Uvic Ocean Physics software page

This is a list of useful software we may need.


If brew is not already on your computer, see Install Homebrew at http://brew.sh and follow the prompts. Brew is the *nix package manager for OS X, and it largely has what we want.


git is the version control system we use. Some of our stuff is kept on github, which is a public repository of our code. See http://jklymak.github.com.

brew install git

You probably want to set up a github account.


sudo gem install jekyll

jekyll is the site generator for these webpages, and how we will serve the documentation for each project. Github runs it automatically if you follow the directions at http://jklymak.github.io/projtemplate. However, if you want to preview the webpage locally before committing and pushing it, then you can run

jekyll serve --baseurl ''

and you will be able to see it at http://localhost:4000/.

Editors and Document Preparation:

For general editing, I use Sublime Text or Emacs.

For formal document preparation, I keep a Latex files. For OS X use MacTeX and it will install TexShop and BibDesk

For LaTeX I use TexShop, or TexPad.

For my bibliographies, I use bibtex and Bibdesk.

Data Analysis

For data analysis I almost exclusive use python now. All the libraries I use can be installed from Anaconda.

Python libraries

Most libraries not included with Anaconda can be included by running

conda update
conda install newlib

You may have to append sudo.

My libraries are at https://github.com/jklymak/pythonlib, and I’ll try to keep them up to date. The way to clone these using git is to go to the directory above where you want to install the library and:

cd ~/python
git clone git://github.com/jklymak/pythonlib.git

This will install a directory ~/python/pythonlib

To make sure python sees this, modify the PYTHONPATH by adding the following two lines to ~/.profile:


jupyter notebook

I run jupyter notebook for most of my analysis. To get this running I type:

% jupyter-notebook

Then, you need to open Firefox, to http://localhost:9999/ and your notebook will appear. You can start entering python code and running it. The result will be saved in Notebookname.ipynb in the directory you are working in (where you choose the Notebookname).