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			126 lines
		
	
	
		
			6.5 KiB
		
	
	
	
		
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								<!-- This manual is for FFTW
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								(version 3.3.10, 10 December 2020).
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								Copyright (C) 2003 Matteo Frigo.
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								Copyright (C) 2003 Massachusetts Institute of Technology.
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								Permission is granted to make and distribute verbatim copies of this
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								<title>Multi-dimensional Transforms (FFTW 3.3.10)</title>
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								<meta name="description" content="Multi-dimensional Transforms (FFTW 3.3.10)">
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								<link href="Concept-Index.html" rel="index" title="Concept Index">
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								<link href="index.html#SEC_Contents" rel="contents" title="Table of Contents">
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								<link href="What-FFTW-Really-Computes.html" rel="up" title="What FFTW Really Computes">
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								<link href="Multi_002dthreaded-FFTW.html" rel="next" title="Multi-threaded FFTW">
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								<link href="1d-Discrete-Hartley-Transforms-_0028DHTs_0029.html" rel="prev" title="1d Discrete Hartley Transforms (DHTs)">
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								<span id="Multi_002ddimensional-Transforms"></span><div class="header">
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								<p>
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								Previous: <a href="1d-Discrete-Hartley-Transforms-_0028DHTs_0029.html" accesskey="p" rel="prev">1d Discrete Hartley Transforms (DHTs)</a>, Up: <a href="What-FFTW-Really-Computes.html" accesskey="u" rel="up">What FFTW Really Computes</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html" title="Index" rel="index">Index</a>]</p>
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								<hr>
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								<span id="Multi_002ddimensional-Transforms-1"></span><h4 class="subsection">4.8.6 Multi-dimensional Transforms</h4>
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								<p>The multi-dimensional transforms of FFTW, in general, compute simply the
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								separable product of the given 1d transform along each dimension of the
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								array.  Since each of these transforms is unnormalized, computing the
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								forward followed by the backward/inverse multi-dimensional transform
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								will result in the original array scaled by the product of the
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								normalization factors for each dimension (e.g. the product of the
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								dimension sizes, for a multi-dimensional DFT).
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								</p>
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								<span id="index-r2c-3"></span>
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								<p>The definition of FFTW’s multi-dimensional DFT of real data (r2c)
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								deserves special attention.  In this case, we logically compute the full
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								multi-dimensional DFT of the input data; since the input data are purely
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								real, the output data have the Hermitian symmetry and therefore only one
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								non-redundant half need be stored.  More specifically, for an n<sub>0</sub> × n<sub>1</sub> × n<sub>2</sub> × … × n<sub>d-1</sub>
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								 multi-dimensional real-input DFT, the full (logical) complex output array
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								<i>Y</i>[<i>k</i><sub>0</sub>, <i>k</i><sub>1</sub>, ...,
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								<i>k</i><sub><i>d-1</i></sub>]
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								has the symmetry:
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								<i>Y</i>[<i>k</i><sub>0</sub>, <i>k</i><sub>1</sub>, ...,
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								<i>k</i><sub><i>d-1</i></sub>] = <i>Y</i>[<i>n</i><sub>0</sub> -
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								<i>k</i><sub>0</sub>, <i>n</i><sub>1</sub> - <i>k</i><sub>1</sub>, ...,
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								<i>n</i><sub><i>d-1</i></sub> - <i>k</i><sub><i>d-1</i></sub>]<sup>*</sup>
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								(where each dimension is periodic).  Because of this symmetry, we only
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								store the
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								<i>k</i><sub><i>d-1</i></sub> = 0...<i>n</i><sub><i>d-1</i></sub>/2+1
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								elements of the <em>last</em> dimension (division by <em>2</em> is rounded
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								down).  (We could instead have cut any other dimension in half, but the
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								last dimension proved computationally convenient.)  This results in the
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								peculiar array format described in more detail by <a href="Real_002ddata-DFT-Array-Format.html">Real-data DFT Array Format</a>.
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								</p>
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								<p>The multi-dimensional c2r transform is simply the unnormalized inverse
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								of the r2c transform.  i.e. it is the same as FFTW’s complex backward
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								multi-dimensional DFT, operating on a Hermitian input array in the
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								peculiar format mentioned above and outputting a real array (since the
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								DFT output is purely real).
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								</p>
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								<p>We should remind the user that the separable product of 1d transforms
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								along each dimension, as computed by FFTW, is not always the same thing
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								as the usual multi-dimensional transform.  A multi-dimensional
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								<code>R2HC</code> (or <code>HC2R</code>) transform is not identical to the
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								multi-dimensional DFT, requiring some post-processing to combine the
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								requisite real and imaginary parts, as was described in <a href="The-Halfcomplex_002dformat-DFT.html">The Halfcomplex-format DFT</a>.  Likewise, FFTW’s multidimensional
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								<code>FFTW_DHT</code> r2r transform is not the same thing as the logical
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								multi-dimensional discrete Hartley transform defined in the literature,
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								as discussed in <a href="The-Discrete-Hartley-Transform.html">The Discrete Hartley Transform</a>.
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								</p>
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								<hr>
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								<div class="header">
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								<p>
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								Previous: <a href="1d-Discrete-Hartley-Transforms-_0028DHTs_0029.html" accesskey="p" rel="prev">1d Discrete Hartley Transforms (DHTs)</a>, Up: <a href="What-FFTW-Really-Computes.html" accesskey="u" rel="up">What FFTW Really Computes</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html" title="Index" rel="index">Index</a>]</p>
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