Substitution System

Substitution System is a simple website to generate generative art using a substitution system. This works by using a random color palette and generating random replacement rules for each color. The replacement rules are a 2x2 grid of random colors from the color palette. A starting 2x2 grid is created, and the replacement rules are applied multiple times to transform the starting grid, doubling the size of the grid in each iteration. Here are two examples:

Plotting Pixel Art

These images also look good when drawn with a pen plotter using vpype and the vpype pixelart plugin.

To plot the images yourself, install vpype with the vpype pixelart plugin.

The following example command can be used to create a plot using a small substitution image (not the one with 1024x1024 pixels).

vpype pixelart \
    --mode line \
    --pen-width 0.6mm \
    --overdraw 0.1 \
    --upscale 5 \
    <path-to-pixelart-image.png> \
    linesort --no-flip \
    write \
    --page-size 10.0x10.0cm \
    --center \
    pixelart.svg

# save the layers of the pixelart.svg in separate files
vpype read pixelart.svg forlayer write "plot%_name or _lid%.svg" end

Use vpype pixelart --help to get more information about the arguments.

Next, I use the AxiCLI to plot the image with the following commands.

# get a preview with the timings
axicli plot.svg --model 2 -vg3 --speed_pendown 15 --report_time -o preview.svg

# plot the image
axicli plot.svg --model 2 --speed_pendown 15 --pen_pos_down 40

Here are two examples I plotted.

Sometimes, it might also look good if the layers are not perfectly aligned.

Contributing

Contributions to this project are welcome. Feel free to report bugs, suggest ideas, or create merge requests.

Developing

The project uses Prettier for linting JavaScript with a print-width of 120, tab-width of 4, and using single quotes.

Website Statistics

There is lightweight tracking for the website using Plausible. Anyone interested can view these statistics. It's worth noting that these statistics might be an underestimate as many users, including myself, use AdBlockers.

License

This project is licensed under the MIT License - see the LICENSE file for details.