All Videos Tagged C# (Grasshopper) - Grasshopper

KMeans clustering.

2019-05-22T23:02:04.873Z

This is the first Machine Learning implementation I did from a number of different learning algorithms I plan to implement within SharpMatter.
K-Means is a clustering algorithm that to seeks to learn from the properties of unlabelled data. K-Means aims to partition a given data set in to N clusters within a given property, each data element will belong to the cluster with the nearest mean. The algorithm uses an iterative technique until the data set reaches the desired N clusters (when clusters don't change). At each iteration step each data set is assigned to the cluster whose average mean has the least squared Euclidean distance , then after the new clusters are formed the new centroids are calculated and the process is repeated. The least squared Euclidean distance basically means how far apart the data elements are from each other. The typical set up is the number of n-dimensional vectors (data) to be clustered, K number of clusters and j number of iterations needed until convergence.

Physarum Polycephalum. Chemical trails

2019-05-22T22:54:48.412Z

Physarum Polycephalum.
Physarum Polycephalum, better known as “Slime Mould” is a single celled organism that can perform complex biological computations without any central controlling mechanism. Due to this property its computational abilities have become widely researched since the beginning of the 21st century. My initial studies were developed with SharpMatter and are based on Jeff Jones book “From Pattern Formation to Material Computation. Multi-Agent Modelling of Physarum Polycephalum ”. Specifically from chapter 3 -3.3. For a brief overview you can look at http://dx.doi.org/10.1162/art1.2010.16.2.16202
Each particle like agent is encoded with very simple rules of behaviour. The agents communicate and interact with each other through a “pheromone value” in the environment. Each agent can receive and modify the local values of the chemical through their 3 different sensors. Diffusion then helps to propagate the chemoattractant values through the environment. Depending on how each agent reads its environment different collective patterns emerge over time. The patterns formed are most of the times dynamic and adaptive to changing environmental conditions.
My further goal through this research is to be able to generate a tool which can be used for solving design problems.

Physarum Polycephalum

2019-05-22T22:52:49.440Z

BB8 vs Tie Fighter Swarm in Rhino (C#)

2017-12-20T14:00:26.446Z

BB8 vs a swarm of 100 tie fighters hunting him with their lasers! I added swarm behavior to the fighters so they fly in a formation similar to birds or schools of fish!
Thanks a lot to my friend and colleague Long Nguyen from ICD for animating BB8's belly and head movement a designing the Tatooine landscape (here: youtu.be/9__mU__FGvA)!
Everything done in C# in Rhino and Grasshopper

BB8 bravely fights of 100 Tie Fighters!

2017-12-20T02:31:53.104Z

It's Star Wars time! So why not have some fun and let BB8 be chased by evil tie fighters!
This programming exercise shows a flock of 40 (later 100) mean tie fighters revolving around BB8 and trying to shoot him with their lasers. Flocking behavior But no worries.... BB8 thankfully survives at the end (spoiler alert)
Thanks a lot to my friend and colleague Long Nguyen from ICD for animating BB8's belly and head movement a designing the Tatooine landscape (here: https://youtu.be/9__mU__FGvA)!
Everything done in C# in Rhino and Grasshopper