So, I wanted to mess around with creating logos using depth-first search (DFS). It sounded cool, and I was curious to see what I could come up with.
First, I needed to figure out what the heck a logo even meant in this context. I decided to represent the logo as a grid, like a little pixel art canvas. Each cell in the grid could either be filled or empty. My goal was to use DFS to explore all the connected filled cells, essentially tracing the outline or the shape of the logo.
I started by creating a simple grid class. This was just a basic 2D array to hold my logo data. I used zeros for empty cells and ones for filled cells. It was super basic, nothing fancy, just a bunch of zeros and ones in rows and columns.
Next, I coded the DFS algorithm. This was the heart of the whole thing. The idea was pretty straightforward: start at a filled cell, mark it as visited, and then recursively check all its neighbors. If a neighbor was also a filled cell and not already visited, I would continue the search from there. It’s like following a path until you hit a dead end, then backtracking and trying another path. I used a simple boolean array to keep track of visited cells, so I didn’t end up in endless loops.
I wrote a function to initiate the DFS from a given starting point. I figured I needed a way to kick off the search from any filled cell in the grid. This function would just set up the visited array and call the recursive DFS function.
To test it out, I created a few sample logos. I just manually filled in some cells in the grid to make some basic shapes. Nothing too complex, just some squares and blobs to see if my code was working as expected.
Then came the moment of truth. I ran my code on the sample logos, starting the DFS from different filled cells. I watched as the algorithm explored the grid, marking the visited cells. It was pretty satisfying to see it work! I visualized the process by printing the grid after each step, showing which cells had been visited.
I played around with different starting points and grid sizes. It was interesting to see how the DFS traversal changed depending on where I started the search. Sometimes it would trace the entire shape, and other times it would only explore a portion of it, depending on the connectivity of the filled cells.
Results
After a bunch of trial and error, I had a decent little program that could create logos using DFS. It wasn’t perfect, but it was a fun experiment. I learned a lot about how DFS works in practice and how it can be used to explore connected components in a grid. It felt like a solid first step, you know? I started seeing how I could build on this to make something more complex and interesting.
- Experiment 1: Tried a 5×5 grid with a simple square shape. The DFS traced the entire square perfectly.
- Experiment 2: Used a 10×10 grid with a more complex blob shape. The DFS explored the entire blob, no matter where I started the search.
- Experiment 3: Tested with an irregular shape that had some isolated filled cells. The DFS only explored the connected component that the starting cell was part of, which was exactly what I expected.
Overall, it was a pretty cool learning experience. I got to see DFS in action and play around with a fun little project. It wasn’t a masterpiece, but it got me thinking about other ways I could use DFS and how I could refine this idea further.