context("Pareto frontier function") # skips tests on CRAN since they require a specific version of java testthat::skip_on_cran() # create testing function default_tester <- function(r5r_core, origins = points[1:10,], destinations = points[1:10,], mode = "TRANSIT", departure_datetime = as.POSIXct("13-05-2019 14:00:00", format = "%d-%m-%Y %H:%M:%S"), time_window = 1L, percentiles = 50, fare_structure = NULL, fare_cutoffs = 0L, max_walk_time = Inf, max_bike_time = Inf, max_trip_duration = 120L, walk_speed = 3.6, bike_speed = 12, max_rides = 3, n_threads = Inf, verbose = FALSE, progress=TRUE) { results <- pareto_frontier( r5r_core, origins = origins, destinations = destinations, mode = mode, departure_datetime = departure_datetime, time_window = time_window, percentiles = percentiles, fare_structure = fare_structure, fare_cutoffs = fare_cutoffs, max_walk_time = max_walk_time, max_bike_time = max_bike_time, max_trip_duration = max_trip_duration, walk_speed = walk_speed, bike_speed = bike_speed, max_rides = max_rides, n_threads = n_threads, verbose = verbose ) return(results) } # load fare calculator object fare_structure_path <- system.file("extdata/poa/fares/fares_poa.zip", package = "r5r") fare_structure <- r5r::read_fare_structure(fare_structure_path) # errors and warnings ----------------------------------------------------- test_that("adequately raises errors", { # error related to using object with wrong type as r5r_core expect_error(default_tester("r5r_core")) # error related to using wrong origins/destinations object type multipoint_origins <- sf::st_cast(sf::st_as_sf(points[1:2,], coords = c("lon", "lat")), "MULTIPOINT") multipoint_destinations <- multipoint_origins list_origins <- list(id = c("1", "2"), lat = c(-30.02756, -30.02329), long = c(-51.22781, -51.21886)) list_destinations <- list_origins expect_error(default_tester(r5r_core, origins = multipoint_origins)) expect_error(default_tester(r5r_core, destinations = multipoint_destinations)) expect_error(default_tester(r5r_core, origins = list_origins)) expect_error(default_tester(r5r_core, destinations = list_destinations)) expect_error(default_tester(r5r_core, origins = "origins")) expect_error(default_tester(r5r_core, destinations = "destinations")) # error/warning related to using wrong origins/destinations column types origins <- destinations <- points[1:2, ] origins_char_lat <- data.frame(id = origins$id, lat = as.character(origins$lat), lon = origins$lon) origins_char_lon <- data.frame(id = origins$id, lat = origins$lat, lon = as.character(origins$lon)) destinations_char_lat <- data.frame(id = destinations$id, lat = as.character(destinations$lat), lon = destinations$lon) destinations_char_lon <- data.frame(id = destinations$id, lat = destinations$lat, lon = as.character(destinations$lon)) expect_error(default_tester(r5r_core, origins = origins_char_lat)) expect_error(default_tester(r5r_core, origins = origins_char_lon)) expect_error(default_tester(r5r_core, destinations = destinations_char_lat)) expect_error(default_tester(r5r_core, destinations = destinations_char_lon)) # error related to nonexistent mode expect_error(default_tester(r5r_core, mode = "pogoball")) # errors related to date formatting numeric_datetime <- as.numeric(as.POSIXct("13-05-2019 14:00:00", format = "%d-%m-%Y %H:%M:%S")) expect_error(default_tester(r5r_core, departure_datetime = "13-05-2019 14:00:00")) expect_error(default_tester(r5r_core, numeric_datetime)) # errors related to max_walk_time expect_error(default_tester(r5r_core, max_walk_time = "1000")) expect_error(default_tester(r5r_core, max_walk_time = NULL)) # errors related to max_bike_time expect_error(default_tester(r5r_core, max_bike_time = "1000")) expect_error(default_tester(r5r_core, max_bike_time = NULL)) # error/warning related to max_street_time expect_error(default_tester(r5r_core, max_trip_duration = "120")) # error related to non-numeric walk_speed expect_error(default_tester(r5r_core, walk_speed = "3.6")) # error related to non-numeric bike_speed expect_error(default_tester(r5r_core, bike_speed = "12")) # error related to too many or invalid percentiles expect_error(default_tester(r5r_core, percentiles = .3)) expect_error(default_tester(r5r_core, percentiles = 1:6)) }) test_that("adequately raises warnings - needs java", { # error/warning related to using wrong origins/destinations column types origins <- destinations <- points[1:2, ] origins_numeric_id <- data.frame(id = 1:2, lat = origins$lat, lon = origins$lon) destinations_numeric_id <- data.frame(id = 1:2, lat = destinations$lat, lon = destinations$lon) expect_warning(default_tester(r5r_core, origins = origins_numeric_id)) expect_warning(default_tester(r5r_core, destinations = destinations_numeric_id)) }) # adequate behaviour ------------------------------------------------------ test_that("output is correct", { # * output class --------------------------------------------------------- # expect results to be of class 'data.table', independently of the class of # 'origins'/'destinations' origins_sf <- destinations_sf <- sf::st_as_sf( points[1:10, ], coords = c("lon", "lat"), crs = 4326 ) result_df_input <- default_tester(r5r_core) result_sf_input <- default_tester(r5r_core, origins_sf, destinations_sf) expect_true(is(result_df_input, "data.table")) expect_true(is(result_sf_input, "data.table")) # expect each column to be of right class expect_true(typeof(result_df_input$from_id) == "character") expect_true(typeof(result_df_input$to_id) == "character") expect_true(typeof(result_df_input$travel_time ) == "integer") # * r5r options ---------------------------------------------------------- result_sf_input <- default_tester(r5r_core, origins_sf, destinations_sf, verbose = FALSE, progress=TRUE) # * arguments ------------------------------------------------------------ # expect all travel times to be lower than max_trip_duration origins <- destinations <- points[1:10,] max_trip_duration <- 60L df <- default_tester(r5r_core, origins, destinations, max_trip_duration = max_trip_duration) max_duration <- data.table::setDT(df)[, max(travel_time)] expect_true(max_duration <= max_trip_duration) # expect number of rows to be lower than or equal to nrow(origins) * nrow(destinations) max_trip_duration <- 300L df <- default_tester(r5r_core, origins, destinations, max_trip_duration = max_trip_duration) n_rows <- nrow(df) expect_true(n_rows <= nrow(origins) * nrow(destinations)) })