This article used an open-source python repository for its analysis. It is well-suited for reproduction as more literature evolves on the intersection of urban planning and climate change. The adapted code is published alongside the article.
This article was meant to be entirely reproducible, with the data and code published alongside the article. It is however not embedded within a container (e.g. Docker). Will it past the reproducibility test tomorrow? next year? I'm curious.
The method is trained on the data that were available, but it is meant to be re-trainable as soon as new data are published. It would be great to be really sure that even someone else will be able to do it. In case we receive any feedback, we would be really happy to improve our Github repository so as to make the reproduction easier!
I tried hard to make this paper as reproducible as possible, but as techniques and dependencies become more complex, it is hard to make it 100% clear. Any form of feedback is more than welcome.
It uses the drake R package that should make reproducibility of R projects much easier (just run make.R and you're done). However, it does depend on very specific package versions, which are provided by the accompanying docker image.