Name | BindingGP JSON |
Version |
0.0.36
JSON |
| download |
home_page | https://github.com/boliqq07/bgp |
Summary | This is for symbolic regression.Some of code are non-originality, just copy for use. All the referenced code are marked,details can be shown in their sources |
upload_time | 2023-05-05 12:50:43 |
maintainer | wangchangxin |
docs_url | None |
author | wangchangxin |
requires_python | >=3.6 |
license | |
keywords |
symbolic
regression
|
VCS |
|
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
<div align="center">
<img alt="BGP" src="https://github.com/MGEdata/bgp/blob/master/img.jpg?raw=true">
</div>
[![Python Versions](https://img.shields.io/pypi/pyversions/bindinggp.svg)](https://pypi.org/project/bindinggp/)
[![Version](https://img.shields.io/github/tag/MGEdata/bgp.svg)](https://github.com/MGEdata/bgp/releases/latest)
![pypi Versions](https://badge.fury.io/py/BindingGP.svg)
BGP
----------------------
Welcome to BGP.
BGP (Binding Genetic Programming) is an open python library that implements a comprehensive set of symbolic regression
tools for materials informatics.
This tool contains a symbol regression tool with dimension calculation, which is aimed at establish expressions with
physical limitation.
BGP inspired by:
[XenonPy](https://github.com/yoshida-lab/XenonPy),
[matminer](https://hackingmaterials.github.io/matminer/ ),
[deap](https://github.com/DEAP/deap),
[sympy](https://www.sympy.org/en/index.html)
Quick Install
----------------------
```bash
pip install BindingGP
```
Document
----------------------
The usage of this package and **install** deatils are collected in BGP document.
Turn to [BGP document](https://bgp.readthedocs.io/en/latest/) for more details.
License
----------------------
GNU LGPL-3.0 License
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