Determine which direction of DFT to execute.

Real to Real transform kinds.

Allows FFTW to overwrite the input array with arbitrary data; this can sometimes allow more efficient algorithms to be employed.

Setting this flag implies that two memory allocations will be done, one for work space, and one for the result. When estimate is not set, we will be doing two memory allocations anyway, so we set this flag as well (since we don't retain the work array anyway).

preserveInput specifies that an out-of-place transform must not change its input array. This is ordinarily the default, except for complex to real transforms for which destroyInput is the default. In the latter cases, passing preserveInput will attempt to use algorithms that do not destroy the input, at the expense of worse performance; for multi-dimensional complex to real transforms, however, no input-preserving algorithms are implemented so the Haskell bindings will set destroyInput and do a transform with two memory allocations.

estimate specifies that, instead of actual measurements of different algorithms, a simple heuristic is used to pick a (probably sub-optimal) plan quickly. With this flag, the input/output arrays are not overwritten during planning.

This is the only planner flag for which a single memory allocation is possible.

measure tells FFTW to find an optimized plan by actually computing several FFTs and measuring their execution time. Depending on your machine, this can take some time (often a few seconds). measure is the default planning option.

patient is like measure, but considers a wider range of algorithms and often produces a "more optimal" plan (especially for large transforms), but at the expense of several times longer planning time (especially for large transforms).

exhaustive is like patient but considers an even wider range of algorithms, including many that we think are unlikely to be fast, to produce the most optimal plan but with a substantially increased planning time.

1-dimensional complex DFT.

1-dimensional complex inverse DFT. Inverse of dft.

Multi-dimensional forward DFT.

Multi-dimensional inverse DFT.

Normalized general complex DFT

Complex to Complex DFT, un-normalized.

1-dimensional real to complex DFT.

1-dimensional complex to real DFT with logically even dimension. Inverse of dftRC.

1-dimensional complex to real DFT with logically odd dimension. Inverse of dftRC.

Multi-dimensional forward DFT of real data.

Multi-dimensional inverse DFT of Hermitian-symmetric data (where only the non-negative frequencies are given).

Multi-dimensional inverse DFT of Hermitian-symmetric data (where only the non-negative frequencies are given) and the last transformed dimension is logically odd.

Real to Complex DFT.

Normalized general complex to real DFT where the last transformed dimension is logically even.

Normalized general complex to real DFT where the last transformed dimension is logicall odd.

Complex to Real DFT where last transformed dimension is logically even.

Complex to Real DFT where last transformed dimension is logically odd.

1-dimensional real to half-complex DFT.

1-dimensional half-complex to real DFT. Inverse of dftRH after normalization.

1-dimensional Discrete Hartley Transform. Self-inverse after normalization.

1-dimensional Type 1 discrete cosine transform.

1-dimensional Type 2 discrete cosine transform. This is commonly known as the DCT.

1-dimensional Type 3 discrete cosine transform. This is commonly known as the inverse DCT.

1-dimensional Type 4 discrete cosine transform.

1-dimensional Type 1 discrete sine transform.

1-dimensional Type 2 discrete sine transform.

1-dimensional Type 3 discrete sine transform.

1-dimensional Type 4 discrete sine transform.

Multi-dimensional real to half-complex transform. The result is not normalized.

Multi-dimensional half-complex to real transform. The result is not normalized.

Multi-dimensional Discrete Hartley Transform. The result is not normalized.

Multi-dimensional Type 1 discrete cosine transform.

Multi-dimensional Type 2 discrete cosine transform. This is commonly known as the DCT.

Multi-dimensional Type 3 discrete cosine transform. This is commonly known as the inverse DCT. The result is not normalized.

Multi-dimensional Type 4 discrete cosine transform.

Multi-dimensional Type 1 discrete sine transform.

Multi-dimensional Type 2 discrete sine transform.

Multi-dimensional Type 3 discrete sine transform.

Multi-dimensional Type 4 discrete sine transform.

Multi-dimensional real to real transform. The result is not normalized.

Real to Real transforms.

Add wisdom to the FFTW cache. Returns True if it is successful.

Tries to import wisdom from a global source, typically etcfftw/wisdom. Returns True if it was successful.

Queries the FFTW cache. The String can be written to a file so the wisdom can be reused on a subsequent run.