/// <summary>
/// returns the fft spectrum of a cross-correlation function.
/// </summary>
/// <param name="v1"></param>
/// <param name="v2"></param>
/// <returns></returns>
public static double[] CrossCorr(double[] v1, double[] v2)
{
int n = v1.Length; // assume both vectors of same length
double[] r;
alglib.corrr1d(v1, n, v2, n, out r);
// alglib.complex[] f;
// alglib.fftr1d(newOp, out f);
// System.LoggedConsole.WriteLine("{0}", alglib.ap.format(f, 3));
// for (int i = 0; i < op.Length; i++) LoggedConsole.WriteLine("{0} {1:f2}", i, op[i]);
// rearrange corr output and NormaliseMatrixValues
int xcorrLength = 2 * n;
double[] xCorr = new double[xcorrLength];
// for (int i = 0; i < n - 1; i++) newOp[i] = r[i + n]; //rearrange corr output
// for (int i = n - 1; i < opLength-1; i++) newOp[i] = r[i - n + 1];
for (int i = 0; i < n - 1; i++)
{
xCorr[i] = r[i + n] / (i + 1); // rearrange and NormaliseMatrixValues
}
for (int i = n - 1; i < xcorrLength - 1; i++)
{
xCorr[i] = r[i - n + 1] / (xcorrLength - i - 1);
}
// add extra value at end so have length = power of 2 for FFT
// xCorr[xCorr.Length - 1] = xCorr[xCorr.Length - 2];
// LoggedConsole.WriteLine("xCorr length = " + xCorr.Length);
// for (int i = 0; i < xCorr.Length; i++) LoggedConsole.WriteLine("{0} {1:f2}", i, xCorr[i]);
// DataTools.writeBarGraph(xCorr);
xCorr = DataTools.DiffFromMean(xCorr);
FFT.WindowFunc wf = FFT.Hamming;
var fft = new FFT(xCorr.Length, wf);
var spectrum = fft.Invoke(xCorr);
return(spectrum);
}// CrossCorrelation()
public static Image <Rgb24> DrawWaveAndFft(double[] signal, int sr, TimeSpan startTime, double[] fftSpectrum, int maxHz, double[] scores)
{
int imageHeight = 300;
double max = -2.0;
foreach (double value in signal)
{
double absValue = Math.Abs(value);
if (absValue > max)
{
max = absValue;
}
}
double scalingFactor = 0.5 / max;
// now process neighbourhood of each max
int nyquist = sr / 2;
int windowWidth = signal.Length;
int binCount = windowWidth / 2;
double hzPerBin = nyquist / (double)binCount;
if (fftSpectrum == null)
{
FFT.WindowFunc wf = FFT.Hamming;
var fft = new FFT(windowWidth, wf);
fftSpectrum = fft.Invoke(signal);
}
int requiredBinCount = (int)(maxHz / hzPerBin);
var subBandSpectrum = DataTools.Subarray(fftSpectrum, 1, requiredBinCount); // ignore DC in bin zero.
var endTime = startTime + TimeSpan.FromSeconds(windowWidth / (double)sr);
string title1 = $"Bandpass filtered: tStart={startTime.ToString()}, tEnd={endTime.ToString()}";
var image4A = DrawWaveform(title1, signal, signal.Length, imageHeight, scalingFactor);
string title2 = $"FFT 1->{maxHz}Hz., hz/bin={hzPerBin:f1}, score={scores[0]:f3}={scores[1]:f3}+{scores[2]:f3}";
var image4B = DrawGraph(title2, subBandSpectrum, signal.Length, imageHeight, 1);
var imageList = new List <Image <Rgb24> > {
image4A, image4B
};
Pen pen1 = new Pen(Color.Wheat, 1f);
var stringFont = Drawing.Arial9;
var bmp2 = new Image <Rgb24>(signal.Length, 25);
bmp2.Mutate(g2 =>
{
g2.DrawLine(pen1, 0, 0, signal.Length, 0);
g2.DrawLine(pen1, 0, bmp2.Height - 1, signal.Length, bmp2.Height - 1);
int barWidth = signal.Length / subBandSpectrum.Length;
for (int i = 1; i < subBandSpectrum.Length - 1; i++)
{
if (subBandSpectrum[i] > subBandSpectrum[i - 1] && subBandSpectrum[i] > subBandSpectrum[i + 1])
{
string label = $"{i + 1},";
g2.DrawText(label, stringFont, Color.Wheat, new PointF((i * barWidth) - 3, 3));
}
}
});
imageList.Add(bmp2);
var image = ImageTools.CombineImagesVertically(imageList);
return(image);
}