R/filters.R

In tidytransit: Read, Validate, Analyze, and Map GTFS Feeds

#' Get a set of stops for a given set of service ids and route ids
#' 
#' @param gtfs_obj gtfs feed (tidygtfs object)
#' @param service_ids the service for which to get stops 
#' @param route_ids the route_ids for which to get stops 
#' @return stops table for a given service or route
#' 
#' @export
#' @examples \donttest{
#' library(dplyr)
#' local_gtfs_path <- system.file("extdata", "google_transit_nyc_subway.zip", package = "tidytransit")
#' nyc <- read_gtfs(local_gtfs_path)
#' select_service_id <- filter(nyc$calendar, monday==1) %>% pull(service_id)
#' select_route_id <- sample_n(nyc$routes, 1) %>% pull(route_id)
#' filtered_stops_df <- filter_stops(nyc, select_service_id, select_route_id)
#' }
filter_stops <- function(gtfs_obj, service_ids, route_ids) {
  some_trips <- dplyr::filter(gtfs_obj$trips, 
                              .data$service_id %in% service_ids &
                                .data$route_id %in% route_ids)
  
  some_stop_times <- dplyr::filter(gtfs_obj$stop_times,
                                   .data$trip_id %in% some_trips$trip_id) 
  
  some_stops <- dplyr::filter(gtfs_obj$stops,
                              .data$stop_id %in% some_stop_times$stop_id)
  
  return(some_stops)
}

#' Filter a gtfs feed so that it only contains a given set of trips
#' 
#' Only stop_times, stops, routes, services (in calendar and calendar_dates), shapes, 
#' frequencies and transfers belonging to one of those trips are kept.
#' 
#' @param gtfs_obj gtfs feed (tidygtfs object)
#' @param trip_ids vector with trip_ids
#' @return tidygtfs object with filtered tables
#' 
#' @seealso \code{\link{filter_feed_by_stops}}, \code{\link{filter_feed_by_area}}, \code{\link{filter_feed_by_date}}
#' @export
filter_feed_by_trips = function(gtfs_obj, trip_ids) {
  route_ids = gtfs_obj$trips[which(gtfs_obj$trips$trip_id %in% trip_ids),]
  route_ids <- unique(route_ids$route_id)
  
  # first batch via trip_ids
  gtfs_obj$stop_times <- gtfs_obj$stop_times[which(gtfs_obj$stop_times$trip_id %in% trip_ids),]
  gtfs_obj$routes <- gtfs_obj$routes[which(gtfs_obj$routes$route_id %in% route_ids),]
  gtfs_obj$trips <- gtfs_obj$trips[which(gtfs_obj$trips$trip_id %in% trip_ids),]
  
  # other
  trip_stop_ids = gtfs_obj$stop_times$stop_id
  service_ids = unique(gtfs_obj$trips$service_id)
  gtfs_obj$stops <- gtfs_obj$stops[which(gtfs_obj$stops$stop_id %in% trip_stop_ids),]
  
  gtfs_obj$.$dates_services <- filter(gtfs_obj$.$dates_services, service_id %in% service_ids)
  if(feed_contains(gtfs_obj, "calendar")) {
    gtfs_obj$calendar <- gtfs_obj$calendar[which(gtfs_obj$calendar$service_id %in% service_ids),]
  }
  if(feed_contains(gtfs_obj, "calendar_dates")) {
    gtfs_obj$calendar_dates <- gtfs_obj$calendar_dates[which(gtfs_obj$calendar_dates$service_id %in% service_ids),]
  }
  if(feed_contains(gtfs_obj, "shapes")) {
    gtfs_obj$shapes <- gtfs_obj$shapes[which(gtfs_obj$shapes$shape_id %in% gtfs_obj$trips$shape_id),]
  }
  if(feed_contains(gtfs_obj, "frequencies")) {
    gtfs_obj$frequencies <- gtfs_obj$frequencies[which(gtfs_obj$frequencies$trip_id %in% trip_ids),]
  }
  if(feed_contains(gtfs_obj, "transfers")) {
    gtfs_obj$transfers <- gtfs_obj$transfers[which(
      gtfs_obj$transfers$from_stop_id %in% trip_stop_ids & 
        gtfs_obj$transfers$to_stop_id %in% trip_stop_ids),]
  }
  
  gtfs_obj
}


#' Filter a gtfs feed so that it only contains trips that pass a given area
#' 
#' @inherit filter_feed_by_trips description return
#' 
#' @param gtfs_obj gtfs feed (tidygtfs object)
#' @param area all trips passing through this area are kept. Either a bounding box 
#'             (numeric vector with xmin, ymin, xmax, ymax) or a sf object.
#' @seealso \code{\link{filter_feed_by_stops}}, \code{\link{filter_feed_by_trips}}, \code{\link{filter_feed_by_date}}
#' @export
filter_feed_by_area <- function(gtfs_obj, area) {
  if(inherits(gtfs_obj$stops, "sf") && inherits(area, "sf")) {
    if(sf::st_crs(gtfs_obj$stops) != sf::st_crs(area)) {
      stop("feed and area are not in the same coordinate reference system")
    }
    sf::st_agr(gtfs_obj$stops) <- "constant"
    stops_area = sf::st_intersection(gtfs_obj$stops, sf::st_geometry(area))
    stop_ids = stops_area$stop_id
  } else {
    if(inherits(area, "sf")) {
      if(sf::st_crs(area)$input != "EPSG:4326") {
        area <- sf::st_transform(area, 4326)
      }
      area <- sf::st_bbox(area)
    } else {
      if(length(area) != 4 | !is.numeric(area)) {
        stop("bbox_area must be a numeric vector of length four, with xmin, ymin, xmax and ymax values")
      }
    }
    stop_ids = gtfs_obj$stops %>% filter_bbox(area)
    stop_ids <- unique(stop_ids$stop_id)
  }
  
  filter_feed_by_stops(gtfs_obj, stop_ids)
}

#' Filter a gtfs feed so that it only contains trips that pass the given stops
#' 
#' @inherit filter_feed_by_trips description return
#' 
#' @note
#' The returned gtfs_obj likely contains more than just the stops given (i.e. all stops
#' that belong to a trip passing the initial stop).
#' 
#' @param gtfs_obj gtfs feed (tidygtfs object)
#' @param stop_ids vector with stop_ids. You can either provide stop_ids or stop_names 
#' @param stop_names vector with stop_names (will be converted to stop_ids)
#' 
#' @seealso \code{\link{filter_feed_by_trips}}, \code{\link{filter_feed_by_trips}}, \code{\link{filter_feed_by_date}}
#' @export
filter_feed_by_stops = function(gtfs_obj, stop_ids = NULL, stop_names = NULL) {
  if(inherits(stop_ids, "sf")) {
    stop("Please use filter_feed_by_area with sf objects")
  }
  if(!is.null(stop_names)) {
    if(!is.null(stop_ids)) stop("Please provide either stop_ids or stop_names")
    stop_ids = gtfs_obj$stops$stop_id[which(gtfs_obj$stops$stop_name %in% stop_names)]
  }
  if(is.null(stop_ids) && is.null(stop_names)) stop("Please provide either stop_ids or stop_names")
  
  if(!any(stop_ids %in% gtfs_obj$stops$stop_id)) {
    stop("stop_ids found in stops table: ", paste(stop_ids, collapse = ", "))
  }

  trip_ids = gtfs_obj$stop_times[which(gtfs_obj$stop_times$stop_id %in% stop_ids),]
  trip_ids <- unique(trip_ids$trip_id)
  filter_feed_by_trips(gtfs_obj, trip_ids)
}

#' Filter a gtfs feed so that it only contains trips running on a given date
#' 
#' @inherit filter_feed_by_trips description return
#' 
#' @inheritParams filter_stop_times
#' 
#' @seealso \code{\link{filter_stop_times}}, \code{\link{filter_feed_by_trips}}, 
#'          \code{\link{filter_feed_by_trips}}, \code{\link{filter_feed_by_date}}
#' @export
filter_feed_by_date = function(gtfs_obj, extract_date,
                               min_departure_time, max_arrival_time) {
  st = filter_stop_times(gtfs_obj, extract_date, min_departure_time, max_arrival_time)
  st <- dplyr::as_tibble(st)
  attributes(st)$stops <- NULL
  attributes(st)$transfers <- NULL
  attributes(st)$sorted <- NULL
  attributes(st)$index <- NULL
  gtfs_obj$stop_times <- st[colnames(gtfs_obj$stop_times)]

  trip_ids <- unique(gtfs_obj$stop_times$trip_id)
  gtfs_obj$.$dates_services <- filter(gtfs_obj$.$dates_services, date == extract_date)
  filter_feed_by_trips(gtfs_obj, trip_ids)
}


filter_bbox <- function(data, bbox, coord_cols = c("stop_lon", "stop_lat")) {
  if(is.null(names(bbox))) {
    names(bbox)  <- c("xmin", "ymin", "xmax", "ymax")
  }
  
  data[which(data[[coord_cols[1]]] >= bbox["xmin"] &
               data[[coord_cols[2]]] >= bbox["ymin"] &
               data[[coord_cols[1]]] <= bbox["xmax"] &
               data[[coord_cols[2]]] <= bbox["ymax"]),]
}