#' Whittle Duplicate Conflict-Years by Conflict Hostility
#'
#' @description \code{whittle_conflicts_hostility()} is in a class of
#' do-it-yourself functions for coercing (i.e. "whittling") conflict-year
#' data with cross-sectional units to unique conflict-year data by
#' cross-sectional unit. The inspiration here is clearly the problem
#' of whittling dyadic dispute-year data into true dyad-year data (like in
#' the Gibler-Miller-Little conflict data). This particular
#' function will keep the observations with the highest observed hostility.
#'
#' @return \code{whittle_conflicts_hostility()} takes a dyad-year data frame
#' or leader-dyad-year data frame with a declared conflict attribute type
#' and, grouping by the dyad and year, returns just those observations that
#' have the highest observed dispute-level fatality. This will not eliminate
#' all duplicates, far from it, but it's a sensible second or third cut
#' (after whittling onsets in \code{whittle_conflicts_onsets()} the extent
#' to which dispute-level hostility is a good heuristic for
#' dispute-level severity/importance.
#'
#' @details Dyads are capable of having multiple disputes in a given year,
#' which can create a problem for merging into a complete dyad-year
#' data frame. Consider the case of France and Italy in 1860, which
#' had three separate dispute onsets that year (MID#0112, MID#0113, MID#0306),
#' as illustrative of the problem. The default process in \pkg{peacesciencer}
#' employs several rules to whittle down these duplicate dyad-years for
#' merging into a dyad-year data frame. These are available in
#' \code{add_cow_mids()} and \code{add_gml_mids()}.
#'
#' \code{wc_hostility()} is a simple, less wordy, shortcut for the same function.
#'
#' @author Steven V. Miller
#'
#' @param data a data frame with a declared conflict attribute type.
#' @param ... optional, only to make the shortcut work
#'
#' @references
#'
#' Miller, Steven V. 2021. "How {peacesciencer} Coerces Dispute-Year Data into Dyad-Year Data".
#' URL: \url{http://svmiller.com/peacesciencer/articles/coerce-dispute-year-dyad-year.html}
#'
#' @name whittle_conflicts_hostility
#'
#' @examples
#'
#' \donttest{
#' # just call `library(tidyverse)` at the top of the your script
#' library(magrittr)
#' gml_dirdisp %>% whittle_conflicts_onsets() %>% whittle_conflicts_hostility()
#'
#' cow_mid_dirdisps %>% whittle_conflicts_onsets() %>% whittle_conflicts_hostility()
#'
#'
#' }
#'
whittle_conflicts_hostility <- function(data) {
if(is.null(attributes(data)$ps_conflict_type)) {
stop("The 'whittle' class of functions in {peacesciencer} only works on conflict data available in the package.")
}
if (length(attributes(data)$ps_data_type) > 0 && attributes(data)$ps_data_type == "dyad_year" && attributes(data)$ps_conflict_type == "gml") {
attr_ps_data_type <- attributes(data)$ps_data_type
attr_ps_system <- attributes(data)$ps_system
attr_ps_conflict_type <- attributes(data)$ps_conflict_type
data %>%
arrange(.data$ccode1, .data$ccode2, .data$year) %>%
group_by(.data$ccode1, .data$ccode2, .data$year) %>%
mutate(duplicated = ifelse(n() > 1, 1, 0)) %>%
group_by(.data$ccode1, .data$ccode2, .data$year, .data$duplicated) %>%
# Keep the highest hostility
filter(.data$hostlev == max(.data$hostlev)) %>%
arrange(.data$ccode1, .data$ccode2, .data$year) %>%
# practice safe group_by()
ungroup() %>%
select(-.data$duplicated) -> data
attr(data, "ps_data_type") <- attr_ps_data_type
attr(data, "ps_system") <- attr_ps_system
attr(data, "ps_conflict_type") <- attr_ps_conflict_type
} else if (length(attributes(data)$ps_data_type) > 0 && attributes(data)$ps_data_type == "dyad_year" && attributes(data)$ps_conflict_type == "cow-mid") {
attr_ps_data_type <- attributes(data)$ps_data_type
attr_ps_system <- attributes(data)$ps_system
attr_ps_conflict_type <- attributes(data)$ps_conflict_type
data %>%
left_join(., cow_mid_disps %>% select(.data$dispnum, .data$hostlev)) %>%
arrange(.data$ccode1, .data$ccode2, .data$year) %>%
group_by(.data$ccode1, .data$ccode2, .data$year) %>%
mutate(duplicated = ifelse(n() > 1, 1, 0)) %>%
group_by(.data$ccode1, .data$ccode2, .data$year, .data$duplicated) %>%
# Keep the highest hostlev
filter(.data$hostlev == max(.data$hostlev)) %>%
arrange(.data$ccode1, .data$ccode2, .data$year) %>%
# practice safe group_by()
ungroup() %>%
select(-.data$duplicated) -> data
attr(data, "ps_data_type") <- attr_ps_data_type
attr(data, "ps_system") <- attr_ps_system
attr(data, "ps_conflict_type") <- attr_ps_conflict_type
} else if (length(attributes(data)$ps_data_type) > 0 && attributes(data)$ps_data_type == "leader_dyad_year" && attributes(data)$ps_conflict_type == "gml") {
data[ , c('styear', 'stmon', 'settle', 'fatality', 'mindur', 'maxdur', 'hiact', 'hostlev', 'recip', 'outcome')] <- list(NULL)
attr_ps_data_type <- attributes(data)$ps_data_type
attr_ps_system <- attributes(data)$ps_system
attr_ps_conflict_type <- attributes(data)$ps_conflict_type
data %>%
left_join(., gml_mid_disps ) -> hold_this
hold_this %>%
arrange(.data$ccode1, .data$obsid1, .data$ccode2, .data$obsid2, .data$year) %>%
group_by(.data$ccode1, .data$obsid1, .data$ccode2, .data$obsid2, .data$year) %>%
mutate(duplicated = ifelse(n() > 1, 1, 0)) %>%
group_by(.data$ccode1, .data$obsid1, .data$ccode2, .data$obsid2, .data$year, .data$duplicated) %>%
# Keep the highest hostility
filter(.data$hostlev == max(.data$hostlev)) %>%
arrange(.data$ccode1, .data$obsid1, .data$ccode2, .data$obsid2, .data$year) %>%
# practice safe group_by()
ungroup() %>%
select(-.data$duplicated) -> data
data[ , c('styear', 'stmon', 'settle', 'fatality', 'mindur', 'maxdur', 'hiact', 'hostlev', 'recip', 'outcome')] <- list(NULL)
attr(data, "ps_data_type") <- attr_ps_data_type
attr(data, "ps_system") <- attr_ps_system
attr(data, "ps_conflict_type") <- attr_ps_conflict_type
} else {
stop("whittle_conflicts_hostility() doesn't recognize the data supplied to it.")
}
return(data)
}
#' @rdname whittle_conflicts_hostility
#' @export
wc_hostility <- function(...) peacesciencer::whittle_conflicts_hostility(...)
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