ATLASxAnalyses/9f3e1da53738master
README.md
ATLASx Analysis tools
The data and scripts contained in this repository allow the user to reproduce the figures in the ATLASx manuscript from the original data files.
Installation
Requirements
- python 2.7 or higher (Tested and recommended: Python 3.9.6)
- pip
The code is adapted for python 3, but it can also be executed in python 2.s
Runtimes are indicated for each script and were determined on a MacBook Pro running macOS BigSur.
Download repository
$ git clone https://c4science.ch/source/ATLASxAnalysis.git
To install the required dependencies: $ cd ATLASxAnalysis $ make
Note
Data files are stored using git large file storage (lfs). The make file will install git lfs automatically. However, if lfs was not installed previously, the repository has to be updated after installation: $ git pull This is needed to retrieve the data files from the repository after installation.
Usage
Network Analysis
$ cd NetworkAnalysis/Source Plot component distribution for database scopes $ python3 get_component_distribution.py #Runtime: 97s By default, the database scopes will be plotted. For a resolution by data source, add data_sources as an argument to the above command: $ python3 get_component_distribution.py data_sources #Runtime: 11s
CSV file conversion
CVS files of networks are quite practical for visualisation, e.g. in the Gephi software. To convert the gpickle files for database scopes to CSV, run the following: $ python3 print_csv_from_gpickle.py #Runtime: 52s As above, for single data sources use: $ python3 print_csv_from_gpickle.py data_sources #Runtime: 50s
The output is automatically written to ~/Downloads .
The data files used in the repository is the same as the one used in the manuscript, which has been downloaded on 8 November 2020. For updated network files, please contact the authors of the paper directly.