Install Virtual Environment using pip:

pip install virtualenv

Cloning the app into a folder named "incdb-poc"

git clone https://github.com/UCL-CS35/incdb-poc.git incdb-poc

Create the "incdb" virtual environment

mkvirtualenv incdb

Install required Python packages

cd /path/to/incdb-poc
workon incdb
pip install -r requirements.txt

Before proceeding, it is important to note that the AFNI toolkit is currently incompatible on Windows. In order to test the merging process, the easiest suggestion is to install a Virtual Machine software (such as VirutalBox), install a free Linux distribution and run Neurosynth within the system.

The AFNI toolkit consists of various functions to read and manipulate brain imaging data (in this case, merging). To install the AFNI tool kit, follow the link below:

• https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/background_install/download_links.html

Under section B, download the package for the relevant operating system you are running the kit from, and follow this link:

• https://afni.nimh.nih.gov/pub/dist/doc/htmldoc/background_install/install_instructs/index.html

For complete installation instructions. It also to note that this process will require modifying your system’s shell (BASH or tcsh) in order to run the AFNI toolkit within Terminal. If you have completed this process and are able to run the command ‘afni’ within the Terminal, continue to the next section.

Nipype serves as a Python interface for many of AFNI’s functions (since it is not natively written in Python) in order to easily integrate the toolkit within Flask. To install nipype, run:

pip install nipype

To install the Nipype package. Nipype also requires additional dependencies to be installed as described in the link below under the ‘Dependencies’ section

• http://nipy.org/nipype/users/install.html

You can test your Nipype installation using the command :

python -c "import nipype; nipype.test()"

Run Celery Work

celery worker -A app.initializers.mycelery -l info

Run Redis Server

redis-server

To install redis-server from source on Ubuntu, follow the tutorial by Digital Ocean, https://www.digitalocean.com/community/tutorials/how-to-install-and-use-redis/

Initialising the Database

# Setup Neruoysnth Dataset
# Create DB tables and populate with Terms from Neurosynth
# Populate the roles and users tables	
python manage.py init_db

# Start the Flask development web server
./runserver.sh    # will run "python manage.py runserver"

Point your web browser to http://http://127.0.0.1:5000/

You can make use of the following users:

• email jeremy@incdb.com with password Password1 with Administrative Privileges.
• email ong@incdb.com with password Password1.
• email johnson@incdb.com with password Password1.
• email rajind@incdb.com with password Password1.

# Run all the automated tests in the tests/ directory
./runtests.sh         # will run "py.test -s tests/"

Out of Memory during Installation of Python Packages

As matplotlib and nilearn both require a large memory space during installation, the remote server might run out of memory. One way to overcome this issue is to add Swap on the server. Swap is created from the hard drive space and used by the operating system to store data for a non-permanent basis when it run out memory in the RAM to hold the data.

If you face the Out of Memory issue, follow the tutorial by Digital Ocean to add Swap to your remote server. https://www.digitalocean.com/community/tutorials/how-to-add-swap-on-ubuntu-14-04

Trouble installing SciPy and NumPy

Try installing the dependencies of python-scipy and python-numpy using the following command:

sudo apt-get build-dep python-numpy python-scipy

• If you make changes in the Models and run into DB schema issues, delete the sqlite DB file app.sqlite.

• If you have any other troubles with setting up INcDb, tell us on the Discussion Forum.