public static INumberTable Filter(INumberTable inTable, double lowFreq, double highFreq, int dimension, INumberTable baseTable)
{
int lowIdx = (int)(lowFreq * dimension);
int hiIdx = (int)(highFreq * dimension);
List <int> columns = new List <int>();
for (int i = 0; i < dimension; i++)
{
if ((i >= lowIdx) && (i <= hiIdx))
{
columns.Add(i);
}
}
INumberTable B = baseTable.SelectColumns(columns);
INumberTable Bt = B.Transpose2();
int b = B.Columns;
int r = inTable.Rows;
int m = inTable.Columns;
INumberTable outTable = null;
//Depending on the size of m relative to r and b, we can
//optimize the calculation by arrange the matrix multiplication.
if (2 * r * b < m * (r + b))
{
// The complexity in this arrangement is 2*m*r*b.
outTable = FourierTransform.MatrixProduct(FourierTransform.MatrixProduct(inTable, B), Bt);
}
else
{
// The complexity in this arrangement is m*m*(r+b).
outTable = FourierTransform.MatrixProduct(inTable, FourierTransform.MatrixProduct(B, Bt));
}
IList <IColumnSpec> oSpecList = outTable.ColumnSpecList;
IList <IColumnSpec> iSpecList = inTable.ColumnSpecList;
for (int col = 0; col < outTable.Columns; col++)
{
oSpecList[col].CopyFrom(iSpecList[col]);
}
return(outTable);
}
public INumberTable Transform(INumberTable inTable)
{
return(FourierTransform.MatrixProduct(inTable, haar));
}
