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An r2r kind of `FFTW_R2HC`

(r2hc) corresponds to an r2c DFT
(see One-Dimensional DFTs of Real Data) but with “halfcomplex”
format output, and may sometimes be faster and/or more convenient than
the latter.
The inverse hc2r transform is of kind `FFTW_HC2R`

.
This consists of the non-redundant half of the complex output for a 1d
real-input DFT of size `n`

, stored as a sequence of `n`

real
numbers (`double`

) in the format:

r_{0}, r_{1}, r_{2}, ..., r_{n/2}, i_{(n+1)/2-1}, ..., i_{2}, i_{1}

Here,
r_{k}is the real part of the kth output, and
i_{k}is the imaginary part. (Division by 2 is rounded down.) For a
halfcomplex array `hc[n]`

, the kth component thus has its
real part in `hc[k]`

and its imaginary part in `hc[n-k]`

, with
the exception of `k`

`==`

`0`

or `n/2`

(the latter
only if `n`

is even)—in these two cases, the imaginary part is
zero due to symmetries of the real-input DFT, and is not stored.
Thus, the r2hc transform of `n`

real values is a halfcomplex array of
length `n`

, and vice versa for hc2r.

Aside from the differing format, the output of
`FFTW_R2HC`

/`FFTW_HC2R`

is otherwise exactly the same as for
the corresponding 1d r2c/c2r transform
(i.e. `FFTW_FORWARD`

/`FFTW_BACKWARD`

transforms, respectively).
Recall that these transforms are unnormalized, so r2hc followed by hc2r
will result in the original data multiplied by `n`

. Furthermore,
like the c2r transform, an out-of-place hc2r transform will
*destroy its input* array.

Although these halfcomplex transforms can be used with the
multi-dimensional r2r interface, the interpretation of such a separable
product of transforms along each dimension is problematic. For example,
consider a two-dimensional `n0`

by `n1`

, r2hc by r2hc
transform planned by ```
fftw_plan_r2r_2d(n0, n1, in, out, FFTW_R2HC,
FFTW_R2HC, FFTW_MEASURE)
```

. Conceptually, FFTW first transforms the rows
(of size `n1`

) to produce halfcomplex rows, and then transforms the
columns (of size `n0`

). Half of these column transforms, however,
are of imaginary parts, and should therefore be multiplied by i
and combined with the r2hc transforms of the real columns to produce the
2d DFT amplitudes; FFTW's r2r transform does *not* perform this
combination for you. Thus, if a multi-dimensional real-input/output DFT
is required, we recommend using the ordinary r2c/c2r
interface (see Multi-Dimensional DFTs of Real Data).