool.Parse(data.Substring(2, data.IndexOf("\r") - 2));
this.complementCoding = CC;
data = data.Substring(data.IndexOf("\r") + 2);
//if (data.Contains("F1"))
{
int F1Count = int.Parse(data.Substring(2, data.IndexOf("\r") - 2));
if (CC)
{
this.ARTModule = new ConSelFAM.NET.ConSelfART(F1Count / 2, -1, this.rho, this.alpha, this.beta, this.complementCoding);
}
else
{
this.ARTModule = new ConSelFAM.NET.ConSelfART(F1Count, -1, this.rho, this.alpha, this.beta, this.complementCoding);
}
data = data.Substring(data.IndexOf("\r") + 2);
}
{
int MFCategoryCount = Int32.Parse(data.Substring(16, data.IndexOf("\r") - 16)); //16 characters in 'MFCategoryCount '
data = data.Substring(data.IndexOf("\r") + 2);
this.mapField = new MAPField();
for (int i = 0; i < MFCategoryCount; i++)
{
int catCode = Int32.Parse(data.Substring(0, data.IndexOf("\r")));
data = data.Substring(data.IndexOf("\r") + 2);
string catName = data.Substring(0, data.IndexOf("\r"));
data = data.Substring(data.IndexOf("\r") + 2);
this.mapField.addNewCategory(catName, catCode);
}
int contextCount = Int32.Parse(data.Substring(13, data.IndexOf("\r") - 13)); //13 characters in 'ContextCount '
data = data.Substring(data.IndexOf("\r") + 2);
for (int contextIndex = 0; contextIndex < contextCount; contextIndex++)
{
int contextCode = Int32.Parse(data.Substring(8 /*7 characters in 'Context '*/, data.IndexOf("\r") - 8));
LayerF2 F2Layer = new LayerF2();
this.ARTModule.contextField.Add(contextCode, F2Layer);
data = data.Substring(data.IndexOf("\r") + 2);
int F2Count = 0;
//if (data.Contains("F2"))
F2Count = int.Parse(data.Substring(8 /*8 characters in 'F2Count '*/, data.IndexOf("\r") - 8));
data = data.Substring(data.IndexOf("\r") + 2);
for (int i = 0; i < F2Count; i++)
{
// Parse and set F2 Neuron Prototype
double[] prototype = new double[this.ARTModule.F1.Count];
data = data.Substring(data.IndexOf("\r") + 2);
string pt = data.Substring(0, data.IndexOf("\r"));
int F1count = this.ARTModule.F1.Count;
for (int j = 0; j < F1count; j++)
{
prototype[j] = double.Parse(pt.Substring(0, pt.IndexOf("\t")).Trim());
if (j < (this.ARTModule.F1.Count - 1))
{
pt = pt.Substring(pt.IndexOf("\t") + 1);
}
}
data = data.Substring(data.IndexOf("\r") + 2);
data = data.Substring(data.IndexOf("\r") + 2);//discard tdConnWs word from data string
// Parse and set tdConnection Weights
double[] weights = new double[this.ARTModule.F1.Count];
string ws = data.Substring(0, data.IndexOf("\r"));
for (int j = 0; j < this.ARTModule.F1.Count; j++)
{
weights[j] = double.Parse(ws.Substring(0, ws.IndexOf("\t")).Trim());
if (j < (this.ARTModule.F1.Count - 1))
{
ws = ws.Substring(ws.IndexOf("\t") + 1);
}
}
data = data.Substring(data.IndexOf("\r") + 2);
int f2NeuronIndex = F2Layer.AddF2Neuron((LayerF1)this.ARTModule.F1, weights, prototype);
// Parse and set map field connection weights
data = data.Substring(data.IndexOf("\r") + 2);
string catcode = data.Substring(0, data.IndexOf("\r")).Trim();
int code = int.Parse(catcode);
mapField.getCategory(code).addConnection((F2Neuron)F2Layer[f2NeuronIndex]);
}
}
}
}
