global_LEC

This is a repo for looking how to efficiently perform global LEC analysis.

Things to look at

single_point_analysis.ipynb is a nice way to explore how the algorithm works when looking at a single starting point. It visualises the paths taken, and the costs it calculates.
australia.ipynb shows how to use the same code to perform an LEC analysis on the scale of Australia, using parallel map functions for speedup.
ugs.py has all the code for doing the slightly modified Dijkstra's algorithm

The data was taken from the escape models notebooks.

Checkout this repo, and cd into it. Then run:

docker run -d -v $PWD:/live/share -p 127.0.0.1:8888:8888 geodels/escape-docker:python3

and then connect to the running JuPyter Notebook server.

Name		Name	Last commit message	Last commit date
Latest commit History 15 Commits
australia		australia
earth		earth
.gitattributes		.gitattributes
.gitignore		.gitignore
All_in_one-Aus.ipynb		All_in_one-Aus.ipynb
All_in_one.ipynb		All_in_one.ipynb
All_in_one_2.ipynb		All_in_one_2.ipynb
LICENSE		LICENSE
README.md		README.md
SmoothingSphere.ipynb		SmoothingSphere.ipynb
australia.ipynb		australia.ipynb
costed_aus.vtk		costed_aus.vtk
costed_aus_new.vtk		costed_aus_new.vtk
costed_earth.vtk		costed_earth.vtk
costed_globe_new.vtk		costed_globe_new.vtk
costed_tas.vtk		costed_tas.vtk
costed_tas_new.vtk		costed_tas_new.vtk
earth.ipynb		earth.ipynb
single_point_analysis.ipynb		single_point_analysis.ipynb
tasmania.ipynb		tasmania.ipynb
ugs.py		ugs.py