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date Fri, 07 Feb 2020 11:51:13 +0000
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Chris@10 3 <title>Multi-dimensional Transforms - FFTW 3.3.3</title>
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Chris@10 48 <a name="Multi-dimensional-Transforms"></a>
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Chris@10 50 <p>
Chris@10 51 Previous:&nbsp;<a rel="previous" accesskey="p" href="1d-Discrete-Hartley-Transforms-_0028DHTs_0029.html#g_t1d-Discrete-Hartley-Transforms-_0028DHTs_0029">1d Discrete Hartley Transforms (DHTs)</a>,
Chris@10 52 Up:&nbsp;<a rel="up" accesskey="u" href="What-FFTW-Really-Computes.html#What-FFTW-Really-Computes">What FFTW Really Computes</a>
Chris@10 53 <hr>
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Chris@10 55
Chris@10 56 <h4 class="subsection">4.8.6 Multi-dimensional Transforms</h4>
Chris@10 57
Chris@10 58 <p>The multi-dimensional transforms of FFTW, in general, compute simply the
Chris@10 59 separable product of the given 1d transform along each dimension of the
Chris@10 60 array. Since each of these transforms is unnormalized, computing the
Chris@10 61 forward followed by the backward/inverse multi-dimensional transform
Chris@10 62 will result in the original array scaled by the product of the
Chris@10 63 normalization factors for each dimension (e.g. the product of the
Chris@10 64 dimension sizes, for a multi-dimensional DFT).
Chris@10 65
Chris@10 66 <p><a name="index-r2c-325"></a>The definition of FFTW's multi-dimensional DFT of real data (r2c)
Chris@10 67 deserves special attention. In this case, we logically compute the full
Chris@10 68 multi-dimensional DFT of the input data; since the input data are purely
Chris@10 69 real, the output data have the Hermitian symmetry and therefore only one
Chris@10 70 non-redundant half need be stored. More specifically, for an n<sub>0</sub>&nbsp;&times;&nbsp;n<sub>1</sub>&nbsp;&times;&nbsp;n<sub>2</sub>&nbsp;&times;&nbsp;&hellip;&nbsp;&times;&nbsp;n<sub>d-1</sub> multi-dimensional real-input DFT, the full (logical) complex output array
Chris@10 71 <i>Y</i>[<i>k</i><sub>0</sub>, <i>k</i><sub>1</sub>, ...,
Chris@10 72 <i>k</i><sub><i>d-1</i></sub>]has the symmetry:
Chris@10 73 <i>Y</i>[<i>k</i><sub>0</sub>, <i>k</i><sub>1</sub>, ...,
Chris@10 74 <i>k</i><sub><i>d-1</i></sub>] = <i>Y</i>[<i>n</i><sub>0</sub> -
Chris@10 75 <i>k</i><sub>0</sub>, <i>n</i><sub>1</sub> - <i>k</i><sub>1</sub>, ...,
Chris@10 76 <i>n</i><sub><i>d-1</i></sub> - <i>k</i><sub><i>d-1</i></sub>]<sup>*</sup>(where each dimension is periodic). Because of this symmetry, we only
Chris@10 77 store the
Chris@10 78 <i>k</i><sub><i>d-1</i></sub> = 0...<i>n</i><sub><i>d-1</i></sub>/2+1elements of the <em>last</em> dimension (division by 2 is rounded
Chris@10 79 down). (We could instead have cut any other dimension in half, but the
Chris@10 80 last dimension proved computationally convenient.) This results in the
Chris@10 81 peculiar array format described in more detail by <a href="Real_002ddata-DFT-Array-Format.html#Real_002ddata-DFT-Array-Format">Real-data DFT Array Format</a>.
Chris@10 82
Chris@10 83 <p>The multi-dimensional c2r transform is simply the unnormalized inverse
Chris@10 84 of the r2c transform. i.e. it is the same as FFTW's complex backward
Chris@10 85 multi-dimensional DFT, operating on a Hermitian input array in the
Chris@10 86 peculiar format mentioned above and outputting a real array (since the
Chris@10 87 DFT output is purely real).
Chris@10 88
Chris@10 89 <p>We should remind the user that the separable product of 1d transforms
Chris@10 90 along each dimension, as computed by FFTW, is not always the same thing
Chris@10 91 as the usual multi-dimensional transform. A multi-dimensional
Chris@10 92 <code>R2HC</code> (or <code>HC2R</code>) transform is not identical to the
Chris@10 93 multi-dimensional DFT, requiring some post-processing to combine the
Chris@10 94 requisite real and imaginary parts, as was described in <a href="The-Halfcomplex_002dformat-DFT.html#The-Halfcomplex_002dformat-DFT">The Halfcomplex-format DFT</a>. Likewise, FFTW's multidimensional
Chris@10 95 <code>FFTW_DHT</code> r2r transform is not the same thing as the logical
Chris@10 96 multi-dimensional discrete Hartley transform defined in the literature,
Chris@10 97 as discussed in <a href="The-Discrete-Hartley-Transform.html#The-Discrete-Hartley-Transform">The Discrete Hartley Transform</a>.
Chris@10 98
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