= Installing current version of ANUGA research code on Windows  =

== Introduction ==

{{{anuga}}} is developed on Linux (Ubuntu) and hence the installation on Linux (Ubuntu) is more streamlined. But it is possible to install on windows. First you need to install the required {{{python}}} environment, then download the {{{anuga}}} source and then compile and test. The most time consuming part of the process is getting the {{{python}}} environment setup. 


== Python ==

We use {{{python}}} as our programming environment together with a number of standard python packages such as {{{numpy, scipy, matplotlib, netcdf4}}}.  One way to install all the required packages is to use a distribution like {{{python_xy}}}, {{{Anaconda}}} and the related {{{miniconda}}} environments. Also itshould be possible to download the appropriate pre-compiled packages from [http://www.lfd.uci.edu/~gohlke/pythonlibs]. I suggest {{{miniconda}}} as it allows you to only install the packages that are needed (so is a bit quicker). 

=== Miniconda ===

Download and run the [http://conda.pydata.org/miniconda.html Miniconda] installer.

Be sure to choose the win32 {{{python 2.7}}} version. This is the version for which we are developing. 

At the moment {{{anuga}}} has memory problems with {{{win64}}} so avoid that for the time being. 
You are most welcome to help track down the problems and provide a bug fix :-).

== Anuga python package dependencies ==

Assuming {{{conda}}} is now installed,  we need to install a number of other packages, via the {{{conda install}}} command. 

Fire up {{{cmd.exe}}} and install all the packages via
{{{
conda install python=2.7 pip nose numpy scipy netcdf4 matplotlib gdal
}}}

== GCC compiler ==

We need a gcc compiler with openmp support to install {{{anuga}}}. 

We suggest that you download and install the version of MinGW provided by [http://tdm-gcc.tdragon.net/ TDM-GCC].
Mark the ``openmp`` and ``gfortran`` options in the "Choose Components" part of the installation. 

We need to force the {{{python}}} installation scripts to use this compiler. Add a configuratoin file named {{{pydistutils.cfg}}} to your home directory {{{C:\Users\yourName}}} with the contents

{{{
[build]
compiler=mingw32
}}}


== Manual install ==

It is possible to install the required environment manually. You would need to install {{{Mingw}}} to provide a compiler, the standard distribution of {{{python27}}} and then precompiled python libraries for {{{numpy, scipy, matplotlib, netcdf4}}} from a site like [http://www.lfd.uci.edu/~gohlke/pythonlibs/]. It would be interesting to hear feedback on this option, as there is an opportunity to use versions using the Intel Math Kernel Library, which should provide a useful increase in speed. 


== Download ANUGA ==

You should now have all the dependencies installed. You should fire up a new {{{cmd.exe}}} and install {{{anuga}}}

First we need to get the anuga source code.

=== Zipped version ===

A zipped version of the latest development version of {{{anuga}}} is available from github at [https://github.com/GeoscienceAustralia/anuga_core/archive/master.zip] and the latest released version at sourceforge [http://sourceforge.net/projects/anuga/files/anuga_1.3/anuga_1.3.10.zip] You will need to unzip the file into a directory called {{{anuga_core}}} perhaps in your home directory.

=== Checkout anuga via svn  ===

You can also check out the anuga repository using subversion.
I suggest installing [http://tortoisesvn.net/downloads.html tortoise svn downloads] and then checking out the following svn repository.
When you installed {{{tortoise svn}}} it creates a few extra menu items to your right click menu in the file manager. Just choose "tortoise" checkout to download the code. 

{{{
https://anuga.anu.edu.au/svn/anuga/trunk/anuga_core
}}}

=== Checkout anuga via git ===

The URL for the git repository to clone is

{{{
https://github.com/GeoscienceAustralia/anuga_core.git
}}}


== Installing ANUGA ==

You should now have an anuga_core directory.

Now go to the directory anuga_core and build and install anuga.
Fire up a cmd terminal, change to the {{{anuga_core}}} directory and run

{{{
python setup.py build install
}}}

Hopefully no errors.

== Run Unit tests ==

From the anuga_core directory run the unit tests via:

{{{
python runtests.py
}}}


=== Note ===
At present the Anaconda (conda) version of {{{gdal}}} is missing the {{{gdal}}} data directory (presumably to save space). This will cause some error messages of the form "ERROR 4: Unable to open EPSG support file gcs.csv". It should be fine to disregard these errors messages. It would be possible to download the gdal data directory and point the {{{GDAL_DATA}}} environment variable to the data directory.


== Conclusion ==

Hopefully all the unit tests pass. As this is bleeding edge there are sometimes a small number of failures as this is a work in progress. Have a look at the demos in the directory anuga_core/documentation/user_manual/demos (along with the user manual) to see how to use anuga.

== Updating ==

From time to time you should update your version of anuga. This is fairly easy if you used subversion or git to obtain the source. You will then just need to {{{update}}} (with subversion) or {{{pull}}} (with git).


Then again from the {{{anuga_core}}} directory recompile the code and check the unit tests via

{{{
python setup.py install
python runtests.py
}}}