**OVERVIEW**

Venation is an implementation of a generative algorithm aiming to mimick biological venation patterns. It is a fairly straightforward implementation of the [1] algorithm for turning a field of nutrients (e.g. mesh points) into a branching structure reminiscent of leaves venation pattern.

It is geared specifically at the Python community so as to renew / encourage / further the interest in generative art. It is still rough and there are definitely a number of other approaches to decrease computation time, increase complexity and variability of the patterns, make it more faster, more robust, more elegant. That being said due to time constraints, I thought it effective and fun enough that it was worth it to make this available to the community and go from there.

Have fun!

**WHAT IS VENATION** - Quick overview of patterns found in living organisms.

**APPROACH** - Algorithmic approach and pitfalls.

**WHAT IS VENATION**

Simulation-based visual modeling of patterns found in living organisms has a long history, bridging biology, theoretical studies of **morphogenesis**, and computer graphics.
Together with **spiral phyllotaxis** and the branching structures of tree architecture, **venation patterns** are among the most admirable aspects of the natural beauty of plants.
So what is venation? By definition, it simply consist in the arrangement of veins, as in a leaf or in the wing of an insect.

Example of the growing pattern of veins in a leaf (taken from [1])

**APPROACH**

Inspired by the paper Modeling and visualization of leaf venation patterns.
The algorithm basic principle relies on iteratively **growing seeds (black disks with white centers)** towards the nearest set of **nutrients (red disks)**. This is done by assigning each source of auxin the seed node that is closest to it; thus establishing the set of sources influencing each node.

Illustration of the algorithm for generating open venation patterns [1]