On 14-Sep-2010 00:55, Eric Firing wrote: > On 09/13/2010 12:08 PM, Virgil Stokes wrote: >> On 2010-09-13 21:55, Benjamin Root wrote: >>> On Mon, Sep 13, 2010 at 2:38 PM, Virgil Stokes <v...@it.uu.se >>> <mailto:v...@it.uu.se>> wrote: >>> >>> I have tried to produce a very simple plot with my recent >>> installation of matplotlib (1.0.0 64-bit) and numpy (1.5.0 64-bit) >>> using the following code (taken from the matplotlib tutorial >>> material). >>> >>> *import matplotlib >>> import numpy >>> import matplotlib.pyplot as plt >>> >>> print matplotlib.__version__ >>> print numpy.__version__ >>> >>> plt.plot([1,2,3,4]) >>> plt.ylabel('some numbers') >>> plt.show()* >>> >>> If I execute this in Windows 7 (64-bit) it works correctly. If I >>> execute this in Windows Vista (32-bit) it works correctly. >>> If I execute this in Ubuntu 10.04 64-bit the versions are printed >>> out correctly and thus I believe that the packages are being >>> imported; but, /no plot is produced!/ >>> >>> Why not? >>> >>> >>> Virgil, >>> >>> Did you build matplotlib from source? >> I did try this and believe that it succeeded (saw no errors displayed >> during the build). >>> If so, then chances are that one or more backends were not built >>> properly. >> But, I do not understand what you mean here... >>> This typically happens if you do not have all the build dependencies. >> And what can I do to correct this? >>> >>> Note, the build will not necessarily fail if some dependencies are >>> missing because the core portions of matplotlib still build successfully. >> Sorry Ben, bu I do not understand what you mean here. >> Would you please explain how I can use some combination of the following >> (with Python 2.6 on Ubuntu 10.04 both 64-bit) to get a working >> matplotlib and numpy. >> >> * *python-numpy_1.4.1-4_amd64.deb* >> * *python-numpy_1.5.0-1ppa1_amd64.deb* >> * *numpy-1.5.0.tar.gz* >> >> and, >> >> * *matplotlib_0.99.3-1ubuntu1.debian.tar.gz* >> * *matplotlib_0.99.3.orig.tar.gz* >> * *matplotlib-1.0.0.tar.gz* >> >> This has become such a frustrating task that I would settle for vers. >> 0.99.3 of matplotlib and/or vers. 1.4.1-4 of numpy. I thought I >> understood Python and Ubuntu 10.04 enough to accomplish this task; but, >> obviously this was not the case. And I have looked at the FAQs and help >> given at matplotlib's homepage. > > If you would like up-to-date versions of both numpy and matplotlib, then you > can either find and install the *dev packages individually, or do something > like this: > > sudo apt-get build-dep python-matplotlib > sudo apt-get remove python Very interesting --- what do these two commands actually do? (Just a short explanation would be appreciated) > > Now untar your numpy, go in, build and install: > > setup.py build > sudo setup.py install Yes, this makes good sense... > > And last, do the same for matplotlib, preferably with a checkout from svn. > Some bugs have been fixed since the last release. Never, have installed from svn; but, I assume that there is a tar file there that I can download and use for a 64-bit Linux system. > > Before all of this, you might do well to uninstall whatever versions or parts > of numpy and matplotlib had been installed via your previous efforts. Yes, I have already done this; but, I will check this carefully again before I start the reinstallation process. > > The point of the first apt-get is to install things like freetype and the gui > toolkits. The only problem is that this also installs an old version of > numpy, hence the second apt-get command. Ok, this seems to have answered my previous question. > > The good news is that once you get over the hump of having the dependencies > installed, subsequent updates and compilations of numpy and matplotlib are > easy. It is usually advisable to delete the build directory, since setup.py > is not very smart with respect to knowing what needs to be recompiled. > Sometimes it is also necessary to clean out the old version from its > installation location. See attached script for an example of mpl > uninstallation. This is exactly where I was headed --- a complete and new mpl installation with the latest matplotlib.
Thanks for all the tips and pointing me in the correct direction. I will get back to you on how it went. --V ------------------------------------------------------------------------------ Start uncovering the many advantages of virtual appliances and start using them to simplify application deployment and accelerate your shift to cloud computing. http://p.sf.net/sfu/novell-sfdev2dev _______________________________________________ Matplotlib-users mailing list Matplotlib-users@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/matplotlib-users
