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ProjectPythia / vapor-python-cookbook

Getting started with vapor python
https://projectpythia.org/vapor-python-cookbook/
Apache License 2.0
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Quickstart guide, keyframing, small updates #14

Closed ifranda closed 3 months ago

ifranda commented 3 months ago

Adding two new notebooks

github-actions[bot] commented 3 months ago

👋 Thanks for opening this PR! The Cookbook will be automatically built with GitHub Actions. To see the status of your deployment, click below. 🔍 Git commit SHA: 46053bbf8872b2bcf7d1c5b1291d88610e368650 ✅ Deployment Preview URL: https://ProjectPythia.github.io/vapor-python-cookbook/_preview/14

ifranda commented 3 months ago

Any suggestions are appreciated!

For downloading the datasets and session files, I included links to the files in Google Drive. Let me know if there is a better way!

ifranda commented 3 months ago

I think we'd be able to! Is the dataset too big to host on GitHub? That would probably be the easiest because then they'd have it when they clone the repository. It's about 170 MB. Otherwise I think we could find another way!

NihanthCW commented 3 months ago

RDA would be a good option. I've moved VAPOR sample data to RDA. We can move Katrina data to the same place?

ifranda commented 3 months ago

Good ideas! Another thought -- if users are following along by copying and pasting into their own workspace instead of cloning the whole repository, they won't have access to the get_data.py script. Another idea I had was to have a cell for command lines, like this:

!curl -o Katrina.zip "https://data.rda.ucar.edu/ds897.7/Katrina.zip"
!unzip -o Katrina.zip -d ./data
!rm Katrina.zip
NihanthCW commented 3 months ago

Agreed.

ifranda commented 3 months ago

Ok, I've made some updates and I think it runs better!

ifranda commented 3 months ago

I got the image renderer working with a fresh conda build! But it looks like Natural Earth is the only builtin map at the moment, and I think that one only renders land, unless I'm wrong about that? Do you know if there's a way to get the oceans to render? Otherwise maybe we could try adding BigBlueMarble to the builtin maps

This is what it looks like at the moment: image

Using the filepath to BigBlueMarble: image

NihanthCW commented 3 months ago

You are right. The oceans are black in the dataset. Could this be another file that we could download? Alternatively, the black ocean down't look bad too... I believe we intentionally donot include blue marble to avoid making the maps package too large. Let's chat tomorrow.