autoreject 0.4.3

Description:

autoreject 0.4.3

autoreject

This is a library to automatically reject bad trials and repair bad sensors in magneto-/electroencephalography (M/EEG) data.

The documentation can be found under the following links:

for the stable release
for the latest (development) version


Installation
We recommend the Anaconda Python distribution
and a Python version >= 3.8.
To obtain the stable release of autoreject, you can use pip:
pip install -U autoreject
Or conda:
conda install -c conda-forge autoreject
If you want the latest (development) version of autoreject, use:
pip install https://api.github.com/repos/autoreject/autoreject/zipball/master
If you do not have admin privileges on the computer, use the --user flag
with pip.
To check if everything worked fine, you can do:
python -c 'import autoreject'
and it should not give any error messages.
Below, we list the dependencies for autoreject.
All required dependencies are installed automatically when you install autoreject.

mne (>=1.0)
numpy (>=1.20.2)
scipy (>=1.6.3)
scikit-learn (>=0.24.2)
joblib
matplotlib (>=3.4.0)

Optional dependencies are:

openneuro-py (>= 2021.10.1, for fetching data from OpenNeuro.org)




Quickstart
The easiest way to get started is to copy the following three lines of code
in your script:
>>> from autoreject import AutoReject
>>> ar = AutoReject()
>>> epochs_clean = ar.fit_transform(epochs) # doctest: +SKIP
This will automatically clean an epochs object read in using MNE-Python. To get the
rejection dictionary, simply do:
>>> from autoreject import get_rejection_threshold
>>> reject = get_rejection_threshold(epochs) # doctest: +SKIP
We also implement RANSAC from the PREP pipeline
(see PyPREP for a full implementation of the PREP pipeline).
The API is the same:
>>> from autoreject import Ransac
>>> rsc = Ransac()
>>> epochs_clean = rsc.fit_transform(epochs) # doctest: +SKIP
For more details check out the example to
automatically detect and repair bad epochs.


Bug reports
Please use the GitHub issue tracker to report bugs.


Cite
[1] Mainak Jas, Denis Engemann, Federico Raimondo, Yousra Bekhti, and Alexandre Gramfort, “Automated rejection and repair of bad trials in MEG/EEG.”
In 6th International Workshop on Pattern Recognition in Neuroimaging (PRNI), 2016.
[2] Mainak Jas, Denis Engemann, Yousra Bekhti, Federico Raimondo, and Alexandre Gramfort. 2017.
“Autoreject: Automated artifact rejection for MEG and EEG data”.
NeuroImage, 159, 417-429.