Generative Art
Purchase
If you are interested in buying one of my pieces, then please contact me by email (thomasp85@gmail.com), through Twitter, or Instagram. I print myself (with some help for A1 and A0) on high quality paper using pigment ink. The price is US$100 for A4, US$150 for A3, US$450 for A1, and US$650 for A0, plus shipping.
On generative art
I’m a generative artist focusing mainly on exploring the beauty of dynamic systems. For me, the sweet spot of generative art lies in creating a system that you know well enough to set it up for success, but is so complex that you still get surprised when you see the result. The more I become familiar with a system I’ve developed, the more it feels like a (slightly unpredictable) brush to paint with.
The process of generative art is dual, in that it both requires the development of a system, as well as development of a visualisation method for the output of the system. A single system can give rise to very heterogeneous results if different visualisation approaches are employed. Mixing and matching existing systems and visualisation methods as well as developing new ones over time is the cornerstone of making generative art.
All my systems and visualisations are programmed in R, an open source programming language for statistics and data analysis. I’ve developed and released many tools that are central to my work, and help maintain others. Some of the packages I use most often are ggplot2, ggforce, ambient, particles, tidygraph, and ggraph. I do not share the code I use to create my pieces. The main reason for this is that I don’t think it would be beneficial to anyone. People interested in getting started with generative art would become to focused on my ideas instead of developing their own. Knowing the answer is the killer of creativity.
Gallery
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constructive323 -
constructive280 -
folding flow 62 -
folding flow 41 -
folding flow 3 -
folding flow 12 -
yonder4193 -
yonder400 -
yonder2345 -
yonder1831 -
winds6040 -
winds603 -
winds472 -
winds2857 -
winds2020 -
prism848 -
prism627 -
prism46 -
prism11 -
emergence6802 -
emergence55 -
emergence526 -
storms4500 -
storms351 -
storms3118 -
phases9032 -
phases705 -
phases330033 -
phases2423 -
genesis99 -
genesis9458 -
genesis93656 -
genesis90008 -
genesis6400 -
genesis45734 -
genesis4563 -
genesis4321 -
genesis39672 -
genesis338 -
genesis33 -
genesis3 -
genesis1300 -
genesis112 -
genesis100100 -
attraction12 -
attraction06 -
attraction03 -
unfold09 -
unfold08 -
unfold07 -
unfold06 -
unfold05 -
unfold04 -
unfold03 -
unfold02 -
unfold01 -
fill02 -
unwind08 -
unwind07 -
unwind04 -
unwind01
On generative art
I’m a generative artist focusing mainly on exploring the beauty of dynamic systems. For me, the sweet spot of generative art lies in creating a system that you know well enough to set it up for success, but is so complex that you still get surprised when you see the result. The more I become familiar with a system I’ve developed, the more it feels like a (slightly unpredictable) brush to paint with.
The process of generative art is dual, in that it both requires the development of a system, as well as development of a visualisation method for the output of the system. A single system can give rise to very heterogeneous results if different visualisation approaches are employed. Mixing and matching existing systems and visualisation methods as well as developing new ones over time is the cornerstone of making generative art.
All my systems and visualisations are programmed in R, an open source programming language for statistics and data analysis. I’ve developed and released many tools that are central to my work, and help maintain others. Some of the packages I use most often are ggplot2, ggforce, ambient, particles, tidygraph, and ggraph. I do not share the code I use to create my pieces. The main reason for this is that I don’t think it would be beneficial to anyone. People interested in getting started with generative art would become to focused on my ideas instead of developing their own. Knowing the answer is the killer of creativity.