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@@ -17,12 +17,13 @@ The rest of the subjects were pre-processed with provided pre-processing informa
├── test: Contains unittests and one visual check.
├── utils: Contains helper methods
| ├── ccs_eeg_semesterproject: Methods given in the lecture.
| ├── ccs_eeg_utils_reduced: Method for reading in BIDS.
| ├── ccs_eeg_utils_reduced: Method for reading in BIDS provided in the lecture.
| ├── file_utils.py: Methods for reading in files and getting epochs.
| └── plot_utils.py: Methods for manually created plots.
├── preprocessing_and_cleaning.py: The preprocessing pipeline.
├── erp_analysis.py: The ERP-Analysis and computation of ERP peaks.
── decoding_tf_analysis.py: Decoding and time-frequency analysis.
── decoding_tf_analysis.py: Decoding and time-frequency analysis.
└── semesterproject_report_voggesberger: The report of the project.
```
### Running the project

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@@ -254,6 +254,6 @@ def time_frequency(dataset, filename, scaling='lin', compute_tfr=True):
if __name__ == '__main__':
mne.set_log_level(verbose=VERBOSE_LEVEL)
ds = 'N170'
# decoding(ds, 'faces_vs_cars', True)
decoding(ds, 'faces_vs_cars', True)
time_frequency(ds, 'face_intact_vs_all_0.1_50hz_ncf2', 'log', True)

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