Graph Layouts by t-SNE
usage: tsnet.py [-h] [--star] [--perplexity PERPLEXITY]
[--learning_rate LEARNING_RATE] [--output OUTPUT]
input_graph
Read a graph, and produce a layout with tsNET(*).
positional arguments:
input_graph
optional arguments:
-h, --help show this help message and exit
--star Use the tsNET* scheme. (Requires PivotMDS layout in
./pivotmds_layouts/ as initialization.) Note: Use
higher learning rates for larger graphs, for faster
convergence.
--perplexity PERPLEXITY, -p PERPLEXITY
Perplexity parameter.
--learning_rate LEARNING_RATE, -l LEARNING_RATE
Learning rate (hyper)parameter for optimization.
--output OUTPUT, -o OUTPUT
Save layout to the specified file.
python3
numpy
matplotlib
graph-tool
theano
scikit-learn