Jupyter notebook and web UI for modelling visualising DNA concentration over time.

While developing the workflow, we are using a Jupyter notebook. Assuming you have your Python sci dev environment set up (Python 3.5 was used during development), you can start it from the root of the git repository with:

jupyter notebook --notebook-dir=./notebook

And see it in your browser at http://127.0.0.1:8888/.

If you just want to view the contents, you can see it here without installing anything.

Assuming a Python sci/dev environment, which would on e.g. OS X be more or less:

• install OS X command line tools (or Xcode)

• install Homebrew

• install some binary dependencies

   brew install python3 gcc freetype
  

• install some Python global dependencies

   pip install virtualenvwrapper
  

Get ready:

mkvirtualenv -p /usr/bin/python3 TruePCR
pip install -r requirements/dev.txt
npm install
bower install
grunt build

See if any migrations are necessary:

./manage.py migrate

Link up your front+backend:

util/bootstrap.sh

Then in one tab spin up the frontend workflow:

grunt serve

And in another the backend workflow:

./manage.py runserver_plus

Everything the same, except:

pip install -r requirements/prod.txt
util/boostrap.sh prod

Or use the prod brunch:

grunt publish
cd prod
git checkout prod
./manage.py runserver

To deploy to Heroku, from the repo root run:

grunt publish
(cd prod; git push heroku prod:master)