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#' Summarise Hand-off Files from Reserve Level Reports
#'
#' Summarise the seasonal kendall results from reserve level report hand-off files
#'
#' @param path chr string of full path to .csv handoff files
#' @param param chr string of variable to summarise
#' @param res_region a \code{data.frame} of look-up values that match 3-letter NERR site ids with regions
#'
#' @importFrom dplyr bind_rows group_by summarise
#' @importFrom magrittr %>%
#' @importFrom rlang .data
#' @importFrom tidyr pivot_longer
#'
#' @export
#'
#' @details This function is intended for use with the NERRS national level reporting scripts. It returns a \code{data.frame} that summarises the result of the reserve level seasonal kendall trend analyses found in the hand-off files generated by the reserve level reporting scripts. The summary groups reserves into regional classifications based on user-specified regions given in \code{res_region}.
#'
#' @author Julie Padilla
#'
#' @concept reporting
#'
#' @return Returns a \code{data.frame}
#'
summarise_handoff_files <- function(path, param, res_region = NULL) {
par_regex <- paste(param, '.csv$', sep = '')
files <- list.files('handoff_files', pattern = par_regex)
files <- paste0(path, '/', files, sep = '')
# generate a list of reserve abbreviations from found files
abbrev <- substr(files, 15, 17)
# check for existence of res_region
if(is.null(res_region))
stop('res_region must be specified. res_region should be a data.frame with two columns: one that consists of unique NERR reserve ids, and one that regional classifications.')
# load data for parameter of interest
x <- lapply(files, read.csv, header = TRUE, stringsAsFactors = FALSE, encoding = 'UTF-8') %>% bind_rows
x$NERR.Site.ID <- abbrev
x <- left_join(res_region, x)
# convert to tidy format
# x <- gather(x, key = .data$station, value = .data$trend, 4:length(names(x)))
# names(x)[c(4:5)] <- c('station', 'trend') # no longer needed with pivot_longer
x <- pivot_longer(x, 4:length(names(x)),
names_to = 'station', values_to = 'trend')
# remove results where trend is NA
x <- x[!is.na(x$trend), ]
# reassign values that dplyr can use
x$trend <- gsub('i', 'dec', x$trend)
x$trend <- gsub('h', 'inc', x$trend)
x$trend <- gsub('\u2014', 'insig', x$trend)
x$trend <- gsub('x', 'insuff', x$trend)
# summarise
x_summary <- x %>%
group_by(.data$Region) %>%
summarise(station_ct = n()
, decreasing = sum(.data$trend == 'dec')
, increasing = sum(.data$trend == 'inc')
, no_trend = sum(.data$trend == 'insig')
, insuff_data = sum(.data$trend == 'insuff'))
# tack on the parameter
x_summary$parameter <- param
# return the summary
return(x_summary)
}
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