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|  | (version 3.3.10, 10 December 2020). | ||
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|  | Copyright (C) 2003 Matteo Frigo. | ||
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|  | <title>One-Dimensional DFTs of Real Data (FFTW 3.3.10)</title> | ||
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|  | <span id="One_002dDimensional-DFTs-of-Real-Data"></span><div class="header"> | ||
|  | <p> | ||
|  | Next: <a href="Multi_002dDimensional-DFTs-of-Real-Data.html" accesskey="n" rel="next">Multi-Dimensional DFTs of Real Data</a>, Previous: <a href="Complex-Multi_002dDimensional-DFTs.html" accesskey="p" rel="prev">Complex Multi-Dimensional DFTs</a>, Up: <a href="Tutorial.html" accesskey="u" rel="up">Tutorial</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> | ||
|  | <span id="One_002dDimensional-DFTs-of-Real-Data-1"></span><h3 class="section">2.3 One-Dimensional DFTs of Real Data</h3> | ||
|  | 
 | ||
|  | <p>In many practical applications, the input data <code>in[i]</code> are purely | ||
|  | real numbers, in which case the DFT output satisfies the “Hermitian” | ||
|  | <span id="index-Hermitian"></span> | ||
|  | redundancy: <code>out[i]</code> is the conjugate of <code>out[n-i]</code>.  It is | ||
|  | possible to take advantage of these circumstances in order to achieve | ||
|  | roughly a factor of two improvement in both speed and memory usage. | ||
|  | </p> | ||
|  | <p>In exchange for these speed and space advantages, the user sacrifices | ||
|  | some of the simplicity of FFTW’s complex transforms. First of all, the | ||
|  | input and output arrays are of <em>different sizes and types</em>: the | ||
|  | input is <code>n</code> real numbers, while the output is <code>n/2+1</code> | ||
|  | complex numbers (the non-redundant outputs); this also requires slight | ||
|  | “padding” of the input array for | ||
|  | <span id="index-padding"></span> | ||
|  | in-place transforms.  Second, the inverse transform (complex to real) | ||
|  | has the side-effect of <em>overwriting its input array</em>, by default. | ||
|  | Neither of these inconveniences should pose a serious problem for | ||
|  | users, but it is important to be aware of them. | ||
|  | </p> | ||
|  | <p>The routines to perform real-data transforms are almost the same as | ||
|  | those for complex transforms: you allocate arrays of <code>double</code> | ||
|  | and/or <code>fftw_complex</code> (preferably using <code>fftw_malloc</code> or | ||
|  | <code>fftw_alloc_complex</code>), create an <code>fftw_plan</code>, execute it as | ||
|  | many times as you want with <code>fftw_execute(plan)</code>, and clean up | ||
|  | with <code>fftw_destroy_plan(plan)</code> (and <code>fftw_free</code>).  The only | ||
|  | differences are that the input (or output) is of type <code>double</code> | ||
|  | and there are new routines to create the plan.  In one dimension: | ||
|  | </p> | ||
|  | <div class="example"> | ||
|  | <pre class="example">fftw_plan fftw_plan_dft_r2c_1d(int n, double *in, fftw_complex *out, | ||
|  |                                unsigned flags); | ||
|  | fftw_plan fftw_plan_dft_c2r_1d(int n, fftw_complex *in, double *out, | ||
|  |                                unsigned flags); | ||
|  | </pre></div> | ||
|  | <span id="index-fftw_005fplan_005fdft_005fr2c_005f1d"></span> | ||
|  | <span id="index-fftw_005fplan_005fdft_005fc2r_005f1d"></span> | ||
|  | 
 | ||
|  | <p>for the real input to complex-Hermitian output (<em>r2c</em>) and | ||
|  | complex-Hermitian input to real output (<em>c2r</em>) transforms. | ||
|  | <span id="index-r2c"></span> | ||
|  | <span id="index-c2r"></span> | ||
|  | Unlike the complex DFT planner, there is no <code>sign</code> argument. | ||
|  | Instead, r2c DFTs are always <code>FFTW_FORWARD</code> and c2r DFTs are | ||
|  | always <code>FFTW_BACKWARD</code>. | ||
|  | <span id="index-FFTW_005fFORWARD-1"></span> | ||
|  | <span id="index-FFTW_005fBACKWARD-1"></span> | ||
|  | (For single/long-double precision | ||
|  | <code>fftwf</code> and <code>fftwl</code>, <code>double</code> should be replaced by | ||
|  | <code>float</code> and <code>long double</code>, respectively.) | ||
|  | <span id="index-precision-1"></span> | ||
|  | </p> | ||
|  | 
 | ||
|  | <p>Here, <code>n</code> is the “logical” size of the DFT, not necessarily the | ||
|  | physical size of the array.  In particular, the real (<code>double</code>) | ||
|  | array has <code>n</code> elements, while the complex (<code>fftw_complex</code>) | ||
|  | array has <code>n/2+1</code> elements (where the division is rounded down). | ||
|  | For an in-place transform, | ||
|  | <span id="index-in_002dplace-1"></span> | ||
|  | <code>in</code> and <code>out</code> are aliased to the same array, which must be | ||
|  | big enough to hold both; so, the real array would actually have | ||
|  | <code>2*(n/2+1)</code> elements, where the elements beyond the first | ||
|  | <code>n</code> are unused padding.  (Note that this is very different from | ||
|  | the concept of “zero-padding” a transform to a larger length, which | ||
|  | changes the logical size of the DFT by actually adding new input | ||
|  | data.)  The <em>k</em>th element of the complex array is exactly the | ||
|  | same as the <em>k</em>th element of the corresponding complex DFT.  All | ||
|  | positive <code>n</code> are supported; products of small factors are most | ||
|  | efficient, but an <i>O</i>(<i>n</i> log <i>n</i>) | ||
|  |  algorithm is used even for prime sizes. | ||
|  | </p> | ||
|  | <p>As noted above, the c2r transform destroys its input array even for | ||
|  | out-of-place transforms.  This can be prevented, if necessary, by | ||
|  | including <code>FFTW_PRESERVE_INPUT</code> in the <code>flags</code>, with | ||
|  | unfortunately some sacrifice in performance. | ||
|  | <span id="index-flags-1"></span> | ||
|  | <span id="index-FFTW_005fPRESERVE_005fINPUT"></span> | ||
|  | This flag is also not currently supported for multi-dimensional real | ||
|  | DFTs (next section). | ||
|  | </p> | ||
|  | <p>Readers familiar with DFTs of real data will recall that the 0th (the | ||
|  | “DC”) and <code>n/2</code>-th (the “Nyquist” frequency, when <code>n</code> is | ||
|  | even) elements of the complex output are purely real.  Some | ||
|  | implementations therefore store the Nyquist element where the DC | ||
|  | imaginary part would go, in order to make the input and output arrays | ||
|  | the same size.  Such packing, however, does not generalize well to | ||
|  | multi-dimensional transforms, and the space savings are miniscule in | ||
|  | any case; FFTW does not support it. | ||
|  | </p> | ||
|  | <p>An alternative interface for one-dimensional r2c and c2r DFTs can be | ||
|  | found in the ‘<samp>r2r</samp>’ interface (see <a href="The-Halfcomplex_002dformat-DFT.html">The Halfcomplex-format DFT</a>), with “halfcomplex”-format output that <em>is</em> the same size | ||
|  | (and type) as the input array. | ||
|  | <span id="index-halfcomplex-format"></span> | ||
|  | That interface, although it is not very useful for multi-dimensional | ||
|  | transforms, may sometimes yield better performance. | ||
|  | </p> | ||
|  | <hr> | ||
|  | <div class="header"> | ||
|  | <p> | ||
|  | Next: <a href="Multi_002dDimensional-DFTs-of-Real-Data.html" accesskey="n" rel="next">Multi-Dimensional DFTs of Real Data</a>, Previous: <a href="Complex-Multi_002dDimensional-DFTs.html" accesskey="p" rel="prev">Complex Multi-Dimensional DFTs</a>, Up: <a href="Tutorial.html" accesskey="u" rel="up">Tutorial</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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