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Machine learning weather nowcasting library

Project description

mlcast

The MLCast Community is a collaborative effort bringing together meteorological services, research institutions, and academia across Europe to develop a unified Python package for AI-based nowcasting. This is an initiative of the E-AI WG6 (Nowcasting) of EUMETNET.

This repo contains the mlcast package for machine learning-based weather nowcasting.

Project Status

⚠️ Under Development - This package is currently in early development stages and not usable by end users. The API and functionality are subject to change.

Installation

# Install from pipy
pip install mlcast

or

# Install from source
git clone https://github.com/mlcast-community/mlcast
cd mlcast
uv pip install -e .

# For development
uv pip install -e ".[dev]"

Project Structure

mlcast/
├── src/mlcast/          # Main package source code
│   ├── __init__.py      # Package initialization and version
│   ├── data/            # Data loading and preprocessing
│   │   ├── zarr_datamodule.py   # PyTorch Lightning data module for Zarr
│   │   └── zarr_dataset.py      # PyTorch dataset for Zarr arrays
│   ├── models/          # Lightning model implementations
│   │   └── base.py      # Abstract base classes for nowcasting models
│   └── modules/         # Pure PyTorch neural network modules
│       └── convgru_modules.py   # ConvGRU encoder-decoder modules
├── examples/            # Example scripts and notebooks
│   └── scripts/
│       └── simple_train.py      # Basic training example
├── pyproject.toml       # Project metadata and dependencies
├── LICENSE              # Apache 2.0 license
└── README.md            # This file

Development

This project uses uv for dependency management. To set up the development environment:

# Install uv if not already installed
curl -LsSf https://astral.sh/uv/install.sh | sh

# Install dependencies
uv sync

# Run pre-commit hooks
uv run pre-commit install

Contributing

Please feel free to raise issues or PRs if you have any suggestions or questions.

Links to presentations for discussion about the API

License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

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