public void mLineAutoSpectr(double[] temparr, int imgW, int imgH)
{
Random r = new Random();
int lineInd = r.Next(0, imgH);
double[] line = temparr.Skip(lineInd * imgW).Take(imgW).ToArray <double>();
double[] dLineDt = new double[imgW];
for (int i = 0; i < imgW - 2; i++)
{
dLineDt[i] = line[i] - line[i + 1];
}
ComplexNum[] lineAutocor = new ComplexNum[imgW];
for (int i = 0; i < imgW; i++)
{
lineAutocor[i] = new ComplexNum(Statistics.Crosscorrelation(dLineDt, dLineDt, i));
}
FourierTransfom ft = new FourierTransfom();
double Fgr = 1.0 / 1;
double Fdelta = Fgr / lineAutocor.Length;
ComplexNum[] res = ft.mTransform(lineAutocor);
for (int i = 0; i < mCount; i++)
{
mArguments[i] = i * Fdelta;
}
mFunc = t => res[t].abs;
}
public virtual void pSetObrFurie(double[] tempArr)
{
int N = tempArr.Length;
mArguments = new double[N];
mValues = new double[N];
for (int i = 0; i < mCount; i++)
{
mArguments[i] = i;
}
mLeftBorder = 0;
mRightBorder = N - 1;
FourierTransfom fs = new FourierTransfom();
ComplexNum[] lFurieResult = fs.mObrTransform(ComplexNum.CompArrOfDoble(tempArr));
Func <int, double> temp = (k =>
{
return(lFurieResult[k].RePlusIm);
});
mFunc = temp;
}
public void mLineSpectr(double[] temparr, int imgW, int imgH)
{
Random r = new Random();
int lineInd = r.Next(0, imgH);
double[] line = temparr.Skip(lineInd * imgW).Take(imgW).ToArray <double>();
FourierTransfom ft = new FourierTransfom();
double Fgr = 1.0 / (1 * 2);
double Fdelta = 2 * Fgr / line.Length;
mCount = (int)(Fgr / Fdelta);
mDelta = Fdelta;
mRightBorder = Fgr;
mLeftBorder = 0;
mValues = new double[mCount];
ComplexNum[] res = ft.mTransform(ComplexNum.CompArrOfDoble(line), Fgr, Fdelta);
mArguments = new double[mCount];
for (int i = 0; i < mCount; i++)
{
mArguments[i] = i * Fdelta;
}
mFunc = t => res[t].abs;
}
