Thanks for the replies.
Robert is right; many numerical operations, particularly complex ones,
generate different values across platforms, and we deal with these by
storing the values from some platform as a reference and using
allclose(), which requires extra work. But many basic operations
generate the same underlying values on IEEE 754-compliant platforms but
don't always format floats consistently (see
http://bugs.python.org/issue1580 for a lengthy discussion on this). My
impression is that Python 2.7 does a better job here, but at this point
a lot of differences also crop up between 2.6 (or less) and 2.7 due to
the changed formatting built into 2.7, and these are the result of
formatting differences; the numbers themselves are identical (in our
experience so far, at any rate). This is a current pain-point which an
exact representation would alleviate.
In response to David, we haven't implemented a separate print; we rely
on the Numpy repr/str for ndarrays and the printoptions that allow some
control over float formatting. I'm basically proposing to add a bit
more control there. And thanks for the info on supported versions of
Python.
Ken
On 12/2/10 8:14 AM, Robert Kern wrote:
> On Wed, Dec 1, 2010 at 13:18, Ken Basye<kbas...@jhu.edu> wrote:
>> Hi Numpy folks,
>> ? ? When working with floats, I prefer to have exact string
>> representations in doctests and other reference-based testing; I find it
>> helps a lot to avoid chasing cross-platform differences that are really
>> about the string conversion rather than about numerical differences.
> Unfortunately, there are still cross-platform numerical differences
> that are real (but are irrelevant to the validity of the code under
> test). Hex-printing for floats only helps a little to make doctests
> useful for numerical code.
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