The following python packages are required to run. Anaconda environments are supported.
- numpy
- scikit-learn
- matplotlib
- pandas
- seaborn
- scipy
- setuptools
- more_itertools
As of now, only Linux and macOS are supported.
Install any packages that may be missing.
Download the 'data' folder inside 'preprocessed_data' folder from osf and store in the root directory of the project. Link: https://osf.io/hca7b/
The starting point of the code is the classification/cluster_analysis_perm_reg_overlap.py file.
python classification/notebooks/cluster_analysis_perm_reg_overlap.py -h
usage: cluster_analysis_perm_reg_overlap.py [-h] --age_group AGE_GROUP --randomize_labels RANDOMIZE_LABELS --animacy ANIMACY --tgm TGM --across_groups ACROSS_GROUPS
[--across_groups_group_1 ACROSS_GROUPS_GROUP_1] [--across_groups_group_2 ACROSS_GROUPS_GROUP_2] --embeddings EMBEDDINGS
[--monte_carlo_iterations MONTE_CARLO_ITERATIONS]
Run decoding analysis on EEG data.
optional arguments:
-h, --help show this help message and exit
--age_group AGE_GROUP
Age of participants. 9 or 12.
--randomize_labels RANDOMIZE_LABELS
Whether to randomize the labels for the permutation test.
--animacy ANIMACY Whether to do animacy decoding.
--tgm TGM Whether to do TGM analysis.
--across_groups ACROSS_GROUPS
Whether to do across groups analysis.
--across_groups_group_1 ACROSS_GROUPS_GROUP_1
Age of participants for group 1. 9 or 12.
--across_groups_group_2 ACROSS_GROUPS_GROUP_2
Age of participants for group 2. 9 or 12.
--embeddings EMBEDDINGS
Which embeddings to use. Options are w2v, fine_tuned, or phoneme
--monte_carlo_iterations MONTE_CARLO_ITERATIONS
Number of Monte Carlo iterations to run.
NOTE: If you face an error while running the code, please open an issue on GitHub, or start a discussion thread.