T w e n t y S i d e d

Today we’re finally going to start adding some features to make this thing look a bit more… What? You say you want another digression on noise filtering and interpolation techniques? You sure? Okay then!

(Nerd!)

If you remember from last time, we’re taking tables of random white noise and expanding them to create “interesting” patterns. Stuff like this:

Now, I really don’t want to have the next bunch of images be black & white scramble squares. That’s boring and it’s actually hard to see the effect I’m talking about. So I’ve altered my program to output example images that will use color-blending to make the gradients more clear. So the above image now looks like this:

Just remember we’re not really dealing with color data right now. We’re actually just generating heaps of numbers between zero (dark blue) and one (red) and this color-fade makes it easier to see what we’re doing. Okay? Great.

Continue reading ⟩⟩ “Project Octant Part 5:The Rainbow Collection”

Shamus Young is a programmer, an author, and nearly a composer. He works on this site full time. If you'd like to support him, you can do so via Patreon or PayPal.

Perlin Noise is a technique for quickly generating a metric crapload of really interesting pseudo-randomness. “Interesting” in that it forms nice organic patterns instead of pure random noise. “Pseudo Random” in that you can give it the same input and get the same output. “Crapload” means that you can make a final data set thousands of times larger than the noise you start with.

Note that in the context of this project I’m going to discuss Perlin in terms of 2D images, but I’m using it in 3D. It’s just easier to show you what we’re doing in 2D.

We begin with a basic image of really random noise, which I will depict as a 2D greyscale image. The more random the better. We want areas of light, dark, and medium brightness. We want it to be really diverse overall, but have small local clusters of bright or darkness. We don’t want large areas to be homogeneous, and we don’t want the small areas just just be a scatter of white and black pixels. We can accomplish this a lot of ways. I could churn out a bunch of values in a random number generator, for example. Or, we can just open up a new image in your Photoshop of choice, crank up the noise filter on a blank image, and hit save.

Awesome, right?

Continue reading ⟩⟩ “Project Octant Part 4: The Beautiful Noise”

Shamus Young is a programmer, an author, and nearly a composer. He works on this site full time. If you'd like to support him, you can do so via Patreon or PayPal.

Qt is a cross-platform application and UI framework with APIs for C++ programming. In English, that means it’s a bunch of software that you can add to your project to make programs with a GUI that will run on Windows, Linux, or Mac. This is actually a big deal. There’s a reason that so few programs are cross-platform: It’s hard to write code that will run anywhere.

I know I keep sending you back to the Object-Disoriented Programming post so often it sort of feels like a Rickroll at this point, but this is a really important problem. C++ itself is very barebones. It doesn’t load fonts. It doesn’t understand images. It doesn’t understand windowed environments. To do these things you need an SDK. You’ll need one for each new thing you want to do. Each one might tie you to a particular operating system, and they’re very likely to conflict with each other in annoying ways. By the time you get all the stuff you need for GUI, images, sound, graphics, threading, and input, your project will be this Frankenstein’s Monster of sewn-together systems. And you haven’t even started coding yet!

Continue reading ⟩⟩ “Project Octant Part 3: Using Qt”

Shamus Young is a programmer, an author, and nearly a composer. He works on this site full time. If you'd like to support him, you can do so via Patreon or PayPal.