Skip to content

scaubrey/PyLoopKit

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

PyLoopKit

A set of Python tools for building closed-loop insulin delivery apps (Python port of LoopKit)

Sample Prediction Figure from PyLoopKit

Link to Tidepool Loop repository version used for algorithm

Link of Tidepool LoopKit repository version used for algorithm

To use this project

Please review the documentation for usage instructions, input data requirements, and other important details.

To recreate the Virtual Environment

  1. This environment was developed with Anaconda. You'll need to install Miniconda or Anaconda for your platform.
  2. In a terminal, navigate to the directory where the environment.yml is located (likely the PyLoopKit folder).
  3. Run conda env create; this will download all of the package dependencies and install them in a virtual environment named py-loop. PLEASE NOTE: this may take up to 30 minutes to complete.

To use the Virtual Environment

In Bash run source activate py-loop, or in the Anaconda Prompt run conda activate py-loop to start the environment.

Run deactivate to stop the environment.

About

A set of Python tools for building closed-loop insulin delivery apps (Python port of LoopKit)

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • HTML 98.2%
  • Python 1.8%