Initial release

Author: nik-sm

.gitignore

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+data*
+results*
+results_baseline*
+venv*
+*.vscode
+
+*.pyc
+*__pycache__

LICENSE.md

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+CAMBI Copyright 2021 (“Licensor”)
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+Hippocratic License Version Number: 2.1.
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README.md

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+Code to reproduce experiments in "Target-Related Alpha Attenuation in a Brain-Computer Interface Rapid Serial Visual Presentation Calibration"
+
+# Setup
+
+## Dependencies
+Depends on python3.7+. See https://github.com/CAMBI-tech/BciPy for other transitive dependencies.
+
+Create a virtualenv environment for the project and install required packages with:
+```shell
+python3 -m virtualenv venv
+source venv/bin/activate
+python -m pip install --upgrade pip setuptools wheel
+python -m pip install -r requirements.txt
+```
+
+# Usage
+To request access to the data used for these experiments, please contact us at https://www.cambi.tech/contact.
+Data should be stored in `data` with the following structure:
+```shell
+data/bcipy_recordings
+├── <SUBJECT_ID_0>                                                       # Subject ID
+│   ├── <SESSION_0_1Hz>                                                  # Recording session with 1 Hz stimulus
+│   │   ├── parameters.json                                              # Experimental configuration
+│   │   ├── raw_data.csv                                                 # Raw EEG data 
+│   │   └── triggers.txt                                                 # Stimulus timing data
+│   └── <SESSION_0_4Hz>                                                  # Recording session with 4 Hz stimulus
+│       └── ...
+├── <SUBJECT_ID_1>
+│   └── ...
+...
+└── <SUBJECT_ID_N>
+```
+
+To run this code with data from another source, replace the `load_data` function in [alpha_experiment.py](alpha/alpha_experiment.py) with a function that loads data from the desired source.
+Your function must produce data with shape `(trials, channels, samples)`.
+
+Given a folder of data for a single subject, and an integer individual alpha frequency (IAF), reproduce experiments on alpha-band classifiers with:
+```shell
+source venv/bin/activate
+python alpha/alpha_experiment.py --input <PATH/TO/DATA> --output <PATH/TO/RESULTS> --freq <IAF>
+```
+
+Similarly, to reproduce baseline experiments using BciPy's current PCA/RDA/KDE P300 classifier, run:
+```shell
+source venv/bin/activate
+python alpha/baseline.py --input <PATH/TO/DATA> --output <PATH/TO/RESULTS>
+```