Standardize the Accelerometry Data

Usage

acti_standardize_data(
  data,
  subset_xyz = TRUE,
  colname_time = "time",
  check_xyz = TRUE
)

acti_standardise_data(
  data,
  subset_xyz = TRUE,
  colname_time = "time",
  check_xyz = TRUE
)

Arguments

data: A `data.frame` with a column for time in `POSIXct` (usually `time`), and `X`, `Y`, `Z`
subset_xyz: should only the `time` (if available) and `XYZ` be subset?
colname_time: column name of header for time
check_xyz: Check if X/Y/Z is in the data

Value

A `data.frame` with `X/Y/Z` and a time in `time` (if available).

Examples


acti_standardize_data(acti_raw_data)
#> # A tibble: 240,500 × 4
#>    time                    X      Y     Z
#>    <dttm>              <dbl>  <dbl> <dbl>
#>  1 2019-09-17 18:40:00 0      0.008 0.996
#>  2 2019-09-17 18:40:00 0.016  0     1.01 
#>  3 2019-09-17 18:40:00 0.02  -0.008 1.00 
#>  4 2019-09-17 18:40:00 0.016 -0.012 1.01 
#>  5 2019-09-17 18:40:00 0.016 -0.008 1.01 
#>  6 2019-09-17 18:40:00 0.008 -0.008 1.01 
#>  7 2019-09-17 18:40:00 0.016 -0.008 1.02 
#>  8 2019-09-17 18:40:00 0.02  -0.004 1.02 
#>  9 2019-09-17 18:40:00 0.016  0     1.01 
#> 10 2019-09-17 18:40:00 0.012  0     1.02 
#> # ℹ 240,490 more rows
acti_standardise_data(acti_raw_data)
#> # A tibble: 240,500 × 4
#>    time                    X      Y     Z
#>    <dttm>              <dbl>  <dbl> <dbl>
#>  1 2019-09-17 18:40:00 0      0.008 0.996
#>  2 2019-09-17 18:40:00 0.016  0     1.01 
#>  3 2019-09-17 18:40:00 0.02  -0.008 1.00 
#>  4 2019-09-17 18:40:00 0.016 -0.012 1.01 
#>  5 2019-09-17 18:40:00 0.016 -0.008 1.01 
#>  6 2019-09-17 18:40:00 0.008 -0.008 1.01 
#>  7 2019-09-17 18:40:00 0.016 -0.008 1.02 
#>  8 2019-09-17 18:40:00 0.02  -0.004 1.02 
#>  9 2019-09-17 18:40:00 0.016  0     1.01 
#> 10 2019-09-17 18:40:00 0.012  0     1.02 
#> # ℹ 240,490 more rows