Re: [Numpy-discussion] [ANN] Announcing the SciPy conference schedule
A humble suggestion--for the March meeting of the american physical society, there is a roommate finder for splitting hotel rooms. This could be useful in keeping expenses down for some. There should be a way to do it without liability Cheers, William On Wed, Jul 15, 2009 at 10:13 PM, Gael Varoquaux gael.varoqu...@normalesup.org wrote: The SciPy conference committee is pleased to announce the schedule of the conference: http://conference.scipy.org/schedule This year’s program is very rich. In order to limit the number of interesting talks that we had to turn down, we decided to reduce the length of talks. Although this results in many short talks, we hope that it will foster discussions, and give new ideas. Many subjects are covered, both varying technical subject in the scientific computing spectrum, and covering a lot of different research areas. I would personally like to thank the members of the program committee, who spent time reviewing the proposed abstracts and giving the chairs feedback. Fernando Perez and the tutorial presenters are hard at work finishing planning all the details of the two-day tutorial session that will precede the conference. An introduction tutorial track and an advanced tutorial track, both covering various aspect of scientific computing in Python, presented by experts in the field, should help many people getting up to speed on the amazing technology driving this community. The SciPy 2009 program committee * Co-Chair Gaël Varoquaux, Applied Mathematics and Neuroscience, * Neurospin, CEA - INRIA Saclay (France) * Co-Chair Stéfan van der Walt, Applied Mathematics, University of * Stellenbosch (South Africa) * Michael Aivazis, Center for Advanced Computing Research, California * Institute of Technology (USA) * Brian Granger, Physics Department, California Polytechnic State * University, San Luis Obispo (USA) * Aric Hagberg, Theoretical Division, Los Alamos National Laboratory * (USA) * Konrad Hinsen, Centre de Biophysique Moléculaire, CNRS Orléans * (France) * Randall LeVeque, Mathematics, University of Washington, Seattle * (USA) * Travis Oliphant, Enthought (USA) * Prabhu Ramachandran, Department of Aerospace Engineering, IIT * Bombay (India) * Raphael Ritz, International Neuroinformatics Coordinating Facility * (Sweden) * William Stein, Mathematics, University of Washington, Seattle (USA) Conference Chair: Jarrod Millman, Neuroscience Institute, UC Berkeley (USA) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] alternative mechanism for initializing anarray
Hello,
all these alternative mechanisms for initializing
arrays risk to break current code. Isn't it?
Then one would need to specify the data type
with a kw argument while with the current
implementation the second argument is the data type
irregardless of whether or not it is given with
the dtype keyword.
np.array(['AB','S4'])
array(['AB', 'S4'],
dtype='|S2')
np.array('AB','S4')
array('AB', dtype='|S4')
Best,
Luca
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Re: [Numpy-discussion] Scipy Conference 2009 Lecture Recordings
On Thu, Jul 16, 2009 at 6:39 PM, Gökhan SEVER gokhanse...@gmail.com wrote: On Thu, Jul 16, 2009 at 4:30 PM, Fernando Perez fperez@gmail.comwrote: If someone has a camera that can do the recordings in a format that can then be directly recompressed at the command line with something like mencoder, that would be great. From experience, any recording mode that requires later manual editing sounds great in principle, and then nobody finds the time to do all the work. There is a one great approach posted here at http://yeoldeclue.com/cgi-bin/blog/blog.cgi?rm=viewpostnodeid=1246925071 Seems like his one man army approach worked very nicely. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion I wish I was free to do a beautiful production quality video recording for the community. I would really enjoy doing that. I also feel it is quite important considering lectures of this kind are so, so instructive. If it is too much work to do video, that's perfectly ok. Not preferable, but definately O.K. Besides I'd rather have a rich audio recording then haphazard video/audio If someone could just get a decent recording of the audio, then the slides and audio can be edited together as a screencast on a website. I could imagine a pipe of the stage microphone to a (possibly spare) computer. I could then see it then being uploaded to a storage server for the future editing. The talk given, provides so much more insight than the slides (pdf) alone. Just think how enticing it is for scipy new comers to have screencasts to watch. ~Pete ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Mirror/flip numpy array?
Hello list, I have a really simple newbie question: How can I mirror/flip a numpy.ndarray? I.e. mirror switches the colums (leftmost becomes rightmost and so on), flip changes the rows (top becomes bottom and so on)? Kind regards, Joe ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Mirror/flip numpy array?
In [1]: a=array([1,2,3]) In [2]: a[::-1] Out[2]: array([3, 2, 1]) Johannes Bauer wrote: Hello list, I have a really simple newbie question: How can I mirror/flip a numpy.ndarray? I.e. mirror switches the colums (leftmost becomes rightmost and so on), flip changes the rows (top becomes bottom and so on)? Kind regards, Joe ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Mirror/flip numpy array?
On Fri, Jul 17, 2009 at 6:21 AM, Gary Rubengru...@bigpond.net.au wrote: In [1]: a=array([1,2,3]) In [2]: a[::-1] Out[2]: array([3, 2, 1]) Johannes Bauer wrote: Hello list, I have a really simple newbie question: How can I mirror/flip a numpy.ndarray? I.e. mirror switches the colums (leftmost becomes rightmost and so on), flip changes the rows (top becomes bottom and so on)? There's also np.fliplr (left right) and np.flipud (up down). The last line of these functions are return m[:, ::-1] and return m[::-1,...], respectively. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Using interpolate with zero-rank array raises error
Date: Thu, 16 Jul 2009 23:37:58 -0400 From: Ralf Gommers ralf.gomm...@googlemail.com It seems to me that there are quite a few other functions that will give errors with 0-D arrays (apply_along/over_axis are two that come to mind). There is nothing to interpolate so I'm not surprised. Hmm, I don't quite understand. In the example below, the 0-D array (`x0`) gives the x-value(s) where you want interpolated values. This shouldn't require a non-scalar, and in fact, interp currently accepts python scalars (but not Numpy scalars). If the 0-D array replaced `x` and `y`---the known data points--- then, I agree there would be nothing to interpolate. I believe the example functions you cite are similar to replacing `x` and `y` below with scalar values. ... or am I just missing something? Thanks, -Tony When using interpolate with a zero-rank array, I get ValueError: object of too small depth for desired array. The following code reproduces this issue import numpy as np x0 = np.array(0.1) x = np.linspace(0, 1) y = np.linspace(0, 1) np.interp(x0, x, y) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] suggestion for generalizing numpy functions
On Mon, Jul 13, 2009 at 7:12 PM, Darren Dale dsdal...@gmail.com wrote: 2009/7/13 Stéfan van der Walt ste...@sun.ac.za Hi Darren 2009/7/13 Darren Dale dsdal...@gmail.com: I've put together a first cut at implementing __array_prepare__, which appears to work, and I would like to request feedback. Here is an overview of the approach: This is pretty neat! Do you have a quick snippet at hand illustrating its use? That would be helpful, wouldn't it? The attached script is a modified version of RealisticInfoArray from http://docs.scipy.org/doc/numpy/user/basics.subclassing.html . It should yield the following output: starting with [0 1 2 3 4] which is of type class '__main__.MyArray' and has info attribute = information subtracting 3 from [0 1 2 3 4] subtract calling __array_prepare__ on [0 1 2 3 4] input output array is now of type class '__main__.MyArray' output array values are still uninitialized: [13991160178956839578752 13991161488553639254560 48] __array_prepare__ is updating info attribute on output __array_prepare__ finished, subtract ufunc is taking over subtract calling __array_wrap__ on [0 1 2 3 4] input output array has initial value: [-3 -2 -1 0 1] __array_wrap__ is setting output endpoints to 0 yielding [ 0 -2 -1 0 0] which is of type class '__main__.MyArray' and has info attribute = new_information This is a gentle ping, hoping to get some feedback so this feature has a chance of being included in the next release. Darren ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] VIGRA, NumPy and Fortran-order (again)
Hi, as I mentioned in the past [1], we considered refactoring our VIGRA (an image analysis library [2]) python bindings to be based on NumPy [3]. However, we have the problem that VIGRA uses Fortran-order indexing (i.e. there's operator()(x, y) in C++), and this should of course be the same in Python. (It is more important to us to have the same indexing in VIGRA's python bindings and in VIGRA itself, than to have the same indexing as in e.g. MPL or PIL.) As discussing in-depth in [1], numpy does not support Fortran order very well. First, there are performance issues, but even more important: the order is not preserved when performing simple operations. :-( In [8]: numpy.isfortran(a) Out[8]: True In [9]: numpy.isfortran(a + 4) Out[9]: False In [10]: numpy.isfortran(a.copy()) Out[10]: False In the worst case, this means that VIGRA functions exported to python only for unstrided images cannot be called on the results of any numpy function call. Do you agree that this is a bug^H^H^Hmissing feature and how difficult would it be to implement that? The specs would be: preserve the *ordering* of the strides (i.e. we're using mixed-order for RGB images to be able to write image[x, y] = (r, g, b)), and in the case of multiple input arguments, use the same rules (i.e. array priority) as for the output type determination. If I understood Travis' comments in the above-mentioned thread [1] correctly, this would already fix some of the performance issues along the way (since it would suddenly allow the use of special, optimized code paths). Have a nice day, Hans [1] http://mail.scipy.org/pipermail/numpy-discussion/2007-November/029837.html [2] http://hci.iwr.uni-heidelberg.de/vigra/ [3] https://mailhost.informatik.uni-hamburg.de/pipermail/vigra/2009- May/000610.html ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [SciPy-user] [ANN] Announcing the SciPy conference schedule
On Fri, Jul 17, 2009 at 02:38, william ratcliffwilliam.ratcl...@gmail.com wrote: A humble suggestion--for the March meeting of the american physical society, there is a roommate finder for splitting hotel rooms. This could be useful in keeping expenses down for some. There should be a way to do it without liability A wiki page would probably be the best thing given the short time frame. I recommend either the Saga or the Vagabond hotels for keeping costs down and staying close to campus. -- Robert Kern I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth. -- Umberto Eco ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] suggestion for generalizing numpy functions
On Fri, Jul 17, 2009 at 10:03 AM, Darren Dale dsdal...@gmail.com wrote:
On Mon, Jul 13, 2009 at 7:12 PM, Darren Dale dsdal...@gmail.com wrote:
2009/7/13 Stéfan van der Walt ste...@sun.ac.za
Hi Darren
2009/7/13 Darren Dale dsdal...@gmail.com:
I've put together a first cut at implementing __array_prepare__, which
appears to work, and I would like to request feedback. Here is an
overview
of the approach:
This is pretty neat! Do you have a quick snippet at hand illustrating
its use?
That would be helpful, wouldn't it? The attached script is a modified
version of RealisticInfoArray from
http://docs.scipy.org/doc/numpy/user/basics.subclassing.html . It should
yield the following output:
starting with [0 1 2 3 4]
which is of type class '__main__.MyArray'
and has info attribute = information
subtracting 3 from [0 1 2 3 4]
subtract calling __array_prepare__ on [0 1 2 3 4] input
output array is now of type class '__main__.MyArray'
output array values are still uninitialized:
[13991160178956839578752 13991161488553639254560
48]
__array_prepare__ is updating info attribute on output
__array_prepare__ finished, subtract ufunc is taking over
subtract calling __array_wrap__ on [0 1 2 3 4] input
output array has initial value: [-3 -2 -1 0 1]
__array_wrap__ is setting output endpoints to 0
yielding [ 0 -2 -1 0 0]
which is of type class '__main__.MyArray'
and has info attribute = new_information
This is a gentle ping, hoping to get some feedback so this feature has a
chance of being included in the next release.
I have a question about the C-api. If I want to make the default
implementation of __array_prepare__ (or __array_wrap__, is anyone out
there?) simply pass through the output array:
static PyObject *
array_preparearray(PyArrayObject *self, PyObject *args)
{
PyObject *arr;
if (PyTuple_Size(args) 1) {
PyErr_SetString(PyExc_TypeError,
only accepts 1 argument);
return NULL;
}
arr = PyTuple_GET_ITEM(args, 0);
if (!PyArray_Check(arr)) {
PyErr_SetString(PyExc_TypeError,
can only be called with ndarray object);
return NULL;
}
return arr;
}
Is this sufficient, or do I need to worry about calling Py_INCREF?
Thanks,
Darren
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Re: [Numpy-discussion] suggestion for generalizing numpy functions
On Fri, Jul 17, 2009 at 9:44 AM, Darren Dale dsdal...@gmail.com wrote:
On Fri, Jul 17, 2009 at 10:03 AM, Darren Dale dsdal...@gmail.com wrote:
On Mon, Jul 13, 2009 at 7:12 PM, Darren Dale dsdal...@gmail.com wrote:
2009/7/13 Stéfan van der Walt ste...@sun.ac.za
Hi Darren
2009/7/13 Darren Dale dsdal...@gmail.com:
I've put together a first cut at implementing __array_prepare__, which
appears to work, and I would like to request feedback. Here is an
overview
of the approach:
This is pretty neat! Do you have a quick snippet at hand illustrating
its use?
That would be helpful, wouldn't it? The attached script is a modified
version of RealisticInfoArray from
http://docs.scipy.org/doc/numpy/user/basics.subclassing.html . It should
yield the following output:
starting with [0 1 2 3 4]
which is of type class '__main__.MyArray'
and has info attribute = information
subtracting 3 from [0 1 2 3 4]
subtract calling __array_prepare__ on [0 1 2 3 4] input
output array is now of type class '__main__.MyArray'
output array values are still uninitialized:
[13991160178956839578752 13991161488553639254560
48]
__array_prepare__ is updating info attribute on output
__array_prepare__ finished, subtract ufunc is taking over
subtract calling __array_wrap__ on [0 1 2 3 4] input
output array has initial value: [-3 -2 -1 0 1]
__array_wrap__ is setting output endpoints to 0
yielding [ 0 -2 -1 0 0]
which is of type class '__main__.MyArray'
and has info attribute = new_information
This is a gentle ping, hoping to get some feedback so this feature has a
chance of being included in the next release.
I have a question about the C-api. If I want to make the default
implementation of __array_prepare__ (or __array_wrap__, is anyone out
there?) simply pass through the output array:
static PyObject *
array_preparearray(PyArrayObject *self, PyObject *args)
{
PyObject *arr;
if (PyTuple_Size(args) 1) {
PyErr_SetString(PyExc_TypeError,
only accepts 1 argument);
return NULL;
}
arr = PyTuple_GET_ITEM(args, 0);
if (!PyArray_Check(arr)) {
PyErr_SetString(PyExc_TypeError,
can only be called with ndarray object);
return NULL;
}
return arr;
}
Is this sufficient, or do I need to worry about calling Py_INCREF?
PyObject* *PyTuple_GetItem*(PyObject *p, Py_ssize_t pos) Return value: Borrowed
reference.
Return the object at position pos in the tuple pointed to by p. If pos is
out of bounds, return NULL and sets an IndexError exception. It's a borrowed
reference so you need to call Py_INCREF on it. I find this Python C-API
documentation http://www.python.org/doc/2.5/api/api.htmluseful.
Chuck
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[Numpy-discussion] Universal file format
Hi all, Is there a Python tool to read and write files in the so-called universal format ? I found a Matlab implementation http://www.mathworks.com/matlabcentral/fileexchange/6395 Any pointer would be appreciated. Thanks in advance Nils http://www.sdrl.uc.edu/universal-file-formats-for-modal-analysis-testing-1 http://zone.ni.com/devzone/cda/tut/p/id/4463 ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Scipy Conference 2009 Lecture Recordings
On Thu, Jul 16, 2009 at 10:05 AM, Gael Varoquaux gael.varoqu...@normalesup.org wrote: On Wed, Jul 15, 2009 at 11:29:27PM -0400, Peter Alexander wrote: I sure wish I was able to attend this year's event. I'm wondering, and really hoping, if/that the lectures will be recorded and then posted for the whole community's benefit? The problem is that this requires actually a lot of work, to get something useful out of the recordings. I don't think it will happen :(. Gaël ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion Gaël, Your recently posted mayavi tutorial video and Fernando's previous py4science recordings in very good quality. I have learnt a great amount of information just by watching those videos. For me, most important gains, hearing the developer lingo and usage techniques that can't be easily find in any documentation as well as presentation skills. I think, it would be great to have a similar equipment setup during the SciPy09. -- Gökhan ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Scipy Conference 2009 Lecture Recordings
On Fri, Jul 17, 2009 at 10:37 AM, Gökhan SEVERgokhanse...@gmail.com wrote: I think, it would be great to have a similar equipment setup during the SciPy09. Absolutely. It would be *great* to have the tutorials and talks recorded. If anyone steps up to bring equipment, record the talks, and post them, everyone would be very appreciative. If no one offers to do this, it won't happen. If anyone wants to volunteer to take care of this, feel free to contact Gael, Stefan, or I off-list. Jarrod ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Scipy Conference 2009 Lecture Recordings
I would also like to see this. Have we looked at using videolectures.net? In my field, the people from videolectures.net takes care of filming and editing. I am not sure, but they might actually be free as they have a big grant from the EU to do this sort of thing. It might be worth pinging them to find out if it would be possible and how much, if any, it would cost. Best, Jonathan. On Fri, Jul 17, 2009 at 2:21 PM, Jarrod Millmanmill...@berkeley.edu wrote: On Fri, Jul 17, 2009 at 10:37 AM, Gökhan SEVERgokhanse...@gmail.com wrote: I think, it would be great to have a similar equipment setup during the SciPy09. Absolutely. It would be *great* to have the tutorials and talks recorded. If anyone steps up to bring equipment, record the talks, and post them, everyone would be very appreciative. If no one offers to do this, it won't happen. If anyone wants to volunteer to take care of this, feel free to contact Gael, Stefan, or I off-list. Jarrod ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Scipy Conference 2009 Lecture Recordings
On Fri, Jul 17, 2009 at 11:29 AM, Jonathan Taylorjonathan.tay...@utoronto.ca wrote: I would also like to see this. Have we looked at using videolectures.net? In my field, the people from videolectures.net takes care of filming and editing. I am not sure, but they might actually be free as they have a big grant from the EU to do this sort of thing. It might be worth pinging them to find out if it would be possible and how much, if any, it would cost. That's a great idea. BTW, there's an excellent set of lectures with lots of python stuff from last year's NIPS up there, including a very nice talk by John on matplotlib: http://videolectures.net/mloss08_whistler/ It would be *fantastic* if anyone from our community could take up contacting the videolectures guys... Cheers, f ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Scipy Conference 2009 Lecture Recordings
On Fri, Jul 17, 2009 at 10:37 AM, Gökhan SEVERgokhanse...@gmail.com wrote: Your recently posted mayavi tutorial video and Fernando's previous py4science recordings in very good quality. BTW, for those interested, mine are a 2-day intro course on python/science (similar in spirit to our upcoming introductory tutorial track at the conference) that I taught here at UC Berkeley: http://www.archive.org/search.php?query=Fernando+Perez+scientific+python Cheers, f ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] performance matrix multiplication vs. matlab
Following these instructions I have the following problem when I import numpy. Does anyone know why this might be? Thanks, Jonathan. import numpy Traceback (most recent call last): File stdin, line 1, in module File /home/jtaylor/lib/python2.5/site-packages/numpy/__init__.py, line 130, in module import add_newdocs File /home/jtaylor/lib/python2.5/site-packages/numpy/add_newdocs.py, line 9, in module from lib import add_newdoc File /home/jtaylor/lib/python2.5/site-packages/numpy/lib/__init__.py, line 13, in module from polynomial import * File /home/jtaylor/lib/python2.5/site-packages/numpy/lib/polynomial.py, line 18, in module from numpy.linalg import eigvals, lstsq File /home/jtaylor/lib/python2.5/site-packages/numpy/linalg/__init__.py, line 47, in module from linalg import * File /home/jtaylor/lib/python2.5/site-packages/numpy/linalg/linalg.py, line 22, in module from numpy.linalg import lapack_lite ImportError: /usr/local/lib/libptcblas.so: undefined symbol: ATL_cpttrsm On Sat, Jun 6, 2009 at 12:59 PM, Chris Colbertsccolb...@gmail.com wrote: since there is demand, and someone already emailed me, I'll put what I did in this post. It pretty much follows whats on the scipy website, with a couple other things I gleaned from reading the ATLAS install guide: and here it goes, this is valid for Ubuntu 9.04 64-bit (# starts a comment when working in the terminal) download lapack 3.2.1 http://www.netlib.org/lapack/lapack.tgz download atlas 3.8.3 http://sourceforge.net/project/downloading.php?group_id=23725filename=atlas3.8.3.tar.bz2a=65663372 create folder /home/your-user-name/build/atlas #this is where we build create folder /home/your-user-name/build/lapack #atlas and lapack extract the folder lapack-3.2.1 to /home/your-user-name/build/lapack extract the contents of atlas to /home/your-user-name/build/atlas now in the terminal: # remove g77 and get stuff we need sudo apt-get remove g77 sudo apt-get install gfortran sudo apt-get install build-essential sudo apt-get install python-dev sudo apt-get install python-setuptools sudo easy_install nose # build lapack cd /home/your-user-name/build/lapack/lapack-3.2.1 cp INSTALL/make.inc.gfortran make.inc gedit make.inc # #in the make.inc file make sure the line OPTS = -O2 -fPIC -m64 #and NOOPTS = -O0 -fPIC -m64 #the -m64 flags build 64-bit code, if you want 32-bit, simply leave #the -m64 flags out # cd SRC #this should build lapack without error make # build atlas cd /home/your-user-name/build/atlas #this is simply where we will build the atlas #libs, you can name it what you want mkdir Linux_X64SSE2 cd Linux_X64SSE2 #need to turn off cpu-throttling sudo cpufreq-selector -g performance #if you don't want 64bit code remove the -b 64 flag. replace the #number 2400 with your CPU frequency in MHZ #i.e. my cpu is 2.53 GHZ so i put 2530 ../configure -b 64 -D c -DPentiumCPS=2400 -Fa -alg -fPIC --with-netlib-lapack=/home/your-user-name/build/lapack/lapack-3.2.1/Lapack_LINUX.a #the configure step takes a bit, and should end without errors #this takes a long time, go get some coffee, it should end without error make build #this will verify the build, also long running make check #this will test the performance of your build and give you feedback on #it. your numbers should be close to the test numbers at the end make time cd lib #builds single threaded .so's make shared #builds multithreaded .so's make ptshared #copies all of the atlas libs (and the lapack lib built with atlas) #to our lib dir sudo cp *.so /usr/local/lib/ #now we need to get and build numpy download numpy 1.3.0 http://sourceforge.net/project/downloading.php?group_id=1369filename=numpy-1.3.0.tar.gza=93506515 extract the folder numpy-1.3.0 to /home/your-user-name/build #in the terminal cd /home/your-user-name/build/numpy-1.3.0 cp site.cfg.example site.cfg gedit site.cfg ### # in site.cfg uncomment the following lines and make them look like these [DEFAULT] library_dirs = /usr/local/lib include_dirs = /usr/local/include [blas_opt] libraries = ptf77blas, ptcblas, atlas [lapack_opt] libraries = lapack, ptf77blas, ptcblas, atlas ### #if you want single threaded libs, uncomment those lines instead #build numpy- should end without error python setup.py build #install numpy python setup.py install cd /home sudo ldconfig python import numpy numpy.test() #this should run with no errors (skipped tests and known-fails are ok) a = numpy.random.randn(6000, 6000) numpy.dot(a, a) # look at your cpu monitor and verify all cpu cores are at 100% if you built with threads Celebrate with a beer! Cheers! Chris On Sat, Jun 6, 2009 at 10:42 AM, Keith Goodmankwgood...@gmail.com wrote: On Fri, Jun 5, 2009
[Numpy-discussion] ANN: SciPy 2009 early registration extended to July 22nd
The early registration deadline for SciPy 2009 has been extended until Wednesday, July 22, 2009. Please register ( http://conference.scipy.org/to_register ) by this date to take advantage of the reduced early registration rate. Since we just announced the conference schedule, I was asked to provide extra time for people to register. Fortunately, we were able to get a few extra days from our vendors. But we will have to place orders next Thursday, so this is the last time we will be able to extend the deadline for registration. The conference schedule is available here: http://conference.scipy.org/schedule About the conference SciPy 2009, the 8th Python in Science conference, will be held from August 18-23, 2009 at Caltech in Pasadena, CA, USA. The conference starts with two days of tutorials to the scientific Python tools. There will be two tracks, one for introduction of the basic tools to beginners, and one for more advanced tools. The tutorials will be followed by two days of talks. Both days of talks will begin with a keynote address. The first day’s keynote will be given by Peter Norvig, the Director of Research at Google; while, the second keynote will be delivered by Jon Guyer, a Materials Scientist in the Thermodynamics and Kinetics Group at NIST. The program committee will select the remaining talks from submissions to our call for papers. All selected talks will be included in our conference proceedings edited by the program committee. After the talks each day we will provide several rooms for impromptu birds of a feather discussions. Finally, the last two days of the conference will be used for a number of coding sprints on the major software projects in our community. For the 8th consecutive year, the conference will bring together the developers and users of the open source software stack for scientific computing with Python. Attendees have the opportunity to review the available tools and how they apply to specific problems. By providing a forum for developers to share their Python expertise with the wider commercial, academic, and research communities, this conference fosters collaboration and facilitates the sharing of software components, techniques, and a vision for high level language use in scientific computing. For further information, please visit the conference homepage: http://conference.scipy.org. Important Dates --- * Friday, July 3: Abstracts Due * Wednesday, July 15: Announce accepted talks, post schedule * Wednesday, July 22: Early Registration ends * Tuesday-Wednesday, August 18-19: Tutorials * Thursday-Friday, August 20-21: Conference * Saturday-Sunday, August 22-23: Sprints * Friday, September 4: Papers for proceedings due Executive Committee --- * Jarrod Millman, UC Berkeley, USA (Conference Chair) * Gaël Varoquaux, INRIA Saclay, France (Program Co-Chair) * Stéfan van der Walt, University of Stellenbosch, South Africa (Program Co-Chair) * Fernando Pérez, UC Berkeley, USA (Tutorial Chair) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Using interpolate with zero-rank array raises error
Date: Fri, 17 Jul 2009 13:27:25 -0400 From: Ralf Gommers ralf.gomm...@googlemail.com Subject: Re: [Numpy-discussion] Using interpolate with zero-rank array raises error [snip] If it works with scalars it should work with 0-D arrays I think. So you should probably open a ticket and attach your patch. Thanks for your responses and suggestion. I've opened up Ticket #1177 on Trac to address this issue. Best, -Tony___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] VIGRA, NumPy and Fortran-order (again)
On 2009-07-17, Hans Meine me...@informatik.uni-hamburg.de wrote: [clip] As discussing in-depth in [1], numpy does not support Fortran order very well. First, there are performance issues, but even more important: the order is not preserved when performing simple operations. :-( [clip] The specs would be: preserve the *ordering* of the strides (i.e. we're using mixed-order for RGB images to be able to write image[x, y] = (r, g, b)), and in the case of multiple input arguments, use the same rules (i.e. array priority) as for the output type determination. If I understood Travis' comments in the above-mentioned thread [1] correctly, this would already fix some of the performance issues along the way (since it would suddenly allow the use of special, optimized code paths). I was wondering about this too, when working on improving the cache coherency of the reduction operations. Also these would be more efficient if the striding of the output array could be chosen freely. I wonder if it would be OK to make this change... -- Pauli Virtanen ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] performance matrix multiplication vs. matlab
On 17-Jul-09, at 3:57 PM, Jonathan Taylor wrote: File /home/jtaylor/lib/python2.5/site-packages/numpy/linalg/ __init__.py, line 47, in module from linalg import * File /home/jtaylor/lib/python2.5/site-packages/numpy/linalg/ linalg.py, line 22, in module from numpy.linalg import lapack_lite ImportError: /usr/local/lib/libptcblas.so: undefined symbol: ATL_cpttrsm It doesn't look like you ATLAS is linked together properly, specifically fblas. What fortran compiler are you using? What does ldd /usr/local/lib/libptcblas.so say? I seem to recall this sort of thing happening when g77 and gfortran get mixed up together... David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] performance matrix multiplication vs. matlab
On 17-Jul-09, at 4:20 PM, David Warde-Farley wrote: It doesn't look like you ATLAS is linked together properly, specifically fblas. What fortran compiler are you using? ImportError: /usr/local/lib/libptcblas.so: undefined symbol: ATL_cpttrsm Errr, nevermind. I seem to have very selective vision and saw that as 'ptf77blas.so'. Suffice it to say it's an ATLAS build problem and you seem to be doing everything right given the commands. You remembered ldconfig? David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] VIGRA, NumPy and Fortran-order (again)
Pauli Virtanen wrote: On 2009-07-17, Hans Meine me...@informatik.uni-hamburg.de wrote: If I understood Travis' comments in the above-mentioned thread [1] correctly, this would already fix some of the performance issues along the way (since it would suddenly allow the use of special, optimized code paths). I was wondering about this too, when working on improving the cache coherency of the reduction operations. Also these would be more efficient if the striding of the output array could be chosen freely. I wonder if it would be OK to make this change... This is something that I would like to see since I also am using python wrapped fortran. My python is sprinkled with transposes, before and after many numpy operations, to avoid the performance problems. Most of the arrays are created with fortran ordering to avoid copies when passed into fortran. My fortran wrapper, Forthon, automatically handles the ordering conversion, copying if needed, but I try to avoid the copying as much as possible. It would be very nice if some of the ordering issues could be handled under the covers by numpy. Dave ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
