Vapor Visualization Tutorial

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:

1. 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

2. 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 uses imageio and moviepy to create an animation (both .gif & .mp4) out of the snapshots taken in Vapor

3. nco.md: This is a how-to on post-processing netCDF files after they're written

4. python_dependencies.md: This is a list of python packages that are necessary for automate_example.ipynb

Where can I find the already-prepared data?

Check here, and download everything here to your local machine: /mn/stornext/d9/data/rebecrob/tutorial_data

Where can I find a Video Tutorial for automate_example.ipynb?

Sounds fun, click here!