public override void DoEpoch(float t, float round_t)
{
float[,] test2d;
float[] test;
this.FindBMU();
//Slice the pwinner row by row and do some great stuff
m_PWinner = ParallelArrays.Evaluate(m_PWinner);
Slice[] slices = new Slice[2];
for (int i = 0; i < m_Parent.DataSource.PatternCount; ++i)
{
slices[1] = new Slice(0, m_Parent.NeuronMap.GetLength(0));
slices[0] = new Slice(i, 1);
FloatParallelArray s = ParallelArrays.Section(m_PWinner, slices);
s = ParallelArrays.Evaluate(s);
FloatParallelArray bmuw = ParallelArrays.DropDimension(ParallelArrays.InnerProduct(s, m_GPUWeight), 0);
FloatParallelArray bmuc = ParallelArrays.InnerProduct(s, m_GPUCoord);
//Compute distances to bmu
DisposableFloatParallelArray bmucEvaluated = ParallelArrays.Evaluate(bmuc); //Workaround
bmuc = ParallelArrays.Stretch(bmucEvaluated, m_Parent.NeuronMap.GetLength(0), 1);
FloatParallelArray diff = ParallelArrays.Subtract(m_GPUCoord, bmuc);
FloatParallelArray dist = ParallelArrays.Multiply(diff, diff);
dist = ParallelArrays.Sum(dist, 1);
dist = ParallelArrays.Multiply(-1.0f, dist);
//Apply update formula
FloatParallelArray constE = new FloatParallelArray((float)(Math.E), m_Parent.NeuronMap.GetLength(0));
FloatParallelArray sigma = new FloatParallelArray((float)(Math.Pow(Neighborhood(t, round_t) * 0.85, 2)), m_Parent.NeuronMap.GetLength(0));
FloatParallelArray lrate = new FloatParallelArray((float)LearningRate(t, round_t), m_Parent.NeuronMap.GetLength(0), m_Parent.DataSource.PatternLength);
FloatParallelArray omeg = ParallelArrays.Divide(dist, sigma);
//FloatParallelArray momeg = ParallelArrays.Pow(constE, omeg);
FloatParallelArray momeg = ParallelArrays.Pow2(ParallelArrays.Log2(constE) * omeg);
DisposableFloatParallelArray domeg = ParallelArrays.Evaluate(momeg); //Workaround
omeg = ParallelArrays.AddDimension(domeg, 1);
omeg = ParallelArrays.Stretch(omeg, 1, m_Parent.DataSource.PatternLength);
FloatParallelArray sbmuw = ParallelArrays.AddDimension(bmuw, 0);
sbmuw = ParallelArrays.Stretch(sbmuw, m_Parent.NeuronMap.GetLength(0), 1);
m_GPUWeight = ((m_GPUWeight + ((sbmuw - m_GPUWeight) * omeg * lrate)));
}
m_GPUWeight = ParallelArrays.Evaluate(m_GPUWeight);
}
public FloatParallelArray Pop()
{
if (IsEmpty)
{
throw new UnexpectedOperation();
}
if (m_ContArray.Shape[0] - 1 == 0)
{
IsEmpty = true;
return(m_ContArray);
}
Slice slc = new Slice(0, m_ContArray.Shape[0] - 1);
FloatParallelArray popelem = ParallelArrays.Section(m_ContArray, slc);
m_ContArray = ParallelArrays.Replicate(m_ContArray, m_ContArray.Shape[0] - 1);
return(popelem);
}