R/SQOUnified.R

In SCCWRP/SQOUnified_archive: Tools for calculating SQO scores based on three Lines of Evidence (Benthic, Tox, Chem)

#' Compute the SQO index scores.
#'
#' @param benthic_data A data file string name that we want to compute SQO scores for.
#' @param SQO A list of the type of SQO scores that we want to compute
#'     (e.g., \code{c("MAMBI", "RBI")}).
#'     The default is \code{"all"}, meaning that all scores will be computed.
#' @usage
#' data(benthic_data)
#' data(site_assessment_criteria)
#' @examples
#' SQOUnified(benthic_data = benthic_data, LOE = "all")
#' SQOUnified(benthic_data = benthic_data, LOW = 'tox')
#'
#' @importFrom dplyr case_when full_join select rename mutate arrange
#' @importFrom purrr map
#' @importFrom tidyr spread


#' @export
SQOUnified <- function(benthic = NULL, chem = NULL, tox = NULL) {

  #load("data/site_assessment_criteria.RData")

  if (all(is.null(c(benthic,chem,tox)))){
    stop("
      No data was provided.
      Please provide benthic, chemistry and toxicity data to get the integrated site assessments
    ")
  }
  # check the data coming in before anything
  checkdata(benthic, chem, tox)



  # Compute ALL SQO scores

  # ---- Benthic ----
  if (!is.null(benthic)) {
    benthic <- benthic.sqo(benthic) %>%
      mutate(LOE = 'Benthic') %>%
      select(StationID, Replicate, SampleDate, LOE, Index, Score, Category, `Category Score`) %>%
      # David says only keep replicate 1.
      # 999 times out of 1000 there should only be one replicate
      filter(
        Replicate == 1
      ) %>%
      # The way i see it now is, Replicate becomes a useless field.
      # The other datatypes dont use it
      # SampleDate is not very useful either, not in the Bight program at least
      # The fact that the station is called B18 shows it was sampled in 2018, which is all we care about
      # besides, I queried the tbl_infaunalabundance_initial table,
      # there are not two sampledates for the same station, unlike SMC, which has permanent station names,
      # and sampledates are used to distinguish the station at different times
      # The Bight program however, which only samples every 5 years, puts the year of the sample in the stationid
      select(-c(Replicate,SampleDate))

  } else {
    benthic = data.frame(
      StationID = c(),
      LOE = c(),
      Index = c(),
      Score = c(),
      Category = c(),
      `Category Score` = c()
    )
  }

  # ---- Chemistry ----
  if (!is.null(chem)) {
    chem <- chem.sqo(chem) %>%
      mutate(LOE = 'Chemistry') %>%
      select(StationID, LOE, Index, Score, Category, `Category Score`)
  } else {
    chem = data.frame(
      StationID = c(),
      LOE = c(),
      Index = c(),
      Score = c(),
      Category = c(),
      `Category Score` = c()
    )
  }

  # ---- Toxicity ----
  if (!is.null(tox)) {
    tox <- tox.sqo(tox) %>%
      mutate(LOE = 'Toxicity') %>%
      select(StationID, LOE, Index, Score, Category, `Category Score`)
  } else {
    tox <- data.frame(
      StationID = c(),
      LOE = c(),
      Index = c(),
      Score = c(),
      Category = c(),
      `Category Score` = c()
    )
  }

  integrated <- bind_rows(benthic, chem, tox) %>%
    filter(
      grepl("SQO",Index)
    ) %>%
    select(
      StationID, LOE, Category
    ) %>%
    group_by(
      StationID
    ) %>%
    spread(
      LOE, Category
    ) %>%
    inner_join(
      site_assessment_criteria,
      by = c("Benthic","Chemistry","Toxicity")
    ) %>%
    select(
      StationID, `Site Assessment`
    ) %>%
    mutate(
      LOE = "Integrated",
      Index = "Site Assessment",
      Score = NA_real_,
      `Category Score` = NA_real_
    ) %>%
    select(
      StationID,
      LOE,
      Index,
      Score,
      Category = `Site Assessment`,
      `Category Score`
    )

  out <- bind_rows(
    benthic, chem, tox, integrated
  ) %>%
  arrange(
    StationID, LOE, Index
  )

  return(out)


}