Create a figure with metrics shown for each day — create_fig_res_by

The function generates a figure with several common metrics shown for each day of the physical behavior measurement.

Usage

create_fig_res_by_day(
  data,
  minimum_wear_time_for_analysis = 10,
  start_day_analysis = "00:00:00",
  end_day_analysis = "23:59:00",
  language = c("en", "fr", "de"),
  metrics = c("all", "volume", "step_acc", "int_distri"),
  epoch_label = "60s"
)

Arguments

data: A dataframe with results obtained using the prepare_dataset, mark_wear_time, mark_intensity, and then the recap_by_day functions.
minimum_wear_time_for_analysis: A numeric value to indicate the minimum number of hours of wear time that was considered to validate a day.
start_day_analysis: A character value to indicate the start of the period that was considered to validate a day based on wear time.
end_day_analysis: A character value to indicate the end of the period that was considered to validate a day based on wear time.
language: A character value for setting the language with which the figure should be created: en for english; fr for french.
metrics: A character value for setting the metrics to be shown in the figure. "volume" refers to "activity volume" metrics, step_acc" refers to "step accumulation" metrics, and "int_distri" refers to intensity distribution metrics. By default, the function provides all computed metrics.
epoch_label: A character value to be pasted into the names of the variables to build the figure

Value

A ggplot object

Examples

# \donttest{
file <- system.file("extdata", "acc.agd", package = "activAnalyzer")
mydata <- prepare_dataset(data = file)
mydata_with_wear_marks <- mark_wear_time(
    dataset = mydata, 
    TS = "TimeStamp", 
    cts  = "vm", 
    frame = 90, 
    allowanceFrame = 2, 
    streamFrame = 30
    )
#> frame is 90
#> streamFrame is 30
#> allowanceFrame is 2
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",
    )
#> You have computed intensity metrics with the mark_intensity() function using the following inputs: 
#>     axis = vm
#>     sed_cutpoint = 200 counts/min
#>     mpa_cutpoint = 2690 counts/min
#>     vpa_cutpoint = 6167 counts/min
#>     equation = Sasaki et al. (2011) [Adults]
#>     age = 32
#>     weight = 67
#>     sex = male
summary_by_day <- recap_by_day(
    data = mydata_with_intensity_marks, 
    age = 32, 
    weight = 67, 
    sex = "male",
    valid_wear_time_start = "07:00:00",
    valid_wear_time_end = "22:00:00"
    )$df_all_metrics
#> Joining with `by = join_by(date)`
#> Joining with `by = join_by(date)`
#> Joining with `by = join_by(date)`
#> You have computed results with the recap_by_day() function using the following inputs: 
#>          age = 32
#>          weight = 67
#>          sex = male
create_fig_res_by_day(summary_by_day, 
    minimum_wear_time_for_analysis = 10, 
    start_day_analysis = "00:00:00", 
    end_day_analysis = "23:59:00", 
    language = "en")

# }