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#' Relative Importance index (RI)
#'
#' Calculates the relative importance index (RI) per species, published by Pardo-de-Santayana (2003).
#' @usage RIs(data)
#'
#' @references
#' Tardio, Javier, and Manuel Pardo-de-Santayana. 2008. “Cultural Importance Indices: A Comparative Analysis Based on the Useful Wild Plants of Southern Cantabria (Northern Spain) 1.” Economic Botany 62 (1): 24–39.
#'
#' @param data is an ethnobotany data set with column 1 'informant' and 2 'sp_name' as row identifiers of informants and of species names respectively.
#' The rest of the columns are the identified ethnobotany use categories. The data should be populated with counts of uses per person (should be 0 or 1 values).
#'
#' @keywords arith math logic methods misc survey
#'
#' @return Data frame of species and relative importance index (RI) values.
#'
#' @section Warning:
#'
#' Identification for informants and species must be listed by the names 'informant' and 'sp_name' respectively in the data set.
#' The rest of the columns should all represent separate identified ethnobotany use categories. These data should be populated with counts of uses per informant (should be 0 or 1 values).
#'
#' @importFrom dplyr filter summarize select left_join group_by
#' @importFrom magrittr %>%
#' @importFrom stats aggregate
#'
#' @examples
#'
#' #Use built-in ethnobotany data example
#'
#' RIs(ethnobotanydata)
#'
#' #Generate random dataset of three informants uses for four species
#'
#' eb_data <- data.frame(replicate(10,sample(0:1,20,rep=TRUE)))
#' names(eb_data) <- gsub(x = names(eb_data), pattern = "X", replacement = "Use_")
#' eb_data$informant <- sample(c('User_1', 'User_2', 'User_3'), 20, replace=TRUE)
#' eb_data$sp_name <- sample(c('sp_1', 'sp_2', 'sp_3', 'sp_4'), 20, replace=TRUE)
#'
#' RIs(eb_data)
#'
#' @export RIs
#'
RIs <- function(data) {
#Add error stops ####
#Check that packages are loaded
{
if (!requireNamespace("dplyr", quietly = TRUE)) {
stop("Package \"dplyr\" needed for this function to work. Please install it.",
call. = FALSE)
}
if (!requireNamespace("magrittr", quietly = TRUE)) {
stop("Package \"magrittr\" needed for this function to work. Please install it.",
call. = FALSE)
}
}# end package check
## Check that use categories are greater than zero
if (!any(sum(dplyr::select(data, -informant, -sp_name)>0))){
warning("The sum of all UR is not greater than zero. Perhaps not all uses have values or are not numeric.")
data<-data[stats::complete.cases(data), ]
}
## Use 'complete.cases' from stats to get to the collection of obs without NA
if (any(is.na(data))) {
warning("Some of your observations included \"NA\" and were removed. Consider using \"0\" instead.")
data<-data[stats::complete.cases(data), ]
}#end error stops
# Set the variables to NULL first, appeasing R CMD check
FCps <- RFCstestdata <- informant <- sp_name <- RFCstestdata2 <- RNUs <- RNUsdataaggr <- RNUstestdata <- RFCs <- NULL
#create subsettable data for RFCs
RFCdata <- data
RFCdata$FCps <- rowSums(dplyr::select(RFCdata, -informant, -sp_name) > 0)
#all UR greater than zero to count of '1' FC
RFCdata <- RFCdata %>% dplyr::mutate_if(is.numeric, ~1 * (. != 0))
#calculate and create data set of RFCs
RFCs <- RFCdata %>%
dplyr::group_by(sp_name) %>%
dplyr::summarize(FCs = sum(FCps)) %>%
dplyr::mutate(RFCs = FCs/max(FCs), FCs = NULL) %>%
dplyr::arrange(-RFCs)
#create subsettable data for RNUs
RNUstestdata <- data
#calculate RNUs
RNUsdataaggr <- stats::aggregate(dplyr::select(RNUstestdata, -informant, -sp_name),
by = list(sp_name = RNUstestdata$sp_name),
FUN = sum)
#all UR greater than zero to count of '1' FC
RNUsdataaggr <- RNUsdataaggr %>% dplyr::mutate_if(is.numeric, ~1 * (. != 0))
#counts of all use per specise (NUs)
RNUsdataaggr$NUs <- RNUsdataaggr %>% dplyr::select(-sp_name) %>% rowSums()
#divide uses per species by max uses
RNUsdataaggr$RNUs <- RNUsdataaggr$NUs/max(RNUsdataaggr$NUs)
RNUs <- dplyr::select(RNUsdataaggr, sp_name, RNUs)
#merge RNUs and RFCs
RIs <- merge(RNUs, RFCs, by = "sp_name")
RIs$RIs <- (RIs$RNUs + RIs$RFCs)/2
#change sort order
RIs <- dplyr::arrange(RIs, -RIs) %>%
dplyr::select(sp_name, RIs) %>%
dplyr::mutate(RIs = round(RIs, 3))
as.data.frame(RIs)
}
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