fractal-edm-showcase

name	fractal-edm-showcase
title	Fractal EDM Showcase
description	Automated workflow to generate a short fractal showcase video with a synthetic fast‑paced EDM soundtrack, including Seahorse and Elephant valley visual elements.
author	Hermes Agent
created	2026-04-14T00:00:00.000Z

Overview

When to Use

Automated workflow to generate a short fractal showcase video with a synthetic fast‑paced EDM soundtrack, including Seahorse and Elephant valley visual elements.

Overview

This skill contains a reusable operational workflow. Follow the existing task-specific steps and examples in the sections below.

Pitfalls

• Do not hardcode credentials, tokens, or personal secrets.
• Verify external service URLs, paths, and permissions before making changes.
• Keep generated outputs reproducible and record input assumptions.

Verification

• Confirm required inputs and credentials are available.
• Run the smallest safe command or example before scaling up.
• Check produced files, API responses, or plots before reporting success.

This skill automates the creation of a short (~55 s) fractal showcase video that includes:

• Mandelbrot set, Sierpinski triangle, Barnsley fern, Seahorse Valley (tiny central figure), and Elephant Valley (jet‑coloured, slowly zoomed).
• A synthetic, fast‑paced EDM soundtrack (140 BPM) generated entirely in Python.
• Final video‑audio merge using ffmpeg.

The workflow is fully script‑driven and works with the local Manim environment (~/.venvs/manim).

Files & Directory Structure

~/fractals-animation/
├─ script.py                 # Manim scene (see below)
├─ audio/
│   ├─ generate_edm_track.py   # EDM synthesis script
│   ├─ edm_fast.wav            # generated WAV (temporary)
│   ├─ edm_fast.aac            # AAC‑encoded version
│   └─ edm_fast_trimmed.aac    # 55 s trimmed track
└─ media/videos/script/480p15/
    └─ FractalsShowcase_EDM_fast.mp4   # final output

Step‑by‑Step Procedure

1️⃣ Generate PNG fractal assets

The script.py contains helper functions that lazily generate and cache the required images in /tmp/fractals_imgs:

• save_mandelbrot
• save_sierpinski
• save_barnsley_fern
• save_barnsley_elephant
• save_seahorse – creates a tiny seahorse‑like point cloud (scale ≈ 0.00009).
• save_elephant_jet – loads the original elephant PNG, converts to grayscale, applies Matplotlib’s jet colormap and resizes to 512 × 512. Run once (or rely on the caching logic in script.py).

2️⃣ EDM audio synthesis (audio/generate_edm_track.py)

Key parameters (easy to tweak):

BPM = 140                # fast, rocking tempo
TOTAL_SEC = 60           # generate a bit longer, will be trimmed to 55 s
SR = 44100               # 44.1 kHz

The script builds four tracks:

• Kick – decaying sinusoid with pitch drop.
• Snare – band‑passed noise burst.
• Hi‑hat – short high‑frequency square‑wave burst.
• Bass – low‑frequency sinusoid with a 0.25 Hz LFO wobble. All tracks are mixed to stereo, normalised, written to edm_fast.wav, converted to AAC (edm_fast.aac), then trimmed to exactly 55 s (edm_fast_trimmed.aac).

3️⃣ Render the Manim video (draft quality)

source ~/.venvs/manim/bin/activate
manim -ql ~/fractals-animation/script.py FractalsShowcase

The scene order:

1. Title fade‑in/out.
2. Mandelbrot zoom.
3. Sierpinski → Fern.
4. Elephant Valley – displayed with ELEPHANT_JET_IMG, fade‑in, then a 30 s slow zoom (scale(0.5)).
5. Seahorse Valley – tiny central image (scale(0.2)), brief fade‑in/out.
6. Closing caption. All fades are non‑overlapping (clear‑before‑next) to respect the visual style.

4️⃣ Merge audio & video

ffmpeg -y -i /home/hermes/media/videos/script/480p15/FractalsShowcase.mp4 \
       -i /home/hermes/fractals-animation/audio/edm_fast_trimmed.aac \
       -c:v copy -c:a aac -b:a 192k -shortest \
       /home/hermes/fractals-animation/media/videos/script/480p15/FractalsShowcase_EDM_fast.mp4

Resulting file is ~2.5 MB (15 fps, 854 × 480).

Pitfalls & Gotchas

• Variable scope: ELEPHANT_JET_IMG must be defined before it is used in the scene (the original script raised a NameError). Ensure the image‑generation block runs before the class definition.
• Caching: The script checks os.path.exists for each PNG; delete the /tmp/fractals_imgs folder if you need to regenerate with different parameters.
• Audio length mismatch: If you change the video length (e.g., add more scenes), update TOTAL_SEC or the ffmpeg -t trim duration accordingly.
• Zoom speed: Adjust the run_time in self.play(elephant.animate.scale(...)) to achieve the desired visual pacing.
• Manim version: Tested with Manim 0.20.1; newer versions may require minor syntax tweaks.

Re‑use

You can drop the whole ~/fractals-animation folder into a new project, tweak the BPM, scaling factors, or replace the fractal set with your own images. The workflow works on any Linux machine with Python 3.11, Manim, NumPy, Matplotlib, Pillow, and ffmpeg installed.