DIY ZHL

Python subroutines for Buhlmann decompression model, and notebooks to show them off.

Files

• diyzhl.py - Python code

• diyzhl.ipynb - Start here what passes for documentation for the above

• mvalues.ipynb - various ways to show M-values

• dive.ipynb - simple dive sim w/ animated tissue loading bar plot.

Running

• Run in binder: (you can't save your changes, it may take forever to start as this are big conda scipy notebooks)

• If your computer can run docker containers, download the files here to a directory and run in there:

sudo docker run -it --rm --name=notebook --user root -e NB_UID=`id -u` -v `pwd`:/home/jovyan/work -p 8888:8888 jupyter/scipy-notebook

(or just run the run.sh file). You'll see something like

Copy/paste this URL into your browser when you connect for the first time,
    to login with a token:
http://(9aedd0d5f391 or 127.0.0.1):8888/?token=47e7e1e8dcdb15637f15c56952026762153d51c9b9665c84

Paste that into your browser's URL bar, edit it to http://127.0.0.1:8888/?token=47e7e1e8dcdb15637f15c56952026762153d51c9b9665c84 (or the other one if you prefer ipv6), and hit go.