Multi-dimensional transforms work much the same way as one-dimensional
transforms: you allocate arrays of `fftw_complex`

(preferably
using `fftw_malloc`

), create an `fftw_plan`

, execute it as
many times as you want with `fftw_execute(plan)`

, and clean up
with `fftw_destroy_plan(plan)`

(and `fftw_free`

).

FFTW provides two routines for creating plans for 2d and 3d transforms, and one routine for creating plans of arbitrary dimensionality. The 2d and 3d routines have the following signature:

fftw_plan fftw_plan_dft_2d(int n0, int n1, fftw_complex *in, fftw_complex *out, int sign, unsigned flags); fftw_plan fftw_plan_dft_3d(int n0, int n1, int n2, fftw_complex *in, fftw_complex *out, int sign, unsigned flags);

These routines create plans for `n0`

by `n1`

two-dimensional
(2d) transforms and `n0`

by `n1`

by `n2`

3d transforms,
respectively. All of these transforms operate on contiguous arrays in
the C-standard row-major order, so that the last dimension has the
fastest-varying index in the array. This layout is described further in
Multi-dimensional Array Format.

FFTW can also compute transforms of higher dimensionality. In order to
avoid confusion between the various meanings of the the word
“dimension”, we use the term *rank*
to denote the number of independent indices in an array.^{1} For
example, we say that a 2d transform has rank 2, a 3d transform has
rank 3, and so on. You can plan transforms of arbitrary rank by
means of the following function:

fftw_plan fftw_plan_dft(int rank, const int *n, fftw_complex *in, fftw_complex *out, int sign, unsigned flags);

Here, `n`

is a pointer to an array `n[rank]`

denoting an
`n[0]`

by `n[1]`

by ... by `n[rank-1]`

transform.
Thus, for example, the call

fftw_plan_dft_2d(n0, n1, in, out, sign, flags);

is equivalent to the following code fragment:

int n[2]; n[0] = n0; n[1] = n1; fftw_plan_dft(2, n, in, out, sign, flags);

`fftw_plan_dft`

is not restricted to 2d and 3d transforms,
however, but it can plan transforms of arbitrary rank.

You may have noticed that all the planner routines described so far
have overlapping functionality. For example, you can plan a 1d or 2d
transform by using `fftw_plan_dft`

with a `rank`

of `1`

or `2`

, or even by calling `fftw_plan_dft_3d`

with `n0`

and/or `n1`

equal to `1`

(with no loss in efficiency). This
pattern continues, and FFTW's planning routines in general form a
“partial order,” sequences of
interfaces with strictly increasing generality but correspondingly
greater complexity.

`fftw_plan_dft`

is the most general complex-DFT routine that we
describe in this tutorial, but there are also the advanced and guru interfaces,
which allow one to efficiently combine multiple/strided transforms
into a single FFTW plan, transform a subset of a larger
multi-dimensional array, and/or to handle more general complex-number
formats. For more information, see FFTW Reference.

[1] The term “rank” is commonly used in the APL, FORTRAN, and Common Lisp traditions, although it is not so common in the C world.