alpfore

Name	alpfore JSON
Version	0.1.5 JSON
	download
home_page	https://github.com/nherringer/ALPineFOREst
Summary	Active Learning Pipeline For Optimal Ranking Estimation
upload_time	2025-08-23 06:51:13
maintainer	None
docs_url	None
author	Nicholas Herringer
requires_python	<4.0,>=3.7
license	MIT
keywords	active learning molecular simulation machine learning
VCS
bugtrack_url
requirements	No requirements were recorded.
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # ALPineFOREst

**A**ctive **L**earning **Pipel**ine **For** **Optima**l **Ranking Estimation**

[![PyPI version](https://badge.fury.io/py/alpfore.svg)](https://pypi.org/project/alpfore/)

ALPineFOREst is a flexible, modular framework for conducting large-scale active learning campaigns in scientific and materials research. It supports molecular dynamics (MD)-based evaluations, customizable models (e.g., Gaussian Processes), and popular Bayesian optimization strategies like Thompson Sampling — all within a high-throughput, reproducible pipeline.

---

## Installation

Install via PyPI:
```
pip install alpfore
```
Or to install from source:
```
git clone https://github.com/nherringer/ALPineFOREst.git
cd ALPineFOREst
pip install -e .
```


            

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