Jelly-Emotions

NOTE: Our code is largely notebook based.

Requirements

Our requirements are listed in build/requirements.txt

Unix is supported, but we mostly used Mac OS.
64-bit Python 3.8.10 is the version we use (or later version can be used).
CUDA toolkit 11.1 or later.
Python libraries: see requirements.txt for exact library dependencies. You can use the following commands with Miniconda3 to create and activate your jelly_brain Python environment:
- cd ./build/
- conda create -n "jelly_brain" python=3.8.13
- conda activate jelly_brain
- <PATH TO YOUR CONDA PYTHON EXEC> python -m pip install -r requirements.txt
Docker users:
- Ensure you have correctly installed the NVIDIA container runtime.
- Use the Dockerfile to build an image with the required library dependencies.

We borrow a lot from these repositories:

**BrainSpace

https://github.com/MICA-MNI/BrainSpace

ENIGMA toolbox is to be installed spearately following guides online. ENIGMA toolbox is used for subcortical displays

Name		Name	Last commit message	Last commit date
Latest commit History 60 Commits
.vscode		.vscode
docs		docs
media		media
resources		resources
src		src
.gitignore		.gitignore
01_bis-trim_timeseries.ipynb		01_bis-trim_timeseries.ipynb
01_explore-loading.ipynb		01_explore-loading.ipynb
02_static_gradient.ipynb		02_static_gradient.ipynb
03_dynamic_gradient.ipynb		03_dynamic_gradient.ipynb
04_gradient_metrics.ipynb		04_gradient_metrics.ipynb
05_gradient_stability.ipynb		05_gradient_stability.ipynb
06_personality_index.ipynb		06_personality_index.ipynb
07_gradients_matching.ipynb		07_gradients_matching.ipynb
08_frame-selection.ipynb		08_frame-selection.ipynb
09_gradient_films_order.ipynb		09_gradient_films_order.ipynb
10_emotion_cohesion.ipynb		10_emotion_cohesion.ipynb
11_emotion_networks.ipynb		11_emotion_networks.ipynb
12_emotion_prediction.ipynb		12_emotion_prediction.ipynb
Dockerfile		Dockerfile
LICENSE.md		LICENSE.md
README.md		README.md
requirements.txt		requirements.txt