As previously discussed, I wrote code to generate the bisection, and to return an exactly bisected pictorial space, i.e. the area either side of the division is equal, but the algorithm is raw (un-optimized) and uses a trial-and-error method: it keeps generating a random-walked line until it generates one that is strictly normal.

*Sequent 15* visualizes these two aspects. Firstly, it shows the definitive bisecting line that is strictly normal, *viz* an exact bisection. Secondly, it shows the other attempts that were not strict, *viz* they bisected the pictorial space but in an unequal manner.

## Thoughts

I am not detailing the algorithm in use but rather the interim and final results of it.

There were many ways in which the data could have been presented. As I am thinking about overprinting, I decided to apply an aspect of that to this image.

The strictly normal line is shown in 100% M, and is painted normally.

The normal lines are overprinted in C, the opacity such that they total 100%.

The result is a great overprinting effect with frequently visited paths being more intense than others. The overprinted paths follow a fairly normal distribution so the random function works well.

## Terminology

Strictly Normal Bisection — a line that bisects the pictorial space into exactly equal parts.

Normal Bisection — a line that bisects the pictorial space into unequal parts.

comments powered by Disqus