Jupyter notebooks and scripts with code examples, as shown in the lectures of TFY4235 Computational Physics at NTNU, spring 2016. The examples are shown in class as part of the lectures, and with supporting material. They are not intended to be completely stand-alone or self-explanatory.

Try out the code in the notebooks, without installing anything locally, through binder:

To run the python examples locally, there are some dependencies. To install dependencies with conda, use conda env create -f environment.yml. To install dependencies with pip, use pip install -r requirements.txt. Note that the last part of the notebook on NetCDF and HDF5 uses the library Basemap to plot things on a map. Basemap can be installed with conda, but not with pip (at least not at the moment, as far as I can tell). Check out github.com/matplotlib/basemap if you want to install it yourself.