Welcome to anemoi-graphs documentation!

Warning

This documentation is work in progress.

Anemoi is a framework for developing machine learning weather forecasting models. It comprises of components or packages for preparing training datasets, conducting ML model training and a registry for datasets and trained models. Anemoi provides tools for operational inference, including interfacing to verification software. As a framework it seeks to handle many of the complexities that meteorological organisations will share, allowing them to easily train models from existing recipes but with their own data.

The anemoi-graphs package allows you to design custom graphs for training data-driven weather models. The graphs are built using a recipe, which is a YAML file that specifies the nodes and edges of the graph.

• Overview

Building graphs

• Introduction

• Nodes - Coordinates

• Nodes - Attributes

• Edges - Connections

• Edges - Attributes

Modules

• Node builder

• Edge builder

• Node attributes

• Edge attributes

• Graph Creator

• Graph Inspector

• Post processor

Command line tool

• Introduction

• create

• describe

• inspect

Developing Anemoi Graphs

• Contributing

• Code Structure

• Testing

Tutorials

• Getting started

Anemoi packages

• anemoi-utils

• anemoi-transform

• anemoi-datasets

• anemoi-models

• anemoi-graphs

• anemoi-training

• anemoi-inference

• anemoi-registry

License

Anemoi is available under the open source Apache License.