# NAG CL Interfacec06pcc (fft_​complex_​1d)

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## 1Purpose

c06pcc calculates the discrete Fourier transform of a sequence of $n$ complex data values (using complex data type).

## 2Specification

 #include
 void c06pcc (Nag_TransformDirection direct, Complex x[], Integer n, NagError *fail)
The function may be called by the names: c06pcc or nag_sum_fft_complex_1d.

## 3Description

Given a sequence of $n$ complex data values ${z}_{\mathit{j}}$, for $\mathit{j}=0,1,\dots ,n-1$, c06pcc calculates their (forward or backward) discrete Fourier transform (DFT) defined by
 $z^k = 1n ∑ j=0 n-1 zj × exp(±i 2πjk n ) , k= 0, 1, …, n-1 .$
(Note the scale factor of $\frac{1}{\sqrt{n}}$ in this definition.) The minus sign is taken in the argument of the exponential within the summation when the forward transform is required, and the plus sign is taken when the backward transform is required.
A call of c06pcc with ${\mathbf{direct}}=\mathrm{Nag_ForwardTransform}$ followed by a call with ${\mathbf{direct}}=\mathrm{Nag_BackwardTransform}$ will restore the original data.
c06pcc uses a variant of the fast Fourier transform (FFT) algorithm (see Brigham (1974)) known as the Stockham self-sorting algorithm, which is described in Temperton (1983). If $n$ is a large prime number or if $n$ contains large prime factors, then the Fourier transform is performed using Bluestein's algorithm (see Bluestein (1968)), which expresses the DFT as a convolution that in turn can be efficiently computed using FFTs of highly composite sizes.

## 4References

Bluestein L I (1968) A linear filtering approach to the computation of the discrete Fourier transform Northeast Electronics Research and Engineering Meeting Record 10 218–219
Brigham E O (1974) The Fast Fourier Transform Prentice–Hall
Temperton C (1983) Self-sorting mixed-radix fast Fourier transforms J. Comput. Phys. 52 1–23

## 5Arguments

1: $\mathbf{direct}$Nag_TransformDirection Input
On entry: if the forward transform as defined in Section 3 is to be computed, direct must be set equal to $\mathrm{Nag_ForwardTransform}$.
If the backward transform is to be computed, direct must be set equal to $\mathrm{Nag_BackwardTransform}$.
Constraint: ${\mathbf{direct}}=\mathrm{Nag_ForwardTransform}$ or $\mathrm{Nag_BackwardTransform}$.
2: $\mathbf{x}\left[{\mathbf{n}}\right]$Complex Input/Output
On entry: ${\mathbf{x}}\left[\mathit{j}\right]$ must contain ${z}_{\mathit{j}}$, for $\mathit{j}=0,1,\dots ,n-1$.
On exit: the components of the discrete Fourier transform. ${\stackrel{^}{z}}_{k}$ is contained in ${\mathbf{x}}\left[k\right]$, for $0\le k\le n-1$.
3: $\mathbf{n}$Integer Input
On entry: $n$, the number of data values.
Constraint: ${\mathbf{n}}\ge 1$.
4: $\mathbf{fail}$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, ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{n}}\ge 1$.
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 subsequent inverse transform and comparing the results with the original sequence (in exact arithmetic they would be identical).

## 8Parallelism and Performance

c06pcc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c06pcc 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 is approximately proportional to $n×\mathrm{log}\left(n\right)$, but also depends on the factorization of $n$. c06pcc is faster if the only prime factors of $n$ are $2$, $3$ or $5$; and fastest of all if $n$ is a power of $2$. This function internally allocates a workspace of $2n+15$ Complex values. When the Bluestein's FFT algorithm is in use, an additional Complex workspace of size approximately $8n$ is allocated.

## 10Example

This example reads in a sequence of complex data values and prints their discrete Fourier transform (as computed by c06pcc with ${\mathbf{direct}}=\mathrm{Nag_ForwardTransform}$). It then performs an inverse transform using c06pcc with ${\mathbf{direct}}=\mathrm{Nag_BackwardTransform}$, and prints the sequence so obtained alongside the original data values.

### 10.1Program Text

Program Text (c06pcce.c)

### 10.2Program Data

Program Data (c06pcce.d)

### 10.3Program Results

Program Results (c06pcce.r)