NAG FL Interface
c06rbf (fft_real_cosine_simple)
1
Purpose
c06rbf computes the discrete Fourier cosine transforms of $m$ sequences of real data values.
2
Specification
Fortran Interface
Integer, Intent (In) 
:: 
m, n 
Integer, Intent (Inout) 
:: 
ifail 
Real (Kind=nag_wp), Intent (Inout) 
:: 
x(m*(n+3)), work(*) 

C Header Interface
#include <nag.h>
void 
c06rbf_ (const Integer *m, const Integer *n, double x[], double work[], Integer *ifail) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
c06rbf_ (const Integer &m, const Integer &n, double x[], double work[], Integer &ifail) 
}

The routine may be called by the names c06rbf or nagf_sum_fft_real_cosine_simple.
3
Description
Given
$m$ sequences of
$n+1$ real data values
${x}_{\mathit{j}}^{\mathit{p}}$, for
$\mathit{j}=0,1,\dots ,n$ and
$\mathit{p}=1,2,\dots ,m$,
c06rbf simultaneously calculates the Fourier cosine transforms of all the sequences defined by
(Note the scale factor
$\sqrt{\frac{2}{n}}$ in this definition.)
Since the Fourier cosine transform is its own inverse, two consecutive calls of c06rbf will restore the original data.
The transform calculated by this routine can be used to solve Poisson's equation when the derivative of the solution is specified at both left and right boundaries (see
Swarztrauber (1977)).
The routine uses a variant of the fast Fourier transform (FFT) algorithm (see
Brigham (1974)) known as the Stockham selfsorting algorithm, described in
Temperton (1983), together with pre and postprocessing stages described in
Swarztrauber (1982). Special coding is provided for the factors
$2$,
$3$,
$4$ and
$5$.
4
References
Brigham E O (1974) The Fast Fourier Transform Prentice–Hall
Swarztrauber P N (1977) The methods of cyclic reduction, Fourier analysis and the FACR algorithm for the discrete solution of Poisson's equation on a rectangle SIAM Rev. 19(3) 490–501
Swarztrauber P N (1982) Vectorizing the FFT's Parallel Computation (ed G Rodrique) 51–83 Academic Press
Temperton C (1983) Fast mixedradix real Fourier transforms J. Comput. Phys. 52 340–350
5
Arguments

1:
$\mathbf{m}$ – Integer
Input

On entry: $m$, the number of sequences to be transformed.
Constraint:
${\mathbf{m}}\ge 1$.

2:
$\mathbf{n}$ – Integer
Input

On entry: one less than the number of real values in each sequence, i.e., the number of values in each sequence is $n+1$.
Constraint:
${\mathbf{n}}\ge 1$.

3:
$\mathbf{x}\left({\mathbf{m}}\times \left({\mathbf{n}}+3\right)\right)$ – Real (Kind=nag_wp) array
Input/Output

On entry: the data must be stored in
x as if in a twodimensional array of dimension
$\left(1:{\mathbf{m}},0:{\mathbf{n}}+2\right)$; each of the
$m$ sequences is stored in a
row of the array.
In other words, if the
$\left(n+1\right)$ data values of the
$\mathit{p}$th sequence to be transformed are denoted by
${x}_{\mathit{j}}^{\mathit{p}}$, for
$\mathit{j}=0,1,\dots ,n$ and
$\mathit{p}=1,2,\dots ,m$, the first
$m\left(n+1\right)$ elements of the array
x must contain the values
The
$\left(n+2\right)$th and
$\left(n+3\right)$th elements of each row
${x}_{n+2}^{\mathit{p}},{x}_{n+3}^{\mathit{p}}$, for
$\mathit{p}=1,2,\dots ,m$, are required as workspace. These
$2m$ elements may contain arbitrary values as they are set to zero by the routine.
On exit: the
$m$ Fourier cosine transforms stored as if in a twodimensional array of dimension
$\left(1:{\mathbf{m}},0:{\mathbf{n}}+2\right)$. Each of the
$m$ transforms is stored in a
row of the array, overwriting the corresponding original data.
If the
$\left(n+1\right)$ components of the
$\mathit{p}$th Fourier cosine transform are denoted by
${\hat{x}}_{\mathit{k}}^{\mathit{p}}$, for
$\mathit{k}=0,1,\dots ,n$ and
$\mathit{p}=1,2,\dots ,m$, the
$m\left(n+3\right)$ elements of the array
x contain the values

4:
$\mathbf{work}\left(*\right)$ – Real (Kind=nag_wp) array
Workspace

Note: the dimension of the array
work
must be at least
${\mathbf{m}}\times {\mathbf{n}}+2\times {\mathbf{n}}+2\times {\mathbf{m}}+15$.
The workspace requirements as documented for c06rbf may be an overestimate in some implementations.
On exit:
${\mathbf{work}}\left(1\right)$ contains the minimum workspace required for the current values of
m and
n with this implementation.

5:
$\mathbf{ifail}$ – Integer
Input/Output

On entry:
ifail must be set to
$0$,
$1$ or
$1$ to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of $0$ causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of $1$ means that an error message is printed while a value of $1$ means that it is not.
If halting is not appropriate, the value
$1$ or
$1$ is recommended. If message printing is undesirable, then the value
$1$ is recommended. Otherwise, the value
$0$ is recommended.
When the value $\mathbf{1}$ or $\mathbf{1}$ is used it is essential to test the value of ifail on exit.
On exit:
${\mathbf{ifail}}={\mathbf{0}}$ unless the routine detects an error or a warning has been flagged (see
Section 6).
6
Error Indicators and Warnings
If on entry
${\mathbf{ifail}}=0$ or
$1$, explanatory error messages are output on the current error message unit (as defined by
x04aaf).
Errors or warnings detected by the routine:
 ${\mathbf{ifail}}=1$

On entry, ${\mathbf{m}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{m}}\ge 1$.
 ${\mathbf{ifail}}=2$

On entry, ${\mathbf{n}}=\u2329\mathit{\text{value}}\u232a$.
Constraint: ${\mathbf{n}}\ge 1$.
 ${\mathbf{ifail}}=3$

An internal error has occurred in this routine.
Check the routine call and any array sizes.
If the call is correct then please contact
NAG for assistance.
 ${\mathbf{ifail}}=99$
An unexpected error has been triggered by this routine. Please
contact
NAG.
See
Section 7 in the Introduction to the NAG Library FL Interface for further information.
 ${\mathbf{ifail}}=399$
Your licence key may have expired or may not have been installed correctly.
See
Section 8 in the Introduction to the NAG Library FL Interface for further information.
 ${\mathbf{ifail}}=999$
Dynamic memory allocation failed.
See
Section 9 in the Introduction to the NAG Library FL Interface for further information.
7
Accuracy
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).
8
Parallelism and Performance
c06rbf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c06rbf 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 routine. Please also consult the
Users' Note for your implementation for any additional implementationspecific information.
The time taken by c06rbf is approximately proportional to $nm\mathrm{log}\left(n\right)$, but also depends on the factors of $n$. c06rbf is fastest if the only prime factors of $n$ are $2$, $3$ and $5$, and is particularly slow if $n$ is a large prime, or has large prime factors.
10
Example
This example reads in sequences of real data values and prints their Fourier cosine transforms (as computed by c06rbf). It then calls the routine again and prints the results which may be compared with the original sequence.
10.1
Program Text
10.2
Program Data
10.3
Program Results