/// <summary>
/// Frequency domain convolution.
/// </summary>
/// <param name="SignalBuffer">the dry signal.</param>
/// <param name="Filter">the pressure domain impulse response.</param>
/// <returns>the convolved signal.</returns>
public static float[] FFT_Convolution(double[] SignalBuffer, double[] Filter, int threadid)
{
if (SignalBuffer == null)
{
return(null);
}
int minlength = SignalBuffer.Length > Filter.Length ? SignalBuffer.Length : Filter.Length;
int W = (int)Math.Pow(2, Math.Ceiling(Math.Log(minlength, 2)));
if (SignalBuffer.Length < W)
{
Array.Resize(ref SignalBuffer, W);
}
if (Filter.Length < W)
{
Array.Resize(ref Filter, W);
}
MathNet.Numerics.Complex[] freq1 = FFT_General(SignalBuffer, threadid);
MathNet.Numerics.Complex[] freq2 = FFT_General(Filter, threadid);
MathNet.Numerics.Complex[] freq3 = new MathNet.Numerics.Complex[W];
for (int i = 0; i < freq1.Length; i++)
{
freq3[i] = freq1[i] * freq2[i];
}
double[] conv = IFFT_Real_General(freq3, threadid);
float[] output = new float[conv.Length];
double mod = 1d / Math.Sqrt(conv.Length);
for (int i = 0; i < conv.Length; i++)
{
output[i] = (float)(conv[i] * mod); // * mod);
}
double maxfilt = Filter[0];
double maxsig = SignalBuffer[0];
double max = conv[0];
for (int i = 1; i < Filter.Length; i++)
{
Math.Max(maxfilt, Filter[i]);
}
for (int i = 1; i < SignalBuffer.Length; i++)
{
Math.Max(maxsig, SignalBuffer[i]);
}
for (int i = 1; i < conv.Length; i++)
{
Math.Max(max, conv[i]);
}
max++;
maxsig++;
maxfilt++;
return(output);
}
public static MathNet.Numerics.Complex[] Minimum_Phase_TF_Octaves(double[] Octave_filter, int sample_frequency, int length_starttofinish, int threadid)
{
double[] M_spec = Magnitude_Filter(Octave_filter, sample_frequency, length_starttofinish, threadid);
MathNet.Numerics.Complex[] logspec = new MathNet.Numerics.Complex[M_spec.Length];
for (int i = 0; i < M_spec.Length; i++)
{
logspec[i] = Math.Log(M_spec[i]);
}
double[] real_cepstrum = IFFT_Real_General(Mirror_Spectrum(logspec), threadid);
Scale(ref real_cepstrum);
double[] ym = new double[length_starttofinish];
ym[0] = real_cepstrum[0];
for (int i = 1; i < length_starttofinish / 2; i++)
{
ym[i] = 2 * real_cepstrum[i];
}
ym[length_starttofinish / 2] = real_cepstrum[length_starttofinish / 2];
MathNet.Numerics.Complex[] ymspec = FFT_General(ym, threadid);
for (int i = 0; i < ymspec.Length; i++)
{
ymspec[i] = (ymspec[i]).Exponential();
}
return(ymspec);
}
public static MathNet.Numerics.Complex[] Minimum_Phase_TF(double[] M_spec, int sample_frequency, int threadid)
{
MathNet.Numerics.Complex[] logspec = new MathNet.Numerics.Complex[M_spec.Length];
for (int i = 0; i < M_spec.Length; i++)
{
logspec[i] = Math.Log(M_spec[i]);
}
double[] real_cepstrum = IFFT_Real_General(Mirror_Spectrum(logspec), threadid);
Scale(ref real_cepstrum);
double[] ym = new double[real_cepstrum.Length];
ym[0] = real_cepstrum[0];
for (int i = 1; i < M_spec.Length; i++)
{
ym[i] = 2 * real_cepstrum[i];
}
ym[M_spec.Length] = real_cepstrum[M_spec.Length];
MathNet.Numerics.Complex[] ymspec = FFT_General(ym, threadid);
for (int i = 0; i < ymspec.Length; i++)
{
ymspec[i] = (ymspec[i]).Exponential();
}
return(ymspec);
}
public override MathNet.Numerics.Complex Reflection_Narrow(double frequency)
{
MathNet.Numerics.Complex alpha = 0;
for (int a = 0; a < Transfer_FunctionR.Length; a++)
{
alpha += new MathNet.Numerics.Complex(Transfer_FunctionR[a].Interpolate(frequency), Transfer_FunctionI[a].Interpolate(frequency));
}
alpha /= Transfer_FunctionR.Length;
return(alpha);
}
public override MathNet.Numerics.Complex[] Reflection_Spectrum(int sample_frequency, int length, Hare.Geometry.Vector Normal, Hare.Geometry.Vector Dir, int threadid)
{
MathNet.Numerics.Complex[] Ref_trns = new MathNet.Numerics.Complex[length];
for (int j = 0; j < length; j++)
{
Ref_trns[j] = new MathNet.Numerics.Complex(Transfer_Function.Interpolate(j * (sample_frequency / 2) / length), 0);
}
return(Ref_trns);
}
public static double[] Minimum_Phase_Signal(double[] Octave_pressure, int sample_frequency, int length_starttofinish, int threadid)
{
double[] M_spec = Magnitude_Spectrum(Octave_pressure, sample_frequency, length_starttofinish, threadid);
double sum_start = 0;
for (int i = 0; i < M_spec.Length; i++)
{
sum_start += M_spec[i] * M_spec[i];
}
MathNet.Numerics.Complex[] logspec = new MathNet.Numerics.Complex[M_spec.Length];
for (int i = 0; i < M_spec.Length; i++)
{
logspec[i] = Math.Log(M_spec[i]);
}
double[] real_cepstrum = IFFT_Real_General(Mirror_Spectrum(logspec), threadid);
Scale(ref real_cepstrum);
double[] ym = new double[length_starttofinish];
ym[0] = real_cepstrum[0];
for (int i = 1; i < length_starttofinish / 2; i++)
{
ym[i] = 2 * real_cepstrum[i];
}
ym[length_starttofinish / 2] = real_cepstrum[length_starttofinish / 2];
MathNet.Numerics.Complex[] ymspec = FFT_General(ym, threadid);
for (int i = 0; i < ymspec.Length; i++)
{
ymspec[i] = (ymspec[i]).Exponential();
}
double[] Signal = IFFT_Real_General(ymspec, threadid); //This is real valued hopefully... (if not there is a problem...)
for (int i = 0; i < Signal.Length; i++)
{
Signal[i] /= Math.Sqrt(Signal.Length);
}
double sum_end1 = 0;
for (int i = 0; i < ymspec.Length; i++)
{
sum_end1 += Signal[i] * Signal[i];
}
return(Signal);
}
public override MathNet.Numerics.Complex[] Reflection_Spectrum(int sample_frequency, int length, Hare.Geometry.Vector Normal, Hare.Geometry.Vector Dir, int threadid)
{
int a = (int)(Math.Abs(Hare.Geometry.Hare_math.Dot(Dir, Normal)) * 180 / Math.PI / 18);
MathNet.Numerics.Complex[] Ref_trns = new MathNet.Numerics.Complex[length];
for (int j = 0; j < length; j++)
{
double freq = j * (sample_frequency / 2) / length;
Ref_trns[j] = new MathNet.Numerics.Complex(Transfer_FunctionR[a].Interpolate(freq), Transfer_FunctionI[a].Interpolate(freq));
}
return(Ref_trns);
}
public MathNet.Numerics.Complex[][] Interpolate(double[] freq)
{
MathNet.Numerics.Complex[][] Zr = new MathNet.Numerics.Complex[freq.Length][];
for (int f = 0; f < freq.Length; f++)
{
Zr[f] = new MathNet.Numerics.Complex[Zr_Curves_R.Length];
for (int a = 0; a < Zr_Curves_R.Length; a++)
{
Zr[f][a] = new MathNet.Numerics.Complex(Zr_Curves_R[a].Interpolate(freq[f]), Zr_Curves_I[a].Interpolate(freq[f]));
}
}
return(Zr);
}
public static void IFFT(Complex[] xdata, int m)
{
var temp = new MathNet.Numerics.Complex[(int)Math.Pow(2, m)];
for (int i = 0; i < temp.Length; i++)
{
temp[i].Real = xdata[i].Real;
temp[i].Imag = xdata[i].Imag;
}
cft.TransformBackward(temp);
for (int i = 0; i < temp.Length; i++)
{
xdata[i].Real = temp[i].Real;
xdata[i].Imag = temp[i].Imag;
}
}
