Links

Reference material

Tutorials and documentation

Packages and libraries

Ocean modelling

  • PyDOM    | Implements various diagnostics for NEMO ocean model output.
  • OCTANT | Ocean C-grid model setup and analysis toolkit. Tools for ROMS and GETM. Replaces PyROMS.
  • OOFE | Python engine to control the daily execution of ocean model ROMS in operational mode
  • soda2roms | Creates climatology, initial, and boundary files for ROMS

Tides

  • ttide_py    | A direct conversion of Matlab’s T_Tide to Python (from Mitchell O’Flaherty-Sproul)
  • UTide  |  Python distribution of the MatLab package UTide (from Wesley Bowman)
  • PySeidon | Standardized numerical toolbox gathering specific analysis functions for measured and simulated data (FVCOM model) to the EcoEII partners

Seawater properties

Other Ocean tools

  • Python-Oceans  |  Various scripts and functions from rsignell and ocefpaf

Scientific visualization and data analysis

  • PyNGL & PyNIO  | NOAA package for visualization and data analysis

Other websites with lists of links

Other websites of interest

  • PyAOS  |  Python for Atmospheric and Oceanic Sciences (Johnny Lin)

4 thoughts on “Links

  1. I just found a post elsewhere pointing to a bunch of useful links. The second below would be especially useful for current matlab users looking to tryout python.

    Python Scientific Lecture Notes
    http://scipy-lectures.github.com/

    Numpy Guide for Matlab users
    http://www.scipy.org/NumPy_for_Matlab_Users

    The Python g-node also organises a yearly summer school on scientific programming with Python. All the lecture presentations are available on the website.
    Advanced Scientific Programming in Python (St Andrews 2011 Course)
    https://python.g-node.org/wiki/schedule

    MIT open course ware
    6.189 A Gentle Introduction to Programming Using Python
    http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-189-a-gentle-introduction-to-programming-using-python-january-iap-2008/

    How to Think Like a Computer Scientist: Learning with Python 2nd Edition
    http://openbookproject.net/thinkCSpy/

    There are also some books on scientific Python programming published by Springer:
    http://www.springerlink.com/content/978-3-642-02474-0
    http://www.springerlink.com/content/978-3-540-73915-9

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