#' Pairwise Mood's median tests for all comparison of pairs of group medians
#'
#' @param d a data frame
#' @param x unquoted name of quantitative variable
#' @param g unquoted name of grouping variable (can be a factor, is treated as text)
#' @param tol (default 1e-6) any data values closer to overall median than this are discarded
#' @return data frame of groups being compared and unadjusted and Bonferroni-adjusted P-values
#'
#' @author Ken Butler, \email{butler@utsc.utoronto.ca}
#'
#' @examples
#' pairwise_median_test(datasets::mtcars, mpg, cyl)
#'
#' @importFrom stats median
#' @importFrom rlang enquo
#' @importFrom dplyr arrange
#' @importFrom dplyr distinct
#' @importFrom tidyr crossing
#' @importFrom purrr map2_dbl
#' @export
#'
pairwise_median_test <-
  function(d, x, g, tol = 1e-6) {
    x <- enquo(x)
    g <- enquo(g)
    d %>%
      distinct(!!g) %>%
      arrange(!!g) %>%
      pull(!!g) ->
    distinct_groups
    crossing(g1 = distinct_groups, g2 = distinct_groups) %>%
      filter(as.character(g1) < as.character(g2)) ->
    combos
    n <- length(distinct_groups)
    n_pair <- n * (n - 1) / 2
    combos %>%
      mutate(p_value = map2_dbl(g1, g2, ~ median_test_pair(d, !!x, as.character(!!g), .x, .y))) %>%
      mutate(adj_p_value = pmin(p_value * n_pair, 1))
    #
    # grand_median= d %>% summarize(med=median(!!x)) %>% pull(med)
    # tbl = d %>% mutate(y=(!!x)-grand_median) %>%
    #   filter(abs(y)>tol) %>%
    #   mutate(group=(!!g),above=ifelse(y<0,"below","above"))
    # tab=with(tbl,table(group=group,above=above))
    # s=summary(tab,correct=F)
    # d=data.frame(what=c("statistic","df","P-value"),
    #              value=c(s$statistic,s$parameter,s$p.value))
    # list(table=tab,test=d)
  }
#' Mood's median tests for one pair of groups
#'
#' @param d a data frame
#' @param x unquoted name of quantitative variable
#' @param g unquoted name of grouping variable (as character, not a factor)
#' @param g1 first group to compare (as text)
#' @param g2 second group to compare (as text)
#' @param tol (default 1e-6) any data values closer to overall median than this are discarded
#' @return (two-sided) P-value
#'
#' @author Ken Butler, \email{butler@utsc.utoronto.ca}
#'
#' @examples
#' median_test_pair(datasets::mtcars, mpg, cyl, 4, 8)
#'
#' @importFrom stats median
#' @importFrom rlang enquo
#' @importFrom purrr pluck
#' @export
#'
median_test_pair <- function(d, x, g, g1, g2, tol = 1e-6) {
  x <- enquo(x)
  g <- enquo(g)
  d %>%
    filter(!!g == g1 | !!g == g2) %>%
    median_test(!!x, !!g) ->
  test_results
  test_results$test %>% pluck("value", 3)
}