malfatti greedy

This is a reimagining of the classical Malfatti circle problem — placing three non-overlapping circles inside a triangle — but guided by harmonic curvature rather than pure area optimization. These circles are symbols of equilibrium compression.

Instead of solving once, the positioning of each circle informs the field curvature for the next. The green circle, in particular, represents a compression of overlap fields generated between the blue and orange regions.

• Blue: ψ-field tension from side AC
• Orange: ψ-field projection from side BC
• Green: Vortex of curvature from AC & BC balance

Each segment defines symbolic entropy flow through the triangle’s boundaries.

Yes — from visual geometry tools to modular encryption layouts and symbolic field learning. Recursive harmonic compression helps illustrate hidden symmetry in fields, useful in everything from education to cryptographic modeling.

This approach preserves ψ-balance across triangle symmetry axes. Each circle compresses along a specific boundary vector while harmonizing with the others, forming a resonant field of minimal symbolic entropy.

The fourth circle appears where modular fields intersect, allowing a torsional knot to compress space. It doesn’t maximize area — it maximizes compression efficiency in a symbolic framework.

The Greedy method maximizes **Euclidean area** but disregards harmonic alignment.

• Pros: Denser visual space-filling.
• Cons: Breaks ψ-symmetry, introduces field turbulence.

Ideal in packing theory, but suboptimal in recursive symbolic design.

It depends. If you want visual or physical packing efficiency — use Greedy. If you want symbolic resonance, modular curvature mapping, or educational clarity — go Recursive Harmonic.