scrutiny: Error Detection in Science

#
#
# means_1 <- c(4.525, 4.53, 4.535)
# means_2 <- c(3.735, 3.73, 3.725)
#
# sds_1 <- c(1.065, 1.07, 1.075)
# sds_2 <- c(0.925, 0.92, 0.915)
#
# values_1 = means_1
# values_2 = means_2
# dir = "outward"
# label_x_axis = NULL
# label_y_axis = "Test statistic"
# text_size = 12
# color_1 = "royalblue1"
# color_2 = "red"
# alpha_1 = 0.5
# alpha_2 = 0.5
# tag = ggplot2::waiver()
#
#
# # TO DO: CREATE SPACE BETWEEN BAR GROUP WITHIN A *SINGLE* PLOT; SEE
# # https://www.learnbyexample.org/r-bar-plot-ggplot2/
#
#
# # Visualize RIVETS using columns
# #
# # `rivets_plot_cols()` displays the relationship between the rounding bounds of
# # a reported summary statistic (such as means or standard deviations) and a
# # corresponding test statistic (such as *t*).
# #
# # @param values_1,values_2 Numeric or string coercible to numeric (length 3).
# #   Each vector consists of one reported statistic plus the lower and upper
# #   bounds of the original number, as determined by [`unround()`].
# # @param dir String (length 1). Direction on the x-axis in which the test
# #   statistic increases. Either `"forward"`, `"backward"`, `"inward"`, or
# #   `"outward"`.
# # @param label_x_axis String (length 2). X-axis labels. They should signify the
# #   summary statistic.
# # @param label_y_axis String (length 1). Y-axis label. It should signify the
# #   test statistic. Default is `"Test statistic"`.
# # @param text_size Numeric. Base text size. Default is `12`.
# # @param color_1,color_2 String. Line colors. Defaults are `"royalblue1"` and
# #   `"red"`.
# # @param tag Tag for the whole plot. Default is [`waiver()`], i.e., no tag.
# #
# # @return
# # @export
# #
# # @references Brown, N. J. L., & Heathers, J. (2019). Rounded Input Variables,
# #   Exact Test Statistics (RIVETS). PsyArXiv.
# #   https://doi.org/10.31234/osf.io/ctu9z
# #
# # @examples
# # # In the t-test context, a pair of means
# # # along with their rounding bounds:
# # rivets_plot_cols(
# #   values_1 = c(4.525, 4.53, 4.535),
# #   values_2 = c(3.735, 3.73, 3.725),
# #   dir = "outward",
# #   label_x_axis = c("Mean 2", "Mean 1"),
# #   label_y_axis = "Test statistic (t)",
# #   tag = "a"
# # )
# #
# # # Also in the t-test context,
# # # the same for standard deviations:
# # rivets_plot_cols(
# #   values_1 = c(1.065, 1.07, 1.075),
# #   values_2 = c(0.925, 0.92, 0.915),
# #   dir = "backward",
# #   label_x_axis = c("SD 2", "SD 1"),
# #   label_y_axis = "Test statistic (t)",
# #   tag = "b"
# # )
#
#
# rivets_plot_cols <- function(values_1,
#                              values_2,
#                              dir,
#                              label_x_axis = NULL,
#                              label_y_axis = "Test statistic",
#                              text_size = 12,
#                              color_1 = "royalblue1",
#                              color_2 = "red",
#                              alpha_1 = 0.5,
#                              alpha_2 = 0.5,
#                              tag = ggplot2::waiver()) {
#
#
#   # Checks ---
#
#   if (!is.null(label_x_axis)) {
#     if (length(label_x_axis) != 2) {
#       cli::cli_abort(c(
#         "`label_x_axis` has length {length(label_x_axis)}",
#         "x" = "It must have length 0 or 2."
#       ))
#     }
#   }
#
#   check_length(values_1, 3)
#   check_length(values_2, 3)
#   check_length(dir, 1)
#   # check_length(label_x_axis, 2)
#   check_length(label_y_axis, 1)
#   check_length(text_size, 1)
#
#
#   # Main part ---
#
#   if (is.numeric(values_1)) {
#     labels_numbers_1 <- sort(values_1)
#   } else {
#     labels_numbers_1 <- values_1
#   }
#
#   if (is.numeric(values_2)) {
#     labels_numbers_2 <- sort(values_2)
#   } else {
#     labels_numbers_2 <- values_2
#   }
#
#   labels_min_max_1 <- as.factor(c("Min", "Reported", "Max"))
#
#   temp <- values_1
#   values_1 <- values_2
#   values_2 <- temp
#
#   col_sizes_1 <- 3:1
#   col_sizes_2 <- col_sizes_1
#
#   if (dir == "forward") {
#     col_sizes_1 <- rev(col_sizes_1)
#     col_sizes_2 <- rev(col_sizes_2)
#   } else if (dir == "inward") {
#     col_sizes_2 <- rev(col_sizes_2)
#   } else if (dir == "outward") {
#     col_sizes_1 <- rev(col_sizes_1)
#   } else if (dir != "backward") {
#     cli::cli_abort(c(
#       "`dir` given as `{dir}`",
#       "x" = "It has to be either \"forward\", \"backward\",
#       \"inward\", or \"outward\"."
#     ))
#   }
#
#
#   col_sizes <- append(col_sizes_1, col_sizes_2)
#   labels_numbers <- append(labels_numbers_1, labels_numbers_2)
#   labels_min_max <- append(labels_min_max_1, rev(labels_min_max_1))
#   x_position <- c("a", "a", "a", "b", "b", "b")  # c(rep("a", 3), rep("b", 3))
#   side <- c(1, 1, 1, 2, 2, 2)  # c(rep("left", 3), rep("right", 3))
#
#
#   # labels_numbers_1_new <- labels_numbers[1:3] %>%
#   #   restore_zeros() %>%
#   #   stringr::str_flatten(" ")
#
#   # labels_numbers_2_new <- labels_numbers[4:6] %>%
#   #   restore_zeros() %>%
#   #   stringr::str_flatten(" ")
#
#   labels_numbers <- restore_zeros(labels_numbers)
#
#   label_less <- "≤"
#
#   labels_numbers_1_new <- paste(
#     labels_numbers[1L],
#     label_less,
#     labels_numbers[2L],
#     label_less,
#     labels_numbers[3L]
#   )
#
#   labels_numbers_2_new <- paste(
#     labels_numbers[4L],
#     label_less,
#     labels_numbers[5L],
#     label_less,
#     labels_numbers[6L]
#   )
#
#   # labels_numbers_new <-
#   #   c(rep(labels_numbers_1_new, 3), rep(labels_numbers_2_new, 3))
#
#   labels_numbers_new <-
#     rep(c(labels_numbers_1_new, labels_numbers_2_new), 3)
#
#
#   # For labels: Check out the answer starting with "First, create and save as
#   # object plot" at:
#   # https://stackoverflow.com/questions/16279295/axis-labels-for-each-bar-and-each-group-in-bar-charts-with-dodged-groups
#
#
#
#   df <- tibble::tibble(
#     col_sizes,
#     labels_numbers,
#     labels_min_max,
#     x_position,
#     side
#   )
#
#   # Following this site with regards to `geom_col()`:
#   # https://ggplot2.tidyverse.org/reference/position_dodge.html
#   df3 <- tibble::tibble(
#     x = c(rep("a", 3), rep("b", 3)),
#     y = col_sizes,
#     g = c(1:3, 1:3),
#     # color = c(1, 1, 1, 2, 2, 2),
#     labels_numbers,
#     labels_numbers_new,
#     color = rep(c(color_1, color_2), each = 3)
#   )
#
#   dfcol_args <- list(position = "dodge2", width = 0.75)
#
#
#   # New plot, adjusted from ggplot2 docs linked above:
#   plot_out <- ggplot2::ggplot(df3, ggplot2::aes(
#     x, y, group = g, fill = color
#   )) +
#     ggplot2::geom_col(
#       position = "dodge2", fill = df3$color, alpha = alpha_1
#     ) +
#     ggplot2::scale_x_discrete(
#       labels = labels_numbers_new
#     ) +
#     ggplot2::scale_y_continuous(
#       # labels = NULL,  # not sure why this was in the former version!
#       breaks = 1:6,  # 1:3
#       expand = ggplot2::expansion(c(0, 0.05))
#     ) +
#     # ggplot2::scale_color_manual(values = c(color_1, color_2)) +
#     ggplot2::labs(
#       y = label_y_axis,
#       tag = tag
#     ) +
#     ggplot2::theme(
#       panel.grid.major.x = ggplot2::element_blank(),
#       panel.grid.minor.y = ggplot2::element_blank(),
#       legend.position = "none"
#     )
#
#
#   return(plot_out)
#
#
#
#   # # Old RIVETS plot:
#   # ggplot2::ggplot(data = df, ggplot2::aes(
#   #   x = x_position,
#   #   y = col_sizes,
#   #   fill = side
#   # )) +
#   #   ggplot2::geom_col(width = 0.5) +
#   #   ggplot2::scale_x_discrete(
#   #     breaks = 1:6,
#   #     labels = labels_numbers
#   #   ) +
#   #   ggplot2::theme(
#   #     legend.position = "none"
#   #   )
#
#
#   # df <- tibble::tibble(
#   #   col_sizes_1, col_sizes_2,
#   #   labels_min_max_1,
#   #   labels_numbers_1 = factor(labels_numbers_1, levels = labels_numbers_1),
#   #   labels_numbers_2 = factor(labels_numbers_2, levels = labels_numbers_2)
#   # )
#
#
#   # Right-side plot:
#   plot_1 <- ggplot2::ggplot(df, ggplot2::aes(
#     x = labels_numbers_1,
#     y = col_sizes_1
#   )) +
#     ggplot2::geom_col(fill = color_2, alpha = alpha_2) +    # col_1_args
#     ggplot2::scale_y_continuous(
#       labels = NULL,
#       breaks = 1:3,
#       expand = ggplot2::expansion(c(0, 0.05))
#     ) +
#     ggplot2::labs(y = NULL) +
#     ggplot2::theme_minimal(base_size = text_size) +
#     ggplot2::theme(
#       panel.grid.major.x = ggplot2::element_blank(),
#       panel.grid.minor.y = ggplot2::element_blank(),
#       legend.position = "none"
#     )
#
#
#   # Left-side plot:
#   plot_2 <- ggplot2::ggplot(df, ggplot2::aes(
#     x = labels_numbers_2,
#     y = col_sizes_2
#   )) +
#     ggplot2::geom_col(fill = color_1, alpha = alpha_1) +    # col_2_args
#     ggplot2::scale_y_continuous(
#       labels = labels_min_max_1,
#       breaks = 1:3,
#       expand = ggplot2::expansion(c(0, 0.05))
#     ) +
#     ggplot2::theme_minimal(base_size = text_size) +
#     ggplot2::theme(
#       panel.grid.major.x = ggplot2::element_blank(),
#       panel.grid.minor.y = ggplot2::element_blank(),
#       legend.position = "none"
#     ) +
#     ggplot2::labs(
#       y = label_y_axis,
#       tag = tag
#     )
#
#
#   if (is.null(label_x_axis)) {
#     plot_1 <- plot_1 + ggplot2::labs(x = NULL)
#     plot_2 <- plot_2 + ggplot2::labs(x = NULL)
#   } else {
#     plot_1 <- plot_1 + ggplot2::labs(x = label_x_axis[2L])
#     plot_2 <- plot_2 + ggplot2::labs(x = label_x_axis[1L])
#   }
#
#
#   # Create and return a composite plot:
#   patchwork::wrap_plots(
#     plot_2,
#     patchwork::plot_spacer(),
#     plot_1,
#     widths = c(2.5, 1, 2.5)
#   )
#
# }
#
#
#
# # Examples ----------------------------------------------------------------
#
# label_test_stat <- expression(paste(
#   "Test statistic (", italic("t"), ")"
# ))
#
# tag_a <- expression(bold("a"))
# tag_b <- expression(bold("b"))
#
# plot_means <- rivets_plot_cols(
#   values_1 = means_1,
#   values_2 = means_2,
#   dir = "outward",
#   label_x_axis = c("Mean 2", "Mean 1"),
#   label_y_axis = label_test_stat,
#   tag = tag_a
# )
#
# plot_sds <- rivets_plot_cols(
#   values_1 = sds_1,
#   values_2 = sds_2,
#   dir = "backward",
#   label_x_axis = c("Standard deviation 2", "Standard deviation 1"),
#   label_y_axis = label_test_stat,
#   tag = tag_b
# )
#
# plot_both <- patchwork::wrap_plots(plot_means / plot_sds)
#
#
# # ggplot2::ggsave(
# #   "rivets_plot_cols", device = "png",
# #   width = 16, height = 14,
# #   units = "cm"
# # )
#
#
#