Hi All,
For scalar operations Numpy first try to extract the underlying C value
from a Python Integers. It causes bottleneck because it first converts the
Python scalar into its matching NumPy scalar (e.g. PyLong - int32) and
then it extracts the C value from the NumPy scalar.
Its quicker to
(PyLongScalarObject) need allocation in case
of scalar arrays. Instead, can we just some how convert/cast PyArrayObject
to
PyLongScalarObject.??
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Arink Verma
www.arinkverma.in
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= np.asarray(2.0);')
Arink Verma
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at 4:29 PM, Arink Verma arinkve...@gmail.com wrote:
Hi Nathaniel
It's a probabilistic sampling profiler, so if it doesn't have enough
samples then it can miss things. 227 samples is way way too low. You
need to
run the profiled code for longer (a few seconds at least), and if
that's
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I hardly found, any thing to improve and correct.. not even typo in docs?
Where we need to avoid the version checks?
On Fri, May 3, 2013 at 10:52 PM, Charles R Harris charlesr.har...@gmail.com
wrote:
On Thu, May 2, 2013 at 6:47 PM, josef.p...@gmail.com wrote:
On Thu, May 2, 2013 at 6:30
I have created a new PR, have removed one irrelevant version check.
https://github.com/numpy/numpy/pull/3304/files
On Fri, May 3, 2013 at 11:29 PM, Arink Verma arinkve...@iitrpr.ac.inwrote:
I hardly found, any thing to improve and correct.. not even typo in docs?
Where we need to avoid
at 10:12 AM, David Cournapeau courn...@gmail.comwrote:
On Thu, May 2, 2013 at 5:25 AM, Arink Verma arinkve...@iitrpr.ac.in
wrote:
@Raul
I will pull new version, and try to include that also.
What is wrong with macros for inline function?
Yes, time for ufunc is reduced to almost half
that.
Does the merge has to be related to gsoc project, or any other improvement
can be consider?
On Thu, May 2, 2013 at 6:44 PM, Nathaniel Smith n...@pobox.com wrote:
On Thu, May 2, 2013 at 6:26 AM, Arink Verma arinkve...@iitrpr.ac.in
wrote:
Yes, we need to ensure that..
Code generator can
have not gotten around to it, but it
would be nice if you jump on that boat.
On the has lookup table, haven't looked at the implementation but the
speed up is remarkable.
Cheers !
Raul
On 30/04/2013 8:26 PM, Arink Verma wrote:
Hi all!
I have written my application[1] for *Performance
Hi all!
I have written my application[1] for *Performance parity between numpy
arrays and Python scalars[2]. *It would be a great help if you view it.
Does it look achievable and deliverable according to the project.
[1]
Hello everyone
I am Arink, computer science student and open source enthusiastic. This
year I am interested to work on project Performance parity between numpy
arrays and Python scalars[1].
I tried to adobt rald's work on numpy1.7[2] (which was done for numpy1.6
[3]).
Till now by avoiding
a) the
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