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