#r5rgui has been on CRAN for a few days now! Your handy helper to quickly visually explore routes built by #rstats #r5r ( @UrbanDemog ), powered by #mapgl (https://walker-data.com/mapgl/). Learn more at https://www.ekotov.pro/r5rgui/

Pythonで爆速ルート検索！R5pyの構築とR5Rとの違いを紹介！
https://qiita.com/ko_wa/items/48bfb58db9e52d72ee93?utm_campaign=popular_items&utm_medium=feed&utm_source=popular_items

#qiita #Python #経路検索 #公共交通 #R5py #R5R

#Accessibility modelers using #r5r #rstats, check this GUI for playing around with R5 network. If many people find it useful, I would get signal if I should invest any more free time into it. https://github.com/e-kotov/r5rgui (uses #mapgl by Kyle Walker (https://walker-data.com/) and #r5r by @UrbanDemog et al)

Are you in Toronto and interested in transportation? I'll be teaching transportation modeling to calculate travel times and accessibility to destinations in #rstats using #r5r ! Free workshop April 8 @ UofT https://www.eventbrite.ca/e/bousfield-urban-accessibility-r-crash-course-tickets-1284533186339?aff=oddtdtcreator

Some days are just better.

It is rewarding to see an analysis go brrrrrrrr after spending a lot of time trying to solve some problems in my pipeline, automating many steps, figuring out how #r5r and #r5py work, and circumventing some hard-coded problems of R5.

I am wondering if the generation of an #isochrone is slower or faster compared to generating a grid-based travel-time matrix with #R5R or #R5py.

Both would get me the result I want in slightly different ways. I need to calculate the travel times to all somewhat major border crossing points in Europe. Calculating 30, 60 and 90 minute isochrones (private car) for Finland's 12 over-land points is taking over an hour in R5R, which is not optimal given that there are 1800+ points across Europe.

Apparently, the easiest way to calculate an #isochrone for travel times is to use #R5r in #Rstats. Trouble is, I've only had one beginner course of R, so I am a bit scared of my ability to troubleshoot anything.

Apparently there is nothing similarly fast in #Python to generate hundreds of isochrones across Europe.

#rJavaEnv and #r5r #rstats downloads periodically see bumps in daily downloads. Someone somewhere is conducting a workshop on #accessibility...?

#r5r: https://ipeagit.github.io/r5r/

#rJavaEnv: https://www.ekotov.pro/rJavaEnv/

our map of proximity to outdoor skating rinks in Toronto from about a year ago

(thinking about this again since I'm on my way to a rink soon :)

more about this map: https://schoolofcities.github.io/access-to-outdoor-rinks-toronto

#toronto #maps #r5r #openstreetmap #qgis #inkscape #gimp

#rstats since it's release is early-mid September 2024 #rJavaEnv (ekotov.pro/rJavaEnv/) is averaging 500+ downloads per month. It's your trusty companion for #r5r, #RSelenium, #openNLP and 100+ other #Java dependent packages. Install Java in one line of code + use with #targets #ReproducibleResearch

#urbantransitions2024 8.30am, people setting up posters. I think mine is in the best spot. A snapshot with my workflow using #rstats #r5r, #targets, my own #rJavaEnv https://www.ekotov.pro/rJavaEnv/ , and #mlr3 is all I can share right now online, for details you have to be here in person)

today's quick map ......

transit isochrones from downtown eau claire

using #qgis #openstreetmap #gtfs #r5r

5/ 🔍 Once installed, rJavaEnv::java_check_version_rjava() Checks the installed Java version using rJava::.init() in a separate R session. For rJava-dependent packages such as #r5r

🚀 Introducing rJavaEnv: A new R package to manage multiple Java JDKs for your R projects! 🎉
https://github.com/e-kotov/rJavaEnv

#rstats #gischat #rspatial #rJava

Using #r5r and #OpenTripPlanner, or another rJava/Java dependent package, this tool for you!

Thread 🧵👇

Having this basic understanding of how both geographical systems can be connected, we can improve spatial analyses that revolve around proximity and accessibility, e.g. using the #r5r package @UrbanDemog

Work in progress.

#OpenScience research project that investigates the #walking sheds at the core of the 15-minute neighborhood, and their associated network attributes. Powered by #openstreetmap, #OpenData, and #rstats

@Belenmr @robinlovelace
@UrbanDemog

https://github.com/paezha/15-minute-neighborhood

#ReproducibleResearch #transportation #ActiveTravel #Cities #Urbanism #Rstats #15MinCity #r5r #SimpleFeatures #igraph

Last week @tenkahen and @dhersz delivered at @CASAUCL a bilingual workshop on accessibility modelling using both #r5py (#Python) & #r5r (#rstats)

r5r: https://ipeagit.github.io/r5r/
r5py: https://r5py.readthedocs.io/

Doing transport accessibility analysis has never been so easy :)
---
RT @tenkahen
Thanks for the brilliant @CASAUCL students who were eager to learn accessibility modelling with #r5py & #r5r. My first workshop combining #Py…
https://twitter.com/tenkahen/status/1599689869130813440