On Fri, Dec 11, 2015, 18:04 David Cournapeau <courn...@gmail.com> wrote:
On Fri, Dec 11, 2015 at 4:22 PM, Anne Archibald <archib...@astron.nl> wrote: Actually, GCC implements 128-bit floats in software and provides them as __float128; there are also quad-precision versions of the usual functions. The Intel compiler provides this as well, I think, but I don't think Microsoft compilers do. A portable quad-precision library might be less painful. The cleanest way to add extended precision to numpy is by adding a C-implemented dtype. This can be done in an extension module; see the quaternion and half-precision modules online. We actually used __float128 dtype as an example of how to create a custom dtype for a numpy C tutorial we did w/ Stefan Van der Walt a few years ago at SciPy. IIRC, one of the issue to make it more than a PoC was that numpy hardcoded things like long double being the higest precision, etc... But that may has been fixed since then. I did some work on numpy's long-double support, partly to better understand what would be needed to make quads work. The main obstacle is, I think, the same: python floats are only 64-bit, and many functions are stuck passing through them. It takes a lot of fiddling to make string conversions work without passing through python floats, for example, and it takes some care to produce scalars of the appropriate type. There are a few places where you'd want to modify the guts of numpy if you had a higher precision available than long doubles. Anne
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