[Numpy-discussion] floating point arithmetic issue

David Cournapeau cournape@gmail....
Fri Jul 30 09:15:28 CDT 2010

2010/7/30 Guillaume Chérel <guillaume.c.cherel@gmail.com>:
>  Hi,
> Thanks for all your answers and the references (and yes, I have to admit
> that I've been a bit lazy with Goldberg's article, though it looks very
> thorough).
> But as numpy is designed for scientific computing, is there no
> implementation of an "exact type"
> (http://floating-point-gui.de/formats/exact/) to avoid floating point
> issues?

I think there is a misunderstanding: the *vast* majority of scientific
computing use floating point. The most commonly used way of doing
"exact" computation is to do it symbolically, which is inapproriate in
most practical cases. Arbitrary precision is also very different from
exact precision - arbitrary precision means you are trading
speed/memory for more precision, but there will still be errors.

I don't really understand the exact problem you are trying to solve,
but since you are approximating something, I am doubtful you need
exact precision, and in that case, floating point as used in numpy
(and every other software doing *numerical* computation) is likely to
be enough.



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