https://github.com/inconvergent/differential-line

a generative algorithm
https://github.com/inconvergent/differential-line

algorithm animation generative generative-art growth

Last synced: about 1 month ago
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a generative algorithm

• Host: GitHub
• URL: https://github.com/inconvergent/differential-line
• Owner: inconvergent
• License: mit
• Archived: true
• Created: 2015-07-23T23:44:31.000Z (about 9 years ago)
• Default Branch: master
• Last Pushed: 2018-05-23T10:55:28.000Z (over 6 years ago)
• Last Synced: 2024-07-19T03:07:54.213Z (about 2 months ago)
• Topics: algorithm, animation, generative, generative-art, growth
• Language: Python
• Homepage: https://inconvergent.net/generative/differential-line/
• Size: 7.17 MB
• Stars: 679
• Watchers: 22
• Forks: 96
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
Differential Line

=============

![ani](/img/ani2.gif?raw=true "animation")

This algorithm simulates the way a number of biological things in nature grows.

Among other things it is made to mimic the growth of the human brain, as well

as a great number of plants.

Specifically this code is a line-based implementation of behaviour very similar

to Floraform by Nervous System:

https://n-e-r-v-o-u-s.com/projects/sets/floraform/

Another relevant paper (which I discovered later) is this:

http://www.dgp.toronto.edu/~karan/artexhibit/mazes.pdf

![ani](/img/ani.gif?raw=true "animation")

![img](/img/img.jpg?raw=true "image")

In brief; we start of with a number of connected nodes in a circle. Gradually

we introduce new nodes on the line—prioritizing segments where the curve bends

more sharply.  Over time the curve grows increasingly intricate, but it never

self-intersects.

![img](/img/img1.jpg?raw=true "image")

![img](/img/img2.jpg?raw=true "image")

If we start with a different shape, and draw the outside position of the object

for each growth step, we can get an entirely different kind of system with an

interesting 3D illusion.

![img](/img/img3.jpg?raw=true "image")

## Prerequisites

In order for this code to run you must first download and install these two

repositories:

*    `iutils`: http://github.com/inconvergent/iutils

*    `zonemap`: https://github.com/inconvergent/zonemap

*    `fn`: https://github.com/inconvergent/fn (used to generate

     filenames, you can remove this dependency in the main files)

## Other Dependencies

The code also depends on:

*    `gi` (replaces pyGTK)

*    `numpy`

*    `cython`

*    `python-cairo` (do not install with pip, this generally does not work)

## Running it on Linux (Ubuntu)

To install the libraries locally, run `./install`. I have only tested this code

in Ubuntu 14.04 LTS, but my guess is that it should work on most other

platforms platforms as well.  However i know that the scripted install in

`./install` will not work in Windows

## Running it on Windows?

The code will probably work just fine under Windows, but I'm not sure how to

install it. (Let me know if you get it working!)

## Why all the main files?

If you just want to try this out you should have a look at `main_ani.py`. It is

pretty safe to ignore all the others main files. (They implement different

behaviour, and some of them are very experimental.)

## Similar code

If you find this alorithm insteresting you might also want to check out:

https://github.com/inconvergent/differential-mesh.

Recently I also implemented a version of this algorithm using CUDA:

https://github.com/inconvergent/differential-line-cuda