On Tue, Jul 16, 2013 at 7:15 PM, Geoffrey Irving wrote:
> On Tue, Jul 16, 2013 at 4:51 PM, Anthony Scopatz
> wrote:
> > Hi Geoffrey,
> >
> > Not to toot my own horn here too much, but you really should have a look
> at
> > xdress (http://xdress.org/ and https://github.com/xdress/xdress).
> XDre
and to put so far reported findings into some kind of automated form,
please welcome
http://www.onerussian.com/tmp/numpy-vbench/#benchmarks-performance-analysis
This is based on a simple 1-way anova of last 10 commits and some point
in the past where 10 other commits had smallest timing and were
Hey Geoffrey,
Let's definitely take this off (this) list. The discussion could get
involved :).
Be Well
Anthony
On Tue, Jul 16, 2013 at 7:15 PM, Geoffrey Irving wrote:
> On Tue, Jul 16, 2013 at 4:51 PM, Anthony Scopatz
> wrote:
> > Hi Geoffrey,
> >
> > Not to toot my own horn here too much,
On Tue, Jul 16, 2013 at 4:51 PM, Anthony Scopatz wrote:
> Hi Geoffrey,
>
> Not to toot my own horn here too much, but you really should have a look at
> xdress (http://xdress.org/ and https://github.com/xdress/xdress). XDress
> will generate a wrapper of the Force class for you and then also crea
Hi Geoffrey,
Not to toot my own horn here too much, but you really should have a look at
xdress (http://xdress.org/ and https://github.com/xdress/xdress). XDress
will generate a wrapper of the Force class for you and then also create a
custom numpy dtype for this class. In this way, you could ge
Is there a standard way of creating an object array restricted to a
particular python type? I want a safe way of sending arrays of
objects back and forth between Python and C++, and it'd be great if I
could use numpy arrays on the Python side instead of creating a new
type.
For example, I might h
Hi,
On Tue, Jul 16, 2013 at 11:55 AM, Nathaniel Smith wrote:
> On Tue, Jul 16, 2013 at 2:34 PM, Arink Verma wrote:
>
>> >Each ndarray does two mallocs, for the obj and buffer. These could be
>> combined into 1 - just allocate the total size and do some pointer
>> >arithmetic, then set OWNDATA
On 16 Jul 2013 11:35, "Arink Verma" wrote:
>
> Hi,
>
> I am working on performance parity between numpy scalar/small array and
python array as GSOC mentored By Charles.
>
> Currently I am looking at PyArray_Return, which allocate separate memory
just for scalar return. Unlike python which allocate
Hi,
I am working on performance parity between numpy scalar/small array and
python array as GSOC mentored By Charles.
Currently I am looking at PyArray_Return, which allocate separate memory
just for scalar return. Unlike python which allocate memory once for
returning result of scalar operatio
