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#' Cultural Value of ethnospecies (CVe)
#'
#' Calculates the Cultural Value (CVe) per ethnospecies.
#' @usage CVe(data)
#'
#' @references
#' Reyes-Garcia, V., T. Huanca, V. Vadez, and W. Leonard. 2006. “Cultural, Practical, and Economic Value of Wild Plants: A Quantitative Study in the Bolivian Amazon.” Economic Botany.
#'
#' @param data is an ethnobotany data set with column 1 'informant' and 2 'sp_name' as row identifiers of informants and of ethnospecies names respectively.
#'
#' @keywords arith math logic methods misc survey
#'
#' @return Data frame of ethnospecies and Cultural Value (CVe) values.
#'
#' @section Warning:
#'
#' Identification for informants and ethnospecies 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 select group_by arrange bind_cols mutate
#' @importFrom magrittr %>%
#'
#'
#' @examples
#'
#' #Use built-in ethnobotany data example
#' CVe(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)
#'
#' CVe(eb_data)
#'
#'@export CVe
#'
CVe <- 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
CVe <- FCs <- UR_UN_FC <- CVe <- URdata <- data_Ci <- data_URs <- URps <- sp_name <- informant <- NULL
URdata <- data #create complete subset-able data
# calculate Use Reports per ethnospecies
# with function URs()
URS <- URs(URdata)
# Uce is the total number of uses reported for ethnospecies e
# with function NUs()
NUS <- NUs(URdata)
# divided by the potential uses of an ethnospecies in the study
NUS$Uce <- NUS$NUs/ncol(dplyr::select(URdata, -informant, -sp_name))
# Ice expresses the number of participants who
# listed the ethnospecies e as useful
# with function FCs()
FCS <- FCs(URdata)
# divided by the total number of people (n)
FCS$Ice <- FCS$FCs/length(unique(URdata$informant))
# bind the three data sets
UR_UN_FC <- dplyr::left_join(NUS, URS) %>% dplyr::left_join(FCS)
# IUce expresses the number of participants who mentioned
# each use of the ethnospecies e (also URs)
# divided by the total number of participants
UR_UN_FC$IUce <- UR_UN_FC$URs/length(unique(URdata$informant))
# calculate CVe = Uce * Ice*EIUce
UR_UN_FC$CVe <- UR_UN_FC$Uce * UR_UN_FC$Ice * UR_UN_FC$IUce
CVe <- dplyr::select(UR_UN_FC, sp_name, CVe) %>%
dplyr::arrange(-CVe) %>%
dplyr::mutate(CVe = round(CVe, 3))
as.data.frame(CVe)
}
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