R/airnow_qualityControl.R

In MazamaScience/PWFSLSmoke: Utilities for Working with Air Quality Monitoring Data

#' @keywords AirNow
#' @export
#' @import MazamaCoreUtils
#'
#' @title Apply Quality Control to AirNow dataframe
#'
#' @param df multi-site restructured dataframe created within \code{airnow_createDataDataframe()}
#' @param limits low and high range of valid values
#' @description Perform range validation on AirNow data. This function also replaces values
#' of \code{-999} with \code{NA}.
#' @return Cleaned up dataframe of AIRSIS monitor data.
#' @seealso \link{airnow_createDataDataframes}

airnow_qualityControl <- function(
  df,
  limits = c(-Inf, Inf)
) {

  logger.debug(" ----- airnow_qualityControl() ----- ")

  # Extract the data portion only (omitting 'datetime')
  dataMatrix <- df[,-1]

  # Count the -999s for logging
  minus999Count <- length(dataMatrix[dataMatrix == -999.0 & !is.na(dataMatrix)])
  if (minus999Count > 0)
    logger.trace("Replacing %d values of -999 with NA", minus999Count)

  # Convert -999.0s to NAs
  dataMatrix[dataMatrix == -999.0 & !is.na(dataMatrix)] <- NA

  # Count the out of range values for logging
  outOfRangeLoCount <- length(dataMatrix[dataMatrix < limits[1] & !is.na(dataMatrix)])
  outOfRangeHiCount <- length(dataMatrix[dataMatrix > limits[2] & !is.na(dataMatrix)])

  if (outOfRangeLoCount > 0)
    logger.trace("Replacing %d values below %s with NA", outOfRangeLoCount, limits[1])

  if (outOfRangeHiCount > 0)
    logger.trace("Replacing %d values above %s with NA", outOfRangeHiCount, limits[2])

  # Convert out of range values to NAs
  dataMatrix[dataMatrix < limits[1] & !is.na(dataMatrix)] <- NA
  dataMatrix[dataMatrix > limits[2] & !is.na(dataMatrix)] <- NA

  # Replace the data
  df[,-1] <- dataMatrix

  return(df)

}