public void GetSpectrumData(float[] samples, int channel)
{
if (!Mathf.IsPowerOfTwo(samples.Length) || samples.Length > MaxChannelSamplesFFT)
{
throw new ArgumentException();
}
int numSamples = 2 * samples.Length;
if (null == FFTInOut || numSamples != FFTInOut.Length)
{
FFTInOut = new double[numSamples];
}
GetOutputDataDouble(FFTInOut, channel);
FFT.RealFFT(FFTInOut, true);
samples[0] = samples[samples.Length - 1] = 0.0f;
for (int i = 2; i < FFTInOut.Length; i += 2)
{
float re = (float)FFTInOut[i];
float im = (float)FFTInOut[i + 1];
samples[i / 2] = Mathf.Sqrt(re * re + im * im) / samples.Length;
}
}
public void ComputeComirvaMatrixUsingLomontRealFFT(ref Comirva.Audio.Util.Maths.Matrix m, int column, float[] audiodata, int pos)
{
// apply the window method (e.g HammingWindow, HannWindow etc)
win.Apply(ref data, audiodata, pos);
double[] fft = new double[data.Length / 2];
Array.Copy(data, fft, data.Length / 2);
lomonFFT.RealFFT(fft, true);
// fft input will now contain the FFT values
// r0, r(n/2), r1, i1, r2, i2 ...
m.MatrixData[0][column] = Math.Sqrt(fft[0] * fft[0] * winsize);
m.MatrixData[winsize / 2 - 1][column] = Math.Sqrt(fft[1] * fft[1] * winsize);
for (int row = 1; row < winsize / 2; row++)
{
// amplitude (or magnitude) is the square root of the power spectrum
// the magnitude spectrum is abs(fft), i.e. Math.Sqrt(re*re + img*img)
// use 20*log10(Y) to get dB from amplitude
// the power spectrum is the magnitude spectrum squared
// use 10*log10(Y) to get dB from power spectrum
m.MatrixData[row][column] = Math.Sqrt((fft[2 * row] * fft[2 * row] +
fft[2 * row + 1] * fft[2 * row + 1]) * winsize);
}
}