| Name | neural-transport JSON |
| Version |
0.0.1
JSON |
| download |
| home_page | None |
| Summary | Neural Transport - A Python library to train neural network emulators of atmospheric transport models. |
| upload_time | 2024-08-20 17:45:54 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | MIT License Copyright (c) 2024 Vitus Benson, Max Planck Institute for Biogeochemistry Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
ai
neural network
transport model
carbon
co2
emulator
pytorch
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
*A Python library to train neural network emulators of atmospheric transport models.*
<a href='https://pypi.python.org/pypi/neural-transport'>
<img src='https://img.shields.io/pypi/v/neural-transport.svg' alt='PyPI' />
</a>
<a href="https://opensource.org/licenses/MIT" target="_blank">
<img src="https://img.shields.io/badge/License-MIT-blue.svg" alt="License">
</a>
<a href="https://twitter.com/vitusbenson" target="_blank">
<img src="https://img.shields.io/twitter/follow/vitusbenson?style=social" alt="Twitter">
</a>
# Installation
```
conda create -n neuraltransport python=3.10
conda activate neuraltransport
conda install -c conda-forge ffmpeg pkg-config libjpeg-turbo opencv cupy cuda-version=11.8
conda install -c conda-forge numpy pandas xesmf cdo python-cdo xarray dask zarr netCDF4 bottleneck matplotlib seaborn cartopy shapely xskillscore xrft pyarrow
conda install pytorch torchvision torchaudio pytorch-cuda=11.8 -c pytorch -c nvidia
conda install pyg -c pyg
pip3 install lightning cdsapi pypdf2 trimesh rtree ipykernel ipywidgets tensorboard einops timm ecmwf-api-client eccodes dm-tree cfgrib
pip3 install git+https://github.com/jbusecke/xmovie.git
pip3 install git+https://github.com/vitusbenson/torch_advection.git
pip install pynvml wandb ruamel.yaml moviepy
pip3 install git+https://github.com/NVIDIA/modulus-makani.git
pip install -e .
```
# Cite NeuralTransport
In case you use NeuralTransport in your research or work, it would be highly appreciated if you include a reference to our [paper](https://arxiv.org/abs/2408.XXXXX) in any kind of publication.
```bibtex
@article{benson2024neuraltransport,
title = {Atmospheric Transport Modeling of CO2 with Neural Networks},
author = {Vitus Benson, Ana Bastos, Christian Reimers, Alexander J. Winkler,
Fanny Yang and Markus Reichstein},
eprint={2408.XXXXX},
archivePrefix={arXiv},
primaryClass={cs.LG},
url={https://arxiv.org/abs/2408.XXXXX},
}
```
# Contact
For questions or comments regarding the usage of this repository, please use the [discussion section](https://github.com/vitusbenson/neural_transport/discussions) on Github. For bug reports and feature requests, please open an [issue](https://github.com/vitusbenson/neural_transport/issues) on GitHub.
In special cases, you can reach out to Vitus (find his email on his [website](https://vitusbenson.github.io/)).
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