/// <summary>
/// Result = A (*) B
/// By using FFT for calculations
/// </summary>
/// <param name="A"></param>
/// <param name="B"></param>
/// <param name="Result"></param>
public static void Convolution_FFT_F( FxVectorF A, FxVectorF B, out FxVectorF Result )
{
FxVectorF A_dftReal,A_dftImag,B_dftReal,B_dftImag;
// copy local the inputs
FxVectorF A_local = A.GetCopy() as FxVectorF;
FxVectorF B_local = B.GetCopy() as FxVectorF;
// get the max size from A,B
int maxSize = ( A_local.Size > B_local.Size ) ? A_local.Size : B_local.Size;
// check that is power of 2
if ( Math.Pow( 2, Math.Log( maxSize, 2 ) ) != maxSize ) {
// calc the size of log2 extence
int sizeLog2 = (int)Math.Floor( Math.Log( maxSize, 2 ) ) + 1;
// calc the new maxSize
maxSize = (int)Math.Pow( 2, sizeLog2 );
// increase the size of A,B
A_local.Padding( maxSize - A_local.Size, true, 0 );
B_local.Padding( maxSize - B_local.Size, true, 0 );
}
// allocate temp file
FxVectorF tmp = new FxVectorF( maxSize );
// check for padding
if ( A_local.Size == maxSize && B_local.Size != maxSize ) {
// increase the size of B
B_local.Padding( maxSize - B_local.Size, true, 0 );
} else if ( B_local.Size == maxSize && A_local.Size != maxSize ) {
A_local.Padding( maxSize - A_local.Size, true, 0 );
}
// calc the DFT of the signal
SignalTools.FFT_F( A_local, tmp, true, out A_dftReal, out A_dftImag );
// calc the DFT of the signal
SignalTools.FFT_F( B_local, tmp, true, out B_dftReal, out B_dftImag );
// allocate result vector
Result = new FxVectorF( maxSize );
float real,imag;
// do the multiplication
for ( int i=0; i < maxSize; i++ ) {
// complex multiplication
real = A_dftReal[i] * B_dftReal[i] - A_dftImag[i] * B_dftImag[i];
imag = A_dftReal[i] * B_dftImag[i] + A_dftImag[i] * B_dftReal[i];
// set the new values
A_dftReal[i] = real;
A_dftImag[i] = imag;
}
// calc the DFT of the signal
SignalTools.FFT_F( A_dftReal, A_dftImag, false, out Result, out B_dftImag );
// cat the padding
int maxInputSize = ( A.Size > B.Size ) ? A.Size : B.Size;
Result = Result.GetSubVector( maxSize - maxInputSize, Result.Size) as FxVectorF;
}
/// <summary>
/// Result = A (*) B
/// By using FFT for calculations
/// The second vector is allready in fft form
/// The two vectors must have the same size and be power of 2
/// </summary>
/// <param name="A"></param>
/// <param name="B_dftReal"></param>
/// <param name="B_dftImag"></param>
/// <param name="Result"></param>
public static void Convolution_FFT_F( FxVectorF A, FxVectorF B_dftReal, FxVectorF B_dftImag, out FxVectorF Result )
{
FxVectorF A_dftReal,A_dftImag;
// copy local the inputs
FxVectorF A_local = A.GetCopy() as FxVectorF;
// get the max size from A,B
int maxSize = ( A_local.Size > B_dftReal.Size ) ? A_local.Size : B_dftReal.Size;
// calc the DFT of the signal
SignalTools.FFT_F( A_local, null, true, out A_dftReal, out A_dftImag );
// allocate result vector
Result = new FxVectorF( maxSize );
float real,imag;
// do the multiplication
for ( int i=0; i < maxSize; i++ ) {
// complex multiplication
real = A_dftReal[i] * B_dftReal[i] - A_dftImag[i] * B_dftImag[i];
imag = A_dftReal[i] * B_dftImag[i] + A_dftImag[i] * B_dftReal[i];
// set the new values
A_dftReal[i] = real;
A_dftImag[i] = imag;
}
// calc the DFT of the signal
SignalTools.FFT_F( A_dftReal, A_dftImag, false, out Result, out B_dftImag );
// cat the padding
int maxInputSize = ( A.Size > B_dftReal.Size ) ? A.Size : B_dftReal.Size;
Result = Result.GetSubVector( maxSize - maxInputSize, Result.Size ) as FxVectorF;
}
private void button13_Click( object sender, EventArgs e )
{
// process the white noise data with the dsp
if ( wn != null ) {
tmpWn = new FxVectorF( wn.Size );
// create the signal spectrum graphs
if ( plot_signal_spectrum == null ) {
power = new FxVectorF( 256 );
#region Plot Creation
signal_spectrum = new FxVectorF( 256 );
// insert the plot of the time filter
filterPlot = new PloterElement( signal_spectrum );
filterPlot.Position.X = 0;
filterPlot.Position.Y = 410;
filterPlot.Origin = new FxVector2f(10, 100);
filterPlot.FitPlots();
canvas_audio.AddElements( filterPlot );
// create the plot for the spectrum
plot_signal_spectrum = new PloterElement( signal_spectrum );
plot_signal_spectrum.Position.X = 0;
plot_signal_spectrum.Position.Y = 10;
plot_signal_spectrum.Origin = new FxVector2f(10, 100);
plot_signal_spectrum.FitPlots();
plot_signal_spectrum.AddPlot( signal_spectrum, PlotType.Lines, Color.Aqua );
// add the signal to canva
canvas_audio.AddElements( plot_signal_spectrum );
// create the plot for the spectrum
plot_signal_spectrum_original = new PloterElement( signal_spectrum );
plot_signal_spectrum_original.Position.X = 600;
plot_signal_spectrum_original.Position.Y = 10;
plot_signal_spectrum_original.Origin = new FxVector2f(10, 100);
plot_signal_spectrum_original.FitPlots();
// add the signal to canva
canvas_audio.AddElements( plot_signal_spectrum_original );
// create the plot for the spectrum
plot_filter_spectrum = new PloterElement( signal_spectrum );
plot_filter_spectrum.Position.X = 600;
plot_filter_spectrum.Position.Y = 410;
plot_filter_spectrum.Origin = new FxVector2f(10, 100);
plot_filter_spectrum.FitPlots();
// add the signal to canva
canvas_audio.AddElements( plot_filter_spectrum );
#endregion
// add filter
UpdateFilter( BiQuadFilter.BandPassFilterConstantPeakGain( 44100, 20000, 0.5f ) );
}
if ( this.fil != null ) {
// use the filter directly
this.fil.Transform( wn, tmpWn );
}
FxVectorF tmpImag,tmpReal;
// calc spectrum
int mod = (int)Math.Ceiling( tmpWn.Size / ( (double)power.Size * 2 ) );
// ===============================================================================================
if ( ShowOutputAudioSpectrum ) {
power.SetValue( 0.0f );
FxVectorF local=tmpWn;
if ( Math.Pow( 2, Math.Floor( Math.Log( local.Size, 2 ) ) ) != local.Size ) {
int newSize;
// calc the size of log2
int sizeLog2 = (int)Math.Floor( Math.Log( local.Size, 2 ) ) - 1;
// calc the new size
newSize = (int)Math.Pow( 2, sizeLog2 );
if ( newSize < 512 )
newSize = 512;
local = tmpWn.GetSubVector( 0, newSize ) as FxVectorF;
}
mod = (int)Math.Ceiling( local.Size / ( (double)power.Size * 2 ) );
// calc the fft
SignalTools.FFT_F( local, null, true, out tmpReal, out tmpImag );
// pass all the data in form of blocks
for ( int i = 0; i < mod; i++ ) {
for ( int j = 0; j < power.Size; j++ ) {
power[j] += (float)( Math.Sqrt( tmpReal[j * mod + i] * tmpReal[j * mod + i] + tmpImag[j * mod + i] * tmpImag[j * mod + i] ) );
}
}
// normalize the result
power.Divide( power.Max() );
// refresh the plot
plot_signal_spectrum.RefreshPlot( power, 0 );
plot_signal_spectrum.FitPlots();
// redraw canvas if we are not going to show output spectrum
if ( !ShowInputAudioSpectrum )
canvas_audio.ReDraw();
}
// ===============================================================================================
if ( ShowInputAudioSpectrum ) {
// calc spectrum
// reset the power
power.SetValue( 0.0f );
FxVectorF local=wn;
if ( Math.Pow( 2, Math.Floor( Math.Log( local.Size, 2 ) ) ) != local.Size ) {
int newSize;
// calc the size of log2
int sizeLog2 = (int)Math.Floor( Math.Log( local.Size, 2 ) ) - 1;
// calc the new size
newSize = (int)Math.Pow( 2, sizeLog2 );
if ( newSize < 512 )
newSize = 512;
local = wn.GetSubVector( 0, newSize ) as FxVectorF;
}
mod = (int)Math.Ceiling( local.Size / ( (double)power.Size * 2 ) );
// calc the fft
SignalTools.FFT_Safe_F( local, null, true, out tmpReal, out tmpImag );
// pass all the data in form of blocks
for ( int i = 0; i < mod; i++ ) {
for ( int j = 0; j < power.Size; j++ ) {
power[j] += (float)( Math.Sqrt( tmpReal[j * mod + i] * tmpReal[j * mod + i] + tmpImag[j * mod + i] * tmpImag[j * mod + i] ) );
}
}
// normalize the result
power.Divide( power.Max() );
// refresh the plot
plot_signal_spectrum_original.RefreshPlot( power, 0 );
plot_signal_spectrum_original.FitPlots();
// redraw canvas
canvas_audio.ReDraw();
}
}
}