Mailman 3 January 2008 - NumPy-Discussion

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by bacmsantos＠gmail.com Jan. 10, 2008

Jan. 10, 2008

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Intel MKL - was: parallel numpy - any info?
by Ray Schumacher Jan. 10, 2008

Jan. 10, 2008

At 10:38 PM 1/8/2008, Albert Strasheim wrote: > > It is still unclear to me whether Python/numpy compiled with MKL > > would be freely re-distributable, as the MSVC version is. > >Read the License Agreement on Intel's site. My interpretation is that >it would be redistributable. > >http://www.intel.com/cd/software/products/asmo-na/eng/266854.htm That was my thought also, but IANAL. Given the number of people who've evidently compiledPython/numeric with it I was left wondering why there are no binaries to be found. We've been using the Enthought distros, and our company now has (finally) decided to purchase the ICC and MKL with the intention of compiling for P4 and Core2 targets. The binaries could then go up on the company's web site. Thanks, Ray Schumacher -- No virus found in this outgoing message. Checked by AVG Free Edition. Version: 7.5.516 / Virus Database: 269.17.13/1214 - Release Date: 1/8/2008 1:38 PM

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Does float16 exist?
by Darren Dale Jan. 10, 2008

Jan. 10, 2008

One of my collaborators would like to use 16bit float arrays. According to http://www.scipy.org/Tentative_NumPy_Tutorial, and references to float16 in numpy.core.numerictypes, it appears that this should be possible, but the following doesnt work: a=arange(10, dtype='float16') TypeError: data type not understood Can anyone offer some advice? Thanks, Darren -- Darren S. Dale, Ph.D. Staff Scientist Cornell High Energy Synchrotron Source Cornell University 275 Wilson Lab Rt. 366 & Pine Tree Road Ithaca, NY 14853 darren.dale(a)cornell.edu office: (607) 255-3819 fax: (607) 255-9001 http://www.chess.cornell.edu

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numpy.linalg.eigvals crashes whn calling lapack_lite.pyd
by Simon Jan. 9, 2008

Jan. 9, 2008

Newbie here. Trying to generate eigenvalues from a matrix using: print numpy.linalg.eigvals(matrix) This works with small matrices, say 5 x 5, but causes python to crash on larger matrices, say 136 x 136, which is not really very large. Setup: Win XP SP2 Python 2.5.1 (from .msi) numpy 1.0.4 (from .msi) pywin32-210 (from .exe installer) When running from either the command line or the Pythonwin IDE, python.exe crashes. The info in the microsoft error reporting thingy is: AppName: python.exe ModName: lapack_lite.pyd Offset: 000b7434 Stepping through linalg.py using Pythonwin, I get as far as line 418 (in the eigvals function): results = lapack_routine('N', 'N', n, a, n, wr, wi, dummy, 1, dummy, 1, work, lwork, 0) and then python.exe crashes. That's the extent of my troubleshooting skills at this stage. I haven't worked out if there is a specific matrix size where this starts occurring. Where to now? I can send the actual data for the matrix if need be, but as it's very large I thought it would mess up the list if I posted it here. Simon

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Failing to understand vectorize behavior
by David Huard Jan. 9, 2008

Jan. 9, 2008

Hi all, I'm having trouble understanding the behavior of vectorize on the following example: >>> import string >>> from numpy import vectorize >>> vstrip = vectorize(string.strip) >>> s = [' aaaaaaaaaaaaaa ' , ' bbbbbbbbbbbbbbbbbb ', ' cccccccccccccccccc '] >>> vstrip(s) array(['aaaaaaaa', 'bbbbbbbb', 'cccccccc'], dtype='|S8') where all strings are cropped to 8 characters. Is this expected ? Thanks, David

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Re: [Numpy-discussion] parallel numpy - any info?
by Ray Schumacher Jan. 9, 2008

Jan. 9, 2008

At 04:27 AM 1/8/2008, you wrote: > 4. Re: parallel numpy (by Brian Granger) - any info? > (Matthieu Brucher) >From: "Matthieu Brucher" <matthieu.brucher(a)gmail.com> > >MKL does the multithreading on its own for level 3 BLAS instructions >(OpenMP). There was brief debate yesterday among the Pythonians in the lab as to whether the MKL operates outside of the GIL, but it was general understanding that it does. It is still unclear to me whether Python/numpy compiled with MKL would be freely re-distributable, as the MSVC version is. >Then you must use tools like the processing module, MPI, ... I have been using shared memory and numpy with good results lately on Win32 with tagged memory. http://projects.scipy.org/pipermail/numpy-discussion/2007-October/029505.ht… On *NIX, arrayfrombuffer(), mmap and MAP_SHARED, or POSH http://poshmodule.sourceforge.net/ seem like the ticket. Whatever happened to pyGA? GA http://www.emsl.pnl.gov/docs/global/ is still around. http://www.ece.lsu.edu/jxr/pohll-02/papers/jarek.pdf Best, Ray Schumacher -- No virus found in this outgoing message. Checked by AVG Free Edition. Version: 7.5.516 / Virus Database: 269.17.13/1211 - Release Date: 1/6/2008 11:57 AM

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Using svnmerge on numpy: am I missing something ?
by David Cournapeau Jan. 9, 2008

Jan. 9, 2008

Hi, for my work related on scons, I have a branch build_with_scons in the numpy trunk, which I have initialized exactly as documented on the numpy wiki (http://projects.scipy.org/scipy/numpy/wiki/MakingBranches). When I try to update my branch with the trunk, I got suprising merge request, in perticular, it tried to merge all trunk revision up to 2871, whereas I created my branch with a copy from the trunk at revision 4676. Am I missing something ? Shouldn't it try to merge from the revision I started the branch (since this revision is a common ancestor) ? cheers, David

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major changes in matplotlib svn
by John Hunter Jan. 8, 2008

Jan. 8, 2008

Apologies for the off-topic post to the numpy list, but we have just committed some potentially code-breaking changes to the matplotlib svn repository, and we want to gve as wide a notification to people as possible. Please do not reply to the numpy list, but rather to a matplotlib mailing list . Migrating to the new matplotlib codebase ======================================== Michael Droettboom has spent the last several months working on the "transforms branch" of matplotlib, in which he rewrote from the ground up the transformation infrastructure in matplotlib, which many found unintuitive and hard to extend. In addition to a cleaner code base, the reorganization allows you to define your own transformations and projections (e.g. map projections) within matplotlib. He has merged his work into the HEAD of the svn trunk, and this will be the basis for future matplotlib releases. If you are a svn user, we encourage you to continue using the trunk as before, but with the understanding that you are now truly on the bleeding edge. Michael has made sure all the examples still pass with the new code base, so for the vast majority of you, I expect to see few problems. But we need to get as many people as possible using the new code base so we can find and fix the remaining problems. We have take the svn code used in the last stable release in the 0.91 series, and made it a maintenance branch so we can still fix bugs and support people who are not ready to migrate to the new transformation infrastructure but nonetheless need access to svn bug fixes. Using the new code ================== To check out the trunk with the latest transforms changes: > svn co https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/trunk/matplotlib If you already have a working copy of the trunk, your next "svn up" will include the latest transforms changes. Before installing, make sure you completely remove the old matplotlib build and install directories, eg: > cd matplotlib > sudo rm -rf build > sudo rm -rf /usr/local/lib/python2.5/site-packages/matplotlib > sudo python setup.py install Using the old svn code ====================== To check out the maintenance branch, in order to commit bugfixes to 0.91.x: > svn co https://matplotlib.svn.sourceforge.net/svnroot/matplotlib/branches/v0_91_ma… matplotlib_0_91_maint Any applicable bugfixes on the 0.91.x maintenance branch should be merged into the trunk so they are fixed there as well. Svnmerge.py makes this process rather straightforward, but you may also manually merge if you prefer. Merging bugfixes on the maint branch to the trunk using svnmerge.py ------------------------------------------------------------------- Download svnmerge.py from here: http://www.orcaware.com/svn/wiki/Svnmerge.py >From the working copy of the *trunk* (svnmerge.py always pulls *to* the current working copy), so > svnmerge.py merge to pull in changes from the maintenance branch. Manually resolve any conflicts, if necessary, test them, and then commit with > svn commit -F svnmerge-commit-message.txt (Note the above will stop working when the maintenance branch is abandoned.) API CHANGES in the new transformation infrastructure ==================================================== While Michael worked hard to keep the API mostly unchanged while performing what has been called "open heart surgery on matplotlib", there have been some changes, as discussed below. The primary goal of these changes was to make it easier to extend matplotlib to support new kinds of projections. This is primarily an internal improvement, and the possible user-visible changes it allows are yet to come. These changes are detailed in the API_CHANGES document.

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parallel numpy (by Brian Granger) - any info?
by dmitrey Jan. 8, 2008

Jan. 8, 2008

Some days ago there was mentioned a parallel numpy that is developed by Brian Granger. Does the project have any blog or website? Has it any description about API and abilities? When 1st release is intended? Regards, D

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how to work with mercurial and numpy right now
by Ondrej Certik Jan. 8, 2008

Jan. 8, 2008

Hi, if you want to play with Mercurial now (without forcing everyone else to leave svn), I suggest this: http://cheeseshop.python.org/pypi/hgsvn I tried that and it works. It's a very easy way to create a hg mirror at your computer. And then you can take this as the official upstream repository (which you don't have write access to). Whenever somone commits to the svn, you just do hgpullsvn and it updates your mercurial repo. Then you just clone it and create branches, for example the scons branch can be easily managed like this. Then you prepare patches, against your "official local mercurial mirror", using for example "hg export", or something, those patches should be possible to apply against the svn repository as well. You sent them for review and then (you or someone else) commit them using svn, then you'll "hgpullsvn" your local mercurial mirror and merge the changes to all your other branches. Ondrej

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