Welcome to the Nexus tutorial. The tutorial will cover not only some basic examples but also show advanced methods to simulate and fit experimental data. In order to follow the tutorial it is helpful to be familiar with Python’s data types, classes, and the modules numpy and matplotlib.

The naming conventions in Nexus are:

  • Modules - lowercase, e.g. nx.lib.moessbauer.

  • Classes - CamelCase, e.g. nx.Beam.

  • Class methods and functions - CamelCase, e.g. nx.ClebshGordon() or nx.Beam.LinearSigma().

  • All class attributes - lower_case_with_underscores, e.g. nx.Beam.jones_vector.

Start with Hello Nexus tutorial for the basics and from there on proceed to the tutorials you need.


In case a jupyter lab or a jupyter notebook is used, be careful with data assignment in Nexus. It is recommended to restart the kernel and re-run all cells after a change of a cell or a second execution of a cell. This might be necessary due to the repeated command processing in jupyter when executing a cell and the object referencing in Nexus.