Hi, I am not sure whether this is really useful to other, but anyway: I release the first version of garnumpy, a system derived from Nick Moffit's gar system, to build a set of packages from sources. The idea is to build numpy + scipy automatically with its dependencies, like a complete LAPACK, umfpack, etc... Right now, support for ATLAS (3.7.28), NETLIB BLAS/LAPACK only is there. It can also build a FFT library (fftw3 supported for now), and a UMFPACK system. This can be useful: - if you are on distributions without a full blas/lapack or umfpack packaged on your system - with a CPU not well supported by last release of ATLAS (Core2Duo, which got a lot of improvements in the 3.7 series) - if you do not want (or like me cannot) install numpy system-wide
It has been successfully used on Fedora Core and Ubuntu with gcc+g77 or gcc+gfortran (by successfully, I mean all scipy tests passed). I don't really know if this is easier to use than building scipy/numpy by hand (it is for me, at least:) ). http://www.ar.media.kyoto-u.ac.jp/members/david/archives/garnumpy/garnumpy-0.1.tgz Here is the Readme: What is garnumpy ? Garnumpy is a system derived from the GAR system by Nick Moffitt to build a self contained scipy environment. It supports optional compilation of most scipy dependencies, including fftw3, ATLAS or NETLIB Blas and Lapack, UMFPACK. What for ? If you want to install a scipy environment, with special libraries, or libraries not packaged on your OS (full lapack using ATLAS, etc...). If you want a self contained directory where everything is installed, for easy removing later (everything in in one directory) As it installs everything in a special directory, you can use garnumpy without special rights (eg non root), and without the risk of destroying anything on your system. How to use ? Short story: cd platform/scipy; make install will install numpy, scipy and all the dependencies (by default, it will build fftw3, and NETLIB BLAS/LAPACK), if you have a "standard" GNU userland. Then, in a shell: source startgarnumpy.sh will set the necessary env variables to use scipy in the current shell. Longer story: before the above, you should: - set main_prefix and GARCHIVEROOT in gar.conf.mk to some values - make garchive will download all the sources in one step (useful if you plan on trying different build options) - if you change main_prefix, you should change accordingly startgarnumpy.sh Other variable to adjust in gar.conf.mk: - BLASLAPACK: set to the wanted BLAS/LAPACK set. By default, netlib, but atlas (for using ATLAS BLAS/LAPACK) and system (using already installed BLAS/LAPACK) are also supported. - SCIPYSANDPKG: a list of packages in scipy sandbox to install - TESTNELIB: set to 1 to test the compiled NETLIB LAPACK library - SOURCEFORGEDL: set to a proper sourceforge mirror (redirection often fail). Variable to adjust in gar.cc.mk (everything related to the build tools, mostly compiler, compiler options and link options should be set here) - CC, F77 and CXX: C, Fortran and C++ compilers You can use the two following working templates: - gar.cc.mk.g77: GNU build system with g77 for F77 code. - gar.cc.mk.gfortran: GNU build system with gfortran for all Fortran code. Supported softwares: - numpy and scipy (in platform) - ipython (in tools) - matplolib (in gui) Dependencises: UBUNTU (6.10): You can build a fully functional scipy + matplotlib by installing the following: sudo apt-get install python python-dev gcc g77 python-gtk2-dev patch swig g++ Fedora Core (6): You can build a fully functional numpy + scipy by installing the following: sudo yum install python python-devel gcc compat-gcc-34-g77 gcc-c++ swig Cheers, David _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion