This Swift module uses LoopAlgorithm to create C functions for generating predictions and prediction dates from JSON data.
This is achieved by creating a foreign function interface (FFI) in Swift by using the unofficial @_cdecl Swift function. This interfaces the Swift code with C. Then we can create a dynamic library, import it into a Python (or other) repositories, and use for example ctypes to compile the C code.
You can find the C-exposed functions in the file Sources/LoopAlgorithmToPython/LoopAlgorithmToPython.swift.
Python API functions are located in loop_to_python_api/api.py.
python_tests/ contains examples of executing all the functions as well as example files providing templates on how to structure the input files.
initialize_exception_handlers()
Initializes the exception and signal handlers in the Swift library to provide more informative error messages.
generate_prediction(json_file, len=72)
Generates a prediction based on the provided JSON input.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.len(optional): The number of prediction values to generate. Defaults to 72.
- Returns: A list of prediction values.
get_prediction_dates(json_file)
Fetches prediction dates based on the provided JSON input.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: A list of prediction dates as strings.
get_prediction_values_and_dates(json_file)
Combines the generate_prediction and get_prediction_dates functions to return both prediction values and dates.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: A tuple containing a list of prediction values and a list of prediction dates.
get_glucose_effect_velocity(json_file, len=72)
Fetches the glucose effect velocity, which is equivalent to Insulin Counteraction Effect (ICE).
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.len(optional): The number of values to fetch. Defaults to 72.
- Returns: A list of glucose effect velocity values.
get_glucose_effect_velocity_dates(json_file)
Fetches the dates associated with the glucose effect velocity.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: A list of dates as strings.
get_glucose_velocity_values_and_dates(json_file)
Combines the get_glucose_effect_velocity and get_glucose_effect_velocity_dates functions to return both glucose effect velocity values and dates.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: A tuple containing a list of glucose effect velocity values and a list of dates.
get_dose_recommendations(json_file)
Uses the Loop algorithm to get the recommended bolus dose and basal rate.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: A dictionary containing the dose recommendation. Example:
{'automatic': {
'bolusUnits': 0,
'basalAdjustment': {
'unitsPerHour': 0.5,
'duration': 1800 # Seconds
}
}
}
get_active_carbs(json_file)
Fetches the active carbohydrates based on the provided JSON input.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: The active carbohydrates as a double.
get_active_insulin(json_file)
Fetches the active insulin based on the provided JSON input.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: The active insulin as a double.
percent_absorption_at_percent_time(percent_time)
Calculates the percentage of carbohydrate absorption at a given percent time using a piecewise linear model.
- Parameters:
percent_time: The time as a fraction (e.g., 0.2 for 20%).
- Returns: The percentage of absorption as a double.
piecewise_linear_percent_rate_at_percent_time(percent_time)
Calculates the percentage rate of carbohydrate absorption at a given percent time using a piecewise linear model.
- Parameters:
percent_time: The time as a fraction (e.g., 0.2 for 20%).
- Returns: The percentage rate of absorption as a double.
linear_percent_rate_at_percent_time(percent_time)
Calculates the percentage rate of carbohydrate absorption at a given percent time using a linear model.
- Parameters:
percent_time: The time as a fraction (e.g., 0.2 for 20%).
- Returns: The percentage rate of absorption as a double.
get_dynamic_carbs_on_board(json_file)
Fetches the dynamic carbohydrates on board based on the provided JSON input.
- Parameters:
json_file: The JSON data input. See python tests and test files for example inputs.
- Returns: The dynamic carbohydrates on board as a double.
The file python_api/libLoopAlgorithmToPython.dylib contains the dynamic library that is containing the C-embedded Swift functions.
After making changes in the Swift code, rebuild the dynamic library by running chmod +x build.sh followed by ./build.sh.
Run command pytest.
Debugging with this pipeline can be a pain... Calling functions with python does not give informative error messages, even though the initialize_exception_handlers() helps a little bit.
What I found the most useful is to go into LoopAlgorithm repository and run existing tests, but changing the input json files to the input json file that I am trying to use with this repository.