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). Users can also experiment with it on their local machines by following the installation instructions provided on the ACCESS-Vis GitHub repository. Please note that limitations may apply depending on hardware resources.
Key Features
Interactive 3D and 4D visualisation for rendering high-quality images and animations directly in Jupyter Notebooks.
Seamless integration with other ACCESS-NRI tools, including data catalogues and evaluation workflows.
Tutorial notebooks to help researchers learn and explore visualisation capabilities in their workflows.
Supports efficient integration with existing Python-based research tools, enhancing accessibility and usability.
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.
Animation support for creating dynamic, engaging visualisations.
How to Use
- ARE Access: Use ACCESS-Vis directly through the Australian Research Environment on Gadi.
- Local Machine: Experiment locally by following installation instructions on the ACCESS-Vis GitHub repository.
Training Resources: Explore example notebooks and tutorials in the ACCESS-Visualisation-Recipes repository.
Known Issues / Limitations
Large datasets may require additional system memory or optimisation strategies for smooth rendering.
Certain advanced visualisations may depend on the capabilities of your graphics hardware.
Please tag @rbeucher and/or @OwKal for questions and support.