spherical-MDS

Graph Layouts on the sphere

usage: layout.py [-h] [--max_iter MAX_ITER]
                [--opt_scale  OPT_SCALE]
                [--epsilon  EPSILON]
                [--learning_rate LEARNING_RATE] [--output OUTPUT]
                input_graph

Read a graph, and produce a layout with SMDS.

positional arguments:
  input_graph

optional arguments:
  -h, --help            show this help message and exit

  --opt_scale           Whether to optimizing the scale of the data.
                        Defaults to 0, which will use a heuristic.
                        A 1 will use the optimization.

  --epsilon -e          Threshold for convergence.

  --learning_rate LEARNING_RATE, -l LEARNING_RATE
                        If given a number, will use a fixed schedule. Will also accept
                        'fraction' 'sqrt' and 'convergent' schedules. Defaults to 'convergent'

  --max_iter            Maximum number of iterations.

  --output OUTPUT, -o OUTPUT
                        Save layout to the specified file.

Example:

# Read the input graph a cube, and saves the output to be viewed in the webapp at webapp/index.html
python3 layout.py graphs/cube.txt

Dependencies

• python3
• numpy
• matplotlib
• graph-tool
• numba
• scikit-learn