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# 3. FFTW Reference

This chapter provides a complete reference for all sequential (i.e., one-processor) FFTW functions. We first define the data types upon which FFTW operates, that is, real, complex, and “halfcomplex” numbers (see section Data Types). Then, in four sections, we explain the FFTW program interface for complex one-dimensional transforms (see section One-dimensional Transforms Reference), complex multi-dimensional transforms (see section Multi-dimensional Transforms Reference), and real one-dimensional transforms (see section Real One-dimensional Transforms Reference), real multi-dimensional transforms (see section Real Multi-dimensional Transforms Reference). Wisdom Reference describes the `wisdom` mechanism for exporting and importing plans. Finally, Memory Allocator Reference describes how to change FFTW’s default memory allocator. For parallel transforms, See section Parallel FFTW.

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## 3.1 Data Types

The routines in the FFTW package use three main kinds of data types. Real and complex numbers should be already known to the reader. We also use the term halfcomplex to describe complex arrays in a special packed format used by the one-dimensional real transforms (taking advantage of the hermitian symmetry that arises in those cases).

By including `<fftw.h>` or `<rfftw.h>`, you will have access to the following definitions:

    typedef double fftw_real;

    typedef struct {
         fftw_real re, im;
    } fftw_complex;

    #define c_re(c)  ((c).re)
    #define c_im(c)  ((c).im)

All FFTW operations are performed on the `fftw_real` and `fftw_complex` data types. For `fftw_complex` numbers, the two macros `c_re` and `c_im` retrieve, respectively, the real and imaginary parts of the number.

A real array is an array of real numbers. A complex array is an array of complex numbers. A one-dimensional array X of n complex numbers is hermitian if the following property holds: for all 0 &lt;= i &lt; n, we have X<sub>i</sub> = conj(X<sub>n-i</sub>). Hermitian arrays are relevant to FFTW because the Fourier transform of a real array is hermitian.

Because of its symmetry, a hermitian array can be stored in half the space of a complex array of the same size. FFTW’s one-dimensional real transforms store hermitian arrays as halfcomplex arrays. A halfcomplex array of size n is a one-dimensional array of n `fftw_real` numbers. A hermitian array X in stored into a halfcomplex array Y as follows. For all integers i such that 0 &lt;= i &lt;= n / 2, we have Y<sub>i</sub> = Re(X<sub>i</sub>). For all integers i such that 0 &lt; i &lt; n / 2, we have Y<sub>n-i</sub> = Im(X<sub>i</sub>).

We now illustrate halfcomplex storage for n = 4 and n = 5, since the scheme depends on the parity of n. Let n = 4. In this case, we have Y<sub>0</sub> = Re(X<sub>0</sub>), Y<sub>1</sub> = Re(X<sub>1</sub>), Y<sub>2</sub> = Re(X<sub>2</sub>), and Y<sub>3</sub> = Im(X<sub>1</sub>). Let now n = 5. In this case, we have Y<sub>0</sub> = Re(X<sub>0</sub>), Y<sub>1</sub> = Re(X<sub>1</sub>), Y<sub>2</sub> = Re(X<sub>2</sub>), Y<sub>3</sub> = Im(X<sub>2</sub>), and Y<sub>4</sub> = Im(X<sub>1</sub>).

By default, the type `fftw_real` equals the C type `double`. To work in single precision rather than double precision, `#define` the symbol `FFTW_ENABLE_FLOAT` in `fftw.h` and then recompile the library. On Unix systems, you can instead use `configure --enable-float` at installation time (see section Installation and Customization).

In version 1 of FFTW, the data types were called `FFTW_REAL` and `FFTW_COMPLEX`. We changed the capitalization for consistency with the rest of FFTW’s conventions. The old names are still supported, but their use is deprecated.

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## 3.2 One-dimensional Transforms Reference

The one-dimensional complex routines are generally prefixed with `fftw_`. Programs using FFTW should be linked with `-lfftw -lm` on Unix systems, or with the FFTW and standard math libraries in general.

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### 3.2.1 Plan Creation for One-dimensional Transforms

    #include <fftw.h>

    fftw_plan fftw_create_plan(int n, fftw_direction dir,
                               int flags);

    fftw_plan fftw_create_plan_specific(int n, fftw_direction dir,
                                        int flags,
                                        fftw_complex *in, int istride,
                                        fftw_complex *out, int ostride);

The function `fftw_create_plan` creates a plan, which is a data structure containing all the information that `fftw` needs in order to compute the 1D Fourier transform. You can create as many plans as you need, but only one plan for a given array size is required (a plan can be reused many times).

`fftw_create_plan` returns a valid plan, or `NULL` if, for some reason, the plan can’t be created. In the default installation, this cannot happen, but it is possible to configure FFTW in such a way that some input sizes are forbidden, and FFTW cannot create a plan.

The `fftw_create_plan_specific` variant takes as additional arguments specific input/output arrays and their strides. For the last four arguments, you should pass the arrays and strides that you will eventually be passing to `fftw`. The resulting plans will be optimized for those arrays and strides, although they may be used on other arrays as well. Note: the contents of the in and out arrays are destroyed by the specific planner (the initial contents are ignored, so the arrays need not have been initialized).

#### Arguments

- `n` is the size of the transform. It can be any positive integer.
- `dir` is the sign of the exponent in the formula that defines the Fourier transform. It can be -1 or +1. The aliases `FFTW_FORWARD` and `FFTW_BACKWARD` are provided, where `FFTW_FORWARD` stands for -1.
- `flags` is a boolean OR (‘`|`’) of zero or more of the following:
- `in`, `out`, `istride`, `ostride` (only for `fftw_create_plan_specific`): see corresponding arguments in the description of `fftw`. (See section Computing the One-dimensional Transform.) In particular, the `out` and `ostride` parameters have the same special meaning for `FFTW_IN_PLACE` transforms as they have for `fftw`.

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### 3.2.2 Discussion on Specific Plans

We recommend the use of the specific planners, even in cases where you will be transforming arrays different from those passed to the specific planners, as they confer the following advantages:

- The resulting plans will be optimized for your specific arrays and strides. This may or may not make a significant difference, but it certainly doesn’t hurt. (The ordinary planner does its planning based upon a stride-one temporary array that it allocates.)
- Less intermediate storage is required during the planning process. (The ordinary planner uses O(`N`) temporary storage, where `N` is the maximum dimension, while it is creating the plan.)
- For multi-dimensional transforms, new parameters become accessible for optimization by the planner. (Since multi-dimensional arrays can be very large, we don’t dare to allocate one in the ordinary planner for experimentation. This prevents us from doing certain optimizations that can yield dramatic improvements in some cases.)

On the other hand, note that the specific planner destroys the contents of the `in` and `out` arrays.

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### 3.2.3 Computing the One-dimensional Transform

    #include <fftw.h>

    void fftw(fftw_plan plan, int howmany,
              fftw_complex *in, int istride, int idist,
              fftw_complex *out, int ostride, int odist);

    void fftw_one(fftw_plan plan, fftw_complex *in,
              fftw_complex *out);

The function `fftw` computes the one-dimensional Fourier transform, using a plan created by `fftw_create_plan` (See section Plan Creation for One-dimensional Transforms.) The function `fftw_one` provides a simplified interface for the common case of single input array of stride 1.

#### Arguments

- `plan` is the plan created by `fftw_create_plan` (see section Plan Creation for One-dimensional Transforms).
- `howmany` is the number of transforms `fftw` will compute. It is faster to tell FFTW to compute many transforms, instead of simply calling `fftw` many times.
- `in`, `istride` and `idist` describe the input array(s). There are `howmany` input arrays; the first one is pointed to by `in`, the second one is pointed to by `in + idist`, and so on, up to `in + (howmany - 1) * idist`. Each input array consists of complex numbers (see section Data Types), which are not necessarily contiguous in memory. Specifically, `in[0]` is the first element of the first array, `in[istride]` is the second element of the first array, and so on. In general, the `i`-th element of the `j`-th input array will be in position `in[i * istride + j * idist]`.
- `out`, `ostride` and `odist` describe the output array(s). The format is the same as for the input array.

The function `fftw_one` transforms a single, contiguous input array to a contiguous output array. By definition, the call

    fftw_one(plan, in, out)

is equivalent to

    fftw(plan, 1, in, 1, 0, out, 1, 0)

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### 3.2.4 Destroying a One-dimensional Plan

    #include <fftw.h>

    void fftw_destroy_plan(fftw_plan plan);

The function `fftw_destroy_plan` frees the plan `plan` and releases all the memory associated with it. After destruction, a plan is no longer valid.

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### 3.2.5 What FFTW Really Computes

In this section, we define precisely what FFTW computes. Please be warned that different authors and software packages might employ different conventions than FFTW does.

The forward transform of a complex array X of size n computes an array Y, where <center><IMG SRC="equation-1.gif" ALIGN="top"></center>

The backward transform computes <center><IMG SRC="equation-2.gif" ALIGN="top"></center>

FFTW computes an unnormalized transform, that is, the equation IFFT(FFT(X)) = n X holds. In other words, applying the forward and then the backward transform will multiply the input by n.

An `FFTW_FORWARD` transform corresponds to a sign of -1 in the exponent of the DFT. Note also that we use the standard “in-order” output ordering—the k-th output corresponds to the frequency k/n (or k/T, where T is your total sampling period). For those who like to think in terms of positive and negative frequencies, this means that the positive frequencies are stored in the first half of the output and the negative frequencies are stored in backwards order in the second half of the output. (The frequency -k/n is the same as the frequency (n-k)/n.)

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## 3.3 Multi-dimensional Transforms Reference

The multi-dimensional complex routines are generally prefixed with `fftwnd_`. Programs using FFTWND should be linked with `-lfftw -lm` on Unix systems, or with the FFTW and standard math libraries in general.

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### 3.3.1 Plan Creation for Multi-dimensional Transforms

    #include <fftw.h>

    fftwnd_plan fftwnd_create_plan(int rank, const int *n,
                                   fftw_direction dir, int flags);

    fftwnd_plan fftw2d_create_plan(int nx, int ny,
                                   fftw_direction dir, int flags);

    fftwnd_plan fftw3d_create_plan(int nx, int ny, int nz,
                                   fftw_direction dir, int flags);

    fftwnd_plan fftwnd_create_plan_specific(int rank, const int *n,
                                            fftw_direction dir,
                                            int flags,
                                            fftw_complex *in, int istride,
                                            fftw_complex *out, int ostride);

    fftwnd_plan fftw2d_create_plan_specific(int nx, int ny,
                                            fftw_direction dir,
                                            int flags,
                                            fftw_complex *in, int istride,
                                            fftw_complex *out, int ostride);

    fftwnd_plan fftw3d_create_plan_specific(int nx, int ny, int nz,
                                            fftw_direction dir, int flags,
                                            fftw_complex *in, int istride,
                                            fftw_complex *out, int ostride);

The function `fftwnd_create_plan` creates a plan, which is a data structure containing all the information that `fftwnd` needs in order to compute a multi-dimensional Fourier transform. You can create as many plans as you need, but only one plan for a given array size is required (a plan can be reused many times). The functions `fftw2d_create_plan` and `fftw3d_create_plan` are optional, alternative interfaces to `fftwnd_create_plan` for two and three dimensions, respectively.

`fftwnd_create_plan` returns a valid plan, or `NULL` if, for some reason, the plan can’t be created. This can happen if memory runs out or if the arguments are invalid in some way (e.g. if `rank` < 0).

The `create_plan_specific` variants take as additional arguments specific input/output arrays and their strides. For the last four arguments, you should pass the arrays and strides that you will eventually be passing to `fftwnd`. The resulting plans will be optimized for those arrays and strides, although they may be used on other arrays as well. Note: the contents of the in and out arrays are destroyed by the specific planner (the initial contents are ignored, so the arrays need not have been initialized). See section Discussion on Specific Plans, for a discussion on specific plans.

#### Arguments

- `rank` is the dimensionality of the arrays to be transformed. It can be any non-negative integer.
- `n` is a pointer to an array of `rank` integers, giving the size of each dimension of the arrays to be transformed. These sizes, which must be positive integers, correspond to the dimensions of row-major arrays—i.e. `n[0]` is the size of the dimension whose indices vary most slowly, and so on. (See section Multi-dimensional Array Format, for more information on row-major storage.) See section Plan Creation for One-dimensional Transforms, for more information regarding optimal array sizes.
- `nx` and `ny` in `fftw2d_create_plan` are positive integers specifying the dimensions of the rank 2 array to be transformed. i.e. they specify that the transform will operate on `nx x ny` arrays in row-major order, where `nx` is the number of rows and `ny` is the number of columns.
- `nx`, `ny` and `nz` in `fftw3d_create_plan` are positive integers specifying the dimensions of the rank 3 array to be transformed. i.e. they specify that the transform will operate on `nx x ny x nz` arrays in row-major order.
- `dir` is the sign of the exponent in the formula that defines the Fourier transform. It can be -1 or +1. The aliases `FFTW_FORWARD` and `FFTW_BACKWARD` are provided, where `FFTW_FORWARD` stands for -1.
- `flags` is a boolean OR (‘`|`’) of zero or more of the following:
- `in`, `out`, `istride`, `ostride` (only for the `_create_plan_specific` variants): see corresponding arguments in the description of `fftwnd`. (See section Computing the Multi-dimensional Transform.)

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### 3.3.2 Computing the Multi-dimensional Transform

    #include <fftw.h>

    void fftwnd(fftwnd_plan plan, int howmany,
                fftw_complex *in, int istride, int idist,
                fftw_complex *out, int ostride, int odist);

    void fftwnd_one(fftwnd_plan p, fftw_complex *in,
                    fftw_complex *out);

The function `fftwnd` computes one or more multi-dimensional Fourier Transforms, using a plan created by `fftwnd_create_plan` (see section Plan Creation for Multi-dimensional Transforms). (Note that the plan determines the rank and dimensions of the array to be transformed.) The function `fftwnd_one` provides a simplified interface for the common case of single input array of stride 1.

#### Arguments

- `plan` is the plan created by `fftwnd_create_plan`. (see section Plan Creation for Multi-dimensional Transforms). In the case of two and three-dimensional transforms, it could also have been created by `fftw2d_create_plan` or `fftw3d_create_plan`, respectively.
- `howmany` is the number of multi-dimensional transforms `fftwnd` will compute.
- `in`, `istride` and `idist` describe the input array(s). There are `howmany` multi-dimensional input arrays; the first one is pointed to by `in`, the second one is pointed to by `in + idist`, and so on, up to `in + (howmany - 1) * idist`. Each multi-dimensional input array consists of complex numbers (see section Data Types), stored in row-major format (see section Multi-dimensional Array Format), which are not necessarily contiguous in memory. Specifically, `in[0]` is the first element of the first array, `in[istride]` is the second element of the first array, and so on. In general, the `i`-th element of the `j`-th input array will be in position `in[i * istride + j * idist]`. Note that, here, `i` refers to an index into the row-major format for the multi-dimensional array, rather than an index in any particular dimension.
- `out`, `ostride` and `odist` describe the output array(s). The format is the same as for the input array.

The function `fftwnd_one` transforms a single, contiguous input array to a contiguous output array. By definition, the call

    fftwnd_one(plan, in, out)

is equivalent to

    fftwnd(plan, 1, in, 1, 0, out, 1, 0)

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### 3.3.3 Destroying a Multi-dimensional Plan

    #include <fftw.h>

    void fftwnd_destroy_plan(fftwnd_plan plan);

The function `fftwnd_destroy_plan` frees the plan `plan` and releases all the memory associated with it. After destruction, a plan is no longer valid.

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### 3.3.4 What FFTWND Really Computes

The conventions that we follow for the multi-dimensional transform are analogous to those for the one-dimensional transform. In particular, the forward transform has a negative sign in the exponent and neither the forward nor the backward transforms will perform any normalization. Computing the backward transform of the forward transform will multiply the array by the product of its dimensions. The output is in-order, and the zeroth element of the output is the amplitude of the zero frequency component.

The Gods forbade using HTML to display mathematical formulas. Please see the TeX or Postscript version of this manual for the proper definition of the n-dimensional Fourier transform that FFTW uses. For completeness, we include a bitmap of the TeX output below: <P><center><IMG SRC="equation-3.gif" ALIGN="top"></center>

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## 3.4 Real One-dimensional Transforms Reference

The one-dimensional real routines are generally prefixed with `rfftw_`. (4) Programs using RFFTW should be linked with `-lrfftw -lfftw -lm` on Unix systems, or with the RFFTW, the FFTW, and the standard math libraries in general.

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### 3.4.1 Plan Creation for Real One-dimensional Transforms

    #include <rfftw.h>

    rfftw_plan rfftw_create_plan(int n, fftw_direction dir, int flags);

    rfftw_plan rfftw_create_plan_specific(int n, fftw_direction dir,
    	    int flags, fftw_real *in, int istride,
    	    fftw_real *out, int ostride);

The function `rfftw_create_plan` creates a plan, which is a data structure containing all the information that `rfftw` needs in order to compute the 1D real Fourier transform. You can create as many plans as you need, but only one plan for a given array size is required (a plan can be reused many times).

`rfftw_create_plan` returns a valid plan, or `NULL` if, for some reason, the plan can’t be created. In the default installation, this cannot happen, but it is possible to configure RFFTW in such a way that some input sizes are forbidden, and RFFTW cannot create a plan.

The `rfftw_create_plan_specific` variant takes as additional arguments specific input/output arrays and their strides. For the last four arguments, you should pass the arrays and strides that you will eventually be passing to `rfftw`. The resulting plans will be optimized for those arrays and strides, although they may be used on other arrays as well. Note: the contents of the in and out arrays are destroyed by the specific planner (the initial contents are ignored, so the arrays need not have been initialized). See section Discussion on Specific Plans, for a discussion on specific plans.

#### Arguments

- `n` is the size of the transform. It can be any positive integer.
- `dir` is the direction of the desired transform, either `FFTW_REAL_TO_COMPLEX` or `FFTW_COMPLEX_TO_REAL`, corresponding to `FFTW_FORWARD` or `FFTW_BACKWARD`, respectively.
- `flags` is a boolean OR (‘`|`’) of zero or more of the following:
- `in`, `out`, `istride`, `ostride` (only for `rfftw_create_plan_specific`): see corresponding arguments in the description of `rfftw`. (See section Computing the Real One-dimensional Transform.) In particular, the `out` and `ostride` parameters have the same special meaning for `FFTW_IN_PLACE` transforms as they have for `rfftw`.

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### 3.4.2 Computing the Real One-dimensional Transform

    #include <rfftw.h>

    void rfftw(rfftw_plan plan, int howmany,
               fftw_real *in, int istride, int idist,
               fftw_real *out, int ostride, int odist);

    void rfftw_one(rfftw_plan plan, fftw_real *in, fftw_real *out);

The function `rfftw` computes the Real One-dimensional Fourier Transform, using a plan created by `rfftw_create_plan` (see section Plan Creation for Real One-dimensional Transforms). The function `rfftw_one` provides a simplified interface for the common case of single input array of stride 1.

Important: When invoked for an out-of-place, `FFTW_COMPLEX_TO_REAL` transform, the input array is overwritten with scratch values by these routines. The input array is not modified for `FFTW_REAL_TO_COMPLEX` transforms.

#### Arguments

- `plan` is the plan created by `rfftw_create_plan` (see section Plan Creation for Real One-dimensional Transforms).
- `howmany` is the number of transforms `rfftw` will compute. It is faster to tell RFFTW to compute many transforms, instead of simply calling `rfftw` many times.
- `in`, `istride` and `idist` describe the input array(s). There are two cases. If the `plan` defines a `FFTW_REAL_TO_COMPLEX` transform, `in` is a real array. Otherwise, for `FFTW_COMPLEX_TO_REAL` transforms, `in` is a halfcomplex array whose contents will be destroyed.
- `out`, `ostride` and `odist` describe the output array(s), and have the same meaning as the corresponding parameters for the input array.

The function `rfftw_one` transforms a single, contiguous input array to a contiguous output array. By definition, the call

    rfftw_one(plan, in, out)

is equivalent to

    rfftw(plan, 1, in, 1, 0, out, 1, 0)

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### 3.4.3 Destroying a Real One-dimensional Plan

    #include <rfftw.h>

    void rfftw_destroy_plan(rfftw_plan plan);

The function `rfftw_destroy_plan` frees the plan `plan` and releases all the memory associated with it. After destruction, a plan is no longer valid.

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### 3.4.4 What RFFTW Really Computes

In this section, we define precisely what RFFTW computes.

The real to complex (`FFTW_REAL_TO_COMPLEX`) transform of a real array X of size n computes an hermitian array Y, where <center><IMG SRC="equation-1.gif" ALIGN="top"></center> (That Y is a hermitian array is not intended to be obvious, although the proof is easy.) The hermitian array Y is stored in halfcomplex order (see section Data Types). Currently, RFFTW provides no way to compute a real to complex transform with a positive sign in the exponent.

The complex to real (`FFTW_COMPLEX_TO_REAL`) transform of a hermitian array X of size n computes a real array Y, where <center><IMG SRC="equation-2.gif" ALIGN="top"></center> (That Y is a real array is not intended to be obvious, although the proof is easy.) The hermitian input array X is stored in halfcomplex order (see section Data Types). Currently, RFFTW provides no way to compute a complex to real transform with a negative sign in the exponent.

Like FFTW, RFFTW computes an unnormalized transform. In other words, applying the real to complex (forward) and then the complex to real (backward) transform will multiply the input by n.

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## 3.5 Real Multi-dimensional Transforms Reference

The multi-dimensional real routines are generally prefixed with `rfftwnd_`. Programs using RFFTWND should be linked with `-lrfftw -lfftw -lm` on Unix systems, or with the FFTW, RFFTW, and standard math libraries in general.

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### 3.5.1 Plan Creation for Real Multi-dimensional Transforms

    #include <rfftw.h>

    rfftwnd_plan rfftwnd_create_plan(int rank, const int *n,
                                     fftw_direction dir, int flags);

    rfftwnd_plan rfftw2d_create_plan(int nx, int ny,
                                     fftw_direction dir, int flags);

    rfftwnd_plan rfftw3d_create_plan(int nx, int ny, int nz,
                                     fftw_direction dir, int flags);

The function `rfftwnd_create_plan` creates a plan, which is a data structure containing all the information that `rfftwnd` needs in order to compute a multi-dimensional real Fourier transform. You can create as many plans as you need, but only one plan for a given array size is required (a plan can be reused many times). The functions `rfftw2d_create_plan` and `rfftw3d_create_plan` are optional, alternative interfaces to `rfftwnd_create_plan` for two and three dimensions, respectively.

`rfftwnd_create_plan` returns a valid plan, or `NULL` if, for some reason, the plan can’t be created. This can happen if the arguments are invalid in some way (e.g. if `rank` < 0).

#### Arguments

- `rank` is the dimensionality of the arrays to be transformed. It can be any non-negative integer.
- `n` is a pointer to an array of `rank` integers, giving the size of each dimension of the arrays to be transformed. Note that these are always the dimensions of the real arrays; the complex arrays have different dimensions (see section Array Dimensions for Real Multi-dimensional Transforms). These sizes, which must be positive integers, correspond to the dimensions of row-major arrays—i.e. `n[0]` is the size of the dimension whose indices vary most slowly, and so on. (See section Multi-dimensional Array Format, for more information.)
- `nx` and `ny` in `rfftw2d_create_plan` are positive integers specifying the dimensions of the rank 2 array to be transformed. i.e. they specify that the transform will operate on `nx x ny` arrays in row-major order, where `nx` is the number of rows and `ny` is the number of columns.
- `nx`, `ny` and `nz` in `rfftw3d_create_plan` are positive integers specifying the dimensions of the rank 3 array to be transformed. i.e. they specify that the transform will operate on `nx x ny x nz` arrays in row-major order.
- `dir` is the direction of the desired transform, either `FFTW_REAL_TO_COMPLEX` or `FFTW_COMPLEX_TO_REAL`, corresponding to `FFTW_FORWARD` or `FFTW_BACKWARD`, respectively.
- `flags` is a boolean OR (‘`|`’) of zero or more of the following:

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### 3.5.2 Computing the Real Multi-dimensional Transform

    #include <rfftw.h>

    void rfftwnd_real_to_complex(rfftwnd_plan plan, int howmany,
                                 fftw_real *in, int istride, int idist,
                                 fftw_complex *out, int ostride, int odist);
    void rfftwnd_complex_to_real(rfftwnd_plan plan, int howmany,
                                 fftw_complex *in, int istride, int idist,
                                 fftw_real *out, int ostride, int odist);

    void rfftwnd_one_real_to_complex(rfftwnd_plan p, fftw_real *in,
                                     fftw_complex *out);
    void rfftwnd_one_complex_to_real(rfftwnd_plan p, fftw_complex *in,
                                     fftw_real *out);

These functions compute the real multi-dimensional Fourier Transform, using a plan created by `rfftwnd_create_plan` (see section Plan Creation for Real Multi-dimensional Transforms). (Note that the plan determines the rank and dimensions of the array to be transformed.) The ‘``rfftwnd_one_``’ functions provide a simplified interface for the common case of single input array of stride 1. Unlike other transform routines in FFTW, we here use separate functions for the two directions of the transform in order to correctly express the datatypes of the parameters.

Important: When invoked for an out-of-place, `FFTW_COMPLEX_TO_REAL` transform with `rank > 1`, the input array is overwritten with scratch values by these routines. The input array is not modified for `FFTW_REAL_TO_COMPLEX` transforms or for `FFTW_COMPLEX_TO_REAL` with `rank == 1`.

#### Arguments

- `plan` is the plan created by `rfftwnd_create_plan`. (see section Plan Creation for Real Multi-dimensional Transforms). In the case of two and three-dimensional transforms, it could also have been created by `rfftw2d_create_plan` or `rfftw3d_create_plan`, respectively.

  `FFTW_REAL_TO_COMPLEX` plans must be used with the ‘``real_to_complex``’ functions, and `FFTW_COMPLEX_TO_REAL` plans must be used with the ‘``complex_to_real``’ functions. It is an error to mismatch the plan direction and the transform function.

- `howmany` is the number of transforms to be computed.
- `in`, `istride` and `idist` describe the input array(s). There are `howmany` input arrays; the first one is pointed to by `in`, the second one is pointed to by `in + idist`, and so on, up to `in + (howmany - 1) * idist`. Each input array is stored in row-major format (see section Multi-dimensional Array Format), and is not necessarily contiguous in memory. Specifically, `in[0]` is the first element of the first array, `in[istride]` is the second element of the first array, and so on. In general, the `i`-th element of the `j`-th input array will be in position `in[i * istride + j * idist]`. Note that, here, `i` refers to an index into the row-major format for the multi-dimensional array, rather than an index in any particular dimension.

  The dimensions of the arrays are different for real and complex data, and are discussed in more detail below (see section Array Dimensions for Real Multi-dimensional Transforms).

- `out`, `ostride` and `odist` describe the output array(s). The format is the same as that for the input array. See below for a discussion of the dimensions of the output array for real and complex data.

The function `rfftwnd_one` transforms a single, contiguous input array to a contiguous output array. By definition, the call

    rfftwnd_one_...(plan, in, out)

is equivalent to

    rfftwnd_...(plan, 1, in, 1, 0, out, 1, 0)

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### 3.5.3 Array Dimensions for Real Multi-dimensional Transforms

The output of a multi-dimensional transform of real data contains symmetries that, in principle, make half of the outputs redundant (see section What RFFTWND Really Computes). In practice, it is not possible to entirely realize these savings in an efficient and understandable format. Instead, the output of the rfftwnd transforms is slightly over half of the output of the corresponding complex transform. We do not “pack” the data in any way, but store it as an ordinary array of `fftw_complex` values. In fact, this data is simply a subsection of what would be the array in the corresponding complex transform.

Specifically, for a real transform of dimensions n<sub>1</sub> x n<sub>2</sub> x ... x n<sub>d</sub>, the complex data is an n<sub>1</sub> x n<sub>2</sub> x ... x (n<sub>d</sub>/2+1) array of `fftw_complex` values in row-major order (with the division rounded down). That is, we only store the lower half (plus one element) of the last dimension of the data from the ordinary complex transform. (We could have instead taken half of any other dimension, but implementation turns out to be simpler if the last, contiguous, dimension is used.)

Since the complex data is slightly larger than the real data, some complications arise for in-place transforms. In this case, the final dimension of the real data must be padded with extra values to accommodate the size of the complex data—two extra if the last dimension is even and one if it is odd. That is, the last dimension of the real data must physically contain 2 * (n<sub>d</sub>/2+1) `fftw_real` values (exactly enough to hold the complex data). This physical array size does not, however, change the logical array size—only n<sub>d</sub> values are actually stored in the last dimension, and n<sub>d</sub> is the last dimension passed to `rfftwnd_create_plan`.

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### 3.5.4 Strides in In-place RFFTWND

The fact that the input and output datatypes are different for rfftwnd complicates the meaning of the `stride` and `dist` parameters of in-place transforms—are they in units of `fftw_real` or `fftw_complex` elements? When reading the input, they are interpreted in units of the datatype of the input data. When writing the output, the `istride` and `idist` are translated to the output datatype’s “units” in one of two ways, corresponding to the two most common situations in which `stride` and `dist` parameters are useful. Below, we refer to these “translated” parameters as `ostride_t` and `odist_t`. (Note that these are computed internally by rfftwnd; the actual `ostride` and `odist` parameters are ignored for in-place transforms.)

First, there is the case where you are transforming a number of contiguous arrays located one after another in memory. In this situation, `istride` is `1` and `idist` is the product of the physical dimensions of the array. `ostride_t` and `odist_t` are then chosen so that the output arrays are contiguous and lie on top of the input arrays. `ostride_t` is therefore `1`. For a real-to-complex transform, `odist_t` is `idist/2`; for a complex-to-real transform, `odist_t` is `idist*2`.

The second case is when you have an array in which each element has `nc` components (e.g. a structure with `nc` numeric fields), and you want to transform all of the components at once. Here, `istride` is `nc` and `idist` is `1`. For this case, it is natural to want the output to also have `nc` consecutive components, now of the output data type; this is exactly what rfftwnd does. Specifically, it uses an `ostride_t` equal to `istride`, and an `odist_t` of `1`. (Astute readers will realize that some extra buffer space is required in order to perform such a transform; this is handled automatically by rfftwnd.)

The general rule is as follows. `ostride_t` equals `istride`. If `idist` is `1` and `idist` is less than `istride`, then `odist_t` is `1`. Otherwise, for a real-to-complex transform `odist_t` is `idist/2` and for a complex-to-real transform `odist_t` is `idist*2`.

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### 3.5.5 Destroying a Multi-dimensional Plan

    #include <rfftw.h>

    void rfftwnd_destroy_plan(rfftwnd_plan plan);

The function `rfftwnd_destroy_plan` frees the plan `plan` and releases all the memory associated with it. After destruction, a plan is no longer valid.

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### 3.5.6 What RFFTWND Really Computes

The conventions that we follow for the real multi-dimensional transform are analogous to those for the complex multi-dimensional transform. In particular, the forward transform has a negative sign in the exponent and neither the forward nor the backward transforms will perform any normalization. Computing the backward transform of the forward transform will multiply the array by the product of its dimensions (that is, the logical dimensions of the real data). The forward transform is real-to-complex and the backward transform is complex-to-real.

The Gods forbade using HTML to display mathematical formulas. Please see the TeX or Postscript version of this manual for the proper definition of the n-dimensional real Fourier transform that RFFTW uses. For completeness, we include a bitmap of the TeX output below: <P><center><IMG SRC="equation-4.gif" ALIGN="top"></center>

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## 3.6 Wisdom Reference

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### 3.6.1 Exporting Wisdom

    #include <fftw.h>

    void fftw_export_wisdom(void (*emitter)(char c, void *), void *data);
    void fftw_export_wisdom_to_file(FILE *output_file);
    char *fftw_export_wisdom_to_string(void);

These functions allow you to export all currently accumulated `wisdom` in a form from which it can be later imported and restored, even during a separate run of the program. (See section Words of Wisdom.) The current store of `wisdom` is not affected by calling any of these routines.

`fftw_export_wisdom` exports the `wisdom` to any output medium, as specified by the callback function `emitter`. `emitter` is a `putc`-like function that writes the character `c` to some output; its second parameter is the `data` pointer passed to `fftw_export_wisdom`. For convenience, the following two “wrapper” routines are provided:

`fftw_export_wisdom_to_file` writes the `wisdom` to the current position in `output_file`, which should be open with write permission. Upon exit, the file remains open and is positioned at the end of the `wisdom` data.

`fftw_export_wisdom_to_string` returns a pointer to a `NULL`-terminated string holding the `wisdom` data. This string is dynamically allocated, and it is the responsibility of the caller to deallocate it with `fftw_free` when it is no longer needed.

All of these routines export the wisdom in the same format, which we will not document here except to say that it is LISP-like ASCII text that is insensitive to white space.

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### 3.6.2 Importing Wisdom

    #include <fftw.h>

    fftw_status fftw_import_wisdom(int (*get_input)(void *), void *data);
    fftw_status fftw_import_wisdom_from_file(FILE *input_file);
    fftw_status fftw_import_wisdom_from_string(const char *input_string);

These functions import `wisdom` into a program from data stored by the `fftw_export_wisdom` functions above. (See section Words of Wisdom.) The imported `wisdom` supplements rather than replaces any `wisdom` already accumulated by the running program (except when there is conflicting `wisdom`, in which case the existing wisdom is replaced).

`fftw_import_wisdom` imports `wisdom` from any input medium, as specified by the callback function `get_input`. `get_input` is a `getc`-like function that returns the next character in the input; its parameter is the `data` pointer passed to `fftw_import_wisdom`. If the end of the input data is reached (which should never happen for valid data), it may return either `NULL` (ASCII 0) or `EOF` (as defined in `<stdio.h>`). For convenience, the following two “wrapper” routines are provided:

`fftw_import_wisdom_from_file` reads `wisdom` from the current position in `input_file`, which should be open with read permission. Upon exit, the file remains open and is positioned at the end of the `wisdom` data.

`fftw_import_wisdom_from_string` reads `wisdom` from the `NULL`-terminated string `input_string`.

The return value of these routines is `FFTW_SUCCESS` if the wisdom was read successfully, and `FFTW_FAILURE` otherwise. Note that, in all of these functions, any data in the input stream past the end of the `wisdom` data is simply ignored (it is not even read if the `wisdom` data is well-formed).

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### 3.6.3 Forgetting Wisdom

    #include <fftw.h>

    void fftw_forget_wisdom(void);

Calling `fftw_forget_wisdom` causes all accumulated `wisdom` to be discarded and its associated memory to be freed. (New `wisdom` can still be gathered subsequently, however.)

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## 3.7 Memory Allocator Reference

    #include <fftw.h>

    void *(*fftw_malloc_hook) (size_t n);
    void (*fftw_free_hook) (void *p);

Whenever it has to allocate and release memory, FFTW ordinarily calls `malloc` and `free`. If `malloc` fails, FFTW prints an error message and exits. This behavior may be undesirable in some applications. Also, special memory-handling functions may be necessary in certain environments. Consequently, FFTW provides means by which you can install your own memory allocator and take whatever error-correcting action you find appropriate. The variables `fftw_malloc_hook` and `fftw_free_hook` are pointers to functions, and they are normally `NULL`. If you set those variables to point to other functions, then FFTW will use your routines instead of `malloc` and `free`. `fftw_malloc_hook` must point to a `malloc`-like function, and `fftw_free_hook` must point to a `free`-like function.

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## 3.8 Thread safety

Users writing multi-threaded programs must concern themselves with the thread safety of the libraries they use—that is, whether it is safe to call routines in parallel from multiple threads. FFTW can be used in such an environment, but some care must be taken because certain parts of FFTW use private global variables to share data between calls. In particular, the plan-creation functions share trigonometric tables and accumulated `wisdom`. (Users should note that these comments only apply to programs using shared-memory threads. Parallelism using MPI or forked processes involves a separate address-space and global variables for each process, and is not susceptible to problems of this sort.)

The central restriction of FFTW is that it is not safe to create multiple plans in parallel. You must either create all of your plans from a single thread, or instead use a semaphore, mutex, or other mechanism to ensure that different threads don’t attempt to create plans at the same time. The same restriction also holds for destruction of plans and importing/forgetting `wisdom`. Once created, a plan may safely be used in any thread.

The actual transform routines in FFTW (`fftw_one`, etcetera) are re-entrant and thread-safe, so it is fine to call them simultaneously from multiple threads. Another question arises, however—is it safe to use the same plan for multiple transforms in parallel? (It would be unsafe if, for example, the plan were modified in some way by the transform.) We address this question by defining an additional planner flag, `FFTW_THREADSAFE`. When included in the flags for any of the plan-creation routines, `FFTW_THREADSAFE` guarantees that the resulting plan will be read-only and safe to use in parallel by multiple threads.

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