R/zwc.R

In arendsee/zwc: fasta word counter

#' @useDynLib zwc
#' @importFrom Rcpp sourceCpp
#' @importFrom graphics hist
NULL

#' Cound words in fasta file
#' 
#' @param k Word size
#' @param file FASTA filename
#' @param text FASTA data as character vector
#' @export
#' @examples
#' # Get system FASTA file holding the Agathis dammara chloroplast
#' # protein seqences
#' aa_file <- system.file("Agathis_dammara.chloroplast.faa", package=("zwc"))
#' # Count 1-mers (character frequency)
#' fasta_wc(aa_file, k=1)
#' # Count 2-mers
#' fasta_wc(aa_file, k=2)
#'
#' # A raw string of text can be given
#' fasta_wc(k=2, text="AAATTTTTAAATATATATATATATATATATA")
#'
#' # Or a FASTA file as a string
#' data(mito_dna)
#' fasta_wc(k=2, text=mito_dna) 
fasta_wc <- function(k=1, file="", text=NULL){
  d <- NULL
  if(file.exists(file)){
    d <- wc_from_file(k, file)
  }
  else if(! is.null(text)){
    d <- wc_from_string(k, text)
  } else {
    warning("Please provide 'file' or 'text' arguments")
  }
  class(d) <- append('wordcount', class(d))
  return(d)
}

#' Histograph of counts
#' 
#' @param x a class wordcount entity
#' @param ... other arguments for hist()
#' @return a histogram plot
#' @export
hist.wordcount <- function(x, ...) {
  # I know, this is a dumb way to plot it, but for now I am just testing
  hist(x$count, ...)
}

#' Bar plot of counts
#' 
#' @param x a class wordcount entity
#' @param ... other arguments for ggplot2::geom_bar()
#' @return a bar plot
#' @export
plot.wordcount <- function(x, ...) {
  ggplot2::ggplot(x) +
    ggplot2::geom_bar(ggplot2::aes_string('word', 'count'), stat='identity', ...)
}