computes the two-dimensional discrete Fourier transform or inverse Fourier transform of a bivariate sequence of complex data values.
int fftw_fft_2d_complex( int iSizeX, int iSizeY, d_complex * vSig, FFT_SIGN iSign = FFT_FORWARD )
- [input] the number of rows of the bivariate data sequence.
- [input] the number of columns of the bivariate data sequence.
- [modify] the complex data sequences for input and the result data after fourier transformation for output
- [input] the transformation to carry out
- = FFT_FORWARD: FFT (by default)
- = FFT_BACKWARD: IFFT.
- Returns 0 for success or error codes for failure.
//Assume the current Worksheet has 6 columns, the first two columns contain 7 data each.
//The first column is the real part of the original complex data and the second column
//is the imaginary part. This piece of code reads in a sequence of these 7 complex data
//values and put the result of the discrete Fourier transform of the original data
//into the third and fourth columns. The third column is the real part and the fourth
//column is the imaginary part. Then inverse Fourier transform is performed, and the
//result is output into the fifth and sixth column.
int n=7, m=8, k=n*m, success;
//Attach two Datasets to these 2 columns
Worksheet wks = Project.ActiveLayer();
Dataset xx(wks, 0);
Dataset yy(wks, 1);
Dataset aa(wks, 2);
Dataset bb(wks, 3);
Dataset cc(wks, 4);
Dataset dd(wks, 5);
vector x = xx, y = yy;
//make a complex vector use x and y
success = fftw_fft_2d_complex(n, m, vc);
//put the result back to the current worksheet, the third and the fourth column.
aa = x;
bb = y;
success = fftw_fft_2d_complex(n, m, vc, FFT_BACKWARD);
//put the result back to the current worksheet, the fifth and the sixth column.
cc = x;
dd = y;
header to Include