wifi-densepose

dearsky/wifi-densepose

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Author	SHA1	Message	Date
Claude	b3916386a3	feat: Add commodity sensing unit tests and fix feature extractor bugs Add comprehensive test suite (36 tests) for the ADR-013 commodity sensing module covering all components: RingBuffer, SimulatedCollector determinism, feature extraction (time-domain stats, FFT spectral analysis, band power isolation), CUSUM change-point detection, presence/motion classification, and end-to-end CommodityBackend pipeline. Fix feature_extractor.py: add missing _trim_to_window method that caused AttributeError on the WifiSample extraction path, add post-trim sample count guard, and handle constant-signal edge case in skewness/kurtosis computation to prevent scipy RuntimeWarning. https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714	2026-02-28 06:24:10 +00:00
Claude	6ed69a3d48	feat: Complete Rust port of WiFi-DensePose with modular crates Major changes: - Organized Python v1 implementation into v1/ subdirectory - Created Rust workspace with 9 modular crates: - wifi-densepose-core: Core types, traits, errors - wifi-densepose-signal: CSI processing, phase sanitization, FFT - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch) - wifi-densepose-api: Axum-based REST/WebSocket API - wifi-densepose-db: SQLx database layer - wifi-densepose-config: Configuration management - wifi-densepose-hardware: Hardware abstraction - wifi-densepose-wasm: WebAssembly bindings - wifi-densepose-cli: Command-line interface Documentation: - ADR-001: Workspace structure - ADR-002: Signal processing library selection - ADR-003: Neural network inference strategy - DDD domain model with bounded contexts Testing: - 69 tests passing across all crates - Signal processing: 45 tests - Neural networks: 21 tests - Core: 3 doc tests Performance targets: - 10x faster CSI processing (~0.5ms vs ~5ms) - 5x lower memory usage (~100MB vs ~500MB) - WASM support for browser deployment	2026-01-13 03:11:16 +00:00

Author

SHA1

Message

Date

Claude

b3916386a3

feat: Add commodity sensing unit tests and fix feature extractor bugs

Add comprehensive test suite (36 tests) for the ADR-013 commodity sensing
module covering all components: RingBuffer, SimulatedCollector determinism,
feature extraction (time-domain stats, FFT spectral analysis, band power
isolation), CUSUM change-point detection, presence/motion classification,
and end-to-end CommodityBackend pipeline.

Fix feature_extractor.py: add missing _trim_to_window method that caused
AttributeError on the WifiSample extraction path, add post-trim sample
count guard, and handle constant-signal edge case in skewness/kurtosis
computation to prevent scipy RuntimeWarning.

https://claude.ai/code/session_01Ki7pvEZtJDvqJkmyn6B714

2026-02-28 06:24:10 +00:00

Claude

6ed69a3d48

feat: Complete Rust port of WiFi-DensePose with modular crates

Major changes:
- Organized Python v1 implementation into v1/ subdirectory
- Created Rust workspace with 9 modular crates:
  - wifi-densepose-core: Core types, traits, errors
  - wifi-densepose-signal: CSI processing, phase sanitization, FFT
  - wifi-densepose-nn: Neural network inference (ONNX/Candle/tch)
  - wifi-densepose-api: Axum-based REST/WebSocket API
  - wifi-densepose-db: SQLx database layer
  - wifi-densepose-config: Configuration management
  - wifi-densepose-hardware: Hardware abstraction
  - wifi-densepose-wasm: WebAssembly bindings
  - wifi-densepose-cli: Command-line interface

Documentation:
- ADR-001: Workspace structure
- ADR-002: Signal processing library selection
- ADR-003: Neural network inference strategy
- DDD domain model with bounded contexts

Testing:
- 69 tests passing across all crates
- Signal processing: 45 tests
- Neural networks: 21 tests
- Core: 3 doc tests

Performance targets:
- 10x faster CSI processing (~0.5ms vs ~5ms)
- 5x lower memory usage (~100MB vs ~500MB)
- WASM support for browser deployment

2026-01-13 03:11:16 +00:00

2 Commits