Matsushima-lab / CLOUD

CLOUD

This is an implementation of the following papers:
[1] Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima. (2024) Detection of Unobserved Common Causes based on NML Code in Discrete, Mixed, and Continuous Variables. Preprint available on arXiv.
[2] Masatoshi Kobayashi, Kohei Miyaguchi, Shin Matsushima, (2022) Detection of Unobserved Common Cause in Discrete Data Based on the MDL Principle. IEEE BigData 2022.

Requirement

• Python 3.8+
• Rye or pip

Setup

With Rye (Recommended)

After installing Rye, executing the following command(s):

$ rye sync
$ rye shell # optional

You can now import and use the CLOUD class:

from cloud import CLOUD

Without Rye

Create a new virtual environment and install the dependencies:

$ python -m venv .venv
$ source .venv/bin/activate
$ pip install -r requirements.lock

Run CLOUD

Sample Data

$ python -m unittest tests/test_cloud.py

If you are using Rye, you can also run the tests with:

$ rye run python -m unittest tests/test_cloud.py

Licence

MIT