Documentation overview#

Note

If you haven’t already installed MOABB, please take a look at our installation guides. Please also kindly find some resources for learn_python from MNE if you need to, and the basic module from NeuroMatch Academy.

The documentation for MOABB is divided into three main sections:

  1. The Getting Started provide a sequential tutorial to start to use MOABB. They are designed to be read in order, and provide detailed explanations, sample code, and expected output for the most common MOABB analysis tasks. The emphasis is on thorough explanations that get new users up to speed quickly, at the expense of covering only a limited number of topics.

  2. MOABB comes with working code samples that exhibit various modules and techniques. The examples are categorized into the four categories: Simple, Advanced, External, and Evaluation. While these examples may not provide the same level of descriptive explanations as tutorials, they are a beneficial resource for discovering novel ideas for analysis or plotting. Moreover, they illustrate how to use MOABB to implement specific module.

  3. The API reference that provides documentation for the classes, functions and methods in the MOABB codebase. This is the same information that is rendered when running help(moabb.<function_name>) in an interactive Python session, or when typing moabb.<function_name>? in an IPython session or Jupyter notebook.

The rest of the MOABB documentation pages are shown in the navigation menu, including the list of example datasets, information about the MOABB license, how to contribute to MOABB, how to cite MOABB, and explanations of the external library dependencies that MOABB uses, including Deep Learning, Code Carbon, Docs and others.