:rocket: **ACCESS-Vis 1.0.0 is now available!**
**Visualisation tools for analysing complex data sets, viewing data in context, and communicating research.**
ACCESS-Vis 1.0.0 is a Python package for 3D visualisation, designed specifically for researchers working in Jupyter Notebooks. ACCESS-Vis leverages OpenGL capabilities provided through the LaVaVu Python package developed by Owen Kaluza (OwKal).
ACCESS-Vis aims to offer an efficient and intuitive solution for visualising complex datasets in high-quality 3D and 4D renderings.
ACCESS-Vis is now available to use on **Gadi** via the [**Australian Research Environment (ARE)**](https://are.nci.org.au/). Users can also experiment with it on their local machines by following the installation instructions provided on the [ACCESS-Vis GitHub repository](https://github.com/ACCESS-NRI/ACCESS-Vis). Please note that limitations may apply depending on hardware resources.
---
**Key Features**
:white_check_mark: **Interactive 3D and 4D visualisation** for rendering high-quality images and animations directly in Jupyter Notebooks.
:white_check_mark: **Seamless integration** with other ACCESS-NRI tools, including data catalogues and evaluation workflows.
:white_check_mark: **Tutorial notebooks** to help researchers learn and explore visualisation capabilities in their workflows.
:white_check_mark: **Supports efficient integration** with existing Python-based research tools, enhancing accessibility and usability.
:white_check_mark: **Easy 3D Earth globe visualisations**, including the position of the sun with respect to the time of year and time of day, powered by orbital information from Astropy.
:white_check_mark: **Animation support** for creating dynamic, engaging visualisations.
---
**How to Use**
- **ARE Access**: Use ACCESS-Vis directly through the [Australian Research Environment on Gadi](https://are.nci.org.au).
- **Local Machine**: Experiment locally by following installation instructions on the [ACCESS-Vis GitHub repository](https://github.com/ACCESS-NRI/ACCESS-Vis).
**Training Resources**: Explore example notebooks and tutorials in the [ACCESS-Visualisation-Recipes repository](https://github.com/ACCESS-NRI/ACCESS-Visualisation-Recipes).
---
**Known Issues / Limitations**
:warning: **Large datasets** may require additional system memory or optimisation strategies for smooth rendering.
:warning: Certain advanced visualisations may depend on the capabilities of your graphics hardware.
Please tag rbeucher and/or OKaluza l for questions and support.