Comments (3)
Hi @mortewle. Thanks for trying our package.
If you are using our sample data, please have in mind that the GTFS provided contains just a few routes. Hence, when calculating a travel time matrix, many travel times will come from walking trips, which should not be affected by the departure time.
I did a small test and, if you look closely, you can see that many travel times are different. Can you try the code below and report the results back, please?
options(java.parameters = "-Xmx4G")
library("r5r")
library("dplyr")
# Start R5R core
r5r_core <- setup_r5(system.file("extdata", package = "r5r"), verbose = FALSE)
# Load points
points_hex <- read.csv(system.file("extdata/poa_hexgrid.csv", package = "r5r"))
# Testing trip date and time
max_walk_distance = 800L
max_trip_duration = 120L
# 8 am
trip_date_time <- lubridate::as_datetime("2019-03-22 08:27:00")
ttm_8am <- travel_time_matrix(r5r_core, points_hex, points_hex,
mode = c("WALK", "BUS"),
departure_datetime = trip_date_time, max_walk_dist = max_walk_distance,
max_trip_duration = max_trip_duration, verbose = FALSE)
# 11 am
trip_date_time <- lubridate::as_datetime("2019-03-22 11:13:00")
ttm_11am <- travel_time_matrix(r5r_core, points_hex, points_hex,
mode = c("WALK", "BUS"),
departure_datetime = trip_date_time, max_walk_dist = max_walk_distance,
max_trip_duration = max_trip_duration, verbose = FALSE)
# Checking results
full_join(ttm_8am, ttm_11am, by=c("fromId", "toId")) %>%
filter(travel_time.x != travel_time.y) %>%
View()
full_join(ttm_8am, ttm_11am, by=c("fromId", "toId")) %>%
filter(travel_time.x == travel_time.y) %>%
View()
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Hi. Looking closer at my results, it seems like all the trips I checked earlier were walking only or had the exact same waiting time for the times I chose, because now I see some divergence. It works with the code you provided as well. Thank you!
Great package by the way!
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Thanks @mortewle!
All feedback is appreciated.
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