private void button4_Click( object sender, EventArgs e )
{
// init the signal
signal = new FxMaths.Vector.FxVectorF( 1024, new Fx1DGeneratorF( SignalGenerator ), 0.1f );
// create a plot base on signal
PloterElement plot = new PloterElement( signal );
plot.Position.X = 0;
plot.Position.Y = 50;
plot.Origin = new FxVector2f(10, 100);
plot.FitPlots();
// add the signal to canva
Signal_Canva.AddElements( plot );
// add text for the signal plot
TextElement text= new TextElement( "Signal Plot:" );
text.Position.X = 10;
text.Position.Y = 10;
// add the text to canva
Signal_Canva.AddElements( text );
}
private void button9_Click( object sender, EventArgs e )
{
// check if we have select file
if ( String.IsNullOrEmpty( audioFileName ) ) {
button8_Click( sender, e );
}
if ( String.IsNullOrEmpty( audioFileName ) ) {
return;
}
// create wave out device
CreateWaveOut();
// create steram file
ISampleProvider sampleProvider = null;
try {
// read the file
fileWaveStream = new Mp3FileReader( audioFileName );
// cretae the wave channel
var waveChannel = new SampleChannel( this.fileWaveStream );
waveChannel.Volume = 0.5f;
// create the sampler
sampleProvider = new MeteringSampleProvider( waveChannel );
} catch ( Exception createException ) {
MessageBox.Show( String.Format( "{0}", createException.Message ), "Error Loading File" );
return;
}
try {
// in the wave out ( give and the call back for the editing
waveOut.Init( new SampleToWaveProvider( sampleProvider), callback);
} catch ( Exception initException ) {
MessageBox.Show( String.Format( "{0}", initException.Message ), "Error Initializing Output" );
return;
}
if ( plot_signal_spectrum == null )
{
#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));
}
// start play
waveOut.Play();
}
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();
}
}
}
