protected virtual void Initialize(int p, int N, double alpha)
{
_fibonacciSequence = FibonacciSequence.GetSequence(p, N);
this.alpha = alpha;
var cacheMatrices = Cache.TryGetFHTMatrix(new Tuple <int, int>(p, N));
if (cacheMatrices != null)
{
_fhtMatrix = cacheMatrices.Item1;
_fhtMatrixInverse = cacheMatrices.Item2;
}
else
{
_fhtMatrix = FibonacciHaarTransformationMatrix(p, N);
_fhtMatrixInverse = new SparseMatrix(_fhtMatrix.RowCount);
_fhtMatrix.Transpose(_fhtMatrixInverse);
_fhtMatrix.Multiply(0.5, _fhtMatrix);
Cache.AddFHTMatrix(new Tuple <int, int>(p, N), new Tuple <Matrix, Matrix>(_fhtMatrix, _fhtMatrixInverse));
}
}
/// <summary>
/// Populates the FHT matrix according to reccurent formulae and returns it as MathNet SparseMatrix
/// </summary>
/// <param name="p">p-sequence to use</param>
/// <param name="N">Matrix dimension</param>
/// <returns></returns>
protected static Matrix FibonacciHaarTransformationMatrix(int p, int N)
{
double[,] pnMatrix = { { Math.Sqrt(2) } };
double[,] pp1Matrix = { { 1, 1 }, { 1, -1 } };
var fibonacci = FibonacciSequence.GetSequence(p, N);
var n = fibonacci.IndexOfElement(N);
double[,] pprev, prev, current = new double[0, 0];
Queue <double[, ]> intermediate = new Queue <double[, ]>();
for (int i = 0; i <= p; i++)
{
intermediate.Enqueue(pnMatrix);
}
intermediate.Enqueue(pp1Matrix);
for (int i = p + 2; i <= n; i++)
{
int size = fibonacci.GetElementByIndex(i);
int pSize = fibonacci.GetElementByIndex(i - 1);
int ppSize = fibonacci.GetElementByIndex(i - p - 1);
int pUpperSize = fibonacci.GetElementByIndex(i - 2);
int pLowerSize = fibonacci.GetElementByIndex(i - p - 2);
int ppUpperSize = pLowerSize;
int ppLowerSize = fibonacci.GetElementByIndex(i - 2 * p - 2);
prev = intermediate.Last();
pprev = intermediate.ElementAt(intermediate.Count - p - 1);
current = new double[size, size];
for (int j = 0; j < pUpperSize; j++)
{
for (int k = 0; k < pSize; k++)
{
current[j, k] = prev[j, k];
}
}
for (int j = pUpperSize; j < pSize; j++)
{
for (int k = 0; k < pSize; k++)
{
current[j + pLowerSize, k] = prev[j, k];
}
}
for (int j = 0; j < ppUpperSize; j++)
{
for (int k = 0; k < ppSize; k++)
{
current[j + pUpperSize, k + pSize] = pprev[j, k];
}
}
for (int j = ppUpperSize; j < ppSize; j++)
{
for (int k = 0; k < ppSize; k++)
{
current[j + pSize, k + pSize] = pprev[j, k];
}
}
intermediate.Enqueue(current);
intermediate.Dequeue();
}
var fhtMatrix = SparseMatrix.OfArray(current);
fhtMatrix.Multiply(0.5, fhtMatrix);
return(fhtMatrix);
}