On Thu, 2008-06-05 at 08:24 +0200, Michael Abshoff wrote:
I am not what I would call familiar with numpy internals, so is there a
magic thing I can do to make numpy aware that ctypes exists?
I don't think any magic is needed. As long as importing ctypes works
from the python you used to
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 for picking
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 along
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
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 this for
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 please
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 please
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 too.
