R/features.R

In njtierney/brolgar: Browse Over Longitudinal Data Graphically and Analytically in R

#' Calculate features of a `tsibble` object in conjunction with [features()]
#' 
#' You can calculate a series of summary statistics (features) of a given 
#'   variable for a dataset. For example, a three number summary, the minimum, 
#'   median, and maximum, can be calculated for a given variable. This is 
#'   designed to work with the [features()] function shown in the examples.
#'   Other available features in `brolgar` include:
#'   
#'   - [feat_three_num()] - minimum, median, maximum
#'   - [feat_five_num()] - minimum, q25, median, q75, maximum.
#'   - [feat_ranges()] - min, max, range difference, interquartile range.
#'   - [feat_spread()]  - variance, standard deviation, median absolute distance,
#'    and interquartile range
#'   - [feat_monotonic()] - is it always increasing, decreasing, or unvarying?
#'   - [feat_diff_summary()] - the summary statistics of the differences 
#'  amongst a value, including the five number summary, as well as the 
#'  standard deviation and variance. Returns NA if there is only one 
#'  observation, as we can't take the difference of one observation, and a 
#'  difference of 0 in these cases would be misleading.
#'   
#'   - [feat_brolgar()]  all features in brolgar.
#' 
#' @param x A vector to extract features from.
#' @param ... Further arguments passed to other functions.
#' @name brolgar-features
#' @examples
#' 
#' # You can use any of the features `feat_*` in conjunction with `features` 
#' # like so:
#' heights %>%
#'   features(height_cm, # variable you want to explore
#'            feat_three_num) # the feature summarisation you want to perform

#' @rdname brolgar-features
#' @export
feat_three_num <- function(x, ...) {
  c(min = b_min(x, ...),
    med = b_median(x, ...), 
    max = b_max(x, ...))
}

#' @rdname brolgar-features
#' @export
feat_five_num <- function(x, ...) {
  c(
    min = b_min(x, ...),
    q25 = b_q25(x, ...),
    med = b_median(x, ...),
    q75 = b_q75(x, ...),
    max = b_max(x, ...)
  )
}

#' @rdname brolgar-features
#' @export
feat_ranges <- function(x, ...){
  c(
    min = b_min(x, ...),
    max = b_max(x, ...),
    range_diff = b_range_diff(x, ...),
    iqr = b_iqr(x, ...)
  )
}

#' @rdname brolgar-features
#' @export
feat_spread <- function(x, ...){
  c(
    var = b_var(x, ...),
    sd = b_sd(x, ...),
    mad = b_mad(x, ...),
    iqr = b_iqr(x, ...)
  )
}

#' @rdname brolgar-features
#' @export
feat_monotonic <- function(x, ...) {
  c(increase = increasing(x, ...),
    decrease = decreasing(x, ...), 
    unvary = unvarying(x, ...),
    monotonic = monotonic(x, ...))
}

#' @rdname brolgar-features
#' @export
feat_brolgar <- function(x, ...){
  c(
    min = b_min(x, ...),
    max = b_max(x, ...),
    median = b_median(x, ...),
    mean = b_mean(x, ...),
    q25 = b_q25(x, ...),
    q75 = b_q75(x, ...),
    range = b_range(x, ...),
    range_diff = b_range_diff(x, ...),
    sd = b_sd(x, ...),
    var = b_var(x, ...),
    mad = b_mad(x, ...),
    iqr = b_iqr(x, ...),
    increase = increasing(x, ...),
    decrease = decreasing(x, ...), 
    unvary = unvarying(x, ...),
    feat_diff_summary(x, ...)
  )
}

#' @rdname brolgar-features
#' @export
feat_diff_summary <- function(x, ...){
  c(
  diff_min = b_diff_min(x, ...),
  diff_q25 = b_diff_q25(x, ...),
  diff_median = b_diff_median(x, ...),
  diff_mean = b_diff_mean(x, ...),
  diff_q75 = b_diff_q75(x, ...),
  diff_max = b_diff_max(x, ...),
  diff_var = b_diff_var(x, ...),
  diff_sd = b_diff_sd(x, ...),
  diff_iqr = b_diff_iqr(x, ...)
  )
}