= Installation procedures for the imminent ANUGA numpy release = This page describes the procedures used to install the ANUGA support packages which allow you to run numpy ANUGA on Ubuntu 8.10 (32 or 64 bit) and 32 bit Windows (XP or Vista). This page will exist until the numpy release is finalised, at which time these procedures will be moved to the ANUGA installation guide. The procedures below use various support packages such as '''numpy'''. The files containing the packages may be downloaded from [https://sourceforge.net/projects/anuga/ SourceForge] in the [https://sourceforge.net/project/showfiles.php?group_id=172848&package_id=326049 numpy_support_software] package. Source package installations require you to unpack a *.tgz file. It doesn't matter ''where'' you do this, as you don't need the unpacked directory after a successful installation. You could use /tmp, for instance. These procedures were written before the numpy trunk became the main branch in the repository. Any paths to numpy code mentioned here will be those in the old system. After numpy code goes into the main branch this document will be amended, but you should check the ANUGA wiki [https://datamining.anu.edu.au/anuga front page] for announcements. === Ubuntu 8.10 - 32 bit === Using the Ubuntu Synaptic package manager, install the following packages: {{{ subversion python-dev python-profiler g++ python-psyco python-numpy }}} Of course, if you prefer using the console, you could do: {{{ sudo install subversion }}} and so on. Next, you need to install !NetCDF 4.0.1 from the source package: {{{ tar xzf netcdf.tar.gz cd netcdf-4.0.1 ./configure make check sudo make install }}} Now install !ScientificPython 2.9.0: {{{ tar xzf ScientificPython-2.9.0.tar.gz cd ScientificPython-2.9.0 python setup.py build --numpy sudo python setup.py install }}} And finally, install numpy and matplotlib through Synaptic: {{{ python-matplotlib }}} === Ubuntu 8.10 - 64 bit === Using the Ubuntu Synaptic package manager, install the following packages: {{{ subversion python-dev python-profiler g++ python-numpy }}} Of course, if you prefer using the console, you could do: {{{ sudo install subversion }}} and so on. You need to specify a special flag for source package builds: {{{ export CFLAGS=-fPIC }}} Make sure that you perform any builds below in the terminal window you performed the above console command. Next, you need to install !NetCDF 4.0.1 from the source package: {{{ tar xzf netcdf.tar.gz cd netcdf-4.0.1 ./configure make check sudo make install }}} Now install !ScientificPython 2.9.0: {{{ tar xzf ScientificPython-2.9.0.tar.gz cd ScientificPython-2.9.0 python setup.py build --numpy sudo python setup.py install }}} And finally, install matplotlib through Synaptic: {{{ python-matplotlib }}} === Windows === = Testing the installation = === Ubuntu === Before testing, you must have installed the ANUGA system. How to get the source code is documented elsewhere, but to be brief, you can either download the latest '''numpy''' release package and unpack it into the suggested place ({{{/usr/lib/python2.5/site-packages}}}), or you can get the numpy source tree through subversion. If you get the numpy ANUGA system through subversion, you will probably download the {{{branches/numpy}}} source tree to a place of your choice, say {{{~/ANUGA}}}. In this case you need to set the PYTHONPATH environment variable to run ANUGA: {{{ cd ~/ANUGA svn co https://datamining.anu.edu.au/svn/ga/branches/numpy svn co https://datamining.anu.edu.au/svn/ga/branches/numpy_anuga_validation # need to validate ANUGA export PYTHONPATH=~/ANUGA/numpy }}} To test your ANUGA install, do: {{{ cd ~/ANUGA/numpy/anuga python compile_all.py python test_all.py }}} To validate ANUGA, do: {{{ cd ~/ANUGA/numpy_anuga_validation/automated_validation_tests python validate_all.py }}} === Windows === Before testing, you must have installed the ANUGA system. How to get the source code is documented elsewhere, but to be brief, you can either download the latest '''numpy''' release package and unpack it into the suggested place ({{{/usr/lib/python2.5/site-packages}}}), or you can get the numpy source tree through subversion. If you get the numpy ANUGA system through subversion, you will probably download the {{{branches/numpy}}} source tree to a place of your choice, say {{{~/ANUGA}}}. In this case you need to set the PYTHONPATH environment variable to run ANUGA: {{{ cd ~/ANUGA svn co https://datamining.anu.edu.au/svn/ga/branches/numpy svn co https://datamining.anu.edu.au/svn/ga/branches/numpy_anuga_validation # need to validate ANUGA export PYTHONPATH=~/ANUGA/numpy }}} To test your ANUGA install, do: {{{ cd ~/ANUGA/numpy/anuga python compile_all.py python test_all.py }}} To validate ANUGA, do: {{{ cd ~/ANUGA/numpy_anuga_validation/automated_validation_tests python validate_all.py }}}