R/denormalize.R

In aqp: Algorithms for Quantitative Pedology

# create a (redundant) horizon-level attribute from a site-level attribute
# @ authors: andrew brown & dylan beaudette
#' Create a (redundant) horizon-level attribute from a site-level attribute
#'
#' @description Create a (redundant) horizon-level attribute from a site-level attribute. Specify a SoilProfileCollection and a site-level attribute from that SPC (by name) to receive a vector of length equal to the number of horizons containing the site-level values. This vector is directly usable with the SoilProfileCollection horizon setter.
#' 
#' \code{denormalize} is the inverse operation for the formula interface that "normalizes" a horizon level variable to site level:
#' 
#' \code{site(object) <- ~ horizonvar}
#' 
#' @details "Denormalization" is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data. Sometimes it is beneficial to have site-level attributes denormalized for grouping of horizon-level data in analyses. \code{denormalize} achieves this result for SoilProfileCollections. 
#' 
#' @author Andrew G. Brown, Dylan Beaudette
#' 
#' @param object A SoilProfileCollection
#' @param attr Site-level attribute name (character string) to denormalize to horizon.
#' @return A vector of values of equal length to the number of rows in the horizon table of the input SPC.
#' 
#' @export denormalize
#'
#' @examples
#' 
#' data(sp1)
#' 
#' # create a SoilProfileCollection from horizon data
#' depths(sp1) <- id ~ top + bottom
#' 
#' # create random site-level attribute `sitevar` with a binary (0/1) outcome
#' sp1$sitevar <- round(runif(length(sp1)))
#' 
#' # use denormalize() to create a mirror of sitevar in the horizon table
#' # name the attribute something different (e.g. `hz.sitevar`) to 
#' # prevent collision with the site attribute
#' # the attributes can have the same name but you will then need 
#' # site() or horizons() to access explicitly
#' sp1$hz.sitevar <- denormalize(sp1, 'sitevar')
#' 
#' # compare number of profiles to number of sitevar assignments
#' length(sp1)
#' table(sp1$sitevar)
#' 
#' # compare number of horizons to number of horizon-level copies of sitevar `hz.'sitevar`
#' nrow(sp1)
#' table(sp1$hz.sitevar)
denormalize <- function(object, attr) {
  
  # extract relevant pieces
  h <- horizons(object)
  s <- site(object)
  idn <- idname(object)
  if(!attr %in% names(s))
    stop("column name %s not found", call. = FALSE)
  
  # make a lookup table of attr in site
  lut <- s[[attr]]
  names(lut) <- s[[idn]]
  
  # return a horizon level attribute for same site IDs
  return(lut[h[[idn]]])
}