Mesh Clustering

Mesh Clustering

Grasshopper Course

What is the course about?

Mesh clustering is a concept of creating mesh patterns be defining relationships between neighbouring mesh faces. We will examine two approaches to these in this course, the first being through a closest point algorithm and the second with a basic look at Graph Theory.

The closest point algorithm will allow us to create long connected stripes over or mesh any geometry by defining relationships with neighbouring faces on a mesh. We will apply this algorithm, and extend its capabilities with a double-sided approach and attractor algorithms.

Graph theory could be thought of as the study of graphs compiled as mathematical structures used to pair relations between objects. A graph is made up of vertices (or nodes) which are connected by edges (or links), and this will allow us to create a variety of different mesh patterns on our geometry.

What will you learn in each video?

In this lesson we will create a closest point looping algorithm with Anemone, which will form the basis for our mesh clustering in later tutorials. This algorithm starts at a specific point on this list, and then visits every point on this that is the closest point to the previously visited point.

In this lesson we will apply a closest point looping algorithm to it to a simple mesh geometry. We will then reorder the faces in our mesh geometry so they correspond to the order of our closest point algorithm.

In this lesson we will continue developing a Mesh Clustering algorithm and attempt to turn our mesh faces into a series of striped paths that follow the logic of the closest point walking algorithm.

To further extend the capabilities of our mesh clustering algorithm, we can apply our stripe pattern on both sides of our geometry to add extra depth to our geometry.

In this lesson we will explore the patterns created in the Graph Theory plugin for grasshopper called ‘Ivy’. Ivy uses notions and algorithms from Graph Theory and applies them towards mesh geometry exploration. We will primarily be interested in the aesthetic nature of these graphs, and will apply their logic on a mesh geometry.

We can extend our mesh clustering and graph theory mesh patterns with the application of an attractor algorithm to our geometries to give further variation to the aesthetic of our outcomes.

What are the learning objectives for the course?

Course image gallery:

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