Getting Started

Documentation

Documentation can be found here:

Getting help

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

Plots and GUIs

Eelbrain plots have two different “modes”. When created in a notebook, plots are static images, but they can be modified through initial parameters, the plots’ methods, and matplotlib. When created from an iPython terminal, plots should open in separate windows with different GUI elements that allow interaction with the plots. This allows, for example, scrolling through time.

When using a terminal, the terminal usually stays active while allowing interaction with plots. This functionality relies on Prompt Toolkit, and can become unreliable with highly interactive GUIs (primarily the ICA and trial selection GUIs). These GUIs may be more reliable after disabling Prompt Toolkit through calling:

>>> configure(prompt_toolkit=False)

After disabling Prompt Toolkit, the GUI has to be explicitly invoked. This can be done by running gui.run():

>>> configure(prompt_toolkit=False)
>>> plot.Array(array_1)
>>> plot.Array(array_2)
>>> gui.run()

Or by using run=True in a plot command:

>>> configure(prompt_toolkit=False)
>>> plot.Array(array, run=True)

To return control to the Terminal, quit the python application that opens the plot windows.

Note

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.

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().

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