The function may be called by the names: c06pjc, nag_sum_fft_complex_multid or nag_fft_multid_full.
c06pjc computes the multidimensional discrete Fourier transform of a multidimensional sequence of complex data values , where , and so on. Thus the individual dimensions are , and the total number of data values is .
The discrete Fourier transform is here defined (e.g., for ) by:
where and . The plus or minus sign in the argument of the exponential terms in the above definition determine the direction of the transform: a minus sign defines the forward direction and a plus sign defines the backward direction.
The extension to higher dimensions is obvious. (Note the scale factor of in this definition.)
A call of c06pjc with followed by a call with will restore the original data.
The data values must be supplied in a one-dimensional array using column-major storage ordering of multidimensional data (i.e., with the first subscript varying most rapidly).
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).
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
1: – Nag_TransformDirectionInput
On entry: if the forward transform as defined in Section 3 is to be computed, direct must be set equal to .
If the backward transform is to be computed, direct must be set equal to .
2: – IntegerInput
On entry: , the number of dimensions (or variables) in the multivariate data.
3: – const IntegerInput
On entry: the elements of nd must contain the dimensions of the ndim variables; that is, must contain the dimension of the th variable.
, for .
4: – IntegerInput
On entry: , the total number of data values.
n must equal the product of the first ndim elements of the array nd.
5: – ComplexInput/Output
On entry: the complex data values. Data values are stored in x using column-major ordering for storing multidimensional arrays; that is, is stored in .
On exit: the corresponding elements of the computed transform.
6: – NagError *Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).
6Error Indicators and Warnings
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
On entry, argument had an illegal value.
On entry, .
On entry, , product of nd elements is .
Constraint: n must equal the product of the dimensions held in array nd.
On entry, .
Constraint: , for all .
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.
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.
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
c06pjc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
c06pjc 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 , but also depends on the factorization of the individual dimensions . c06pjc is faster if the only prime factors are , or ; and fastest of all if they are powers of .
This example reads in a bivariate sequence of complex data values and prints the two-dimensional Fourier transform. It then performs an inverse transform and prints the sequence so obtained, which may be compared to the original data values.