On Mon, Feb 02, 2009 at 08:01:54AM +0200, Stéfan van der Walt wrote:
> The GzipFile in Python 2.5 does not support the 2nd ("whence")
> argument. The solution may be to use this wrapper from the EffBot:
> http://effbot.org/librarybook/gzip-example-2.py
> In order to "back-port" that functionality.
2009/2/2 Matthew Miller :
> I'd like to log the state of my program as it progresses. Using the
> numpy.save / numpy.load functions on the same filehandle repeatedly works
> very well for this -- but ends up making a file which very quickly grows to
> gigabytes. The data compresses well, though, so
Hi everyone.
I'd like to log the state of my program as it progresses. Using the
numpy.save / numpy.load functions on the same filehandle repeatedly works
very well for this -- but ends up making a file which very quickly grows to
gigabytes. The data compresses well, though, so I thought I'd use P
On Sun, Feb 1, 2009 at 7:33 PM, Pierre GM wrote:
>
> On Feb 1, 2009, at 6:32 PM, Darren Dale wrote:
> >
> >
> > Is there an analog to __array_wrap__ for preprocessing arrays on
> > their way *into* a ufunc? For example, it would be nice if one could
> > do something like:
> >
> > numpy.sin([1,2,3
On Feb 1, 2009, at 6:32 PM, Darren Dale wrote:
>
>
> Is there an analog to __array_wrap__ for preprocessing arrays on
> their way *into* a ufunc? For example, it would be nice if one could
> do something like:
>
> numpy.sin([1,2,3]*arcseconds)
>
> where we have the opportunity to inspect the c
I've been playing with __array_wrap__ to make quantities with units play
well with numpy's ufuncs. For example, __array_wrap__ makes it is possible
to do the following:
>>> numpy.sqrt([1.,4.,9.]*m**2)
array([1.,2.,3.])*m
Is there an analog to __array_wrap__ for preprocessing arrays on their way
*
David Froger gmail.com> writes:
> Hy,My question is about reading Fortran binary file (oh no this question
> again...)
I've posted this before, but I finally got it cleaned up for the Cookbook.
For this purpose I use a subclass of file that has methods for reading
unformatted Fortran data. Se
On Sun, Feb 1, 2009 at 12:24 AM, Robert Kern wrote:
> On Sat, Jan 31, 2009 at 10:30, Sebastian Walter
> wrote:
>> Wouldn't it be nice to have numpy a little more generic?
>> All that would be needed was a little check of the arguments.
>>
>> If I do:
>> numpy.trace(4)
>> shouldn't numpy be smart
Beautiful! That should do the trick. Now let's see how this performs against
the
list comprehension...
Thanks a lot!
Raik
Rick White wrote:
> Here's a technique that works:
>
> Python 2.4.2 (#5, Nov 21 2005, 23:08:11)
> [GCC 4.0.0 20041026 (Apple Computer, Inc. build 4061)] on darwin
> Type "h
