The tube map is an excellent way of explaining pathfinding algorithms. In fact, it is often used in company interviews as a way of testing the candidate's knowledge of graph data structures and shortest path algorithms.
This project aims to visualise algorithms such as BFS, DFS, Dijkstra and A* using the tube map.
Press the thumbnail above to view the final video on YouTube, or click here.
For a detailed explanation of what this project was all about and how I did it, please see my blog post.
I converted the official tube map provided by TfL into an SVG file and removed clutter such as DLR, Trams and Thameslink that do not belong on a map of the London Underground. Next, I individually selected each station in the SVG in Inkscape and gave it a unique ID. In this case, I based the ID off the three-letter station codes that TfL uses.
In addition, I downloaded the average inter-station travel times from a TfL FOI request provided in XLSX format. This was converted into a CSV for simpler parsing.
tube.py is a wrapper for importing the aforementioned SVG and inter-station travel times and provides methods for individually showing / hiding stations on the map as well as changing their opacity.
In main.py are the actual pathfinding algorithms. During their execution, they show/hide visited stations and write to an SVG file for every frame.
The SVG files can then be rasterised and formed into an MP4 using ffmpeg to create a visualisation of the pathfinding algorithms at work.