[Numpy-discussion] Ternary plots anywhere?
Dear all, Perhaps this is a bit off topic for the mailing list, but this is probably the only mailing list that is common to users of all python plotting packages. I am trying to find a python implementation of ternary/triangular plots: http://en.wikipedia.org/wiki/Ternary_plot but I have been unsuccessful. Is there any on-going project around? Thanks for your time. Best regards, Armando ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [ANN] Bento (ex-toydist) 0.0.3
David Cournapeau wrote: On Fri, Jul 2, 2010 at 1:56 PM, Robert Pyle rp...@post.harvard.edu wrote: Hi, While I agree that toydist needs a new name, Bento might not be a good choice. It's already the name of a database system for Macintosh from Filemaker, an Apple subsidiary. I'd be *very* surprised if the name Bento is not copyrighted. Can you copyright a word ? I thought this was the trademark part of the law. For example, linux is a trademark owned by Linus Torvald. Also, well known packages use words which are at least as common as bento in English (sphinx, twisted, etc...), and as likely to be trademarked. But IANAL... There's been lots of discussions about this on the Sage list, since there's lots of software called Sage. It seems that the consensus of IANAL advice on that list is that as long as they're not competing in the same market they're OK. For instance, there's been some talk about whether it's OK to include economics utilities in Sage since there's an accounting software (?) called Sage -- that sort of thing. Thanks for your work David, I'll make sure to check it out soon! Dag Sverre ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [ANN] Bento (ex-toydist) 0.0.3
On 07/02/2010 05:05 PM, Dag Sverre Seljebotn wrote: David Cournapeau wrote: On Fri, Jul 2, 2010 at 1:56 PM, Robert Pylerp...@post.harvard.edu wrote: Hi, While I agree that toydist needs a new name, Bento might not be a good choice. It's already the name of a database system for Macintosh from Filemaker, an Apple subsidiary. I'd be *very* surprised if the name Bento is not copyrighted. Can you copyright a word ? I thought this was the trademark part of the law. For example, linux is a trademark owned by Linus Torvald. Also, well known packages use words which are at least as common as bento in English (sphinx, twisted, etc...), and as likely to be trademarked. But IANAL... There's been lots of discussions about this on the Sage list, since there's lots of software called Sage. It seems that the consensus of IANAL advice on that list is that as long as they're not competing in the same market they're OK. For instance, there's been some talk about whether it's OK to include economics utilities in Sage since there's an accounting software (?) called Sage -- that sort of thing. Thanks. that's useful to know. Thanks for your work David, I'll make sure to check it out soon! Note that cython setup.py can be automatically converted - there is a small issue with the setup docstring which contains rest syntax incompatible with bento.info format (when empty lines has a different amount of space than the current indentation). But once you manually edit those, you can build egg, windows installer and install cython. In particular, the cython script is exucutablified like setuptools does, so cython is a bit more practical to use on windows. cheers, David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] memory leak using numpy and cvxopt
Hi all, I am hitting a memory leak with the combination of numpy and cvxopt.matrix. As I am not where it occurs, I am cross posting. On my machine (Fedora 13, x86_64) this example quickly eats up all my memory. --- from cvxopt import matrix import numpy as np N = 2000 X = np.ones((N, N)) Y = matrix(0.0, (N, N)) while True: Y[:N, :N] = X --- I don't hit the leak if copy blocks of 1-d arrays. Regards, Tillmann ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [ANN] Bento (ex-toydist) 0.0.3
On Jul 2, 2010, at 1:11 AM, David Cournapeau wrote: On Fri, Jul 2, 2010 at 1:56 PM, Robert Pyle rp...@post.harvard.edu wrote: Hi, While I agree that toydist needs a new name, Bento might not be a good choice. It's already the name of a database system for Macintosh from Filemaker, an Apple subsidiary. I'd be *very* surprised if the name Bento is not copyrighted. Can you copyright a word ? I thought this was the trademark part of the law. For example, linux is a trademark owned by Linus Torvald. Also, well known packages use words which are at least as common as bento in English (sphinx, twisted, etc...), and as likely to be trademarked. But IANAL... cheers, David It was very late last night when I wrote. I meant to say 'trademark' rather than 'copyright'. But IANAL, also. Bob ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [ANN] Bento (ex-toydist) 0.0.3
Hi, Can you copyright a word ? I thought this was the trademark part of the law. For example, linux is a trademark owned by Linus Torvald. Also, well known packages use words which are at least as common as bento in English (sphinx, twisted, etc...), and as likely to be trademarked. I got ripely panned for doing this before, but... If you have a look at - to reduce controversy - : http://cyber.law.harvard.edu/metaschool/fisher/domain/tm.htm#7 you'll see a summary of the criteria used. I read this stuff as meaning that, if you're doing something that has a low 'likelihood of confusion' with the other guy / gal doing 'Bento', and the other 'Bento' trademark is not 'famous', you're probably, but not certainly, safe from successful prosecution. See you, Matthew ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] memory leak using numpy and cvxopt
Fri, 02 Jul 2010 14:56:47 +0200, Tillmann Falck wrote: I am hitting a memory leak with the combination of numpy and cvxopt.matrix. As I am not where it occurs, I am cross posting. Probably a bug in cvxopt, as also the following leaks memory: from cvxopt import matrix N = 2000 X = [0]*N Y = matrix(0.0, (N, N)) while True: Y[:N, :1] = X -- Pauli Virtanen ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] OT: request help building pymex win64
Hi, Sorry for the offtopic post but I wondered if any Windows experts who are familiar with topics like linking python on windows and visual studio runtimes etc. might be able to help. I'm on a bit of a mission to get pymex built for 64 bit windows. Pymex ( http://github.com/kw/pymex ) is a matlab package that embeds the Python interpreter in a mex file and provides a very elegant interface for manipulating python objects from matlab, as well as converting between data times when necessary. It builds easily on mac, linux and win32 with mingw, but I really need it also for 64 bit windows. (It works very well with numpy as well so not completely OT). I have looked at trying to get a 64bit mingw working to build mex files, but that seemed quite difficult, so instead I am trying to build with VS 2008 Express Edition + Windows 7 SDK (for 64 bit support). As far as I can tell this is installed OK as I can build the example mex64 files OK. I have made some modifications to pymex to get it to build under vs 2008 ( http://github.com/robince/pymex/tree/win64 ). And I can get it to build and link (I believe using the implicit dll method of linking against C:\Python26\libs\python26.lib of the amd64 python.org python) without errors, but when I run it seems to segfaults whenever a pointer is passed between the mex side and python26.dll. I asked this stackoverflow question which has some more details (build log) http://stackoverflow.com/questions/3167134/trying-to-embed-python-into-matlab-mex-win64 Anyway I'm completely in the dark but wondered if some of the experts on here would be able to spot something (perhaps to do with incompatible C runtimes - I am not sure what runtime Python is built with but I thought it was VS 2008). Cheers Robin ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] OT: request help building pymex win64
On Sat, Jul 3, 2010 at 1:37 AM, Robin robi...@gmail.com wrote: Hi, Sorry for the offtopic post but I wondered if any Windows experts who are familiar with topics like linking python on windows and visual studio runtimes etc. might be able to help. I'm on a bit of a mission to get pymex built for 64 bit windows. Pymex ( http://github.com/kw/pymex ) is a matlab package that embeds the Python interpreter in a mex file and provides a very elegant interface for manipulating python objects from matlab, as well as converting between data times when necessary. It builds easily on mac, linux and win32 with mingw, but I really need it also for 64 bit windows. (It works very well with numpy as well so not completely OT). I have looked at trying to get a 64bit mingw working to build mex files, but that seemed quite difficult, so instead I am trying to build with VS 2008 Express Edition + Windows 7 SDK (for 64 bit support). As far as I can tell this is installed OK as I can build the example mex64 files OK. I have made some modifications to pymex to get it to build under vs 2008 ( http://github.com/robince/pymex/tree/win64 ). And I can get it to build and link (I believe using the implicit dll method of linking against C:\Python26\libs\python26.lib of the amd64 python.org python) without errors, but when I run it seems to segfaults whenever a pointer is passed between the mex side and python26.dll. I asked this stackoverflow question which has some more details (build log) http://stackoverflow.com/questions/3167134/trying-to-embed-python-into-matlab-mex-win64 Anyway I'm completely in the dark but wondered if some of the experts on here would be able to spot something (perhaps to do with incompatible C runtimes - I am not sure what runtime Python is built with but I thought it was VS 2008). The problem may be that matlab is built with one runtime, and Python with another Unless your matlab is very recent, it is actually quite likely to be compiled with VS 2005, which means you should use python 2.5 instead (or built python2.6 with VS 2005, but I am not sure it is even possible without herculean efforts). David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] OT: request help building pymex win64
On Fri, Jul 2, 2010 at 5:47 PM, David Cournapeau courn...@gmail.com wrote: The problem may be that matlab is built with one runtime, and Python with another Unless your matlab is very recent, it is actually quite likely to be compiled with VS 2005, which means you should use python 2.5 instead (or built python2.6 with VS 2005, but I am not sure it is even possible without herculean efforts). Thanks for your help! I thought of that, but then VS 2008 is an officially supported compiler for the version of matlab I am using (2009a). http://www.mathworks.com/support/compilers/release2009a/win64.html So I thought on the matlab/mex side 2008 should be fine, and I thought since Python is built with 2008 that should also be OK. But obviously something isn't! Cheers Robin ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] OT: request help building pymex win64
That's an excellent point. I've noticed on my (Linux) workstation that pymex works fine, but PyCUDA fails to import properly, because PyCUDA is a Boost::Python project and expects a different libstdc++ than the one that MATLAB jams into its LD_LIBRARY_PATH. (I got around this using an evil LD_PRELOAD, but that's another story) So yeah. Robin has been converting my C99isms C++-isms to get the Visual Studio compiler to accept it - and in the process, I suppose, adding a libstdc++ dependency that wasn't there to begin with that MATLAB doesn't like. Anyone know if there's a switch somewhere to get VS 2008 to accept some semblance of C99 source? Otherwise you might need to convert those bits into valid C89. I really need to convert this thing into Cython some day. On Fri, Jul 2, 2010 at 12:47 PM, David Cournapeau courn...@gmail.com wrote: On Sat, Jul 3, 2010 at 1:37 AM, Robin robi...@gmail.com wrote: Hi, Sorry for the offtopic post but I wondered if any Windows experts who are familiar with topics like linking python on windows and visual studio runtimes etc. might be able to help. I'm on a bit of a mission to get pymex built for 64 bit windows. Pymex ( http://github.com/kw/pymex ) is a matlab package that embeds the Python interpreter in a mex file and provides a very elegant interface for manipulating python objects from matlab, as well as converting between data times when necessary. It builds easily on mac, linux and win32 with mingw, but I really need it also for 64 bit windows. (It works very well with numpy as well so not completely OT). I have looked at trying to get a 64bit mingw working to build mex files, but that seemed quite difficult, so instead I am trying to build with VS 2008 Express Edition + Windows 7 SDK (for 64 bit support). As far as I can tell this is installed OK as I can build the example mex64 files OK. I have made some modifications to pymex to get it to build under vs 2008 ( http://github.com/robince/pymex/tree/win64 ). And I can get it to build and link (I believe using the implicit dll method of linking against C:\Python26\libs\python26.lib of the amd64 python.org python) without errors, but when I run it seems to segfaults whenever a pointer is passed between the mex side and python26.dll. I asked this stackoverflow question which has some more details (build log) http://stackoverflow.com/questions/3167134/trying-to-embed-python-into-matlab-mex-win64 Anyway I'm completely in the dark but wondered if some of the experts on here would be able to spot something (perhaps to do with incompatible C runtimes - I am not sure what runtime Python is built with but I thought it was VS 2008). The problem may be that matlab is built with one runtime, and Python with another Unless your matlab is very recent, it is actually quite likely to be compiled with VS 2005, which means you should use python 2.5 instead (or built python2.6 with VS 2005, but I am not sure it is even possible without herculean efforts). David ___ 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] OT: request help building pymex win64
On Sat, Jul 3, 2010 at 1:58 AM, Robin robi...@gmail.com wrote: On Fri, Jul 2, 2010 at 5:47 PM, David Cournapeau courn...@gmail.com wrote: The problem may be that matlab is built with one runtime, and Python with another Unless your matlab is very recent, it is actually quite likely to be compiled with VS 2005, which means you should use python 2.5 instead (or built python2.6 with VS 2005, but I am not sure it is even possible without herculean efforts). Thanks for your help! I thought of that, but then VS 2008 is an officially supported compiler for the version of matlab I am using (2009a). http://www.mathworks.com/support/compilers/release2009a/win64.html What mathworks means by supported may not include what you are doing, though. Generally,on windows, people design API to be independent of runtimes (because you more or less have to), and do not use much of the standard C library anyway. This is not true for python. IOW, supporting VS 2008 does not mean built with 2008, that's a limitation of python (and also caused by the desire of MS to complete screw up the C library, but that's another story). Also, matlab could be built with 2008, and not use the same runtime as python. Even if the same version is used in both python and matlab, but the process uses two copies, the issues remain the same. You should use depends.exe to check for this (and maybe the MS debugger as well). Also, I would double check the issue is not something else altogether, David ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [Matplotlib-users] Vectorization
I am moving this over to numpy-discussion maillist... I don't have a firm answer for you, but I did notice one issue in your code. You call arange(len(dx) - 1) for your loops, but you probably really need arange(1, len(dx) - 1) because you are accessing elements both after *and* before the current index. An index of -1 is actually valid because that means the last element of the array, and may not be what you intended. Ben Root On Fri, Jul 2, 2010 at 1:15 PM, Nicolas Bigaouette nbigaoue...@gmail.comwrote: Hi all, I don't really know where to ask, so here it is. I was able to vectorize the normalization calculation in quantum mechanics: phi|phi. Basically it's a volume integral of a scalar field. Using: norm = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): norm += psi[k,j,i]**2 * dx[i] * dy[j] * dz[k] if dead slow. I replaced that with: norm = (psi**2 * dx*dy[:,numpy.newaxis]*dz[:,numpy.newaxis,numpy.newaxis]).sum() which is almost instantanious. I want to do the same for the calculation of the kinetic energy: phi|p^2|phi/2m. There is a laplacian in the volume integral which complicates things: K = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): K += -0.5 * m * phi[k,j,i] * ( (phi[k,j,i-1] - 2.0*phi[k,j,i] + phi[k,j,i+1]) / dx[i]**2 + (phi[k,j-1,i] - 2.0*phi[k,j,i] + phi[k,j+1,i]) / dy[j]**2 + (phi[k-1,j,i] - 2.0*phi[k,j,i] + phi[k+1,j,i]) / dz[k]**2 ) My question is, how would I vectorize such loops? I don't know how I would manage the numpy.newaxis code-foo with neighbours dependency... Any idea? Thanx! -- This SF.net email is sponsored by Sprint What will you do first with EVO, the first 4G phone? Visit sprint.com/first -- http://p.sf.net/sfu/sprint-com-first ___ Matplotlib-users mailing list matplotlib-us...@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [Matplotlib-users] Vectorization
On Fri, Jul 2, 2010 at 11:33 AM, Benjamin Root ben.r...@ou.edu wrote: I am moving this over to numpy-discussion maillist... I don't have a firm answer for you, but I did notice one issue in your code. You call arange(len(dx) - 1) for your loops, but you probably really need arange(1, len(dx) - 1) because you are accessing elements both after *and* before the current index. An index of -1 is actually valid because that means the last element of the array, and may not be what you intended. Ben Root On Fri, Jul 2, 2010 at 1:15 PM, Nicolas Bigaouette nbigaoue...@gmail.com wrote: Hi all, I don't really know where to ask, so here it is. I was able to vectorize the normalization calculation in quantum mechanics: phi|phi. Basically it's a volume integral of a scalar field. Using: norm = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): norm += psi[k,j,i]**2 * dx[i] * dy[j] * dz[k] if dead slow. I replaced that with: norm = (psi**2 * dx*dy[:,numpy.newaxis]*dz[:,numpy.newaxis,numpy.newaxis]).sum() which is almost instantanious. I want to do the same for the calculation of the kinetic energy: phi|p^2|phi/2m. There is a laplacian in the volume integral which complicates things: K = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): K += -0.5 * m * phi[k,j,i] * ( (phi[k,j,i-1] - 2.0*phi[k,j,i] + phi[k,j,i+1]) / dx[i]**2 + (phi[k,j-1,i] - 2.0*phi[k,j,i] + phi[k,j+1,i]) / dy[j]**2 + (phi[k-1,j,i] - 2.0*phi[k,j,i] + phi[k+1,j,i]) / dz[k]**2 ) My question is, how would I vectorize such loops? I don't know how I would manage the numpy.newaxis code-foo with neighbours dependency... Any idea? If no one knows how to vectorize it then one way to go is cython. If you convert your arrays to lists then it is very easy to convert the loop to cython. Fast too. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [Matplotlib-users] Vectorization
On Fri, Jul 2, 2010 at 11:45 AM, Keith Goodman kwgood...@gmail.com wrote: On Fri, Jul 2, 2010 at 11:33 AM, Benjamin Root ben.r...@ou.edu wrote: I am moving this over to numpy-discussion maillist... I don't have a firm answer for you, but I did notice one issue in your code. You call arange(len(dx) - 1) for your loops, but you probably really need arange(1, len(dx) - 1) because you are accessing elements both after *and* before the current index. An index of -1 is actually valid because that means the last element of the array, and may not be what you intended. Ben Root On Fri, Jul 2, 2010 at 1:15 PM, Nicolas Bigaouette nbigaoue...@gmail.com wrote: Hi all, I don't really know where to ask, so here it is. I was able to vectorize the normalization calculation in quantum mechanics: phi|phi. Basically it's a volume integral of a scalar field. Using: norm = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): norm += psi[k,j,i]**2 * dx[i] * dy[j] * dz[k] if dead slow. I replaced that with: norm = (psi**2 * dx*dy[:,numpy.newaxis]*dz[:,numpy.newaxis,numpy.newaxis]).sum() which is almost instantanious. I want to do the same for the calculation of the kinetic energy: phi|p^2|phi/2m. There is a laplacian in the volume integral which complicates things: K = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): K += -0.5 * m * phi[k,j,i] * ( (phi[k,j,i-1] - 2.0*phi[k,j,i] + phi[k,j,i+1]) / dx[i]**2 + (phi[k,j-1,i] - 2.0*phi[k,j,i] + phi[k,j+1,i]) / dy[j]**2 + (phi[k-1,j,i] - 2.0*phi[k,j,i] + phi[k+1,j,i]) / dz[k]**2 ) My question is, how would I vectorize such loops? I don't know how I would manage the numpy.newaxis code-foo with neighbours dependency... Any idea? If no one knows how to vectorize it then one way to go is cython. If you convert your arrays to lists then it is very easy to convert the loop to cython. Fast too. Some more thoughts: you pull phi[k,j,i] four times per loop. Setting phikji = phi[k,j,i] might give a little more speed. Might also help to do stuff like phi_i = phi[:,:,i], phi_ip1 = phi[:,:,i+1], etc right after for i in range(). Also everything gets multiplied by -0.5 * m * phi so you should do that outside the loop. You can square the d's (dx, dy, and dz) outside the loop. Doing all these and then using cython should makes things very fast. ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [Matplotlib-users] Vectorization
On 07/02/2010 01:45 PM, Keith Goodman wrote: On Fri, Jul 2, 2010 at 11:33 AM, Benjamin Rootben.r...@ou.edu wrote: I am moving this over to numpy-discussion maillist... I don't have a firm answer for you, but I did notice one issue in your code. You call arange(len(dx) - 1) for your loops, but you probably really need arange(1, len(dx) - 1) because you are accessing elements both after *and* before the current index. An index of -1 is actually valid because that means the last element of the array, and may not be what you intended. Ben Root On Fri, Jul 2, 2010 at 1:15 PM, Nicolas Bigaouettenbigaoue...@gmail.com wrote: Hi all, I don't really know where to ask, so here it is. I was able to vectorize the normalization calculation in quantum mechanics:phi|phi. Basically it's a volume integral of a scalar field. Using: norm = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): norm += psi[k,j,i]**2 * dx[i] * dy[j] * dz[k] if dead slow. I replaced that with: norm = (psi**2 * dx*dy[:,numpy.newaxis]*dz[:,numpy.newaxis,numpy.newaxis]).sum() which is almost instantanious. I want to do the same for the calculation of the kinetic energy: phi|p^2|phi/2m. There is a laplacian in the volume integral which complicates things: K = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): K += -0.5 * m * phi[k,j,i] * ( (phi[k,j,i-1] - 2.0*phi[k,j,i] + phi[k,j,i+1]) / dx[i]**2 + (phi[k,j-1,i] - 2.0*phi[k,j,i] + phi[k,j+1,i]) / dy[j]**2 + (phi[k-1,j,i] - 2.0*phi[k,j,i] + phi[k+1,j,i]) / dz[k]**2 ) My question is, how would I vectorize such loops? I don't know how I would manage the numpy.newaxis code-foo with neighbours dependency... Any idea? If no one knows how to vectorize it then one way to go is cython. If you convert your arrays to lists then it is very easy to convert the loop to cython. Fast too. ___ Since things do not depend on previous results. Without thinking much can you just replace all your phi[] references to being phi[].sum()? Probably wrong but hopefully you can figure out what I mean. My reasoning is that over three loops then K = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): K += -0.5 * m * phi[k,j,i] is just sum of all the entries except the last dimension in each axis of phi ie K= -0.5 * m * phi[0:len(dz)-1, 0:len(dz)-1,0:len(dx)-1].sum() Similarity for the remaining places you have to sum the appropriate sections of the phi array. So phi[k,j,i-1] becomes something like: phi[:,:,0:i-1].sum() except you have to address the division. Therefore you have to sum over the appropriate access (phi[:,:,0:i-1].sum(axis=2)/dx[0:i-1]**2).sum() # or numpy.dot((phi[:,:,0:i-1].sum(axis=2), 1/(dx[0:i-1]**2)) Then I got confused when say i=0 because the reference phi[k,j,i-1] becomes phi[k,j,-1] - which is the last index of that axis. Is that what you meant to happen? Bruce ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] [Matplotlib-users] Vectorization
On Jul 2, 2010, at 11:33 AM, Benjamin Root wrote: I want to do the same for the calculation of the kinetic energy: phi|p^2|phi/2m. There is a laplacian in the volume integral which complicates things: K = 0.0 for i in numpy.arange(len(dx)-1): for j in numpy.arange(len(dy)-1): for k in numpy.arange(len(dz)-1): K += -0.5 * m * phi[k,j,i] * ( (phi[k,j,i-1] - 2.0*phi[k,j,i] + phi[k,j,i+1]) / dx[i]**2 + (phi[k,j-1,i] - 2.0*phi[k,j,i] + phi[k,j+1,i]) / dy[j]**2 + (phi[k-1,j,i] - 2.0*phi[k,j,i] + phi[k+1,j,i]) / dz[k]**2 ) My question is, how would I vectorize such loops? I don't know how I would manage the numpy.newaxis code-foo with neighbours dependency... Any idea? How about: K = -0.5 * m * ( phi[1:-1,1:-1,1:-1] * ( np.diff(phi[1:-1,1:-1,:], 2, 2) / dx[None,None,1:-1]**2 + np.diff(phi[1:-1,:,1:-1], 2, 1) / dy[None,1:-1,None]**2 + np.diff(phi[:,1:-1,1:-1], 2, 0) / dz[1:-1,None,None]**2 ) ).sum() (Not tested) ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] cython and f2py
Hi All, Sorry if this has been documented or discussed already, but my searches have come up short. Can someone please recommend a way to setup both Cython and Fortran extensions in a single package with numpy.distutils (or something else)? E.g.: from numpy.distutils.core import setup, Extension ext_modules = [ Extension( 'cext', ['cext.pyx'] ), Extension( 'fext', ['fext.f90'] ), ] setup( name = 'test', ext_modules = ext_modules, ) Can numpy.distutils be directed to process *.pyx with Cython rather than Pyrex? Is is kosher to call setup twice in the same script, once for Fortran, and once for Cython using Cython.Distutils.build_ext, or would that do bad things? I guess I could just pre-process the Cython stuff, and have distutils work with the generated C, but I don't like that as much. I am using numpy version 1.4.0, but can update to the development version if that helps. Thanks, Geoff ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] cython and f2py
On Fri, Jul 2, 2010 at 12:53 PM, Geoffrey Ely g...@usc.edu wrote: Hi All, Sorry if this has been documented or discussed already, but my searches have come up short. Can someone please recommend a way to setup both Cython and Fortran extensions in a single package with numpy.distutils (or something else)? E.g.: from numpy.distutils.core import setup, Extension ext_modules = [ Extension( 'cext', ['cext.pyx'] ), Extension( 'fext', ['fext.f90'] ), ] setup( name = 'test', ext_modules = ext_modules, ) Can numpy.distutils be directed to process *.pyx with Cython rather than Pyrex? Is is kosher to call setup twice in the same script, once for Fortran, and once for Cython using Cython.Distutils.build_ext, or would that do bad things? I guess I could just pre-process the Cython stuff, and have distutils work with the generated C, but I don't like that as much. That's what I do. I think it is easier for users (some might not have cython). If the C extension doesn't compile I fallback to the python versions of the functions. http://github.com/kwgoodman/la/blob/master/setup.py ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] cython and f2py
Hi, Can numpy.distutils be directed to process *.pyx with Cython rather than Pyrex? Yes, but at the moment I believe you have to monkey-patch numpy distutils : see the top of http://github.com/matthew-brett/nipy/blob/master/setup.py and generate_a_pyrex_source around line 289 of: http://github.com/matthew-brett/nipy/blob/master/build_helpers.py for how we've done it - there may be a better way - please post if you find it! Best, Matthew ___ NumPy-Discussion mailing list NumPy-Discussion@scipy.org http://mail.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] PATCH: reference leaks for 'numpy.core._internal' module object
The simple test below show the issue.
import sys
import numpy as np
from numpy.core import _internal
def f(a = np.zeros(4)):
a = np.zeros(4)
b = memoryview(a)
c = np.asarray(b)
print sys.getrefcount(_internal)
while 1:
f()
The patch it trivial (I've added a little extra, unrelated NULL check):
Index: numpy/core/src/multiarray/buffer.c
===
--- numpy/core/src/multiarray/buffer.c (revision 8468)
+++ numpy/core/src/multiarray/buffer.c (working copy)
@@ -747,9 +747,13 @@
}
str = PyUString_FromStringAndSize(buf, strlen(buf));
free(buf);
+if (str == NULL) {
+return NULL;
+}
descr = (PyArray_Descr*)PyObject_CallMethod(
_numpy_internal, _dtype_from_pep3118, O, str);
Py_DECREF(str);
+Py_DECREF(_numpy_internal);
if (descr == NULL) {
PyErr_Format(PyExc_ValueError,
'%s' is not a valid PEP 3118 buffer format string, buf);
PS: I think that such implementation should at least handle the very
simple one/two character format (eg, 'i', 'f', 'd', 'Zf', 'Zd', etc.)
without calling Python code... Of course, complaints without patches
should not be taken too seriously ;-)
--
Lisandro Dalcin
---
CIMEC (INTEC/CONICET-UNL)
Predio CONICET-Santa Fe
Colectora RN 168 Km 472, Paraje El Pozo
Tel: +54-342-4511594 (ext 1011)
Tel/Fax: +54-342-4511169
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