R/data_2x2.R

In jorvlan/openvis: Create visualizations based on best open science practices

#' Repeated measures data structure
#'
#' This function transforms your data array('s) into the data structure that is needed to visualize a 2x2 repeated measure.
#' @name data_2x2
#' @param array_1 <numeric> the array of datapoints to be plotted
#' @param array_2 <numeric> the array of datapoints to be plotted
#' @param array_3 <numeric> the array of datapoints to be plotted
#' @param array_4 <numeric> the array of datapoints to be plotted
#' @param array_5 <numeric> the array of datapoints to be plotted
#' @param array_6 <numeric> the array of datapoints to be plotted
#' @param label_1 <string> group 1
#' @param label_2 <string> group 2
#' @param spread_x_ticks <bool> FALSE if 2 x ticks, TRUE if 4 x ticks
#' @param jit_distance <numeric> the amount of distance between jittered datapoints (0 by default)
#' @param jit_seed <numeric> the amount used in set.seed() (321 by default)
#' @return data_2x2
#'
#' @examples
#' \dontrun{
#' # Using an example dataset
#' df_2x2_1.0 <- data_2x2(
#'                       array_1 = iris$Sepal.Length[1:50],
#'                       array_2 = iris$Sepal.Length[51:100],
#'                       array_3 = iris$Sepal.Length[101:150],
#'                       array_4 = iris$Sepal.Length[81:130],
#'                       label_1 = 'congruent',
#'                       label_2 = 'incongruent',
#'                       jit_distance = .05,
#'                       jit_seed = 321,
#'                       spread_x_ticks = TRUE)
#'
#'
#'}
#'@export
data_2x2 <- function(array_1, array_2, array_3, array_4, array_5, array_6, label_1, label_2, jit_distance = 0, jit_seed = 321,
                              spread_x_ticks = FALSE) {

  # check arguments
  if (!is.numeric(array_1) & !is.numeric(array_2) & !is.numeric(array_3) & !is.numeric(array_4))
    stop("Input an array of integers as your data")

  if (!is.numeric(jit_distance))
    stop("Input an integer value for the amount of jitter")

  if(!is.numeric(jit_seed))
    stop("Input an integer value for the set.seed() function")

  if (length(array_1) > length(array_2) & length(array_3) & length(array_4)) {
    n <- length(array_1)
  }  else if (length(array_1) == length(array_2) & length(array_3) & length(array_4)) {
    n <- length(array_1)
  }  else if (length(array_2) > length(array_1) & length(array_3) & length(array_4)) {
    n <- length(array_2)
  }  else if (length(array_3) > length(array_1) & length(array_2) & length(array_4)) {
    n <- length(array_3)
  }  else {
    n <- length(array_4)
  }

  if (jit_distance > .2)
    stop("The maximum amount of jitter is 0.2, please specify a lower amount.")
  # set seed generator
  set.seed(jit_seed)

  if (missing(array_5) & missing(array_6) & spread_x_ticks == FALSE)
  data_2x2 <- data.frame(y_axis = c(array_1, array_2, array_3, array_4),
                         x_axis = rep(c(1,1.01,2,2.01), each=n),
                         id = factor(rep(1:n,2)),
                         group = rep(c(label_1, label_2), each=n))

  else if (!missing(array_5) & !missing(array_6) & spread_x_ticks == FALSE)
  data_2x2 <- data.frame(y_axis = c(array_1, array_2, array_3, array_4, array_5, array_6),
                          x_axis = rep(c(1,1.01,2,2.01,3,3.01), each=n),
                          id = factor(rep(1:n,2)),
                          group = rep(c(label_1, label_2), each=n))

  else if (missing(array_5) & missing(array_6) & spread_x_ticks == TRUE)
  data_2x2 <- data.frame(y_axis = c(array_1, array_2, array_3, array_4),
                           x_axis = rep(c(1,2,3,4), each=n),
                           id = factor(rep(1:n,2)),
                           group = rep(c(label_1, label_2), each=n))

  data_2x2$jit <- jitter(data_2x2$x_axis, amount = jit_distance)

  #data_2x2 <- data.frame(y_axis_2x2 = c(array_1, array_2, array_3, array_4),
  #                       x_axis_2x2 = rep(c(1,2), each=n),
  #                       id_2x2 = factor(rep(1:n,2)))

  #data_2x2$jit_2x2 <- jitter(data_2x2$x_axis_2x2, amount = jit_distance)
  #data_2x2$jit2_2x2 <- jitter(data_2x2$x2_axis_2x2, amount = jit_distance)

  # return dataframe
  return(data_2x2)

}