diff Lib/fftw-3.2.1/doc/html/.svn/text-base/One_002dDimensional-DFTs-of-Real-Data.html.svn-base @ 15:585caf503ef5 tip

Tidy up for ROLI
author Geogaddi\David <d.m.ronan@qmul.ac.uk>
date Tue, 17 May 2016 18:50:19 +0100
parents 636c989477e7
children
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--- a/Lib/fftw-3.2.1/doc/html/.svn/text-base/One_002dDimensional-DFTs-of-Real-Data.html.svn-base	Wed May 04 11:02:59 2016 +0100
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-
-<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 &ldquo;Hermitian&rdquo;
-<a name="index-Hermitian-45"></a>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>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
-&ldquo;padding&rdquo; of the input array for
-<a name="index-padding-46"></a>in-place transforms.  Second, the inverse transform (complex to real)
-has the side-effect of <em>destroying 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>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>),
-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:
-
-<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>
-   <p><a name="index-fftw_005fplan_005fdft_005fr2c_005f1d-47"></a><a name="index-fftw_005fplan_005fdft_005fc2r_005f1d-48"></a>
-for the real input to complex-Hermitian output (<dfn>r2c</dfn>) and
-complex-Hermitian input to real output (<dfn>c2r</dfn>) transforms. 
-<a name="index-r2c-49"></a><a name="index-c2r-50"></a>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>. 
-<a name="index-FFTW_005fFORWARD-51"></a><a name="index-FFTW_005fBACKWARD-52"></a>(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.) 
-<a name="index-precision-53"></a>
-Here, <code>n</code> is the &ldquo;logical&rdquo; 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,
-<a name="index-in_002dplace-54"></a><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.  The kth element of the complex array is
-exactly the same as the kth 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>&nbsp;log&nbsp;<i>n</i>) algorithm is used even for prime
-sizes.
-
-   <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. 
-<a name="index-flags-55"></a><a name="index-FFTW_005fPRESERVE_005fINPUT-56"></a>This flag is also not currently supported for multi-dimensional real
-DFTs (next section).
-
-   <p>Readers familiar with DFTs of real data will recall that the 0th (the
-&ldquo;DC&rdquo;) and <code>n/2</code>-th (the &ldquo;Nyquist&rdquo; 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>An alternative interface for one-dimensional r2c and c2r DFTs can be
-found in the `<samp><span class="samp">r2r</span></samp>' interface (see <a href="The-Halfcomplex_002dformat-DFT.html#The-Halfcomplex_002dformat-DFT">The Halfcomplex-format DFT</a>), with &ldquo;halfcomplex&rdquo;-format output that <em>is</em> the same size
-(and type) as the input array. 
-<a name="index-halfcomplex-format-57"></a>That interface, although it is not very useful for multi-dimensional
-transforms, may sometimes yield better performance.
-
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