# Getting started
# Citing
If you are using AGATA in your research, please support the research by citing:
Cappon G, Sparacino G, Facchinetti A. AGATA: A toolbox for automated glucose data analysis.
J Diabetes Sci Technol. 2022. DOI: 10.1177/19322968221147570.
# Step 1: Install AGATA
Installation of AGATA can be easily performed by including the AGATA folder in the MATLAB® PATH. To do so:
Download the latest AGATA release (e.g.
X.Y.Z
) from Github --> here (opens new window);Unzip the downloaded archive and move the
agata-X.Y.Z
folder to the desired location, for example~/MATLAB/
;Open MATLAB®;
To use the AGATA functions in the current MATLAB® session (or within a specific script), add
agata-X.Y.Z
source folder and subfolders to the current MATLAB® PATH by executing in the command window (or at the top of the script)
addpath(genpath('~/MATLAB/agata-X.Y.Z/src'))
- Enjoy!
As an alternative, AGATA functionalities can be accessed via a dedicated graphical user interface (GUI) which can be installed as a standalone application. This solution is particularly convenient since it does not require users to have a valid MATLAB® licence to run AGATA.
To install AGATA's standalone version:
- Download the latest AGATA release (e.g.
X.Y.Z
) from Github --> here (opens new window); - Run the installer that you can find in the
standalone
folder. Be careful to run the right installer depending on the target operating system. - Enjoy!
# Step 2: Test AGATA
Once included in the MATLAB® PATH, it is time to test drive AGATA. For example, lets assume you want to compute the percentage of time in hyperglycemia of a given glucose trace using the function timeInHyperglycemia
(opens new window).
- Generate a dummy timetable representing a glucose trace:
time = datetime(2000,1,1,0,0,0):minutes(5):datetime(2000,1,1,0,0,0)+minutes(50);
data = timetable(zeros(length(time),1),'VariableNames', {'glucose'}, 'RowTimes', time);
data.glucose(1) = 40;
data.glucose(2:3) = 60;
data.glucose(4) = 80;
data.glucose(5:6) = 120;
data.glucose(7:8) = 200;
data.glucose(9:10) = 260;
data.glucose(11) = nan;
- Use
timeInHyperglycemia
(opens new window) to get the percentage of time in hyperglycemia (i.e., 40%):
tHyper = timeInHyperglycemia(data);
assert(tHyper == 40);