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 38 Commits
australia		australia
earth		earth
outputs		outputs
utils/docker		utils/docker
.gitattributes		.gitattributes
.gitignore		.gitignore
LECMesh.py		LECMesh.py
LICENSE		LICENSE
README.md		README.md
SmoothingSphere.ipynb		SmoothingSphere.ipynb
australia.ipynb		australia.ipynb
earth.ipynb		earth.ipynb
gadi_job.pbs		gadi_job.pbs
mpi_global.py		mpi_global.py
mpi_new_func.py		mpi_new_func.py
mpi_oahu.py		mpi_oahu.py
mpi_tas.py		mpi_tas.py
new_func.py		new_func.py
single_point_analysis.ipynb		single_point_analysis.ipynb
tasmania.ipynb		tasmania.ipynb