On Fri, Mar 14, 2014 at 1:43 AM, alex argri...@ncsu.edu wrote:
I think everyone who wants fast numpy linalg already connects to
something like OpenBLAS or MKL. When these are not available, numpy
uses its own lapack-lite which is way slower. I don't think you are
going to beat OpenBLAS, so
Thank you Olsen,
My objective was to find out, how many values
are falling under different ranges. ie, find RMS ,5 and then rms between .5
and .8 etc. If there is a speficic python way of handling mask and making
boolean operation with out any doubt, I was
Dear Oslen,
I had a detailed look at the example you send and points I got were below
a = np.arange(-8, 8).reshape((4, 4))
b = ma.masked_array(a, mask=a 0)
Out[33]: b[b4]
masked_array(data = [-- -- -- -- -- -- -- -- 0 1 2 3],
mask = [ True True True
On 2014/03/13 9:09 PM, Sudheer Joseph wrote:
Dear Oslen,
I had a detailed look at the example you send and points I got were below
a = np.arange(-8, 8).reshape((4, 4))
b = ma.masked_array(a, mask=a 0)
Out[33]: b[b4]
masked_array(data = [-- -- -- -- -- -- -- -- 0 1 2 3],
Thank you Eric,
The compress is the option which is gets the correct
numbers.
a = np.arange(-8, 8).reshape((4, 4))
In [67]: b = ma.masked_array(a, mask=a 0)
In [68]: bb=b.compressed()
In [69]: b[b4].size
Out[69]: 12
In [70]:
Am 13.03.2014 um 18:35 schrieb Leo Mao lmao20...@gmail.com:
Hi,
Thanks a lot for your advice, Chuck.
Following your advice, I have modified my draft of proposal. (attachment)
I think it still needs more comments so that I can make it better.
And I found that maybe I can also make some
On Friday, March 14, 2014, Gregor Thalhammer gregor.thalham...@gmail.com
wrote:
Am 13.03.2014 um 18:35 schrieb Leo Mao lmao20...@gmail.com javascript:;
:
Hi,
Thanks a lot for your advice, Chuck.
Following your advice, I have modified my draft of proposal. (attachment)
I think it
Am 14.03.2014 um 11:00 schrieb Eric Moore e...@redtetrahedron.org:
On Friday, March 14, 2014, Gregor Thalhammer gregor.thalham...@gmail.com
wrote:
Am 13.03.2014 um 18:35 schrieb Leo Mao lmao20...@gmail.com:
Hi,
Thanks a lot for your advice, Chuck.
Following your advice, I
Just a comment, supporting a library that is bsd 3 clauses could help
to higly reduce the compilation problem like what we have with blas.
We could just include it in numpy/download it automatically or
whatever to make the install trivial and then we could suppose all
users have it. Deadling with
Announcing HDF5 for Python (h5py) 2.3.0 BETA
The h5py team is happy to announce the availability of h5py 2.3.0 beta. This
beta release will be available for approximately two weeks.
What's h5py?
The h5py package is a Pythonic interface
Hi everyone,
Thanks for your relies!
I think Gregor's uvml package is really a good starting point for me.
I think the actual choice of the library could be made a configurable
option.
Sounds like a good idea? If the implementations are very similar, maybe I
can implement multiple libraries
On Fri, Mar 14, 2014 at 4:33 PM, Leo Mao lmao20...@gmail.com wrote:
Yeppp is bsd 3 clauses so I think Yeppp is really a good choice.
Is there a list of licenses which can be added into numpy without pain? (how
about LGPL3 ?)
No, just BSD and its rough equivalents like the Expat license.
--
Well, that was fast. Guido says he'll accept the addition of '@' as an
infix operator for matrix multiplication, once some details are ironed
out:
https://mail.python.org/pipermail/python-ideas/2014-March/027109.html
http://legacy.python.org/dev/peps/pep-0465/
Specifically, we need to figure
That's the best news I've had all week.
Thanks for all your work on this Nathan.
-A
On Fri, Mar 14, 2014 at 8:51 PM, Nathaniel Smith n...@pobox.com wrote:
Well, that was fast. Guido says he'll accept the addition of '@' as an
infix operator for matrix multiplication, once some details are
This is great news. Excellent work Nathaniel and all others!
Frédéric
On Fri, Mar 14, 2014 at 8:57 PM, Aron Ahmadia a...@ahmadia.net wrote:
That's the best news I've had all week.
Thanks for all your work on this Nathan.
-A
On Fri, Mar 14, 2014 at 8:51 PM, Nathaniel Smith n...@pobox.com
This id good for Numpyists but this will be another operator that good also
help in another contexts.
As a math user, I was first very skeptical but finally this is a good news
for non Numpyists too.
Christophe BAL
Le 15 mars 2014 02:01, Frédéric Bastien no...@nouiz.org a écrit :
This is great
That’s great.
Does this mean that, in the not-so-distant future, the matrix class will go the
way of the dodos? I have had more subtle to fix bugs sneak into code b/c
something returns a matrix instead of an array than almost any other single
source I can think of. Having two almost
Hi all,
Here's the main blocker for adding a matrix multiply operator '@' to
Python: we need to decide what we think its precedence and associativity
should be. I'll explain what that means so we're on the same page, and what
the choices are, and then we can all argue about it. But even better
On Sat, Mar 15, 2014 at 3:18 AM, Chris Laumann chris.laum...@gmail.com wrote:
That’s great.
Does this mean that, in the not-so-distant future, the matrix class will go
the way of the dodos? I have had more subtle to fix bugs sneak into code b/c
something returns a matrix instead of an
Hi all,
Let me preface my two cents by saying that I think the best part of @ being
accepted is the potential for deprecating the matrix class — the syntactic
beauty of infix for matrix multiply is a nice side effect IMHO :) This may be
why my basic attitude is:
I don’t think it matters very
Congratulations Nathaniel!
This is great news!
Well done on starting the process and taking things forward.
Travis
On Mar 14, 2014 7:51 PM, Nathaniel Smith n...@pobox.com wrote:
Well, that was fast. Guido says he'll accept the addition of '@' as an
infix operator for matrix multiplication,
Hi all,
Here's the second thread for discussion about Guido's concerns about
PEP 465. The issue here is that PEP 465 as currently written proposes
two new operators, @ for matrix multiplication and @@ for matrix power
(analogous to * and **):
http://legacy.python.org/dev/peps/pep-0465/
The
On Fri, Mar 14, 2014 at 9:32 PM, Nathaniel Smith n...@pobox.com wrote:
Here are the interesting use cases for @@ that I can think of:
- 'vector @@ 2' gives the squared Euclidean length (because it's the
same as vector @ vector). Kind of handy.
- 'matrix @@ n' of course gives the matrix
On Fri, Mar 14, 2014 at 9:15 PM, Chris Laumann chris.laum...@gmail.comwrote:
Hi all,
Let me preface my two cents by saying that I think the best part of @
being accepted is the potential for deprecating the matrix class -- the
syntactic beauty of infix for matrix multiply is a nice side
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