Back to corpus
architecturetechnical paper candidatescore 70
Computational Choreography - Complete System Architecture
The Computational Choreography (CC) system transforms raw motion sensor data into musically-coherent audio control signals. The architecture follows a strict **bottom-up dependency graph** where lower layers know nothing about higher layers.
Full HTML reader
Read the full artifact
Extracted abstract or opening context
## Table of Contents 1. [Executive Overview](#1-executive-overview) 2. [System Stack Diagram](#2-system-stack-diagram) 3. [Crate Hierarchy](#3-crate-hierarchy) 4. [Layer-by-Layer Breakdown](#4-layer-by-layer-breakdown) 5. [Data Flow Pipeline](#5-data-flow-pipeline) 6. [Module Reference](#6-module-reference) 7. [Type System](#7-type-system) 8. [Frozen Contracts](#8-frozen-contracts) 9. [CC-Echelon Workspace Deep Dive](#9-cc-echelon-workspace-deep-dive) (18 crates, ~50,000 lines) 10. [CC-RAG-Plus-Plus Deep Dive](#10-cc-rag-plus-plus-deep-dive) (51 files, 24,879 lines) 11. [Python Layer Architecture](#11-python-layer-architecture) (~60,000 lines) 12. [Complete Data Flow Pipeline](#12-complete-data-flow-pipeline) 13. [FROZEN Contracts & Schema Versions](#13-frozen-contracts--schema-versions) 14. [Complete Crate Reference Table](#14-complete-crate-reference-table) 15. [Glossary of Key Terms](#15-glossary-of-key-terms)
The Computational Choreography (CC) system transforms raw motion sensor data into musically-coherent audio control signals. The architecture follows a strict **bottom-up dependency graph** where lower layers know nothing about higher layers.
| Metric | Value | |--------|-------| | **Total Rust Crates** | 32 (13 top-level + 18 cc-echelon + 1 workspace) | | **Python Packages** | 2 (cc-ml, cc-core) | | **Total Rust Source Lines** | ~185,000 | | **Total Python Source Lines** | ~60,000 | | **cc-rag-plus-plus** | 24,879 lines (51 files) | | **cc-echelon workspace** | ~50,000 lines (18 sub-crates) | | **cc-window-aligner** | ~22,000 lines | | **cc-ml Python** | ~33,000 lines | | **cc-core Python** | ~27,000 lines | | **Test Coverage** | 400+ tests | | **FROZEN Contracts** | 5 (v1.0.0) | | **CC-Echelon Sub-crates** | 18 | | **ML Model Families** | 11 |
| File | Lines | Purpose | |------|-------|---------| | `lib.rs` | 692 | LatentVector, Quaternion, Vec3, numeric utilities |
| File | Lines | Purpose | |------|-------|---------| | `lib.rs` | 270 | Confidence, ValidityHorizon, SemanticValue, UnavailableReason | | `frame.rs` | 400 | SemanticFrame v1, SemanticFrameBuilder, SemanticProvenance | | `phase.rs` | 290 | CyclicCoordinate, PhaseState, PhaseType | | `momentum.rs` | 300 | HeadingVector, MomentumState, ImpulseIndicator | | `tension.rs` | 293 | TensionState, TensionTrend, TensionProxies | | `intent.rs` | 200 | IntentState, IntentAvailability | | `stability.rs` | 396 | StabilityState, StabilityFlags, HealthMetrics | | `regime.rs` | 335 | RegimeType, RegimeDescriptor, RegimeEvidence |
Promotion decision
What has to happen next
Promote into a technical note or architecture paper with implementation anchors.
Why this is not always a full paper yet
Corpus pages are public-safe readers for discovered workspace artifacts. They are not automatically final papers. A corpus item becomes a polished paper only after the editable source, evidence checkpoints, references, figures, render path, and release status are attached through the paper schema.