A 2D map of the entire fleet conversation history — 2,000 session turns and 500 Lean theorems, each encoded as a 768-dimensional vector by the PEMCLAU embedding model, then compressed to 2D via UMAP. Points that are close together talk about the same things. Clusters reveal thematic structure in the fleet's cognitive history.
The result is a "water-lily pond" of meaning — like Monet's Nymphéas, beautiful at any distance.
pemclau-sessions-v1 — 236K total indexed turns · 2,000 sampled herejoffe-math-theorems-v1 — 5.7K total theorems · 500 sampled herefleet-sync/loom/pemclau_monet.pyTo generate a larger portrait (more nodes = richer map):
python3 pemclau_monet.py --sample 10000
Requires: qdrant running on yone · PEMCLAU collection · UMAP installed
JSON output → fleet-sync/loom/portraits/monet-portrait.json → copy to static/
Water lilies = UMAP clusters. Impressionist scatter. Each pond reflects a thematic region of the fleet mind. Beauty from distance.
Pointillism = individual turns. Every cell is one utterance. Grid view reveals density and temporal rhythm. Close up: pixels. Far: painting.
Ballet spirals = temporal flow. Sessions wound into a radial coil. The fleet's dance through time, SOSTLE as the choreography.
γ₁ = 14.134725141734693 — the imaginary part of the first non-trivial zero of the Riemann zeta function. All fleet coordinates, frequencies, and ring radii are grounded here. [theorem: FleetDay.lean]
The γ₁ frequency ring in DEGAS marks r = γ₁ × scale. Sessions that fall on this ring are at resonance with the Riemann floor.
→ LEGACY SESSION PORTRAIT (SAYBOOK FC1 · 5151 lines · 22 days)