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d@0 3 <title>Multi-Dimensional DFTs of Real Data - FFTW 3.2.1</title>
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d@0 57
d@0 58 <h3 class="section">2.4 Multi-Dimensional DFTs of Real Data</h3>
d@0 59
d@0 60 <p>Multi-dimensional DFTs of real data use the following planner routines:
d@0 61
d@0 62 <pre class="example"> fftw_plan fftw_plan_dft_r2c_2d(int n0, int n1,
d@0 63 double *in, fftw_complex *out,
d@0 64 unsigned flags);
d@0 65 fftw_plan fftw_plan_dft_r2c_3d(int n0, int n1, int n2,
d@0 66 double *in, fftw_complex *out,
d@0 67 unsigned flags);
d@0 68 fftw_plan fftw_plan_dft_r2c(int rank, const int *n,
d@0 69 double *in, fftw_complex *out,
d@0 70 unsigned flags);
d@0 71 </pre>
d@0 72 <p><a name="index-fftw_005fplan_005fdft_005fr2c_005f2d-58"></a><a name="index-fftw_005fplan_005fdft_005fr2c_005f3d-59"></a><a name="index-fftw_005fplan_005fdft_005fr2c-60"></a>
d@0 73 as well as the corresponding <code>c2r</code> routines with the input/output
d@0 74 types swapped. These routines work similarly to their complex
d@0 75 analogues, except for the fact that here the complex output array is cut
d@0 76 roughly in half and the real array requires padding for in-place
d@0 77 transforms (as in 1d, above).
d@0 78
d@0 79 <p>As before, <code>n</code> is the logical size of the array, and the
d@0 80 consequences of this on the the format of the complex arrays deserve
d@0 81 careful attention.
d@0 82 <a name="index-r2c_002fc2r-multi_002ddimensional-array-format-61"></a>Suppose that the real data has dimensions 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> (in row-major order).
d@0 83 Then, after an r2c transform, the output is 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>/2 + 1) array of
d@0 84 <code>fftw_complex</code> values in row-major order, corresponding to slightly
d@0 85 over half of the output of the corresponding complex DFT. (The division
d@0 86 is rounded down.) The ordering of the data is otherwise exactly the
d@0 87 same as in the complex-DFT case.
d@0 88
d@0 89 <p>Since the complex data is slightly larger than the real data, some
d@0 90 complications arise for in-place transforms. In this case, the final
d@0 91 dimension of the real data must be padded with extra values to
d@0 92 accommodate the size of the complex data&mdash;two values if the last
d@0 93 dimension is even and one if it is odd.
d@0 94 <a name="index-padding-62"></a>That is, the last dimension of the real data must physically contain
d@0 95 2 * (n<sub>d-1</sub>/2+1)<code>double</code> values (exactly enough to hold the complex data).
d@0 96 This physical array size does not, however, change the <em>logical</em>
d@0 97 array size&mdash;only
d@0 98 n<sub>d-1</sub>values are actually stored in the last dimension, and
d@0 99 n<sub>d-1</sub>is the last dimension passed to the plan-creation routine.
d@0 100
d@0 101 <p>For example, consider the transform of a two-dimensional real array of
d@0 102 size <code>n0</code> by <code>n1</code>. The output of the r2c transform is a
d@0 103 two-dimensional complex array of size <code>n0</code> by <code>n1/2+1</code>, where
d@0 104 the <code>y</code> dimension has been cut nearly in half because of
d@0 105 redundancies in the output. Because <code>fftw_complex</code> is twice the
d@0 106 size of <code>double</code>, the output array is slightly bigger than the
d@0 107 input array. Thus, if we want to compute the transform in place, we
d@0 108 must <em>pad</em> the input array so that it is of size <code>n0</code> by
d@0 109 <code>2*(n1/2+1)</code>. If <code>n1</code> is even, then there are two padding
d@0 110 elements at the end of each row (which need not be initialized, as they
d@0 111 are only used for output).
d@0 112
d@0 113 <p>The following illustration depicts the input and output arrays just
d@0 114 described, for both the out-of-place and in-place transforms (with the
d@0 115 arrows indicating consecutive memory locations):
d@0 116
d@0 117 <div class="block-image"><img src="rfftwnd.png" alt="rfftwnd.png"></div>
d@0 118
d@0 119 <p>These transforms are unnormalized, so an r2c followed by a c2r
d@0 120 transform (or vice versa) will result in the original data scaled by
d@0 121 the number of real data elements&mdash;that is, the product of the
d@0 122 (logical) dimensions of the real data.
d@0 123 <a name="index-normalization-63"></a>
d@0 124 (Because the last dimension is treated specially, if it is equal to
d@0 125 <code>1</code> the transform is <em>not</em> equivalent to a lower-dimensional
d@0 126 r2c/c2r transform. In that case, the last complex dimension also has
d@0 127 size <code>1</code> (<code>=1/2+1</code>), and no advantage is gained over the
d@0 128 complex transforms.)
d@0 129
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