2) 'n' is some constant. you calculate r= n*noise(x), the result is r = r - (int)r. classic example this is used to create wood grains.

Sorry... Seems to be something which could be helpful, (if you say that It's an classic example? yeah... I think so) but I didn't understand it yet :/ You simply multiplicate

`noise(x)` by

`n`. What exactly is

`noise(x)`? It seems to be the point where all the magic happens...

What are you really trying to do? Simplex noise done right already interpolates properly. IIRC something cubic (splines).

Yes. But simplex noise has to be done first

(I've tried out hermetic spline curves (I somehow didn't got that working properly...) and cubic splines are the next ones I want to test.

I just tried using the Math.log1p(x) function with the inputs 0 and 1.

It gives an output that ranges from 0 to 0.6931471805599453.

So one could get an output range from 0 to 1 by multiplying by the inverse: 1.4426950408889634

I assume you can normalize the distance between the two points you wish to interpolate.

1 2
| double A = Math.log1p(x) * 1.4426950408889634; |

Then, you can multiply your two values by A and 1-A.

Does this work? Math is NOT my forte.

Erm... intresting... I've never heard about

` log1p`... what curve does it give, if I feed x values ranging from 0 to 1 to the function? You say they range from 0 to 0.693, but in which way?

P.S. Am VERY interested to see what you are coming up with using textures & noise!! I hope you will post some graphics at some point.

First: I will show screenshots

(They won't be special... only some trees on a 2D planet... (side scrolling view)) or maybe I'll post a curve graph from what it generates...

Second: textures?

Are you talking about the simplex noise? I didn't want to generated textures, and my "simplex noise" is 1-dimensional

(propably the name is anothe one...). But the simplex noise is constructed like simplex noise is constructed usually... I think...

My "algorithm" consists of 2 data structures (? Should I call them like that? they are 2 classes...):

- SimplexNoiseLayer
- SimplexNoise

`SimplexNoiseLayer` has following properties:

- length (the number of values to generate... (the length on the x axis (no y-axis present)))
- density (hard to explain... for example if density is 4, then every 4th value in the array will be set to randomly either -1 or 1)
- interpolator (a class for interpolating 2 values with a given "time" factor)

`SimplexNoise`:

- An array/list of as much
`SimplexNoiseLayer`s to "combine".

- An array of "importances" for each layer.

The the importance for each layer gives informaiton about how strong it will affect the values for the "final" array.

Everything is 1-Dimensional.

[size=8pt]The words written in these "-ses are words I don't really know how to describe... I'm not a native english speaker here...[/size]

The only problem for me right now is the simplex noise interpolator... The other stuff works... the interpolator should give something wich looks somehow like this (from google):