The function plot_agp produces an AGP plot that collapses all data into a single 24 hr "modal day".
plot_agp(data, LLTR = 70, ULTR = 180, smooth = TRUE, span = 0.3, dt0 = NULL,
inter_gap = 45, tz = "", title = FALSE)Plot of a 24 hr modal day collapsing all data to a single day.
DataFrame object with column names "id", "time", and "gl". Should only be data for 1 subject. In case multiple subject ids are detected, a warning is produced and only 1st subject is used.
Default: 70. Lower Limit of Target Range in mg/dL.
Default: 180. Upper Limit of Target Range in mg/dL.
Boolean indicating whether quantiles should be smoothed before plotting, default is TRUE
Optional parameter indicating span for loess smoothing. Default is 0.3, larger values result in more smoothing, recommended to choose between 0.1 to 0.7.
The time frequency for interpolation in minutes, the default will match the CGM meter's frequency (e.g. 5 min for Dexcom).
The maximum allowable gap (in minutes) for interpolation. The values will not be interpolated between the glucose measurements that are more than inter_gap minutes apart. The default value is 45 min.
A character string specifying the time zone to be used. System-specific (see as.POSIXct), but " " is the current time zone, and "GMT" is UTC (Universal Time, Coordinated). Invalid values are most commonly treated as UTC, on some platforms with a warning.
Indicator whether the title of the plot should display the subject ID. The default is FALSE (no title).
Elizabeth Chun
Only a single subject's data may be plotted. If smooth = TRUE, then the quantiles are loess smoothed with the specified span before plotting. The horizontal green lines represent the target range, default is 70-180 mg/dL. The black line is the median glucose value for each time of day. The dark blue shaded area represents 50% of glucose values - those between the 25th and 75 quantiles. The light blue shaded area shows 90% of the glucose values - those between the 5th and 95th quantiles. Additionally, the percents shown on the right hand side of the plot show which quantiles each line refers to - e.g. the line ending at 95% is the line corresponding to the 95th quantiles of glucose values.
Johnson et al. (2019) Utilizing the Ambulatory Glucose Profile to Standardize and Implement Continuous Glucose Monitoring in Clinical Practice, Diabetes Technology and Therapeutics 21:S2 S2-17-S2-25, tools:::Rd_expr_doi("10.1089/dia.2019.0034").
data(example_data_1_subject)
plot_agp(example_data_1_subject)
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