Skip to content

Installation Instructions

Jump to bottom
Francesco Battaglia edited this page Nov 18, 2018 · 4 revisions

Installation instructions

These installation instructions are meant for Ubuntu Linux, and have been tested on a new install of Ubuntu 18.04 with updates. There are three methods offered for installation: 1) from conda packages 2) with Docker 3) from source files The first two are meant for production and for unexperienced users. With time we will decide for one of the other method.

installation from conda package

The installation uses Miniconda Python. A shell script automates installation of miniconda, creation of a virtual environment, installation of score and copying of some auxiliary files to the necessary locations. If you have previous versions of miniconda on your system, you are advised to remove them prior to start installation. For example, from a terminal window, type

rm -rf ~/miniconda
  1. Download the installation script from this link and save it in your home directory. Or from a terminal window, type
cd
wget https://raw.githubusercontent.com/MemDynLab/score/master/install_scripts/install_score.sh
  1. Run the installation script. From a terminal window type
cd
bash install_score.sh
  1. open a new terminal window, as the new shell will have some needed initialization. To run score type
conda activate score
score

An example csv sheet is copied in ~/score_example. You can use that for initial tests.

To upgrade score (when a new version becomes available) type

conda activate score 
conda upgrade -c memdynlab score

Installation from sources

This method is intended for experienced users/developers. We will assume the source tree lives in ~/src, so type

mkdir -p ~/src
cd ~/src
  1. Clone the repository (or even better, fork it first, if you intend to modify it, and type
git clone https://github.com/MemDynLab/score.git

(if you have forked it, replace MemDynLab with your username

  1. Get in the source directory by typing
cd score
  1. Create a virtual environment with the necessary packages by typing
conda env create -n score -f environment.yml

(confirm when asked)

  1. Install the software by typing
python setup.py install
  1. You have to install by hand some necessary files, to a standard system directory
cp score_behavior/score_config.json ~/.local/share/Score
cd score_behavior/resources
cp -r objects ~/.local/share/Score
  1. an example csv sheet is to be found in score_behavior/resources/csv
Clone this wiki locally