CaptainLuma
commented
4 days ago Hi Roman, thank you so much for taking interest in Origin Shift. The Labyrinthian library is really great! I love the idea of a site which catalogs all maze generating techniques and shows visual demo's for each, and I think the Labyrinthian is a wonderful execution of that idea. It is so cool to have my algorithm featured on there.
The problem of the algorithm not always traversing the whole grid is a problem that a few people have pointed out. I believe it has to do with my suggested iteration equation of "i = 10a" being inaccurate. I basically eyeballed the equation and only tested it out with smaller mazes. A more accurate equation could be found mathematically, though I am not really skilled enough in math to do this. But if I do discover a more accurate equation, then I will let you know.
Thank you again for adding Origin Shift to your site. It is an honor!
- Luma
On Tue, 2 Jul 2024 at 16:35, Roman Dykyi @.***> wrote:
Hi, I'm the author of the Labyrinthian https://github.com/romandykyi/Labyrinthian library, which specializes in step-by-step generation of various graph-based maze types (e.g., delta, theta, upsilon) using different algorithms. Recently, I integrated your Origin Shift algorithm into my library, and users can now visualize the generation process in this online demo https://romandykyi.github.io/LabyrinthianDemo/.
In my implementation, I start by selecting a cell (random by default) and perform a BFS from it to create the initial spanning tree (perfect maze). Then, I apply n iterations (n = 10 * mazeCellsCount by default, as per your suggestion in your video).
Your algorithm has truly impressed me. Unlike other graph-based algorithms like Kruskal or Wilson that generate a random spanning tree from scratch, Origin Shift operates on an existing spanning tree and dynamically modifies it. I also find it particularly innovative that directed graphs can be utilized effectively for maze generation, I haven't encountered a similar approach before.
However, Origin Shift does have its limitations. Occasionally, it fails to fully traverse the graph, especially with Delta mazes, even with 10 * mazeCellsCount iterations: Triangular.maze.size.50.png (view on web) https://github.com/CaptainLuma/New-Maze-Generating-Algorithm/assets/94003504/01f862e3-866a-4b4f-8d48-5ee9455d3c95
Despite this, I believe your algorithm has significant potential for enhancement or as a valuable secondary post-processing tool.
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Hi, I'm the author of the Labyrinthian library, which specializes in step-by-step generation of various graph-based maze types (e.g., delta, theta, upsilon) using different algorithms. Recently, I integrated your Origin Shift algorithm into my library, and users can now visualize the generation process in this online demo.
In my implementation, I start by selecting a cell (random by default) and perform a BFS from it to create the initial spanning tree (perfect maze). Then, I apply
niterations (n = 10 * mazeCellsCountby default, as per your suggestion in your video).Your algorithm has truly impressed me. Unlike other graph-based algorithms like Kruskal or Wilson that generate a random spanning tree from scratch, Origin Shift operates on an existing spanning tree and dynamically modifies it. I also find it particularly innovative that directed graphs can be utilized effectively for maze generation, I haven't encountered a similar approach before.
However, Origin Shift does have its limitations. Occasionally, it fails to fully traverse the graph, especially with Delta mazes, even with
10 * mazeCellsCountiterations:Despite this, I believe your algorithm has significant potential for enhancement or as a valuable secondary post-processing tool.