R/export_trip_list.R

In tlumip/swimctr: Oregon SWIM v2.5 Commercial Transport (CT) Model

#' Export local and inter-regional trip records in a combined trip list file
#'
#' @param hourly_faf_trips Data frame containing the final inter-regional flows,
#'   with origin, destination, and departure time appended for each trip
#' @param hourly_local_trips Data frame containing the final local (internal)'
#'   truck flows, with origin, destination, and departure time appended for each
#'   trip
#' @param save_to Filename for saving the final combined trip list in comma-
#'   separated value (CSV) format
#'
#' @details This function will typically be the last part of the model to run,
#'   for it combines the local and inter-regional truck trip records into a
#'   single trip file, with common fields for both. Missing values are inserted
#'   for data present in one dataset, but not in the other. The result is saved
#'   in a file for network analyses or post-processing. No values are returned
#'   by the function.
#'
#' @export
#' @examples
#' export_trip_list(hourly_faf_trips, hourly_local_trips, "Trips_CTTruck.csv")

export_trip_list <- function(hourly_faf_trips, hourly_local_trips, save_to) {

  ct_msg(header = "Export trip list")

  # Process the inter-regional (FAF) trip list first
  regional <- hourly_faf_trips %>%
    dplyr::transmute(
      origin = as.integer(origin),
      tripStartTime = as.integer(departure_time),
      destination = as.integer(destination),
      tourMode = direction,
      tripMode = status,
      truckID = NA,
      truckType = truck_type,
      sctg2, value, tons, travelTime = NA, distance = NA, dataset = "faf"
    )

  # Next do the same with local trips. At the present time CT does not specify
  # the commodity of the truck, so it as well as value and tons are set to
  # missing values
  local <- hourly_local_trips %>%
    dplyr::transmute(
      origin = origin,
      tripStartTime = as.integer(departure_time),
      destination = destination,
      tourMode = "internal",
      tripMode = "loaded",
      truckID = NA,
      truckType = truck_type,
      sctg2 = NA, value = NA, tons = NA, travelTime = travel_time, distance, dataset = "ct"
    )

  # Now simply combine the two datasets, and write them out to the specified
  # output file in CSV format
    combined <- dplyr::bind_rows(regional, local) %>%
      dplyr::arrange(origin, destination) %>%
      dplyr::mutate(
        origin = as.character(origin), destination = as.character(destination),
        truckID = 1:n())

  readr::write_csv(combined, save_to)
  print(paste(nrow(combined), "total trip records written to", save_to),
    quote = FALSE)

  # No value is returned
}