[SciPy-User] understanding machine precision
Tue Dec 14 13:05:30 CST 2010
On Tue, Dec 14, 2010 at 1:47 PM, Robert Kern <email@example.com> wrote:
> On Tue, Dec 14, 2010 at 12:42, Keith Goodman <firstname.lastname@example.org> wrote:
>> On Tue, Dec 14, 2010 at 9:42 AM, <email@example.com> wrote:
>>> I thought that we get deterministic results, with identical machine
>>> precision errors, but I get (with some random a0, b0)
>>>>>> for i in range(5):
>>> x = scipy.linalg.lstsq(a0,b0)
>>> x2 = scipy.linalg.lstsq(a0,b0)
>>> print np.max(np.abs(x-x2))
>> I've started a couple of threads in the past on repeatability. Most of
>> the discussion ends up being about ATLAS. I suggest repeating the test
>> without ATLAS.
> On OS X with numpy linked against the builtin Accelerate.framework
> (which is based off of ATLAS), I get the same result every time.
Windows 7, numpy 64 bit mkl binaries from Christoph, I get 0.0 every time.
Using 32 bit mkl binaries in IPython interpreter and from the command
line I do not get reproducible results. If I do astype(float32) I
seem to get 0.0 most of the times but more infrequently get something
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