Good things to know. On Tue, Feb 1, 2011 at 1:10 PM, Sturla Molden <stu...@molden.no> wrote:
> Den 01.02.2011 20:50, skrev John Salvatier: > > I am curious: why you recommend against this? Using the C-API through > > cython seems more attractive than using the Cython-specific numpy > > features since they need a specific number of dimensions (and I don't > > think they broadcast) and don't seem that much easier. Are there > > hidden disadvantages to using the C-API? Have I misunderstood something? > > There is one more thing which should be mentioned: > > If the algorithm needs to pass an ndarray to a function, this might > cause excessive reference counting and boxing/unboxing with Cython. It > gets even worse if we want to pass a subarray view of an ndarray, for > which Cython will create a new array object. Cython will only play > nicely with NumPy arrays if there are no function calls. If there are > function calls, we must give up ndarrays and use C pointers directly. > Users who don't know the internals of Cython might think that using an > ndarray as a function argument is a good idea, or even use slicing to > create a view of a subarray. Cython does not forbid this, but it hurts > performance immensely. In the NumPy C API we can pass a pointer to a > PyArrayObject, adding no overhead beyond the function call. But > subarrays are as primitive as in Cython. This makes anything but trivial > "computational kernels" painful in Cython or the NumPy C API. > > Personally I avoid both Cython and the NumPy C API for this reason. > There is a very nive language called Fortran 95, for which the compiler > knows how to work with arrays. For those that don't use Fortran 95, > there are libraries for C++ such as Blitz++. > > > Sturla > > > > _______________________________________________ > NumPy-Discussion mailing list > NumPy-Discussion@scipy.org > http://mail.scipy.org/mailman/listinfo/numpy-discussion >
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