# NAG CL Interfacec06pyc (fft_​real_​3d)

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## 1Purpose

c06pyc computes the three-dimensional discrete Fourier transform of a trivariate sequence of real data values.

## 2Specification

 #include
 void c06pyc (Integer n1, Integer n2, Integer n3, const double x[], Complex y[], NagError *fail)
The function may be called by the names: c06pyc or nag_sum_fft_real_3d.

## 3Description

c06pyc computes the three-dimensional discrete Fourier transform of a trivariate sequence of real data values ${x}_{{j}_{1}{j}_{2}{j}_{3}}$, for ${j}_{1}=0,1,\dots ,{n}_{1}-1$, ${j}_{2}=0,1,\dots ,{n}_{2}-1$ and ${j}_{3}=0,1,\dots ,{n}_{3}-1$.
The discrete Fourier transform is here defined by
 $z^ k1 k2 k3 = 1 n1 n2 n3 ∑ j1=0 n1-1 ∑ j2=0 n2-1 ∑ j3=0 n3-1 x j1 j2 j3 × exp(-2πi( j1 k1 n1 + j2 k2 n2 + j3 k3 n3 )) ,$
where ${k}_{1}=0,1,\dots ,{n}_{1}-1$, ${k}_{2}=0,1,\dots ,{n}_{2}-1$ and ${k}_{3}=0,1,\dots ,{n}_{3}-1$. (Note the scale factor of $\frac{1}{\sqrt{{n}_{1}{n}_{2}{n}_{3}}}$ in this definition.)
The transformed values ${\stackrel{^}{z}}_{{k}_{1}{k}_{2}{k}_{3}}$ are complex. Because of conjugate symmetry (i.e., ${\stackrel{^}{z}}_{{k}_{1}{k}_{2}{k}_{3}}$ is the complex conjugate of ${\stackrel{^}{z}}_{\left({n}_{1}-{k}_{1}\right)\left({n}_{2}-{k}_{2}\right)\left({n}_{3}-{k}_{3}\right)}$), only slightly more than half of the Fourier coefficients need to be stored in the output.
A call of c06pyc followed by a call of c06pzc will restore the original data.
This function performs multiple one-dimensional discrete Fourier transforms by the fast Fourier transform (FFT) algorithm in Brigham (1974) and Temperton (1983).

## 4References

Brigham E O (1974) The Fast Fourier Transform Prentice–Hall
Temperton C (1983) Fast mixed-radix real Fourier transforms J. Comput. Phys. 52 340–350

## 5Arguments

1: $\mathbf{n1}$Integer Input
On entry: ${n}_{1}$, the first dimension of the transform.
Constraint: ${\mathbf{n1}}\ge 1$.
2: $\mathbf{n2}$Integer Input
On entry: ${n}_{2}$, the second dimension of the transform.
Constraint: ${\mathbf{n2}}\ge 1$.
3: $\mathbf{n3}$Integer Input
On entry: ${n}_{3}$, the third dimension of the transform.
Constraint: ${\mathbf{n3}}\ge 1$.
4: $\mathbf{x}\left[{\mathbf{n1}}×{\mathbf{n2}}×{\mathbf{n3}}\right]$const double Input
On entry: the real input dataset $x$, where ${x}_{{j}_{1}{j}_{2}{j}_{3}}$ is stored in ${\mathbf{x}}\left[{j}_{3}×{n}_{1}{n}_{2}+{j}_{2}×{n}_{1}+{j}_{1}\right]$, for ${j}_{1}=0,1,\dots ,{n}_{1}-1$, ${j}_{2}=0,1,\dots ,{n}_{2}-1$ and ${j}_{3}=0,1,\dots ,{n}_{3}-1$.
5: $\mathbf{y}\left[\mathit{dim}\right]$Complex Output
Note: the dimension, dim, of the array y must be at least $\left({\mathbf{n1}}/2+1\right)×{\mathbf{n2}}×{\mathbf{n3}}$.
On exit: the complex output dataset $\stackrel{^}{z}$, where ${\stackrel{^}{z}}_{{k}_{1}{k}_{2}{k}_{3}}$ is stored in ${\mathbf{y}}\left[{k}_{3}×\left({n}_{1}/2+1\right){n}_{2}+{k}_{2}×\left({n}_{1}/2+1\right)+{k}_{1}\right]$, for ${k}_{1}=0,1,\dots ,{n}_{1}/2$, ${k}_{2}=0,1,\dots ,{n}_{2}-1$ and ${k}_{3}=0,1,\dots ,{n}_{3}-1$. Note the first dimension is cut roughly by half to remove the redundant information due to conjugate symmetry.
6: $\mathbf{fail}$NagError * Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

## 6Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
On entry, argument $⟨\mathit{\text{value}}⟩$ had an illegal value.
NE_INT
On entry, ${\mathbf{n1}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{n1}}\ge 1$.
On entry, ${\mathbf{n2}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{n2}}\ge 1$.
On entry, ${\mathbf{n3}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{n3}}\ge 1$.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.

## 7Accuracy

Some indication of accuracy can be obtained by performing a forward transform using c06pyc and a backward transform using c06pzc, and comparing the results with the original sequence (in exact arithmetic they would be identical).

## 8Parallelism and Performance

c06pyc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c06pyc makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

The time taken by c06pyc is approximately proportional to ${n}_{1}{n}_{2}{n}_{3}\mathrm{log}\left({n}_{1}{n}_{2}{n}_{3}\right)$, but also depends on the factors of ${n}_{1}$, ${n}_{2}$ and ${n}_{3}$. c06pyc is fastest if the only prime factors of ${n}_{1}$, ${n}_{2}$ and ${n}_{3}$ are $2$, $3$ and $5$, and is particularly slow if one of the dimensions is a large prime, or has large prime factors.
Workspace is internally allocated by c06pyc. The total size of these arrays is approximately proportional to ${n}_{1}{n}_{2}{n}_{3}$.

## 10Example

This example reads in a trivariate sequence of real data values and prints their discrete Fourier transforms as computed by c06pyc. Inverse transforms are then calculated by calling c06pzc showing that the original sequences are restored.

### 10.1Program Text

Program Text (c06pyce.c)

### 10.2Program Data

Program Data (c06pyce.d)

### 10.3Program Results

Program Results (c06pyce.r)