Noise Fields, Noise Fields, Noise Fields

Noise Field (512 px x 512 px). An applied noise function. A.G. (c) 2016.

Here we have pretty much the same thing as before, i.e. a function called noisefield() that returns an image. This time what we did, or tried to do, was to generate a "LINE" first that is a list of 512 "RGB tuples" which in this case, as before, are randomly generated (via the noxel() function).

Then, simply enough, all we did was create an entity called "MATRIX" that is made up of 512 "LINEs". We used an "iter" function to create an object called "nixel", as you can see, that iterates over the "MATRIX" object which is basically just a very long sequence of RGB tuples made up of the concatenation of 512 "LINEs"

What you can see in the image above, created via this Python script, is an interesting series of LINEs, each with randomly chosen RGB tuple values.

Here is the code, hosted on Github as a Github Gist.

You might as well ask, since I know you're thinking it: Why go through all the troube? Couldn't you do this much more simply with less code and in a much more idiomatic style, plus much more elegantly? The answer is, yes, of course I could. This is only the beginning. I have structured the code this way because I want to be able to create what I call "mod" functions which are "modulations of the noise field", so to speak. I want to be able to create noise fields and then apply functions to them, either on a pixel-by-pixel basis or else on the whole image, or else on individual "LINEs" which in this case, as vectors if you will of random "RGB tuples", the LINEs that is, are actually "column" vectors and not "row" vectors, if you will. That is to say, the LINEs in the Image, of individual random RGB tuples, appear "horizontally", but the actual LINE in the code ends up being in the "vertical" direction. This is not a glitch, it's because in the code in the 5th line of the noisefield() function, we have (x,y), i.e.

im.putpixel((x, y), nixel.next())

We could just as easily make the uniform-colored lines appear on the vertical axis in the final image just by switching (x,y) to (y,x). To be continued...