material descriptor library
Project description
What is XenonPy project
XenonPy is a Python library focus on the material informatics which be designed for material explore based on machine learning.
The main purpose of this project is to build a complex system to calculate various chem/phys descriptors for machine learning then extend them to explore material space. To reach this target, system also provide model training routines and try to re-use pre-trained model by various deep learning methods such as transfer learning.
This project has just started and a long way to run. The final goal of this project is to build a All-In-One virtual environment for material development come with:
Massive dataset and Pre-trained models out-of-box
Various descriptor calculation methods
Model training and re-use
Combined with deep learning methods seamless
Visualization tools for analysis and publish ready
XenonPy inspired by matminer: https://hackingmaterials.github.io/matminer/.
XenonPy is a open source project https://github.com/yoshida-lab/XenonPy.
See our documents for details: http://xenonpy.readthedocs.io
Contribution guidelines
Discussion with others
Docstring use Numpy style.
Check codes with Pylint
Writing tests if possible
Contract
Copyright and license
Code and documentation © 2017 TsumiNa. Released under the BSD-3 license.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for xenonpy-0.1.0b8-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b4deea59180f4d5e1e2bc420f296c3c193ccc1ae57391567ba5111506d94f6db |
|
MD5 | 4b7aa6b1194547b7fedb7186052a93a3 |
|
BLAKE2b-256 | d6b54f035649c83e25c4f9e509c12151411046ffbd75dde5d041e274942f66fb |