US COVID-19 Spread Analysis/Visualization using Information Theory

STAT 430 final project

Contributed by

All required dependencies are specified in requirements.txt.

We provide jupyter notebook file covid_raw_data_testing.ipynb to download and visualize correlation data between state-wise case reports.

To further analyze directional causality, use the script:

python analysis.py         # Single-core (debug)
mpirun python analysis.py  # Multi-core

To visualize data in interactive plotting, you can launch the dash app by:

python app/main.py

Name		Name	Last commit message	Last commit date
Latest commit History 2 Commits
app		app
assets		assets
.gitignore		.gitignore
CovidRawDataManager.py		CovidRawDataManager.py
CovidTemporalPrediction.py		CovidTemporalPrediction.py
EventDetection.py		EventDetection.py
GeographyDataManager.py		GeographyDataManager.py
GraphUtility.py		GraphUtility.py
LICENSE		LICENSE
README.md		README.md
TransferEntropy.py		TransferEntropy.py
analysis.py		analysis.py
exploratory_data_analysis.ipynb		exploratory_data_analysis.ipynb
requirements.txt		requirements.txt
time_series_forecast.ipynb		time_series_forecast.ipynb