R/antibiotic.R

In kwstat/lucid: Printing Floating Point Numbers in a Human-Friendly Format

#' Effectiveness of 3 antibiotics against 16 bacterial species.
#' 
#' Effectiveness of 3 antibiotics against 16 bacterial species.
#' 
#' The values reported are the minimum inhibitory concentration (MIC) in
#' micrograms/milliliter, which represents the concentration of antibiotic
#' required to prevent growth in vitro.
#' 
#' @name antibiotic
#' @docType data
#' @format A data frame with 16 observations on the following 5 variables.
#' \describe{ 
#' \item{\code{bacteria}}{bacterial species, 16 levels}
#' \item{\code{penicillin}}{MIC for penicillin}
#' \item{\code{streptomycin}}{MIC for streptomycin}
#' \item{\code{neomycin}}{MIC for neomycin} 
#' \item{\code{gramstain}}{Gram staining (positive or negative)} 
#' }
#' @source Will Burtin (1951). \emph{Scope}.  Fall, 1951.
#' @references
#' 
#' Wainer, H. (2009). A Centenary Celebration for Will Burtin: A Pioneer of
#' Scientific Visualization.  \emph{Chance}, 22(1), 51-55.
#' https://chance.amstat.org/2009/02/visrev221/
#' 
#' Wainer, H. (2009). Visual Revelations: Pictures at an Exhibition.
#' \emph{Chance}, 22(2), 46--54.
#' https://chance.amstat.org/2009/04/visrev222/
#' 
#' Wainer, H. (2014). Medical Illuminations: Using Evidence, Visualization and
#' Statistical Thinking to Improve Healthcare.
#' @keywords datasets
#' @examples
#' 
#' data(antibiotic)
#' lucid(antibiotic)
#' 
#' \dontrun{
#' # Plot the data similar to Fig 2.14 of Wainer's book, "Medical Illuminations"
#' 
#' require(lattice)
#' require(reshape2)
#' 
#' # Use log10 transform
#' dat <- transform(antibiotic,
#'                  penicillin=log10(penicillin),
#'                  streptomycin=log10(streptomycin),
#'                  neomycin=log10(neomycin))
#' dat <- transform(dat, sgn = ifelse(dat$gramstain=="neg", "-", "+"))
#' dat <- transform(dat,
#'                  bacteria = paste(bacteria, sgn))
#' dat <- transform(dat, bacteria=reorder(bacteria, -penicillin))
#' 
#' dat <- melt(dat)
#' 
#' op <- tpg <- trellis.par.get()
#' tpg$superpose.symbol$pch <- toupper(substring(levels(dat$variable),1,1))
#' tpg$superpose.symbol$col <- c("darkgreen","purple","orange")
#' trellis.par.set(tpg)
#' dotplot(bacteria ~ value, data=dat, group=variable,
#'         cex=2,
#'         scales=list(x=list(at= -3:3,
#'                       labels=c('.001', '.01', '.1', '1', '10', '100', '1000'))),
#'         main="Bacterial response to Neomycin, Streptomycin, and Penicillin",
#'         xlab="Minimum Inhibitory Concentration (mg/L)")
#' 
#' trellis.par.set(op)
#' 
#' }
#' 
#' 
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