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https://github.com/NVIDIA/earth2studio
Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
https://github.com/NVIDIA/earth2studio
ai climate-science deep-learning weather
Last synced: 3 months ago
JSON representation
Open-source deep-learning framework for exploring, building and deploying AI weather/climate workflows.
- Host: GitHub
- URL: https://github.com/NVIDIA/earth2studio
- Owner: NVIDIA
- License: apache-2.0
- Created: 2024-04-05T17:39:51.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-05-29T03:51:32.000Z (5 months ago)
- Last Synced: 2024-05-29T12:14:51.507Z (5 months ago)
- Topics: ai, climate-science, deep-learning, weather
- Language: Python
- Homepage: https://nvidia.github.io/earth2studio/
- Size: 110 MB
- Stars: 31
- Watchers: 2
- Forks: 4
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE
- Citation: CITATION.cff
Awesome Lists containing this project
- open-sustainable-technology - Earth2Studio - A Python-based package designed to get users up and running with AI weather and climate models fast. Our mission is to enable everyone to build, research and explore AI driven meteorology. (Climate Change / Earth and Climate Modeling)
README
[![python version][e2studio_python_img]][e2studio_python_url]
[![license][e2studio_license_img]][e2studio_license_url]
[![format][e2studio_format_img]][e2studio_format_url]
[![coverage][e2studio_cov_img]][e2studio_cov_url]
Earth2Studio is a Python-based package designed to get users up and running
with AI weather and climate models *fast*.
Our mission is to enable everyone to build, research and explore AI driven meteorology.
**- Earth2Studio Documentation -**
[Install][e2studio_install_url] | [User-Guide][e2studio_userguide_url] |
[Examples][e2studio_examples_url] | [API][e2studio_api_url]
## Quick start
Install Earth2Studio:
```bash
pip install earth2studio
```
Run a deterministic weather prediction in just a few lines of code:
```python
from earth2studio.models.px import DLWP
from earth2studio.data import GFS
from earth2studio.io import NetCDF4Backend
from earth2studio.run import deterministic as run
model = DLWP.load_model(DLWP.load_default_package())
ds = GFS()
io = NetCDF4Backend("output.nc")
run(["2024-01-01"], 10, model, ds, io)
```
## Features
Earth2Studio provides access to pre-trained AI weather models and inference
features through an easy to use and extendable Python interface.
This package focuses on supplying users the tools to build their own
workflows, pipelines, APIs, packages, etc. via modular components including:
- Collection of pre-trained weather/climate prediction models
- Collection of pre-trained diagnostic weather models
- Variety of online and on-prem data sources for initialization, scoring, analysis, etc.
- IO utilities for exporting predicted data to user friendly formats
- Suite of perturbation methods for building ensemble predictions
- Sample workflows and examples for common tasks / use cases
- Seamless integration into other Nvidia packages including [Modulus][modulus_repo_url]
For a more complete list of feature set, be sure to view the [documentation][e2studio_docs_url].
Don't see what you need?
Great news, extension and customization are at the heart of our [design][e2studio_customization_url].
## Contributors
Check out the [Contributing](CONTRIBUTING.md) document for details about the technical
requirements and the userguide for higher level philosophy, structure, and design.
## License
Earth2Studio is provided under the Apache License 2.0, please see
[LICENSE file][e2studio_license_url] for full license text.
[e2studio_python_img]: https://img.shields.io/badge/Python-3.10%2B-blue?style=flat-square&logo=python
[e2studio_license_img]: https://img.shields.io/badge/License-Apache%202.0-green?style=flat-square
[e2studio_format_img]: https://img.shields.io/badge/Code%20Style-Black-black?style=flat-square
[e2studio_cov_img]: https://img.shields.io/codecov/c/github/nickgeneva/earth2studio?style=flat-square&logo=codecov
[e2studio_python_url]: https://www.python.org/downloads/
[e2studio_license_url]: ./LICENSE
[e2studio_format_url]: https://github.com/psf/black
[e2studio_cov_url]: ./test/
[e2studio_docs_url]: https://nvidia.github.io/earth2studio/
[e2studio_install_url]: https://nvidia.github.io/earth2studio/userguide/about/install.html
[e2studio_userguide_url]: https://nvidia.github.io/earth2studio/userguide/
[e2studio_examples_url]: https://nvidia.github.io/earth2studio/examples/
[e2studio_api_url]: https://nvidia.github.io/earth2studio/modules/
[e2studio_customization_url]: https://nvidia.github.io/earth2studio/
[modulus_repo_url]: https://github.com/NVIDIA/modulus