https://github.com/caiyunapp/wxbtool
A toolkit for WeatherBench based on PyTorch
https://github.com/caiyunapp/wxbtool
climate-model climate-science machinelearning weather-bench
Last synced: about 1 year ago
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A toolkit for WeatherBench based on PyTorch
- Host: GitHub
- URL: https://github.com/caiyunapp/wxbtool
- Owner: caiyunapp
- License: mit
- Created: 2020-06-06T09:23:17.000Z (about 6 years ago)
- Default Branch: master
- Last Pushed: 2021-10-12T03:37:46.000Z (over 4 years ago)
- Last Synced: 2025-04-10T07:05:54.370Z (about 1 year ago)
- Topics: climate-model, climate-science, machinelearning, weather-bench
- Language: Python
- Size: 10.7 MB
- Stars: 5
- Watchers: 8
- Forks: 3
- Open Issues: 1
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# wxbtool
[](https://zenodo.org/badge/latestdoi/269931312)
A toolkit for WeatherBench based on PyTorch
Install
--------
```bash
pip install wxbtool
```
Cheat sheet
-----------
Start a data set server for 3-days prediction of t850 by Weyn's solution
```bash
wxb dserve -m wxbtool.specs.res5_625.t850weyn -s Setting3d
```
Start a training process for a UNet model following Weyn's solution
```bash
wxb train -m wxbtool.zoo.res5_625.unet.t850d3sm_weyn
```
Start a testing process for a UNet model following Weyn's solution
```bash
wxb test -m wxbtool.zoo.res5_625.unet.t850d3sm_weyn
```
How to use
-----------
* [quick start](https://github.com/caiyunapp/wxbtool/wiki/quick-start)
* understanding the physical process by plotting
* develop your own neural model
* try a toy physical model
* explore the possibility to combine neural and physical model together
How to release
---------------
```bash
python3 setup.py sdist bdist_wheel
python3 -m twine upload dist/*
git tag va.b.c master
git push origin va.b.c
```
Contributors
------------
* Mingli Yuan ([Mountain](https://github.com/mountain))
* Ren Lu