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