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7.2 Reversing array dimensions

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A minor annoyance in calling FFTW from Fortran is that FFTW's array Chris@10: dimensions are defined in the C convention (row-major order), while Chris@10: Fortran's array dimensions are the opposite convention (column-major Chris@10: order). See Multi-dimensional Array Format. This is just a Chris@10: bookkeeping difference, with no effect on performance. The only Chris@10: consequence of this is that, whenever you create an FFTW plan for a Chris@10: multi-dimensional transform, you must always reverse the Chris@10: ordering of the dimensions. Chris@10: Chris@10:

For example, consider the three-dimensional (L × M × N) arrays: Chris@10: Chris@10:

       complex(C_DOUBLE_COMPLEX), dimension(L,M,N) :: in, out
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To plan a DFT for these arrays using fftw_plan_dft_3d, you could do: Chris@10: Chris@10:

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       plan = fftw_plan_dft_3d(N,M,L, in,out, FFTW_FORWARD,FFTW_ESTIMATE)
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That is, from FFTW's perspective this is a N × M × L array. Chris@10: No data transposition need occur, as this is only Chris@10: notation. Similarly, to use the more generic routine Chris@10: fftw_plan_dft with the same arrays, you could do: Chris@10: Chris@10:

       integer(C_INT), dimension(3) :: n = [N,M,L]
Chris@10:        plan = fftw_plan_dft_3d(3, n, in,out, FFTW_FORWARD,FFTW_ESTIMATE)
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Note, by the way, that this is different from the legacy Fortran Chris@10: interface (see Fortran-interface routines), which automatically Chris@10: reverses the order of the array dimension for you. Here, you are Chris@10: calling the C interface directly, so there is no “translation” layer. Chris@10: Chris@10:

An important thing to keep in mind is the implication of this for Chris@10: multidimensional real-to-complex transforms (see Multi-Dimensional DFTs of Real Data). In C, a multidimensional real-to-complex DFT Chris@10: chops the last dimension roughly in half (N × M × L real input Chris@10: goes to N × M × L/2+1 complex output). In Fortran, because Chris@10: the array dimension notation is reversed, the first dimension of Chris@10: the complex data is chopped roughly in half. For example consider the Chris@10: ‘r2c’ transform of L × M × N real input in Fortran: Chris@10: Chris@10:

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       type(C_PTR) :: plan
Chris@10:        real(C_DOUBLE), dimension(L,M,N) :: in
Chris@10:        complex(C_DOUBLE_COMPLEX), dimension(L/2+1,M,N) :: out
Chris@10:        plan = fftw_plan_dft_r2c_3d(N,M,L, in,out, FFTW_ESTIMATE)
Chris@10:        ...
Chris@10:        call fftw_execute_dft_r2c(plan, in, out)
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Alternatively, for an in-place r2c transform, as described in the C Chris@10: documentation we must pad the first dimension of the Chris@10: real input with an extra two entries (which are ignored by FFTW) so as Chris@10: to leave enough space for the complex output. The input is Chris@10: allocated as a 2[L/2+1] × M × N array, even though only Chris@10: L × M × N of it is actually used. In this example, we will Chris@10: allocate the array as a pointer type, using ‘fftw_alloc’ to Chris@10: ensure aligned memory for maximum performance (see Allocating aligned memory in Fortran); this also makes it easy to reference the Chris@10: same memory as both a real array and a complex array. Chris@10: Chris@10:

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       real(C_DOUBLE), pointer :: in(:,:,:)
Chris@10:        complex(C_DOUBLE_COMPLEX), pointer :: out(:,:,:)
Chris@10:        type(C_PTR) :: plan, data
Chris@10:        data = fftw_alloc_complex(int((L/2+1) * M * N, C_SIZE_T))
Chris@10:        call c_f_pointer(data, in, [2*(L/2+1),M,N])
Chris@10:        call c_f_pointer(data, out, [L/2+1,M,N])
Chris@10:        plan = fftw_plan_dft_r2c_3d(N,M,L, in,out, FFTW_ESTIMATE)
Chris@10:        ...
Chris@10:        call fftw_execute_dft_r2c(plan, in, out)
Chris@10:        ...
Chris@10:        call fftw_destroy_plan(plan)
Chris@10:        call fftw_free(data)
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