Changes between Version 39 and Version 40 of NumpyInstall


Ignore:
Timestamp:
Jun 11, 2009, 2:41:04 PM (13 years ago)
Author:
rwilson
Comment:

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  • NumpyInstall

    v39 v40  
    2727* [wiki:NumpyUbuntuTest Ubuntu - post-installation test and validation]
    2828* [wiki:NumpyWindowsTest Windows - post-installation test and validation]
    29 
    30 === Ubuntu 8.10 - 32 bit ===
    31 
    32 Using the Ubuntu Synaptic package manager, install the following packages:
    33 {{{
    34 subversion
    35 python-dev
    36 python-profiler
    37 g++
    38 python-psyco
    39 python-numpy
    40 }}}
    41 
    42 Of course, if you prefer using the console, you could do:
    43 {{{
    44 sudo install subversion
    45 }}}
    46 and so on.
    47 
    48 Next, you need to install NetCDF 4.0.1 from the source package:
    49 {{{
    50 tar xzf netcdf.tar.gz
    51 cd netcdf-4.0.1
    52 ./configure
    53 make check
    54 sudo make install
    55 }}}
    56 
    57 Now install !ScientificPython 2.9.0:
    58 {{{
    59 tar xzf ScientificPython-2.9.0.tar.gz
    60 cd ScientificPython-2.9.0
    61 python setup.py build --numpy
    62 sudo python setup.py install
    63 }}}
    64 
    65 And finally, install matplotlib through Synaptic:
    66 {{{
    67 python-matplotlib
    68 }}}
    69 
    70 === Ubuntu 8.10 - 64 bit ===
    71 
    72 Using the Ubuntu Synaptic package manager, install the following packages:
    73 {{{
    74 subversion
    75 python-dev
    76 python-profiler
    77 g++
    78 python-numpy
    79 }}}
    80 
    81 Of course, if you prefer using the console, you could do:
    82 {{{
    83 sudo install subversion
    84 }}}
    85 and so on.
    86 
    87 You need to specify a special flag for source package builds:
    88 {{{
    89 export CFLAGS=-fPIC
    90 }}}
    91 Note: you must execute the above console command in any terminal in which you do the NetCDF and
    92 !ScientificPython source builds (below).
    93 
    94 Next, you need to install NetCDF 4.0.1 from the source package:
    95 {{{
    96 tar xzf netcdf.tar.gz
    97 cd netcdf-4.0.1
    98 ./configure
    99 make check
    100 sudo make install
    101 }}}
    102 
    103 Now install !ScientificPython 2.9.0:
    104 {{{
    105 tar xzf ScientificPython-2.9.0.tar.gz
    106 cd ScientificPython-2.9.0
    107 python setup.py build --numpy
    108 sudo python setup.py install
    109 }}}
    110 
    111 And finally, install matplotlib through Synaptic:
    112 {{{
    113 python-matplotlib
    114 }}}
    115 
    116 === Windows ===
    117 
    118 Install python 2.5:
    119 {{{
    120 execute python-2.5.4.msi
    121 }}}
    122 and add ';C:\python25' to the end of the PATH environmental variable.
    123 
    124 Install the MinGW package (requires an internet connection) by:
    125 {{{
    126 execute MinGW-5.1.4.exe
    127  . install MinGW base tools
    128  . g++ compiler
    129  . MinGW Make
    130 }}}
    131 and add ';C:\MinGW\bin' to the end of the PATH environmental variable.
    132 
    133 Install numpy:
    134 {{{
    135 execute numpy-1.3.0-win32-superpack-python2.5.exe
    136 }}}
    137 
    138 install NetCDF4:
    139 {{{
    140 execute netCDF_binary_4.0.exe
    141 }}}
    142 and add ';C:\netcdf4\bin' to the end of the PATH environmental variable
    143 
    144 Install !ScientificPython:
    145 {{{
    146 execute ScientificPython-2.9.0.win32-py2.5.exe
    147 }}}
    148 
    149 install psyco:
    150 {{{
    151 execute psyco-1.6.win32-py25.exe
    152 }}}
    153 This is not strictly required, but it's small and speeds up your ANUGA system.
    154 
    155 Install matplotlib:
    156 {{{
    157 execute matplotlib-0.98.5.2.win32-py2.5.exe
    158 }}}
    159 
    160 = Testing the installation =
    161 
    162 === Ubuntu ===
    163 
    164 Before testing, you must have installed the ANUGA system.  How to get the source code is documented
    165 elsewhere, but to be brief, you can either download the latest '''numpy''' release package and unpack
    166 it into the suggested place ({{{/usr/lib/python2.5/site-packages}}}), or you can get the numpy source
    167 tree through subversion.
    168 
    169 If you get the numpy ANUGA system through subversion, you will probably download the {{{branches/numpy}}}
    170 source tree to a place of your choice, say {{{~/ANUGA}}}.  In this case you need to set the PYTHONPATH
    171 environment variable to run ANUGA:
    172 {{{
    173 cd ~/ANUGA
    174 svn co https://datamining.anu.edu.au/svn/ga/branches/numpy
    175 svn co https://datamining.anu.edu.au/svn/ga/branches/numpy_anuga_validation  # need to validate ANUGA
    176 export PYTHONPATH=~/ANUGA/numpy
    177 }}}
    178 Note that the PYTHONPATH environment variable needs to be persistent, so you might consider putting the
    179 above command in the appropriate file (~/.bashrc, etc).
    180 
    181 To test your ANUGA install, do:
    182 {{{
    183 cd ~/ANUGA/numpy/anuga
    184 python compile_all.py
    185 python test_all.py
    186 }}}
    187 
    188 To validate ANUGA, do:
    189 {{{
    190 cd ~/ANUGA/numpy_anuga_validation/automated_validation_tests
    191 python validate_all.py
    192 }}}
    193 
    194 === Windows ===
    195 
    196 Before testing, you must have installed the ANUGA system.  How to get the source code is documented
    197 elsewhere, but to be brief, you can either download the latest '''numpy''' release package and unpack
    198 it into the suggested place ({{{C:\Python25\Lib\site-packages}}}), or you can get the numpy source
    199 tree through subversion.  Follow the test and validation precodures in the current installation guide
    200 if you go this way.
    201 
    202 If you get the numpy ANUGA system through subversion, you will probably download the {{{branches/numpy}}}
    203 source tree to a place of your choice, say {{{C:\ANUGA}}}.  In this case you need to set the PYTHONPATH
    204 environment variable to run ANUGA:
    205 {{{
    206 cd C:\ANUGA
    207 checkout https://datamining.anu.edu.au/svn/ga/branches/numpy
    208 checkout https://datamining.anu.edu.au/svn/ga/branches/numpy_anuga_validation  # needed to validate ANUGA
    209 set PYTHONPATH environment variable to C:\ANUGA\numpy
    210 }}}
    211 The Windows Tortoise SVN client can be used to access the repository.
    212 
    213 To test your ANUGA install, do:
    214 {{{
    215 cd C:\ANUGA\numpy\anuga
    216 python compile_all.py
    217 python test_all.py
    218 }}}
    219 
    220 To validate ANUGA, do:
    221 {{{
    222 cd C:\ANUGA\numpy_anuga_validation\automated_validation_tests
    223 python validate_all.py
    224 }}}