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| Chris@42 | 25 <title>FFTW 3.3.5: Real even/odd DFTs (cosine/sine transforms)</title> | 
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| Chris@42 | 36 <link href="More-DFTs-of-Real-Data.html#More-DFTs-of-Real-Data" rel="up" title="More DFTs of Real Data"> | 
| Chris@42 | 37 <link href="The-Discrete-Hartley-Transform.html#The-Discrete-Hartley-Transform" rel="next" title="The Discrete Hartley Transform"> | 
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| Chris@42 | 72 <a name="Real-even_002fodd-DFTs-_0028cosine_002fsine-transforms_0029"></a> | 
| Chris@42 | 73 <div class="header"> | 
| Chris@42 | 74 <p> | 
| Chris@42 | 75 Next: <a href="The-Discrete-Hartley-Transform.html#The-Discrete-Hartley-Transform" accesskey="n" rel="next">The Discrete Hartley Transform</a>, Previous: <a href="The-Halfcomplex_002dformat-DFT.html#The-Halfcomplex_002dformat-DFT" accesskey="p" rel="prev">The Halfcomplex-format DFT</a>, Up: <a href="More-DFTs-of-Real-Data.html#More-DFTs-of-Real-Data" accesskey="u" rel="up">More DFTs of Real Data</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html#Concept-Index" title="Index" rel="index">Index</a>]</p> | 
| Chris@42 | 76 </div> | 
| Chris@42 | 77 <hr> | 
| Chris@42 | 78 <a name="Real-even_002fodd-DFTs-_0028cosine_002fsine-transforms_0029-1"></a> | 
| Chris@42 | 79 <h4 class="subsection">2.5.2 Real even/odd DFTs (cosine/sine transforms)</h4> | 
| Chris@42 | 80 | 
| Chris@42 | 81 <p>The Fourier transform of a real-even function <em>f(-x) = f(x)</em> is | 
| Chris@42 | 82 real-even, and <em>i</em> times the Fourier transform of a real-odd | 
| Chris@42 | 83 function <em>f(-x) = -f(x)</em> is real-odd.  Similar results hold for a | 
| Chris@42 | 84 discrete Fourier transform, and thus for these symmetries the need for | 
| Chris@42 | 85 complex inputs/outputs is entirely eliminated.  Moreover, one gains a | 
| Chris@42 | 86 factor of two in speed/space from the fact that the data are real, and | 
| Chris@42 | 87 an additional factor of two from the even/odd symmetry: only the | 
| Chris@42 | 88 non-redundant (first) half of the array need be stored.  The result is | 
| Chris@42 | 89 the real-even DFT (<em>REDFT</em>) and the real-odd DFT (<em>RODFT</em>), also | 
| Chris@42 | 90 known as the discrete cosine and sine transforms (<em>DCT</em> and | 
| Chris@42 | 91 <em>DST</em>), respectively. | 
| Chris@42 | 92 <a name="index-real_002deven-DFT"></a> | 
| Chris@42 | 93 <a name="index-REDFT"></a> | 
| Chris@42 | 94 <a name="index-real_002dodd-DFT"></a> | 
| Chris@42 | 95 <a name="index-RODFT"></a> | 
| Chris@42 | 96 <a name="index-discrete-cosine-transform"></a> | 
| Chris@42 | 97 <a name="index-DCT"></a> | 
| Chris@42 | 98 <a name="index-discrete-sine-transform"></a> | 
| Chris@42 | 99 <a name="index-DST"></a> | 
| Chris@42 | 100 </p> | 
| Chris@42 | 101 | 
| Chris@42 | 102 <p>(In this section, we describe the 1d transforms; multi-dimensional | 
| Chris@42 | 103 transforms are just a separable product of these transforms operating | 
| Chris@42 | 104 along each dimension.) | 
| Chris@42 | 105 </p> | 
| Chris@42 | 106 <p>Because of the discrete sampling, one has an additional choice: is the | 
| Chris@42 | 107 data even/odd around a sampling point, or around the point halfway | 
| Chris@42 | 108 between two samples?  The latter corresponds to <em>shifting</em> the | 
| Chris@42 | 109 samples by <em>half</em> an interval, and gives rise to several transform | 
| Chris@42 | 110 variants denoted by REDFT<em>ab</em> and RODFT<em>ab</em>: <em>a</em> and | 
| Chris@42 | 111 <em>b</em> are <em>0</em> or <em>1</em>, and indicate whether the input | 
| Chris@42 | 112 (<em>a</em>) and/or output (<em>b</em>) are shifted by half a sample | 
| Chris@42 | 113 (<em>1</em> means it is shifted).  These are also known as types I-IV of | 
| Chris@42 | 114 the DCT and DST, and all four types are supported by FFTW’s r2r | 
| Chris@42 | 115 interface.<a name="DOCF3" href="#FOOT3"><sup>3</sup></a> | 
| Chris@42 | 116 </p> | 
| Chris@42 | 117 <p>The r2r kinds for the various REDFT and RODFT types supported by FFTW, | 
| Chris@42 | 118 along with the boundary conditions at both ends of the <em>input</em> | 
| Chris@42 | 119 array (<code>n</code> real numbers <code>in[j=0..n-1]</code>), are: | 
| Chris@42 | 120 </p> | 
| Chris@42 | 121 <ul> | 
| Chris@42 | 122 <li> <code>FFTW_REDFT00</code> (DCT-I): even around <em>j=0</em> and even around <em>j=n-1</em>. | 
| Chris@42 | 123 <a name="index-FFTW_005fREDFT00"></a> | 
| Chris@42 | 124 | 
| Chris@42 | 125 </li><li> <code>FFTW_REDFT10</code> (DCT-II, “the” DCT): even around <em>j=-0.5</em> and even around <em>j=n-0.5</em>. | 
| Chris@42 | 126 <a name="index-FFTW_005fREDFT10"></a> | 
| Chris@42 | 127 | 
| Chris@42 | 128 </li><li> <code>FFTW_REDFT01</code> (DCT-III, “the” IDCT): even around <em>j=0</em> and odd around <em>j=n</em>. | 
| Chris@42 | 129 <a name="index-FFTW_005fREDFT01"></a> | 
| Chris@42 | 130 <a name="index-IDCT"></a> | 
| Chris@42 | 131 | 
| Chris@42 | 132 </li><li> <code>FFTW_REDFT11</code> (DCT-IV): even around <em>j=-0.5</em> and odd around <em>j=n-0.5</em>. | 
| Chris@42 | 133 <a name="index-FFTW_005fREDFT11"></a> | 
| Chris@42 | 134 | 
| Chris@42 | 135 </li><li> <code>FFTW_RODFT00</code> (DST-I): odd around <em>j=-1</em> and odd around <em>j=n</em>. | 
| Chris@42 | 136 <a name="index-FFTW_005fRODFT00"></a> | 
| Chris@42 | 137 | 
| Chris@42 | 138 </li><li> <code>FFTW_RODFT10</code> (DST-II): odd around <em>j=-0.5</em> and odd around <em>j=n-0.5</em>. | 
| Chris@42 | 139 <a name="index-FFTW_005fRODFT10"></a> | 
| Chris@42 | 140 | 
| Chris@42 | 141 </li><li> <code>FFTW_RODFT01</code> (DST-III): odd around <em>j=-1</em> and even around <em>j=n-1</em>. | 
| Chris@42 | 142 <a name="index-FFTW_005fRODFT01"></a> | 
| Chris@42 | 143 | 
| Chris@42 | 144 </li><li> <code>FFTW_RODFT11</code> (DST-IV): odd around <em>j=-0.5</em> and even around <em>j=n-0.5</em>. | 
| Chris@42 | 145 <a name="index-FFTW_005fRODFT11"></a> | 
| Chris@42 | 146 | 
| Chris@42 | 147 </li></ul> | 
| Chris@42 | 148 | 
| Chris@42 | 149 <p>Note that these symmetries apply to the “logical” array being | 
| Chris@42 | 150 transformed; <strong>there are no constraints on your physical input | 
| Chris@42 | 151 data</strong>.  So, for example, if you specify a size-5 REDFT00 (DCT-I) of the | 
| Chris@42 | 152 data <em>abcde</em>, it corresponds to the DFT of the logical even array | 
| Chris@42 | 153 <em>abcdedcb</em> of size 8.  A size-4 REDFT10 (DCT-II) of the data | 
| Chris@42 | 154 <em>abcd</em> corresponds to the size-8 logical DFT of the even array | 
| Chris@42 | 155 <em>abcddcba</em>, shifted by half a sample. | 
| Chris@42 | 156 </p> | 
| Chris@42 | 157 <p>All of these transforms are invertible.  The inverse of R*DFT00 is | 
| Chris@42 | 158 R*DFT00; of R*DFT10 is R*DFT01 and vice versa (these are often called | 
| Chris@42 | 159 simply “the” DCT and IDCT, respectively); and of R*DFT11 is R*DFT11. | 
| Chris@42 | 160 However, the transforms computed by FFTW are unnormalized, exactly | 
| Chris@42 | 161 like the corresponding real and complex DFTs, so computing a transform | 
| Chris@42 | 162 followed by its inverse yields the original array scaled by <em>N</em>, | 
| Chris@42 | 163 where <em>N</em> is the <em>logical</em> DFT size.  For REDFT00, | 
| Chris@42 | 164 <em>N=2(n-1)</em>; for RODFT00, <em>N=2(n+1)</em>; otherwise, <em>N=2n</em>. | 
| Chris@42 | 165 <a name="index-normalization-3"></a> | 
| Chris@42 | 166 <a name="index-IDCT-1"></a> | 
| Chris@42 | 167 </p> | 
| Chris@42 | 168 | 
| Chris@42 | 169 <p>Note that the boundary conditions of the transform output array are | 
| Chris@42 | 170 given by the input boundary conditions of the inverse transform. | 
| Chris@42 | 171 Thus, the above transforms are all inequivalent in terms of | 
| Chris@42 | 172 input/output boundary conditions, even neglecting the 0.5 shift | 
| Chris@42 | 173 difference. | 
| Chris@42 | 174 </p> | 
| Chris@42 | 175 <p>FFTW is most efficient when <em>N</em> is a product of small factors; note | 
| Chris@42 | 176 that this <em>differs</em> from the factorization of the physical size | 
| Chris@42 | 177 <code>n</code> for REDFT00 and RODFT00!  There is another oddity: <code>n=1</code> | 
| Chris@42 | 178 REDFT00 transforms correspond to <em>N=0</em>, and so are <em>not | 
| Chris@42 | 179 defined</em> (the planner will return <code>NULL</code>).  Otherwise, any positive | 
| Chris@42 | 180 <code>n</code> is supported. | 
| Chris@42 | 181 </p> | 
| Chris@42 | 182 <p>For the precise mathematical definitions of these transforms as used by | 
| Chris@42 | 183 FFTW, see <a href="What-FFTW-Really-Computes.html#What-FFTW-Really-Computes">What FFTW Really Computes</a>.  (For people accustomed to | 
| Chris@42 | 184 the DCT/DST, FFTW’s definitions have a coefficient of <em>2</em> in front | 
| Chris@42 | 185 of the cos/sin functions so that they correspond precisely to an | 
| Chris@42 | 186 even/odd DFT of size <em>N</em>.  Some authors also include additional | 
| Chris@42 | 187 multiplicative factors of | 
| Chris@42 | 188 √2for selected inputs and outputs; this makes | 
| Chris@42 | 189 the transform orthogonal, but sacrifices the direct equivalence to a | 
| Chris@42 | 190 symmetric DFT.) | 
| Chris@42 | 191 </p> | 
| Chris@42 | 192 <a name="Which-type-do-you-need_003f"></a> | 
| Chris@42 | 193 <h4 class="subsubheading">Which type do you need?</h4> | 
| Chris@42 | 194 | 
| Chris@42 | 195 <p>Since the required flavor of even/odd DFT depends upon your problem, | 
| Chris@42 | 196 you are the best judge of this choice, but we can make a few comments | 
| Chris@42 | 197 on relative efficiency to help you in your selection.  In particular, | 
| Chris@42 | 198 R*DFT01 and R*DFT10 tend to be slightly faster than R*DFT11 | 
| Chris@42 | 199 (especially for odd sizes), while the R*DFT00 transforms are sometimes | 
| Chris@42 | 200 significantly slower (especially for even sizes).<a name="DOCF4" href="#FOOT4"><sup>4</sup></a> | 
| Chris@42 | 201 </p> | 
| Chris@42 | 202 <p>Thus, if only the boundary conditions on the transform inputs are | 
| Chris@42 | 203 specified, we generally recommend R*DFT10 over R*DFT00 and R*DFT01 over | 
| Chris@42 | 204 R*DFT11 (unless the half-sample shift or the self-inverse property is | 
| Chris@42 | 205 significant for your problem). | 
| Chris@42 | 206 </p> | 
| Chris@42 | 207 <p>If performance is important to you and you are using only small sizes | 
| Chris@42 | 208 (say <em>n<200</em>), e.g. for multi-dimensional transforms, then you | 
| Chris@42 | 209 might consider generating hard-coded transforms of those sizes and types | 
| Chris@42 | 210 that you are interested in (see <a href="Generating-your-own-code.html#Generating-your-own-code">Generating your own code</a>). | 
| Chris@42 | 211 </p> | 
| Chris@42 | 212 <p>We are interested in hearing what types of symmetric transforms you find | 
| Chris@42 | 213 most useful. | 
| Chris@42 | 214 </p> | 
| Chris@42 | 215 <div class="footnote"> | 
| Chris@42 | 216 <hr> | 
| Chris@42 | 217 <h4 class="footnotes-heading">Footnotes</h4> | 
| Chris@42 | 218 | 
| Chris@42 | 219 <h3><a name="FOOT3" href="#DOCF3">(3)</a></h3> | 
| Chris@42 | 220 <p>There are also type V-VIII transforms, which | 
| Chris@42 | 221 correspond to a logical DFT of <em>odd</em> size <em>N</em>, independent of | 
| Chris@42 | 222 whether the physical size <code>n</code> is odd, but we do not support these | 
| Chris@42 | 223 variants.</p> | 
| Chris@42 | 224 <h3><a name="FOOT4" href="#DOCF4">(4)</a></h3> | 
| Chris@42 | 225 <p>R*DFT00 is | 
| Chris@42 | 226 sometimes slower in FFTW because we discovered that the standard | 
| Chris@42 | 227 algorithm for computing this by a pre/post-processed real DFT—the | 
| Chris@42 | 228 algorithm used in FFTPACK, Numerical Recipes, and other sources for | 
| Chris@42 | 229 decades now—has serious numerical problems: it already loses several | 
| Chris@42 | 230 decimal places of accuracy for 16k sizes.  There seem to be only two | 
| Chris@42 | 231 alternatives in the literature that do not suffer similarly: a | 
| Chris@42 | 232 recursive decomposition into smaller DCTs, which would require a large | 
| Chris@42 | 233 set of codelets for efficiency and generality, or sacrificing a factor of | 
| Chris@42 | 234 2 | 
| Chris@42 | 235 in speed to use a real DFT of twice the size.  We currently | 
| Chris@42 | 236 employ the latter technique for general <em>n</em>, as well as a limited | 
| Chris@42 | 237 form of the former method: a split-radix decomposition when <em>n</em> | 
| Chris@42 | 238 is odd (<em>N</em> a multiple of 4).  For <em>N</em> containing many | 
| Chris@42 | 239 factors of 2, the split-radix method seems to recover most of the | 
| Chris@42 | 240 speed of the standard algorithm without the accuracy tradeoff.</p> | 
| Chris@42 | 241 </div> | 
| Chris@42 | 242 <hr> | 
| Chris@42 | 243 <div class="header"> | 
| Chris@42 | 244 <p> | 
| Chris@42 | 245 Next: <a href="The-Discrete-Hartley-Transform.html#The-Discrete-Hartley-Transform" accesskey="n" rel="next">The Discrete Hartley Transform</a>, Previous: <a href="The-Halfcomplex_002dformat-DFT.html#The-Halfcomplex_002dformat-DFT" accesskey="p" rel="prev">The Halfcomplex-format DFT</a>, Up: <a href="More-DFTs-of-Real-Data.html#More-DFTs-of-Real-Data" accesskey="u" rel="up">More DFTs of Real Data</a>   [<a href="index.html#SEC_Contents" title="Table of contents" rel="contents">Contents</a>][<a href="Concept-Index.html#Concept-Index" title="Index" rel="index">Index</a>]</p> | 
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