R/pat_trimDate.R

In MazamaScience/AirSensor: Process and Display Data from Air Quality Sensors

#' @export
#' @importFrom rlang .data
#' 
#' @title Trim a PurpleAir Timeseries object to full days
#' 
#' @param pat PurpleAir Timeseries \emph{pat} object.
#' 
#' @description Trims the date range of a \emph{pat} object to local time date
#' boundaries which are \emph{within} the range of data. This has the effect
#' of removing partial-day data records and is useful when calculating
#' full-day statistics.
#' 
#' @return A subset of the given \emph{pat} object.
#' 
#' @examples
#' library(AirSensor)
#' 
#' UTC_days <- 
#'   pat_filterDate(
#'     example_pat, 
#'     startdate = 20220702, 
#'     enddate = 20220705,
#'     timezone = "UTC"
#'   )
#' 
#' pat_multiPlot(UTC_days)
#'
#' local_days <- pat_trimDate(UTC_days)
#' pat_multiPlot(local_days)
#'

pat_trimDate <- function(
  pat = NULL
) {
  
  # ----- Validate parameters --------------------------------------------------
  
  MazamaCoreUtils::stopIfNull(pat)
  
  if ( !pat_isPat(pat) )
    stop("Parameter 'pat' is not a valid 'pa_timeseries' object.")
  
  if ( pat_isEmpty(pat) )
    stop("Parameter 'pat' has no data.")
  
  # Remove any duplicate data records
  pat <- pat_distinct(pat)
  
  # ----- Get the start and end times ------------------------------------------
  
  timeRange <- range(pat$data$datetime)
  timezone <- pat$meta$timezone
  
  # NOTE:  The dateRange() is used to restrict the time range to days that have
  # NOTE:  complete data.
  # NOTE:
  # NOTE:  floor/ceiling the start date depending on whether you are already
  # NOTE:  at the date boundary
  
  hour <- 
    MazamaCoreUtils::parseDatetime(timeRange[1], timezone = timezone) %>%
    lubridate::hour() # hour resolution is good enough to count as an entire day
  
  if ( hour == 0 ) {
    ceilingStart = FALSE
  } else {
    ceilingStart = TRUE
  }
  
  dateRange <-
    MazamaCoreUtils::dateRange(
      startdate = timeRange[1],
      enddate = timeRange[2],
      timezone = timezone,
      unit = "sec",
      ceilingStart = ceilingStart, # date boundary *after* the start
      ceilingEnd = FALSE   # date boundary *before* the end
    )
  
  # ----- Subset the "pat" object ----------------------------------------------
  
  data <- 
    pat$data %>%
    dplyr::filter(.data$datetime >= dateRange[1]) %>%
    dplyr::filter(.data$datetime < dateRange[2])
  
  pat$data <- data
  
  # ----- Return ---------------------------------------------------------------
  
  # Remove any duplicate data records
  pat <- pat_distinct(pat)
  
  return(pat)
  
}