There is a good discussion of the future of 64 bit python on the
pythonmac list.
Also, Apple seems to be indicating that 10.6 will only support Intel64
-- so some day this will all be default!
by the way, sys.maxint is another easy way to check, without needing numpy.
-Chris
--
Christop
On Thu, Jun 5, 2008 at 10:16 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> How can that lead to instability? If the last half-million values are
> small then they won't have a big impact on the mean even if they are
> ignored. The variance is a mean too (of the squares), so it should be
> stable t
On Thu, Jun 5, 2008 at 7:55 PM, Alan McIntyre <[EMAIL PROTECTED]>
wrote:
> On Thu, Jun 5, 2008 at 9:06 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> > On Thu, Jun 5, 2008 at 4:54 PM, Christopher Marshall
> > Are you worried that the mean might overflow on the intermediate sum?
>
> I suspect (but
On Thu, Jun 5, 2008 at 6:55 PM, Alan McIntyre <[EMAIL PROTECTED]> wrote:
> On Thu, Jun 5, 2008 at 9:06 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>> On Thu, Jun 5, 2008 at 4:54 PM, Christopher Marshall
>> Are you worried that the mean might overflow on the intermediate sum?
>
> I suspect (but ple
On Thu, Jun 5, 2008 at 9:06 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> On Thu, Jun 5, 2008 at 4:54 PM, Christopher Marshall
> Are you worried that the mean might overflow on the intermediate sum?
I suspect (but please correct me if I'm wrong, Christopher) he's
asking whether there's cases wher
On Thu, Jun 5, 2008 at 4:54 PM, Christopher Marshall
<[EMAIL PROTECTED]> wrote:
> I will be calculating the mean and variance of a vector with millions of
> elements.
>
> I was wondering how well numpy's mean and variance functions handle the
> numerical stability of such a calculation.
How's th
I will be calculating the mean and variance of a vector with millions of
elements.
I was wondering how well numpy's mean and variance functions handle the
numerical stability of such a calculation.
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Charles Doutriaux wrote:
> Arthur
> I'm forwarding your question to the numpy list, I'm hoping somebody
> there will be able to help you with that.
>
Try using numpy.oldnumeric.load(f).
Or, just replace in the pickle stream:
Numeric --> numpy.oldnumeric
It should work fine. If you have pro
Arthur
I'm forwarding your question to the numpy list, I'm hoping somebody
there will be able to help you with that.
C.
Arthur M. Greene wrote:
> Hi All,
>
> This does not involve the CDAT-5 code, but rather files pickled under
> earlier versions of CDAT. These files store the variable type alo
Michael Abshoff wrote:
> Jonathan Wright wrote:
>>
>> ...etc. We needed this for generating the .so library file name for
>> ctypes
>
> Can you elaborate on this a little?
The "we" refered to another project (not numpy) where we needed to
distinguish 32 bit from 64 bit platforms. We have code f
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