Metadata-Version: 2.1
Name: alpfore
Version: 0.1.1
Summary: Active Learning Pipeline For Optimal Ranking Estimation
Home-page: https://github.com/nherringer/ALPineFOREst
License: MIT
Keywords: active learning,molecular simulation,machine learning
Author: Nicholas Herringer
Author-email: nherringer@uchicago.edu
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Project-URL: Repository, https://github.com/nherringer/ALPineFOREst
Description-Content-Type: text/markdown

# 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 .
```

