create_fig_mx_summary {activAnalyzer} | R Documentation |
Create a radar plot for the mean or median MX metrics relating to the measurement of physical behavior
Description
This function creates a radar plot in relation to MX metrics as illustrated in Rowlands et al. (2018; doi:10.1249/MSS.0000000000001561) paper.
Usage
create_fig_mx_summary(
data,
labels = NULL,
mpa_cutpoint = 2690,
vpa_cutpoint = 6167
)
Arguments
data |
A dataframe with physical behavior metrics summarised using means or medians of valid days. It should have
been obtained using the |
labels |
A vector of numeric values setting the breaks of the Y axis of the radar plot. Default is a vector of 6 values with a start at 0 and an end at the maximum of all the computed MX metrics. |
mpa_cutpoint |
A numeric value at and above which time is considered as spent in moderate-to-vigorous physical activity (in counts/epoch length used to compute MX metrics). Defaut value is from Sasaki et al. (2011; doi:10.1016/j.jsams.2011.04.003) relating to vector magnitude. |
vpa_cutpoint |
A numeric value at and above which time is considered as spent in vigorous physical activity (in counts/epoch length used to compute MX metrics). Defaut value is from Sasaki et al. (2011; doi:10.1016/j.jsams.2011.04.003) relating to vector magnitude. |
Value
A ggplot object
Examples
file <- system.file("extdata", "acc.agd", package = "activAnalyzer")
mydata <- prepare_dataset(data = file)
mydata_with_wear_marks <- mark_wear_time(
dataset = mydata,
TS = "TimeStamp",
to_epoch = 60,
cts = "vm",
frame = 90,
allowanceFrame = 2,
streamFrame = 30
)
mydata_with_intensity_marks <- mark_intensity(
data = mydata_with_wear_marks,
col_axis = "vm",
equation = "Sasaki et al. (2011) [Adults]",
sed_cutpoint = 200,
mpa_cutpoint = 2690,
vpa_cutpoint = 6167,
age = 32,
weight = 67,
sex = "male"
)
summary_by_day <- recap_by_day(
data = mydata_with_intensity_marks,
col_axis = "vm",
age = 32,
weight = 67,
sex = "male",
valid_wear_time_start = "07:00:00",
valid_wear_time_end = "22:00:00",
start_first_bin = 0,
start_last_bin = 10000,
bin_width = 500
)$df_all_metrics
recap <- average_results(data = summary_by_day, minimum_wear_time = 10, fun = "median")
create_fig_mx_summary(
data = recap,
labels = seq(2500, 12500, 2500)
)