Package 'GTFSwizard'

Description

Converts a list-like GTFS feed to the class used by GTFSwizard. Character GTFS dates are converted to [Date] values, a date-to-service lookup is created, and missing shapes can optionally be inferred from stop locations.

Usage

as_wizardgtfs(gtfs_list, build_shapes = TRUE)

Arguments

Details

The input is checked for required tables, required fields, primary-key duplication, foreign-key consistency, increasing stop and shape sequences, valid service dates, and valid GTFS time strings. Times remain character values because GTFS permits hours greater than 24.

Value

A 'wizardgtfs' object.

See Also

[GTFSwizard::create_gtfs()], [GTFSwizard::get_shapes()]

Examples

gtfs_wizard <- as_wizardgtfs(for_rail_gtfs, build_shapes = TRUE)

Description

Creates and validates a GTFS Schedule feed from data frames. The required files and fields follow the current GTFS Schedule reference, including its conditional rules for route names, stop locations, and service calendars.

Usage

create_gtfs(
  agency,
  routes,
  trips,
  stop_times,
  stops,
  calendar = NULL,
  calendar_dates = NULL,
  shapes = NULL,
  frequencies = NULL,
  transfers = NULL,
  fare_attributes = NULL,
  fare_rules = NULL,
  build_shapes = TRUE,
  zipfile = NULL,
  ...
)

Arguments

Value

A validated 'wizardgtfs' object, invisibly written as well when 'zipfile' is supplied.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/)

Examples

feed <- create_gtfs(
  agency = data.frame(
    agency_id = "A", agency_name = "Demo Transit",
    agency_url = "https://example.com",
    agency_timezone = "America/Fortaleza"
  ),
  routes = data.frame(
    route_id = "R1", agency_id = "A", route_short_name = "1",
    route_long_name = "Central", route_type = 3
  ),
  trips = data.frame(route_id = "R1", service_id = "WK", trip_id = "T1"),
  stop_times = data.frame(
    trip_id = "T1", arrival_time = c("08:00:00", "08:10:00"),
    departure_time = c("08:00:00", "08:10:00"),
    stop_id = c("S1", "S2"), stop_sequence = c(1, 2)
  ),
  stops = data.frame(
    stop_id = c("S1", "S2"), stop_name = c("First", "Second"),
    stop_lat = c(-3.73, -3.74), stop_lon = c(-38.52, -38.53)
  ),
  calendar = data.frame(
    service_id = "WK", monday = 1, tuesday = 1, wednesday = 1,
    thursday = 1, friday = 1, saturday = 0, sunday = 0,
    start_date = "20260101", end_date = "20261231"
  )
)

Description

Adds a number of seconds to every non-empty arrival and departure time for selected trips. GTFS times above 24 hours are preserved.

Usage

delay_trip(gtfs, trip, duration)

Arguments

Value

A modified 'wizardgtfs' object.

See Also

[GTFSwizard::edit_speed()], [GTFSwizard::set_dwelltime()]

Examples

delayed <- delay_trip(
  for_rail_gtfs,
  trip = for_rail_gtfs$trips$trip_id[1:2],
  duration = 300
)

Description

Multiplies dwell time at selected trip-stop calls and propagates each change to all later times in the same trip. Arrival at the edited stop is retained; departure and subsequent calls move by the dwell-time difference.

Usage

edit_dwelltime(gtfs, trips = "all", stops = "all", factor)

Arguments

Value

A modified 'wizardgtfs' object.

See Also

[GTFSwizard::set_dwelltime()], [GTFSwizard::get_dwelltimes()]

Examples

edited <- edit_dwelltime(
  for_rail_gtfs,
  trips = for_rail_gtfs$trips$trip_id[1:2],
  stops = for_rail_gtfs$stops$stop_id[1:2],
  factor = 1.5
)

Description

Changes travel time between consecutive stops by dividing it by a speed multiplier. Dwell times are preserved and all downstream times are shifted.

Usage

edit_speed(gtfs, trips = "all", stops = "all", factor)

Arguments

Value

A modified 'wizardgtfs' object.

See Also

[GTFSwizard::get_speeds()], [GTFSwizard::get_durations()]

Examples

edited <- edit_speed(
  for_rail_gtfs,
  trips = for_rail_gtfs$trips$trip_id[1:2],
  stops = "all",
  factor = 1.25
)

Description

Opens a lightweight Shiny dashboard for exploring a GTFS feed. The dashboard shows summary cards, route and stop maps, service calendar, and key operational charts. Route, service, service-pattern, stop, date, and time filters update the dashboard without changing the original object.

Usage

explore_gtfs(gtfs = NULL)

Arguments

Value

A Shiny app object.

References

Ceder, A. (2007). *Public Transit Planning and Operation*. Vuchic, V. R. (2005). *Urban Transit: Operations, Planning, and Economics*. White, P. (2008). *Public Transport: Its Planning, Management and Operation*. Cascetta, E. (2009). *Transportation Systems Analysis*.

See Also

[GTFSwizard::as_wizardgtfs()], [GTFSwizard::get_shapes()], [GTFSwizard::plot_calendar()]

Examples

if (interactive()) {
  explore_gtfs()
  explore_gtfs(GTFSwizard::for_rail_gtfs)
}

Description

Filters a GTFS feed while preserving referential integrity across routes, trips, stops, shapes, calendars, frequencies, fares, and transfers.

Usage

filter_servicepattern(gtfs, servicepattern = NULL)

filter_date(gtfs, dates = NULL)

filter_service(gtfs, service)

filter_route(gtfs, route, keep = TRUE)

filter_trip(gtfs, trip, keep = TRUE)

filter_stop(gtfs, stop)

filter_time(gtfs, from = "00:00:00", to = "48:00:00")

Arguments

Details

'filter_stop()' retains the requested stop calls and therefore may return partial trips. 'filter_time()' retains individual stop calls whose arrival or departure falls inside the inclusive time interval and may also return partial trips. This behavior is useful for network experiments. Route, trip, service, service-pattern, and date filters retain complete trips.

'filter_date()' rewrites service availability as 'calendar_dates' additions for exactly the selected dates. Other filters preserve the selected services' original date ranges and exceptions.

Value

A 'wizardgtfs' object.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/)

See Also

[GTFSwizard::as_wizardgtfs()], [GTFSwizard::get_servicepattern()]

Examples

typical <- filter_servicepattern(for_rail_gtfs)
one_day <- filter_date(for_rail_gtfs, "2021-02-10")
one_route <- filter_route(for_rail_gtfs, for_rail_gtfs$routes$route_id[1])
two_trips <- filter_trip(for_rail_gtfs, for_rail_gtfs$trips$trip_id[1:2])
serving_stop <- filter_stop(for_rail_gtfs, for_rail_gtfs$stops$stop_id[1])
morning <- filter_time(for_rail_gtfs, from = "06:30:00", to = "10:00:00")

Description

A dataset containing GTFS (General Transit Feed Specification) data for Fortaleza's transit system by bus. The data includes information on routes, trips, stops, stop times, and other elements necessary for transit planning and analysis.

Format

An object of class wizardgtfs, containing multiple data frames:

agency

Data frame with 1 row and 7 columns, providing information about the transit agency, including agency name, URL, timezone, and contact details.

calendar

Data frame with 3 rows and 10 columns, detailing service availability by day of the week, start and end dates for each service.

fare_attributes

Data frame with 2 rows and 6 columns, showing fare information, including price, currency, payment method, and transfer rules.

fare_rules

Data frame with 345 rows and 5 columns, linking fare IDs to routes, along with optional restrictions on origins, destinations, and zones.

routes

Data frame with 345 rows and 9 columns, listing route details such as route ID, agency ID, route short and long names, route type, and colors.

shapes

Data frame with 125,776 rows and 5 columns, representing the spatial paths of routes with latitude, longitude, point sequence, and cumulative distance traveled.

stop_times

Data frame with 2,659,737 rows and 9 columns, including stop times for each trip, with arrival and departure times, stop sequence, and stop ID information.

stops

Data frame with 4,676 rows and 12 columns, containing information about each stop, including stop ID, name, location (latitude and longitude), and accessibility.

trips

Data frame with 85,410 rows and 9 columns, detailing trips associated with routes, including trip IDs, route IDs, direction, block, and shape IDs.

Details

The GTFS data format is widely used for representing public transportation schedules and associated geographic information. This dataset follows the GTFS standard and includes elements for advanced analysis in transit planning.

Source

Fortaleza transit agency (ETUFOR).

Examples

# Load the dataset
data(for_bus_gtfs)

# Access trips data
head(for_bus_gtfs$trips)

# Access stops data
head(for_bus_gtfs$stops)

Description

This dataset contains GTFS (General Transit Feed Specification) data for Fortaleza's rail transit system, managed by METROFOR. The data includes information on routes, trips, stops, stop times, shapes, and other necessary elements for transit analysis and planning.

Format

An object of class wizardgtfs, consisting of multiple data frames:

agency

Data frame with 1 row and 7 columns, providing information about the transit agency, including agency name, URL, timezone, language, and contact details.

calendar

Data frame with 1 row and 10 columns, detailing the service availability by day of the week, along with start and end dates for each service.

calendar_dates

Data frame with 26 rows and 3 columns, listing specific dates and exceptions (e.g., holidays) that modify the usual service pattern.

routes

Data frame with 3 rows and 9 columns, listing route details such as route ID, short and long names, route type, and colors associated with each route.

stops

Data frame with 39 rows and 10 columns, containing information about each stop, including stop ID, name, location (latitude and longitude), and additional details.

stop_times

Data frame with 3,420 rows and 10 columns, detailing arrival and departure times for each trip, along with stop sequences and stop IDs.

trips

Data frame with 215 rows and 7 columns, providing trip-specific information such as trip ID, headsign, direction, associated service ID, route ID, and shape ID.

shapes

Data frame with 80 rows and 5 columns, representing spatial paths of routes using latitude, longitude, point sequence, and cumulative distance traveled.

Details

The GTFS data format is widely adopted for representing public transportation schedules and spatial information. This dataset follows GTFS standards and is tailored for advanced analysis, particularly in transit planning and operations. Key tables included are 'agency', 'routes', 'stops', 'stop_times', 'trips', and 'shapes', each providing essential attributes for a comprehensive transit analysis.

Source

Cia Cearense de Transportes Metropolitanos (METROFOR).

Examples

# Load the dataset
data(for_rail_gtfs)

# Access trips data
head(for_rail_gtfs$trips)

# Access stops data
head(for_rail_gtfs$stops)

Description

Returns the departure at the lowest 'stop_sequence' for every trip.

Usage

get_1stdeparture(gtfs)

Arguments

Value

A tibble with 'route_id', 'trip_id', 'departure_time', and 'stop_id'.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/#stop_timestxt)

Examples

head(get_1stdeparture(for_rail_gtfs))

Description

Finds frequently served adjacent stop pairs, joins connected pairs into corridors, and measures them in a local metric CRS.

Usage

get_corridor(gtfs, i = 0.01, min_length = 1500, ...)

Arguments

Value

An 'sf' object with 'corridor', list-columns 'stop_id' and 'trip_id', numeric 'length' in meters, and WGS84 geometry. Segments are straight lines between stop coordinates, not shape geometry.

See Also

[GTFSwizard::plot_corridor()]

Examples

corridors <- get_corridor(for_rail_gtfs, i = 0.2, min_length = 100)

Description

The 'get_distances' function calculates distances within a 'wizardgtfs' object based on various methods. Depending on the 'method' chosen, it can calculate average route distances, trip-specific distances, or detailed distances between stops.

Usage

get_distances(gtfs, method = "by_trip", trips = "all")

Arguments

Details

The function calls specific sub-functions based on the selected method:

- "by_route": Calculates average distances per route.

- "by_trip": Calculate distances per trip.

- "detailed": Calculates detailed stop-to-stop distances within each route. Note that this method may be slow for large datasets.

Legacy dotted values remain accepted. If an invalid 'method' is provided, the function defaults to '"by_trip"' and issues a warning.

Value

A data frame with calculated distances based on the specified method:

If 'method = "by_route"'

Returns a summary by route and direction with trip counts, average distance, service pattern, and pattern frequency.

If 'method = "by_trip"'

Returns trip distance with route, direction, service pattern, and pattern frequency.

If 'method = "detailed"'

Returns a data frame with columns: 'shape_id', 'from_stop_id', 'to_stop_id', and 'distance'.

See Also

[GTFSwizard::as_wizardgtfs()], [GTFSwizard::get_servicepattern()]

Examples

# Calculate average route distances
distances_by_route <- get_distances(gtfs = for_rail_gtfs, method = "by_route", trips = 'all')

# Calculate distances by trip
distances_by_trip <- get_distances(gtfs = for_rail_gtfs, method = "by_trip", trips = 'all')


# Calculate detailed distances between stops
detailed_distances <- get_distances(gtfs = for_rail_gtfs, method = "detailed", trips = 'all')

Description

Calculates scheduled trip and segment durations in seconds.

Usage

get_durations(gtfs, method = "by_trip", trips = "all")

Arguments

Details

This function calls specific sub-functions based on the selected method:

- "by_route": Calculates average durations for each route.

- "by_trip": Calculates the total duration of each trip.

- "detailed": Calculates detailed durations between consecutive stops within each trip, excluding dwell times.

Legacy dotted values remain accepted. If an invalid 'method' is specified, the function defaults to '"by_trip"' and provides a warning.

Value

A data frame containing trip durations based on the specified method:

If 'method = "by_route"'

Includes dwell from first departure to final arrival and groups by direction when available.

If 'method = "by_trip"'

Includes dwell from first departure to final arrival and retains direction when available.

If 'method = "detailed"'

It does not include dwell times. Returns a data frame with columns: 'route_id', 'trip_id', 'hour', 'from_stop_id', 'to_stop_id', 'duration', 'service_pattern', and 'pattern_frequency'.

See Also

[GTFSwizard::as_wizardgtfs()], [GTFSwizard::get_servicepattern()]

Examples

# Calculate average route durations
durations_by_route <- get_durations(gtfs = for_rail_gtfs, method = "by_route", trips = 'all')

# Calculate trip durations
durations_by_trip <- get_durations(gtfs = for_rail_gtfs, method = "by_trip", trips = 'all')

# Calculate detailed durations between stops
detailed_durations <- get_durations(gtfs = for_rail_gtfs, method = "detailed", trips = 'all')

Description

The 'get_dwelltimes' function calculates dwell times within a 'wizardgtfs' object using different methods. Depending on the selected 'method', it can provide average dwell times per route, per trip, by hour, or detailed dwell times at each stop.

Usage

get_dwelltimes(gtfs, max_dwelltime = 90, method = "by_trip", ...)

Arguments

Details

This function calls specific sub-functions based on the selected method:

- "by_hour": Calculates the average dwell time for each hour of the day.

- "by_route": Calculates average dwell times across each route.

- "by_trip": Calculates the mean dwell time for each trip.

- "detailed": Calculates departure minus arrival at each stop call.

Legacy dotted values remain accepted. If an invalid 'method' is specified, the function defaults to '"by_trip"' and provides a warning.

Value

A data frame containing dwell times based on the specified method:

If 'method = "by_hour"'

Returns a data frame with columns: 'hour', 'trips', 'average.dwelltime', 'service_pattern', and 'pattern_frequency'.

If 'method = "by_route"'

Returns average dwell time by route, direction, and service pattern.

If 'method = "by_trip"'

Returns average dwell time by trip, retaining direction when available.

If 'method = "detailed"'

Returns a data frame with columns: 'route_id', 'trip_id', 'stop_id', 'hour', 'dwell_time', 'service_pattern', and 'pattern_frequency'.

See Also

[GTFSwizard::as_wizardgtfs()], [GTFSwizard::get_servicepattern()]

Examples

# Calculate dwell times by hour
dwelltimes_by_hour <- get_dwelltimes(gtfs = for_rail_gtfs, max_dwelltime = 120, method = "by_hour")

# Calculate dwell times by route
dwelltimes_by_route <- get_dwelltimes(gtfs = for_rail_gtfs, max_dwelltime = 90, method = "by_route")

# Calculate dwell times by trip
dwelltimes_by_trip <- get_dwelltimes(gtfs = for_rail_gtfs, max_dwelltime = 45, method = "by_trip")

# Calculate detailed dwell times between stops
detailed_dwelltimes <- get_dwelltimes(gtfs = for_rail_gtfs, max_dwelltime = 60, method = "detailed")

Description

Estimates the number of active trip instances from their first departure to final arrival. Frequency-based services are expanded from 'frequencies.txt'.

Usage

get_fleet(gtfs, method = "by_route")

Arguments

Value

A tibble containing fleet estimates by the selected grouping and service pattern. GTFS times beyond 24 hours remain in the following service day rather than being wrapped. Route outputs include 'direction_id' when available.

Examples

get_fleet(for_rail_gtfs, "by_route")
get_fleet(for_rail_gtfs, "by_hour")

Description

Counts trip departures by route, shape, stop, or hour. Trips referenced by ‘frequencies.txt' are expanded using the period’s inclusive 'start_time', exclusive 'end_time', and 'headway_secs', as required by GTFS.

Usage

get_frequency(gtfs, method = "by_trip")

Arguments

Value

A tibble containing the selected identifiers, frequency, service pattern, and number of dates represented by the pattern.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/#frequenciestxt)

See Also

[GTFSwizard::get_headways()]

Examples

get_frequency(for_rail_gtfs, "by_route")
get_frequency(for_rail_gtfs, "detailed")

Description

Calculates elapsed minutes between successive service instances. Frequency based trips are expanded according to 'frequencies.txt'.

Usage

get_headways(gtfs, method = "by_trip")

Arguments

Details

Route, hour, and trip methods compare first departures. Stop and detailed methods compare arrivals at the same stop, route, direction, and service pattern. The first service instance in each group has no headway and is omitted.

Value

A tibble. Headway values are always returned in 'headway_minutes'; 'valid_trips' is the number of intervals summarized.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/#frequenciestxt)

See Also

[GTFSwizard::get_frequency()]

Examples

get_headways(for_rail_gtfs, "by_route")
get_headways(for_rail_gtfs, "by_hour")

Description

Identify Stops Serving Multiple Routes

Usage

get_hubs(gtfs)

Arguments

Value

A WGS84 'sf' object with one row per served stop, list-columns 'trip_id' and 'route_id', counts 'n_trip' and 'n_routes', and point geometry.

See Also

[GTFSwizard::plot_hubs()], [GTFSwizard::get_stops_sf()]

Examples

get_hubs(for_rail_gtfs)

Description

Groups 'service_id' values that operate on exactly the same set of dates.

Usage

get_servicepattern(gtfs)

Arguments

Value

A tibble with one row per 'service_id', its 'service_pattern', and 'pattern_frequency', the number of active dates in that pattern. Pattern numbers are ordered from most to least frequent.

See Also

[GTFSwizard::filter_servicepattern()]

Examples

get_servicepattern(for_rail_gtfs)

Description

Builds one shape for each unique ordered stop pattern and assigns it to the corresponding trips.

Usage

get_shapes(gtfs)

Arguments

Details

Consecutive stop coordinates are connected directly. The result is useful for visualization and approximate distance analysis, but it is not a map-matched representation of the vehicle path.

Value

A 'wizardgtfs' object with a new 'shapes' table and updated 'trips$shape_id'.

See Also

[GTFSwizard::get_shapes_sf()], [GTFSwizard::get_shapes_df()]

Examples

gtfs_with_shapes <- get_shapes(for_rail_gtfs)

Description

Convert Shape Geometries to a GTFS Shapes Table

Usage

get_shapes_df(shape)

Arguments

Details

Distances are geodesic approximations between consecutive coordinates. GTFS permits any consistent distance unit; this function uses meters.

Value

A tibble containing 'shape_id', WGS84 point coordinates, 'shape_pt_sequence', and cumulative 'shape_dist_traveled' in meters.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/#shapestxt)

See Also

[GTFSwizard::get_shapes_sf()], [GTFSwizard::get_shapes()]

Examples

shapes_sf <- get_shapes_sf(for_rail_gtfs)$shapes
shapes_df <- get_shapes_df(shapes_sf)

Description

Convert GTFS Shapes to Simple Features

Usage

get_shapes_sf(gtfs)

Arguments

Value

For a data frame, one WGS84 'LINESTRING' feature per 'shape_id'. For a GTFS object, the same object with its 'shapes' table replaced by that 'sf' object. If present, 'shape_dist_traveled' is summarized as its maximum value for each shape.

See Also

[GTFSwizard::get_shapes_df()], [GTFSwizard::get_shapes()]

Examples

gtfs_sf <- get_shapes_sf(for_rail_gtfs)
shapes_sf <- get_shapes_sf(for_rail_gtfs$shapes)

Description

Combines distance in meters and duration in seconds to calculate kilometers per hour.

Usage

get_speeds(gtfs, method = "by_trip", trips = "all")

Arguments

Details

Detailed distances are straight-line geodesic distances between stops. Route and trip distances follow 'shapes.txt', or inferred straight-line shapes if the feed has none.

Value

A tibble with 'average.speed' for route and trip methods, or segment-level 'speed' for the detailed method. 'direction_id' is retained when available.

See Also

[GTFSwizard::get_distances()], [GTFSwizard::get_durations()]

Examples

get_speeds(for_rail_gtfs, "by_route")
get_speeds(for_rail_gtfs, "by_trip")

Description

Convert GTFS Stops to Simple Features

Usage

get_stops_sf(gtfs)

Arguments

Value

For a data frame, a WGS84 point 'sf' object. For a GTFS object, the same object with its 'stops' table converted to 'sf'.

Examples

gtfs_sf <- get_stops_sf(for_rail_gtfs)
stops_sf <- get_stops_sf(for_rail_gtfs$stops)

Description

Selects a UTM zone from the geographic centroid, or a polar stereographic CRS outside UTM's latitude range.

Usage

latlon2epsg(sf_obj)

Arguments

Value

The input transformed to EPSG 326xx/327xx, EPSG 3413, or EPSG 3031.

See Also

[sf::st_transform()]

Examples

shapes <- get_shapes_sf(for_rail_gtfs)$shapes
metric_shapes <- latlon2epsg(shapes)

Description

Combines two feeds table by table. By default, all identifiers and their foreign-key references receive feed-specific suffixes, preventing accidental collisions.

Usage

merge_gtfs(gtfs_x = NULL, gtfs_y = NULL, suffix = TRUE, ...)

Arguments

Details

Standard references in routes, trips, stop times, shapes, calendars, frequencies, transfers, pathways, fare tables, networks, and booking rules are updated together. Non-standard tables are row-bound without identifier rewriting.

Value

A validated 'wizardgtfs' object.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/)

Examples

merged <- merge_gtfs(for_rail_gtfs, for_rail_gtfs, suffix = TRUE)

Description

Creates a calendar heatmap of scheduled trips by service date.

Usage

plot_calendar(
  gtfs,
  ncol = 4,
  facet_by_year = FALSE,
  fill = c("trips", "service_pattern")
)

Arguments

Value

A 'ggplot' object.

See Also

[GTFSwizard::get_servicepattern()]

Examples

plot_calendar(for_rail_gtfs, ncol = 4)
plot_calendar(
  for_rail_gtfs,
  facet_by_year = TRUE,
  fill = "service_pattern"
)

Description

Plot High-Frequency Corridors

Usage

plot_corridor(gtfs, i = 0.01, min_length = 1500, ...)

Arguments

Value

A 'ggplot' map.

See Also

[GTFSwizard::get_corridor()]

Description

Shows the distribution and weighted mean of scheduled trip departures by hour. Service-pattern date counts provide the weights.

Usage

plot_frequency(gtfs)

Arguments

Value

A 'ggplot' object.

See Also

[GTFSwizard::get_frequency()]

Examples

plot_frequency(for_rail_gtfs)

Description

Plot System Headway by Hour

Usage

plot_headways(gtfs)

Arguments

Value

A 'ggplot' object with headway in minutes.

See Also

[GTFSwizard::get_headways()]

Examples

plot_headways(for_rail_gtfs)

Description

Plot Transit Hubs

Usage

plot_hubs(gtfs, i = 0.05)

Arguments

Details

To keep dense networks readable, at most 40 of the highest-ranked stops are drawn. Ranking uses distinct route count and then trip count.

Value

A 'ggplot' map.

See Also

[GTFSwizard::get_hubs()]

Description

Shows the distribution of scheduled end-to-end trip duration for the busiest routes.

Usage

plot_routeduration(gtfs, top_n = 20L)

Arguments

Value

A 'ggplot' object. Each observation is one scheduled trip; boxes summarize duration in minutes by route.

References

[FTA Evaluation Introduction](https://www.transit.dot.gov/research-innovation/evaluation-introduction)

Examples

plot_routeduration(for_rail_gtfs)

Description

Creates a heatmap of scheduled departures by route, hour, and service pattern. The tile fill is the number of scheduled trips.

Usage

plot_routefrequency(gtfs, route = NULL, top_n = 25L)

Arguments

Value

A 'ggplot' object.

See Also

[GTFSwizard::get_frequency()]

Examples

plot_routefrequency(
  for_rail_gtfs,
  route = for_rail_gtfs$routes$route_id[1:2]
)

Description

Creates a heatmap of average scheduled departures on active service dates.

Usage

plot_serviceheatmap(gtfs)

Arguments

Value

A 'ggplot' object. Each tile is a weekday-hour combination and its fill is the mean number of scheduled trip departures per active date.

References

[GTFS Schedule Reference](https://gtfs.org/documentation/schedule/reference/)

Examples

plot_serviceheatmap(for_rail_gtfs)

Description

Shows the first departure and final arrival for route and service-pattern combinations. The longest and most frequently operated route-pattern combinations are retained when the feed is large.

Usage

plot_servicespan(gtfs, top_n = 30L)

Arguments

Value

A 'ggplot' object. Each horizontal line is one route and service pattern; its endpoints are scheduled clock hours.

References

[GTFS Routes, Stops, and Trips](https://gtfs.org/documentation/schedule/examples/routes-stops-trips/)

Examples

plot_servicespan(for_rail_gtfs)

Description

Sums scheduled end-to-end trip durations for each route and service pattern.

Usage

plot_servicesupply(gtfs, top_n = 20L)

Arguments

Value

A 'ggplot' object. Each bar is scheduled vehicle-hours for one route on one representative service-pattern day.

References

[FTA National Transit Database](https://www.transit.dot.gov/ntd)

Examples

plot_servicesupply(for_rail_gtfs)

Description

Imports a GTFS zip archive and converts it to 'wizardgtfs'.

Usage

read_gtfs(file_path = NULL, files = NULL, quiet = TRUE, ...)

Arguments

Value

A validated 'wizardgtfs' object.

See Also

[GTFSwizard::write_gtfs()], [GTFSwizard::as_wizardgtfs()]

Examples

path <- tempfile(fileext = ".zip")
write_gtfs(for_rail_gtfs, path)
gtfs <- read_gtfs(path)

Description

Creates persistent selection metadata while leaving every GTFS table unchanged. Bare columns and computed values define groups, similarly to [dplyr::group_by()]. Logical expressions restrict the records represented by those groups.

Usage

selection(gtfs, ..., add = FALSE)

unselection(gtfs)

Arguments

Details

A bare expression such as 'route_id' creates one group per route. Multiple grouping expressions create combinations, for example 'selection(gtfs, route_id, direction_id)'. Logical expressions such as 'route_id selection but do not remove rows from the GTFS feed.

Spatial expressions may use 'geometry' with ' '

Value

The unchanged feed with class 'wizardgtfs_selected' and a 'selection' attribute. The attribute contains 'groups', 'group_vars', selected route, trip, and stop IDs, and the original expressions.

See Also

[GTFSwizard::unselection()], [dplyr::group_by()]

Examples

grouped <- selection(for_rail_gtfs, route_id, direction_id)
attr(grouped, "selection")$groups

selected <- selection(
  for_rail_gtfs,
  route_id,
  stop_id %in% for_rail_gtfs$stops$stop_id[1:3]
)

bbox <- sf::st_bbox(
  c(xmin = -38.58, ymin = -3.81, xmax = -38.50, ymax = -3.75),
  crs = sf::st_crs(4326)
)
spatial <- selection(
  for_rail_gtfs,
  geometry %intersects% sf::st_as_sfc(bbox)
)

Description

Sets dwell time at selected trip-stop calls and propagates each change to all later times in the same trip. Arrival at the edited stop is retained.

Usage

set_dwelltime(gtfs, duration = 30, trips = "all", stops = "all")

Arguments

Value

A modified 'wizardgtfs' object.

See Also

[GTFSwizard::edit_dwelltime()], [GTFSwizard::get_dwelltimes()]

Examples

edited <- set_dwelltime(
  for_rail_gtfs,
  duration = 30,
  trips = for_rail_gtfs$trips$trip_id[1:2],
  stops = for_rail_gtfs$stops$stop_id[1:2]
)

Description

Splits each selected trip into approximately equal consecutive parts. The boundary stop is included at the end of one part and the start of the next, producing valid complete stop sequences.

Usage

split_trip(gtfs, trip, split = 1L)

Arguments

Details

New IDs use '.part1', '.part2', and so on. New straight-line shapes are inferred from stop coordinates for the split parts. Frequency periods are shifted by each part's offset from the original first departure. Trip-level transfers are reassigned to the part containing their transfer stop. Trips with fewer than three retained stop-time records cannot be split.

Value

A modified 'wizardgtfs' object.

See Also

[GTFSwizard::get_shapes()], [GTFSwizard::merge_gtfs()]

Examples

gtfs_split <- split_trip(
  for_rail_gtfs,
  trip = for_rail_gtfs$trips$trip_id[1],
  split = 2
)

Description

The 'tidy_raptor' function calculates travel times from a set of origin stops to all reachable stops within a GTFS dataset. It uses the RAPTOR (Round-Based Public Transit Routing) algorithm from the 'tidytransit' package and integrates it with the GTFSwizard framework.

Usage

tidy_raptor(
  gtfs,
  min_departure = "0:0:0",
  max_arrival = "23:59:59",
  dates = NULL,
  stop_ids,
  arrival = FALSE,
  time_range = 3600,
  max_transfers = NULL,
  keep = "all",
  filter = TRUE,
  separate_starts = FALSE
)

Arguments

Value

A tibble containing the RAPTOR algorithm results, including:

from_stop_id

The ID of the stop where the journey starts.

to_stop_id

The ID of the stop where the journey ends.

departure_time

Departure time from the origin stop.

arrival_time

Arrival time at the destination stop.

travel_time

Total travel time in seconds.

transfers

Number of transfers in the journey.

Note

Ensure that the 'stop_times' is present and correctly structured in the GTFS dataset. Time values in 'min_departure', 'max_arrival', and 'time_range' should be correctly formatted to avoid errors. GTFS times beyond 24:00:00 are supported.

See Also

[tidytransit::raptor()], [GTFSwizard::as_wizardgtfs()], [GTFSwizard::filter_time()]

Examples

tidy_raptor(for_rail_gtfs,
   min_departure = '06:20:00',
   max_arrival = '09:40:00',
   dates = "2021-12-13",
   max_transfers = 2,
   keep = "all",
   stop_ids = '66')

Description

Print, Summarize, and Plot 'wizardgtfs' Objects

Usage

## S3 method for class 'wizardgtfs'
print(x, ..., n = 5L)

## S3 method for class 'wizardgtfs'
summary(object, ...)

## S3 method for class 'summary.wizardgtfs'
print(x, ...)

## S3 method for class 'wizardgtfs'
plot(x, ...)

Arguments

Value

'print()' returns 'x' invisibly; 'summary()' returns a 'summary.wizardgtfs' object; 'plot()' returns a 'ggplot' object.

Description

Exports a GTFS object to a zip archive. Internal 'dates_services' data are omitted, GTFS dates use 'YYYYMMDD', and spatial stops/shapes are converted back to standard text-table columns.

Usage

write_gtfs(gtfs, zipfile, ...)

Arguments

Value

The normalized output path, invisibly.

See Also

[GTFSwizard::read_gtfs()]

Examples

path <- tempfile(fileext = ".zip")
write_gtfs(for_rail_gtfs, path)