Filters a GTFS object by time of day, keeping (or dropping) the relevant
entries in each file. Please see the details section for more information on
how this function filters the frequencies and stop_times tables, as well
as how it handles stop_times tables that contain trips with some empty
departure and arrival times.
filter_by_time_of_day(
gtfs,
from,
to,
keep = TRUE,
full_trips = FALSE,
update_frequencies = TRUE
)A GTFS object, as created by read_gtfs().
A string. The starting point of the time of day, in the "HH:MM:SS" format.
A string. The ending point of the time of day, in the "HH:MM:SS" format.
A logical. Whether the entries related to the specified time of
day should be kept or dropped (defaults to TRUE, which keeps the entries).
A logical. Whether trips should be treated as immutable
blocks or each of its stops should be considered separately when filtering
the stop_times table (defaults to FALSE, which considers each stop
individually). Please check the details section for more information on how
this parameter changes the function behaviour.
A logical. Whether the frequencies table should
have its start_time and end_time fields updated to fit inside/outside the
specified time of day (defaults to FALSE, which doesn't update the fields).
The GTFS object passed to the gtfs parameter, after the filtering
process.
When filtering the frequencies table, filter_by_time_of_day() respects
the exact_times field. This field indicates whether the service follows a
fixed schedule throughout the day or not. If it's 0 (or if it's not
present), the service does not follow a fixed schedule. Instead, the
operators try to maintain the listed headways. In such cases, if
update_frequencies is TRUE we just update start_time and end_time to
the appropriate value of from or to (which of this value is used depends
on keep).
If exact_times is 1, however, operators try to strictly adhere to the start
times and headway. As a result, when updating the start_time field we need
to follow the listed headway. For example, take a trip that has its start
time listed as 06:00:00, its end time listed as 08:00:00 and its headway
listed as 300 secs (5 minutes). If you decide to filter the feed to keep the
time of day between 06:32:00 and 08:00:00 while updating frequencies, the
start_time field must be updated to 06:35:00 in order to preserve the
correct departure times of this trips, instead of simply updating it to
06:32:00.
Another things to keep an eye on when filtering the frequencies table is
that the corresponding stop_times entries of trips listed in the
frequencies table should not be filtered, even if their departure and
arrival times fall outside the specified time of day. This is because the
stop_times entries of frequencies' trips are just templates that describe
how long a segment between two stops takes, so the departure and arrival
times listed there do not actually represent the actual departure and
arrival times seen in practice. Taking the same example listed above, the
corresponding stop_times entries of that trip could describe a departure
from the first stop at 12:00:00 and an arrival at the second stop at
12:03:00. That doesn't mean the trip will actually leave and arrive at the
stops at these times, but rather that it takes 3 minutes to get from the
first to the second stop. So when the trip departs from the first stop at
06:35:00, it will get to the second at 06:38:00.
When filtering the stop_times table, a few other details should be
observed. First, one could wish to filter a GTFS object in order to keep all
trips that cross a given time of day, whereas others may want to keep only
the specific entries that fall inside the specified time of day. For
example, take a trip that leaves the first stop at 06:30:00, gets to the
second at 06:35:00 and then gets to the third at 06:45:00. When filtering to
keep entire trips that cross the time of day between 06:30:00 and 06:40:00,
all three stops will have to be kept. If, however, you want to keep only the
entries that fall within the specified time of day, only the first two
should be kept. To control such behaviour you need to set the full_trips
parameter. When it's TRUE, the function behaves like the first case, and
when it's FALSE, like the second.
When using full_trips in conjunction with keep, please note how their
behaviour stack. When both are TRUE, trips are always fully kept. When
keep is FALSE, however, trips are fully dropped, even if some of their
stops are visited outside the specified time of day.
Finally, please note that many GTFS feeds may contain stop_times entries
with empty departure and arrival times. In such cases, filtering by time of
day with full_trips as FALSE will drop the entries with empty times.
Please set full_trips to TRUE to preserve these entries.
Other filtering functions:
filter_by_agency_id(),
filter_by_route_id(),
filter_by_route_type(),
filter_by_service_id(),
filter_by_sf(),
filter_by_shape_id(),
filter_by_spatial_extent(),
filter_by_stop_id(),
filter_by_trip_id(),
filter_by_weekday()
data_path <- system.file("extdata/spo_gtfs.zip", package = "gtfstools")
gtfs <- read_gtfs(data_path)
# taking a look at the original frequencies and stop_times
head(gtfs$frequencies)
#> trip_id start_time end_time headway_secs
#> <char> <char> <char> <int>
#> 1: CPTM L07-0 04:00:00 04:59:00 720
#> 2: CPTM L07-0 05:00:00 05:59:00 360
#> 3: CPTM L07-0 06:00:00 06:59:00 360
#> 4: CPTM L07-0 07:00:00 07:59:00 360
#> 5: CPTM L07-0 08:00:00 08:59:00 360
#> 6: CPTM L07-0 09:00:00 09:59:00 480
head(gtfs$stop_times)
#> trip_id arrival_time departure_time stop_id stop_sequence
#> <char> <char> <char> <char> <int>
#> 1: CPTM L07-0 04:00:00 04:00:00 18940 1
#> 2: CPTM L07-0 04:08:00 04:08:00 18920 2
#> 3: CPTM L07-0 04:16:00 04:16:00 18919 3
#> 4: CPTM L07-0 04:24:00 04:24:00 18917 4
#> 5: CPTM L07-0 04:32:00 04:32:00 18916 5
#> 6: CPTM L07-0 04:40:00 04:40:00 18965 6
smaller_gtfs <- filter_by_time_of_day(gtfs, "05:00:00", "06:00:00")
# filter_by_time_of_day filters the frequencies table but doesn't filter the
# stop_times table because they're just templates
head(smaller_gtfs$frequencies)
#> trip_id start_time end_time headway_secs
#> <char> <char> <char> <int>
#> 1: CPTM L07-0 05:00:00 05:59:00 360
#> 2: CPTM L07-1 05:00:00 05:59:00 360
#> 3: CPTM L08-0 05:00:00 05:59:00 480
#> 4: CPTM L08-1 05:00:00 05:59:00 480
#> 5: CPTM L09-0 05:00:00 05:59:00 480
#> 6: CPTM L09-1 05:00:00 05:59:00 480
head(smaller_gtfs$stop_times)
#> trip_id arrival_time departure_time stop_id stop_sequence
#> <char> <char> <char> <char> <int>
#> 1: CPTM L07-0 04:00:00 04:00:00 18940 1
#> 2: CPTM L07-0 04:08:00 04:08:00 18920 2
#> 3: CPTM L07-0 04:16:00 04:16:00 18919 3
#> 4: CPTM L07-0 04:24:00 04:24:00 18917 4
#> 5: CPTM L07-0 04:32:00 04:32:00 18916 5
#> 6: CPTM L07-0 04:40:00 04:40:00 18965 6
# frequencies entries can be adjusted using update_frequencies = TRUE
smaller_gtfs <- filter_by_time_of_day(
gtfs,
"05:30:00",
"06:00:00",
update_frequencies = TRUE
)
head(smaller_gtfs$frequencies)
#> trip_id start_time end_time headway_secs
#> <char> <char> <char> <int>
#> 1: CPTM L07-0 05:30:00 05:59:00 360
#> 2: CPTM L07-1 05:30:00 05:59:00 360
#> 3: CPTM L08-0 05:30:00 05:59:00 480
#> 4: CPTM L08-1 05:30:00 05:59:00 480
#> 5: CPTM L09-0 05:30:00 05:59:00 480
#> 6: CPTM L09-1 05:30:00 05:59:00 480
# when keep = FALSE, the behaviour of the function in general, and of
# update_frequencies in particular, is a bit different
smaller_gtfs <- filter_by_time_of_day(
gtfs,
"05:30:00",
"06:00:00",
keep = FALSE,
update_frequencies = TRUE
)
head(smaller_gtfs$frequencies)
#> trip_id start_time end_time headway_secs
#> <char> <char> <char> <int>
#> 1: CPTM L07-0 04:00:00 04:59:00 720
#> 2: CPTM L07-0 05:00:00 05:30:00 360
#> 3: CPTM L07-0 06:00:00 06:59:00 360
#> 4: CPTM L07-0 07:00:00 07:59:00 360
#> 5: CPTM L07-0 08:00:00 08:59:00 360
#> 6: CPTM L07-0 09:00:00 09:59:00 480
# let's remove the frequencies table to check the behaviour of full_trips
gtfs$frequencies <- NULL
smaller_gtfs <- filter_by_time_of_day(
gtfs,
"05:30:00",
"06:00:00"
)
head(smaller_gtfs$stop_times)
#> trip_id arrival_time departure_time stop_id stop_sequence
#> <char> <char> <char> <char> <int>
#> 1: CPTM L07-0 05:36:00 05:36:00 18926 13
#> 2: CPTM L07-0 05:44:00 05:44:00 18971 14
#> 3: CPTM L07-0 05:52:00 05:52:00 18972 15
#> 4: CPTM L07-0 06:00:00 06:00:00 18973 16
#> 5: CPTM L07-1 05:36:00 05:36:00 18965 13
#> 6: CPTM L07-1 05:44:00 05:44:00 18916 14
smaller_gtfs <- filter_by_time_of_day(
gtfs,
"05:30:00",
"06:00:00",
full_trips = TRUE
)
head(smaller_gtfs$stop_times)
#> trip_id arrival_time departure_time stop_id stop_sequence
#> <char> <char> <char> <char> <int>
#> 1: CPTM L07-0 04:00:00 04:00:00 18940 1
#> 2: CPTM L07-0 04:08:00 04:08:00 18920 2
#> 3: CPTM L07-0 04:16:00 04:16:00 18919 3
#> 4: CPTM L07-0 04:24:00 04:24:00 18917 4
#> 5: CPTM L07-0 04:32:00 04:32:00 18916 5
#> 6: CPTM L07-0 04:40:00 04:40:00 18965 6