This repository holds various prediction algorithms for BG, using data from the OpenAPS Data Commons (which comes from Nightscout), with the intention to compare these algorithms to existing in-use prediction algorithms in the open source diabetes community.
The OpenAPS data must be in a subdirectory called "data" with a subdirectory of the ID number that contains the devicestatus.json file. For example:
./data/12345678/devicestatus.json
where . represents the current directory with the code
The code requires the following files:
bgdataframe.py
bgarray.py
datamatrix.py
mlalgorithm.py
ClarkeErrorGrid.py
This code also requires the following libraries:
pandas
numpy
gatspy
sklearn
Once all of these have been satsified, you can run the code with the following command:
python main.py