LÖVE

substitute541 wrote:Added new documentation. See project page.

Mermersk wrote:

substitute541 wrote:Added new documentation. See project page.

Nice! I was testing-learning this library again.

I was wondering in the previous version there was "setnormalized(true/false)", But it's not in the new version, is it now in this new version always on true ? I have no Idea what it means/does, all I know is that when using fractal noise and on normalized(true) it kinda looks like a landmap.

Also what is "setLacunarity()" after some testing of values from 0 to 1(on fractal noise) it seems to just do the same as "setPersistence()".

One thing more, when you have fractal noise and you add colour to it you get like 2 primary colours, like blue and brown, wich look like land and sea. Now it's easy to change how it looks(smoothness, colors, ruggedness) but how would for example make one color more dominant than the other and vice versa?

Nice that you added Billow noise!

val = noise:getValue(x, y) -- get value from noise at position [x, y]
val = val*0.5+0.5 -- scale the range of the value from 0-1 (for convenience)

if val < 0.2 then
    color = blue
else
    color = green
end

...

love.graphics.setPixel(x, y, color[1], color[2], color[3], 255)

Mermersk wrote:Thanks fro the reply!

I have one more, Billow noise is supposed to be good for clouds. But I don't get it looking like here: http://www.burnweb.net/libnoise/_img/bi ... w_gray.png

I only get a variation of this: https://love2d.org/imgmirrur/7ZHT7Gp.png (octaves = 23 and frequency = 0.01).

So I think my question is how do I make it more "Puffy" like image 1 ?

substitute541 wrote:

Mermersk wrote:Thanks fro the reply!

I have one more, Billow noise is supposed to be good for clouds. But I don't get it looking like here: http://www.burnweb.net/libnoise/_img/bi ... w_gray.png

I only get a variation of this: https://love2d.org/imgmirrur/7ZHT7Gp.png (octaves = 23 and frequency = 0.01).

So I think my question is how do I make it more "Puffy" like image 1 ?

I don't think you are using the values correctly. Remember that the values range from -1 to 1, so you may have to scale it. For example, if you are using the values in a gray scale image, each of your color channels must have a value noiseval*127+128.

Also, I think that image was generated with billow noise scaled in the lower range, so that the lower values clamps to -1.