Peter Buš

Peter Buš

@peterbus
PETER BUŠ ARCHITECTURE | COMPUTATIONAL DESIGN | RESEARCH | Shenzhen, China
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Language Breakdown

Lines of code distribution across 10 owned repositories

1.0M Total LOC
Jupyter Notebook
740,649 lines
72.2%
N/A
C#
163,526 lines
15.9%
N/A
Processing
101,847 lines
9.9%
N/A
Python
17,081 lines
1.7%
N/A
ShaderLab
2,419 lines
0.2%
N/A
I

I-Shaped Developer

I-shaped

Specialist — deep expertise in Jupyter Notebook

Jupyter Notebook
C#
Processing
Python
ShaderLab

Collaboration Network

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Peter Buš
0 active collaborators

Repos

17

PRs

0

Growth

+18%

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Coding Streak

Contribution activity over the past year

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Top Repositories

Parametric-Tolerance-Model-for-Numerically-Controlled-Digital-Fabrication-

A Rhino-Grasshopper parametric definition for modification of tolerances for the WikiHouse components (Skylark 250). The model is described in the eCAADe 2023 paper titled: A Parametric Tolerance Model for Numerically Controlled Digital Fabrication Adaptation of kit-of-parts components for a pre-manufactured WikiHouse scenario.

2 1
Modelling-of-Large-datasets-of-fractal-like-3D-models-to-train-GAN

This strategy of Rhino | Grasshopper pipeline introduces the generation of fractals-like meshes in 3D to obtain a large amount of user-defined OBJ files. It builds upon a C# script inside Rhino Grasshopper interface which produces intricate and complex fractal-like structures, based on Mesh Normal Vector manipulation. Then, the design space is explored implementing the DSE addon by MIT, to deliver a series of parameters setup for the core script and finally the design space is stored as OBJ file utilising Python script to write OBJ files. The OBJ writing strategy was introduced in the Digital Futures 2021 workshop by Diego Pinochet.

2 0
Jupyter Notebook
XR-and-AI-driven-Generative-Methods-for-Architecture
1 0
C#
Co-Creative-Assemblies-DF-Workshop-2023
1 0
C#
Hand-Tracking-to-navigate-a-robot--Rhino-Grasshopper-framework
1 0
Python
EmCity

The programme provides a visual representation of urban growth based on emergent phenomena. The programme is based on an agent based model where agents seek accessible urban features in a desirable distance. The agents' movements and behaviour are controlled by the user via GUI. The model uses various Processing libraries like Plethora, Toxiclibs, Nervous System, PeasyCam or ControlP5.

1 1
Processing
AR_Foundation_with_XR_Interaction

Basic setup of the AR-based scene implemented with XR Interaction toolkit components. The placement prefab can be changed to anything else. Basic interactions such as scale, rotation and dragging are explored. Ready for deployment for Android (or iOS).

0 1
C#
Robot-Learning-GAIL-using-Unity-ML-agents
0 0
C#
3D_Grid2Grid-Pick-and-Drop---Eva-robot

Pick and drop scenario for Automata Eva robot. Extension of the previous Automata 2D Grid class into 3D Grid, operating with 3D dimensional space. The robot picks and drops between two 3-dimensional grids, continuously from one to another. Tested with Eva SDK 4.0.0., using the slower motion. The dimensions of the grids need to be tested, depending of the sizes of objects the robot pics and drops. The scenario operates with small prisms, dimensions: 7 x 5 x 3.5 cm ( in thickness).

0 0
Python
Eva_2D_Drawing

Code to program EVA robot to follow 2D toolpath using Fusion360

0 0
Python

Open Source Impact

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