Changes between Version 39 and Version 40 of NumpyInstall

Timestamp:

Jun 11, 2009, 2:41:04 PM (15 years ago)

Author:

rwilson

Comment:

--

NumpyInstall

@@ -27 +27 @@
 * [wiki:NumpyUbuntuTest Ubuntu - post-installation test and validation]
 * [wiki:NumpyWindowsTest Windows - post-installation test and validation]
-
-=== 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 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
-}}}
-Note: you must execute the above console command in any terminal in which you do the NetCDF and
-!ScientificPython source builds (below).
-
-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 ===
-
-Install python 2.5:
-{{{
-execute python-2.5.4.msi
-}}}
-and add ';C:\python25' to the end of the PATH environmental variable.
-
-Install the MinGW package (requires an internet connection) by:
-{{{
-execute MinGW-5.1.4.exe
- . install MinGW base tools
- . g++ compiler
- . MinGW Make
-}}}
-and add ';C:\MinGW\bin' to the end of the PATH environmental variable.
-
-Install numpy:
-{{{
-execute numpy-1.3.0-win32-superpack-python2.5.exe
-}}}
-
-install NetCDF4:
-{{{
-execute netCDF_binary_4.0.exe
-}}}
-and add ';C:\netcdf4\bin' to the end of the PATH environmental variable
-
-Install !ScientificPython:
-{{{
-execute ScientificPython-2.9.0.win32-py2.5.exe
-}}}
-
-install psyco:
-{{{
-execute psyco-1.6.win32-py25.exe
-}}}
-This is not strictly required, but it's small and speeds up your ANUGA system.
-
-Install matplotlib:
-{{{
-execute matplotlib-0.98.5.2.win32-py2.5.exe
-}}}
-
-= 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
-}}}
-Note that the PYTHONPATH environment variable needs to be persistent, so you might consider putting the
-above command in the appropriate file (~/.bashrc, etc).
-
-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 ({{{C:\Python25\Lib\site-packages}}}), or you can get the numpy source
-tree through subversion.  Follow the test and validation precodures in the current installation guide
-if you go this way.
-
-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 {{{C:\ANUGA}}}.  In this case you need to set the PYTHONPATH
-environment variable to run ANUGA:
-{{{
-cd C:\ANUGA
-checkout https://datamining.anu.edu.au/svn/ga/branches/numpy
-checkout https://datamining.anu.edu.au/svn/ga/branches/numpy_anuga_validation  # needed to validate ANUGA
-set PYTHONPATH environment variable to C:\ANUGA\numpy
-}}}
-The Windows Tortoise SVN client can be used to access the repository.
-
-To test your ANUGA install, do:
-{{{
-cd C:\ANUGA\numpy\anuga
-python compile_all.py
-python test_all.py
-}}}
-
-To validate ANUGA, do:
-{{{
-cd C:\ANUGA\numpy_anuga_validation\automated_validation_tests
-python validate_all.py
-}}}