public TrainOutstar(CPNNetwork theNetwork, IMLDataSet theTraining, double theLearningRate)
: base(TrainingImplementationType.Iterative)
{
this._x268cb8b20222b0dc = true;
this._x87a7fc6a72741c2e = theNetwork;
this._x823a2b9c8bf459c5 = theTraining;
this._x9b481c22b6706459 = theLearningRate;
}
private void Validate(CPNNetwork cpn)
{
Assert.AreEqual(5, cpn.InputCount);
Assert.AreEqual(4, cpn.InstarCount);
Assert.AreEqual(3, cpn.OutputCount);
Assert.AreEqual(3, cpn.OutstarCount);
Assert.AreEqual(2, cpn.WinnerCount);
Assert.AreEqual(5, cpn.WeightsInputToInstar.Rows);
Assert.AreEqual(4, cpn.WeightsInputToInstar.Cols);
Assert.AreEqual(4, cpn.WeightsInstarToOutstar.Rows);
Assert.AreEqual(3, cpn.WeightsInstarToOutstar.Cols);
}
/// <inheritdoc/>
public Object Read(Stream mask0)
{
IDictionary <String, String> networkParams = null;
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
int inputCount = 0;
int instarCount = 0;
int outputCount = 0;
int winnerCount = 0;
Matrix m1 = null;
Matrix m2 = null;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("CPN") &&
section.SubSectionName.Equals("PARAMS"))
{
networkParams = section.ParseParams();
}
if (section.SectionName.Equals("CPN") &&
section.SubSectionName.Equals("NETWORK"))
{
IDictionary <String, String> paras = section.ParseParams();
inputCount = EncogFileSection.ParseInt(paras,
PersistConst.InputCount);
instarCount = EncogFileSection.ParseInt(paras,
PersistConst.Instar);
outputCount = EncogFileSection.ParseInt(paras,
PersistConst.OutputCount);
winnerCount = EncogFileSection.ParseInt(paras,
PropertyWinnerCount);
m1 = EncogFileSection.ParseMatrix(paras,
PropertyInputToInstar);
m2 = EncogFileSection.ParseMatrix(paras,
PropertyInstarToInput);
}
}
var result = new CPNNetwork(inputCount, instarCount, outputCount,
winnerCount);
EngineArray.PutAll(networkParams, result.Properties);
result.WeightsInputToInstar.Set(m1);
result.WeightsInstarToOutstar.Set(m2);
return(result);
}
public object Read(Stream mask0)
{
IDictionary<string, string> source = null;
EncogFileSection section;
IDictionary<string, string> dictionary2;
EncogReadHelper helper = new EncogReadHelper(mask0);
int theInputCount = 0;
int theInstarCount = 0;
int theOutstarCount = 0;
int theWinnerCount = 0;
Matrix other = null;
Matrix matrix2 = null;
goto Label_0097;
Label_0075:
if (3 == 0)
{
goto Label_00D0;
}
if ((((uint) theInstarCount) + ((uint) theOutstarCount)) > uint.MaxValue)
{
goto Label_019A;
}
Label_0097:
if ((section = helper.ReadNextSection()) != null)
{
if (!section.SectionName.Equals("CPN"))
{
goto Label_00D0;
}
goto Label_019A;
}
CPNNetwork network = new CPNNetwork(theInputCount, theInstarCount, theOutstarCount, theWinnerCount);
EngineArray.PutAll<string, string>(source, network.Properties);
if ((((uint) theInputCount) & 0) != 0)
{
goto Label_0176;
}
network.WeightsInputToInstar.Set(other);
network.WeightsInstarToOutstar.Set(matrix2);
if (((uint) theInstarCount) <= uint.MaxValue)
{
return network;
}
goto Label_00E4;
Label_00D0:
if (!section.SectionName.Equals("CPN"))
{
goto Label_0097;
}
if (((uint) theInstarCount) >= 0)
{
if (section.SubSectionName.Equals("NETWORK"))
{
dictionary2 = section.ParseParams();
theInputCount = EncogFileSection.ParseInt(dictionary2, "inputCount");
goto Label_0176;
}
if (((uint) theInstarCount) >= 0)
{
goto Label_0097;
}
goto Label_0075;
}
return network;
Label_00E4:
theWinnerCount = EncogFileSection.ParseInt(dictionary2, "winnerCount");
other = EncogFileSection.ParseMatrix(dictionary2, "inputToInstar");
matrix2 = EncogFileSection.ParseMatrix(dictionary2, "instarToInput");
if (2 != 0)
{
goto Label_0075;
}
goto Label_00D0;
Label_0176:
theInstarCount = EncogFileSection.ParseInt(dictionary2, "instar");
if (((uint) theWinnerCount) >= 0)
{
theOutstarCount = EncogFileSection.ParseInt(dictionary2, "outputCount");
if ((((uint) theInputCount) + ((uint) theInstarCount)) < 0)
{
goto Label_019A;
}
}
goto Label_00E4;
Label_019A:
if (section.SubSectionName.Equals("PARAMS"))
{
source = section.ParseParams();
}
goto Label_00D0;
}
public void Test(CPNNetwork network, String[][] pattern, double[][] input)
{
for (int i = 0; i < pattern.Length; i++)
{
IMLData inputData = new BasicMLData(input[i]);
IMLData outputData = network.Compute(inputData);
double angle = DetermineAngle(outputData);
// display image
for (int j = 0; j < HEIGHT; j++)
{
if (j == HEIGHT - 1)
app.WriteLine("[" + pattern[i][j] + "] -> " + ((int) angle) + " deg");
else
app.WriteLine("[" + pattern[i][j] + "]");
}
Console.WriteLine();
}
}
public void TrainOutstar(CPNNetwork network, IMLDataSet training)
{
int epoch = 1;
IMLTrain train = new TrainOutstar(network, training, 0.1);
for (int i = 0; i < 1000; i++)
{
train.Iteration();
app.WriteLine("Training outstar, Epoch #" + epoch);
epoch++;
}
}
/// <inheritdoc/>
public Object Read(Stream mask0)
{
IDictionary<String, String> networkParams = null;
var ins0 = new EncogReadHelper(mask0);
EncogFileSection section;
int inputCount = 0;
int instarCount = 0;
int outputCount = 0;
int winnerCount = 0;
Matrix m1 = null;
Matrix m2 = null;
while ((section = ins0.ReadNextSection()) != null)
{
if (section.SectionName.Equals("CPN")
&& section.SubSectionName.Equals("PARAMS"))
{
networkParams = section.ParseParams();
}
if (section.SectionName.Equals("CPN")
&& section.SubSectionName.Equals("NETWORK"))
{
IDictionary<String, String> paras = section.ParseParams();
inputCount = EncogFileSection.ParseInt(paras,
PersistConst.InputCount);
instarCount = EncogFileSection.ParseInt(paras,
PersistConst.Instar);
outputCount = EncogFileSection.ParseInt(paras,
PersistConst.OutputCount);
winnerCount = EncogFileSection.ParseInt(paras,
PropertyWinnerCount);
m1 = EncogFileSection.ParseMatrix(paras,
PropertyInputToInstar);
m2 = EncogFileSection.ParseMatrix(paras,
PropertyInstarToInput);
}
}
var result = new CPNNetwork(inputCount, instarCount, outputCount,
winnerCount);
EngineArray.PutAll(networkParams, result.Properties);
result.WeightsInputToInstar.Set(m1);
result.WeightsInstarToOutstar.Set(m2);
return result;
}
private CPNNetwork Create()
{
CPNNetwork result = new CPNNetwork(5, 4, 3, 2);
return result;
}
