[Numpy-discussion] numpy ndarray questions
Mon Jan 26 22:28:43 CST 2009
> On Tue, 2009-01-27 at 12:49 +0900, David Cournapeau wrote:
>> Jochen wrote:
>>> Hi all,
>>> I just wrote ctypes bindings to fftw3 (see
>>> for the post to scipy).
>>> Now I have a couple of numpy related questions:
>>> In order to be able to use simd instructions I
>>> create an ndarray subclass, which uses fftw_malloc to allocate the
>>> memory and fftw_free to free the memory when the array is deleted. This
>>> works fine for inplace operations however if someone does something like
>>> a = fftw3.AlignedArray(1024,complex)
>>> a = a+1
>>> a.ctypes.data points to a different memory location (this is actually an
>>> even bigger problem when executing fftw plans), however
>>> type(a) still gives me <class 'fftw3.planning.AlignedArray'>.
>> I can't comment about subclassing ndarrays, but I can give you a hint
>> about aligned allocator problem: you could maintain two list of cached
>> plans, automatically detect whether your arrays are aligned or not, and
>> use the appropriate list of plans; one list is for aligned arrays, one
>> for unaligned. Before removing support for fftw, I played with some C++
>> code to do exactly that. You can tell fftw to create plans for unaligned
>> arrays by using FFTW_UNALIGNED flag:
> Hi David,
> I have actually kept more closely to the fftw way of doing things, i.e.
> I create a plan python object from two arrays, it also stores the two
> arrays to prevent someone to delete the original arrays and then
> executing the plan.
I am not sure I follow you when you say the "fftw way": you can avoid
having to store the arrays altogether while still using fftw plans,
there is nothing "unfftw" about using plans that way. I think trying to
guarantee that your arrays data buffers won't change is more complicated.
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