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#' identityWordcount
#'
#' Create frequency-count table from a set of characters
#' which are assigned a standardized rank-order scores
#' from 10.0 to 1.0.
#'
#' @param orgn.df data.frame, scientific_name, pident
#' @param ntop numeric, return only N top words [50]
#' @return table, identity-count table with 100% - 20% standard
#' @keywords palmid wordcloud plot
#'
#' @import dplyr ggplot2
#' @export
identityWordcount <- function(orgn.df, ntop = 50){
# Standardize wordcount to fixed-rank values
# for consistent wordcloud plotting
# return only 'ntop' words
# in worcloud2() use:
# size = 0.2, ellipticity = 0.5
# Sort by 'pident', keep highest unique scientific_name match
orgn.df <- orgn.df[ order(orgn.df$pident, decreasing = T), ]
orgn.df <- orgn.df[ !duplicated(orgn.df$scientific_name), ]
# Transform pident to pseudo-Freq
# 100% --> 10
# 50% --> 5
# 25% --> 1
orgn.df$Freq <- ( ((orgn.df$pident - 25) / 75) * 9 ) + 1
return(orgn.df[1:ntop, ])
}
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