Is the following inteded? Why array(1) is not fortran contiguous?
In [1]: from numpy import *
In [2]: __version__
Out[2]: '1.0.3'
In [3]: array(1).flags
Out[3]:
C_CONTIGUOUS : True
F_CONTIGUOUS : False
OWNDATA : True
WRITEABLE : True
ALIGNED : True
UPDATEIFCOPY : False
--
Lisandro
On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
>
> On 7/20/07, Charles R Harris < [EMAIL PROTECTED]> wrote:
> >
> > I expect using sqrt(x) will be faster than x**.5.
> >
>
> I did test this at one po
On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
On 7/20/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
>
> I expect using sqrt(x) will be faster than x**.5.
>
I did test this at one point and was also surprised that sqrt(x) seemed
slower than **.5. However I found out
On 7/20/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
I expect using sqrt(x) will be faster than x**.5.
I did test this at one point and was also surprised that sqrt(x) seemed
slower than **.5. However I found out otherwise while preparing a timeit
script to demonstrate this observation.
On 7/20/07, Charles R Harris <[EMAIL PROTECTED]> wrote:
[SNIP]
I expect using sqrt(x) will be faster than x**.5.
You might want to check that. I believe that x**0.5 is one of the magic
special cases that is optimized to run fast (by calling sqrt in this case).
IIRC the full set is [-1, 0, 0
On 7/20/07, Kevin Jacobs <[EMAIL PROTECTED]> <[EMAIL PROTECTED]>
wrote:
On 7/20/07, Anne Archibald <[EMAIL PROTECTED]> wrote:
>
> On 20/07/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
> > lorenzo bolla wrote:
> > > hi all.
> > > is there a function in numpy to compute the exp of a matrix, similar
On 7/20/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
Your sqrtm_eig(x) function won't work if x is defective.
See test_defective.py for details.
I've added several defective matrices to my test cases and the SVD method
doesn't work well as I'd thought (which is obvious in retrospect). I'm
goi
On Fri, 20 Jul 2007 14:45:43 -0400
"Kevin Jacobs <[EMAIL PROTECTED]>"
<[EMAIL PROTECTED]> wrote:
> On 7/20/07, Nils Wagner <[EMAIL PROTECTED]>
>wrote:
>>
>> Your sqrtm_eig(x) function won't work if x is defective.
>> See test_defective.py for details.
>
>
> I am aware, though at least on my s
On 7/20/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
Your sqrtm_eig(x) function won't work if x is defective.
See test_defective.py for details.
I am aware, though at least on my system, the SVD-based method is by far the
fastest and robust (and can be made more robust by the addition of a
rela
A Divendres 20 Juliol 2007 20:16, Christopher Barker escrigué:
> Another small note:
>
> I'm pretty sure sqlite stores everything as strings. This just plain has
> to be slower than storing the raw binary representation (and may mean
> for slight differences in fp values on the round-trip). HDF is
Another small note:
I'm pretty sure sqlite stores everything as strings. This just plain has
to be slower than storing the raw binary representation (and may mean
for slight differences in fp values on the round-trip). HDF is designed
for this sort of thing, sqlite is not.
-Chris
--
Chris
On Fri, 20 Jul 2007 13:03:09 -0400
"Kevin Jacobs <[EMAIL PROTECTED]>"
<[EMAIL PROTECTED]> wrote:
On 7/20/07, Anne Archibald <[EMAIL PROTECTED]>
wrote:
On 20/07/07, Nils Wagner <[EMAIL PROTECTED]>
wrote:
> lorenzo bolla wrote:
> > hi all.
> > is there a function in numpy to compute the exp o
On 7/20/07, Anne Archibald <[EMAIL PROTECTED]> wrote:
On 20/07/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
> lorenzo bolla wrote:
> > hi all.
> > is there a function in numpy to compute the exp of a matrix, similar
> > to expm in matlab?
> > for example:
> > expm([[0,0],[0,0]]) = eye(2)
> Numpy d
On 20/07/07, Nils Wagner <[EMAIL PROTECTED]> wrote:
> lorenzo bolla wrote:
> > hi all.
> > is there a function in numpy to compute the exp of a matrix, similar
> > to expm in matlab?
> > for example:
> > expm([[0,0],[0,0]]) = eye(2)
> Numpy doesn't provide expm but scipy does.
> >>> from scipy.lina
Vincent,
A Divendres 20 Juliol 2007 15:35, Vincent Nijs escrigué:
> Still curious however ... does no one on this list use (and like) sqlite?
First of all, while I'm not a heavy user of relational databases, I've used
them as references for benchmarking purposes. Hence, based on my own
benchma
Pearu Peterson wrote:
> Xavier Gnata wrote:
>
>
>> I just would like to be able to tell numpy to use liblapack.so instead
>> of this non free libmkl_lapack32.so
>>
>
> For that set the following environment variable when building numpy/scipy:
>
>export MKL=None
>
> Hth,
> Pearu
>
ok
On Fri, Jul 20, 2007 at 08:35:51AM -0500, Vincent Nijs wrote:
> Sounds very interesting! Would you mind sharing an example (with code if
> possible) of how you organize your experimental data in pytables. I have
> been thinking about how I might organize my data in pytables and would luv
> to hear
lorenzo bolla wrote:
> hi all.
> is there a function in numpy to compute the exp of a matrix, similar
> to expm in matlab?
> for example:
> expm([[0,0],[0,0]]) = eye(2)
>
> thanks,
> lorenzo.
>
>
> __
hi all.
is there a function in numpy to compute the exp of a matrix, similar to expm
in matlab?
for example:
expm([[0,0],[0,0]]) = eye(2)
thanks,
lorenzo.
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Thanks Francesc!
That does work much better:
-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=
PyTables version: 2.0
HDF5 version: 1.6.5
NumPy version: 1.0.4.dev3852
Zlib version: 1.2.3
BZIP2 version: 1.0.2 (30-Dec-2001)
Python version:2.5.1 (r251
On 7/20/07, Vincent Nijs <[EMAIL PROTECTED]> wrote:
Gael,
Sounds very interesting! Would you mind sharing an example (with code if
possible) of how you organize your experimental data in pytables. I have
been thinking about how I might organize my data in pytables and would luv
to hear how an e
Gael,
Sounds very interesting! Would you mind sharing an example (with code if
possible) of how you organize your experimental data in pytables. I have
been thinking about how I might organize my data in pytables and would luv
to hear how an experienced user does that.
Given the speed differences
>Hi,
>Well maybe it is a bug on my box (thunderbird) but the topic of the
thread is "-lmkl_lapack64 on i368 ??".
>Nothing to do with "Logical Selector" ;) Should I post another mail
about this topic?
>Xavier
>ps : I'm just sorry for the noise if it is a bug on my side.
>--
Hi Xavier,
I di
Xavier Gnata wrote:
>
> I just would like to be able to tell numpy to use liblapack.so instead
> of this non free libmkl_lapack32.so
For that set the following environment variable when building numpy/scipy:
export MKL=None
Hth,
Pearu
___
Numpy
A Divendres 20 Juliol 2007 04:42, Vincent Nijs escrigué:
> I am interesting in using sqlite (or pytables) to store data for scientific
> research. I wrote the attached test program to save and load a simulated
> 11x500,000 recarray. Average save and load times are given below (timeit
> with 20 repe
>>> Hi,
>>>
>>> I'm trying to update numpy by compiling the up to date svn:
>>>
>>> I get this error :
>>> gcc: numpy/linalg/lapack_litemodule.c
>>> gcc -pthread -shared
>>> build/temp.linux-i686-2.4/numpy/linalg/lapack_litemodule.o
>>> -lmkl_lapack32 -lmkl_lapack64 -lmkl -lvml -lguide -lpthread
Gael Varoquaux (el 2007-07-20 a les 11:24:34 +0200) va dir::
> I new I really should put these things on line, I have just been wanting
> to iron them a bit, but it has been almost two year since I have touched
> these, so ...
>
> http://scipy.org/Cookbook/hdf5_in_Matlab
Wow, that looks really s
On Fri, Jul 20, 2007 at 01:59:13AM -0700, Andrew Straw wrote:
> I want that Matlab script!
I new I really should put these things on line, I have just been wanting
to iron them a bit, but it has been almost two year since I have touched
these, so ...
http://scipy.org/Cookbook/hdf5_in_Matlab
Fee
Gael Varoquaux wrote:
> On Thu, Jul 19, 2007 at 09:42:42PM -0500, Vincent Nijs wrote:
>>I'd luv to hear from people using sqlite, pytables, and cPickle about
>>their experiences.
>
> I was about to point you to this discussion:
> http://projects.scipy.org/pipermail/scipy-user/2007-April/01
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