Hi,
Le 23/02/2012 02:24, Matthew Brett a écrit :
Luckily I was in fact using longdouble in the live code,
I had never exotic floating point precision, so thanks for your post
which made me take a look at docstring and documentation.
If I got it right from the docstring, 'np.longdouble',
On 02/22/2012 10:45 PM, Chao YUE wrote:
Hi all,
Is anyone using some python geospatial package that can do jobs like
intersection, etc. the job is like you automatically extract a region
on a global map etc.
thanks and cheers,
Chao
Chao,
shapely would do this, though I found it had a
On Feb 23, 2012, at 3:06 AM, Pierre Haessig wrote:
Hi,
Le 23/02/2012 02:24, Matthew Brett a écrit :
Luckily I was in fact using longdouble in the live code,
I had never exotic floating point precision, so thanks for your post
which made me take a look at docstring and documentation.
If I
On Thu, Feb 23, 2012 at 11:40 AM, Francesc Alted franc...@continuum.io wrote:
Exactly. I'd update this to read:
float96 96 bits. Only available on 32-bit (i386) platforms.
float128 128 bits. Only available on 64-bit (AMD64) platforms.
Except float96 is actually 80 bits. (Usually?) Plus
Le 23/02/2012 12:40, Francesc Alted a écrit :
However, I was surprised that float128 is not mentioned in the array of
available types in the user guide.
http://docs.scipy.org/doc/numpy/user/basics.types.html
Is there a specific reason for this absence, or is just about visiting
the
On Feb 23, 2012, at 5:43 AM, Nathaniel Smith wrote:
On Thu, Feb 23, 2012 at 11:40 AM, Francesc Alted franc...@continuum.io
wrote:
Exactly. I'd update this to read:
float9696 bits. Only available on 32-bit (i386) platforms.
float128 128 bits. Only available on 64-bit (AMD64)
On Feb 23, 2012, at 6:06 AM, Francesc Alted wrote:
On Feb 23, 2012, at 5:43 AM, Nathaniel Smith wrote:
On Thu, Feb 23, 2012 at 11:40 AM, Francesc Alted franc...@continuum.io
wrote:
Exactly. I'd update this to read:
float9696 bits. Only available on 32-bit (i386) platforms.
2012/2/23 Vincent Schut sc...@sarvision.nl
On 02/22/2012 10:45 PM, Chao YUE wrote:
Hi all,
Is anyone using some python geospatial package that can do jobs like
intersection, etc. the job is like you automatically extract a region
on a global map etc.
thanks and cheers,
Chao
Hi!
I was wondering whether it would be easy/possible/reasonable to have
classes for arrays that have special structure in order to use less
memory and speed up some computations?
For instance:
- symmetric matrix could be stored in almost half the memory required by
a non-symmetric matrix
-
Hi,
On Thu, Feb 23, 2012 at 4:23 AM, Francesc Alted franc...@continuum.io wrote:
On Feb 23, 2012, at 6:06 AM, Francesc Alted wrote:
On Feb 23, 2012, at 5:43 AM, Nathaniel Smith wrote:
On Thu, Feb 23, 2012 at 11:40 AM, Francesc Alted franc...@continuum.io
wrote:
Exactly. I'd update this to
On Thu, Feb 23, 2012 at 5:23 AM, Francesc Alted franc...@continuum.iowrote:
On Feb 23, 2012, at 6:06 AM, Francesc Alted wrote:
On Feb 23, 2012, at 5:43 AM, Nathaniel Smith wrote:
On Thu, Feb 23, 2012 at 11:40 AM, Francesc Alted franc...@continuum.io
wrote:
Exactly. I'd update this to
On 02/23/2012 05:50 AM, Jaakko Luttinen wrote:
Hi!
I was wondering whether it would be easy/possible/reasonable to have
classes for arrays that have special structure in order to use less
memory and speed up some computations?
For instance:
- symmetric matrix could be stored in almost half
On 02/23/2012 09:47 AM, Dag Sverre Seljebotn wrote:
On 02/23/2012 05:50 AM, Jaakko Luttinen wrote:
Hi!
I was wondering whether it would be easy/possible/reasonable to have
classes for arrays that have special structure in order to use less
memory and speed up some computations?
For
Le 23/02/2012 17:28, Charles R Harris a écrit :
That's correct. They are both extended precision (80 bits), but
aligned on 32bit/64bit boundaries respectively. Sun provides a true
quad precision, also called float128, while on PPC long double is an
odd combination of two doubles.
This is
Hi,
On Thu, Feb 23, 2012 at 10:11 AM, Pierre Haessig
pierre.haes...@crans.org wrote:
Le 23/02/2012 17:28, Charles R Harris a écrit :
That's correct. They are both extended precision (80 bits), but
aligned on 32bit/64bit boundaries respectively. Sun provides a true
quad precision, also called
On Thu, Feb 23, 2012 at 10:42 AM, Matthew Brett matthew.br...@gmail.comwrote:
Hi,
On Thu, Feb 23, 2012 at 10:11 AM, Pierre Haessig
pierre.haes...@crans.org wrote:
Le 23/02/2012 17:28, Charles R Harris a écrit :
That's correct. They are both extended precision (80 bits), but
aligned on
Hi,
On Thu, Feb 23, 2012 at 10:45 AM, Mark Wiebe mwwi...@gmail.com wrote:
On Thu, Feb 23, 2012 at 10:42 AM, Matthew Brett matthew.br...@gmail.com
wrote:
Hi,
On Thu, Feb 23, 2012 at 10:11 AM, Pierre Haessig
pierre.haes...@crans.org wrote:
Le 23/02/2012 17:28, Charles R Harris a écrit :
On Thu, Feb 23, 2012 at 10:55 AM, Matthew Brett matthew.br...@gmail.comwrote:
Hi,
On Thu, Feb 23, 2012 at 10:45 AM, Mark Wiebe mwwi...@gmail.com wrote:
On Thu, Feb 23, 2012 at 10:42 AM, Matthew Brett matthew.br...@gmail.com
wrote:
Hi,
On Thu, Feb 23, 2012 at 10:11 AM, Pierre
dear all,
I haven't read all 180 e-mails, but I didn't see this on Travis's
initial list.
All of the existing flat file reading solutions I have seen are
not suitable for many applications, and they compare very unfavorably
to tools present in other languages, like R. Here are some of the
main
Is mkl only used for linear algebra? Will it speed up e.g., elementwise
transendental functions?
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On Feb 23, 2012, at 1:33 PM, Neal Becker wrote:
Is mkl only used for linear algebra? Will it speed up e.g., elementwise
transendental functions?
Yes, MKL comes with VML that has this type of optimizations:
http://software.intel.com/sites/products/documentation/hpc/mkl/vml/vmldata.htm
Also,
23.02.2012 20:44, Francesc Alted kirjoitti:
On Feb 23, 2012, at 1:33 PM, Neal Becker wrote:
Is mkl only used for linear algebra? Will it speed up e.g., elementwise
transendental functions?
Yes, MKL comes with VML that has this type of optimizations:
And also no, in the sense that Numpy
Hi,
23.02.2012 20:32, Wes McKinney kirjoitti:
[clip]
To be clear: I'm going to do this eventually whether or not it
happens in NumPy because it's an existing problem for heavy
pandas users. I see no reason why the code can't emit structured
arrays, too, so we might as well have a common
Le 23/02/2012 20:08, Mark Wiebe a écrit :
+1, I think it's good for its name to correspond to the name in C/C++,
so that when people search for information on it they will find the
relevant information more easily. With a bunch of NumPy-specific
aliases, it just creates more hassle for
This is actually on my short-list as well --- it just didn't make it to the
list.
In fact, we have someone starting work on it this week. It is his first
project so it will take him a little time to get up to speed on it, but he will
contact Wes and work with him and report progress to this
On Thu, Feb 23, 2012 at 3:08 PM, Travis Oliphant tra...@continuum.io wrote:
This is actually on my short-list as well --- it just didn't make it to the
list.
In fact, we have someone starting work on it this week. It is his first
project so it will take him a little time to get up to speed
Pauli Virtanen wrote:
23.02.2012 20:44, Francesc Alted kirjoitti:
On Feb 23, 2012, at 1:33 PM, Neal Becker wrote:
Is mkl only used for linear algebra? Will it speed up e.g., elementwise
transendental functions?
Yes, MKL comes with VML that has this type of optimizations:
And also no,
On Thu, Feb 23, 2012 at 2:08 PM, Travis Oliphant tra...@continuum.iowrote:
This is actually on my short-list as well --- it just didn't make it to
the list.
In fact, we have someone starting work on it this week. It is his first
project so it will take him a little time to get up to speed
Wes -
I designed the recfile package to fill this need. It might be a start.
Some features:
- the ability to efficiently read any subset of the data without
loading the whole file.
- reads directly into a recarray, so no overheads.
- object oriented interface, mimicking
On Thu, Feb 23, 2012 at 3:19 PM, Warren Weckesser
warren.weckes...@enthought.com wrote:
On Thu, Feb 23, 2012 at 2:08 PM, Travis Oliphant tra...@continuum.io
wrote:
This is actually on my short-list as well --- it just didn't make it to
the list.
In fact, we have someone starting work on it
On Thu, Feb 23, 2012 at 3:23 PM, Erin Sheldon erin.shel...@gmail.com wrote:
Wes -
I designed the recfile package to fill this need. It might be a start.
Some features:
- the ability to efficiently read any subset of the data without
loading the whole file.
- reads directly
Le jeudi 23 février 2012 21:24:28, Wes McKinney a écrit :
That would indeed be great. Reading large files is a real pain whatever the
python method used.
BTW, could you tell us what you mean by large files?
cheers,
Éric.
Sweet, between this, Continuum folks, and me and my guys I think we
Excerpts from Wes McKinney's message of Thu Feb 23 15:24:44 -0500 2012:
On Thu, Feb 23, 2012 at 3:23 PM, Erin Sheldon erin.shel...@gmail.com wrote:
I designed the recfile package to fill this need. It might be a start.
Can you relicense as BSD-compatible?
If required, that would be fine with
On Feb 23, 2012, at 2:19 PM, Neal Becker wrote:
Pauli Virtanen wrote:
23.02.2012 20:44, Francesc Alted kirjoitti:
On Feb 23, 2012, at 1:33 PM, Neal Becker wrote:
Is mkl only used for linear algebra? Will it speed up e.g., elementwise
transendental functions?
Yes, MKL comes with VML
Le 23/02/2012 20:32, Wes McKinney a écrit :
If anyone wants to get involved in this particular problem right
now, let me know!
Hi Wes,
I'm totally out of the implementations issues you described, but I have
some million-lines-long CSV files so that I experience some slowdown
when loading those.
Le 23/02/2012 21:08, Travis Oliphant a écrit :
I think loadtxt is now the 3rd or 4th text-reading interface I've seen in
NumPy.
Ok, now I understand why I got confused ;-)
--
Pierre
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Description: OpenPGP digital signature
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On Thu, Feb 23, 2012 at 3:31 PM, Éric Depagne e...@depagne.org wrote:
Le jeudi 23 février 2012 21:24:28, Wes McKinney a écrit :
That would indeed be great. Reading large files is a real pain whatever the
python method used.
BTW, could you tell us what you mean by large files?
cheers,
Excerpts from Wes McKinney's message of Thu Feb 23 15:45:18 -0500 2012:
Reasonably wide CSV files with hundreds of thousands to millions of
rows. I have a separate interest in JSON handling but that is a
different kind of problem, and probably just a matter of forking
ultrajson and having it
On Thu, Feb 23, 2012 at 3:55 PM, Erin Sheldon erin.shel...@gmail.com wrote:
Excerpts from Wes McKinney's message of Thu Feb 23 15:45:18 -0500 2012:
Reasonably wide CSV files with hundreds of thousands to millions of
rows. I have a separate interest in JSON handling but that is a
different kind
On Thu, Feb 23, 2012 at 04:07:04PM -0500, Wes McKinney wrote:
In this last case for example, around 500 MB of RAM is taken up for an
array that should only be about 80-90MB. If you're a data scientist
working in Python, this is _not good_.
But why, oh why, are people storing big data in CSV?
But why, oh why, are people storing big data in CSV?
Well, that's what scientist do :-)
Éric.
G
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Un clavier azerty en vaut deux
On Thu, Feb 23, 2012 at 21:09, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Feb 23, 2012 at 04:07:04PM -0500, Wes McKinney wrote:
In this last case for example, around 500 MB of RAM is taken up for an
array that should only be about 80-90MB. If you're a data scientist
working in
Excerpts from Wes McKinney's message of Thu Feb 23 16:07:04 -0500 2012:
That's pretty good. That's faster than pandas's csv-module+Cython
approach almost certainly (but I haven't run your code to get a read
on how much my hardware makes a difference), but that's not shocking
at all:
In [1]:
On Thu, Feb 23, 2012 at 3:14 PM, Robert Kern robert.k...@gmail.com wrote:
On Thu, Feb 23, 2012 at 21:09, Gael Varoquaux
gael.varoqu...@normalesup.org wrote:
On Thu, Feb 23, 2012 at 04:07:04PM -0500, Wes McKinney wrote:
In this last case for example, around 500 MB of RAM is taken up for an
On Thu, Feb 23, 2012 at 4:20 PM, Erin Sheldon erin.shel...@gmail.com wrote:
Excerpts from Wes McKinney's message of Thu Feb 23 16:07:04 -0500 2012:
That's pretty good. That's faster than pandas's csv-module+Cython
approach almost certainly (but I haven't run your code to get a read
on how much
Le 23/02/2012 22:38, Benjamin Root a écrit :
labmate/officemate/advisor is using Excel...
... or an industrial partner with its windows-based software that can
export (when it works) some very nice field data from a proprietary
Honeywell data logger.
CSV data is better than no data ! (and better
Hi there,
I'm having a problem building NumPy on Python 2.7.1 and OS X 10.7.3. Here is my
build log:
https://gist.github.com/1895377
Does anyone have any idea what might be happening? I get a very similar error
when compiling with clang.
Installing a binary really isn't an option for me due
===
Announcing Theano 0.5
===
This is a major version, with lots of new features, bug fixes, and some
interface changes (deprecated or potentially misleading features were
removed).
Upgrading to Theano 0.5 is recommended for everyone, but you
Hi,
On Thu, Feb 23, 2012 at 2:56 PM, Pierre Haessig
pierre.haes...@crans.org wrote:
Le 23/02/2012 20:08, Mark Wiebe a écrit :
+1, I think it's good for its name to correspond to the name in C/C++,
so that when people search for information on it they will find the
relevant information more
Hey all,
I would like to gather concrete information about NumPy users and have some
data to look at regarding the user base and features that are of interest.
We have been putting together a survey that I would love feedback on from
members of this list. If you have time and are
For convenience, here's a link to the mailing list thread on this topic
from a couple months ago:
http://thread.gmane.org/gmane.comp.python.numeric.general/47094 .
Drew
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As others on this list, I've also been confused a bit by the prolific numpy
interfaces to reading text. Would it be an idea to create some sort of object
oriented solution for this purpose?
reader = np.FileReader('my_file.txt')
reader.loadtxt() # for backwards compat.; np.loadtxt could
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