Leverage the power of shaders for scientific visualisation in Jupyter
Project description
Shaders For Scientific Visualisation
Author: Thomas Mathieson
Student ID: 2576219m
Supervisor: Dr. John Williamson
A python library for advanced interactive data visualisation on the GPU. This project is being developed for my Level 4 Individual Project at the University of Glasgow for my Computing Science degree.
The dissertation and accompanying notes and planning documents can be found here.
Installation
You can install using pip
:
pip install pySSV
If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable the nbextension:
jupyter nbextension enable --py [--sys-prefix|--user|--system] pySSV
Getting Started
Try the example notebook
Create a suitable python environment (optional if you already have a python environment with jupyterlab setup) and install the package using pip
:
conda create -n pySSV -c conda-forge python jupyterlab
conda activate pySSV
pip install pySSV
Download the example notebook from github:
curl -o introduction.ipynb https://github.com/space928/Shaders-For-Scientific-Visualisation/raw/main/examples/introduction.ipynb
Start JupyterLab and play around with the notebook:
jupyter lab .\introduction.ipynb
Building From Source
Create a dev environment:
conda create -n pySSV-dev -c conda-forge nodejs yarn python jupyterlab=4
conda activate pySSV-dev
Install the python package. This will also build the TS package.
pip install -e ".[test, examples]"
The jlpm
command is JupyterLab's pinned version of
yarn that is installed with JupyterLab. You may use
yarn
or npm
in lieu of jlpm
below.
When developing your extensions, you need to manually enable your extensions with the notebook / lab frontend. For lab, this is done by the command:
jupyter labextension develop --overwrite .
jlpm run build
For classic notebook, you need to run:
jupyter nbextension install --sys-prefix --symlink --overwrite --py pySSV
jupyter nbextension enable --sys-prefix --py pySSV
Note that the --symlink
flag doesn't work on Windows, so you will here have to run
the install
command every time that you rebuild your extension. For certain installations
you might also need another flag instead of --sys-prefix
, but we won't cover the meaning
of those flags here.
How to see your changes
Typescript:
If you use JupyterLab to develop then you can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the widget.
# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm run watch
# Run JupyterLab in another terminal
jupyter lab
After a change wait for the build to finish and then refresh your browser and the changes should take effect.
Python:
If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
Acknowledgements
Thanks to Dr. John H. Williamson for his support throughout the project.
This project was made using the fabulous Jupyter Widget template: https://github.com/jupyter-widgets/widget-ts-cookiecutter
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