Re: [Numpy-discussion] Proposed Roadmap Overview
On Tue, Feb 21, 2012 at 4:04 AM, Travis Oliphant tra...@continuum.io wrote: It uses llvm-py (modified to work with LLVM 3.0) and code I wrote to do the translation from Python byte-code to LLVM. This LLVM can then be JITed. I have several applications that I would like to use this for. It would be possible to write more of NumPy using this approach. Initially, it makes it *very* easy to create a machine-code ufunc from Python code. There are other use-cases of having loops written in Python and plugged in to a calculation, filtering, or indexing framework that this system will be useful for. Very neat! It's interesting that you decided to use Python bytecode as your source representation. I'm curious what your strategy is for overcoming all the challenges that have plagued previous attempts to efficiently compile real Python? (Unladen Swallow, PyPy, etc.) Just support some subset of the language that's easy to handle and do type inference over? Or do you plan to continue using Python as your input language? I guess the conventional wisdom would be that there's a lot of potential for using LLVM to generate efficient specialized loops for numpy on the fly (cf. llvm-pipe for a similar and successful project), but that the key would be to use a more specialized representation than Python bytecode -- one that left out hard/irrelevant parts of the language, that had richer type information, that didn't change around for different Python releases, etc. -- Nathaniel ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] is there an efficient way to get a random set of subsets/combinations?
Thank you guys for replies! On Mon, 20 Feb 2012, Christopher Jordan-Squire wrote: If you're using numpy 2.0 (the development branch), the function numpy.random.choice might do what you're looking for. yeap -- handy one, although would require manual control over repetitions lazy me was trying to avoid ;) On Tue, 21 Feb 2012, Val Kalatsky wrote: Hi Slava, Mom, is that you? ;-) Since your k is only 10, here is a�quickie: import numpy as np arr = np.arange(n) for i in range(k): � � np.random.shuffle(arr) � � print np.sort(arr[:p]) If your ever get non-unique entries in a set of k=10 for your n and p, consider yourself lucky:) well -- I just thought that there might be an ideal function which in limit would return all combinations if given large enough k for reasonably small (n, p)... but indeed I should just put a logic in place to treat those cases separately. -- =--= Keep in touch www.onerussian.com Yaroslav Halchenko www.ohloh.net/accounts/yarikoptic ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Where is arrayobject.h?
What is the correct way to find the installed location of arrayobject.h? On fedora, I had been using: (via scons): import distutils.sysconfig PYTHONINC = distutils.sysconfig.get_python_inc() PYTHONLIB = distutils.sysconfig.get_python_lib(1) NUMPYINC = PYTHONLIB + '/numpy/core/include' But on ubuntu, this fails. It seems numpy was installed into /usr/local/lib/..., while PYTHONLIB expands to /usr/lib/python2.7/dist-packages. Is there a universal method? ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Where is arrayobject.h?
On 21/02/2012 19:26, Neal Becker wrote: What is the correct way to find the installed location of arrayobject.h? On fedora, I had been using: (via scons): import distutils.sysconfig PYTHONINC = distutils.sysconfig.get_python_inc() PYTHONLIB = distutils.sysconfig.get_python_lib(1) NUMPYINC = PYTHONLIB + '/numpy/core/include' But on ubuntu, this fails. It seems numpy was installed into /usr/local/lib/..., while PYTHONLIB expands to /usr/lib/python2.7/dist-packages. Is there a universal method? I use: import numpy numpy.get_include() If that is universal I cannot tell. Armando ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Proposed Roadmap Overview
On Sun, Feb 19, 2012 at 05:44:27AM -0500, David Warde-Farley wrote: I think the comments about the developer audience NumPy will attract are important. There may be lots of C++ developers out there, but the intersection of (truly competent in C++) and (likely to involve oneself in NumPy development) may well be quite small. That's a very valid concern. It is reminiscent of a possible cause to our lack of contributors to Mayavi: contributing to Mayavi requires knowing VTK. One of the major benefits of Mayavi is that it makes it is to use the power of VTK without understanding it well. The intersection of the people interested in using Mayavi and able to contribute to it is almost empty. This is stricking to me, because I know a lot of who know VTK well. Most of them couldn't care less for Mayavi: they are happy coding directly in VTK in C++. This is also a reason why I don't code UIs any more: I simply cannot find the resource to maintain them in proportion with the number of users that they garner. A sad statement. Gael ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Live coding demonstration
This is the sort of programming environment I would love to have in python. http://flowingdata.com/2012/02/20/live-coding-and-inventing-on-principle/ -- --- | Alan K. Jackson| To see a World in a Grain of Sand | | a...@ajackson.org | And a Heaven in a Wild Flower, | | www.ajackson.org | Hold Infinity in the palm of your hand | | Houston, Texas | And Eternity in an hour. - Blake | --- ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
