Grow intricate coral-like forms with a deterministic, editable reaction-diffusion simulation. An independently implemented Gray–Scott solver evolves two concentration fields. A restrained turquoise and warm-ivory map makes the developing spots, splits and connected shapes visible. PopNow can supply missing artwork, footage or sound after a quote; owned material and the local example work without a connection.
- Uses PopNow for
- Music & voice
- Needs
- Python 3 · FFmpeg
The skill is free. Optional AI images, video and sound are quoted for your approval before generation. API-key calls use your separate API balance in USD; generation through ChatGPT or Claude connected via OAuth/MCP uses your website credits.
v1.0.0 · Updated Oct 25, 2026 · 3.3 MB · Use it for personal and client work; please don't resell or share the package.
What you get
An 8-second 1280 × 720 H.264 MP4 made by the local algorithm
An independently implemented Gray–Scott solver evolves two concentration fields. A restrained turquoise and warm-ivory map makes the developing spots, splits and connected shapes visible.
Editable JSON, a six-frame contact sheet and a receipt with actual checks
Good for
- Organic motion studies, generative art and evolving textures
- Original creative work using owned or licensed material
Not for
- Medical imagery, real-cell behavior or a seamless loop
- Publishing without watching the rendered result
How to use it
You say
Use the PopNow skill "Reaction Diffusion Organism" (reaction-diffusion-organism) for this: Grow intricate coral-like forms with a deterministic, editable reaction-diffusion simulation. Use the bundled project, render the example and inspect the full result before delivery.
Then try
Change seed from 43 to 19 to grow a genuinely different initial colony.
Use my licensed music; keep source audio discarded.
What to have ready
- A numerical seed and a stable feed/kill regime; no image input is required.
- Python 3.10+, FFmpeg/ffprobe, Pillow and NumPy
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Questions
Is this a prerecorded texture or an actual simulation?
It is a local NumPy simulation with a nine-point Laplacian and periodic boundaries. The receipt records concentration bounds, state hash and first-to-last change.
What happens if parameters erase the pattern?
A uniform or non-finite result fails validation. Even valid regimes differ visually; review the composition before presenting it as a finished work.
Does the local render spend generation funds?
No. It reads local media and renders locally. Missing media can be made through PopNow after an exact quote and approval; no paid call occurs in the renderer.