In ITSLeeds/pct: Propensity to Cycle Tool

# knitr::opts_chunk$set(echo = FALSE)
# test you can install packages
# install.packages("remotes", quiet = TRUE)

# test you have the right packages installed
pkgs = c("sf", "stplanr", "pct", "tmap", "dplyr")
remotes::install_cran(pkgs, quiet = TRUE)

# test you can read-in csv files:
od_data = read.csv("https://github.com/npct/pct-outputs-regional-notR/raw/master/commute/msoa/avon/od_attributes.csv")
head(od_data)
od_data$pcycle = od_data$bicycle / od_data$all

Dear Propensity to Cycle Tool Advanced Workshop Participant,

I am looking forward to the event this Thursday and wanted to share with you a few links and reminders beforehand.

The first thing to say is that this is an Advanced Workshop based on the statistical programming language R so you will be expected to run code in R/RStudio. You will be expected to 'get you hands dirty' and write some code so it's important that you have your computer set-up and ready to before the course starts. To check that R is working on your computer, please ensure that you can run the entirety of this script in RStudio: https://github.com/ITSLeeds/pct/blob/master/inst/test-setup.R

If you see this plot appear after running line 14 (shown below - see this in context in the link above), congratulations on getting a basic R set-up working.

plot(od_data$rf_dist_km, od_data$pcycle, cex = od_data$all / mean(od_data$all))

# test the sf package: read-in and download zones and centroids
library(sf)
u1 = "https://github.com/npct/pct-outputs-regional-notR/raw/master/commute/msoa/avon/c.geojson"
u1b = "https://github.com/npct/pct-outputs-regional-notR/raw/master/commute/msoa/avon/z.geojson"
centroids = read_sf(u1)
districts = read_sf(u1b)
plot(districts$geometry)
centroids_geo = st_centroid(districts)
plot(centroids$geometry, add = TRUE)
plot(centroids_geo$geometry, add = TRUE, col = "red")

# check interactive mapping with tmap
library(tmap)
tmap_mode("view")
u2 = "https://github.com/npct/pct-outputs-regional-notR/raw/master/commute/msoa/avon/l.geojson"
desire_lines = sf::read_sf(u2)
desire_lines_subset = desire_lines[desire_lines$all > 100, ]
tm_shape(desire_lines_subset) +
  tm_lines(col = "bicycle", palette = "viridis", lwd = "all", scale = 9)

# check route network generation with stplanr
library(stplanr)
u3 = "https://github.com/npct/pct-outputs-regional-notR/raw/master/commute/msoa/avon/rf.geojson"
routes = sf::read_sf(u3)
library(dplyr)
routes_1 = routes %>%
  slice(which.max(bicycle))
tm_shape(routes_1) +
  tm_lines()
rnet = overline(routes, "bicycle")
b = c(0, 0.5, 1, 2, 3, 8) * 1e3
tm_shape(rnet) +
  tm_lines(scale = 2, col = "bicycle", palette = "viridis", breaks = b)

# check analysis with dplyr and estimation of cycling uptake with pct function
library(pct)

routes$Potential = pct::uptake_pct_godutch(
  distance = routes$rf_dist_km,
  gradient = routes$rf_avslope_perc
) *
  routes$all
rnet_potential = overline(routes, "Potential")

After running the lines from 15 onwards you should see a number of plots and other outputs. The following line of code should, after running all the code in the link above, tell you the average number of cyclists on route network segments in Avon under the PCT's Go Dutch scenario:

round(mean(rnet_potential$Potential))

What number did you get? We will test you during the course so make sure you try to reproduce the result. A more visual check that your computer is set-up to do transport data science with R for modelling cycling uptake is plotting the result. If you got the plot shown below after running the following code (you will need to have run all previous lines), congratulations, you're ready to go!

tm_shape(rnet_potential) +
  tm_lines(lwd = "Potential", scale = 9, col = "Potential", palette = "viridis", breaks = b)

If you have any issues reproducing the code, please double check your R install and make sure you have installed the necessary.

You will need to have a recent version of R and RStudio installed. Double check you have at least R 4.0.0 and RStudio 1.2 installed. If not, ensure that you have the latest versions installed.

If you have any issues, please open an issue here: https://github.com/ITSLeeds/pct/issues (As a last resort you can email at [e-mail] although I may not be able to respond before the event).

The second thing to say is that having a GitHub account will help you ask questions and share reproducible examples, so please sign-up if you have not yet registered: https://github.com

After you have signed-up, please check it works by saying hi on this issue (we will also use this link to answer code related questions during the course): https://github.com/ITSLeeds/pct/issues/74

The third thing is about routing. If you want to do routing on the network, please sign-up at https://www.cyclestreets.net/api/apply/. You should save the resulting key on your system by running the following commands:

# uncomment these lines to install cyclestreets
# install.packages("usethis")
# install.packages("cyclestreets")
usethis::edit_r_environ()

Then add the following line to the file that pops up:

CYCLESTREETS=ca43ed677e5e6fe1

For more info on testing if this worked, see:

The fourth and final thing to say: please ensure that you have at least taken a read of (and ideally have reproduced some of the code examples in) these links:

• The original paper on the Propensity to Cycle Tool: https://www.jtlu.org/index.php/jtlu/article/view/862
• The transport chapter (12) in the open source book Geocomputation with R
• The vignette that describes the pct R package, which can be found here: https://itsleeds.github.io/pct/articles/pct.html
• Information on how to create reproducible examples (this will be useful when asking for help during the workshop): https://reprex.tidyverse.org/

Hope this is useful, please prioritise getting R up-and-running and let us know if you have any issues.

All the best,

Robin

P.s. there is one more thing to say: we plan a virtual 'to the pub' session after the event from 5pm to 6pm so make sure you have beer (or whatever refreshment takes your fancy) in stock if you want to join for a post workshop social.

ITSLeeds/pct documentation built on April 13, 2025, 5:49 p.m.