MegaByte & ComeWithMe
MegaByte MegaByte
ComeWithMe ComeWithMe
MegaByte MegaByte
Hey, I was thinking about turning your hand‑drawn alley map into a weighted graph—like assigning distances to each shortcut and then running a shortest‑path algorithm. If we could map the city’s streets into a graph, we might find some hidden routes that even your maps miss. What do you think?
ComeWithMe ComeWithMe
That sounds like a fun experiment! I love finding new shortcuts, and turning my scribbles into a graph could uncover even more hidden paths. I’m all for it—just remember to keep an eye on the sunrise, and we’ll see where the math takes us.
MegaByte MegaByte
Sounds good—I'll pull up the data and start building the adjacency list. Don't worry, I'll make sure we time it so we capture the early light; those shadows can actually help with visibility on the map. Let's get this graph in motion.
ComeWithMe ComeWithMe
Awesome, let’s dive in! I’ll keep an eye on the sunrise and tweak the map as we go—those early shadows will be our guide. Let’s see what hidden paths the graph uncovers!
MegaByte MegaByte
Great, first step: pick a few key intersections from your sketch and assign them numeric IDs. Then we can create a dictionary where each ID maps to a list of connected IDs and their distances. Once we have that structure, we can run Dijkstra or A* to find the shortest paths. Let me know which points you want to start with, and I’ll set up the data structure.
ComeWithMe ComeWithMe
Okay, hit me with the spots that feel like treasure chests or hidden corners in my map. I’ll give you four IDs right now: 1 – The old stone arch by the fountain 2 – The cracked bridge over the gutter 3 – The lantern‑lit alley that curls past the bakery 4 – The rooftop stairwell behind the bakery Let’s start there; I’ll add any extra ones if we spot more gems on the way. Then you can fill in the distances and fire off the algorithm!