iglu (version 4.2.2)

optimized_iglu_functions: Optimized Calculations of Time Dependent iglu Metrics

Description

The function optimized_iglu_functions optimizes the calculation of all time dependent iglu metrics by extracting the CGMS2DayByDay calculation and passing the result into each function.

Usage

optimized_iglu_functions(data, dt0 = NULL, inter_gap = 45, tz = "", timelag = 15, lag = 1)

Value

If a data.frame object is passed, then a tibble object with 1 row for each subject and one column for each metric is returned.

Arguments

data

DataFrame object with column names "id", "time", and "gl".

dt0

The time frequency for interpolation in minutes, the default will match the CGM meter's frequency (e.g. 5 min for Dexcom).

inter_gap

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.

tz

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.

timelag

Integer indicating the time period (# minutes) over which rate of change is calculated. Default is 15, e.g. rate of change is the change in glucose over the past 15 minutes divided by 15.

lag

Integer indicating which lag (# days) to use. Default is 1.

Details

Returns a tibble object with 1 row for each subject and a column for each metric. This function includes time dependent iglu metrics only. For metric specific information, please see the corresponding function documentation.

Examples

data(example_data_1_subject)
optimized_iglu_functions(example_data_1_subject)

# Pass some arguments to possibly change the defaults
optimized_iglu_functions(example_data_1_subject, dt0 = 5, inter_gap = 30)

data(example_data_5_subject)
optimized_iglu_functions(example_data_5_subject)