Welcome to GRATIS - A GRaph Tool for Information Systems Scientists!

A tool made for graph creation, analysis and visualization.

CLI (Command Line Interface)

Gratis also supports a command line interface that can be used in order to generate graphs.

• Help

  • python app.py -h
    
    

• Gratis version

  • python app.py -v
    
    

Available graph models:

Graph model	Number
Homogeneous	1
Erdős Rényi	2
Custom Erdős Rényi	3
Random Fixed	4
Scale Free	5
Custom Scale Free	6

Graph creation examples:

• Creating a Homogeneous graph with 10 nodes:

  • python app.py -g -m 1 -nov 10
    
    

• Creating an Erdős Rényi graph with 10 nodes, 0.5 probability of connection and the number 7 as the seed:

  • python app.py -g -m 2 -nov 10 -p 0.5 -s 7
    
    

• Creating a Custom Erdős Rényi graph with 10 nodes, 0.5 probability of connection, 12 edges, and the number 7 as the seed:

  • python app.py -g -m 3 -nov 10 -p 0.5 -noe 12 -s 7
    
    

• Creating a Random Fixed graph with 10 nodes, 3 graph degree, and the number 7 as the seed:

  • python app.py -g -m 4 -nov 10 -gd 3 -s 7
    
    

• Creating a Scale Free graph using the Preferential Attachment mechanism with 10 nodes, and the number 7 as the seed:

  • python app.py -g -m 5 -nov 10 -s 7
    
    

• Creating a Full Scale Free graph using the Preferential Attachment and the Incremental growth mechanisms with 10 nodes, 3 initial nodes, and the number 7 as the seed:

  • python app.py -g -m 5 -nov 10 -noin 3 -s 7
    
    

• Creating a Custom Scale Free graph using the Preferential Attachment mechanism with 10 nodes, 12 edges, and the number 7 as the seed:

  • python app.py -g -m 6 -nov 10 -noe 12 -s 7
    
    

• Creating a Custom Full Scale Free graph using the Preferential Attachment and the Incremental growth mechanisms with 10 nodes, 3 initial nodes, 2 initial connections per node, and the number 7 as the seed:

  • python app.py -g -m 6 -nov 10 -noin 3 -icpn 2 -s 7

The default graph representation is as an Adjacency Matrix. This can be changed by using the -gr flag which stands for graph representation e.g.:
python app.py -g -m 3 -nov 10 -p 0.5 -noe 12 -s 7 -gr 2

Available graph representations:

Graph representation	Number
Adjacency Matrix	1
Adjacency List	2

Note: The python app.py should be replaced by the corresponding gratis executable/binary file e.g.:
./gratis -g -m 3 -nov 10 -p 0.5 -noe 12 -s 7

Development setup

1. In order to run this project you need:

   • Python3 or above

2. To install all needed packages and run the project:
   2.1. Debian and Ubuntu based systems:

   1. Clone or download zip and extract the project.
   2. cd Gratis/
   3. sudo ./install-dependencies.sh
   4. python3 app.py

   2.2. Windows systems:

   1. Download and install python3 and above from https://www.python.org/ (python3.6 is the safe choice)
   2. Download the appropriate python-igraph module for your windows system with the appropriate python version you installed. (e.g. if you have python3.6 and windows 64-bit you will download the file python_igraph‑0.7.1.post6‑cp36‑cp36m‑win_amd64.whl from https://www.lfd.uci.edu/~gohlke/pythonlibs/#python-igraph.
   3. Install the python-igraph module with python -m pip install <module_name.whl>
   4. Clone or download zip and extract the project.
   5. cd Gratis\
   6. python -m pip install -r requirements.txt
   7. python app.py

3. To install and run through pipenv:

   1. Download and install python3 or above.
   2. python3.x -m pip install pipenv (Note: .x is a wildcard)
   3. cd Gratis
   4. pipenv install
   5. pipenv shell
   6. python app.py