3 ms·
You missed that the noise function is given n-dimensional coordinates as an argument. Rather than picturing an RNG, you can think of it as a texture unit that s
by n3k5 7y ago
You missed that the noise function is given n-dimensional coordinates as an argument. Rather than picturing an RNG, you can think of it as a texture unit that samples from an n-dimensional image of some noise with certain characteristics.
The order in which sample values are retrieved doesn't matter — of course it doesn't! It's important that fragments (think 'pixels' in case you're wondering what fragments are) can be evaluated independently and in any order, as computing fragments is supposed to be a massively parallel operation.
It this context, you have to throw out the concept of 'previous' sample values and replace it with 'nearby' values.
- strainer 7y agoThanks, I wasn't clear on what that vector f*x was. So the noise function is mapping pattern values to coordinates, and the SBM function is combining/layering its patterns calculated with different powers at different scales. Still on the face of it that advice "the choice of noise function doesn't matter much" is tricky, considering "white noise" is mentioned in the intro which takes no coordinates, but white noise walks of different scales can be combined I think to produce a non-white noise walk. Besides this combining in a loop the same kind of noise/texture with different power over different scales, I would be interested in also varying the kinds of texture that are layered into different scales.