cannam@95: cannam@95:
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fftw_plan fftw_plan_dft_r2c_1d(int n0, cannam@95: double *in, fftw_complex *out, cannam@95: unsigned flags); cannam@95: fftw_plan fftw_plan_dft_r2c_2d(int n0, int n1, cannam@95: double *in, fftw_complex *out, cannam@95: unsigned flags); cannam@95: fftw_plan fftw_plan_dft_r2c_3d(int n0, int n1, int n2, cannam@95: double *in, fftw_complex *out, cannam@95: unsigned flags); cannam@95: fftw_plan fftw_plan_dft_r2c(int rank, const int *n, cannam@95: double *in, fftw_complex *out, cannam@95: unsigned flags); cannam@95:cannam@95:
cannam@95: Plan a real-input/complex-output discrete Fourier transform (DFT) in
cannam@95: zero or more dimensions, returning an fftw_plan
(see Using Plans).
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Once you have created a plan for a certain transform type and cannam@95: parameters, then creating another plan of the same type and parameters, cannam@95: but for different arrays, is fast and shares constant data with the cannam@95: first plan (if it still exists). cannam@95: cannam@95:
The planner returns NULL
if the plan cannot be created. A
cannam@95: non-NULL
plan is always returned by the basic interface unless
cannam@95: you are using a customized FFTW configuration supporting a restricted
cannam@95: set of transforms, or if you use the FFTW_PRESERVE_INPUT
flag
cannam@95: with a multi-dimensional out-of-place c2r transform (see below).
cannam@95:
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rank
is the rank of the transform (it should be the size of the
cannam@95: array *n
), and can be any non-negative integer. (See Complex Multi-Dimensional DFTs, for the definition of “rank”.) The
cannam@95: ‘_1d’, ‘_2d’, and ‘_3d’ planners correspond to a
cannam@95: rank
of 1
, 2
, and 3
, respectively. The rank
cannam@95: may be zero, which is equivalent to a rank-1 transform of size 1, i.e. a
cannam@95: copy of one real number (with zero imaginary part) from input to output.
cannam@95:
cannam@95: n0
, n1
, n2
, or n[0..rank-1]
, (as appropriate
cannam@95: for each routine) specify the size of the transform dimensions. They
cannam@95: can be any positive integer. This is different in general from the
cannam@95: physical array dimensions, which are described in Real-data DFT Array Format.
cannam@95:
cannam@95: in
and out
point to the input and output arrays of the
cannam@95: transform, which may be the same (yielding an in-place transform).
cannam@95: These arrays are overwritten during planning, unless
cannam@95: FFTW_ESTIMATE
is used in the flags. (The arrays need not be
cannam@95: initialized, but they must be allocated.) For an in-place transform, it
cannam@95: is important to remember that the real array will require padding,
cannam@95: described in Real-data DFT Array Format.
cannam@95:
cannam@95: flags
is a bitwise OR (‘|’) of zero or more planner flags,
cannam@95: as defined in Planner Flags.
cannam@95:
cannam@95: The inverse transforms, taking complex input (storing the non-redundant cannam@95: half of a logically Hermitian array) to real output, are given by: cannam@95: cannam@95:
fftw_plan fftw_plan_dft_c2r_1d(int n0, cannam@95: fftw_complex *in, double *out, cannam@95: unsigned flags); cannam@95: fftw_plan fftw_plan_dft_c2r_2d(int n0, int n1, cannam@95: fftw_complex *in, double *out, cannam@95: unsigned flags); cannam@95: fftw_plan fftw_plan_dft_c2r_3d(int n0, int n1, int n2, cannam@95: fftw_complex *in, double *out, cannam@95: unsigned flags); cannam@95: fftw_plan fftw_plan_dft_c2r(int rank, const int *n, cannam@95: fftw_complex *in, double *out, cannam@95: unsigned flags); cannam@95:cannam@95:
cannam@95: The arguments are the same as for the r2c transforms, except that the cannam@95: input and output data formats are reversed. cannam@95: cannam@95:
FFTW computes an unnormalized transform: computing an r2c followed by a
cannam@95: c2r transform (or vice versa) will result in the original data
cannam@95: multiplied by the size of the transform (the product of the logical
cannam@95: dimensions).
cannam@95: An r2c transform produces the same output as a FFTW_FORWARD
cannam@95: complex DFT of the same input, and a c2r transform is correspondingly
cannam@95: equivalent to FFTW_BACKWARD
. For more information, see What FFTW Really Computes.
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