Metadata-Version: 2.4
Name: pyrfm
Version: 0.1.5
Summary: Random Feature Method (RFM) tools in Python
Home-page: https://ifaay.github.io
Author: Yifei Sun
Author-email: yfsun99@stu.suda.edu.cn
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.10
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: torch>=2.1.0
Requires-Dist: numpy>=1.23
Requires-Dist: pandas>=1.5
Requires-Dist: matplotlib>=3.5
Requires-Dist: scipy>=1.9
Requires-Dist: spdlog>=2.0.0
Dynamic: author
Dynamic: author-email
Dynamic: classifier
Dynamic: description
Dynamic: description-content-type
Dynamic: home-page
Dynamic: license-file
Dynamic: requires-dist
Dynamic: requires-python
Dynamic: summary

# A Python package for Random Feature Method (RFM)

## Quick Install

```
pip install git+https://github.com/IFaay/pyRFM.git
```

or

```
git clone https://github.com/IFaay/pyRFM.git
cd pyRFM
pip install .
```

## Update

```
pip install --upgrade --force-reinstall git+https://github.com/IFaay/pyRFM.git
```

and re-download / pull the source code.

## Remark

All examples run successfully on a host equipped with 8GB of GPU memory and 32GB of RAM.
Example scripts are located in the [examples](https://github.com/IFaay/pyRFM/tree/master/examples) folder.

## Reference

[1] J. Chen, X. Chi, W. E, and Z. Yang, “Bridging traditional and machine learning-based algorithms for solving pdes:
The random feature method,” J. Mach. Learn., vol. 1, no. 3, pp. 268–298, 2022, doi: 10.4208/jml.220726.

[2] J. Chen, W. E, and Y. Luo, “The random feature method for time-dependent problems,” East Asian Journal on Applied
Mathematics, vol. 13, no. 3, pp. 435–463, 2023, doi: 10.4208/eajam.2023-065.050423.

[3] J. Chen, W. E, and Y. Sun, “Optimization of Random Feature Method in the High-Precision Regime,” Com Appl Math
Comput, Mar. 2024, doi: 10.1007/s42967-024-00389-8.
