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
On 16 Jul 2013 11:35, Arink Verma arinkve...@gmail.com 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
Hi,
On Tue, Jul 16, 2013 at 11:55 AM, Nathaniel Smith n...@pobox.com wrote:
On Tue, Jul 16, 2013 at 2:34 PM, Arink Verma arinkve...@gmail.com 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
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
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
On Tue, Jul 16, 2013 at 4:51 PM, Anthony Scopatz scop...@gmail.com 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
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 irv...@naml.us wrote:
On Tue, Jul 16, 2013 at 4:51 PM, Anthony Scopatz scop...@gmail.com
wrote:
Hi Geoffrey,
Not to toot my
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
On Tue, Jul 16, 2013 at 7:15 PM, Geoffrey Irving irv...@naml.us wrote:
On Tue, Jul 16, 2013 at 4:51 PM, Anthony Scopatz scop...@gmail.com
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
