honegumi 0.4.0

Honegumi (骨組み) is an interactive "skeleton code" generator for API tutorials focusing on optimization packages.

Honegumi ("ho-nay-goo-mee"), which means "skeletal framework" in Japanese, is a package for interactively creating API tutorials with a focus on optimization packages such as Meta's Ax Platform

Honegumi

Real-world materials science optimization tasks are complex! To cite a few examples:

Topic	Description
Noise	Repeat measurements are stochastic
Multi-fidelity	Some measurements are higher quality but much more costly
Multi-objective	Almost always, tasks have multiple properties that are important
High-dimensional	Like finding the proverbial "needle-in-a-haystack", the search spaces are enormous
Constraints	Not all combinations of parameters are valid (i.e., constraints)
Mixed-variable	Often there is a mixture of numerical and categorical variables

However, applications of state-of-the-art algorithms to these materials science tasks have been limited. Meta's Adaptive Experimentation (Ax) platform is one of the few optimization platforms capable of handling these challenges without oversimplification. While Ax and its backbone, BoTorch, have gained traction in chemistry and materials science, advanced implementations are still challenging, even for veteran materials informatics practitioners. In addition to combining multiple algorithms, there are other logistical issues, such as using existing data, embedding physical descriptors, and modifying search spaces. To address these challenges, we present Honegumi (骨組み or "ho-neh-goo-mee"): An interactive "skeleton code" generator for materials-relevant optimization. Similar to PyTorch's installation docs, users interactively select advanced topics to generate robust templates that are unit-tested with invalid configurations crossed out. Honegumi is the first Bayesian optimization template generator of its kind, and we envision that this tool will reduce the barrier to entry for applying advanced Bayesian optimization to real-world materials science tasks.

Quick Start

You don't need to install anything. Just navigate to https://honegumi.readthedocs.io/, select the desired options, and click the "Open in Colab" badge.

If you're interested in collaborating, see the contribution guidelines and the high-level roadmap of Honegumi's development.

License

Note

This project has been set up using PyScaffold 4.4.1 and the dsproject extension 0.7.2.