This project (along with other projects, but this one especially) brings good memories.
When I first began developing NoiseGenerator, I was diving into the realm of
procedural generation,
specifically, procedural map generation. Popular games like Minecraft use it,
so I, in pursuit of experience in Game-Development, thought of implementing a procedural-generation algorithm.
Algorithms like such utilize "noise", Perlin Noise,
most recognizably, so I prioritized developing that algorithm. Development involved a lot
of time researching how the algorithm works, as I read online articles, watched Youtube videos,
and scoured through Stack Ovoerflow in order to realize how my algorithm should work.
It got to the point that I started working on this project during breaks at school.
Some of my friends would pass by and I would tell them about it. Checking in occasionally,
they would see how development was going, and I would have the chance to explain what
the program did and why I was doing it. Unsurprisingly, this developed my own
understanding, now that I had to put the abstract knowledge into words.
This project, being both an opportunity to learn and to connect, is important to me, for
that exact reason; the project brought about fond memories to me.
The photos below are samples resulting from the library, along with tweaking of certain colors.
"output" is a basic example of procedural map generation, as it uses Perlin Noise
along with parameters to determine what "biome" (presented with colors) the area would be.
Green -> Grass, Blue -> Water, Grey -> Stone, White -> Snow. The data for the photo is all
floating-point numbers, but when you turn them into familiar colors, they can easiliy represent
a full map. I enjoy graphics so much ;-;