# BAE  
Braindecode Augmentations for EEG signals. 

## Content

This repository allows to train deep learning models using data-augmentation methods that are implemented in the braindecode python library. It was used in the paper CADDA to train the convolutional neural network introduced by Chambon et al in order to perform a sleep staging task on the sleep Physionet dataset. It furthermore enables the user to handcraft class-wise augmentations and to use them.  

## Installation 
The python package BAE can be installed with the following command line: 
```
pip install –e .
``` 

## Usage
Then, the experience can be reproduced with the simple command line: 
```
./experience/run.sh
```

The outputs of the experience are pandas DataFrames that contain the model’s predictionz on train, validation and test sets along with the ground truth values.  