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Lagrangian Coherent Structure identification for machine learning
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Figure out how to run pyqg #6

Closed rabernat closed 3 years ago

rabernat commented 3 years ago

Using same configurations as Zhang

https://pyqg.readthedocs.io/

rabernat commented 3 years ago

This includes how to track Lagrangian particles

hscannell commented 3 years ago

Using the examples found here, I've figured out how to run pyqg and advance Lagrangian particles. I've been able to make short animations using run_with_snapshots, but I'm still wrangling with FFMpeg to export movies. Right now I have it set up so that you can display Matplotlib animations as a JavaScript widget within the notebook. This is size prohibited and I'd ideally like to get xmovie working. I'm having some CI issues with xmovie and cartopy.

Here are some fun screenshots of the animations showing particles and velocity vectors plotted on top of the PV anomaly field in the upper layer. Screen Shot 2021-02-17 at 2 59 13 PM Screen Shot 2021-02-17 at 3 02 21 PM

Next step involves tweaking the QG model to mimic Zhang et al. (2020) and identifying RCLVs with floater.

rabernat commented 3 years ago

This is fantastic! Great work!

Now that you have spun up a bit, I think this might be a good time to reach out to Wenda to get the precise settings he used for his experiments. Do you agree?

hscannell commented 3 years ago

Yes, absolutely. If he could make his code available to us that would certainly be helpful.

rabernat commented 3 years ago

I reached out to Wenda via email. Now we are just waiting to hear back.

hscannell commented 3 years ago

Today we talked about some of the nuances of visually identifying LCS in pyqg. At first, I was drawn to taking an Eulerian view of the PV anomaly field; however after animating the particle paths I can see the coherency aspect more clearly (snapshot below).

Screen Shot 2021-02-19 at 3 24 03 PM