Manhattan

Taking it's name from a non-euclidean distance equation (also known as Taxicab), 'Manhattan' explores the output of random points fed into a Voronoi diagram built using the manhattan distance equation.

The manhattan distance equation results in graphs that have a much 'lower resolution' and appear more blocky.

It's this blockiness that this project aims to exploit and leverage as the core mechanic for the artwork.

The L1 voronoi graph is produced with a modified version of this manhattan-vornoi NPM library. The output is saved into SVG and then imported into Blender. A custom python script then continues the generative process by applying colour, ranom perturbations along the z-axis and some small extrusion.

These pieces are rendered at 20% of the 16,000 x 10,000 final render size (which takes about 12 hours with dual GTX 970 cards).

The final renders have significantly more detail:



This forms the first of a series of works based on voronoi graphs using manhattan distances.

Series

Detail (1:1)

Dimensions

3200 x 2000 (Non-standard Landscape)

FAQ

Can this exact image be re-produced? Yes so long as the point set and colour assignment are saved (which they are).

Are there any other images on this website that were generated by this algorithm? No

Is this a limited edition print? No

How can I buy a print? Please get in touch with your requirements.