Hi! This repository includes the Jupyter notebooks we'll reference during the tutorial, as well as a few how-to docs. Note that I have already prepared Vapor-readable data in advance, but I also want to show you how to create such files. During the tutorial, we'll focus on the data I've prepared using VAPOR_Visualization.ipynb
and nco.md
, and then we'll use automate_example.ipynb
to make an animation of our Vapor renderings.
In this repository, you'll find:
-
VAPOR_Visualization.ipynb
: This Jupyter Notebook demonstrates how to pull variables from a Bifrost simulation, how to calculate a few secondary variables, and how to write that information into a netCDF file that is CF-compliant and readable in Vapor -
automate_example.ipynb
: This Jupyter Notebook demonstrates how to write a tailored automation script using pyautogui, which is super helpful when your Vapor commands get repetitive. Then, the script usesimageio
andmoviepy
to create an animation (both.gif
&.mp4
) out of the snapshots taken in Vapor -
nco.md
: This is a how-to on post-processing netCDF files after they're written -
python_dependencies.md
: This is a list of python packages that are necessary forautomate_example.ipynb
Check here, and download everything here to your local machine: /mn/stornext/d9/data/rebecrob/tutorial_data