nag_sum_fft_real_3d (c06pyc) Example Program Results Below we define X(i,j,k)=x[k*n1*n2+j*n1+i] where i and j are the row and column indices of the matrices printed. Y is defined similarly (but having n1/2+1 rows only due to conjugate symmetry). Original data values X(i,j,k) for k = 0 1.541 0.346 1.754 0.584 1.284 0.855 0.010 1.960 0.089 X(i,j,k) for k = 1 0.161 1.907 0.042 1.004 1.137 0.725 1.844 0.240 1.660 X(i,j,k) for k = 2 1.989 0.001 1.991 1.408 0.467 1.647 0.452 1.424 0.708 X(i,j,k) for k = 3 0.037 1.915 0.151 0.252 1.834 0.096 1.154 0.987 0.872 Components of discrete Fourier transform Y(i,j,k) for k = 0 ( 5.755, 0.000) (-0.268,-0.420) (-0.268, 0.420) ( 0.081, 0.015) ( 0.038, 0.198) ( 0.067,-0.122) Y(i,j,k) for k = 1 (-0.277,-0.237) ( 0.109,-0.756) (-0.688, 0.210) ( 0.060, 0.156) (-0.275, 0.295) ( 0.280, 0.012) Y(i,j,k) for k = 2 ( 0.415, 0.000) ( 0.175, 0.871) ( 0.175,-0.871) ( 0.645,-0.478) ( 1.585, 0.616) (-0.113,-1.555) Y(i,j,k) for k = 3 (-0.277, 0.237) (-0.688,-0.210) ( 0.109, 0.756) ( 0.047,-0.077) ( 0.201, 0.061) (-0.128,-0.117) Original sequence as restored by inverse transform X(i,j,k) for k = 0 1.541 0.346 1.754 0.584 1.284 0.855 0.010 1.960 0.089 X(i,j,k) for k = 1 0.161 1.907 0.042 1.004 1.137 0.725 1.844 0.240 1.660 X(i,j,k) for k = 2 1.989 0.001 1.991 1.408 0.467 1.647 0.452 1.424 0.708 X(i,j,k) for k = 3 0.037 1.915 0.151 0.252 1.834 0.096 1.154 0.987 0.872