This software has been written for Python 2, but minimum work should be required to port it to Python 3. We recommend to install the dependencies of the software in a virtual environment (using the virtualenv
and virtualenvwrapper
tools).
This section assumes that the user has access to the pip
utility. Note that the pip version packaged with your distribution might be notably obsolete. In that case, pip has to be installed according to the instructions detailed in the link above.
Spot-On can be installed using pip v.9.0
or any further version.
Finally, for the exports, Spot-On relies on the Inkscape software to perform file conversions.
We first install a tool to manage Python's virtual environements: virtualenvwrapper
and create a virtualenv called fastSPT. This is only required if you want to work in a virtual environment (recommended).
pip install virtualenvwrapper
export WORKON_HOME=~/.envs
mkdir -p $WORKON_HOME
source /usr/local/bin/virtualenvwrapper.sh ## or: source ~/.local/bin/virtualenvwrapper.sh
mkvirtualenv fastSPT
Some of the dependencies might already be installed on your system, or might be directly available through your operating system's package manager. It is possible to use those provided that they are recent enough. In particular, numpy
and scipy
are fairly standard librairies and come often preinstalled with your system. Also, installing Numpy
and Scipy
require compilation tools (build-essential
, python-dev
).
You will also need the git
tool to download the files. Under Ubuntu/Debian GNU/Linux flavours, it can be installed by typing:
sudo apt-get install python-dev libffi-dev libssl-dev ## Required to compile dependencies
sudo apt-get install gfortran libopenblas-dev liblapack-dev ## Required by Scipy
sudo apt-get install git inkscape
sudo apt-get install redis-server
See this: http://docs.celeryproject.org/en/latest/userguide/configuration.html#conf-redis-result-backend
git clone https://gitlab.com/tjian-darzacq-lab/Spot-On.git
cd Spot-On
pip install pip -U # update to the last version of pip
pip install -r requirements.txt
make init ## This will download demo datasets and fitted (a,b) fitted values
tmux
export WORKON_HOME=~/.envs
source /usr/local/bin/virtualenvwrapper.sh ## or: source ~/.local/bin/virtualenvwrapper.sh
cd Spot-On/
workon fastSPT
python manage.py runserver
celery -A SPTGUI worker -l INFO # In a different terminal
Open a Django shell: python manage.py shell
and type the command: import SPTGUI.statistics_tests as stats;stats.test_statistics()
. This should run the tests for the statistics on all the existing entries of the database.