Getting Started

Documentation

Documentation can be found here:

• Introduction to the fundamental Eelbrain data types.

• Examples demonstrating different applications.

• Eelbrain, a Python toolkit for time-continuous analysis with temporal response functions: A tutorial on using Eelbrain for analyzing an EEG experiment with temporal response functions. Including a GitHub repoitory with code to reproduce all figures in the paper.

• The MneExperiment Pipeline for step-by-step instructions on setting up a M/EEG experiment pipeline.

• Reference on API and details of all the functionality.

Getting help

To get help, you may want to check (and contribute to):

• The Eelbrian wiki.

• GitHub Dicussions.

Interacting with other Python libraries

Pandas

Convert an Eelbrain Dataset to a pandas.DataFrame using Dataset.as_dataframe(). Useful libraries: Pingouin (statistics); Seaborn (plotting).

R

When using R from Python through the rpy2 bridge, transfer data between R data.frame and Eelbrain Dataset using Dataset.from_r() and Dataset.to_r().

MacOS: Framework Build

On macOS, the GUI backend that Eelbrain uses when run from the command-line interpreter requires a special build of Python called a “Framework build”. Eelbrain installs a shortcut to start IPython with a Framework build:

$ eelbrain

This automatically launches IPython with the “eelbrain” profile. A default startup script that executes from eelbrain import * is created, and can be changed in the corresponding IPython profile.

Windows: Scrolling

Scrolling inside a plot axes normally uses arrow keys, but this is currently not possible on Windows (due to an issue in Matplotlib). Instead, the following keys can be used:

	↑ i
← j		→ l
	↓ k