R/RcppExports.R

In gtfsrouter: Routing with 'GTFS' (General Transit Feed Specification) Data

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

#' rcpp_convert_time
#'
#' @noRd
rcpp_convert_time <- function(hms) {
    .Call(`_gtfsrouter_rcpp_convert_time`, hms)
}

#' rcpp_time_to_seconds
#'
#' Vectorize the above function
#'
#' @noRd
rcpp_time_to_seconds <- function(times) {
    .Call(`_gtfsrouter_rcpp_time_to_seconds`, times)
}

#' rcpp_make_timetable
#'
#' Make timetable from GTFS stop_times. Both stop_ids and trip_ids are vectors
#' of unique values which are converted to unordered_maps on to 1-indexed
#' integer values.
#'
#' @noRd
rcpp_make_timetable <- function(stop_times, stop_ids, trip_ids) {
    .Call(`_gtfsrouter_rcpp_make_timetable`, stop_times, stop_ids, trip_ids)
}

#' rcpp_csa
#'
#' Connection Scan Algorithm for GTFS data. The timetable has 
#' [departure_station, arrival_station, departure_time, arrival_time,
#'     trip_id],
#' with all entries as integer values, including times in seconds after
#' 00:00:00. The station and trip IDs can be mapped back on to actual station
#' IDs, but do not necessarily form a single set of unit-interval values
#' because the timetable is first cut down to only that portion after the
#' desired start time. These are nevertheless used as direct array indices
#' throughout, so are all size_t objects rather than int. All indices in the
#' timetable and transfers DataFrames, as well as start_/end_stations, are
#' 1-based, but they are still used directly which just means that the first
#' entries (that is, entry [0]) of station and trip vectors are never used.
#'
#' @noRd
rcpp_csa <- function(timetable, transfers, nstations, ntrips, start_stations, end_stations, start_time, max_transfers) {
    .Call(`_gtfsrouter_rcpp_csa`, timetable, transfers, nstations, ntrips, start_stations, end_stations, start_time, max_transfers)
}

#' rcpp_freq_to_stop_times
#'
#' @noRd
rcpp_freq_to_stop_times <- function(frequencies, stop_times, nrows, sfx) {
    .Call(`_gtfsrouter_rcpp_freq_to_stop_times`, frequencies, stop_times, nrows, sfx)
}

#' Haversine for variable x and y
#'
#' @return single distance
#'
#' @note The sxd and syd values could be calculated in arrays, each value of
#' which could be determined with only n operations, rather than the n2 used
#' here. Doing so, however, requires very large C arrays which are often
#' problematic, so this is safer.
#'
#' @noRd
NULL

rcpp_transfer_nbs <- function(stops, dlim) {
    .Call(`_gtfsrouter_rcpp_transfer_nbs`, stops, dlim)
}

#' rcpp_traveltimes
#'
#' Calculate isochrones using Connection Scan Algorithm for GTFS data. Works
#' largely as rcpp_csa. Returns a list of integer vectors, with [i] holding
#' sequences of stations on a given route, the end one being the terminal
#' isochrone point, and [i+1] holding correpsonding trip numbers.
#'
#' All elements of all data are 1-indexed
#'
#' @noRd
rcpp_traveltimes <- function(timetable, transfers, nstations, start_stations, start_time_min, start_time_max, minimise_transfers, max_traveltime) {
    .Call(`_gtfsrouter_rcpp_traveltimes`, timetable, transfers, nstations, start_stations, start_time_min, start_time_max, minimise_transfers, max_traveltime)
}