## Copyright (c) 2015-2019, James P. Howard, II <jh@jameshoward.us>
##
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#' @title Statistics Canada Name Coding
#'
#' @description
#' The modified Statistics Canada name coding procedure
#'
#' @param word string or vector of strings to encode
#' @param maxCodeLen maximum length of the resulting encodings, in characters
#' @param clean if \code{TRUE}, return \code{NA} for unknown alphabetical characters
#'
#' @details
#'
#' The variable \code{word} is the name to be encoded. The variable
#' \code{maxCodeLen} is the limit on how long the returned name code
#' should be. The default is 4.
#'
#' The \code{statcan} algorithm is only defined for inputs over the
#' standard French alphabet. Non-alphabetical characters are removed
#' from the string in a locale-dependent fashion. This strips spaces,
#' hyphens, and numbers. Other letters, such as "Ü," may be permissible
#' in the current locale but are unknown to \code{statcan}. For inputs
#' outside of its known range, the output is undefined and \code{NA} is
#' returned and a \code{warning} this thrown. If \code{clean} is
#' \code{FALSE}, \code{statcan} attempts to process the strings. The
#' default is \code{TRUE}.
#'
#' @return the Statistics Canada encoded character vector
#'
#' @references
#'
#' James P. Howard, II, "Phonetic Spelling Algorithm Implementations
#' for R," \emph{Journal of Statistical Software}, vol. 25, no. 8,
#' (2020), p. 1--21, <10.18637/jss.v095.i08>.
#'
#' Billy T. Lynch and William L. Arends. "Selection of surname coding
#' procedure for the SRS record linkage system." United States
#' Department of Agriculture, Sample Survey Research Branch, Research
#' Division, Washington, 1977.
#'
#' @family phonics
#'
#' @examples
#' statcan("William")
#' statcan(c("Peter", "Peady"))
#' statcan("Stevenson", maxCodeLen = 8)
#'
#' @export
statcan <- function(word, maxCodeLen = 4, clean = TRUE) {
## Remove umlauts and eszett
word <- gsub("\u00C0|\u00C2", "A", word, perl = TRUE)
word <- gsub("\u00C8|\u00C9|\u00CA|\u00CB", "E", word, perl = TRUE)
word <- gsub("\u00CE|\u00CF", "I", word, perl = TRUE)
word <- gsub("\u00D4", "O", word, perl = TRUE)
word <- gsub("\u00D9|\u00DB|\u00DC", "U", word, perl = TRUE)
word <- gsub("\u0178", "Y", word, perl = TRUE)
word <- gsub("\u00C7", "C", word, perl = TRUE)
## First, uppercase it and test for unprocessable characters
word <- toupper(word)
word[is.null(word)] <- NA
listNAs <- is.na(word)
if(any(nonalpha <- grepl("[^A-Z]", word, perl = TRUE)) && clean)
warning("unknown characters found, results may not be consistent")
word <- gsub("[^A-Z]*", "", word, perl = TRUE)
## First character of key = first character of name
first <- substr(word, 1, 1)
word <- substr(word, 2, nchar(word))
## Delete vowels and Y
word <- gsub("A|E|I|O|U|Y", "", word, perl = TRUE)
## Append word except for first character to first
word <- paste(first, word, sep = "")
## Remove duplicate consecutive characters
word <- gsub("([A-Z])\\1+", "\\1", word, perl = TRUE)
## Truncate to requested length
word <- substr(word, 1, maxCodeLen)
## Yeah, we already processed them, but now get rid of them
word[listNAs] <- NA
if(clean)
word[nonalpha] <- NA
return(word)
}
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