Moving Toward Version 1.0 of Causation Entropy

[kslote1]

Hello everyone,

We’re excited to announce that the Causation Entropy package is moving toward its 1.0 release. 🎉
his is a major milestone, and we’d like to use this discussion to collect ideas, feedback, and contributions from the community.

Goals for v1.0

• Stability: Finalize and clean up the core API for long-term use.
• Documentation: Expand tutorials and examples (e.g., neuroscience, climate networks, financial systems).
• Testing: Improve CI/CD coverage, including edge cases and performance benchmarking.

📌 Open Questions

Are there functions in the API that feel redundant or confusing?
Which features are must-have for 1.0, and which can wait for later versions?
Do we want to define a clear set of “core algorithms” (e.g., Optimal Causation Entropy, iterative pruning, bootstrap methods)?
How can we make the package more accessible to new users (not just experts in causal inference)?

💡 Ways You Can Help

• Share your use cases: How are you applying causation entropy in your field?
• Suggest improvements or missing features.
• Contribute to documentation examples (notebooks, tutorials, demos).

Help with testing and validation across different datasets.

This is an exciting point for the project, and we’d love to shape Causation Entropy 1.0 together with the community.
Please share your thoughts below!

Thanks,
Kevin
email: [email protected]