public override void FindBMU()
{
//Normalize the weight vector
FloatParallelArray transpose = ParallelArrays.Transpose(m_GPUWeight, 1, 0);
FloatParallelArray weightsq = ParallelArrays.InnerProduct(m_GPUWeight, ParallelArrays.Transpose(m_GPUWeight, 1, 0));
FloatParallelArray weightsum = ParallelArrays.Sum(weightsq, 0);
FloatParallelArray weightlength = ParallelArrays.Sqrt(weightsum);
weightlength = ParallelArrays.Stretch(ParallelArrays.AddDimension(weightlength, 1), 1, m_Parent.DataSource.PatternLength);
FloatParallelArray weightnorm = ParallelArrays.Divide(m_GPUWeight, weightlength);
weightnorm = ParallelArrays.Transpose(weightnorm, 1, 0);
//Normalize the input vector
FloatParallelArray inputsq = ParallelArrays.InnerProduct(m_GPUInput, ParallelArrays.Transpose(m_GPUInput, 1, 0));
FloatParallelArray inputsum = ParallelArrays.Sum(inputsq, 0);
FloatParallelArray inputlength = ParallelArrays.Sqrt(inputsum);
inputlength = ParallelArrays.Stretch(ParallelArrays.AddDimension(inputlength, 1), 1, m_Parent.DataSource.PatternLength);
FloatParallelArray inputnorm = ParallelArrays.Divide(m_GPUInput, inputlength);
FloatParallelArray pacc = ParallelArrays.InnerProduct(inputnorm, weightnorm);
//Replication bug here...
FloatParallelArray bmxval = ParallelArrays.MaxVal(pacc, 1);
//MSR Vivian Swelson workaround
DisposableFloatParallelArray bmxvalEvaluated = ParallelArrays.Evaluate(bmxval);
bmxval = ParallelArrays.AddDimension(bmxvalEvaluated, 1);
bmxval = ParallelArrays.Stretch(bmxval, 1, m_Parent.NeuronMap.GetLength(0));
//Winner matrix (0 = winner)
FloatParallelArray pwinner = ParallelArrays.Subtract(pacc, bmxval);
//Convert to 1 = winner, 0 otherwise
FloatParallelArray zero = new FloatParallelArray(0.0f, pwinner.Shape);
FloatParallelArray one = new FloatParallelArray(1.0f, pwinner.Shape);
BoolParallelArray bmask = ParallelArrays.CompareEqual(pwinner, zero);
m_PWinner = ParallelArrays.Cond(bmask, one, zero);
}
