/// <summary>
/// Froms the bar series to a double array.
/// </summary>
/// <param name="thebarserie">The thebarserie.</param>
/// <returns></returns>
public static double[] FromBarSeriestoDouble(Encog.App.Quant.Loader.OpenQuant.IDataSeries thebarserie)
{
double[] outputtedseries = new double[thebarserie.Count];
int index = 0;
foreach (Data.Data.Bar abar in thebarserie)
{
outputtedseries[index] = abar.Close;
index++;
}
return outputtedseries;
}
public double CalculateScore(Encog.ML.IMLMethod network)
{
return score ();
}
public SupportVectorMachine(int theInputCount, Encog.ML.SVM.SVMType svmType, Encog.ML.SVM.KernelType kernelType)
{
goto Label_02B7;
Label_000B:
this._paras.nr_weight = 0;
Label_0017:
this._paras.weight_label = new int[0];
this._paras.weight = new double[0];
this._paras.gamma = 1.0 / ((double) this._inputCount);
goto Label_00C6;
Label_0057:
this._paras.C = 1.0;
this._paras.eps = 0.001;
this._paras.p = 0.1;
this._paras.shrinking = 1;
this._paras.probability = 0;
if ((((uint) theInputCount) + ((uint) theInputCount)) >= 0)
{
goto Label_000B;
}
Label_00C6:
if (0 == 0)
{
return;
}
goto Label_02B7;
Label_00D1:
this._paras.degree = 3.0;
this._paras.coef0 = 0.0;
this._paras.nu = 0.5;
if (0 != 0)
{
goto Label_0256;
}
this._paras.cache_size = 100.0;
if (0 == 0)
{
goto Label_0057;
}
goto Label_019C;
Label_0134:
this._paras.kernel_type = 3;
goto Label_00D1;
Label_0167:
this._paras.kernel_type = 0;
goto Label_00D1;
Label_019C:
switch (kernelType)
{
case Encog.ML.SVM.KernelType.Linear:
goto Label_0167;
case Encog.ML.SVM.KernelType.Poly:
this._paras.kernel_type = 1;
goto Label_00D1;
case Encog.ML.SVM.KernelType.RadialBasisFunction:
this._paras.kernel_type = 2;
goto Label_00D1;
case Encog.ML.SVM.KernelType.Sigmoid:
goto Label_0134;
default:
throw new NeuralNetworkError("Invalid kernel type");
}
Label_01CD:
throw new NeuralNetworkError("Invalid svm type");
if ((((uint) theInputCount) - ((uint) theInputCount)) < 0)
{
goto Label_0134;
}
if (8 != 0)
{
goto Label_019C;
}
if ((((uint) theInputCount) + ((uint) theInputCount)) < 0)
{
goto Label_01CD;
}
goto Label_0167;
if (0 == 0)
{
goto Label_00D1;
}
goto Label_0057;
Label_0256:
this._paras.svm_type = 2;
goto Label_019C;
Label_02B7:
this._inputCount = theInputCount;
this._paras = new svm_parameter();
if ((((uint) theInputCount) - ((uint) theInputCount)) > uint.MaxValue)
{
goto Label_00D1;
}
switch (svmType)
{
case Encog.ML.SVM.SVMType.SupportVectorClassification:
this._paras.svm_type = 0;
if (0 != 0)
{
goto Label_0017;
}
goto Label_019C;
case Encog.ML.SVM.SVMType.NewSupportVectorClassification:
this._paras.svm_type = 1;
if ((((uint) theInputCount) | uint.MaxValue) == 0)
{
goto Label_000B;
}
goto Label_019C;
case Encog.ML.SVM.SVMType.SupportVectorOneClass:
goto Label_0256;
case Encog.ML.SVM.SVMType.EpsilonSupportVectorRegression:
this._paras.svm_type = 3;
if ((((uint) theInputCount) + ((uint) theInputCount)) <= uint.MaxValue)
{
goto Label_019C;
}
goto Label_02B7;
case Encog.ML.SVM.SVMType.NewSupportVectorRegression:
this._paras.svm_type = 4;
if (((uint) theInputCount) > uint.MaxValue)
{
return;
}
goto Label_019C;
default:
goto Label_01CD;
}
}
public SortedField(int theIndexindex, Encog.App.Analyst.CSV.Sort.SortType t, bool theAscending)
{
this._xc0c4c459c6ccbd00 = theIndexindex;
this.Ascending = theAscending;
this._x0a082a37646d8463 = t;
}