Figure 1.

Structure and workflows of the Neuronal Network Mean-field Toolbox (NNMT). (A) Basic workflow: individual mean-field based analysis methods are implemented as functions, called _tools(), that can be used directly by explicitly passing the required arguments. (B) Model workflow: to facilitate the handling of parameters and results, they can be stored in a model class instance, which can be passed to a tool(), which wraps the basic workflow of the respective _tool(). (C) Structure of the Python package. In addition to the tool collection (red frame), containing the tools() and the _tools(), and pre-defined model classes, the package provides utility functions for handling parameter files and unit conversions, as well as software aiding the implementation of new methods.