Installation¶

Firstly, you’ll need Python. This comes with pretty much every linux distribution and is also installed by default on Mac OS X. For Windows, I’d recommend using a Python distribution, such as anaconda or enthought canopy. The code should be compatible with Windows as Python and all the libraries used are platform independent. Nonetheless, I only use it on Mac OSX and Linux so I can’t guarantee that there won’t be bugs not present on other OSs.

Installation¶

Once all the requirements outlined below are met, you are ready to install Soapy. Download the source from github, either as a zip file, or clone the git repository with:

git clone https://github.com/soapy/soapy.git

If downloading the code as a zip, you can choose which version to use with the drop down box on the left of the page, entitled branch:master. Whilst I try not to, the master branch will occasionally be broken so you might want to get the latest stable version by clicking “tags” in the dropdown list, and selecting the most recent version number.

Once the code is downloaded (and unzipped) or cloned, navigate to the resulting directory using the command line. You can import it into python straight away from this directory. To use the soapy script, run:

python soapy <options> <configfile>

If you wish to have it available elsewhere on your system, either set the relavant PATH and PYTHONPATH variables to <soapy dir>/bin and <soapy dir>/ respectively, or run the install script with:

python setup.py install

This latter method may require superuser permissions for your system and should setup the paths for you. You should now be able to run soapy and import soapy into python from any directory on your system.

Required Libraries¶

soapy doesn’t have too many requirements in terms of external libraries, though it does rely on some. There are also some optional libraries which are recommended for plotting or performance.

Required¶

numpy
scipy
pyfits *or* astropy

Recommended¶

for performance¶

pyfftw (Highly Recommended!)

for gui¶

PyQt4
pyqtgraph (http://www.pyqtgraph.org)
matplotlib
ipython

Linux¶

If your starting with python from scratch, there a couple of options. For Ubuntu (14.04+) linux users, all these packages can be installed via apt-get:

sudo apt-get install python-numpy python-scipy python-fftw python-astropy python-qt4 python-matplotlib ipython ipython-qtconsole python-pyqtgraph

for Red-hat based systems these packages should also be available from repositories, though I’m not sure of they’re names. Again, get pyqtgraph from http://www.pyqtgraph.org, but download the source. pyqtgraph, like most python packages is pretty easy to install from source, just download the package, unpack, navigate into the package and run sudo python setup.py install

Mac OSX¶

for mac os, all of these packages can be install via macports, with:

sudo port install python27 py27-numpy py27-scipy py27-astropy py27-pyfftw py27-pyqt4 py27-ipython py27-pyqtgraph py27-jupyter

Any OS¶

For any OS, including Windows, python distributions exist which include lots of python packages useful for science. A couple of good examples are Enthought Canopy (https://www.enthought.com), which is free for academics, and Anaconda (https://store.continuum.io/cshop/anaconda/) which is also free.

A lot of python packages are also listed on pypi. Usually when python is installed, a script called easy_install is installed also, which can be used to get any package on pypi with easy_install <package>. Confusingly, pip is now the recommended Python package manager instead of easy_install. If you’ve only got easy_install you can install pip using easy_install pip, or it can be installed using the script linked here.

Once you have pip, the required libraries can be installed by using the requirements.txt file. From the soapy directory, just run (may need to be as sudo):

pip -r requirements.txt

and all the requirements should be installed for you!

Testing¶

Once you think everything is installed, tests can be run by navigating to the test directory and running

python testSimulation.py

Currently, this only runs system wide tests, but further, more atomic tests will be added in future. To run the tests, soapy must be either “installed”, or manually put into the PYTHONPATH.