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Introduction​

This is the website of the generative art workshop, taught by Jovana Andrejević, Nina Andrejević, and George Varnavides, in IAP 2022. This is the fifth iteration of the generative art workshop taught over IAP by the instructors (previously taught in 2021, 2020 with Amina Matt, and in 2017 and 2018 with Emma Vargo). We are indebted to Emma and Amina for some of the original content we'll use in the workshop.

Generative art is a type of audiovisual art generated using an algorithm. It often lies at the intersection of mathematical patterns and aesthetic appeal and its results can be stunning and refreshing. In this four-day workshop we will explore some of the aspects of generative art, starting with traditional examples such as mathematical fractals and chaotic attractors, and extending it to discrete and continuous physical systems such as diffusion limited aggregation and microstructural evolution. We will also be exploring multiple media such as visual and audio.

Communication​

There are three main ways in which we'll communicate for this workshop:

  • Website: To quickly peruse the notebooks used in the workshop.
  • Github repository: To access the notebooks and files used in the workshop.
  • Mailing list: To communicate class-wide announcements (only as needed).

Programming Languages​

While there are many great programming and scripting languages to do generative art with, the class will be taught using Python and the Wolfram Language. This choice is partly due to the following reasons (aside from the instructors' familiarity with these languages):

  1. Ease of prototyping (and learning) code
  2. Built-in (high-level) visualization functions
  3. The interactive Notebook format compliments the way we prototype and think of generative art

We'll try and provide most of the content in both languages; while we'll alternate presenting certain concepts in the Wolfram Language and others in Python, you will have the corresponding notebook in the other language for reference.

Installation instructions (Wolfram Language)​

If you're an MIT affiliate, you can get a free academic license for Mathematica following IST's instructions here: https://ist.mit.edu/mathematica/desktop. If you don't have access to an academic license, you can sign up for a free Wolfram Cloud license here: https://www.wolframcloud.com/.

Installation instructions (Python)​

We'll be using Google's Colaboratory to run Jupyter notebooks in Python. Google Colab is a cloud-based, free Jupyter notebook environment, and the notebooks can be downloaded if you prefer to run with a local Jupyter installation. All you need to use Google Colab is a Google account.