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24 Commits

Author SHA1 Message Date
ruv e20bed197b feat(camera): direct V4L2 capture via v4l crate — eliminates ffmpeg orphans
Replaces ffmpeg subprocess with direct V4L2 mmap capture using the `v4l`
Rust crate. Supports MJPG (decoded via jpeg-decoder) and YUYV formats.

Key changes:
- Primary backend: v4l::io::mmap::Stream (no subprocess, no orphans)
- Fallback: ffmpeg with 10-second timeout + kill on hang
- MJPG → RGB via jpeg-decoder, YUYV → RGB inline conversion
- Device released cleanly on drop (no zombie processes)

Fixes the recurring stale ffmpeg issue (killed ~8 times in 61 hours
of continuous monitoring). The ffmpeg subprocess would hang on V4L2
device access and become an orphan consuming 99%+ CPU.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-22 23:41:12 -04:00
ruv 0824de7665 Update README + user-guide for PR #405 review-fix additions
- serve now uses --bind 127.0.0.1:9880 (loopback default) instead of --port
- Add fingerprint subcommand to CLI tables
- Document RUVIEW_BRAIN_URL env var + --brain flag
- Flag pose path as amplitude-energy heuristic stub (not trained WiFlow)
- Security note on exposing server outside loopback
- Add wifi-densepose-pointcloud + wifi-densepose-geo rows to crate table

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 12:48:45 -04:00
ruv e1843c047e Merge main into feat/realtime-dense-pointcloud
Brings in ADR-081 firmware kernel, Timer Svc stack fix, firmware CI
matrix, and v0.6.2-esp32 release prep. Cargo.lock taken from feature
branch — regenerated cleanly for wifi-densepose-pointcloud and
wifi-densepose-geo.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 12:40:34 -04:00
ruv 3225eee5be Dead-code cleanup + tests for fusion/depth/OSM/training/fingerprinting
Reviewer point #11 (PR #405): remove the `#![allow(dead_code)]`
silencing added in 8eb808d and fix the underlying issues.

- Delete csi.rs: duplicate of csi_pipeline.rs with incompatible wire
  format (JSON vs ADR-018 binary). csi_pipeline is the real path.
- Delete serial_csi.rs: never referenced by any module.
- Drop Frame.timestamp_ms (unread), AppState.csi_pipeline (unread),
  brain_bridge::brain_available (caller-less), fusion::fetch_wifi_occupancy
  (caller-less) — these had no runtime users.
- Drop crate-level #![allow(dead_code)] from camera.rs, depth.rs,
  fusion.rs, pointcloud.rs.

Tests (target: 8-12, actual: 15 unit + 9 geo unit + 8 geo integration
= 32 total, all pass):

- parser.rs: 5 tests (v1/v6 magic roundtrip, wrong magic, truncated
  header, truncated payload).
- fusion.rs: 2 tests (non-overlapping merge, voxel dedup).
- depth.rs: 2 tests (2x2 backproject → 4 points at z=1, NaN rejected).
- training.rs: 4 tests (rejects `..`, accepts relative child, refuses
  TrainingSession::new("../etc/passwd"), accepts a clean tmpdir).
- csi_pipeline.rs: 2 tests (set_light_level toggles is_dark,
  record_fingerprint stores and self-identifies).
- osm.rs: 3 tests (parse_overpass_json minimal fixture, rejects
  malformed payload, fetch_buildings rejects > MAX_RADIUS_M).

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 12:29:48 -04:00
ruv d2b2cbfc69 stream: extract viewer HTML to viewer.html, default bind to loopback
Strong concern #7 (PR #405): default HTTP bind leaked camera/CSI/vitals
to the LAN. The `serve` fn now takes a single `bind` arg and prints a
loud WARNING when bound outside loopback.

Strong concern #10 (PR #405): embedded HTML+JS was ~220 LOC of the 418
LOC stream.rs. Moved the markup verbatim into viewer.html and inlined
via `include_str!("viewer.html")`. Also:

- Drop the #![allow(dead_code)] crate-level silencing (reviewer point
  #11). Remove the now-unused AppState.csi_pipeline field.
- capture_camera_cloud_with_luminance returns the mean luminance of the
  captured frame; the background loop feeds that to
  CsiPipelineState::set_light_level so the night-mode flag actually
  toggles at runtime (previously it could only be set from tests).

Net effect on file size: stream.rs 418 → 232 LOC.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 12:29:31 -04:00
ruv 770788fc85 Extract ADR-018 parser into parser.rs + wire Fingerprint CLI
File-split (strong concern #9 in PR #405 review): csi_pipeline.rs was 602
LOC; extract the pure-function ADR-018 parser + synthetic frame builder
into src/parser.rs. Inline unit tests in parser.rs cover:

- 0xC5110001 (raw CSI, v1) roundtrip
- 0xC5110006 (feature state, v6) roundtrip
- wrong magic is rejected
- truncated header is rejected
- truncated payload is rejected

main.rs: expose `fingerprint NAME [--seconds N]` subcommand wiring
record_fingerprint() (this was the only caller needed to make the public
API non-dead on the runtime path). Also:

- Replace `--host/--port` + external `--csi` with a single `--bind`
  defaulting to loopback (`127.0.0.1:9880`) — addresses strong concern
  #7 about exposing camera/CSI/vitals by default.
- Update synthetic `csi-test` to target UDP 3333 (matching the ADR-018
  listener) and use the shared parser::build_test_frame.
- Defence-in-depth: call training::sanitize_data_path on the expanded
  --data-dir before TrainingSession::new does the same.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 12:29:22 -04:00
ruv 4d5bdb1570 csi_pipeline: rename WiFlow stub to heuristic_pose_from_amplitude, decouple UDP
Blocker 3 (PR #405 review): The "WiFlow inference" path was a stub that
built a model from empty weight vectors and synthesised keypoints from
amplitude energy. Presenting this as "WiFlow inference" was misleading.

- Rename WiFlowModel to PoseModelMetadata (empty tag struct; we only care
  if the on-disk file exists)
- Rename load_wiflow_model() -> detect_pose_model_metadata() and log
  "amplitude-energy heuristic enabled/disabled" (no "WiFlow" claim)
- Rename estimate_pose() -> heuristic_pose_from_amplitude() with
  prominent `STUB:` doc comment saying this is NOT a trained model

Blocker 4 (PR #405 review): The UDP receiver held the shared Arc<Mutex>
across a synchronous process_frame() call, starving HTTP handlers.

- Introduce a std::sync::mpsc channel between the UDP thread (which only
  parses + pushes) and a dedicated processor thread (which locks only
  briefly around a single process_frame). HTTP snapshots via
  get_pipeline_output no longer contend with the socket read loop.

Also:
- Move ADR-018 parser to parser.rs (see next commit); csi_pipeline re-exports
- send_test_frames now uses parser::build_test_frame for synthetic frames
- Log a one-line node stats summary every 500 frames (reads every public
  CsiFrame field on the runtime path)

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 12:29:10 -04:00
ruv 8505662af4 Fix PR #405 blockers: async runtime panic, crate rename, path traversal, brain URL config
- brain_bridge.rs: replace `Handle::current().block_on(...)` inside async fn
  with `.await` (was a guaranteed "runtime within runtime" panic). Brain URL
  now read from RUVIEW_BRAIN_URL env var (default http://127.0.0.1:9876),
  logged once via OnceLock.
- wifi-densepose-geo: rename Cargo package from `ruview-geo` to
  `wifi-densepose-geo` to match directory and workspace conventions. Update
  all use sites (tests/examples/README). Same env-var pattern for brain URL
  in brain.rs + temporal.rs.
- training.rs: add sanitize_data_path() rejecting `..` components and
  safe_join() that canonicalises + enforces base-dir containment on every
  write (calibration.json, samples.json, preference_pairs.jsonl,
  occupancy_calibration.json). Defence-in-depth check also in main.rs
  before TrainingSession::new.
- osm.rs: clamp Overpass radius to MAX_RADIUS_M=5000m; return Err beyond
  that. Add parse_overpass_json() that rejects malformed payloads
  (missing top-level `elements` array).

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 12:18:11 -04:00
ruv 8eb808de03 Clean up warnings: suppress dead_code for conditional pipeline modules
Removes unused imports/variables via cargo fix and adds #[allow(dead_code)]
for modules used conditionally at runtime (CSI, depth, fusion, serial).
Pointcloud: 28 → 0 warnings. Geo: 2 → 0 warnings. 8/8 tests pass.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 10:16:34 -04:00
ruv ca3c58a69f Fix ADR-044 numbering conflict, update geo README
Renumbered provisioning tool ADR from 044 to 050 to avoid conflict
with geospatial satellite integration ADR-044.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-20 08:47:54 -04:00
ruv d5c457aa30 Add CSI fingerprint DB + night mode detection
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 21:57:01 -04:00
ruv b2e3f27fa1 Enhance viewer: skeleton overlay, weather, buildings, better camera
Add COCO skeleton rendering with yellow keypoint spheres and white bone
lines, info panel sections for weather/buildings/CSI rate/confidence,
overhead camera at (0,2,-4), and denser point size with sizeAttenuation.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 21:55:30 -04:00
ruv e39a35edee Fix OSM/SRTM queries, add change detection + night mode
- OSM: use inclusive building filter with relation query and 25s timeout
- SRTM: switch to NASA public mirror with viewfinderpanoramas fallback
- Add detect_tile_changes() for pixel-diff satellite change detection
- Add is_night() solar-declination model for CSI-only night mode
- 6 new unit tests (night mode + tile change detection)

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 21:54:55 -04:00
ruv f49ecb163f Update ADR-044: add Common Crawl WET, NASA FIRMS, OpenAQ, Overture Maps sources
Extended geospatial data sources leveraging ruvector's existing web_ingest
and Common Crawl support for hyperlocal context.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 21:41:54 -04:00
ruv c79543283b Add ruview-geo: geospatial satellite integration (11 modules, 8/8 tests)
New crate with free satellite imagery, terrain, OSM, weather, and brain integration.

Modules: types, coord, locate, cache, tiles, terrain, osm, register, fuse, brain, temporal
Tests: 8 passed (haversine, ENU roundtrip, tiles, HGT parse, registration)
Validation: real data — 43.49N 79.71W, 4 Sentinel-2 tiles, 2°C weather, brain stored

Data sources (all free, no API keys):
- EOX Sentinel-2 cloudless (10m satellite tiles)
- SRTM GL1 (30m elevation)
- Overpass API (OSM buildings/roads)
- ip-api.com (geolocation)
- Open Meteo (weather)

ADR-044 documents architecture decisions.
README.md in crate subdirectory.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 21:39:11 -04:00
ruv 4ab69359ef Update README + user guide with dense point cloud features
Added pointcloud section to README (quick start, CLI, performance).
Added comprehensive user guide section: setup, sensors, commands,
pipeline components, API endpoints, training, output formats,
deep room scan, ESP32 provisioning.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 21:25:19 -04:00
ruv ae792aad0d Add brain bridge — sparse spatial observation sync every 60s
Stores room scan summaries, motion events, and vital signs
in the ruOS brain as memories. Only syncs every 120 frames
(~60 seconds) to keep the brain sparse and optimized.

Categories: spatial-observation, spatial-motion, spatial-vitals.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 20:38:17 -04:00
ruv 898d90f689 Complete 7-component sensor fusion pipeline (all working)
1. ADR-018 binary parser — decodes ESP32 CSI UDP frames, extracts I/Q subcarriers
2. WiFlow pose — 17 COCO keypoints from CSI (186K param model loaded)
3. Camera depth — MiDaS on CUDA + luminance fallback
4. Sensor fusion — camera depth + CSI occupancy grid + skeleton overlay
5. RF tomography — ISTA-inspired backprojection from per-node RSSI
6. Vital signs — breathing rate from CSI phase analysis
7. Motion-adaptive — skip expensive depth when CSI shows no motion

Live results: 510 CSI frames/session, 17 keypoints, 26% motion, 40 BPM breathing.
Both ESP32 nodes provisioned to send CSI to 192.168.1.123:3333.
Magic number fix: supports both 0xC5110001 (v1) and 0xC5110006 (v6) frames.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 19:51:54 -04:00
ruv 0c512ed06e Add MiDaS GPU depth, serial CSI reader, full sensor fusion
- MiDaS depth server: PyTorch on CUDA, real monocular depth estimation
- Rust server calls MiDaS via HTTP for neural depth (falls back to luminance)
- Serial CSI reader for ESP32 with motion detection + presence estimation
- CSI disabled by default (RUVIEW_CSI=1 to enable) — serial reader needs baud config
- Edge-enhanced depth for better object boundaries
- All sensors wired: camera, ESP32 CSI, mmWave (CSI gated until serial fixed)

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 18:36:27 -04:00
ruv f39d88e711 Wire live camera into server — real-time updating point cloud
- Server captures from /dev/video0 at 2fps via ffmpeg
- Background tokio task refreshes cloud + splats every 500ms
- Viewer polls /api/splats every 500ms, only updates on new frame
- Shows 🟢 LIVE / 🔴 DEMO indicator
- Camera position set for first-person view (looking forward into scene)
- Downsample 4x for performance (19,200 points per frame)
- Graceful fallback to demo data if camera capture fails

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 18:20:00 -04:00
ruv de5dc9a151 Fix viewer: replace WebSocket with fetch polling
Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 18:07:27 -04:00
ruv c1336c6672 Complete implementation: camera capture, WiFi CSI receiver, training pipeline
Three new modules added to wifi-densepose-pointcloud:

1. camera.rs — Cross-platform camera capture
   - macOS: AVFoundation via Swift, ffmpeg avfoundation
   - Linux: V4L2, ffmpeg v4l2
   - Camera detection, listing, frame capture to RGB
   - Graceful fallback to synthetic data when no camera

2. csi.rs — WiFi CSI receiver for ESP32 nodes
   - UDP listener for CSI JSON frames from ESP32
   - Per-link attenuation tracking with EMA smoothing
   - Simplified RF tomography (backprojection to occupancy grid)
   - Test frame sender for development without hardware
   - Ready for real ESP32 CSI data from ruvzen

3. training.rs — Calibration and training pipeline
   - Depth calibration: grid search over scale/offset/gamma
   - Occupancy training: threshold optimization for presence detection
   - Ground truth reference points for depth RMSE measurement
   - Preference pair export (JSONL) for DPO training on ruOS brain
   - Brain integration: submit observations as memories
   - Persistent calibration files (JSON)

New CLI commands:
   ruview-pointcloud cameras         # list available cameras
   ruview-pointcloud train           # run calibration + training
   ruview-pointcloud csi-test        # send test CSI frames
   ruview-pointcloud serve --csi     # serve with live CSI input

All tested: demo, training (10 samples, 4 reference points, 3 pairs),
CSI receiver (50 test frames), server API.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 18:01:25 -04:00
ruv 6cb0859806 Optimize pointcloud: larger splat voxels, smaller responses, faster fusion
- Gaussian splat voxel size: 0.10 → 0.15 (42% fewer splats: 1718 → 994)
- Splat response: 399 KB → 225 KB (44% smaller)
- Pipeline: 22.2ms mean (100 runs, σ=0.3ms)
- Cloud API: 1.11ms avg, 905 req/s
- Splats API: 1.39ms avg, 719 req/s
- Binary: 1.0 MB arm64 (Mac Mini), tested

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 17:53:56 -04:00
ruv 5ebd78e796 Add wifi-densepose-pointcloud: real-time dense point cloud from camera + WiFi CSI
New crate with 5 modules:
- depth: monocular depth estimation + 3D backprojection (ONNX-ready, synthetic fallback)
- pointcloud: Point3D/ColorPoint types, PLY export, Gaussian splat conversion
- fusion: WiFi occupancy volume → point cloud + multi-modal voxel fusion
- stream: HTTP + Three.js viewer server (Axum, port 9880)
- main: CLI with serve/capture/demo subcommands

Demo output: 271 WiFi points + 19,200 depth points → 4,886 fused → 1,718 Gaussian splats.
Serves interactive 3D viewer at http://localhost:9880 with Three.js orbit controls.

ADR-SYS-0021 documents the architecture for camera + WiFi CSI dense point cloud pipeline.

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-04-19 17:45:24 -04:00
1878 changed files with 11427 additions and 214900 deletions
+31 -36
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"name": "AetherArena (AA) — Official Spatial-Intelligence Benchmark",
"adr": "ADR-149",
"adrPath": "docs/adr/ADR-149-public-community-leaderboard-huggingface.md",
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"initializedDate": "2026-05-30",
"targetDate": "2026-08-31",
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"aetherArenaRepo": "does not exist yet — needs user authorization to create ruvnet/aether-arena public repo",
"hfSpace": "does not exist yet — needs HF_TOKEN and user authorization to deploy ruvnet/aether-arena HF Space",
"smokeDataset": "not committed",
"resultsLedger": "not created",
"ruviewBaseline": "PCK@20 ~2.5% self-reported, not formally entered",
"ciGate": "not added to workflow"
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"m1": {
"name": "ADR-149 Accepted + committed",
"status": "DONE",
"completedDate": "2026-05-30",
"completionCriteria": "ADR-149 file committed to docs/adr/ with status Accepted",
"notes": "Done this session. File at docs/adr/ADR-149-public-community-leaderboard-huggingface.md"
},
"m2": {
"name": "Deterministic scorer runner bin (aa_score_runner.rs)",
"status": "NOT_STARTED",
"completionCriteria": "aa_score_runner.rs compiles, runs ruview_metrics on a committed fixture, emits RuViewTier + SHA-256 proof hash, mirrors existing *_proof_runner.rs pattern; cargo test passes",
"estimatedEffort": "3-5 days",
"owner": "wifi-densepose-train crate or new aa-scorer crate"
},
"m3": {
"name": "CI harness-gate: GitHub Actions workflow",
"status": "NOT_STARTED",
"completionCriteria": "A GitHub Actions workflow runs aa_score_runner on every PR as a build gate; PR fails if scorer fails determinism check; workflow committed and green",
"estimatedEffort": "2-3 days",
"dependency": "M2 must be done first"
},
"m4": {
"name": "aether-arena repo scaffold",
"status": "NOT_STARTED",
"completionCriteria": "ruvnet/aether-arena repo created with: README (four-part framing: Public leaderboard / Private eval split / Open scorer / Signed results); aa-submission.toml manifest schema; VERIFY.md (ADR-149 §7 stranger acceptance test); neutrality/governance section (§2.8); contribution guide",
"estimatedEffort": "3-5 days",
"blockers": ["Needs user authorization to create public ruvnet/aether-arena repo on GitHub"]
},
"m5": {
"name": "Public smoke split committed + private MM-Fi held-out split prep",
"status": "NOT_STARTED",
"completionCriteria": "Public smoke split committed to aether-arena repo (stranger can score locally); private MM-Fi held-out split prepared under non-public path with CC BY-NC 4.0 attribution; Wi-Pose explicitly excluded from v0",
"estimatedEffort": "5-7 days",
"riskNotes": "MM-Fi CC BY-NC 4.0: AA must remain non-commercial and carry MM-Fi attribution; raw frames stay in private split; only derived CSI features + scores may be exposed"
},
"m6": {
"name": "HF Space (Gradio) skeleton",
"status": "BLOCKED",
"completionCriteria": "HF Space deployed at ruvnet/aether-arena with submission lifecycle (submitted->validated->quarantined->smoke_scored->full_scored->published/rejected); sandboxed scorer container wired; basic leaderboard table rendered",
"estimatedEffort": "7-10 days",
"blockers": [
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"Needs user authorization to create/deploy ruvnet/aether-arena HF Space (outward-facing public deployment)"
]
},
"m7": {
"name": "Signed append-only Parquet results ledger",
"status": "NOT_STARTED",
"completionCriteria": "HF dataset ruvnet/aether-arena-results created; append-only Parquet ledger with signed rows; determinism_gate enforced; no row can be silently edited",
"estimatedEffort": "3-5 days",
"ledgerSchema": "submitter, model_ref, category, feature_set, tier, pck20, oks, mota, vitals_bpm_err, latency_p50, latency_p95, privacy_leakage, cross_room_deg, proof_sha256, scored_at, harness_version",
"dependency": "M6 must be scaffolded first"
},
"m8": {
"name": "RuView baseline entry + public launch",
"status": "NOT_STARTED",
"completionCriteria": "RuView wifi-densepose-pretrained baseline entered (honest PCK@20 ~2.5%); ADR-149 §7 five-step stranger acceptance test passes; v0 live with Presence + Pose + Edge-latency + Determinism categories active; Privacy and Cross-room shown as gated/coming-soon",
"estimatedEffort": "3-5 days",
"dependency": "M4+M5+M6+M7 complete",
"notes": "ML SOTA improvement (PCK@20 ~72%) is a SEPARATE stretch goal blocked on ADR-079 P7-P9 camera ground truth. NOT a blocker for infra launch."
}
},
"activeMilestone": "m2",
"completedMilestones": ["m1"],
"knownRisks": [
"HF_TOKEN not confirmed present in .env — check before M6 work begins",
"ruvnet/aether-arena public repo creation is outward-facing — needs explicit user authorization",
"MM-Fi CC BY-NC 4.0: AA must stay legally non-commercial and brand-distinct from commercial RuView product; or seek MM-Fi commercial grant before any paid tier",
"Wi-Pose has research-use-only terms (no redistribution grant) — excluded from v0; revisit only if terms are clarified with authors",
"HF Space free CPU tier may be too slow for Candle/tch inference pipeline — may need ZeroGPU or self-hosted scorer on cognitum-20260110 GCloud A100/L4",
"ADR-079 camera-ground-truth (PCK@20 SOTA) is P7-P9 pending — NOT an infra blocker; must not be conflated with AA infra completion",
"Neutrality/governance risk: RuView seeded the scorer — must be demonstrably scored through the same public pipeline as any other entrant (§2.8 controls)"
],
"driftSignals": {
"timeline": "GREEN — just initialized, no timeline pressure yet",
"scope": "GREEN — scope locked at four-part structure per ADR-149 §2 decision",
"approach": "GREEN — reuse pattern (existing ruview_metrics + proof.rs) confirmed in ADR-149",
"dependency": "YELLOW — HF_TOKEN and ruvnet/aether-arena repo authorization are external blockers with unknown ETA",
"priority": "GREEN — active feature branch feat/adr-136-146-streaming-engine in progress; AA infra can proceed in parallel on its own branch"
},
"stretchGoals": {
"sotaML": "MM-Fi PCK@20 SOTA ~72% — separate ML effort blocked on ADR-079 P7-P9 camera-ground-truth data collection; NOT an infra exit criterion",
"privacyAxis": "ADR-145 §10 membership-inference attacker — activate Privacy leaderboard axis once attacker is implemented and published",
"crossRoom": "Multi-room held-out split — activate Cross-room generalization axis",
"multiOrgSteering": "Invite co-maintainers from other projects once >=N external entries land"
},
"sessionHistory": [
{
"date": "2026-05-30",
"type": "initialization",
"accomplished": [
"ADR-149 Accepted and committed to docs/adr/",
"Horizon record initialized in .claude-flow/horizons/aether-arena-aa.json",
"Memory stored in horizons namespace under key horizon-aether-arena-aa",
"Session check-in record stored in horizon-sessions namespace"
]
}
]
}
+3 -3
View File
@@ -1,11 +1,11 @@
{
"timestamp": "2026-05-25T06:07:33.385Z",
"projectRoot": "C:\\Users\\ruv\\Projects\\wifi-densepose",
"timestamp": "2026-02-28T16:13:19.193Z",
"projectRoot": "/home/user/wifi-densepose",
"structure": {
"hasPackageJson": false,
"hasTsConfig": false,
"hasClaudeConfig": true,
"hasClaudeFlow": true
},
"scannedAt": 1779689253386
"scannedAt": 1772295199193
}
+1 -1
View File
@@ -1,5 +1,5 @@
{
"timestamp": "2026-05-25T05:38:20.448Z",
"timestamp": "2026-02-28T16:05:19.091Z",
"patternsConsolidated": 0,
"memoryCleaned": 0,
"duplicatesRemoved": 0
-17
View File
@@ -1,17 +0,0 @@
{
"timestamp": "2026-05-25T05:59:05.405Z",
"mode": "local",
"memoryUsage": {
"rss": 9891840,
"heapTotal": 35598336,
"heapUsed": 26516560,
"external": 3952418,
"arrayBuffers": 55689
},
"uptime": 27163.5846658,
"optimizations": {
"cacheHitRate": 0.78,
"avgResponseTime": 45
},
"note": "Install Claude Code CLI for AI-powered optimization suggestions"
}
+9 -81
View File
@@ -1,84 +1,12 @@
{
"timestamp": "2026-05-25T06:08:29.589Z",
"mode": "headless",
"workerType": "audit",
"model": "haiku",
"durationMs": 56168,
"executionId": "audit_1779689253421_dfflmb",
"success": true,
"findings": {
"vulnerabilities": [
{
"severity": "high",
"file": ".claude/helpers/github-safe.js",
"line": 50,
"description": "Command injection vulnerability in execSync call. User-controlled arguments in `newArgs` are joined without shell escaping. An attacker can inject shell metacharacters (e.g., `; rm -rf /`) via the body content or through command/subcommand parameters. The temp file approach is safe, but the command construction `gh ${command} ${subcommand} ${newArgs.join(' ')}` allows shell injection.",
"example": "gh issue comment 123 'test`whoami`' would execute whoami"
},
{
"severity": "high",
"file": "scripts/csi-spectrogram.js",
"line": 45,
"description": "Sensitive credential exposure via command-line arguments. The `--seed-token` parameter is passed as a CLI argument, which is visible in process listings (ps aux output). This violates secure credential handling practices. Tokens should be read from environment variables or secure config files, not command-line args.",
"example": "node scripts/csi-spectrogram.js --seed-token secret_abc_123 exposes token in process list"
},
{
"severity": "medium",
"file": "scripts/apnea-detector.js",
"line": 71,
"description": "Unsafe buffer reading without comprehensive length validation. The code checks `buf.length` at 32 bytes (line 70) but then reads at fixed offsets (lines 72-76) without validating that each read stays within bounds. If a malformed packet is received, `readInt8/readUInt16LE/readUInt32LE` may read unintended data or zeros.",
"example": "A 33-byte buffer would pass the check but reading UInt32LE at offset 8 would go out of bounds"
},
{
"severity": "medium",
"file": "scripts/benchmark-rf-scan.js",
"line": 110,
"description": "Potential out-of-bounds buffer access in parseCSIFrame. While the bounds check at line 107 is present, the `nSubcarriers` value from the packet is used to calculate required buffer size without validation of the value itself. A maliciously crafted packet with extremely large nSubcarriers could cause memory issues.",
"example": "Packet with nSubcarriers=999999 would request excessive buffer allocation"
},
{
"severity": "medium",
"file": "scripts/csi-spectrogram.js",
"line": 39,
"description": "Unsafe URL construction with untrusted `seed-url` parameter. The `--seed-url` argument is used directly for HTTPS requests without validation. This could allow SSRF (Server-Side Request Forgery) or DNS rebinding attacks if an attacker controls the seed URL.",
"example": "node scripts/csi-spectrogram.js --seed-url http://internal.local:9000 could access internal services"
},
{
"severity": "low",
"file": ".claude/helpers/statusline.js",
"line": 140,
"description": "Shell command injection risk in execSync calls. Commands like `ps aux 2>/dev/null | grep -c agentic-flow` use grep patterns that could be vulnerable if any variables are interpolated (though currently hardcoded). The `execSync` with shell=true is generally risky.",
"example": "If any pattern becomes user-controlled: `grep -c ${pattern}` could inject shell metacharacters"
},
{
"severity": "low",
"file": ".claude/helpers/memory.js",
"line": 10,
"description": "Unvalidated JSON parsing. The code parses JSON from MEMORY_FILE without try-catch in the loadMemory function (catches error but doesn't validate structure). Malformed JSON or corrupted memory file could cause issues.",
"example": "Memory file with circular JSON structure could cause issues when stringifying"
},
{
"severity": "low",
"file": "scripts/device-fingerprint.js",
"line": 72,
"description": "Hardcoded device fingerprints and network configuration. While not a traditional 'hardcoded secret', the KNOWN_DEVICES array contains identifiable SSIDs and MAC addresses that could be used to correlate network infrastructure. This data should be externalized or sanitized.",
"example": "SSID 'ruv.net' and 'Cohen-Guest' could identify specific installations"
}
],
"riskScore": 42,
"recommendations": [
"**CRITICAL**: Replace `execSync` command construction in github-safe.js with proper shell escaping using `child_process.execFile()` instead of `execSync()`, or use the `shell: false` option with array arguments to avoid shell parsing entirely.",
"**CRITICAL**: Move `--seed-token` from CLI arguments to environment variable `SEED_TOKEN` in csi-spectrogram.js. Update documentation to instruct users: `export SEED_TOKEN=...` instead of passing via CLI.",
"**HIGH**: Add comprehensive buffer bounds validation in all UDP packet parsing functions (apnea-detector.js, benchmark-rf-scan.js, etc.). Validate both the buffer length AND the parsed header values before using them in calculations.",
"**HIGH**: Validate and sanitize the `--seed-url` parameter in csi-spectrogram.js. Whitelist allowed domains or restrict to localhost/internal IPs only. Add URL scheme validation (https only).",
"**MEDIUM**: Replace hardcoded device fingerprints (KNOWN_DEVICES) with externalized configuration or environment variables. Document that this data contains identifiable network information.",
"**MEDIUM**: Add input validation to `parseArgs()` results in all scripts. Validate numeric ranges, file paths, and enum values before use.",
"**LOW**: Wrap JSON.parse() calls in try-catch blocks throughout (memory.js, session.js) with explicit error handling and recovery.",
"**LOW**: Audit all uses of `require()` with dynamic paths. Ensure paths are always derived from fixed `__dirname` and not user-controlled.",
"**LOW**: Remove or sandbox the ability to pass arbitrary URLs via CLI. Consider using a configuration file (YAML/JSON) for endpoint URLs instead.",
"**INFO**: Add a pre-commit hook to detect hardcoded credentials using tools like `detect-secrets` or `truffleHog`."
]
"timestamp": "2026-03-06T13:17:27.368Z",
"mode": "local",
"checks": {
"envFilesProtected": true,
"gitIgnoreExists": true,
"noHardcodedSecrets": true
},
"rawOutputPreview": "# Security Audit Report — wifi-densepose\n\n```json\n{\n \"vulnerabilities\": [\n {\n \"severity\": \"high\",\n \"file\": \".claude/helpers/github-safe.js\",\n \"line\": 50,\n \"description\": \"Command injection vulnerability in execSync call. User-controlled arguments in `newArgs` are joined without shell escaping. An attacker can inject shell metacharacters (e.g., `; rm -rf /`) via the body content or through command/subcommand parameters. The temp file approach is safe, but the command construction `gh ${command} ${subcommand} ${newArgs.join(' ')}` allows shell injection.\",\n \"example\": \"gh issue comment 123 'test`whoami`' would execute whoami\"\n },\n {\n \"severity\": \"high\",\n \"file\": \"scripts/csi-spectrogram.js\",\n \"line\": 45,\n \"description\": \"Sensitive credential exposure via command-line arguments. The `--seed-token` parameter is passed as a CLI argument, which is visible in process listings (ps aux output). This violates secure credential handling practices. Tokens should be read from environment variables or secure config files, not command-line args.\",\n \"example\": \"node scripts/csi-spectrogram.js --seed-token secret_abc_123 exposes token in process list\"\n },\n {\n \"severity\": \"medium\",\n \"file\": \"scripts/apnea-detector.js\",\n \"line\": 71,\n \"description\": \"Unsafe buffer reading without comprehensive length validation. The code checks `buf.length` at 32 bytes (line 70) but then reads at fixed offsets (lines 72-76) without validating that each read stays within bounds. If a malformed packet is received, `readInt8/readUInt16LE/readUInt32LE` may read unintended data or zeros.\",\n \"example\": \"A 33-byte buffer would pass the check but reading UInt32LE at offset 8 would go out of bounds\"\n },\n {\n \"severity\": \"medium\",\n \"file\": \"scripts/benchmark-rf-scan.js\",\n \"line\": 110,\n \"description\": \"Potential out-of-bounds buffer access in parseCSIFrame. While the bounds check at line 107 is pres",
"rawOutputLength": 7077
"riskLevel": "low",
"recommendations": [],
"note": "Install Claude Code CLI for AI-powered security analysis"
}
-106
View File
@@ -1,106 +0,0 @@
{
"timestamp": "2026-05-25T06:11:52.519Z",
"mode": "headless",
"workerType": "testgaps",
"model": "sonnet",
"durationMs": 259124,
"executionId": "testgaps_1779689253395_srltd5",
"success": true,
"findings": {
"sections": [
{
"title": "Test Coverage Gap Analysis — wifi-densepose",
"content": "\n",
"level": 2
},
{
"title": "Coverage Summary by Crate",
"content": "\n| Crate | Tests Found | Status | Priority |\n|-------|-------------|--------|----------|\n| `wifi-densepose-core` | 26 inline | Good | Low |\n| `wifi-densepose-signal` | ~60 (validation only) | Moderate | **High** |\n| `wifi-densepose-nn` | **0** | Critical | **P1** |\n| `wifi-densepose-train` | ~60 (config/dataset) | Moderate | High |\n| `wifi-densepose-mat` | 1 integration test | Critical | **P1** |\n| `wifi-densepose-ruvector` | **0** | Critical | **P1** |\n| `wifi-densepose-sensing-server` | 4 integration tests | Moderate | High |\n| `wifi-densepose-wasm` | 3 compliance tests | Low | Low |\n\n---\n\n",
"level": 3
},
{
"title": "Tier 1: Critical Gaps",
"content": "\n",
"level": 2
},
{
"title": "1. `wifi-densepose-nn` — Zero test coverage",
"content": "\nEvery public API is untested. Place these at `v2/crates/wifi-densepose-nn/tests/inference_tests.rs`:\n\n```rust\n// v2/crates/wifi-densepose-nn/tests/inference_tests.rs\n\n#[cfg(test)]\nmod tensor_tests {\n use wifi_densepose_nn::tensor::Tensor;\n\n #[test]\n fn tensor_shape_mismatch_returns_error() {\n // data has 6 elements but shape claims 3×3=9\n let result = Tensor::new(vec![1.0f32; 6], &[3, 3]);\n assert!(result.is_err(), \"shape mismatch must be rejected\");\n }\n\n #[test]\n fn tensor_empty_data_returns_error() {\n let result = Tensor::new(vec![], &[0]);\n assert!(result.is_err());\n }\n\n #[test]\n fn tensor_nan_values_are_detected() {\n let t = Tensor::new(vec![f32::NAN, 1.0, 2.0], &[3]).unwrap();\n assert!(t.has_nan(), \"NaN in data must be detectable\");\n }\n\n #[test]\n fn tensor_inf_values_are_detected() {\n let t = Tensor::new(vec![f32::INFINITY, 1.0], &[2]).unwrap();\n assert!(t.has_inf());\n }\n}\n\n#[cfg(test)]\nmod modality_translator_tests {\n use wifi_densepose_nn::translator::ModalityTranslator;\n\n #[test]\n fn translator_rejects_wrong_subcarrier_count() {\n // standard expects 56 subcarriers; feed 57\n let csi = vec![0.0f32; 57 * 3]; // 57 subcarriers × 3 antennas\n let translator = ModalityTranslator::default();\n let result = translator.translate(&csi, 57, 3);\n assert!(result.is_err());\n }\n\n #[test]\n fn translator_handles_all_zeros() {\n let csi = vec![0.0f32; 56 * 3];\n let translator = ModalityTranslator::default();\n let result = translator.translate(&csi, 56, 3);\n // zero input should produce some output without panic\n assert!(result.is_ok());\n }\n}\n\n#[cfg(test)]\nmod inference_engine_tests {\n use wifi_densepose_nn::inference::InferenceEngine;\n\n #[test]\n fn load_nonexistent_model_returns_error() {\n let result = InferenceEngine::from_path(\"/nonexistent/model.onnx\");\n assert!(result.is_err());\n }\n\n #[test]\n fn load_corrupted_bytes_returns_error() {\n let tmp = tempfile::NamedTempFile::new().unwrap();\n std::fs::write(tmp.path(), b\"not a valid onnx file\").unwrap();\n let result = InferenceEngine::from_path(tmp.path());\n assert!(result.is_err());\n }\n\n #[test]\n fn batch_size_zero_returns_error() {\n // can't run inference on an empty batch\n // requires a valid model; skip if no model file in test fixtures\n // use #[ignore] or a feature flag for CI\n }\n}\n```\n\n---\n\n",
"level": 3
},
{
"title": "2. `wifi-densepose-mat` — Disaster response safety gaps",
"content": "\nPlace at `v2/crates/wifi-densepose-mat/tests/`:\n\n```rust\n// v2/crates/wifi-densepose-mat/tests/detection_edge_cases.rs\n\n#[cfg(test)]\nmod breathing_rate_edge_cases {\n use wifi_densepose_mat::detection::breathing::BreathingDetector;\n\n #[test]\n fn zero_bpm_is_classified_critical() {\n let detector = BreathingDetector::default();\n // flat-line signal — no breathing detected\n let signal = vec![0.0f32; 1000];\n let result = detector.classify(&signal).unwrap();\n assert_eq!(result.triage_category, TriageCategory::Immediate);\n }\n\n #[test]\n fn agonal_breathing_rate_triggers_immediate() {\n // < 6 BPM is agonal; simulate 3 BPM signal\n let detector = BreathingDetector::default();\n let signal = generate_breathing_signal(3.0, 1000, 100.0); // 3 BPM, 1000 samples @ 100 Hz\n let result = detector.classify(&signal).unwrap();\n assert_eq!(result.triage_category, TriageCategory::Immediate);\n }\n\n #[test]\n fn normal_breathing_is_classified_minor() {\n let detector = BreathingDetector::default();\n let signal = generate_breathing_signal(15.0, 1000, 100.0); // 15 BPM\n let result = detector.classify(&signal).unwrap();\n assert_eq!(result.triage_category, TriageCategory::Minor);\n }\n\n #[test]\n fn all_nan_signal_returns_error_not_panic() {\n let detector = BreathingDetector::default();\n let signal = vec![f32::NAN; 1000];\n let result = detector.classify(&signal);\n assert!(result.is_err(), \"NaN input must be caught, not panic\");\n }\n\n fn generate_breathing_signal(bpm: f32, samples: usize, sample_rate: f32) -> Vec<f32> {\n let freq = bpm / 60.0;\n (0..samples)\n .map(|i| (2.0 * std::f32::consts::PI * freq * i as f32 / sample_rate).sin())\n .collect()\n }\n}\n\n#[cfg(test)]\nmod alert_deduplication {\n use wifi_densepose_mat::alerting::{AlertDispatcher, Alert, TriageCategory};\n use std::time::Duration;\n\n #[test]\n fn duplicate_alerts_within_window_are_suppressed() {\n let mut dispatcher = AlertDispatcher::new();\n let alert = Alert::new(\"survivor-1\", TriageCategory::Immediate);\n dispatcher.dispatch(alert.clone());\n dispatcher.dispatch(alert.clone()); // same survivor, same category\n assert_eq!(dispatcher.queued_count(), 1, \"duplicate must be deduplicated\");\n }\n\n #[test]\n fn escalation_from_minor_to_immediate_is_forwarded() {\n let mut dispatcher = AlertDispatcher::new();\n dispatcher.dispatch(Alert::new(\"survivor-1\", TriageCategory::Minor));\n dispatcher.dispatch(Alert::new(\"survivor-1\", TriageCategory::Immediate));\n // escalation is not a duplicate — must pass through\n assert!(dispatcher.last_alert_for(\"survivor-1\").map(|a| a.category) == Some(TriageCategory::Immediate));\n }\n}\n\n#[cfg(test)]\nmod kalman_tracker_edge_cases {\n use wifi_densepose_mat::tracking::KalmanTracker;\n\n #[test]\n fn position_jump_does_not_corrupt_state() {\n let mut tracker = KalmanTracker::new();\n tracker.update([1.0, 1.0, 0.5]); // initial position\n tracker.update([50.0, 50.0, 0.5]); // physically impossible jump\n let pos = tracker.estimated_position();\n // should not panic; should clamp or flag anomaly\n assert!(pos.iter().all(|v| v.is_finite()));\n }\n\n #[test]\n fn lost_track_resumes_on_re_detection() {\n let mut tracker = KalmanTracker::new();\n tracker.update([1.0, 1.0, 0.5]);\n // simulate 10 missed frames\n for _ in 0..10 { tracker.predict(); }\n assert_eq!(tracker.state(), TrackState::Lost);\n tracker.update([1.1, 1.1, 0.5]); // re-detected nearby\n assert_eq!(tracker.state(), TrackState::Confirmed);\n }\n}\n```\n\n---\n\n",
"level": 3
},
{
"title": "3. `wifi-densepose-ruvector` — Zero coverage on all 5 integration modules",
"content": "\n```rust\n// v2/crates/wifi-densepose-ruvector/tests/viewpoint_tests.rs\n\n#[cfg(test)]\nmod attention_tests {\n use wifi_densepose_ruvector::viewpoint::attention::CrossViewpointAttention;\n\n #[test]\n fn attention_weights_sum_to_one() {\n let attn = CrossViewpointAttention::new(3); // 3 viewpoints\n let features = vec![[1.0f32; 64], [2.0f32; 64], [3.0f32; 64]];\n let weights = attn.compute_weights(&features);\n let sum: f32 = weights.iter().sum();\n assert!((sum - 1.0).abs() < 1e-5, \"attention must be a probability distribution\");\n }\n\n #[test]\n fn single_viewpoint_gets_full_weight() {\n let attn = CrossViewpointAttention::new(1);\n let features = vec![[1.0f32; 64]];\n let weights = attn.compute_weights(&features);\n assert!((weights[0] - 1.0).abs() < 1e-6);\n }\n\n #[test]\n fn zero_feature_vectors_do_not_produce_nan() {\n let attn = CrossViewpointAttention::new(2);\n let features = vec![[0.0f32; 64], [0.0f32; 64]];\n let weights = attn.compute_weights(&features);\n assert!(weights.iter().all(|w| w.is_finite()));\n }\n}\n\n#[cfg(test)]\nmod sketch_tests {\n use wifi_densepose_ruvector::sketch::WireSketch;\n\n #[test]\n fn round_trip_serialization() {\n let sketch = WireSketch::from_keypoints(&[[0.5f32, 0.5], [0.3, 0.7]]);\n let bytes = sketch.to_bytes();\n let restored = WireSketch::from_bytes(&bytes).unwrap();\n assert_eq!(sketch, restored);\n }\n\n #[test]\n fn deserialize_truncated_bytes_returns_error() {\n let sketch = WireSketch::from_keypoints(&[[0.5f32, 0.5]]);\n let mut bytes = sketch.to_bytes();\n bytes.truncate(bytes.len() / 2); // truncate halfway\n assert!(WireSketch::from_bytes(&bytes).is_err());\n }\n\n #[test]\n fn empty_keypoint_list_is_handled() {\n let sketch = WireSketch::from_keypoints(&[]);\n assert_eq!(sketch.keypoint_count(), 0);\n }\n}\n```\n\n---\n\n",
"level": 3
},
{
"title": "Tier 2: Signal Processing Gaps",
"content": "\n",
"level": 2
},
{
"title": "4. `wifi-densepose-signal` — RuvSense module untested",
"content": "\n```rust\n// v2/crates/wifi-densepose-signal/tests/ruvsense_tests.rs\n\n#[cfg(test)]\nmod coherence_gate_tests {\n use wifi_densepose_signal::ruvsense::coherence_gate::{CoherenceGate, GateDecision};\n\n #[test]\n fn high_coherence_signal_is_accepted() {\n let gate = CoherenceGate::new(0.7); // threshold = 0.7\n let decision = gate.evaluate(0.95);\n assert_eq!(decision, GateDecision::Accept);\n }\n\n #[test]\n fn low_coherence_signal_is_rejected() {\n let gate = CoherenceGate::new(0.7);\n let decision = gate.evaluate(0.3);\n assert_eq!(decision, GateDecision::Reject);\n }\n\n #[test]\n fn borderline_coherence_triggers_recalibrate() {\n let gate = CoherenceGate::new(0.7);\n let decision = gate.evaluate(0.68); // just below threshold\n assert_eq!(decision, GateDecision::Recalibrate);\n }\n}\n\n#[cfg(test)]\nmod phase_align_tests {\n use wifi_densepose_signal::ruvsense::phase_align::PhaseAligner;\n\n #[test]\n fn phase_at_plus_pi_does_not_wrap_incorrectly() {\n let aligner = PhaseAligner::new();\n let phases = vec![std::f32::consts::PI - 0.001, std::f32::consts::PI + 0.001];\n let aligned = aligner.align(&phases);\n // jump across ±π boundary must be handled continuously\n let diff = (aligned[1] - aligned[0]).abs();\n assert!(diff < 0.01, \"phase jump at ±π must be < 0.01 rad after alignment\");\n }\n\n #[test]\n fn single_phase_value_aligns_to_itself() {\n let aligner = PhaseAligner::new();\n let phases = vec![1.5f32];\n let aligned = aligner.align(&phases);\n assert_eq!(aligned.len(), 1);\n assert!((aligned[0] - 1.5).abs() < 1e-6);\n }\n\n #[test]\n fn empty_phase_array_returns_empty() {\n let aligner = PhaseAligner::new();\n let aligned = aligner.align(&[]);\n assert!(aligned.is_empty());\n }\n}\n\n#[cfg(test)]\nmod adversarial_detection_tests {\n use wifi_densepose_signal::ruvsense::adversarial::AdversarialDetector;\n\n #[test]\n fn physically_impossible_amplitude_is_flagged() {\n let detector = AdversarialDetector::new();\n // WiFi amplitude cannot exceed hardware saturation level\n let frame = vec![1e9f32; 56]; // absurdly large\n assert!(detector.is_suspicious(&frame));\n }\n\n #[test]\n fn normal_amplitude_range_passes() {\n let detector = AdversarialDetector::new();\n let frame = vec![0.5f32; 56]; // typical normalized value\n assert!(!detector.is_suspicious(&frame));\n }\n\n #[test]\n fn multi_link_inconsistency_is_detected() {\n // link A reports body moving right; link B reports no motion\n // physically inconsistent — flag as adversarial\n let detector = AdversarialDetector::new();\n let result = detector.check_multi_link_consistency(\n &[1.0, 2.0, 3.0], // link A\n &[0.0, 0.0, 0.0], // link B (no motion)\n );\n assert!(result.is_inconsistent());\n }\n}\n```\n\n---\n\n",
"level": 3
},
{
"title": "Tier 2: Training Pipeline Gaps",
"content": "\n",
"level": 2
},
{
"title": "5. `wifi-densepose-train` — Geometry encoder and rapid adaptation untested",
"content": "\n```rust\n// v2/crates/wifi-densepose-train/tests/test_geometry.rs\n\n#[cfg(test)]\nmod film_layer_tests {\n use wifi_densepose_train::geometry::FilmLayer;\n\n #[test]\n fn film_layer_output_shape_matches_input() {\n let film = FilmLayer::new(64, 32); // 64-dim features, 32-dim condition\n let features = vec![0.5f32; 64];\n let condition = vec![1.0f32; 32];\n let output = film.forward(&features, &condition).unwrap();\n assert_eq!(output.len(), 64, \"FiLM output must match feature dimensionality\");\n }\n\n #[test]\n fn film_layer_zero_condition_acts_as_identity() {\n let film = FilmLayer::new(64, 32);\n let features = vec![1.0f32; 64];\n let zero_condition = vec![0.0f32; 32];\n let output = film.forward(&features, &zero_condition).unwrap();\n // scale=1, shift=0 → identity; output ≈ input\n for (o, f) in output.iter().zip(features.iter()) {\n assert!((o - f).abs() < 0.1, \"zero condition should approximate identity\");\n }\n }\n}\n\n// v2/crates/wifi-densepose-train/tests/test_rapid_adapt.rs\n\n#[cfg(test)]\nmod rapid_adaptation_tests {\n use wifi_densepose_train::rapid_adapt::RapidAdapter;\n\n #[test]\n fn adapter_updates_on_single_sample() {\n let mut adapter = RapidAdapter::new(5); // 5 adaptation steps\n let csi_sample = vec![0.1f32; 56 * 3];\n let pose_label = vec![0.5f32; 17 * 2]; // 17 keypoints × (x, y)\n let result = adapter.adapt_step(&csi_sample, &pose_label);\n assert!(result.is_ok());\n }\n\n #[test]\n fn adapter_with_zero_steps_is_no_op() {\n let adapter = RapidAdapter::new(0);\n // 0 adaptation steps → weights unchanged\n let initial_weights = adapter.clone_weights();\n let _ = adapter.adapt_step(&vec![0.1f32; 168], &vec![0.5f32; 34]);\n assert_eq!(adapter.clone_weights(), initial_weights);\n }\n}\n```\n\n---\n\n",
"level": 3
},
{
"title": "Tier 3: Server Integration Gaps",
"content": "\n",
"level": 2
},
{
"title": "6. `wifi-densepose-sensing-server` — Auth and semantic analyzers",
"content": "\n```rust\n// v2/crates/wifi-densepose-sensing-server/tests/auth_tests.rs\n\n#[cfg(test)]\nmod bearer_auth_tests {\n use wifi_densepose_sensing_server::auth::{BearerValidator, TokenError};\n\n #[test]\n fn missing_authorization_header_returns_unauthorized() {\n let validator = BearerValidator::new(\"secret-token\");\n let result = validator.validate(None);\n assert!(matches!(result, Err(TokenError::Missing)));\n }\n\n #[test]\n fn wrong_token_is_rejected() {\n let validator = BearerValidator::new(\"correct-token\");\n let result = validator.validate(Some(\"Bearer wrong-token\"));\n assert!(matches!(result, Err(TokenError::Invalid)));\n }\n\n #[test]\n fn malformed_header_without_bearer_prefix_is_rejected() {\n let validator = BearerValidator::new(\"token\");\n let result = validator.validate(Some(\"token\")); // missing \"Bearer \" prefix\n assert!(matches!(result, Err(TokenError::Malformed)));\n }\n\n #[test]\n fn correct_token_is_accepted() {\n let validator = BearerValidator::new(\"correct-token\");\n let result = validator.validate(Some(\"Bearer correct-token\"));\n assert!(result.is_ok());\n }\n}\n\n// v2/crates/wifi-densepose-sensing-server/tests/semantic_tests.rs\n\n#[cfg(test)]\nmod fall_detection_tests {\n use wifi_densepose_sensing_server::semantic::fall_detector::FallDetector;\n\n #[test]\n fn no_motion_does_not_trigger_fall() {\n let mut detector = FallDetector::new();\n for _ in 0..30 { // 30 frames of stillness\n detector.update_pose(stationary_pose());\n }\n assert!(!detector.fall_detected());\n }\n\n #[test]\n fn rapid_downward_velocity_triggers_fall() {\n let mut detector = FallDetector::new();\n // simulate person going from standing (y=1.7m) to prone (y=0.3m) in 3 frames\n for (frame, y) in [(0, 1.7f32), (1, 1.0), (2, 0.3)] {\n detector.update_pose(pose_at_height(y));\n }\n assert!(detector.fall_detected());\n }\n\n #[test]\n fn sitting_down_slowly_does_not_trigger_fall() {\n let mut detector = FallDetector::new();\n // gradual height decrease over 30 frames is sitting, not falling\n for i in 0..30 {\n let y = 1.7f32 - (i as f32 * 0.04); // ~1.2m drop over 30 frames\n detector.update_pose(pose_at_height(y));\n }\n assert!(!detector.fall_detected());\n }\n}\n```\n\n---\n\n",
"level": 3
},
{
"title": "Cross-Cutting Gap Summary",
"content": "| Gap Category | Severity | Affects | Recommended Action |\n|---|---|---|---|\n| `wifi-densepose-nn` has 0 tests | **Critical** | Inference pipeline | Add `tests/inference_tests.rs` per skeleton above |\n| `wifi-densepose-ruvector` has 0 tests | **Critical** | Viewpoint fusion, sketches | Add `tests/viewpoint_tests.rs` |\n| MAT disaster response missing edge cases | **Critical** | 0 BPM, agonal breathing, dedup | Add `tests/detection_edge_cases.rs` |\n| Signal RuvSense 28 modules untested | High | Core sensing logic | Add `tests/ruvsense_tests.rs` |\n| NN error paths (bad model files, OOM) | High | Production reliability | Add error path tests to nn |\n| Train geometry + rapid adapt = 0 tests | High | Domain adaptation | Add `tests/test_geometry.rs` |\n| Server auth token validation | High | Security boundary | Add `tests/auth_tests.rs` |\n| NaN/Inf propagation in f32 pipelines | High | All numeric crates | Add boundary tests per module |\n| Concurrent state under Arc<Mutex> | Medium | sensing-server, mat | Add contention tests |\n\nThe highest-ROI starting point is `wifi-densepose-nn` and `wifi-densepose-mat` — the nn crate has zero tests on the core inference pipeline, and mat covers life-safety scenarios where classification errors have real consequences.",
"level": 2
}
],
"codeBlocks": [
{
"language": "rust",
"code": "// v2/crates/wifi-densepose-nn/tests/inference_tests.rs\n\n#[cfg(test)]\nmod tensor_tests {\n use wifi_densepose_nn::tensor::Tensor;\n\n #[test]\n fn tensor_shape_mismatch_returns_error() {\n // data has 6 elements but shape claims 3×3=9\n let result = Tensor::new(vec![1.0f32; 6], &[3, 3]);\n assert!(result.is_err(), \"shape mismatch must be rejected\");\n }\n\n #[test]\n fn tensor_empty_data_returns_error() {\n let result = Tensor::new(vec![], &[0]);\n assert!(result.is_err());\n }\n\n #[test]\n fn tensor_nan_values_are_detected() {\n let t = Tensor::new(vec![f32::NAN, 1.0, 2.0], &[3]).unwrap();\n assert!(t.has_nan(), \"NaN in data must be detectable\");\n }\n\n #[test]\n fn tensor_inf_values_are_detected() {\n let t = Tensor::new(vec![f32::INFINITY, 1.0], &[2]).unwrap();\n assert!(t.has_inf());\n }\n}\n\n#[cfg(test)]\nmod modality_translator_tests {\n use wifi_densepose_nn::translator::ModalityTranslator;\n\n #[test]\n fn translator_rejects_wrong_subcarrier_count() {\n // standard expects 56 subcarriers; feed 57\n let csi = vec![0.0f32; 57 * 3]; // 57 subcarriers × 3 antennas\n let translator = ModalityTranslator::default();\n let result = translator.translate(&csi, 57, 3);\n assert!(result.is_err());\n }\n\n #[test]\n fn translator_handles_all_zeros() {\n let csi = vec![0.0f32; 56 * 3];\n let translator = ModalityTranslator::default();\n let result = translator.translate(&csi, 56, 3);\n // zero input should produce some output without panic\n assert!(result.is_ok());\n }\n}\n\n#[cfg(test)]\nmod inference_engine_tests {\n use wifi_densepose_nn::inference::InferenceEngine;\n\n #[test]\n fn load_nonexistent_model_returns_error() {\n let result = InferenceEngine::from_path(\"/nonexistent/model.onnx\");\n assert!(result.is_err());\n }\n\n #[test]\n fn load_corrupted_bytes_returns_error() {\n let tmp = tempfile::NamedTempFile::new().unwrap();\n std::fs::write(tmp.path(), b\"not a valid onnx file\").unwrap();\n let result = InferenceEngine::from_path(tmp.path());\n assert!(result.is_err());\n }\n\n #[test]\n fn batch_size_zero_returns_error() {\n // can't run inference on an empty batch\n // requires a valid model; skip if no model file in test fixtures\n // use #[ignore] or a feature flag for CI\n }\n}"
},
{
"language": "rust",
"code": "// v2/crates/wifi-densepose-mat/tests/detection_edge_cases.rs\n\n#[cfg(test)]\nmod breathing_rate_edge_cases {\n use wifi_densepose_mat::detection::breathing::BreathingDetector;\n\n #[test]\n fn zero_bpm_is_classified_critical() {\n let detector = BreathingDetector::default();\n // flat-line signal — no breathing detected\n let signal = vec![0.0f32; 1000];\n let result = detector.classify(&signal).unwrap();\n assert_eq!(result.triage_category, TriageCategory::Immediate);\n }\n\n #[test]\n fn agonal_breathing_rate_triggers_immediate() {\n // < 6 BPM is agonal; simulate 3 BPM signal\n let detector = BreathingDetector::default();\n let signal = generate_breathing_signal(3.0, 1000, 100.0); // 3 BPM, 1000 samples @ 100 Hz\n let result = detector.classify(&signal).unwrap();\n assert_eq!(result.triage_category, TriageCategory::Immediate);\n }\n\n #[test]\n fn normal_breathing_is_classified_minor() {\n let detector = BreathingDetector::default();\n let signal = generate_breathing_signal(15.0, 1000, 100.0); // 15 BPM\n let result = detector.classify(&signal).unwrap();\n assert_eq!(result.triage_category, TriageCategory::Minor);\n }\n\n #[test]\n fn all_nan_signal_returns_error_not_panic() {\n let detector = BreathingDetector::default();\n let signal = vec![f32::NAN; 1000];\n let result = detector.classify(&signal);\n assert!(result.is_err(), \"NaN input must be caught, not panic\");\n }\n\n fn generate_breathing_signal(bpm: f32, samples: usize, sample_rate: f32) -> Vec<f32> {\n let freq = bpm / 60.0;\n (0..samples)\n .map(|i| (2.0 * std::f32::consts::PI * freq * i as f32 / sample_rate).sin())\n .collect()\n }\n}\n\n#[cfg(test)]\nmod alert_deduplication {\n use wifi_densepose_mat::alerting::{AlertDispatcher, Alert, TriageCategory};\n use std::time::Duration;\n\n #[test]\n fn duplicate_alerts_within_window_are_suppressed() {\n let mut dispatcher = AlertDispatcher::new();\n let alert = Alert::new(\"survivor-1\", TriageCategory::Immediate);\n dispatcher.dispatch(alert.clone());\n dispatcher.dispatch(alert.clone()); // same survivor, same category\n assert_eq!(dispatcher.queued_count(), 1, \"duplicate must be deduplicated\");\n }\n\n #[test]\n fn escalation_from_minor_to_immediate_is_forwarded() {\n let mut dispatcher = AlertDispatcher::new();\n dispatcher.dispatch(Alert::new(\"survivor-1\", TriageCategory::Minor));\n dispatcher.dispatch(Alert::new(\"survivor-1\", TriageCategory::Immediate));\n // escalation is not a duplicate — must pass through\n assert!(dispatcher.last_alert_for(\"survivor-1\").map(|a| a.category) == Some(TriageCategory::Immediate));\n }\n}\n\n#[cfg(test)]\nmod kalman_tracker_edge_cases {\n use wifi_densepose_mat::tracking::KalmanTracker;\n\n #[test]\n fn position_jump_does_not_corrupt_state() {\n let mut tracker = KalmanTracker::new();\n tracker.update([1.0, 1.0, 0.5]); // initial position\n tracker.update([50.0, 50.0, 0.5]); // physically impossible jump\n let pos = tracker.estimated_position();\n // should not panic; should clamp or flag anomaly\n assert!(pos.iter().all(|v| v.is_finite()));\n }\n\n #[test]\n fn lost_track_resumes_on_re_detection() {\n let mut tracker = KalmanTracker::new();\n tracker.update([1.0, 1.0, 0.5]);\n // simulate 10 missed frames\n for _ in 0..10 { tracker.predict(); }\n assert_eq!(tracker.state(), TrackState::Lost);\n tracker.update([1.1, 1.1, 0.5]); // re-detected nearby\n assert_eq!(tracker.state(), TrackState::Confirmed);\n }\n}"
},
{
"language": "rust",
"code": "// v2/crates/wifi-densepose-ruvector/tests/viewpoint_tests.rs\n\n#[cfg(test)]\nmod attention_tests {\n use wifi_densepose_ruvector::viewpoint::attention::CrossViewpointAttention;\n\n #[test]\n fn attention_weights_sum_to_one() {\n let attn = CrossViewpointAttention::new(3); // 3 viewpoints\n let features = vec![[1.0f32; 64], [2.0f32; 64], [3.0f32; 64]];\n let weights = attn.compute_weights(&features);\n let sum: f32 = weights.iter().sum();\n assert!((sum - 1.0).abs() < 1e-5, \"attention must be a probability distribution\");\n }\n\n #[test]\n fn single_viewpoint_gets_full_weight() {\n let attn = CrossViewpointAttention::new(1);\n let features = vec![[1.0f32; 64]];\n let weights = attn.compute_weights(&features);\n assert!((weights[0] - 1.0).abs() < 1e-6);\n }\n\n #[test]\n fn zero_feature_vectors_do_not_produce_nan() {\n let attn = CrossViewpointAttention::new(2);\n let features = vec![[0.0f32; 64], [0.0f32; 64]];\n let weights = attn.compute_weights(&features);\n assert!(weights.iter().all(|w| w.is_finite()));\n }\n}\n\n#[cfg(test)]\nmod sketch_tests {\n use wifi_densepose_ruvector::sketch::WireSketch;\n\n #[test]\n fn round_trip_serialization() {\n let sketch = WireSketch::from_keypoints(&[[0.5f32, 0.5], [0.3, 0.7]]);\n let bytes = sketch.to_bytes();\n let restored = WireSketch::from_bytes(&bytes).unwrap();\n assert_eq!(sketch, restored);\n }\n\n #[test]\n fn deserialize_truncated_bytes_returns_error() {\n let sketch = WireSketch::from_keypoints(&[[0.5f32, 0.5]]);\n let mut bytes = sketch.to_bytes();\n bytes.truncate(bytes.len() / 2); // truncate halfway\n assert!(WireSketch::from_bytes(&bytes).is_err());\n }\n\n #[test]\n fn empty_keypoint_list_is_handled() {\n let sketch = WireSketch::from_keypoints(&[]);\n assert_eq!(sketch.keypoint_count(), 0);\n }\n}"
},
{
"language": "rust",
"code": "// v2/crates/wifi-densepose-signal/tests/ruvsense_tests.rs\n\n#[cfg(test)]\nmod coherence_gate_tests {\n use wifi_densepose_signal::ruvsense::coherence_gate::{CoherenceGate, GateDecision};\n\n #[test]\n fn high_coherence_signal_is_accepted() {\n let gate = CoherenceGate::new(0.7); // threshold = 0.7\n let decision = gate.evaluate(0.95);\n assert_eq!(decision, GateDecision::Accept);\n }\n\n #[test]\n fn low_coherence_signal_is_rejected() {\n let gate = CoherenceGate::new(0.7);\n let decision = gate.evaluate(0.3);\n assert_eq!(decision, GateDecision::Reject);\n }\n\n #[test]\n fn borderline_coherence_triggers_recalibrate() {\n let gate = CoherenceGate::new(0.7);\n let decision = gate.evaluate(0.68); // just below threshold\n assert_eq!(decision, GateDecision::Recalibrate);\n }\n}\n\n#[cfg(test)]\nmod phase_align_tests {\n use wifi_densepose_signal::ruvsense::phase_align::PhaseAligner;\n\n #[test]\n fn phase_at_plus_pi_does_not_wrap_incorrectly() {\n let aligner = PhaseAligner::new();\n let phases = vec![std::f32::consts::PI - 0.001, std::f32::consts::PI + 0.001];\n let aligned = aligner.align(&phases);\n // jump across ±π boundary must be handled continuously\n let diff = (aligned[1] - aligned[0]).abs();\n assert!(diff < 0.01, \"phase jump at ±π must be < 0.01 rad after alignment\");\n }\n\n #[test]\n fn single_phase_value_aligns_to_itself() {\n let aligner = PhaseAligner::new();\n let phases = vec![1.5f32];\n let aligned = aligner.align(&phases);\n assert_eq!(aligned.len(), 1);\n assert!((aligned[0] - 1.5).abs() < 1e-6);\n }\n\n #[test]\n fn empty_phase_array_returns_empty() {\n let aligner = PhaseAligner::new();\n let aligned = aligner.align(&[]);\n assert!(aligned.is_empty());\n }\n}\n\n#[cfg(test)]\nmod adversarial_detection_tests {\n use wifi_densepose_signal::ruvsense::adversarial::AdversarialDetector;\n\n #[test]\n fn physically_impossible_amplitude_is_flagged() {\n let detector = AdversarialDetector::new();\n // WiFi amplitude cannot exceed hardware saturation level\n let frame = vec![1e9f32; 56]; // absurdly large\n assert!(detector.is_suspicious(&frame));\n }\n\n #[test]\n fn normal_amplitude_range_passes() {\n let detector = AdversarialDetector::new();\n let frame = vec![0.5f32; 56]; // typical normalized value\n assert!(!detector.is_suspicious(&frame));\n }\n\n #[test]\n fn multi_link_inconsistency_is_detected() {\n // link A reports body moving right; link B reports no motion\n // physically inconsistent — flag as adversarial\n let detector = AdversarialDetector::new();\n let result = detector.check_multi_link_consistency(\n &[1.0, 2.0, 3.0], // link A\n &[0.0, 0.0, 0.0], // link B (no motion)\n );\n assert!(result.is_inconsistent());\n }\n}"
},
{
"language": "rust",
"code": "// v2/crates/wifi-densepose-train/tests/test_geometry.rs\n\n#[cfg(test)]\nmod film_layer_tests {\n use wifi_densepose_train::geometry::FilmLayer;\n\n #[test]\n fn film_layer_output_shape_matches_input() {\n let film = FilmLayer::new(64, 32); // 64-dim features, 32-dim condition\n let features = vec![0.5f32; 64];\n let condition = vec![1.0f32; 32];\n let output = film.forward(&features, &condition).unwrap();\n assert_eq!(output.len(), 64, \"FiLM output must match feature dimensionality\");\n }\n\n #[test]\n fn film_layer_zero_condition_acts_as_identity() {\n let film = FilmLayer::new(64, 32);\n let features = vec![1.0f32; 64];\n let zero_condition = vec![0.0f32; 32];\n let output = film.forward(&features, &zero_condition).unwrap();\n // scale=1, shift=0 → identity; output ≈ input\n for (o, f) in output.iter().zip(features.iter()) {\n assert!((o - f).abs() < 0.1, \"zero condition should approximate identity\");\n }\n }\n}\n\n// v2/crates/wifi-densepose-train/tests/test_rapid_adapt.rs\n\n#[cfg(test)]\nmod rapid_adaptation_tests {\n use wifi_densepose_train::rapid_adapt::RapidAdapter;\n\n #[test]\n fn adapter_updates_on_single_sample() {\n let mut adapter = RapidAdapter::new(5); // 5 adaptation steps\n let csi_sample = vec![0.1f32; 56 * 3];\n let pose_label = vec![0.5f32; 17 * 2]; // 17 keypoints × (x, y)\n let result = adapter.adapt_step(&csi_sample, &pose_label);\n assert!(result.is_ok());\n }\n\n #[test]\n fn adapter_with_zero_steps_is_no_op() {\n let adapter = RapidAdapter::new(0);\n // 0 adaptation steps → weights unchanged\n let initial_weights = adapter.clone_weights();\n let _ = adapter.adapt_step(&vec![0.1f32; 168], &vec![0.5f32; 34]);\n assert_eq!(adapter.clone_weights(), initial_weights);\n }\n}"
},
{
"language": "rust",
"code": "// v2/crates/wifi-densepose-sensing-server/tests/auth_tests.rs\n\n#[cfg(test)]\nmod bearer_auth_tests {\n use wifi_densepose_sensing_server::auth::{BearerValidator, TokenError};\n\n #[test]\n fn missing_authorization_header_returns_unauthorized() {\n let validator = BearerValidator::new(\"secret-token\");\n let result = validator.validate(None);\n assert!(matches!(result, Err(TokenError::Missing)));\n }\n\n #[test]\n fn wrong_token_is_rejected() {\n let validator = BearerValidator::new(\"correct-token\");\n let result = validator.validate(Some(\"Bearer wrong-token\"));\n assert!(matches!(result, Err(TokenError::Invalid)));\n }\n\n #[test]\n fn malformed_header_without_bearer_prefix_is_rejected() {\n let validator = BearerValidator::new(\"token\");\n let result = validator.validate(Some(\"token\")); // missing \"Bearer \" prefix\n assert!(matches!(result, Err(TokenError::Malformed)));\n }\n\n #[test]\n fn correct_token_is_accepted() {\n let validator = BearerValidator::new(\"correct-token\");\n let result = validator.validate(Some(\"Bearer correct-token\"));\n assert!(result.is_ok());\n }\n}\n\n// v2/crates/wifi-densepose-sensing-server/tests/semantic_tests.rs\n\n#[cfg(test)]\nmod fall_detection_tests {\n use wifi_densepose_sensing_server::semantic::fall_detector::FallDetector;\n\n #[test]\n fn no_motion_does_not_trigger_fall() {\n let mut detector = FallDetector::new();\n for _ in 0..30 { // 30 frames of stillness\n detector.update_pose(stationary_pose());\n }\n assert!(!detector.fall_detected());\n }\n\n #[test]\n fn rapid_downward_velocity_triggers_fall() {\n let mut detector = FallDetector::new();\n // simulate person going from standing (y=1.7m) to prone (y=0.3m) in 3 frames\n for (frame, y) in [(0, 1.7f32), (1, 1.0), (2, 0.3)] {\n detector.update_pose(pose_at_height(y));\n }\n assert!(detector.fall_detected());\n }\n\n #[test]\n fn sitting_down_slowly_does_not_trigger_fall() {\n let mut detector = FallDetector::new();\n // gradual height decrease over 30 frames is sitting, not falling\n for i in 0..30 {\n let y = 1.7f32 - (i as f32 * 0.04); // ~1.2m drop over 30 frames\n detector.update_pose(pose_at_height(y));\n }\n assert!(!detector.fall_detected());\n }\n}"
}
]
},
"rawOutputPreview": "The exploration is complete. Here's the full coverage analysis with test skeletons for each critical gap.\n\n---\n\n## Test Coverage Gap Analysis — wifi-densepose\n\n### Coverage Summary by Crate\n\n| Crate | Tests Found | Status | Priority |\n|-------|-------------|--------|----------|\n| `wifi-densepose-core` | 26 inline | Good | Low |\n| `wifi-densepose-signal` | ~60 (validation only) | Moderate | **High** |\n| `wifi-densepose-nn` | **0** | Critical | **P1** |\n| `wifi-densepose-train` | ~60 (config/dataset) | Moderate | High |\n| `wifi-densepose-mat` | 1 integration test | Critical | **P1** |\n| `wifi-densepose-ruvector` | **0** | Critical | **P1** |\n| `wifi-densepose-sensing-server` | 4 integration tests | Moderate | High |\n| `wifi-densepose-wasm` | 3 compliance tests | Low | Low |\n\n---\n\n## Tier 1: Critical Gaps\n\n### 1. `wifi-densepose-nn` — Zero test coverage\n\nEvery public API is untested. Place these at `v2/crates/wifi-densepose-nn/tests/inference_tests.rs`:\n\n```rust\n// v2/crates/wifi-densepose-nn/tests/inference_tests.rs\n\n#[cfg(test)]\nmod tensor_tests {\n use wifi_densepose_nn::tensor::Tensor;\n\n #[test]\n fn tensor_shape_mismatch_returns_error() {\n // data has 6 elements but shape claims 3×3=9\n let result = Tensor::new(vec![1.0f32; 6], &[3, 3]);\n assert!(result.is_err(), \"shape mismatch must be rejected\");\n }\n\n #[test]\n fn tensor_empty_data_returns_error() {\n let result = Tensor::new(vec![], &[0]);\n assert!(result.is_err());\n }\n\n #[test]\n fn tensor_nan_values_are_detected() {\n let t = Tensor::new(vec![f32::NAN, 1.0, 2.0], &[3]).unwrap();\n assert!(t.has_nan(), \"NaN in data must be detectable\");\n }\n\n #[test]\n fn tensor_inf_values_are_detected() {\n let t = Tensor::new(vec![f32::INFINITY, 1.0], &[2]).unwrap();\n assert!(t.has_inf());\n }\n}\n\n#[cfg(test)]\nmod modality_translator_tests {\n use wifi_densepose_nn::translator::ModalityTranslator;\n\n #[test]\n fn translator_rejects",
"rawOutputLength": 18269
}
-15
View File
@@ -1,15 +0,0 @@
{
"name": "ruview",
"description": "RuView Marketplace: Claude Code + Codex plugins for WiFi sensing — configuration, applications, model training, and onboarding, from practical to advanced",
"owner": {
"name": "ruvnet",
"url": "https://github.com/ruvnet/RuView"
},
"plugins": [
{
"name": "ruview",
"source": "./plugins/ruview",
"description": "End-to-end RuView toolkit: getting started, ESP32 hardware setup, configuration, sensing applications (presence / vitals / pose / sleep / MAT), camera-free + camera-supervised model training, advanced multistatic sensing, CLI / API / WASM, mmWave radar, and witness verification"
}
]
}
-1
View File
@@ -1 +0,0 @@
{"sessionId":"d80c93c2-51b7-42e8-a0fc-dc47cff1200f","pid":45748,"acquiredAt":1779668018388}
+4 -1
View File
@@ -126,7 +126,10 @@
"Bash(node .claude/*)",
"mcp__claude-flow__:*"
],
"deny": []
"deny": [
"Read(./.env)",
"Read(./.env.*)"
]
},
"attribution": {
"commit": "Co-Authored-By: claude-flow <ruv@ruv.net>",
-58
View File
@@ -1,58 +0,0 @@
version: 2
updates:
# Keep all third-party GitHub Actions on verified, pinned commit SHAs.
# Pairs with the SHA pinning in security-scan.yml and ci.yml so that
# future bumps stay automated and reviewable rather than drifting back
# to mutable @master / @main refs. See issue #442.
- package-ecosystem: github-actions
directory: /
schedule:
interval: weekly
open-pull-requests-limit: 5
labels:
- dependencies
- github-actions
# Mobile app npm deps. Includes the @xmldom/xmldom, node-forge, and
# picomatch advisories from #442 plus axios and any future surface.
- package-ecosystem: npm
directory: /ui/mobile
schedule:
interval: weekly
open-pull-requests-limit: 10
labels:
- dependencies
- mobile
# Desktop UI npm deps. Direct vite devDep currently has a HIGH advisory
# (dev-server-only path traversal); track future bumps automatically.
- package-ecosystem: npm
directory: /v2/crates/wifi-densepose-desktop/ui
schedule:
interval: weekly
open-pull-requests-limit: 5
labels:
- dependencies
- desktop
# Python deps used by v1/ and the FastAPI service. requirements.txt is
# only loosely pinned; let Dependabot surface upstream CVE bumps.
- package-ecosystem: pip
directory: /
schedule:
interval: weekly
open-pull-requests-limit: 10
labels:
- dependencies
- python
# Rust workspace (15+ crates). cargo audit is not currently wired into
# any workflow, so Dependabot is the primary automated bump path.
- package-ecosystem: cargo
directory: /v2
schedule:
interval: weekly
open-pull-requests-limit: 10
labels:
- dependencies
- rust
@@ -1,94 +0,0 @@
name: AetherArena harness gate (ADR-149)
# Runs the AetherArena scoring harness as a PR build gate. Every PR that touches
# the scorer, the metrics, or the benchmark scaffold must keep the deterministic
# score hash stable (ADR-149 §2.5 determinism_gate). If the scoring maths changes,
# the hash moves and this gate fails until `expected_score.sha256` is regenerated
# and reviewed — so scorer drift can never land silently.
#
# This is the "a PR that runs the harness as part of the build process" requirement.
on:
pull_request:
paths:
- 'v2/crates/wifi-densepose-train/src/ruview_metrics.rs'
- 'v2/crates/wifi-densepose-train/src/ablation.rs'
- 'v2/crates/wifi-densepose-train/src/bin/aa_score_runner.rs'
- 'aether-arena/**'
- '.github/workflows/aether-arena-harness.yml'
push:
branches: ['feat/adr-149-aether-arena']
workflow_dispatch:
permissions:
contents: read
pull-requests: write
jobs:
harness-gate:
name: Run AA scorer harness (determinism gate)
runs-on: ubuntu-latest
defaults:
run:
working-directory: v2
steps:
- uses: actions/checkout@v4
- name: Install Rust toolchain
run: rustup show && rustc --version
- name: Cache cargo
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: aa-harness-${{ runner.os }}-${{ hashFiles('v2/Cargo.lock') }}
# 1. Build the pure-Rust scorer (no torch / no GPU → fast PR gate).
- name: Build AA score runner
run: cargo build -p wifi-densepose-train --bin aa_score_runner --no-default-features
# 2. Determinism gate: the committed expected hash must still match. A
# non-zero exit here fails the PR.
- name: Run determinism gate
run: cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features
# 3. Repeatability analysis (witness chain): the harness must produce one
# identical proof hash across many runs — any nondeterminism fails here.
- name: Repeatability analysis (16 runs)
run: cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --repeat 16
# 4. Real-scoring smoke: score a sample prediction against the public smoke
# split, exercising the actual model-scoring path (not just the fixture).
- name: Real-scoring smoke test
run: |
cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- \
--split ../aether-arena/fixtures/smoke_split.json \
--pred ../aether-arena/fixtures/smoke_pred.json --json
# 5. Witness ledger chain integrity: the append-only results ledger must
# verify (every prev_hash link + row_hash intact = no silent edits).
- name: Verify witness ledger chain
working-directory: aether-arena/ledger
run: python3 ledger_tools.py verify
# 6. Emit the witness row + repeatability into the PR run summary.
- name: Witness row → job summary
if: always()
run: |
ROW=$(cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --json)
REP=$(cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --repeat 16)
{
echo "## AetherArena harness gate (witness chain)"
echo ""
echo "Deterministic witness (ADR-149 §2.2 / proof + repeatability):"
echo '```json'
echo "$ROW"
echo "$REP"
echo '```'
echo ""
echo "If the determinism gate failed, the scoring maths changed: regenerate with"
echo '`cargo run -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --generate-hash > aether-arena/fixtures/expected_score.sha256` and review the diff.'
} >> "$GITHUB_STEP_SUMMARY"
@@ -1,99 +0,0 @@
name: BFLD MQTT Integration
# Runs the env-gated mosquitto integration tests from iters 24 + 29 of the
# BFLD rollout (ADR-118 / ADR-122 §2.2). Spins up an eclipse-mosquitto:2
# service container, exports BFLD_MQTT_BROKER, runs `cargo test --features
# mqtt`. Local developers can reproduce with:
#
# scoop install mosquitto # Windows
# # or: docker run -p 1883:1883 eclipse-mosquitto:2
# BFLD_MQTT_BROKER=tcp://localhost:1883 \
# cargo test -p wifi-densepose-bfld --features mqtt
on:
push:
branches:
- main
- 'feat/adr-118-*'
- 'feat/bfld-*'
paths:
- 'v2/crates/wifi-densepose-bfld/**'
- '.github/workflows/bfld-mqtt-integration.yml'
pull_request:
paths:
- 'v2/crates/wifi-densepose-bfld/**'
- '.github/workflows/bfld-mqtt-integration.yml'
workflow_dispatch:
jobs:
mqtt-live-broker:
name: cargo test --features mqtt (live mosquitto)
runs-on: ubuntu-latest
timeout-minutes: 15
services:
mosquitto:
image: eclipse-mosquitto:2
ports:
- 1883:1883
# Allow anonymous connections — local-only CI broker, no exposure
# to the public internet, never touches production credentials.
options: >-
--health-cmd "mosquitto_pub -h localhost -t healthcheck -m ping || exit 1"
--health-interval 5s
--health-timeout 3s
--health-retries 10
env:
BFLD_MQTT_BROKER: tcp://localhost:1883
CARGO_TERM_COLOR: always
CARGO_INCREMENTAL: 0
RUSTFLAGS: -D warnings
steps:
- name: Checkout
uses: actions/checkout@v4
- name: Install Rust toolchain
uses: dtolnay/rust-toolchain@stable
with:
components: clippy
- name: Cache cargo registry + target
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: bfld-mqtt-${{ runner.os }}-${{ hashFiles('v2/Cargo.lock') }}
- name: Wait for mosquitto to be ready
run: |
for i in {1..20}; do
if nc -z localhost 1883; then
echo "mosquitto reachable on port 1883 (attempt $i)"
exit 0
fi
echo "waiting for mosquitto ($i/20)..."
sleep 1
done
echo "mosquitto never became reachable" >&2
exit 1
- name: cargo test --no-default-features (baseline regression)
working-directory: v2
run: cargo test -p wifi-densepose-bfld --no-default-features
- name: cargo test (default features)
working-directory: v2
run: cargo test -p wifi-densepose-bfld
- name: cargo test --features mqtt (incl. live mosquitto roundtrip)
working-directory: v2
run: cargo test -p wifi-densepose-bfld --features mqtt
- name: cargo clippy --features mqtt (lint gate)
working-directory: v2
run: cargo clippy -p wifi-densepose-bfld --features mqtt --all-targets -- -D warnings
continue-on-error: true
+37 -164
View File
@@ -15,50 +15,38 @@ env:
jobs:
# Code Quality and Security Checks
# The Python codebase moved to `archive/v1/` when the runtime was rewritten in
# Rust under `v2/`. The lint/format/type/scan checks below still run against
# the archive for hygiene, but with `continue-on-error: true` everywhere — the
# archive is frozen reference code, not active development, so a stale lint
# rule shouldn't gate PRs to the Rust workspace.
code-quality:
name: Code Quality & Security
runs-on: ubuntu-latest
continue-on-error: true
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
continue-on-error: true
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
cache: 'pip'
- name: Install dependencies
continue-on-error: true
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
pip install black flake8 mypy bandit safety
- name: Code formatting check (Black)
continue-on-error: true
run: black --check --diff archive/v1/src archive/v1/tests
run: black --check --diff src/ tests/
- name: Linting (Flake8)
continue-on-error: true
run: flake8 archive/v1/src archive/v1/tests --max-line-length=88 --extend-ignore=E203,W503
run: flake8 src/ tests/ --max-line-length=88 --extend-ignore=E203,W503
- name: Type checking (MyPy)
continue-on-error: true
run: mypy archive/v1/src --ignore-missing-imports
run: mypy src/ --ignore-missing-imports
- name: Security scan (Bandit)
run: bandit -r archive/v1/src -f json -o bandit-report.json
run: bandit -r src/ -f json -o bandit-report.json
continue-on-error: true
- name: Dependency vulnerability scan (Safety)
@@ -66,7 +54,6 @@ jobs:
continue-on-error: true
- name: Upload security reports
continue-on-error: true
uses: actions/upload-artifact@v4
if: always()
with:
@@ -83,84 +70,29 @@ jobs:
- name: Checkout code
uses: actions/checkout@v4
# `wifi-densepose-desktop` is a Tauri v2 app — `glib-sys`, `gtk-sys`,
# `webkit2gtk-sys`, etc. need the Linux dev libraries via pkg-config or the
# workspace test fails at the build step before any test runs (every recent
# main CI run has been red on this for exactly this reason). Install the
# standard Tauri-on-Ubuntu set.
- name: Install Tauri / GTK / serial system dev libraries
run: |
sudo apt-get update
sudo apt-get install -y --no-install-recommends \
libglib2.0-dev \
libgtk-3-dev \
libsoup-3.0-dev \
libjavascriptcoregtk-4.1-dev \
libwebkit2gtk-4.1-dev \
libayatana-appindicator3-dev \
librsvg2-dev \
libxdo-dev \
libudev-dev \
libdbus-1-dev \
libssl-dev \
pkg-config
- name: Install Rust toolchain
uses: dtolnay/rust-toolchain@stable
# Swatinem/rust-cache replaces a naive `actions/cache` of the whole
# `v2/target`. That manual cache of a 38-crate target dir (multi-GB) was an
# intermittent failure source — several CI runs this cycle died at the
# cache/setup step (after toolchain install, before "Run Rust tests"),
# needing a rerun. rust-cache is purpose-built for Rust: it caches the
# registry + git + a pruned target, evicts stale deps, and restores far more
# reliably (and faster) on large workspaces. `workspaces: v2` points it at
# the v2/ cargo workspace (keys on v2/Cargo.lock, caches v2/target).
- name: Cache cargo (Swatinem/rust-cache)
uses: Swatinem/rust-cache@v2
- name: Cache cargo
uses: actions/cache@v4
with:
workspaces: v2
path: |
~/.cargo/registry
~/.cargo/git
rust-port/wifi-densepose-rs/target
key: ${{ runner.os }}-cargo-${{ hashFiles('rust-port/wifi-densepose-rs/Cargo.lock') }}
restore-keys: |
${{ runner.os }}-cargo-
- name: Run Rust tests
working-directory: v2
working-directory: rust-port/wifi-densepose-rs
run: cargo test --workspace --no-default-features
- name: Run ADR-147 worldmodel tests
working-directory: v2
run: cargo test -p wifi-densepose-worldmodel --no-default-features
# ADR-134 CIR tests are behind the `cir` feature so the bench dependency
# (Criterion) only pulls when actually exercised. Run them as a separate
# step so a CIR-only regression is unambiguously attributable.
- name: Run ADR-134 CIR tests
working-directory: v2
run: cargo test -p wifi-densepose-signal --no-default-features --features cir --tests
# ADR-134 + ADR-028 witness guard. The CIR proof runner produces a
# bit-deterministic SHA-256 over CirEstimator output on the synthetic
# reference signal. Any algorithmic regression — changes to ISTA
# convergence, sensing matrix construction, soft-thresholding, or input
# padding — breaks the hash and fails the build. To regenerate after an
# *intentional* change:
# cd v2 && cargo run -p wifi-densepose-signal --bin cir_proof_runner \
# --release --no-default-features -- --generate-hash \
# > ../archive/v1/data/proof/expected_cir_features.sha256
- name: ADR-134 CIR witness proof (determinism guard)
run: bash scripts/verify-cir-proof.sh
- name: ADR-135 calibration witness proof (determinism guard)
run: bash scripts/verify-calibration-proof.sh
# Unit and Integration Tests
# Python pytest matrix — runs against the archived v1 Python tree.
# `continue-on-error: true` for the same reason as code-quality above:
# the archive is frozen reference, not blocking the Rust workspace PRs.
test:
name: Tests
runs-on: ubuntu-latest
continue-on-error: true
strategy:
fail-fast: false
matrix:
python-version: ['3.10', '3.11', '3.12']
services:
@@ -189,51 +121,44 @@ jobs:
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
continue-on-error: true
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
cache: 'pip'
- name: Install dependencies
continue-on-error: true
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
pip install pytest-cov pytest-xdist
- name: Run unit tests
continue-on-error: true
env:
DATABASE_URL: postgresql://postgres:postgres@localhost:5432/test_wifi_densepose
REDIS_URL: redis://localhost:6379/0
ENVIRONMENT: test
run: |
pytest archive/v1/tests/unit/ -v --cov=archive/v1/src --cov-report=xml --cov-report=html --junitxml=junit.xml
pytest tests/unit/ -v --cov=src --cov-report=xml --cov-report=html --junitxml=junit.xml
- name: Run integration tests
continue-on-error: true
env:
DATABASE_URL: postgresql://postgres:postgres@localhost:5432/test_wifi_densepose
REDIS_URL: redis://localhost:6379/0
ENVIRONMENT: test
run: |
pytest archive/v1/tests/integration/ -v --junitxml=integration-junit.xml
pytest tests/integration/ -v --junitxml=integration-junit.xml
- name: Upload coverage reports
continue-on-error: true
uses: codecov/codecov-action@v6
uses: codecov/codecov-action@v4
with:
file: ./coverage.xml
flags: unittests
name: codecov-umbrella
- name: Upload test results
continue-on-error: true
uses: actions/upload-artifact@v4
if: always()
with:
@@ -244,21 +169,17 @@ jobs:
htmlcov/
# Performance and Load Tests
# NOTE: tests/performance/locustfile.py and the src.api.main app path both
# predate the v1→archive/v1 reorganisation. continue-on-error: true until a
# proper locust suite is added under archive/v1/tests/performance/.
performance-test:
name: Performance Tests
runs-on: ubuntu-latest
needs: [test]
continue-on-error: true
if: github.event_name == 'push' && github.ref == 'refs/heads/main'
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
cache: 'pip'
@@ -267,70 +188,36 @@ jobs:
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
pip install pytest # the perf suite is pytest, not locust
pip install locust
# No "Start application" step: the gated test (test_frame_budget.py) drives
# the CSIProcessor pipeline in-process and makes no HTTP calls, so the old
# uvicorn server + `sleep 10` were dead weight — they only existed for the
# now-excluded api_throughput/inference_speed tests, and on every run dumped
# ~50 misleading "router requires hardware setup" ERROR lines for a server
# no test touched. MOCK_POSE_DATA is server-only and unused here.
- name: Start application
run: |
uvicorn src.api.main:app --host 0.0.0.0 --port 8000 &
sleep 10
- name: Run performance tests
working-directory: archive/v1
run: |
# Gate only on the genuine, deterministic perf guard:
# test_frame_budget.py times the *real* CSIProcessor pipeline against
# the ADR 50 ms per-frame budget (single-frame, p95 over 100 frames,
# +Doppler) — a true regression signal.
#
# test_api_throughput.py / test_inference_speed.py are excluded: every
# test there is a TDD red-phase stub (suffix `_should_fail_initially`)
# that times a *mock that sleeps* — meaningless as a perf signal, with
# machine-dependent wall-clock asserts (e.g. `actual_rps >= 40`,
# `batch_time < individual_time`) that are inherently flaky on shared
# CI runners, plus a cross-class fixture-scope bug. Forcing them green
# would be manufacturing a false signal; they stay in-repo for local
# TDD but do not gate CI until the underlying features are implemented.
#
# `python -m pytest` (not the bare `pytest` script) puts the cwd
# (archive/v1) on sys.path so `from src.core...` resolves — the bare
# script omits cwd and raises ModuleNotFoundError: No module named 'src'.
# -o addopts="" drops the root pyproject's --cov/--cov-fail-under=100.
python -m pytest tests/performance/test_frame_budget.py \
-o addopts="" -v --junitxml=perf-junit.xml
locust -f tests/performance/locustfile.py --headless --users 50 --spawn-rate 5 --run-time 60s --host http://localhost:8000
- name: Upload performance results
if: always()
uses: actions/upload-artifact@v4
with:
name: performance-results
path: archive/v1/perf-junit.xml
path: locust_report.html
# Docker Build and Test
# NOTE: the canonical Docker build for the sensing-server is now
# `.github/workflows/sensing-server-docker.yml` (multi-registry push, asset
# smoke tests, bearer-auth smoke tests — #520/#514/#443). This job predates
# that workflow, points at a non-existent root `Dockerfile` with a
# non-existent `target: production`, and pushes to a mis-cased image name —
# `continue-on-error: true` until it's deleted or rewired to call the new
# workflow, so it doesn't gate the rest of the pipeline.
docker-build:
name: Docker Build & Test
runs-on: ubuntu-latest
needs: [code-quality, test, rust-tests]
continue-on-error: true
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
- name: Set up Docker Buildx
continue-on-error: true
uses: docker/setup-buildx-action@v3
- name: Log in to Container Registry
continue-on-error: true
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
@@ -338,9 +225,8 @@ jobs:
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata
continue-on-error: true
id: meta
uses: docker/metadata-action@v6
uses: docker/metadata-action@v5
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
@@ -350,8 +236,7 @@ jobs:
type=raw,value=latest,enable={{is_default_branch}}
- name: Build and push Docker image
continue-on-error: true
uses: docker/build-push-action@v7
uses: docker/build-push-action@v5
with:
context: .
target: production
@@ -363,7 +248,6 @@ jobs:
platforms: linux/amd64,linux/arm64
- name: Test Docker image
continue-on-error: true
run: |
docker run --rm -d --name test-container -p 8000:8000 ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
sleep 10
@@ -371,15 +255,13 @@ jobs:
docker stop test-container
- name: Run container security scan
continue-on-error: true
uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
uses: aquasecurity/trivy-action@master
with:
image-ref: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
format: 'sarif'
output: 'trivy-results.sarif'
- name: Upload Trivy scan results
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -391,14 +273,12 @@ jobs:
runs-on: ubuntu-latest
needs: [docker-build]
if: github.ref == 'refs/heads/main'
permissions:
contents: write # gh-pages deploy needs write (GITHUB_TOKEN is read-only by default -> 403)
steps:
- name: Checkout code
uses: actions/checkout@v4
- name: Set up Python
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
cache: 'pip'
@@ -409,9 +289,6 @@ jobs:
pip install -r requirements.txt
- name: Generate OpenAPI spec
working-directory: archive/v1
env:
MOCK_POSE_DATA: "true" # no CSI hardware in CI
run: |
python -c "
from src.api.main import app
@@ -422,7 +299,6 @@ jobs:
- name: Deploy to GitHub Pages
uses: peaceiris/actions-gh-pages@v4
continue-on-error: true # openapi generation above is the real validation; deploy is best-effort (Pages may be disabled)
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
publish_dir: ./docs
@@ -434,29 +310,26 @@ jobs:
runs-on: ubuntu-latest
needs: [code-quality, test, rust-tests, performance-test, docker-build, docs]
if: always()
permissions:
contents: write # required by softprops/action-gh-release
# GitHub Actions does not allow `secrets.X` directly in step-level `if:`
# expressions — only `env.X`. Promote the secret to env at job scope so
# the gating expression below is parseable.
env:
SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL }}
steps:
- name: Notify Slack on success
if: ${{ env.SLACK_WEBHOOK_URL != '' && needs.code-quality.result == 'success' && needs.test.result == 'success' && needs.docker-build.result == 'success' }}
if: ${{ secrets.SLACK_WEBHOOK_URL != '' && needs.code-quality.result == 'success' && needs.test.result == 'success' && needs.docker-build.result == 'success' }}
uses: 8398a7/action-slack@v3
with:
status: success
channel: '#ci-cd'
text: '✅ CI pipeline completed successfully for ${{ github.ref }}'
env:
SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL }}
- name: Notify Slack on failure
if: ${{ env.SLACK_WEBHOOK_URL != '' && (needs.code-quality.result == 'failure' || needs.test.result == 'failure' || needs.docker-build.result == 'failure') }}
if: ${{ secrets.SLACK_WEBHOOK_URL != '' && (needs.code-quality.result == 'failure' || needs.test.result == 'failure' || needs.docker-build.result == 'failure') }}
uses: 8398a7/action-slack@v3
with:
status: failure
channel: '#ci-cd'
text: '❌ CI pipeline failed for ${{ github.ref }}'
env:
SLACK_WEBHOOK_URL: ${{ secrets.SLACK_WEBHOOK_URL }}
- name: Create GitHub Release
if: github.ref == 'refs/heads/main' && needs.docker-build.result == 'success'
-149
View File
@@ -1,149 +0,0 @@
name: GitHub Clone Tracking → data/clone-data.rvf
# Persists rolling 14-day clone-traffic snapshots to data/clone-data.rvf in
# the ruvector JSONL RVF format. GitHub's /traffic/clones endpoint only
# retains the last 14 days server-side, so without this scheduled scrape
# the data is gone forever the moment it falls outside the window.
#
# Format: JSONL RVF
# - line 1 is a `metadata` segment that initializes the file
# - each subsequent run appends one `clone_snapshot` segment carrying the
# 14-day rollup PLUS per-day breakdown
# - file is idempotent: per-day entries are keyed by `timestamp` so a
# downstream reader can dedupe across overlapping snapshot windows
#
# Schedule: every 14 days (1st + 15th of each month, ~14-day cadence in
# practice). Workflow can also be dispatched manually for backfill or test.
on:
schedule:
# 01:23 UTC on the 1st and 15th of every month — close to 14-day cadence
# without cron's "every 14 days" monthly-reset weirdness. Picking :23
# avoids the cron herd on :00.
- cron: '23 1 1,15 * *'
workflow_dispatch:
permissions:
contents: write
concurrency:
group: clone-tracking
cancel-in-progress: false
jobs:
snapshot:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Fetch /traffic/clones + /traffic/views from GitHub
env:
GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
run: |
mkdir -p data
gh api repos/${{ github.repository }}/traffic/clones > /tmp/clones.json
gh api repos/${{ github.repository }}/traffic/views > /tmp/views.json
echo "--- clones rollup ---"
jq '{count, uniques, days: (.clones | length)}' /tmp/clones.json
echo "--- views rollup ---"
jq '{count, uniques, days: (.views | length)}' /tmp/views.json
- name: Append snapshot to data/clone-data.rvf
env:
REPO: ${{ github.repository }}
run: |
set -e
RVF="data/clone-data.rvf"
FETCHED_AT=$(date -u +"%Y-%m-%dT%H:%M:%SZ")
# Initialize the file with a metadata segment on first run.
if [ ! -f "$RVF" ]; then
echo "Initializing $RVF with metadata segment"
jq -n --arg repo "$REPO" --arg ts "$FETCHED_AT" '{
type: "metadata",
name: "ruview-clone-traffic-history",
version: "1.0.0",
schema: "ruvector.rvf.jsonl/v1",
format: "github-traffic-snapshots",
repo: $repo,
source: "GitHub Traffic API /repos/{repo}/traffic/{clones,views}",
policy: "GitHub retains only 14 days server-side; this file is the long-term record.",
segments: ["metadata", "clone_snapshot", "view_snapshot"],
created_at: $ts,
custom: {
cadence: "twice monthly (1st and 15th, ~14-day intervals)",
idempotency_key: "timestamp (per-day records de-duplicate across overlapping snapshot windows)"
}
}' >> "$RVF"
fi
# Append the clone snapshot.
jq --arg ts "$FETCHED_AT" '{
type: "clone_snapshot",
fetched_at: $ts,
window_count: .count,
window_uniques: .uniques,
per_day: .clones
}' /tmp/clones.json >> "$RVF"
# Append the views snapshot (free with the same auth).
jq --arg ts "$FETCHED_AT" '{
type: "view_snapshot",
fetched_at: $ts,
window_count: .count,
window_uniques: .uniques,
per_day: .views
}' /tmp/views.json >> "$RVF"
echo "--- RVF tail (last 4 lines) ---"
tail -4 "$RVF" | jq -c '{type, fetched_at, window_count, window_uniques}' || true
echo "--- file size ---"
wc -l "$RVF"
- name: Compute aggregates for the commit summary
id: agg
run: |
# Count distinct per-day entries across all snapshots so we can
# show "cumulative observed clones" in the commit message.
python3 - <<'PY'
import json, os
path = "data/clone-data.rvf"
per_day_clones = {}
per_day_views = {}
with open(path, encoding="utf-8") as f:
for line in f:
if not line.strip():
continue
d = json.loads(line)
if d.get("type") == "clone_snapshot":
for entry in d.get("per_day", []):
per_day_clones[entry["timestamp"]] = entry
elif d.get("type") == "view_snapshot":
for entry in d.get("per_day", []):
per_day_views[entry["timestamp"]] = entry
tot_clones = sum(e.get("count", 0) for e in per_day_clones.values())
tot_uniq_clones = sum(e.get("uniques", 0) for e in per_day_clones.values())
tot_views = sum(e.get("count", 0) for e in per_day_views.values())
tot_uniq_views = sum(e.get("uniques", 0) for e in per_day_views.values())
print(f"clone days observed: {len(per_day_clones)} total clones: {tot_clones:,} total unique cloners: {tot_uniq_clones:,}")
print(f"view days observed: {len(per_day_views)} total views: {tot_views:,} total unique viewers: {tot_uniq_views:,}")
with open(os.environ["GITHUB_OUTPUT"], "a") as out:
out.write(f"clones={tot_clones}\n")
out.write(f"clone_days={len(per_day_clones)}\n")
out.write(f"views={tot_views}\n")
out.write(f"view_days={len(per_day_views)}\n")
PY
- name: Commit + push if changed
run: |
git config user.name "github-actions[bot]"
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
if git diff --quiet data/clone-data.rvf; then
echo "no changes to commit"
exit 0
fi
git add data/clone-data.rvf
git commit -m "chore(traffic): clone snapshot — ${{ steps.agg.outputs.clone_days }} days observed → ${{ steps.agg.outputs.clones }} clones, ${{ steps.agg.outputs.view_days }} view-days → ${{ steps.agg.outputs.views }} views"
git push
-200
View File
@@ -1,200 +0,0 @@
name: Cog HA-Matter Release
# ADR-116 P8 — Build + sign + bundle the cog-ha-matter cog on a
# version tag. Upload to gs://cognitum-apps/ runs only when the
# GCP_CREDENTIALS + COGNITUM_OWNER_SIGNING_KEY secrets are set, so
# this workflow is safe to merge before the production credentials
# land — it'll bundle release artifacts to the workflow run page
# either way.
on:
push:
tags:
- 'cog-ha-matter-v*'
workflow_dispatch:
inputs:
dry_run:
description: 'Build + sign + bundle but skip GCS upload'
required: false
default: 'true'
env:
CARGO_TERM_COLOR: always
CRATE: cog-ha-matter
jobs:
build-x86_64:
name: Build x86_64
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup Rust
uses: dtolnay/rust-toolchain@stable
with:
targets: x86_64-unknown-linux-gnu
- name: Cache cargo registry
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: cog-ha-matter-x86_64-${{ hashFiles('v2/Cargo.lock') }}
- name: Build release binary
working-directory: v2/crates/cog-ha-matter/cog
run: make build-x86_64
- name: Compute SHA-256
working-directory: v2/crates/cog-ha-matter/cog
run: make sign-x86_64
- name: Sign with Ed25519 (gated)
if: ${{ env.SIGNING_KEY != '' }}
env:
SIGNING_KEY: ${{ secrets.COGNITUM_OWNER_SIGNING_KEY }}
working-directory: v2/crates/cog-ha-matter/cog
run: |
printf '%s' "$SIGNING_KEY" \
| openssl pkeyutl -sign -inkey /dev/stdin -rawin \
-in dist/cog-ha-matter-x86_64.sha256 \
| base64 -w0 > dist/cog-ha-matter-x86_64.sig
echo "Signed cog-ha-matter-x86_64 ($(wc -c < dist/cog-ha-matter-x86_64.sig) bytes)"
- name: Upload workflow artifact
uses: actions/upload-artifact@v4
with:
name: cog-ha-matter-x86_64
path: |
v2/crates/cog-ha-matter/cog/dist/cog-ha-matter-x86_64
v2/crates/cog-ha-matter/cog/dist/cog-ha-matter-x86_64.sha256
v2/crates/cog-ha-matter/cog/dist/cog-ha-matter-x86_64.sig
if-no-files-found: warn
build-arm:
name: Build aarch64 (arm)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Setup Rust
uses: dtolnay/rust-toolchain@stable
with:
targets: aarch64-unknown-linux-gnu
- name: Install cross-compiler
run: |
sudo apt-get update
sudo apt-get install -y gcc-aarch64-linux-gnu
- name: Cache cargo registry
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: cog-ha-matter-arm-${{ hashFiles('v2/Cargo.lock') }}
- name: Build release binary
working-directory: v2
env:
CARGO_TARGET_AARCH64_UNKNOWN_LINUX_GNU_LINKER: aarch64-linux-gnu-gcc
run: |
cargo build -p cog-ha-matter --release --target aarch64-unknown-linux-gnu
mkdir -p crates/cog-ha-matter/cog/dist
cp target/aarch64-unknown-linux-gnu/release/cog-ha-matter \
crates/cog-ha-matter/cog/dist/cog-ha-matter-arm
# ^ matches Makefile's `dist/$(CRATE)-arm` so `make sign-arm` finds it
- name: Compute SHA-256
working-directory: v2/crates/cog-ha-matter/cog
run: make sign-arm
- name: Sign with Ed25519 (gated)
if: ${{ env.SIGNING_KEY != '' }}
env:
SIGNING_KEY: ${{ secrets.COGNITUM_OWNER_SIGNING_KEY }}
working-directory: v2/crates/cog-ha-matter/cog
run: |
printf '%s' "$SIGNING_KEY" \
| openssl pkeyutl -sign -inkey /dev/stdin -rawin \
-in dist/cog-ha-matter-arm.sha256 \
| base64 -w0 > dist/cog-ha-matter-arm.sig
echo "Signed cog-ha-matter-arm ($(wc -c < dist/cog-ha-matter-arm.sig) bytes)"
- name: Upload workflow artifact
uses: actions/upload-artifact@v4
with:
name: cog-ha-matter-arm
path: |
v2/crates/cog-ha-matter/cog/dist/cog-ha-matter-arm
v2/crates/cog-ha-matter/cog/dist/cog-ha-matter-arm.sha256
v2/crates/cog-ha-matter/cog/dist/cog-ha-matter-arm.sig
if-no-files-found: warn
publish-gcs:
name: Upload to GCS (gated)
needs: [build-x86_64, build-arm]
runs-on: ubuntu-latest
# Skip on dry-run dispatch; skip on tags when GCP_CREDENTIALS unset.
if: >
github.event_name == 'push' &&
vars.HAS_GCP_CREDENTIALS == 'true'
steps:
- uses: actions/checkout@v4
- name: Download x86_64 artifact
uses: actions/download-artifact@v4
with:
name: cog-ha-matter-x86_64
path: dist/
- name: Download arm artifact
uses: actions/download-artifact@v4
with:
name: cog-ha-matter-arm
path: dist/
- name: Auth to GCP
uses: google-github-actions/auth@v2
with:
credentials_json: ${{ secrets.GCP_CREDENTIALS }}
- name: Set up gcloud
uses: google-github-actions/setup-gcloud@v2
- name: Upload binaries + sidecars
run: |
gsutil cp dist/cog-ha-matter-x86_64 gs://cognitum-apps/cogs/x86_64/cog-ha-matter-x86_64
gsutil cp dist/cog-ha-matter-x86_64.sha256 gs://cognitum-apps/cogs/x86_64/cog-ha-matter-x86_64.sha256
gsutil cp dist/cog-ha-matter-arm gs://cognitum-apps/cogs/arm/cog-ha-matter-arm
gsutil cp dist/cog-ha-matter-arm.sha256 gs://cognitum-apps/cogs/arm/cog-ha-matter-arm.sha256
if [ -f dist/cog-ha-matter-x86_64.sig ]; then
gsutil cp dist/cog-ha-matter-x86_64.sig gs://cognitum-apps/cogs/x86_64/cog-ha-matter-x86_64.sig
fi
if [ -f dist/cog-ha-matter-arm.sig ]; then
gsutil cp dist/cog-ha-matter-arm.sig gs://cognitum-apps/cogs/arm/cog-ha-matter-arm.sig
fi
- name: Print app-registry.json snippet for the cognitum-one PR
run: |
for arch in arm x86_64; do
sha=$(cat dist/cog-cog-ha-matter-$arch.sha256)
sig=$([ -f dist/cog-cog-ha-matter-$arch.sig ] && cat dist/cog-cog-ha-matter-$arch.sig || echo "")
cat <<EOF
--- $arch ---
{
"id": "ha-matter",
"version": "${GITHUB_REF_NAME#cog-ha-matter-v}",
"binary_url": "https://storage.googleapis.com/cognitum-apps/cogs/$arch/cog-cog-ha-matter-$arch",
"binary_sha256": "$sha",
"binary_signature": "$sig",
"description": "Home Assistant + Matter Cognitum Seed cog (mDNS + witness chain)",
"min_seed_version": "0.6.0",
"installable_on": ["$arch"]
}
EOF
done
-46
View File
@@ -1,46 +0,0 @@
name: Dashboard a11y + cross-browser
# Runs axe-core a11y assertions on the built dashboard across
# Chromium, Firefox, and WebKit. Closes ADR-092 §11.5 (axe-core)
# and §11.8 (cross-browser).
on:
push:
branches: [main]
paths: ['dashboard/**', 'v2/crates/nvsim/**']
pull_request:
paths: ['dashboard/**']
workflow_dispatch:
permissions:
contents: read
jobs:
a11y:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
with: { targets: wasm32-unknown-unknown }
- name: Install wasm-pack
run: curl https://rustwasm.github.io/wasm-pack/installer/init.sh -sSf | sh
- name: Build nvsim WASM
working-directory: v2
run: |
wasm-pack build crates/nvsim --target web \
--out-dir ../../dashboard/public/nvsim-pkg \
--release -- --no-default-features --features wasm
- uses: actions/setup-node@v6
with: { node-version: 20, cache: npm, cache-dependency-path: dashboard/package-lock.json }
- working-directory: dashboard
run: |
npm ci
npm install --save-dev @playwright/test @axe-core/playwright
npx playwright install --with-deps
npm run build
npx playwright test
-87
View File
@@ -1,87 +0,0 @@
name: nvsim Dashboard → GitHub Pages
# Deploys the nvsim Vite/Lit dashboard to gh-pages/nvsim/ — preserving
# the existing observatory/, pose-fusion/, and root index.html demos
# already published from gh-pages. ADR-092 §9.
on:
push:
branches: [main]
paths:
- 'v2/crates/nvsim/**'
- 'dashboard/**'
- '.github/workflows/dashboard-pages.yml'
workflow_dispatch:
permissions:
contents: write
concurrency:
group: dashboard-pages
cancel-in-progress: true
jobs:
build-and-deploy:
runs-on: ubuntu-latest
steps:
- name: Checkout main
uses: actions/checkout@v4
- name: Install Rust + wasm32 target
uses: dtolnay/rust-toolchain@stable
with:
targets: wasm32-unknown-unknown
- name: Cache cargo registry
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: ${{ runner.os }}-cargo-nvsim-${{ hashFiles('v2/Cargo.lock') }}
restore-keys: ${{ runner.os }}-cargo-nvsim-
- name: Install wasm-pack
run: |
curl https://rustwasm.github.io/wasm-pack/installer/init.sh -sSf | sh
which wasm-pack
- name: Build nvsim WASM
working-directory: v2
run: |
wasm-pack build crates/nvsim \
--target web \
--out-dir ../../dashboard/public/nvsim-pkg \
--release \
-- --no-default-features --features wasm
- name: Setup Node 20
uses: actions/setup-node@v6
with:
node-version: 20
cache: npm
cache-dependency-path: dashboard/package-lock.json
- name: Install dashboard deps
working-directory: dashboard
run: npm ci
- name: Build dashboard
working-directory: dashboard
env:
NVSIM_BASE: /RuView/nvsim/
run: npm run build
- name: Deploy to gh-pages/nvsim/
uses: peaceiris/actions-gh-pages@v4
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
publish_dir: ./dashboard/dist
destination_dir: nvsim
# CRITICAL: preserves observatory/, pose-fusion/, root index.html
# and any other RuView demos already on gh-pages.
keep_files: true
commit_message: 'deploy(nvsim): ${{ github.sha }}'
user_name: 'github-actions[bot]'
user_email: 'github-actions[bot]@users.noreply.github.com'
+12 -12
View File
@@ -30,7 +30,7 @@ jobs:
uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: '20'
@@ -40,18 +40,18 @@ jobs:
targets: ${{ matrix.target }}
- name: Install frontend dependencies
working-directory: v2/crates/wifi-densepose-desktop/ui
working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
run: npm ci
- name: Build frontend
working-directory: v2/crates/wifi-densepose-desktop/ui
working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
run: npm run build
- name: Install Tauri CLI
run: cargo install tauri-cli --version "^2.0.0"
- name: Build Tauri app
working-directory: v2/crates/wifi-densepose-desktop
working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop
run: cargo tauri build --target ${{ matrix.target }}
env:
TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
@@ -68,14 +68,14 @@ jobs:
- name: Package macOS app
run: |
cd v2/target/${{ matrix.target }}/release/bundle/macos
cd rust-port/wifi-densepose-rs/target/${{ matrix.target }}/release/bundle/macos
zip -r "RuView-Desktop-${{ github.event.inputs.version || '0.4.0' }}-macos-${{ steps.arch.outputs.arch }}.zip" "RuView Desktop.app"
- name: Upload macOS artifact
uses: actions/upload-artifact@v4
with:
name: ruview-macos-${{ steps.arch.outputs.arch }}
path: v2/target/${{ matrix.target }}/release/bundle/macos/*.zip
path: rust-port/wifi-densepose-rs/target/${{ matrix.target }}/release/bundle/macos/*.zip
build-windows:
name: Build Windows
@@ -85,7 +85,7 @@ jobs:
uses: actions/checkout@v4
- name: Setup Node.js
uses: actions/setup-node@v6
uses: actions/setup-node@v4
with:
node-version: '20'
@@ -93,18 +93,18 @@ jobs:
uses: dtolnay/rust-toolchain@stable
- name: Install frontend dependencies
working-directory: v2/crates/wifi-densepose-desktop/ui
working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
run: npm ci
- name: Build frontend
working-directory: v2/crates/wifi-densepose-desktop/ui
working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop/ui
run: npm run build
- name: Install Tauri CLI
run: cargo install tauri-cli --version "^2.0.0"
- name: Build Tauri app
working-directory: v2/crates/wifi-densepose-desktop
working-directory: rust-port/wifi-densepose-rs/crates/wifi-densepose-desktop
run: cargo tauri build
env:
TAURI_SIGNING_PRIVATE_KEY: ${{ secrets.TAURI_SIGNING_PRIVATE_KEY }}
@@ -114,13 +114,13 @@ jobs:
uses: actions/upload-artifact@v4
with:
name: ruview-windows-msi
path: v2/target/release/bundle/msi/*.msi
path: rust-port/wifi-densepose-rs/target/release/bundle/msi/*.msi
- name: Upload Windows NSIS artifact
uses: actions/upload-artifact@v4
with:
name: ruview-windows-nsis
path: v2/target/release/bundle/nsis/*.exe
path: rust-port/wifi-densepose-rs/target/release/bundle/nsis/*.exe
create-release:
name: Create Release
+3 -49
View File
@@ -2,11 +2,6 @@ name: Firmware CI
on:
push:
branches:
- '**'
tags:
# ESP32 firmware release tags — build + version-consistency guard (RuView#505).
- 'v*-esp32'
paths:
- 'firmware/**'
- '.github/workflows/firmware-ci.yml'
@@ -16,29 +11,8 @@ on:
- '.github/workflows/firmware-ci.yml'
jobs:
version-guard:
name: Verify version.txt matches release tag
runs-on: ubuntu-latest
if: github.ref_type == 'tag'
steps:
- uses: actions/checkout@v4
- name: Check firmware version.txt == tag
run: |
# Tag form: vX.Y.Z-esp32 → expect version.txt to contain X.Y.Z
TAG="${GITHUB_REF_NAME}"
EXPECTED="${TAG#v}"
EXPECTED="${EXPECTED%-esp32}"
ACTUAL="$(tr -d '[:space:]' < firmware/esp32-csi-node/version.txt)"
echo "Tag: $TAG → expected version.txt: $EXPECTED | actual: $ACTUAL"
if [ "$EXPECTED" != "$ACTUAL" ]; then
echo "::error::firmware/esp32-csi-node/version.txt is '$ACTUAL' but tag '$TAG' expects '$EXPECTED'."
echo "::error::Bump version.txt and re-tag so esp_app_get_description()->version is correct (RuView#505)."
exit 1
fi
echo "version.txt matches the release tag."
build:
name: Build firmware (${{ matrix.target }} / ${{ matrix.variant }})
name: Build ESP32-S3 Firmware (${{ matrix.variant }})
runs-on: ubuntu-latest
container:
image: espressif/idf:v5.4
@@ -47,27 +21,17 @@ jobs:
matrix:
include:
- variant: 8mb
target: esp32s3
sdkconfig: sdkconfig.defaults
partition_table_name: partitions_display.csv
size_limit_kb: 1100
artifact_app: esp32-csi-node.bin
artifact_pt: partition-table.bin
- variant: 4mb
target: esp32s3
sdkconfig: sdkconfig.defaults.4mb
partition_table_name: partitions_4mb.csv
size_limit_kb: 1100
artifact_app: esp32-csi-node-4mb.bin
artifact_pt: partition-table-4mb.bin
# ADR-110: ESP32-C6 research target (Wi-Fi 6 / 802.15.4 / TWT / LP-core)
- variant: c6-4mb
target: esp32c6
sdkconfig: sdkconfig.defaults
partition_table_name: partitions_4mb.csv
size_limit_kb: 1100
artifact_app: esp32-csi-node-c6.bin
artifact_pt: partition-table-c6.bin
steps:
- uses: actions/checkout@v4
@@ -76,22 +40,12 @@ jobs:
working-directory: firmware/esp32-csi-node
run: |
. $IDF_PATH/export.sh
# 4mb variant supplies its own sdkconfig.defaults overlay.
# c6-4mb variant relies on the auto-applied sdkconfig.defaults.esp32c6
# overlay (ESP-IDF auto-loads sdkconfig.defaults.$TARGET when present).
if [ "${{ matrix.variant }}" = "4mb" ]; then
if [ "${{ matrix.variant }}" != "8mb" ]; then
cp "${{ matrix.sdkconfig }}" sdkconfig.defaults
fi
idf.py set-target ${{ matrix.target }}
idf.py set-target esp32s3
idf.py build
- name: Build and run host-side ADR-110 unit tests
if: matrix.variant == 'c6-4mb'
working-directory: firmware/esp32-csi-node/test
run: |
make test_adr110
./test_adr110
- name: Verify binary size (< ${{ matrix.size_limit_kb }} KB gate)
working-directory: firmware/esp32-csi-node
run: |
@@ -1,54 +0,0 @@
name: Fix-Marker Regression Guard
# Asserts that previously-shipped fixes are still present in the tree.
# Manifest: scripts/fix-markers.json Checker: scripts/check_fix_markers.py
# Run locally: python scripts/check_fix_markers.py (also --list / --json)
#
# This complements the heavyweight checks (firmware build, deterministic
# pipeline proof, witness bundle) with a fast per-PR "did someone revert a
# known fix?" gate — the CI analogue of the ruflo witness fix-marker system.
on:
push:
branches:
- main
- master
pull_request:
workflow_dispatch:
jobs:
fix-markers:
name: Verify fix markers
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v6
with:
python-version: '3.11'
- name: Validate the manifest is well-formed JSON
run: python -c "import json; json.load(open('scripts/fix-markers.json')); print('manifest OK')"
- name: Check fix markers
run: python scripts/check_fix_markers.py
- name: Emit machine-readable result (for the run summary)
if: always()
run: |
python scripts/check_fix_markers.py --json > fix-markers-result.json || true
{
echo '### Fix-marker regression guard'
echo ''
echo '```'
python scripts/check_fix_markers.py || true
echo '```'
} >> "$GITHUB_STEP_SUMMARY"
- name: Upload result artifact
if: always()
uses: actions/upload-artifact@v4
with:
name: fix-markers-result
path: fix-markers-result.json
retention-days: 30
-110
View File
@@ -1,110 +0,0 @@
name: ADR-115 MQTT integration tests
# Runs the Mosquitto-broker-backed integration tests for ADR-115's MQTT
# publisher. These prove the publisher reaches a real broker, emits the
# expected HA-discovery topic shape, and honours --privacy-mode at the
# wire boundary (not just in unit-test logic).
#
# Default `cargo test --workspace` does not run these tests because they
# require a broker and pull rumqttc into the build. This workflow opts
# into both by setting --features mqtt and RUVIEW_RUN_INTEGRATION=1.
on:
pull_request:
paths:
- 'v2/crates/wifi-densepose-sensing-server/src/mqtt/**'
- 'v2/crates/wifi-densepose-sensing-server/tests/mqtt_integration.rs'
- 'v2/crates/wifi-densepose-sensing-server/Cargo.toml'
- '.github/workflows/mqtt-integration.yml'
push:
branches: [main]
paths:
- 'v2/crates/wifi-densepose-sensing-server/src/mqtt/**'
workflow_dispatch: {}
jobs:
mqtt-integration:
runs-on: ubuntu-latest
timeout-minutes: 20
# NB: we don't use a `services:` mosquitto container here because the
# eclipse-mosquitto:2.x image rejects anonymous connections by default
# and GH Actions `services` doesn't easily support mounting a custom
# config file. We start mosquitto manually in a step below with an
# inline `allow_anonymous true` config.
env:
RUVIEW_RUN_INTEGRATION: "1"
RUVIEW_TEST_MQTT_PORT: "11883"
CARGO_TERM_COLOR: always
RUST_BACKTRACE: 1
steps:
- uses: actions/checkout@v4
- name: Install mosquitto + clients and start with allow_anonymous
run: |
sudo apt-get update -qq
sudo apt-get install -y mosquitto mosquitto-clients
sudo systemctl stop mosquitto || true
# Inline config: anon listener on 11883 only — no TLS, no auth,
# OK for CI because we test the wire shape, not security.
# Production deployments enable mTLS per ADR-115 §3.9.
cat > /tmp/mosquitto-ci.conf <<'EOF'
listener 11883
allow_anonymous true
persistence false
log_dest stdout
EOF
mosquitto -c /tmp/mosquitto-ci.conf -d
for i in {1..20}; do
if mosquitto_pub -h 127.0.0.1 -p 11883 -t healthcheck -m ok -q 0 2>/dev/null; then
echo "mosquitto reachable on 11883"; exit 0
fi
sleep 2
done
echo "mosquitto never became reachable" >&2
tail -50 /var/log/mosquitto/*.log 2>/dev/null || true
exit 1
- name: Install Rust toolchain
uses: dtolnay/rust-toolchain@stable
with:
toolchain: stable
- name: Cache cargo registry + build
uses: Swatinem/rust-cache@v2
with:
workspaces: v2 -> target
- name: Validate HA Blueprints
run: |
python -m pip install --quiet pyyaml
python scripts/validate-ha-blueprints.py
- name: Verify unit tests still pass under --features mqtt
working-directory: v2
# `cargo test` accepts a single TESTNAME filter, so we run the
# whole --lib suite here. That gives us the full 410-test green
# bar under --features mqtt (which is more reassuring than
# filtering anyway).
run: >-
cargo test -p wifi-densepose-sensing-server
--features mqtt --no-default-features
--lib
--no-fail-fast
- name: Run integration tests against mosquitto
working-directory: v2
run: >-
cargo test -p wifi-densepose-sensing-server
--features mqtt --no-default-features
--test mqtt_integration
--no-fail-fast
-- --test-threads=1 --nocapture
- name: Dump broker logs on failure
if: failure()
run: |
docker ps -a
docker logs $(docker ps -aqf "ancestor=eclipse-mosquitto:2.0.18") || true
-69
View File
@@ -1,69 +0,0 @@
name: nvsim-server → ghcr.io
# Builds and publishes the nvsim-server Docker image to ghcr.io on:
# - push to main affecting nvsim-server or nvsim
# - tag push matching nvsim-server-v*
# - manual workflow_dispatch
#
# ADR-092 §6.2 + §9.4.
on:
push:
branches: [main]
paths:
- 'v2/crates/nvsim-server/**'
- 'v2/crates/nvsim/**'
- '.github/workflows/nvsim-server-docker.yml'
tags: ['nvsim-server-v*']
workflow_dispatch:
permissions:
contents: read
packages: write
jobs:
build-and-publish:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: docker/setup-buildx-action@v3
- uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Extract metadata
id: meta
uses: docker/metadata-action@v6
with:
images: ghcr.io/ruvnet/nvsim-server
tags: |
type=ref,event=branch
type=ref,event=tag
type=sha,format=short
type=raw,value=latest,enable={{is_default_branch}}
- name: Build + push
uses: docker/build-push-action@v7
with:
context: v2
file: v2/crates/nvsim-server/Dockerfile
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
platforms: linux/amd64
- name: Smoke-test the image
run: |
docker pull ghcr.io/ruvnet/nvsim-server:sha-${GITHUB_SHA::7} || \
docker pull ghcr.io/ruvnet/nvsim-server:latest
docker run --rm -d --name nvsim-test -p 7878:7878 \
ghcr.io/ruvnet/nvsim-server:latest
sleep 4
curl -fsS http://localhost:7878/api/health
docker stop nvsim-test
-286
View File
@@ -1,286 +0,0 @@
# ADR-117 P5 — cibuildwheel + PyPI publish workflow for `wifi-densepose`
#
# This workflow is **explicitly NOT** triggered on every push. It runs only on:
# - a maintainer-dispatched `workflow_dispatch`
# - a pushed tag matching `v*-pip` (e.g. `v2.0.0-pip`)
#
# The reason for the `-pip` tag suffix is that the repo already cuts
# `v0.X.Y-esp32` tags for firmware releases (see CLAUDE.md). The `-pip`
# suffix keeps the pip release schedule independent of the firmware
# release schedule.
#
# Sequencing on release day (per ADR-117 §7.3):
# 1. cut tag `v1.99.0-pip` → publishes the tombstone wheel first
# 2. cut tag `v2.0.0-pip` → publishes the PyO3 v2 wheel matrix
#
# Publishes via the `PYPI_API_TOKEN` GitHub Actions secret. The
# token-refresh runbook (GCP Secret Manager → gh secret set) lives in
# docs/integrations/pypi-release.md so KICS does not flag the
# secret name as a generic-secret literal in the workflow.
#
# Q3 (witness hash v2 — open in ADR-117 §11.3) MUST be resolved
# before the first v2.0.0 publish. When v2 lands, add a parallel
# step that verifies the v2 hash against the Rust pipeline.
name: pip-release
on:
workflow_dispatch:
inputs:
target:
description: "Which package to release"
required: true
type: choice
options:
- v2-wheels
- v1-99-tombstone
publish_to:
description: "Where to publish"
required: true
default: testpypi
type: choice
options:
- testpypi # dry-run target
- pypi # production
push:
tags:
- "v*-pip"
permissions:
contents: read
jobs:
# ────────────────────────────────────────────────────────────────
# v2.0.0 — cibuildwheel matrix (5 wheels + sdist)
# ────────────────────────────────────────────────────────────────
build-wheels:
name: Build ${{ matrix.os }} ${{ matrix.arch }}
if: |
github.event_name == 'workflow_dispatch' && inputs.target == 'v2-wheels' ||
startsWith(github.ref, 'refs/tags/v2.')
strategy:
fail-fast: false
matrix:
include:
- os: ubuntu-latest
arch: x86_64
- os: ubuntu-latest
arch: aarch64
- os: macos-13 # x86_64 runner
arch: x86_64
- os: macos-14 # arm64 runner
arch: arm64
- os: windows-latest
arch: AMD64
runs-on: ${{ matrix.os }}
steps:
- uses: actions/checkout@v4
# Linux aarch64 needs QEMU for cross-build on x86_64 runners.
- name: Set up QEMU
if: matrix.os == 'ubuntu-latest' && matrix.arch == 'aarch64'
uses: docker/setup-qemu-action@v3
# ADR-117 §5.4: abi3-py310 — one binary per OS/arch covers all
# Python minor versions ≥ 3.10. Build only cp310 wheels.
- name: Build wheels (cibuildwheel)
uses: pypa/cibuildwheel@v2.21
env:
CIBW_BUILD: "cp310-*"
CIBW_ARCHS_LINUX: ${{ matrix.arch }}
CIBW_ARCHS_MACOS: ${{ matrix.arch }}
CIBW_ARCHS_WINDOWS: ${{ matrix.arch }}
CIBW_BUILD_FRONTEND: "build"
CIBW_BEFORE_BUILD: "pip install maturin>=1.7"
# The PyO3 sdist landing depends on the cargo/Rust toolchain
# being present. cibuildwheel images carry rustup on Linux
# but we also pin a known-good version for reproducibility.
CIBW_BEFORE_ALL_LINUX: "curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y --default-toolchain 1.82"
CIBW_ENVIRONMENT_LINUX: 'PATH="$HOME/.cargo/bin:$PATH"'
# Smoke-test every built wheel before accepting it. Catches
# the case where the wheel imports but the compiled symbols
# are missing.
CIBW_TEST_REQUIRES: "pytest>=8.0"
CIBW_TEST_COMMAND: 'python -c "import wifi_densepose; assert wifi_densepose.hello() == \"ok\"; print(wifi_densepose.__build_features__)"'
with:
package-dir: python
output-dir: wheelhouse
- uses: actions/upload-artifact@v4
with:
name: wheels-${{ matrix.os }}-${{ matrix.arch }}
path: wheelhouse/*.whl
if-no-files-found: error
build-sdist:
name: Build v2 sdist
if: |
github.event_name == 'workflow_dispatch' && inputs.target == 'v2-wheels' ||
startsWith(github.ref, 'refs/tags/v2.')
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: Install maturin
run: pip install maturin>=1.7
- name: Build sdist
working-directory: python
run: maturin sdist --out ../sdist
- uses: actions/upload-artifact@v4
with:
name: sdist
path: sdist/*.tar.gz
if-no-files-found: error
# ────────────────────────────────────────────────────────────────
# v1.99.0 — tombstone wheel (pure Python, single sdist + wheel)
# ────────────────────────────────────────────────────────────────
build-tombstone:
name: Build v1.99.0 tombstone
if: |
github.event_name == 'workflow_dispatch' && inputs.target == 'v1-99-tombstone' ||
startsWith(github.ref, 'refs/tags/v1.99')
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-python@v5
with:
python-version: '3.12'
- name: Install build backend
run: python -m pip install --upgrade pip build>=1.2
- name: Build sdist + wheel
working-directory: python/tombstone
run: python -m build --outdir ../../tombstone-dist
# Inspect what was actually built — the previous v1.99.0-pip run
# showed an `import wifi_densepose` that returned cleanly instead
# of raising, even though build logs said `adding 'wifi_densepose/__init__.py'`.
# Print the wheel manifest + the __init__.py content so any
# future regression is debuggable from the run log alone.
- name: Inspect wheel contents
run: |
set -e
WHL=tombstone-dist/wifi_densepose-1.99.0-py3-none-any.whl
echo "--- wheel listing ---"
python -m zipfile -l "$WHL"
echo "--- wifi_densepose/__init__.py inside the wheel ---"
python -m zipfile -e "$WHL" /tmp/tomb-inspect
cat /tmp/tomb-inspect/wifi_densepose/__init__.py
echo "--- size in bytes ---"
wc -c /tmp/tomb-inspect/wifi_densepose/__init__.py
# Smoke-test in an ISOLATED venv. The previous run's failure
# mode was that the ubuntu-latest runner's system `python` had
# site-packages picking up something other than the user-installed
# wheel, so the import resolved to a different module. A clean
# venv removes any ambiguity about which wifi_densepose is loaded.
- name: Smoke-test tombstone in isolated venv
run: |
set -e
# Copy the wheel to /tmp BEFORE entering the venv — we must
# cd OUT of the repo root because the repo contains a
# `wifi_densepose/` directory left over from the legacy v1
# source. Python puts cwd at sys.path[0], so an import from
# the repo root would resolve to the legacy directory and
# bypass the freshly-installed wheel entirely (this was the
# silent failure mode of the previous two run attempts).
cp tombstone-dist/wifi_densepose-1.99.0-py3-none-any.whl /tmp/
python -m venv /tmp/smoke-venv
/tmp/smoke-venv/bin/python -m pip install --upgrade pip
/tmp/smoke-venv/bin/python -m pip install /tmp/wifi_densepose-1.99.0-py3-none-any.whl
cd /tmp # away from the repo root's stray wifi_densepose/
/tmp/smoke-venv/bin/python -c "import importlib.util as u; s = u.find_spec('wifi_densepose'); print('Resolved to:', s.origin); print('--- file content ---'); print(open(s.origin).read())"
set +e
/tmp/smoke-venv/bin/python -c "import wifi_densepose" 2> import-output.txt
rc=$?
set -e
if [ "$rc" -eq 0 ]; then
echo "ERROR: tombstone import succeeded — should have raised ImportError"
exit 1
fi
if ! grep -q "github.com/ruvnet/RuView" import-output.txt; then
echo "ERROR: tombstone ImportError missing migration URL"
cat import-output.txt
exit 1
fi
echo "Tombstone wheel correctly raises ImportError with migration URL."
- uses: actions/upload-artifact@v4
with:
name: tombstone
path: tombstone-dist/*
if-no-files-found: error
# ────────────────────────────────────────────────────────────────
# Publish — gated by manual dispatch OR by the tag form
# ────────────────────────────────────────────────────────────────
publish-v2:
name: Publish v2 wheels
needs: [build-wheels, build-sdist]
if: |
always() &&
needs.build-wheels.result == 'success' &&
needs.build-sdist.result == 'success' &&
(
github.event_name == 'workflow_dispatch' && inputs.target == 'v2-wheels' ||
startsWith(github.ref, 'refs/tags/v2.')
)
runs-on: ubuntu-latest
steps:
- name: Gather all artifacts into dist/
uses: actions/download-artifact@v4
with:
path: dist-staging
- name: Flatten artifacts
run: |
mkdir -p dist
find dist-staging -type f \( -name '*.whl' -o -name '*.tar.gz' \) -exec cp -v {} dist/ \;
ls -lh dist/
- name: Publish to TestPyPI (dry-run target)
if: github.event_name == 'workflow_dispatch' && inputs.publish_to == 'testpypi'
uses: pypa/gh-action-pypi-publish@release/v1
with:
repository-url: https://test.pypi.org/legacy/
password: ${{ secrets.PYPI_API_TOKEN }}
packages-dir: dist
skip-existing: true
- name: Publish to PyPI
if: |
startsWith(github.ref, 'refs/tags/v2.') ||
(github.event_name == 'workflow_dispatch' && inputs.publish_to == 'pypi')
uses: pypa/gh-action-pypi-publish@release/v1
with:
password: ${{ secrets.PYPI_API_TOKEN }}
packages-dir: dist
publish-tombstone:
name: Publish v1.99 tombstone
needs: [build-tombstone]
if: |
always() &&
needs.build-tombstone.result == 'success' &&
(
github.event_name == 'workflow_dispatch' && inputs.target == 'v1-99-tombstone' ||
startsWith(github.ref, 'refs/tags/v1.99')
)
runs-on: ubuntu-latest
steps:
- uses: actions/download-artifact@v4
with:
name: tombstone
path: dist
- name: Publish to TestPyPI (dry-run target)
if: github.event_name == 'workflow_dispatch' && inputs.publish_to == 'testpypi'
uses: pypa/gh-action-pypi-publish@release/v1
with:
repository-url: https://test.pypi.org/legacy/
password: ${{ secrets.PYPI_API_TOKEN }}
packages-dir: dist
skip-existing: true
- name: Publish to PyPI
if: |
startsWith(github.ref, 'refs/tags/v1.99') ||
(github.event_name == 'workflow_dispatch' && inputs.publish_to == 'pypi')
uses: pypa/gh-action-pypi-publish@release/v1
with:
password: ${{ secrets.PYPI_API_TOKEN }}
packages-dir: dist
-74
View File
@@ -1,74 +0,0 @@
name: Point Cloud Viewer → GitHub Pages
# Publishes the live 3D point cloud viewer to gh-pages/pointcloud/.
# The viewer defaults to a synthetic in-browser demo; users can append
# ?backend=<url> or ?backend=auto to point it at a real ruview-pointcloud
# server (CORS-permitting host required). See ADR-094.
#
# Uses keep_files: true to preserve the existing observatory/, pose-fusion/,
# nvsim/, and root index.html demos already on gh-pages.
on:
push:
branches: [main]
paths:
- 'v2/crates/wifi-densepose-pointcloud/src/viewer.html'
- '.github/workflows/pointcloud-pages.yml'
workflow_dispatch:
permissions:
contents: write
concurrency:
group: pointcloud-pages
cancel-in-progress: true
jobs:
build-and-deploy:
runs-on: ubuntu-latest
steps:
- name: Checkout main
uses: actions/checkout@v4
- name: Stage viewer for Pages
run: |
mkdir -p _site/pointcloud
cp v2/crates/wifi-densepose-pointcloud/src/viewer.html _site/pointcloud/index.html
# Drop a tiny README so direct browsers of the directory get context.
cat > _site/pointcloud/README.md <<'EOF'
# RuView — Live 3D Point Cloud Viewer
Hosted at: https://ruvnet.github.io/RuView/pointcloud/
## Modes
- Default — synthetic in-browser demo (no backend, no network calls).
- `?backend=auto` — fetch from `/api/splats` on the same origin
(only works when the viewer is served by `ruview-pointcloud serve`).
- `?backend=<url>` — fetch from `<url>/api/splats`. The intended
local-ESP32 use is `?backend=http://127.0.0.1:9880`: run
`ruview-pointcloud serve --bind 127.0.0.1:9880` on the same
machine with your ESP32 streaming CSI to UDP port 3333, then
visit the URL above. The local server's CorsLayer permits
requests from `https://ruvnet.github.io`, and modern browsers
permit HTTPS→127.0.0.1 mixed-content as a trustworthy origin.
The "📡 Connect ESP32" button in the viewer prompts for this
URL and persists it in localStorage.
- `?live=1` — require a live backend; show an offline message instead
of falling back to the synthetic demo.
See ADR-094 for the deployment design.
EOF
- name: Deploy to gh-pages/pointcloud/
uses: peaceiris/actions-gh-pages@v4
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
publish_dir: ./_site/pointcloud
destination_dir: pointcloud
# CRITICAL: preserves observatory/, pose-fusion/, nvsim/, and root
# index.html already on gh-pages.
keep_files: true
commit_message: 'deploy(pointcloud): ${{ github.sha }}'
user_name: 'github-actions[bot]'
user_email: 'github-actions[bot]@users.noreply.github.com'
-149
View File
@@ -1,149 +0,0 @@
name: ruview-swarm CI guard
# Dedicated guard for the ADR-148 drone swarm crate (`v2/crates/ruview-swarm`).
# The main ci.yml runs `cargo test --workspace --no-default-features`, which
# only exercises ruview-swarm's DEFAULT feature set. This guard additionally:
# - tests every feature combination (train / ruflo+itar / full)
# - fails on ANY clippy warning in the crate's own code (--no-deps)
# - asserts the ITAR + publish guards stay in place (USML Cat VIII(h)(12))
# - builds the GPU training binary under the `train` feature
#
# Path-scoped so it only runs when the crate or this workflow changes.
on:
push:
branches: [ main, 'feat/*' ]
paths:
- 'v2/crates/ruview-swarm/**'
- '.github/workflows/ruview-swarm-ci.yml'
pull_request:
paths:
- 'v2/crates/ruview-swarm/**'
- '.github/workflows/ruview-swarm-ci.yml'
workflow_dispatch:
env:
CARGO_TERM_COLOR: always
jobs:
# ── Feature-matrix tests ─────────────────────────────────────────────────
tests:
name: tests (${{ matrix.features.label }})
runs-on: ubuntu-latest
strategy:
fail-fast: false
matrix:
features:
- { label: 'default', flags: '--no-default-features' }
- { label: 'train', flags: '--features train' }
- { label: 'ruflo+itar', flags: '--features ruflo,itar-unrestricted' }
- { label: 'full+train', flags: '--features full,train' }
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
- name: Cache cargo
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: ${{ runner.os }}-ruview-swarm-${{ hashFiles('v2/Cargo.lock') }}
restore-keys: ${{ runner.os }}-ruview-swarm-
- name: cargo test -p ruview-swarm ${{ matrix.features.flags }}
working-directory: v2
run: cargo test -p ruview-swarm ${{ matrix.features.flags }} --lib
# ── Clippy: zero warnings in the crate's own code ────────────────────────
clippy:
name: clippy (-D warnings, --no-deps)
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
# v2/rust-toolchain.toml pins channel "1.89" with profile "minimal" (no
# clippy). dtolnay@stable installs clippy on the floating "stable"
# toolchain, but the override makes cargo use the separate "1.89"
# toolchain — so `cargo clippy` errors "cargo-clippy is not installed for
# 1.89". Install clippy on the pinned toolchain that cargo actually uses.
- uses: dtolnay/rust-toolchain@stable
with:
toolchain: "1.89"
components: clippy
- name: Cache cargo
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: ${{ runner.os }}-ruview-swarm-clippy-${{ hashFiles('v2/Cargo.lock') }}
restore-keys: ${{ runner.os }}-ruview-swarm-clippy-
# --no-deps confines linting to ruview-swarm's own source, so pre-existing
# warnings in dependency crates don't gate this PR.
- name: clippy (default)
working-directory: v2
run: cargo clippy -p ruview-swarm --no-default-features --no-deps -- -D warnings
- name: clippy (full,train)
working-directory: v2
run: cargo clippy -p ruview-swarm --features full,train --no-deps -- -D warnings
# ── Build the GPU training binary (train feature) ────────────────────────
train-bin:
name: build train_marl bin
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: dtolnay/rust-toolchain@stable
- name: Cache cargo
uses: actions/cache@v4
with:
path: |
~/.cargo/registry
~/.cargo/git
v2/target
key: ${{ runner.os }}-ruview-swarm-bin-${{ hashFiles('v2/Cargo.lock') }}
restore-keys: ${{ runner.os }}-ruview-swarm-bin-
- name: cargo build --bin train_marl --features train
working-directory: v2
run: cargo build -p ruview-swarm --features train --bin train_marl
- name: train_marl is excluded from the default build
working-directory: v2
run: |
# The training binary requires the `train` feature; a default `--bins`
# build must NOT produce it (keeps default/CI builds light + Candle-free).
# Remove any prior artifact first so this checks what the DEFAULT build
# produces, not a leftover from the train-feature build above.
rm -f target/debug/train_marl
cargo build -p ruview-swarm --no-default-features --bins
if [ -f target/debug/train_marl ]; then
echo "ERROR: train_marl built without the 'train' feature" >&2
exit 1
fi
echo "OK: train_marl correctly gated behind the 'train' feature"
# ── ITAR + publish guards ────────────────────────────────────────────────
export-control-guard:
name: ITAR / publish guard
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- name: publish = false is present (no accidental crates.io publish)
run: |
CARGO=v2/crates/ruview-swarm/Cargo.toml
if ! grep -qE '^\s*publish\s*=\s*false' "$CARGO"; then
echo "ERROR: ruview-swarm Cargo.toml must keep 'publish = false' until" >&2
echo " PR merge + dependency publish + ITAR export sign-off." >&2
exit 1
fi
echo "OK: publish = false present"
- name: default feature set does NOT enable itar-unrestricted
run: |
CARGO=v2/crates/ruview-swarm/Cargo.toml
# USML Cat VIII(h)(12): swarming coordination must be opt-in, never default.
DEFAULT_LINE=$(grep -E '^\s*default\s*=' "$CARGO" || true)
echo "default = $DEFAULT_LINE"
if echo "$DEFAULT_LINE" | grep -q 'itar-unrestricted'; then
echo "ERROR: 'itar-unrestricted' must NOT be in the default feature set" >&2
exit 1
fi
echo "OK: ITAR-gated coordination features are opt-in, not default"
+28 -88
View File
@@ -18,27 +18,23 @@ jobs:
sast:
name: Static Application Security Testing
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
permissions:
security-events: write
actions: read
contents: read
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Set up Python
continue-on-error: true
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
cache: 'pip'
- name: Install dependencies
continue-on-error: true
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
@@ -46,38 +42,34 @@ jobs:
- name: Run Bandit security scan
run: |
# The Python codebase lives under archive/v1/src (it moved there when
# the runtime was rewritten in Rust). Scanning `src/` matched nothing,
# so this SAST step was a silent no-op.
bandit -r archive/v1/src/ -f sarif -o bandit-results.sarif
bandit -r src/ -f sarif -o bandit-results.sarif
continue-on-error: true
- name: Upload Bandit results to GitHub Security
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
sarif_file: bandit-results.sarif
category: bandit
# Removed the deprecated `returntocorp/semgrep-action@v1` step: it was
# redundant (the pip `semgrep --sarif` below is what feeds GitHub Security;
# the action only pushed to the Semgrep cloud app via SEMGREP_APP_TOKEN) and
# it pulled `returntocorp/semgrep-agent:v1` from Docker Hub on every run,
# which intermittently timed out and turned this check red. The pip semgrep
# (installed above) needs no Docker pull. The action's `p/docker` +
# `p/kubernetes` rulesets are folded into the command below so coverage is
# preserved.
- name: Run Semgrep + generate SARIF
- name: Run Semgrep security scan
uses: returntocorp/semgrep-action@v1
with:
config: >-
p/security-audit
p/secrets
p/python
p/docker
p/kubernetes
env:
SEMGREP_APP_TOKEN: ${{ secrets.SEMGREP_APP_TOKEN }}
- name: Generate Semgrep SARIF
run: |
semgrep \
--config=p/security-audit --config=p/secrets --config=p/python \
--config=p/docker --config=p/kubernetes \
--sarif --output=semgrep.sarif archive/v1/src/
semgrep --config=p/security-audit --config=p/secrets --config=p/python --sarif --output=semgrep.sarif src/
continue-on-error: true
- name: Upload Semgrep results to GitHub Security
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -88,25 +80,21 @@ jobs:
dependency-scan:
name: Dependency Vulnerability Scan
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
permissions:
security-events: write
actions: read
contents: read
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
- name: Set up Python
continue-on-error: true
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
cache: 'pip'
- name: Install dependencies
continue-on-error: true
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
@@ -123,7 +111,7 @@ jobs:
continue-on-error: true
- name: Run Snyk vulnerability scan
uses: snyk/actions/python@9adf32b1121593767fc3c057af55b55db032dc04 # v1.0.0
uses: snyk/actions/python@master
env:
SNYK_TOKEN: ${{ secrets.SNYK_TOKEN }}
with:
@@ -131,7 +119,6 @@ jobs:
continue-on-error: true
- name: Upload Snyk results to GitHub Security
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -139,7 +126,6 @@ jobs:
category: snyk
- name: Upload vulnerability reports
continue-on-error: true
uses: actions/upload-artifact@v4
if: always()
with:
@@ -153,7 +139,6 @@ jobs:
container-scan:
name: Container Security Scan
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
needs: []
if: github.event_name == 'push' || github.event_name == 'schedule'
permissions:
@@ -162,16 +147,13 @@ jobs:
contents: read
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
- name: Set up Docker Buildx
continue-on-error: true
uses: docker/setup-buildx-action@v3
- name: Build Docker image for scanning
continue-on-error: true
uses: docker/build-push-action@v7
uses: docker/build-push-action@v5
with:
context: .
target: production
@@ -181,15 +163,13 @@ jobs:
cache-to: type=gha,mode=max
- name: Run Trivy vulnerability scanner
continue-on-error: true
uses: aquasecurity/trivy-action@ed142fd0673e97e23eac54620cfb913e5ce36c25 # v0.36.0
uses: aquasecurity/trivy-action@master
with:
image-ref: 'wifi-densepose:scan'
format: 'sarif'
output: 'trivy-results.sarif'
- name: Upload Trivy results to GitHub Security
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -197,8 +177,7 @@ jobs:
category: trivy
- name: Run Grype vulnerability scanner
continue-on-error: true
uses: anchore/scan-action@v7
uses: anchore/scan-action@v3
id: grype-scan
with:
image: 'wifi-densepose:scan'
@@ -207,7 +186,6 @@ jobs:
output-format: sarif
- name: Upload Grype results to GitHub Security
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -215,7 +193,6 @@ jobs:
category: grype
- name: Run Docker Scout
continue-on-error: true
uses: docker/scout-action@v1
if: always()
with:
@@ -225,7 +202,6 @@ jobs:
summary: true
- name: Upload Docker Scout results
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -236,19 +212,16 @@ jobs:
iac-scan:
name: Infrastructure Security Scan
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
permissions:
security-events: write
actions: read
contents: read
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
- name: Run Checkov IaC scan
continue-on-error: true
uses: bridgecrewio/checkov-action@99bb2caf247dfd9f03cf984373bc6043d4e32ebf # v12.1347.0
uses: bridgecrewio/checkov-action@master
with:
directory: .
framework: kubernetes,dockerfile,terraform,ansible
@@ -258,7 +231,6 @@ jobs:
soft_fail: true
- name: Upload Checkov results to GitHub Security
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -266,8 +238,7 @@ jobs:
category: checkov
- name: Run Terrascan IaC scan
continue-on-error: true
uses: tenable/terrascan-action@3a6e87da8e244513bd77b631e624552643f794c6 # v1.4.1
uses: tenable/terrascan-action@main
with:
iac_type: 'k8s'
iac_version: 'v1'
@@ -276,8 +247,7 @@ jobs:
sarif_upload: true
- name: Run KICS IaC scan
continue-on-error: true
uses: checkmarx/kics-github-action@05aa5eb70eede1355220f4ca5238d96b397e30a6 # v2.1.20
uses: checkmarx/kics-github-action@master
with:
path: '.'
output_path: kics-results
@@ -286,7 +256,6 @@ jobs:
exclude_queries: 'a7ef1e8c-fbf8-4ac1-b8c7-2c3b0e6c6c6c'
- name: Upload KICS results to GitHub Security
continue-on-error: true
uses: github/codeql-action/upload-sarif@v3
if: always()
with:
@@ -297,21 +266,18 @@ jobs:
secret-scan:
name: Secret Scanning
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
permissions:
security-events: write
actions: read
contents: read
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
with:
fetch-depth: 0
- name: Run TruffleHog secret scan
continue-on-error: true
uses: trufflesecurity/trufflehog@17456f8c7d042d8c82c9a8ca9e937231f9f42e26 # v3.95.2
uses: trufflesecurity/trufflehog@main
with:
path: ./
base: main
@@ -319,7 +285,6 @@ jobs:
extra_args: --debug --only-verified
- name: Run GitLeaks secret scan
continue-on-error: true
uses: gitleaks/gitleaks-action@v2
env:
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
@@ -336,34 +301,28 @@ jobs:
license-scan:
name: License Compliance Scan
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
- name: Set up Python
continue-on-error: true
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ env.PYTHON_VERSION }}
cache: 'pip'
- name: Install dependencies
continue-on-error: true
run: |
python -m pip install --upgrade pip
pip install -r requirements.txt
pip install pip-licenses licensecheck
- name: Run license check
continue-on-error: true
run: |
pip-licenses --format=json --output-file=licenses.json
licensecheck --zero
- name: Upload license report
continue-on-error: true
uses: actions/upload-artifact@v4
with:
name: license-report
@@ -373,14 +332,11 @@ jobs:
compliance-check:
name: Security Policy Compliance
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
steps:
- name: Checkout code
continue-on-error: true
uses: actions/checkout@v4
- name: Check security policy files
continue-on-error: true
run: |
# Check for required security files
files=("SECURITY.md" ".github/SECURITY.md" "docs/SECURITY.md")
@@ -398,13 +354,11 @@ jobs:
fi
- name: Check for security headers in code
continue-on-error: true
run: |
# Check for security-related configurations
grep -r "X-Frame-Options\|X-Content-Type-Options\|X-XSS-Protection\|Content-Security-Policy" src/ || echo "⚠️ Consider adding security headers"
- name: Validate Kubernetes security contexts
continue-on-error: true
run: |
# Check for security contexts in Kubernetes manifests
if [[ -d "k8s" ]]; then
@@ -421,21 +375,13 @@ jobs:
security-report:
name: Security Report
runs-on: ubuntu-latest
continue-on-error: true # third-party scanners are flaky / SARIF uploads can 403; don't gate the PR
needs: [sast, dependency-scan, container-scan, iac-scan, secret-scan, license-scan, compliance-check]
if: always()
# Promote secret to env-scope so the gating `if:` on the Slack-notify
# step below is parseable (GitHub Actions rejects `secrets.X` in
# step-level `if:` expressions).
env:
SECURITY_SLACK_WEBHOOK_URL: ${{ secrets.SECURITY_SLACK_WEBHOOK_URL }}
steps:
- name: Download all artifacts
continue-on-error: true
uses: actions/download-artifact@v4
- name: Generate security summary
continue-on-error: true
run: |
echo "# Security Scan Summary" > security-summary.md
echo "" >> security-summary.md
@@ -451,18 +397,13 @@ jobs:
echo "Generated on: $(date)" >> security-summary.md
- name: Upload security summary
continue-on-error: true
uses: actions/upload-artifact@v4
with:
name: security-summary
path: security-summary.md
# GitHub Actions does not allow `secrets.X` in step-level `if:` —
# use env.X instead. Inherits SECURITY_SLACK_WEBHOOK_URL from the
# job-level env block (added below).
- name: Notify security team on critical findings
continue-on-error: true
if: ${{ env.SECURITY_SLACK_WEBHOOK_URL != '' && (needs.sast.result == 'failure' || needs.dependency-scan.result == 'failure' || needs.container-scan.result == 'failure') }}
if: ${{ secrets.SECURITY_SLACK_WEBHOOK_URL != '' && (needs.sast.result == 'failure' || needs.dependency-scan.result == 'failure' || needs.container-scan.result == 'failure') }}
uses: 8398a7/action-slack@v3
with:
status: failure
@@ -474,10 +415,9 @@ jobs:
Workflow: ${{ github.workflow }}
Please review the security scan results immediately.
env:
SLACK_WEBHOOK_URL: ${{ env.SECURITY_SLACK_WEBHOOK_URL }}
SLACK_WEBHOOK_URL: ${{ secrets.SECURITY_SLACK_WEBHOOK_URL }}
- name: Create security issue on critical findings
continue-on-error: true
if: needs.sast.result == 'failure' || needs.dependency-scan.result == 'failure'
uses: actions/github-script@v6
with:
-181
View File
@@ -1,181 +0,0 @@
name: wifi-densepose sensing-server → Docker Hub + ghcr.io
# Build + publish the `wifi-densepose` sensing-server image to both Docker Hub
# (`ruvnet/wifi-densepose`) and ghcr.io (`ghcr.io/ruvnet/wifi-densepose`) on:
# - push to main affecting the Dockerfile, the server crate, the UI assets,
# or this workflow itself,
# - tag push matching v* (release builds),
# - manual workflow_dispatch.
#
# Closes #520 and #514: the stale `:latest` is rebuilt and pushed automatically
# whenever the surface that produces it changes, and the Dockerfile fails the
# build if the observatory/pose-fusion UI assets ever go missing again.
#
# Secrets:
# DOCKERHUB_USERNAME — `ruvnet` (Docker Hub login name)
# DOCKERHUB_TOKEN — Docker Hub access token with read/write/delete scope
# (ghcr.io uses the workflow's GITHUB_TOKEN — no secret needed.)
on:
push:
branches: [main]
paths:
- 'docker/Dockerfile.rust'
- 'docker/docker-entrypoint.sh'
- 'v2/crates/wifi-densepose-sensing-server/**'
- 'v2/crates/wifi-densepose-signal/**'
- 'v2/crates/wifi-densepose-vitals/**'
- 'v2/crates/wifi-densepose-wifiscan/**'
- 'v2/crates/wifi-densepose-bfld/**'
- 'v2/crates/cog-ha-matter/**'
- 'v2/Cargo.toml'
- 'v2/Cargo.lock'
- 'ui/**'
- '.github/workflows/sensing-server-docker.yml'
tags: ['v*']
workflow_dispatch: {}
permissions:
contents: read
packages: write
concurrency:
group: sensing-server-docker-${{ github.ref }}
cancel-in-progress: true
jobs:
build-and-publish:
name: build · push · smoke-test
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
with:
submodules: recursive
# QEMU is required so the amd64 GitHub runner can cross-build the
# linux/arm64 layer below (Dockerfile.rust is arch-agnostic — no `--target`
# flag — so buildx + QEMU is all that's needed; arm64 builds are emulated
# by the runner, not built on a separate arm64 host).
- uses: docker/setup-qemu-action@v3
- uses: docker/setup-buildx-action@v3
- name: Log in to Docker Hub
# Bypassing docker/login-action@v3: the action kept emitting
# "malformed HTTP Authorization header" against a known-good
# dckr_pat_* token (verified by direct curl against the Hub API).
# `docker login --password-stdin` is the documented credential
# path and avoids whatever encoding step the action injects.
env:
DH_USER: ${{ secrets.DOCKERHUB_USERNAME }}
DH_TOKEN: ${{ secrets.DOCKERHUB_TOKEN }}
run: |
printf '%s' "$DH_TOKEN" | docker login docker.io -u "$DH_USER" --password-stdin
- name: Log in to ghcr.io
uses: docker/login-action@v3
with:
registry: ghcr.io
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Compute tags
id: meta
uses: docker/metadata-action@v6
with:
images: |
docker.io/ruvnet/wifi-densepose
ghcr.io/ruvnet/wifi-densepose
tags: |
type=ref,event=branch
type=ref,event=tag
type=sha,format=short
type=raw,value=latest,enable={{is_default_branch}}
- name: Build + push
id: build
uses: docker/build-push-action@v7
with:
context: .
file: docker/Dockerfile.rust
push: true
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
cache-from: type=gha
cache-to: type=gha,mode=max
# README badge advertises `amd64 + arm64`, and #547 promised multi-arch
# as part of the docker publish refresh; arm64 was never actually wired
# in, so Apple Silicon Macs hit `no matching manifest for linux/arm64/v8`
# on `docker pull ruvnet/wifi-densepose:latest` (#136, #625). Build both.
platforms: linux/amd64,linux/arm64
# ---------------------------------------------------------------------
# Smoke-test the freshly-pushed image:
# 1. UI assets that closed #520 are inside `/app/ui` (the Dockerfile's
# RUN guard catches missing ones at build time, this re-checks the
# pushed artifact post-hoc as belt-and-braces).
# 2. /health is up.
# 3. /api/v1/info returns 200 with no auth (LAN-mode default).
# 4. With RUVIEW_API_TOKEN set, /api/v1/info returns 401 without a
# Bearer header, 200 with the correct one (the #443 auth middleware).
# ---------------------------------------------------------------------
- name: Smoke-test image assets + LAN-mode HTTP
run: |
set -euo pipefail
IMAGE="ghcr.io/ruvnet/wifi-densepose:sha-${GITHUB_SHA::7}"
docker pull "$IMAGE"
docker run --rm "$IMAGE" sh -c \
'ls /app/ui/observatory.html /app/ui/pose-fusion.html /app/ui/index.html /app/ui/viz.html >/dev/null'
docker run --rm "$IMAGE" sh -c 'ls -d /app/ui/observatory /app/ui/pose-fusion >/dev/null'
docker run -d --name sm -p 3000:3000 -e CSI_SOURCE=simulated "$IMAGE"
# Wait up to 30 s for /health.
for _ in $(seq 1 30); do
if curl -fsS http://127.0.0.1:3000/health >/dev/null 2>&1; then break; fi
sleep 1
done
curl -fsS http://127.0.0.1:3000/health
curl -fsS http://127.0.0.1:3000/api/v1/info >/dev/null
curl -fsS http://127.0.0.1:3000/ui/observatory.html >/dev/null
curl -fsS http://127.0.0.1:3000/ui/pose-fusion.html >/dev/null
docker stop sm
- name: Smoke-test the bearer-token auth path
run: |
set -euo pipefail
IMAGE="ghcr.io/ruvnet/wifi-densepose:sha-${GITHUB_SHA::7}"
docker run -d --name auth \
-p 3000:3000 \
-e CSI_SOURCE=simulated \
-e RUVIEW_API_TOKEN=smoke-test-token-do-not-use \
"$IMAGE"
for _ in $(seq 1 30); do
if curl -fsS http://127.0.0.1:3000/health >/dev/null 2>&1; then break; fi
sleep 1
done
# /health stays unauthenticated.
curl -fsS http://127.0.0.1:3000/health >/dev/null
# /api/v1/info without a bearer → 401.
code=$(curl -s -o /dev/null -w '%{http_code}' http://127.0.0.1:3000/api/v1/info)
test "$code" = "401" || { echo "expected 401, got $code"; exit 1; }
# Wrong bearer → 401.
code=$(curl -s -o /dev/null -w '%{http_code}' -H 'Authorization: Bearer wrong' http://127.0.0.1:3000/api/v1/info)
test "$code" = "401" || { echo "expected 401 (wrong token), got $code"; exit 1; }
# Correct bearer → 200.
curl -fsS -H 'Authorization: Bearer smoke-test-token-do-not-use' http://127.0.0.1:3000/api/v1/info >/dev/null
docker stop auth
- name: Summary
if: always()
run: |
{
echo "## sensing-server image published"
echo
echo "Tags:"
echo '```'
echo "${{ steps.meta.outputs.tags }}"
echo '```'
echo
echo "Closes #520 (missing observatory/pose-fusion UI assets) and #514 (stale `:latest` for the v0.6+ packet format)."
echo "The Dockerfile fails the build if those UI assets ever disappear again, and this workflow rebuilds + pushes automatically on every change to the surface."
} >> "$GITHUB_STEP_SUMMARY"
-70
View File
@@ -1,70 +0,0 @@
name: three.js demos → GitHub Pages
# Publishes the ADR-097 three.js demos under gh-pages/three.js/.
# Uses keep_files: true so the existing observatory/, pose-fusion/,
# pointcloud/, nvsim/, and root index.html demos are preserved.
#
# Demos 04 and 05 require a Mixamo "X Bot.fbx" placed in assets/.
# That file is intentionally gitignored (license boundary), so this
# workflow does NOT ship it. Demos 01-03 work standalone; the index
# page documents the FBX requirement honestly.
on:
push:
branches: [main]
paths:
- 'examples/three.js/**'
- '.github/workflows/threejs-pages.yml'
workflow_dispatch:
permissions:
contents: write
concurrency:
group: threejs-pages
cancel-in-progress: true
jobs:
build-and-deploy:
runs-on: ubuntu-latest
steps:
- name: Checkout main
uses: actions/checkout@v4
- name: Stage demos for Pages
run: |
mkdir -p _site/three.js
# Copy everything except the local Python server (CI doesn't need it)
# and any stray scratch screenshots.
cp -r examples/three.js/demos _site/three.js/demos
cp -r examples/three.js/screenshots _site/three.js/screenshots
cp examples/three.js/README.md _site/three.js/README.md
# An index.html that lists the 5 demos with the FBX caveat.
cp examples/three.js/index.html _site/three.js/index.html
# Mixamo FBX is gitignored — assets dir won't exist in CI.
# Drop an empty placeholder so the relative path 'assets/' resolves
# to a directory listing (404 on missing file) instead of an opaque
# network error. Browsers showing the 404 path makes the failure
# visible to anyone trying demos 04/05 without their own FBX.
mkdir -p _site/three.js/assets
cat > _site/three.js/assets/README.txt <<'EOF'
The Mixamo "X Bot.fbx" required by demos 04-skinned-fbx.html and
05-skinned-realtime.html is intentionally not redistributed here.
Download your own from https://mixamo.com (FBX Binary, T-Pose,
Without Skin) and place it here as "X Bot.fbx" if you want to
run those demos locally. See examples/three.js/README.md in the
repo for context.
EOF
echo "Staged contents:"
ls -R _site/three.js/ | head -30
- name: Deploy to GitHub Pages
uses: peaceiris/actions-gh-pages@v3
with:
github_token: ${{ secrets.GITHUB_TOKEN }}
publish_dir: _site
# Critical: preserve observatory/, pose-fusion/, pointcloud/, nvsim/
# and the root index.html already on gh-pages.
keep_files: true
commit_message: 'three.js demos: ${{ github.event.head_commit.message }}'
+6 -23
View File
@@ -19,24 +19,8 @@ jobs:
fetch-depth: 0
token: ${{ secrets.GITHUB_TOKEN }}
# Identity must be set BEFORE any operation that can create a commit.
# `git submodule update --remote --merge` used to fail here with
# "Committer identity unknown" because the merge inside vendor/ruvector
# needs an author when the pinned commit isn't a fast-forward of upstream.
- name: Configure git identity
run: |
git config --global user.name "github-actions[bot]"
git config --global user.email "41898282+github-actions[bot]@users.noreply.github.com"
# Use a plain `--remote` checkout (detached HEAD at each submodule's
# configured `branch` tip from .gitmodules) rather than `--merge`. We only
# want to bump the superproject's gitlink to the latest upstream commit;
# there's no reason to create merge commits inside the vendored repos, and
# `--merge` breaks whenever the current pin has diverged from that branch.
- name: Update submodules to latest tracked branch
run: |
git submodule sync --recursive
git submodule update --remote --recursive
- name: Update submodules to latest main
run: git submodule update --remote --merge
- name: Check for changes
id: check
@@ -45,22 +29,21 @@ jobs:
echo "changed=false" >> "$GITHUB_OUTPUT"
else
echo "changed=true" >> "$GITHUB_OUTPUT"
echo "--- submodule pointer changes ---"
git submodule status --recursive || true
git diff --submodule=log -- vendor/ || true
fi
- name: Create PR with updates
if: steps.check.outputs.changed == 'true'
run: |
git config user.name "github-actions[bot]"
git config user.email "41898282+github-actions[bot]@users.noreply.github.com"
BRANCH="chore/update-submodules-$(date +%Y%m%d-%H%M%S)"
git checkout -b "$BRANCH"
git add vendor/
git commit -m "chore: update vendor submodules to latest upstream"
git commit -m "chore: update vendor submodules to latest main"
git push origin "$BRANCH"
gh pr create \
--title "chore: update vendor submodules" \
--body "Automated submodule update to the latest upstream commit on each submodule's tracked branch (see \`.gitmodules\`). Review the pointer diff before merging." \
--body "Automated submodule update to latest upstream main." \
--base main \
--head "$BRANCH"
env:
+13 -32
View File
@@ -4,18 +4,16 @@ on:
push:
branches: [ main, master, 'claude/**' ]
paths:
- 'archive/v1/src/core/**'
- 'archive/v1/src/hardware/**'
- 'archive/v1/data/proof/**'
- 'archive/v1/requirements-lock.txt'
- 'v1/src/core/**'
- 'v1/src/hardware/**'
- 'v1/data/proof/**'
- '.github/workflows/verify-pipeline.yml'
pull_request:
branches: [ main, master ]
paths:
- 'archive/v1/src/core/**'
- 'archive/v1/src/hardware/**'
- 'archive/v1/data/proof/**'
- 'archive/v1/requirements-lock.txt'
- 'v1/src/core/**'
- 'v1/src/hardware/**'
- 'v1/data/proof/**'
- '.github/workflows/verify-pipeline.yml'
workflow_dispatch:
@@ -32,26 +30,26 @@ jobs:
uses: actions/checkout@v4
- name: Set up Python ${{ matrix.python-version }}
uses: actions/setup-python@v6
uses: actions/setup-python@v5
with:
python-version: ${{ matrix.python-version }}
- name: Install pinned dependencies
run: |
python -m pip install --upgrade pip
pip install -r archive/v1/requirements-lock.txt
pip install -r v1/requirements-lock.txt
- name: Verify reference signal is reproducible
run: |
echo "=== Regenerating reference signal ==="
python archive/v1/data/proof/generate_reference_signal.py
python v1/data/proof/generate_reference_signal.py
echo ""
echo "=== Checking data file matches committed version ==="
# The regenerated file should be identical to the committed one
# (We compare the metadata file since data file is large)
python -c "
import json, hashlib
with open('archive/v1/data/proof/sample_csi_meta.json') as f:
with open('v1/data/proof/sample_csi_meta.json') as f:
meta = json.load(f)
assert meta['is_synthetic'] == True, 'Metadata must mark signal as synthetic'
assert meta['numpy_seed'] == 42, 'Seed must be 42'
@@ -59,18 +57,7 @@ jobs:
"
- name: Run pipeline verification
working-directory: archive/v1
env:
# Pin thread count for scipy.fft / BLAS — multi-threaded reduction
# order is otherwise non-deterministic across CI runs (issue #560
# follow-up: 9- and 6-decimal quantization were not enough because
# the divergence is from threading order, not SIMD reordering).
# Single-threaded keeps the proof reproducible at a ~2-3x slowdown.
OMP_NUM_THREADS: "1"
OPENBLAS_NUM_THREADS: "1"
MKL_NUM_THREADS: "1"
VECLIB_MAXIMUM_THREADS: "1"
NUMEXPR_NUM_THREADS: "1"
working-directory: v1
run: |
echo "=== Running pipeline verification ==="
python data/proof/verify.py
@@ -78,13 +65,7 @@ jobs:
echo "Pipeline verification PASSED."
- name: Run verification twice to confirm determinism
working-directory: archive/v1
env:
OMP_NUM_THREADS: "1"
OPENBLAS_NUM_THREADS: "1"
MKL_NUM_THREADS: "1"
VECLIB_MAXIMUM_THREADS: "1"
NUMEXPR_NUM_THREADS: "1"
working-directory: v1
run: |
echo "=== Second run for determinism confirmation ==="
python data/proof/verify.py
@@ -95,7 +76,7 @@ jobs:
echo "=== Scanning for unseeded np.random usage in production code ==="
# Search for np.random calls without a seed in production code
# Exclude test files, proof data generators, and known parser placeholders
VIOLATIONS=$(grep -rn "np\.random\." archive/v1/src/ \
VIOLATIONS=$(grep -rn "np\.random\." v1/src/ \
--include="*.py" \
--exclude-dir="__pycache__" \
| grep -v "np\.random\.RandomState" \
-16
View File
@@ -13,9 +13,6 @@ firmware/esp32-csi-node/managed_components/
firmware/esp32-csi-node/dependencies.lock
firmware/esp32-csi-node/sdkconfig.defaults.bak
# ESP-IDF set-target backup (local only)
firmware/esp32-hello-world/sdkconfig.old
# Claude Flow swarm runtime state
.swarm/
@@ -255,16 +252,3 @@ firmware/esp32-csi-node/build_firmware.batdata/
models/
demo_pointcloud.ply
demo_splats.json
# rvCSI napi-rs addon — generated by `napi build` (do not commit)
v2/crates/rvcsi-node/*.node
v2/crates/rvcsi-node/binding.js
v2/crates/rvcsi-node/binding.d.ts
v2/crates/rvcsi-node/npm/
# AetherArena private optimization staging — never published until reviewed
aether-arena/staging/
# MM-Fi benchmark dataset archives — large data, fetch separately, never commit
assets/MM-Fi/E0*.zip
assets/MM-Fi/*.zip
-4
View File
@@ -10,7 +10,3 @@
path = vendor/sublinear-time-solver
url = https://github.com/ruvnet/sublinear-time-solver
branch = main
[submodule "vendor/rvcsi"]
path = vendor/rvcsi
url = https://github.com/ruvnet/rvcsi
branch = main
+4 -279
View File
@@ -7,277 +7,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
## [Unreleased]
### Fixed
- **Person count no longer leaks up to 10 in heuristic mode — addresses #894.** `field_bridge::occupancy_or_fallback` returned the eigenvalue-based `FieldModel::estimate_occupancy` count **unbounded** (its internal ceiling is 10), while the sibling estimators on the same single-link data — the perturbation-energy fallback right below it and `score_to_person_count` — both cap at 3 ("1-3 for single ESP32"). On noisy / under-calibrated CSI the eigenvalue count inflated, producing the "10 persons reported when 1 present" symptom (seen when `--model` fails to load and the server runs on heuristics). Bounded the eigenvalue path to the shared `MAX_SINGLE_LINK_OCCUPANCY` (3) so every estimator on one link agrees; genuine higher counts come from the multistatic fusion path, not a single-link covariance estimate.
- **MQTT multi-node deployments now create one Home-Assistant device per node — closes #898.** After the #872 MQTT wiring landed, the JSON→`VitalsSnapshot` bridge hard-coded a single `node_id` (the MQTT client id) and the publisher used a single `OwnedDiscoveryBuilder`, so every physical node collapsed into one device (`identifiers:["wifi_densepose_wifi-densepose-1"]`), contradicting the "one device per node" docs. The bridge now emits one snapshot per node in the sensing update's `nodes[]` (each with its own `node_id` + RSSI, falling back to a single aggregate snapshot for wifi/simulate sources), and the publisher derives a per-node builder (`OwnedDiscoveryBuilder::for_node`) that publishes discovery + availability lazily on first sight of each `node_id` and routes state to per-node topics — yielding N distinct HA devices with per-node availability/LWT. Unit-tested (distinct nodes → distinct `wifi_densepose_<node>` identifiers); 71 MQTT tests pass.
- **Person count no longer pinned to 1 — addresses #803.** The aggregate occupancy reported by the sensing server was derived from `smoothed_person_score`, an EMA-smoothed *activity* score (amplitude variance / motion / spectral energy). That score saturates near a single occupant — one moving person maxes it out — so it cannot discriminate occupancy *count* and stayed clamped at 1 across S3/C6 and the Python/Docker/Rust servers. Meanwhile the count-aware per-node estimates the ESP32 paths already compute (firmware `n_persons`, and the DynamicMinCut `corr_persons`) were stashed in `NodeState::prev_person_count` and then **discarded** by the aggregator (same dead-wiring class as #872). The aggregator now takes `max(activity_count, node_max)` via a unit-tested `aggregate_person_count` helper, so a node positively estimating 23 occupants is surfaced instead of overwritten. The fix can only ever *raise* the count when a node reports more people, so the single-occupant case is provably never inflated (regression-guarded by test). **Second half:** the pure-CSI per-node path itself clamped its own estimate — the DynamicMinCut occupancy (`estimate_persons_from_correlation`, 03) was mapped to a score via `corr_persons / 3.0`, putting 2 people at 0.667, *just under* the 0.70 up-threshold of `score_to_person_count`, so the per-node count never climbed past 1 (so `node_max` was also stuck at 1 for CSI-only nodes). Replaced it with a threshold-aligned `corr_persons_to_score` mapping (1→0.40, 2→0.74, 3→0.96) whose steady state round-trips back to the same count through the EMA + hysteresis, while still gating transient noise. A convergence test replays the exact EMA loop to prove min-cut=2 now reports 2 (and documents that the old `/3.0` mapping reported 1). Full multi-person accuracy still depends on the underlying estimator quality; this removes the two server-side clamps that masked it. 586 sensing-server tests pass.
- **MQTT publisher now actually runs (`--mqtt`) — closes #872.** The `--mqtt*` flags were defined only in `cli::Args` (dead code, referenced nowhere) while the binary parses a *separate* `main::Args` with no mqtt fields, and `main.rs` never started the `mqtt::` publisher — so MQTT/Home-Assistant integration was completely unwired (`--mqtt` errored as an unexpected argument, and even with the Docker image's `--features mqtt` build the publisher never ran). Earlier attempts chased a Docker *rebuild*; the real cause was disconnected *code*. Extracted the flags into a shared `cli::MqttArgs` (`#[command(flatten)]` into both structs), spawn the publisher on `--mqtt`, and bridge the JSON sensing broadcast into the typed `VitalsSnapshot` stream with a defensive `serde_json::Value` mapping. Verified end-to-end against `mosquitto`: 20 HA auto-discovery entities + live state (presence/person-count/…). 577 (default) / 580 (`--features mqtt`) tests pass.
- **Mass Casualty triage never reports a survivor with a heartbeat as Deceased (safety) — PR #926.** Both triage paths in `wifi-densepose-mat``TriageCalculator::calculate` (`combine_assessments(Absent, None) ⇒ Deceased`) and the detection path `EnsembleClassifier::determine_triage` (`!has_breathing && !has_movement ⇒ Deceased`) — ignored the `heartbeat` field. A survivor with a detectable **pulse** but no sensed breathing/movement (respiratory arrest — the most time-critical *savable* state, Immediate/Red) was therefore reported **Deceased (Black)** and deprioritized for rescue. The domain path was in fact only reachable *because* a heartbeat made `has_vitals()` true, so every "Deceased" was a live person. Both paths now escalate to **Immediate** when a heartbeat is present; total absence of breathing, movement *and* heartbeat is unchanged (domain → `Unknown`, ensemble → `Deceased`). 2 safety regression tests; full MAT suite (177) green.
- **Per-node Home-Assistant devices now report each node's *own* presence/motion — PR #918.** After the one-device-per-node fan-out landed, the MQTT bridge still applied the *room-level aggregate* `classification` to every node, so in a multi-node deployment a node watching an empty corner inherited another node's "present" (and `motion_level: "absent"` was mis-mapped to full motion). Each node in the broadcast `nodes[]` already carries its own `classification`; the bridge now reads it per node (extracted into a testable `vitals_snapshots_from_sensing_json`), keeping vitals + person count room-level. 4 unit tests.
- **`--model` gives an actionable diagnostic instead of a cryptic magic error — PR #919 (refs #894).** Passing a HuggingFace `ruvnet/wifi-densepose-pretrained` file (`model.safetensors` / `model-q4.bin` / `model.rvf.jsonl`) to `--model` produced `invalid magic at offset 0: … got 0x77455735`, then a silent fall back to heuristics. The load-failure path now detects the format (safetensors / quantized blob / JSONL manifest) and explains that those files are a different format **and** encoder architecture than the RVF binary container the progressive loader expects, pointing to #894. Pure `diagnose_model_load_error` + 4 tests.
- **`--export-rvf` no longer silently produces a placeholder model — PR #920.** The `--export-rvf` handler ran *before* `--train`/`--pretrain` and unconditionally wrote placeholder sine-wave weights, so the documented `--train … --export-rvf <path>` workflow short-circuited to a fake model and never trained (while printing "exported successfully"). It now emits the placeholder **container-format demo** only standalone (with a clear warning), and falls through to real training when `--train`/`--pretrain` is set; docs point to `--save-rvf` for the real model. 3 guard tests.
### Added
- **WiFi-CSI pose: efficiency frontier + per-room calibration service** (ADR-150 §3.23.6). Two beyond-SOTA results on the MM-Fi benchmark, plus the deployment mechanism that resolves real-world generalization:
- **Efficiency frontier** — a **75 K-param model beats published SOTA** (74.3% vs MultiFormer 72.25% torso-PCK@20); every config from `micro` up is Pareto-dominant (smaller *and* more accurate than prior work). Shipped a deployable **int4 edge model (~20 KB, verified 74.08%, 0.135 ms single-thread CPU)** — published at [`ruvnet/wifi-densepose-mmfi-pose/edge`](https://huggingface.co/ruvnet/wifi-densepose-mmfi-pose). See [`docs/benchmarks/wifi-pose-efficiency-frontier.md`](docs/benchmarks/wifi-pose-efficiency-frontier.md).
- **Generalization solved by few-shot calibration** — zero-shot cross-subject (~64%) and cross-environment (~10%) are *not* closeable by algorithms (CORAL, DANN, instance-norm, contrastive foundation-pretraining all tested, all failed) or by more training subjects (saturates ~64%). But **~100200 labeled in-room samples recover SOTA-level pose**: cross-subject 64→76%, **cross-environment 10→73% (60% from just 5 samples)** — deployable as a **~11 KB per-room LoRA adapter** on a frozen shared base. Full empirical chain in ADR-150 §3.23.6.
- **Calibration service (complete, both model paths, cross-language verified)** — `aether-arena/calibration/`: `calibrate.py` (transformer model, `.npz` adapter) + `infer.py` (verified 3.09%→74.29% on an unseen MM-Fi room), **and `cog_calibrate.py`** which fits a `fc1.a/fc1.b/fc2.a/fc2.b` **safetensors** adapter for the deployed cog conv+MLP model (`pose_v1.safetensors`). Consumed by the Rust product engine: `InferenceEngine::with_adapter()` + `cog-pose-estimation run --config <cfg> --adapter <room.safetensors>`. Self-contained regression tests for both Python producers (`test_calibration.py`, `test_cog_calibration.py`) **plus a cross-language Rust integration test** that loads a real `cog_calibrate.py`-generated adapter fixture and asserts it activates + changes engine output. All green.
- **Windows workspace build + test now green** (cross-platform fixes). `wifi-densepose-worldmodel` imported `tokio::net::UnixStream` unconditionally, so `cargo build/test --workspace` failed to compile on Windows (E0432) — now the OccWorld Unix-socket bridge is `#[cfg(unix)]`-gated with a clear non-unix fallback. And `wifi-densepose-bfld`'s `readme_quickstart_uses_canonical_public_api` test checked a multi-line `pipeline\n .process` needle that never matched on a CRLF checkout — now normalizes line endings. Result: **2,682 workspace tests pass / 0 fail on Windows** (the pre-merge gate was previously unrunnable there).
- **`ruview-swarm` crate (ADR-148)** — drone swarm control system with hierarchical-mesh topology, Raft consensus, MAPPO multi-agent reinforcement learning, and CSI sensing integration. 14 modules: topology (Raft/Gossip/Mesh), formation control (virtual-structure/leader-follower/Reynolds flocking), RRT-APF path planning, auction+FNN task allocation, MARL actor + PPO training loop, security (MAVLink v2 HMAC-SHA256 signing, UWB anti-spoofing, geofencing, Remote ID, FHSS anti-jamming), 10-state fail-safe machine, and SwarmOrchestrator. ITAR-gated coordination features (USML Category VIII(h)(12)) behind `itar-unrestricted` feature.
- **Ruflo integration for `ruview-swarm`** — feature-gated (`ruflo`) AI-agent capability layer connecting to the claude-flow daemon: AgentDB mission memory (`memory_store`/`memory_search`), HNSW pattern learning (`agentdb_pattern-store`/`-search`), AIDefence MAVLink message scanning, and SONA intelligence trajectory hooks. `RufloBackend` trait with `HttpRufloBackend` (JSON-RPC 2.0) and `MockRufloBackend` implementations.
### Performance
- `ruview-swarm` benchmarks (criterion, release): MARL actor inference 3.3 µs, RRT-APF planning 0.043 ms, multi-view CSI fusion 58.5 ns, 3-view localization 1.732 m (beats Wi2SAR 5 m SOTA baseline), 4-drone SAR coverage 223 s for 400×400 m (under 240 s target).
### Added
- **ADR-147 — OccWorld world model integration** (`wifi-densepose-worldmodel` v0.3.0 published to crates.io). 15-frame trajectory prediction at 209 ms / 3.37 GB VRAM on RTX 5080. Phase 3 domain adapter `scripts/ruview_occ_dataset.py` (`RuViewOccDataset`) converts WorldGraph snapshots to OccWorld tensors with indoor class remapping + zero ego-poses (validated). Phase 5 retraining pipeline `scripts/occworld_retrain.py` — VQVAE + transformer fine-tuning on RuView occupancy snapshots. See [ADR-147](docs/adr/ADR-147-nvidia-cosmos-world-foundation-model-integration.md) · [benchmark proof](docs/adr/ADR-147-benchmark-proof.md).
### Added
- **ADR-125 (APPLE-FABRIC) — RuView ↔ Apple Home native HAP bridge proposal + reference impl** (issue #796). New ADR-125 lays out a three-phase plan to expose RuView as a discoverable HomeKit accessory on the LAN so a HomePod (as Home Hub) sees presence / vitals / BFLD-derived events natively — zero Home-Assistant intermediary. Two architectural decisions resolved in the ADR per design review: (1) **one HAP bridge with N child accessories** (single pairing, matches Hue/Eve pattern), and (2) **identity-risk mapping is semantic, not probabilistic**`identity_risk_score` and Soul-Signature match probability never cross the HAP boundary; instead three thresholded events are exposed (`Unknown Presence`, `Unexpected Occupancy`, `Unrecognized Activity Pattern`) so RuView reads as calm-tech ambient awareness, not surveillance UX. ADR-125 §2.1.a reference impl ships now: `scripts/hap-test-sensor.py` (HAP-1.1 bridge advertised over mDNS, paired with operator's iPhone) + `scripts/c6-presence-watcher.py` (parses ESP32 `RV_FEATURE_STATE_MAGIC = 0xC5110006` UDP packets with IEEE CRC32 validation, hysteresis, and a Python port of `wifi-densepose-bfld::PrivacyClass` that enforces ADR-125 §2.1.d invariant I1 at the HomeKit edge — only `Anonymous` (2) and `Restricted` (3) frames may cross; `Raw`/`Derived` are refused with exit code 2 and the cited ADR clause). Validated end-to-end on real hardware (no mocks): ESP32-C6 on `ruv.net` → UDP/5005 → mac-mini watcher → BFLD gate → HAP bridge → iPhone Home app shows `Unknown Presence` live characteristic flip. **Empirical**: 50-51 valid CRC-passing feature_state packets per 10 s window from the live C6; zero CRC errors. P2 (Rust-native HAP via the `hap` crate, replaces the Python sidecar) and P3 (Matter Controller once `matter-rs` stabilizes) follow.
### Security
- **ESP32 OTA upload now fails closed when no PSK is provisioned** (#596 audit finding — critical, **breaking change for unprovisioned nodes**). `ota_check_auth()` previously returned `true` when `s_ota_psk[0] == '\0'`, so a freshly-flashed node would accept attacker-controlled firmware over plain HTTP on port 8032 from any host on the WiFi. No Secure Boot V2, no signed-image verification — a single LAN call could brick or backdoor a node. The fix rejects every OTA upload until a PSK is written to NVS (the OTA HTTP server still starts so operators can run `provision.py --ota-psk <hex>` over USB-CDC without reflashing). **Operators affected**: any deployment that relied on the unauthenticated OTA endpoint working out of the box now needs to provision a PSK before subsequent OTA pushes will succeed. Boot-time `ESP_LOGW` makes the new posture visible.
- **Bearer-token auth accepts the scheme case-insensitively (RFC 6750) — PR #929.** `require_bearer` parsed the `Authorization` header with a case-sensitive `strip_prefix("Bearer ")`, so a *correct* `RUVIEW_API_TOKEN` sent as `Authorization: bearer <token>` (or `BEARER`, or with extra whitespace) was rejected with a confusing 401 — needless friction when enabling auth. The scheme is now matched with `eq_ignore_ascii_case` (per RFC 6750 §2.1 / RFC 7235 §2.1); the token compare is unchanged — still exact and constant-time (`ct_eq`) — so a wrong token or a non-Bearer scheme (`Basic …`) still returns 401. Audited the surrounding code while here: `ct_eq` correctly rejects length mismatch (no prefix-auth bypass) and the middleware fails closed. New `accepts_case_insensitive_bearer_scheme` test.
- **Path-traversal vulnerabilities patched in five sensing-server endpoints** (closes #615 — critical). New `wifi_densepose_sensing_server::path_safety::safe_id()` enforces `[A-Za-z0-9._-]` only (no leading `.`, max 64 chars) before any user-controlled identifier reaches a `format!()` building a filesystem path. Applied at:
- `POST /api/v1/recording/start` (`recording.rs``session_name`)
- `GET /api/v1/recording/download/:id` (`recording.rs``id`)
- `DELETE /api/v1/recording/delete/:id` (`recording.rs``id`)
- `POST /api/v1/models/load` (`model_manager.rs``model_id`)
- `training_api.rs` `load_recording_frames` (`dataset_id`s)
Pre-fix, unauthenticated callers could read `../../etc/passwd`-style paths, write arbitrary JSONL files, load attacker-controlled `.rvf` model files, or delete arbitrary files the server process could touch. 9 unit tests in `path_safety::tests` exercise the rejection envelope (empty, too-long, path separators, parent-dir traversal, null byte, whitespace/specials, non-ASCII).
### Fixed
- **WebSocket `/ws/sensing` now reports `esp32:offline` when ESP32 hardware goes stale** (closes #618). `broadcast_tick_task` was re-emitting the cached `latest_update` with a frozen `source: "esp32"` field forever after the hardware lost power or network. The REST `/health` endpoint already called `effective_source()` (which returns `"esp32:offline"` after `ESP32_OFFLINE_TIMEOUT` = 5 s with no UDP frames), but the WS broadcast path was the one consumer that didn't. Result: the UI's "LIVE — ESP32 HARDWARE Connected" banner stayed green long after the hardware went away, and `vital_signs`/`features`/`classification` re-broadcasted the last-seen values indefinitely. Fix: clone the cached `latest_update` per tick, overwrite `source` with `s.effective_source()`, then serialize and broadcast. UI can now switch to an offline state on the same 5-second budget the REST surface uses.
- **Proof replay (`archive/v1/data/proof/verify.py`) is now cross-platform deterministic** (closes #560). Three changes together: (1) `features_to_bytes()` now `np.round(.., HASH_QUANTIZATION_DECIMALS=6)`s each feature array before packing as little-endian f64, collapsing ULP-level drift from scipy.fft pocketfft SIMD reordering; (2) the `Verify Pipeline Determinism` workflow pins `OMP_NUM_THREADS=1`, `OPENBLAS_NUM_THREADS=1`, `MKL_NUM_THREADS=1`, `VECLIB_MAXIMUM_THREADS=1`, `NUMEXPR_NUM_THREADS=1` — multi-threaded BLAS reductions were a deeper source of non-determinism than SIMD reordering, and 6-decimal quantization alone wasn't enough across Azure VM microarchitectures; (3) `expected_features.sha256` regenerated under the new conditions. CI now passes the determinism check (same hash across consecutive runs on canonical Linux x86_64 CI runner: `667eb054c44ac510342665bf9c93d608868a8ead948ae8774b2796ebce6f8fe7`). `scripts/probe-fft-platform.py` updated to mirror `HASH_QUANTIZATION_DECIMALS=6` for cross-machine spot-checks.
- **`archive/v1/src/services/pose_service.py:223` calls the right method on `PhaseSanitizer`** (closes #612). The call was `self.phase_sanitizer.sanitize(phase_data)`, but `PhaseSanitizer`'s full-pipeline entry point is named `sanitize_phase()` (`unwrap_phase` + `remove_outliers` + `smooth_phase` chained, see `archive/v1/src/core/phase_sanitizer.py:266`). The shorter `sanitize` name doesn't exist on the class, so any path that reached this branch raised `AttributeError` and crashed the pose service mid-frame.
- **`adaptive_classifier.rs:94` no longer panics on NaN feature values** (closes #611).
`sorted.sort_by(|a, b| a.partial_cmp(b).unwrap())` returned `None` and panicked
whenever a single `NaN` reached the classifier from real ESP32 hardware (silent
DSP div-by-zero, empty buffer). One bad frame killed the entire sensing-server
process. Swapped for `unwrap_or(Ordering::Equal)`, matching the pattern the
same file already used at lines 149-150 and 155. Per-frame hot path; this was
a real production crash vector.
- **Completed the #611 NaN-panic audit across the sensing-server crate** (follow-up
to #613). The original audit grepped for the literal `partial_cmp(b).unwrap()`
and missed seven additional production sites that use comparator variants
(`partial_cmp(b.1).unwrap()`, `partial_cmp(&variances[b]).unwrap()`). All share
the same crash class — a single `NaN` in CSI-derived state panics the whole
sensing-server. Fixed:
- `adaptive_classifier.rs:205``AdaptiveModel::classify()` argmax over softmax
probs. **Same per-frame hot path as #611**; NaN flows through normalise →
logits → softmax and still reaches this site even after the #613 IQR fix.
- `adaptive_classifier.rs:480, 500` — training-loop argmax in `train()`
(training/per-class accuracy reporting).
- `main.rs:2446, 2449` and `csi.rs:602, 605` — variance-based source/sink
selection in `count_persons_mincut`. The outer `unwrap_or((0, &0))` only
catches an empty iterator; it cannot rescue a comparator panic.
Remaining `partial_cmp(...).unwrap()` sites in the workspace are all inside
`#[cfg(test)]` / `#[test]` blocks (`spectrogram.rs:269`, `depth.rs:234`,
`connectivity.rs:477`, `vital_signs.rs:737`) where inputs are controlled.
- **`ui/utils/pose-renderer.js` no longer divides by zero** when two render frames land in the same `performance.now()` tick (issue #519 Bug 2). `deltaTime` is now `Math.max(currentTime - lastFrameTime, 1)` before the `1000 / deltaTime` division, capping displayed FPS at 1000 — far above any real render rate, but finite so the EMA `averageFps = averageFps * 0.9 + fps * 0.1` no longer poisons itself to `Infinity` on a single zero-dt tick.
### Removed
- **Stub crates `wifi-densepose-api`, `wifi-densepose-db`, `wifi-densepose-config`** (closes #578).
Each was a single-line doc-comment placeholder with an empty `[dependencies]`
section and zero references from any source file or `Cargo.toml`. The names
were reserved early for an envisioned REST/database/config split that never
materialised; the functionality they would provide is covered today by
`wifi-densepose-sensing-server` (Axum REST/WS), per-crate config + CLI args,
and the project's real-time-only (no-persistent-state) posture. Removing them
from the workspace prevents `cargo` from listing dead crates and shipping
empty published artifacts. If any of these names is needed in the future,
they can be reintroduced with a real implementation.
### Added
- **BFLD — Beamforming Feedback Layer for Detection (ADR-118 umbrella + ADR-119 frame format + ADR-120 privacy class + ADR-121 identity risk scoring + ADR-122 RuView HA/Matter exposure + ADR-123 capture path, [#787](https://github.com/ruvnet/RuView/issues/787)).** New crate `wifi-densepose-bfld` (`v2/crates/wifi-densepose-bfld/`) — the privacy-gated WiFi sensing layer that detects when RF data crosses from "ambient sensing" into "identity record" and **structurally prevents** identity-correlated data from leaving the node. Three invariants enforced by the type system (not policy): **I1** raw BFI never exits the node (`Sink` marker-trait hierarchy + `PrivacyClass::Raw.allows_network() == false`), **I2** identity embedding is in-RAM-only (`IdentityEmbedding` has no `Serialize`/`Clone`/`Copy` + `Drop` zeroizes), **I3** cross-site identity correlation is cryptographically impossible (per-site BLAKE3-keyed `SignatureHasher` with daily epoch rotation; mean cross-site Hamming distance ≥120 bits across 100 trials). Ships the complete operator surface: `BfldPipeline` + `BfldPipelineHandle` (worker-thread variant + `spawn_with_oracle` for Soul Signature deployments), `BfldEvent` with JSON publishing (`"blake3:<hex>"` `rf_signature_hash` format per spec), 4 `privacy_class` levels (Raw/Derived/Anonymous/Restricted) with `PrivacyGate::demote` monotonic transformer + irreversible `apply_privacy_gating`, `CoherenceGate` with ±0.05 hysteresis + 5-second debounce + clock-skew resilience (saturating_sub), `SoulMatchOracle` Recalibrate-exemption trait for enrolled-person deployments. **MQTT/HA surface**: `mqtt_topics::render_events` + `publish_event` (class-gated topic routing — Raw/Derived publish 0 topics, Anonymous publishes 6, Restricted publishes 5 with `identity_risk` stripped), `ha_discovery::render_discovery_payloads` + `publish_discovery` (HA-DISCO config payloads with `availability_topic` integration), `availability` module (`online`/`offline` + LWT-aware `with_lwt` helper for `rumqttc::MqttOptions`), `RumqttPublisher` behind a `mqtt` feature gate with `connect_with_lwt` for broker-side auto-offline. **3 operator HA Blueprints** under `v2/crates/cog-ha-matter/blueprints/bfld/` (presence-driven-lighting, motion-aware-HVAC, identity-risk-anomaly-notification with rolling 7-day z-score). **Two runnable examples** (`bfld_minimal` for in-process consumers, `bfld_handle` for the production worker-thread + bootstrap-then-spawn pattern). **GitHub Actions CI workflow** (`.github/workflows/bfld-mqtt-integration.yml`) spins up `eclipse-mosquitto:2` as a service container so the env-gated `mosquitto_integration` and `rumqttc_lwt` tests run end-to-end in CI. **Performance**: `BfldFrame::to_bytes()` measured at **320,255 frames/sec** debug (6.4× ADR-119 AC7 release target of 50k), header-only at 1,654,517 frames/sec, presence-detection latency p95 = **0.9µs** (~1,000,000× under ADR-119 AC2's 1s target), 9.96 Hz motion-publish rate through `BfldPipelineHandle` (10× ADR-122 AC3 floor). **Coverage**: 327 tests at default features, 101 no_std-compatible, 220+ with `--features mqtt`. CRC-32/ISO-HDLC polynomial pinned against `"123456789" → 0xCBF43926`, public-API surface snapshot pinned across all `pub use` re-exports, `BfldError` Display contract pinned for log-grep monitoring rules, reserved-flag-bits forward-compat round-trip property, `apply_privacy_gating` irreversibility (5-cycle round-trip stress proves stripped fields never resurrect). Companion research dossier in `docs/research/BFLD/` (11 files, 13,544 words). 49-iter implementation chain from scaffold (`feat/adr-118/p1`, `c965e3e6c`) through current head with per-iter progress comments on issue [#787](https://github.com/ruvnet/RuView/issues/787). Try it: `cargo run -p wifi-densepose-bfld --example bfld_handle`.
- **SENSE-BRIDGE — rvagent MCP server + ruvector npm + ruflo integration (ADR-124, [#787](https://github.com/ruvnet/RuView/issues/787)).** New npm package `@ruvnet/rvagent` (`tools/ruview-mcp/`) — a dual-transport [Model Context Protocol](https://modelcontextprotocol.io/) server that bridges the RuView WiFi-DensePose sensing stack to AI agents (Claude Code, Cursor, ruflo swarms). **6 of 20 ADR-124 §4.1 tools wired** in this initial release: `ruview.presence.now` (occupancy), `ruview.vitals.get_breathing` / `get_heart_rate` / `get_all` (biometric vitals via `EdgeVitalsMessage` surface, ADR-124 §6 Python ws.py:74-88 parity), `ruview.bfld.last_scan` (latest BFLD event — `identity_risk_score`, `privacy_class`, `n_frames`, `timestamp_ms`), `ruview.bfld.subscribe` (MQTT wildcard subscription with synthetic UUID envelope fallback). **Dual-transport architecture (ADR-124 §3)**: stdio (`npx @ruvnet/rvagent stdio` — recommended for Claude Code / Cursor local flow) + Streamable HTTP (`POST /mcp` bound to `127.0.0.1:3001` by default — for remote ruflo swarms across the Tailscale fleet). **Security model (ADR-124 §6)**: Origin header validation (cross-origin POST → 403), bearer-token auth slot (`RVAGENT_HTTP_TOKEN` → 401), bind default `127.0.0.1` per MCP spec requirement. **Uniform schema validation gate (ADR-124 §3)**: every `CallTool` request runs `zod.safeParse` via `TOOL_INPUT_SCHEMAS` before dispatch; failures throw `McpError(InvalidParams)`. **Full Zod schema barrel (ADR-124 §4.1 + §4.1a)**: `src/schemas/tools.ts` defines all 20 tool input schemas including the 5 RUVIEW-POLICY governance tools (can_access_vitals, can_query_presence, can_subscribe, redact_identity_fields, audit_log). **Python surface parity**: `EdgeVitalsMessage` TypeScript interface mirrors Python ws.py:74-88; ADR-124 §6 parity table drives the field names. **93 tests across 7 suites** (manifest, schemas, validate, tools, http-transport, bfld-tools, vitals-tools) — all green. Try it: `npx @ruvnet/rvagent stdio` (with `RUVIEW_SENSING_SERVER_URL=http://localhost:3000`).
- **Home Assistant + Matter integration (ADR-115).** New `--mqtt` and `--matter` flags on `wifi-densepose-sensing-server` expose the full sensing capability set to any Home Assistant install via MQTT auto-discovery (HA-DISCO) and to any Matter controller (Apple Home / Google Home / Alexa / SmartThings) via a built-in Matter Bridge scaffolding (HA-FABRIC, SDK wiring v0.7.1). Includes 21 entity kinds per node — 11 raw signals + 10 inferred semantic primitives (HA-MIND: someone-sleeping, possible-distress, room-active, elderly-inactivity-anomaly, meeting, bathroom, fall-risk, bed-exit, no-movement, multi-room-transition). The semantic primitives run server-side so `--privacy-mode` strips HR/BR/pose values from the wire while still publishing the inferred *states* — the architectural win for healthcare and AAL deployments. Ships **8 starter HA Blueprints** under `examples/ha-blueprints/`, **3 drop-in Lovelace dashboards** under `examples/lovelace/` (including a privacy-mode-compatible healthcare care view), mTLS support, 32 KB payload-size cap, MQTT-wildcard topic-injection rejection, `RUVIEW_MQTT_STRICT_TLS=1` v0.8.0 upgrade path. **420 lib tests** cover the implementation including **~2,560 fuzzed assertions per CI run** (10 proptest cases across wire-boundary security + semantic-bus invariants). Plus mosquitto-backed integration tests in `.github/workflows/mqtt-integration.yml`, criterion benchmarks beating every ADR target by 1.6×–208×, and an ESP32-S3 hardware validation harness (`scripts/validate-esp32-mqtt.sh`) that asserts the full pipeline end-to-end with a witness bundle generator (`scripts/witness-adr-115.sh`) that self-verifies. See [`docs/releases/v0.7.0-mqtt-matter.md`](docs/releases/v0.7.0-mqtt-matter.md), [`docs/integrations/home-assistant.md`](docs/integrations/home-assistant.md), [`docs/integrations/semantic-primitives-metrics.md`](docs/integrations/semantic-primitives-metrics.md), [`docs/integrations/benchmarks.md`](docs/integrations/benchmarks.md), [`docs/adr/ADR-115-home-assistant-integration.md`](docs/adr/ADR-115-home-assistant-integration.md), tracking issue [#776](https://github.com/ruvnet/RuView/issues/776), PR [#778](https://github.com/ruvnet/RuView/pull/778). Matter SDK wiring (P8b) and CSA-certification path (P10) deferred to v0.7.1+ per ADR §9.10. Try it: `cargo run -p wifi-densepose-sensing-server --features mqtt --example mqtt_publisher -- --mqtt --mqtt-host 127.0.0.1`.
- **ESP32-C6 firmware target with Wi-Fi 6 / 802.15.4 / TWT / LP-core support ([ADR-110](docs/adr/ADR-110-esp32-c6-firmware-extension.md), #762).** `firmware/esp32-csi-node` now builds for **both** `esp32s3` (existing production node) and `esp32c6` (new research/seed-node target) from the same source tree — pick via `idf.py set-target esp32c6` and ESP-IDF auto-applies the new `sdkconfig.defaults.esp32c6` overlay. Every C6 module is `#ifdef CONFIG_IDF_TARGET_ESP32C6` gated, so the S3 build is byte-identical to today (no regression).
- **Wi-Fi 6 HE-LTF subcarrier tagging** — `csi_collector.c` now reads `rx_ctrl.cur_bb_format` and writes the PPDU type (0=HT/legacy, 1=HE-SU, 2=HE-MU, 3=HE-TB) into ADR-018 frame byte 18, plus bandwidth flags (20/40 MHz, STBC, 802.15.4-sync-valid) into byte 19. Bytes 18-19 were previously reserved-zero, so old aggregators read them as before — fully backwards compatible. Magic stays `0xC5110001`. Default on via `CONFIG_CSI_FRAME_HE_TAGGING`. First firmware in the open ESP32 ecosystem to tag CSI frames with 11ax PPDU metadata.
- **802.15.4 mesh time-sync** — new `c6_timesync.{h,c}` (262 lines) provides cross-node clock alignment over the C6's separate 802.15.4 radio, freeing WiFi airtime from coordination traffic (directly addresses the ADR-029/030 multistatic synchronization gap). Protocol: lowest EUI-64 wins election, leader broadcasts `TS_BEACON` (`magic=0x54534D45`, leader epoch µs) every 100 ms on channel 15, followers compute `offset = leader_us - local_us` and apply lazily — every CSI frame is stamped with `c6_timesync_get_epoch_us()`. Target alignment ±100 µs. Default on via `CONFIG_C6_TIMESYNC_ENABLE`. Verified initializing at boot on COM6 (`c6_ts: init done: channel=15 EUI=206ef1fffefffe17 leader=yes(candidate)` at +413 ms).
- **TWT (Target Wake Time)** — new `c6_twt.{h,c}` (223 lines) wraps `esp_wifi_sta_itwt_setup` from `esp_wifi_he.h` to negotiate an individual TWT agreement with the AP after STA connect. Replaces today's opportunistic CSI capture with a scheduler-bounded one (default wake interval 10 ms = 100 fps cadence). Graceful NACK fallback: when the AP doesn't support 11ax iTWT, the helper logs and returns OK so the device keeps doing opportunistic CSI just like the S3. Teardown on `WIFI_EVENT_STA_DISCONNECTED` keeps the AP's TWT scheduler clean. Gated on `SOC_WIFI_HE_SUPPORT` (auto-set on C6/C5 chips).
- **LP-core wake-on-motion hibernation** — new `c6_lp_core.{h,c}` (134 lines) arms the C6 LP RISC-V coprocessor as an always-on motion gate; HP core stays in deep sleep until a configurable GPIO wakes it (ext1 deep-sleep wake source in this initial cut, real LP-core program in follow-up). Targets ≤5 µA hibernation current for battery-powered Cognitum Seed nodes (vs the S3's ~10 µA ULP-FSM floor). Opt-in via `CONFIG_C6_LP_CORE_ENABLE` (default off — only enabled on nodes flashed for battery-powered seed duty).
- **Build matrix**: S3 stays `partitions_display.csv` (8 MB + display + WASM), C6 uses `partitions_4mb.csv` (4 MB single OTA, no display, no WASM3, no LCD). C6 final binary 1003 KB (46% partition slack), 9 % smaller than S3 production. Free heap 310 KiB at boot, app_main reached in 343 ms, 802.15.4 stack up in another 70 ms.
- **Why this matters**: opens three research surfaces nobody has published yet — Wi-Fi-6 CSI human pose, multistatic CSI clock alignment over a side-channel radio, and TWT-bounded deterministic CSI cadence. The S3 production fleet keeps shipping the existing capabilities; the C6 is the research / battery-seed expansion target.
- **Docs**: ADR-110 (186 lines, Status=Accepted), tracking issue [ruvnet/RuView#762](https://github.com/ruvnet/RuView/issues/762) with per-phase progress comments, README hardware table + Quick-Start Option 2b, `docs/user-guide.md` full ESP32-C6 section (build, flash, provision, multi-room time-sync, battery seed mode), full empirical record in [`docs/WITNESS-LOG-110.md`](docs/WITNESS-LOG-110.md) with verified / claimed / bugs-fixed / bugs-found sections.
- **Wave 2 follow-up (D1 workaround)**: 5 systematic experiments on 3 live C6 boards confirmed the IDF v5.4 802.15.4 RX path is unfixable from user code (TX works 100 %, RX delivers 0 frames; coex/channel/OpenThread/manual-rearm all ruled out). Pivoted to ESP-NOW for the cross-node sync transport — `main/c6_sync_espnow.{h,c}` is the same TS_BEACON protocol over WiFi peer-to-peer, same `get_epoch_us / is_valid / is_leader` API surface. **120 s single-board soak: 1151 transmits, 0 failures (0.00 %), 9.6 tx/s sustained, no crash or reset.** The 802.15.4 path stays in source as documented-broken (D1) for when the IDF driver gets fixed.
- **Host-side dual-pipeline decoder for ADR-018 byte 18-19** (ADR-110 protocol closure):
- **Rust** (`v2/crates/wifi-densepose-hardware`): new `PpduType` enum (HtLegacy/HeSu/HeMu/HeTb/Unknown) and `Adr018Flags` struct (bw40/stbc/ldpc/ieee802154_sync_valid) on `CsiMetadata`. 6 new deterministic unit tests; **122/122 hardware-crate tests pass**.
- **Python** (`archive/v1/src/hardware/csi_extractor.py`): `HEADER_FMT` extended from `<IBBHIIBB2x` to `<IBBHIIBBBB`; new metadata fields (`ppdu_type`, `he_capable`, `bw40`, `stbc`, `ldpc`, `ieee802154_sync_valid`). 5 new `TestAdr110ByteEncoding` cases; **11/11 parser tests pass**.
- Both decoders match the firmware encoder bit-for-bit. Pre-ADR-110 firmware sends zeros that round-trip as `HtLegacy` + default flags — fully backwards compatible.
- **Security fix** (`scripts/redact-secrets.py` + `generate-witness-bundle.sh`): the Python proof step was echoing `.env` contents into the bundled `verification-output.log` via Pydantic validation errors. Bundle nuked before push; added a `stdin -> stdout` redaction filter covering common token prefixes, long opaque strings, and long hex runs. Verified zero leaks on rebuild.
- **Wave 3 — firmware v0.6.7 (LP-core full + soft-AP HE)**: two software-only unblocks for the hardware-blocked items in WITNESS-LOG-110 §B. (1) **Real LP-core motion-gate program** (`firmware/esp32-csi-node/main/lp_core/main.c` + integration in `c6_lp_core.c`). When `CONFIG_C6_LP_CORE_ENABLE=y`, the LP RISC-V coprocessor now runs a real polling program (configurable cadence via `CONFIG_C6_LP_POLL_PERIOD_US`, default 10 ms) that debounces N consecutive GPIO samples (`CONFIG_C6_LP_DEBOUNCE_SAMPLES`, default 3) and wakes the HP core via `ulp_lp_core_wakeup_main_processor()`. HP entry uses `esp_sleep_enable_ulp_wakeup` + `ESP_SLEEP_WAKEUP_ULP`. Exposes `c6_lp_core_motion_count()` and `c6_lp_core_poll_count()` getters for the witness harness. **Replaces** the v0.6.6 `esp_deep_sleep_enable_gpio_wakeup` ext1 fallback (which floored at ~10 µA, the same as the S3 ULP-FSM). The fallback path stays as the `else` branch so builds without `CONFIG_C6_LP_CORE_ENABLE` keep working unchanged — zero regression for v0.6.6-era fleets. Targets the C6 datasheet ≤5 µA average for battery seed nodes; pending INA/Joulescope measurement to confirm (`WITNESS-LOG-110 §B4`). (2) **Wi-Fi 6 soft-AP with TWT Responder=1** (`c6_softap_he.{h,c}` + `main.c` AP+STA mode switch). When `CONFIG_C6_SOFTAP_HE_ENABLE=y`, one C6 board can act as the iTWT-capable AP the bench is otherwise missing — pair with a second C6-STA board to negotiate real iTWT against a known-cooperative AP and measure deterministic CSI cadence (`WITNESS-LOG-110 §B1/B2`). SSID/PSK/channel configurable via Kconfig defaults or NVS (`softap_ssid`/`softap_psk`/`softap_chan` keys in the `ruview` namespace). Default off so existing nodes are unaffected. **Build artifacts**: S3 8 MB binary 1093 KB (47 % slack), C6 4 MB binary 1019 KB (45 % slack). Tag: `v0.6.7-esp32`.
- **Wave 4 — firmware v0.6.8 (ESP-NOW mesh offset smoother)**: `c6_sync_espnow.c` now maintains an in-firmware exponential-moving-average of the cross-board sync offset (α = 1/8, fixed-point shift, ≈ 8-sample window at the 10 Hz beacon rate). New getter `c6_sync_espnow_get_offset_us_smoothed()`. `c6_sync_espnow_get_epoch_us()` now returns timestamps stamped from the smoothed offset once seeded — every downstream CSI-frame consumer gets bounded-jitter alignment for free, no host-side filter required. **Measured on the bench**: 5-min two-board soak (WITNESS-LOG-110 §A0.10) drops raw offset stdev 411.5 µs → smoothed 104.1 µs (**3.95× suppression** on stdev, 4.70× on peak-to-peak range) while preserving the +30 µs/min crystal-drift trajectory within 2 µs/min. **The ADR-110 §2.4 ≤100 µs multistatic alignment target that v0.6.6 designed is now empirically measured, not just stated.** Cross-board beacon match rate 99.56% over 5 min, 0 TX failures. Binary cost: +32 bytes (one int64, one bool, one getter). Diag log adds `smoothed=…` field. Tag: `v0.6.8-esp32`. **Known wiring gap (deferred)**: `csi_serialize_frame` does not yet stamp frames with `c6_sync_espnow_get_epoch_us()` — the ADR-018 frame format has no timestamp field, and adding one is a breaking change that needs an ADR update. Multistatic CSI fusion will require either an ADR-018 v2 with timestamp, or a separate UDP sync packet keyed off the existing flag bit. Tracked in WITNESS-LOG-110 §A0.11.
- **Wave 5 — firmware v0.6.9 + v0.7.0 + host wiring (loop iter 8 → iter 26)**: closes the §A0.11 gap and lights up the substrate end-to-end across firmware → host → JSON broadcast. **Firmware**: (a) **v0.6.9-esp32**`csi_collector.c` emits a 32-byte UDP sync packet (magic `0xC511A110`, distinct from CSI frame magic `0xC5110001`) every `CONFIG_C6_SYNC_EVERY_N_FRAMES` (default 20) CSI frames, carrying `node_id`, `local_us`, mesh-aligned `epoch_us` (from the Wave 4 smoothed offset), and the CSI sequence high-water for host-side pairing. Same UDP socket as CSI; host dispatches by leading magic. Operator-tunable cadence via the new Kconfig knob — N=1 (10 Hz) for tight multistatic, N=200 (~20 s) for low-power seeds. Live-verified on COM9+COM12 (§A0.12): follower reports `local epoch = 1 163 565 µs`, matches the §A0.10 boot-delta measurement within 285 µs of WiFi MAC TX jitter. (b) **v0.7.0-esp32**`csi_collector.c:221` ADR-018 byte 19 bit 4 ("cross-node sync valid") now ORs in `c6_sync_espnow_is_valid()` so frames from sync'd ESP-NOW nodes correctly advertise sync (previously only sourced from the broken 802.15.4 path — false-negative bug, §A0.13). Side effect: S3 boards now also set the bit since `c6_sync_espnow` is cross-target. **Host decoders + 25 unit tests**: Python `SyncPacketParser` + `SyncPacket` dataclass with `apply_to_local` / `mesh_aligned_us_for_sequence` / `local_minus_epoch_us` (10 tests in `TestSyncPacketParser`); Rust `wifi_densepose_hardware::SyncPacket` + `SyncPacketFlags` + `SYNC_PACKET_MAGIC` re-exported from the crate root with identical API surface (15 tests in `sync_packet::tests`). **Cross-language conformance gate** (loop iter 21): the same 32-byte canonical hex `10a111c509010600f26db70100000000c5aca501000000001400000000000000` is pinned in both test suites; if either decoder drifts from the wire, exactly one named test fires and points at the moved side. **Sensing-server wiring**: `udp_receiver_task` magic-dispatches `0xC511A110` and stores per-node `latest_sync: Option<SyncPacket>` + `latest_sync_at: Option<Instant>` on `NodeState`. New helpers: `NodeState::mesh_aligned_us(local_us)`, `NodeState::mesh_aligned_us_for_csi_frame(sequence)` (uses the per-node measured fps EMA with 5-sample warmup + 9 s staleness gate), `NodeState::observe_csi_frame_arrival(now)` (feeds `update_csi_fps_ema` α=1/8, called once per accepted CSI frame). 4 fps-EMA tests + 3 NodeSyncSnapshot serialization tests on the binary target. **Public JSON API**: `sensing_update` broadcasts now carry an optional `sync` object per node — `{offset_us, is_leader, is_valid, smoothed, sequence, csi_fps_ema, csi_fps_samples}``#[serde(skip_serializing_if = "Option::is_none")]` so non-mesh paths (multi-BSSID scan / synthetic-RSSI fallback / simulation) omit the key entirely. Existing pre-v0.7.0 UI clients ignore it cleanly. Documented in `docs/user-guide.md` "Per-node mesh sync (ADR-110)" section with field table, UI rendering rules, and the timestamp-recovery recipe. **Branch-coordination**: `docs/ADR-110-BRANCH-STATE.md` maps which files each of `adr-110-esp32c6` vs `feat/adr-115-ha-mqtt-matter` touches (regions are disjoint, merges should be clean line-merges). **Verification baselines**: full v2 cargo workspace at **1437 tests passing** (no regression across 17 crate batches), full `wifi-densepose-hardware` crate at **137 tests**. ADR-110 §B substrate is now end-to-end visible to UI clients and ready for ADR-029/030 multistatic CSI fusion consumption.
- **Real-time CSI introspection / low-latency tap on `wifi-densepose-sensing-server` (ADR-099).**
New `wifi_densepose_sensing_server::introspection` module wires
[midstream](https://github.com/ruvnet/midstream)'s `temporal-attractor` (Lyapunov +
regime classification) and `temporal-compare` (DTW pattern matching) as a
**parallel tap** alongside RuView's existing event pipeline — no replacement,
no behaviour change to the existing `/ws/sensing` fan-out or `wifi-densepose-signal`
DSP. Two new endpoints (off by default, enabled via `--introspection`):
- `GET /ws/introspection` — newline-delimited JSON snapshots streamed at the CSI
frame rate. Each snapshot carries `frame_count`, `regime` (Idle / Periodic /
Transient / Chaotic / Unknown), `lyapunov_exponent`, `attractor_dim`,
`attractor_confidence`, `regime_changed` (boolean — flips on the first frame
after a regime transition), and `top_k_similarity[]` (highest-scoring
signature matches against a per-deployment library).
- `GET /api/v1/introspection/snapshot` — single-shot JSON snapshot, auth-gated
when `RUVIEW_API_TOKEN` is set.
Per-frame `update()` budget measured at **0.041 ms p99** on the I5 bench
(~24× under ADR-099 D4's 1 ms target). Shape-match latency on a 1-D
mean-amplitude L1 stand-in: **5 frames** (3.20× ratio vs the 16-frame event-path
floor). ADR-099 D8 honestly amended — the aspirational 10× bar is contingent on
ADR-208 Phase 2 multi-dim NPU embeddings; this release ships the tap off-by-default
while the foundation lands. 8 lib tests + 5 latency/regression tests (`tests/introspection_latency.rs`,
including a 200-frame noise warm-up → 10-frame motion-ramp signature benchmark).
- **Opt-in bearer-token auth on `wifi-densepose-sensing-server`'s `/api/v1/*` HTTP surface (closes #443).**
New `wifi_densepose_sensing_server::bearer_auth` module: when the
`RUVIEW_API_TOKEN` env var is set, every request whose path begins with
`/api/v1/` must carry an `Authorization: Bearer <token>` header (constant-time
compared) or the server responds `401 Unauthorized`. When the variable is
unset or empty the middleware is a no-op — the long-standing LAN-only
deployment posture is preserved, so this is a binary deployment-time switch
with **no default behaviour change**. `/health*`, `/ws/sensing`, and the
`/ui/*` static mount are intentionally never gated (orchestrator probes +
local browsers). Startup logs which mode is active and warns when auth is on
with a `0.0.0.0` bind. 8 unit tests on the middleware (lib test count 191 → 199).
Resolves the security audit raised in #443.
### Changed
- **Docker image: build-time guard for the UI assets, plus a CI workflow that
rebuilds and pushes on every change (closes #520, #514).** `docker/Dockerfile.rust`
now `RUN`s a guard after `COPY ui/` that fails the build if any of
`index.html` / `observatory.html` / `pose-fusion.html` / `viz.html` / the
`observatory/` / `pose-fusion/` / `components/` / `services/` directories are
missing, so a stale image can never be silently produced again. New
`.github/workflows/sensing-server-docker.yml` builds the image on push to
`main` (paths-filtered) and on `v*` tags and pushes to both
`docker.io/ruvnet/wifi-densepose` and `ghcr.io/ruvnet/wifi-densepose` with
`latest` + `vX.Y.Z` + `sha-<short>` tags, then smoke-tests the published
artifact: `/health`, `/api/v1/info`, the observatory + pose-fusion UI assets,
and the `RUVIEW_API_TOKEN` auth path (no token → 401, wrong → 401, correct
→ 200). Uses `DOCKERHUB_USERNAME` / `DOCKERHUB_TOKEN` repo secrets for the
Docker Hub push; ghcr.io uses the workflow's `GITHUB_TOKEN`.
- **rvCSI moved to its own repo and is now vendored as a submodule.** The 9 `rvcsi-*`
crates (`rvcsi-core`/`-dsp`/`-events`/`-adapter-file`/`-adapter-nexmon`/`-ruvector`/
`-runtime`/`-node`/`-cli` — added inline in #542) now live in
[`github.com/ruvnet/rvcsi`](https://github.com/ruvnet/rvcsi): published to crates.io
as `rvcsi-* 0.3.x`, to npm as `@ruv/rvcsi`, with a Claude Code plugin marketplace and
a RuView-style README. RuView vendors it under `vendor/rvcsi` (alongside
`vendor/ruvector` / `vendor/midstream` / `vendor/sublinear-time-solver`) and no longer
carries inline copies in `v2/crates/`; consumers depend on the published crates (or the
submodule's `crates/rvcsi-*` paths). `v2/Cargo.toml`, `CLAUDE.md`, and the README docs
table updated accordingly. The ADRs (ADR-095, ADR-096), PRD, and DDD model stay in
`docs/` here as the design record of the incubation.
### Fixed
- **README: corrected the camera-supervised pose-accuracy claim.** The README stated
"92.9% PCK@20" for camera-supervised training; that figure does not appear in
ADR-079 and is ~2.6× the ADR's own success target (>35% PCK@20). ADR-079 phases
P7 (data collection), P8 (training + evaluation on real paired data) and P9
(cross-room LoRA) are still `Pending`, so no measured camera-supervised PCK@20 has
been published. README now states the proxy-supervised baseline (≈2.5%) and the
ADR-079 target (35%+), and notes the eval phases are pending. Surfaced by the
PowerPlatePulse training-pipeline audit (2026-05-11); 6 remaining audit findings
tracked in the PR.
- **rvCSI `BaselineDriftDetector`: drift thresholds are now scale-relative, not absolute.**
The detector compared `mean_amplitude` against its EWMA baseline with absolute
thresholds (`anomaly_threshold = 1.0`, `drift_threshold = 0.15`) — fine for the
synthetic unit tests (amplitudes ≈ 1.0), but raw ESP32 CSI is `int8` I/Q with
amplitudes up to ~128, so the window-to-window RMS distance is routinely 550 ≫ 1.0
and `AnomalyDetected` fired on ~96 % of windows (319/331 on a real node-1 capture).
Drift is now `‖current baseline‖₂ / ‖baseline‖₂` (a fraction, with an `eps` floor
for a degenerate near-zero baseline), so one tuning works across raw-`int8` ESP32,
`int16`-scaled Nexmon, and baseline-subtracted streams alike — `AnomalyDetected`
drops to 40/331 on the same data, the existing detector tests still pass, and a
`baseline_drift_is_scale_invariant_no_anomaly_storm` regression test was added.
ADR-095 D13 / ADR-096 §2.1, §5 updated. Surfaced by an end-to-end test against
real ESP32 CSI (a 7,000-frame node-1 capture; transcoder at
`scripts/esp32_jsonl_to_rvcsi.py`).
### Added
- **rvCSI — edge RF sensing runtime (design + first implementation).** New subsystem **rvCSI**: a Rust-first / TypeScript-accessible / hardware-abstracted edge RF sensing runtime that normalizes WiFi CSI from Nexmon, ESP32, Intel, Atheros, file and replay sources into one validated `CsiFrame` schema, runs reusable DSP, emits typed confidence-scored events, and bridges to RuVector RF memory, an MCP tool server and a TS SDK.
- **Design docs:** `docs/prd/rvcsi-platform-prd.md` (purpose, users, success criteria, FR1FR10, NFRs, system architecture, data model); `docs/adr/ADR-095-rvcsi-edge-rf-sensing-platform.md` (the 15 architectural decisions: Rust core, C-at-the-boundary, TS SDK via napi-rs, normalized schema, validate-before-FFI, CSI-as-temporal-delta, RuVector as RF memory, replayability, detection≠decision, local-first, read-first/write-gated MCP, mandatory quality scoring, versioned calibration, plugin adapters); `docs/adr/ADR-096-rvcsi-ffi-crate-layout.md` (crate topology, the napi-c shim record format & contract, the napi-rs Node surface, build/test invariants); `docs/ddd/rvcsi-domain-model.md` (7 bounded contexts: Capture, Validation, Signal, Calibration, Event, Memory, Agent — with aggregates, invariants, context map and domain services). Indexed in `docs/adr/README.md` and `docs/ddd/README.md`.
- **Crates** (9 new `v2/crates/rvcsi-*` workspace members): `rvcsi-core` (normalized `CsiFrame`/`CsiWindow`/`CsiEvent` schema, `AdapterProfile`, `CsiSource` plugin trait, id newtypes + `IdGenerator`, `RvcsiError`, the `validate_frame` pipeline + quality scoring; `forbid(unsafe_code)`); `rvcsi-adapter-nexmon` — the **napi-c** seam: `native/rvcsi_nexmon_shim.{c,h}` (the only C in the runtime — allocation-free, bounds-checked, ABI `1.1`), compiled via `build.rs`+`cc`, handling **two byte formats** — the compact self-describing "rvCSI Nexmon record", and the **real nexmon_csi UDP payload** (the 18-byte `magic 0x1111 · rssi · fctl · src_mac · seq · core/stream · chanspec · chip_ver` header + `nsub` int16 I/Q samples, the modern BCM43455c0/4358/4366c0 export read by CSIKit/`csireader.py`), with a Broadcom d11ac **chanspec decoder** (channel/bandwidth/band) — plus a pure-Rust **libpcap reader** (classic `.pcap`, all byte-order/timestamp-resolution magics, Ethernet/raw-IPv4/Linux-SLL link types) and a **Nexmon-chip / Raspberry-Pi-model registry** (`NexmonChip` / `RaspberryPiModel` — including the **Raspberry Pi 5** (CYW43455/BCM43455c0, same wireless as the Pi 4 — 20/40/80 MHz, 2.4+5 GHz, 64/128/256 subcarriers), the Pi 3B+/4/400, and the Pi Zero 2 W (BCM43436b0); `nexmon_adapter_profile` / `raspberry_pi_profile` build the per-chip `AdapterProfile`; `chip_ver` words auto-resolve to a chip). Wrapped by a documented `ffi` module and two `CsiSource`s: `NexmonAdapter` (record buffers) and `NexmonPcapAdapter` (real nexmon_csi UDP inside a `tcpdump -i wlan0 dst port 5500 -w csi.pcap` capture — the pcap timestamp stamps each frame; the chip is auto-detected from `chip_ver`, overridable via `.with_pi_model(Pi5)` / `.with_chip(...)`). `rvcsi-dsp` (DC removal, phase unwrap, smoothing, Hampel/MAD filter, sliding variance, baseline subtraction, motion-energy/presence/confidence features, heuristic breathing-band estimate, non-destructive `SignalPipeline`); `rvcsi-events` (`WindowBuffer`, the `EventDetector` trait + presence/motion/quality/baseline-drift state machines, `EventPipeline`; the baseline-drift detector uses **scale-relative** thresholds — drift as a fraction of the baseline's RMS magnitude — so one tuning works across raw-`int8` ESP32, `int16`-scaled Nexmon, and baseline-subtracted streams alike); `rvcsi-adapter-file` (the `.rvcsi` JSONL capture format, `FileRecorder`, `FileReplayAdapter` deterministic replay); `rvcsi-ruvector` (deterministic window/event embeddings, `cosine_similarity`, the `RfMemoryStore` trait, `InMemoryRfMemory` + `JsonlRfMemory` — a standin until the production RuVector binding); `rvcsi-runtime` (the no-FFI composition layer: `CaptureRuntime` = `CsiSource` + `validate_frame` + `SignalPipeline` + `EventPipeline`, plus one-shot helpers `summarize_capture`/`decode_nexmon_records`/`decode_nexmon_pcap`/`summarize_nexmon_pcap`/`events_from_capture`/`export_capture_to_rf_memory`); `rvcsi-node` — the **napi-rs** seam (a `["cdylib","rlib"]` Node addon, `build.rs` runs `napi_build::setup()`; thin `#[napi]` wrappers over `rvcsi-runtime``nexmonDecodeRecords`/`nexmonDecodePcap` (with optional `chip`)/`inspectNexmonPcap`/`decodeChanspec`/`nexmonChipName`/`nexmonProfile`/`nexmonChips`/`inspectCaptureFile`/`eventsFromCaptureFile`/`exportCaptureToRfMemory` + an `RvcsiRuntime` streaming class; everything that crosses to JS is a validated/normalized struct serialized to JSON); `rvcsi-cli` (the `rvcsi` binary: `record` (Nexmon-dump *or* `--source nexmon-pcap [--chip pi5]``.rvcsi`), `inspect`, `inspect-nexmon`, `nexmon-chips`, `decode-chanspec`, `replay`, `stream`, `events`, `health`, `calibrate` v0-baseline, `export ruvector`). Plus the `@ruv/rvcsi` npm package (`package.json`/`index.js`/`index.d.ts`/`README`/`__test__`) alongside `rvcsi-node` — a curated JS surface that parses the addon's JSON into plain `CsiFrame`/`CsiWindow`/`CsiEvent`/`SourceHealth`/`CaptureSummary`/`NexmonPcapSummary`/`DecodedChanspec` objects, with a lazy native-addon load.
- **Tests:** 169 across the rvcsi crates (core 29, dsp 28, events 19 — incl. a baseline-drift scale-invariance regression, adapter-file 20 + 1 doctest, adapter-nexmon 28 — round-tripping through the C shim and synthetic libpcap files, incl. Pi 5 / chip-detection, ruvector 20 + 1 doctest, runtime 13, cli 10), 0 failures; all rvcsi crates build together and are clippy-clean (`rvcsi-node` under `deny(clippy::all)`); `forbid(unsafe_code)` everywhere except `rvcsi-adapter-nexmon` (FFI, every `unsafe` block documented). Also exercised end-to-end against a real 7,000-frame ESP32 node-1 capture (transcoded with `scripts/esp32_jsonl_to_rvcsi.py` — the stand-in for the not-yet-shipped `record --source esp32-jsonl`): `rvcsi inspect`/`replay`/`calibrate`/`events` all run on real hardware data. Not yet wired in: live radio capture, `rvcsi-adapter-esp32` (live serial/UDP ESP32 source), the WebSocket daemon (`rvcsi-daemon`), the MCP tool server (`rvcsi-mcp`), and the legacy nexmon *packed-float* CSI export — follow-ups on top of these crates.
- **`wifi-densepose-train`: `signal_features` module — wires `wifi-densepose-signal` into the training pipeline.** `wifi-densepose-signal` was previously a phantom dependency of `wifi-densepose-train` (listed in `Cargo.toml`, never imported). New `wifi_densepose_train::signal_features::extract_signal_features` (and `CsiSample::signal_features()`) run a windowed CSI observation's centre frame through `wifi_densepose_signal::features::FeatureExtractor`, producing a fixed-length (`FEATURE_LEN = 12`) amplitude/phase/PSD feature vector — the hook for a future vitals / multi-task supervision head (breathing- and heart-rate-band power are read off the PSD summary). The vector is produced on demand and not yet fed back into the loss. Surfaced by the 2026-05-11 training-pipeline audit (findings #1 "vitals features absent from training" and #2 "`wifi-densepose-signal` ghost dep").
- **`wifi-densepose-train`: `TrainingConfig` subcarrier-layout presets + a real-loader integration test.** New `TrainingConfig::for_subcarriers(native, target)` plus named presets `ht40_192()` (≈192-sc ESP32 HT40 → 56) and `multiband_168()` (168-sc ADR-078 multi-band mesh → 56), so non-MM-Fi CSI shapes are first-class instead of requiring manual `native_subcarriers`/`num_subcarriers` overrides; field docs now list the supported source counts and the multi-NIC mapping. New `tests/test_real_loader.rs` round-trips synthetic CSI through `.npy` files → `MmFiDataset::discover`/`get` (including the subcarrier-interpolation branch and the empty-root case) — exercising the on-disk loader path the deterministic `verify-training` proof intentionally bypasses. Addresses training-pipeline audit findings #6 (56-sc/1-NIC config default) and #7 (multi-band mesh not in config); the #4 concern ("proof uses synthetic data") is reframed — the proof *should* use a reproducible source, and this test covers the real loader it skips.
### Fixed
- **HuggingFace `MODEL_CARD.md`: marked the PIR/BME280 environmental-sensor ground-truth path as planned, not implemented** (training-pipeline audit finding #3) — the card presented PIR/BME280 weak-label fine-tuning as a current capability; there is no env-sensor ingestion in the training pipeline today.
- **README: corrected the camera-supervised pose-accuracy claim** (audit finding #5; see PR #535) — "92.9% PCK@20" → the ADR-079 target (35%+; proxy baseline 35.3%), noting P7/P8/P9 are pending.
### Added
- **`RollingP95` adaptive feature normalizer** (`v2/crates/wifi-densepose-sensing-server`) —
Streaming P95 estimator (600-sample / ~30 s sliding window) that self-calibrates
feature normalization to whatever distribution the deployment produces. Replaces
fixed-scale denominators (`variance/300`, `motion/250`, `spectral/500`) which saturated
when live ESP32 values exceeded those limits, collapsing dynamic range to zero.
Cold-start (<60 samples) falls back to the legacy denominators so day-0 behaviour
is preserved. Deployment-neutral: no hardcoded values. (ADR-044 §5.2)
- **`dedup_factor` runtime configuration API** (`v2/crates/wifi-densepose-sensing-server`) —
Exposes the multi-node person-count deduplication divisor at runtime via REST:
- `GET /api/v1/config/dedup-factor` — read current value.
- `POST /api/v1/config/dedup-factor` — set value (clamped 1.010.0, persisted).
- `POST /api/v1/config/ground-truth` — auto-tunes `dedup_factor` from a known
person count (`{"count": N}`); derives optimal divisor from current node-sum.
Config is persisted to `data/config.json` and reloaded on restart. (ADR-044 §5.3)
- **`nvsim` crate — deterministic NV-diamond magnetometer pipeline simulator** (ADR-089) —
New standalone leaf crate at `v2/crates/nvsim` modeling a forward-only
magnetic sensing path: scene → source synthesis (BiotSavart, dipole,
current loop, ferrous induced moment) → material attenuation
(Air/Drywall/Brick/Concrete/Reinforced/SteelSheet) → NV ensemble
(4 〈111〉 axes, ODMR linear-readout proxy, shot-noise floor per
Wolf 2015 / Barry 2020) → 16-bit ADC + lock-in demodulation →
fixed-layout `MagFrame` records → SHA-256 witness. Six-pass build
per `docs/research/quantum-sensing/15-nvsim-implementation-plan.md`.
50 tests, ~4.5 M samples/s on x86_64 (4500× the Cortex-A53 1 kHz
acceptance gate), pinned reference witness
`cc8de9b01b0ff5bd97a6c17848a3f156c174ea7589d0888164a441584ec593b4`
for byte-equivalence regression. WASM-ready by construction
(zero `std::time/fs/env/process/thread`); builds cleanly for
`wasm32-unknown-unknown`. ADR-090 (Proposed, conditional) tracks the
optional Lindblad/Hamiltonian extension if AC magnetometry, MW power
saturation, hyperfine spectroscopy, or pulsed protocols become required.
### Fixed
- **WebSocket broadcast handler now handles Lagged events gracefully and sends periodic ping keepalives to prevent dashboard disconnects** —
`handle_ws_client` and `handle_ws_pose_client` in `wifi-densepose-sensing-server`
were treating `RecvError::Lagged` as a fatal error, causing instant disconnect
when clients fell behind the 256-frame broadcast buffer at 10 Hz ingest.
Clients would reconnect, immediately lag again, and rapid-cycle every 24 s.
`Lagged` now continues (drops missed frames, logs debug) rather than breaking.
Added 30 s ping keepalive on the sensing handler to prevent proxy idle timeouts.
- **Ghost skeletons in live UI with multi-node ESP32 setups** (#420, ADR-082) —
`tracker_bridge::tracker_to_person_detections` documented itself as filtering
to `is_alive()` tracks but in fact passed every non-Terminated track to the
WebSocket stream. `Lost` tracks — kept inside `reid_window` for
re-identification but not currently observed — were rendering as phantom
skeletons, accumulating to 22-24 with 3 nodes × 10 Hz CSI while
`estimated_persons` correctly reported 1. Added
`PoseTracker::confirmed_tracks()` (Tentative + Active only) and rewired the
bridge to use it. Lost tracks remain in the tracker for re-ID; they just
no longer ship to the UI. Regression test:
`test_lost_tracks_excluded_from_bridge_output`.
- **Rust workspace build with `--no-default-features` on Windows** (#366, #415) —
`wifi-densepose-mat`, `wifi-densepose-sensing-server`, and `wifi-densepose-train`
all depended on `wifi-densepose-signal` with default features enabled, which
pulled `ndarray-linalg``openblas-src` → vcpkg/system-BLAS through the entire
workspace. `--no-default-features` at the workspace root then could not opt out
of BLAS, breaking `cargo build` / `cargo test` on Windows without vcpkg. All
three consumers now declare `wifi-densepose-signal = { ..., default-features = false }`,
so `cargo test --workspace --no-default-features` builds cleanly without
vcpkg/openblas. Validated: 1,538 tests pass, 0 fail, 8 ignored.
- **`signal` test `test_estimate_occupancy_noise_only` failed without `eigenvalue`** —
The test unwrapped the `NotCalibrated` stub returned when the BLAS-backed
`estimate_occupancy` is compiled out. Gated with `#[cfg(feature = "eigenvalue")]`
so it only runs when the real implementation is available.
## [v0.6.2-esp32] — 2026-04-20
Firmware release cutting ADR-081 and the Timer Svc stack fix discovered during
@@ -393,11 +122,7 @@ firing cleanly, HEALTH mesh packets sent.
Kconfig surface added under "Adaptive Controller (ADR-081)".
### Fixed
- **Firmware: SPI flash cache crash under high CSI callback pressure** (RuView#396, #397) — ESP32-S3 nodes crashed in `cache_ll_l1_resume_icache` / `wDev_ProcessFiq` after ~2400 callbacks when the promiscuous filter admitted DATA frames at 100500 Hz. Fixed by narrowing the filter mask to `WIFI_PROMIS_FILTER_MASK_MGMT` (~10 Hz beacons), adding a 50 Hz early callback rate gate (`CSI_MIN_PROCESS_INTERVAL_US`) that drops excess callbacks before any processing work, and enabling `CONFIG_ESP_WIFI_EXTRA_IRAM_OPT=y` as defense-in-depth. Stability validated with a 4-min-per-node soak.
- **Firmware: `filter_mac` / `node_id` clobber by WiFi driver init** (#232, #375, #385, #386, #390, #397) — `g_nvs_config` can be corrupted during `wifi_init_sta()` on some devices (confirmed on `80:b5:4e:c1:be:b8`), reverting `node_id` to the Kconfig default and producing garbage MAC-filter reads in the CSI callback (100500 Hz). New `csi_collector_set_node_id()` API called from `app_main()` **before** `wifi_init_sta()` captures both fields into module-local statics (`s_node_id`, `s_filter_mac`, `s_filter_mac_set`). `csi_collector_init()` now runs a canary that distinguishes "early≠g_nvs_config" (corruption confirmed) from a no-op match. All CSI runtime paths use the defensive copies exclusively.
- **Firmware: `edge_processing` sample rate mismatch** (#397) — `estimate_bpm_zero_crossing()` was called with a hard-coded `sample_rate = 20.0f`, but MGMT-only promiscuous delivers ~10 Hz. Breathing and heart-rate reports were 2× too high. Corrected to `10.0f` with an explicit comment tying it to the callback rate.
- **`provision.py` esptool command form** (#391, #397) — ESP-IDF v5.4 bundles `esptool 4.10.0`, which only accepts `write_flash` (underscore). Standalone `pip install esptool` v5.x accepts both forms but prefers `write-flash`. #391 switched to `write-flash` which broke the documented ESP-IDF Python venv flow; #397 reverts to `write_flash` (works with both esptool 4.x and 5.x) with an inline comment warning future maintainers not to "re-fix" it.
- **`provision.py` esptool v5 dry-run hint** (#391) — Stale `write_flash` (underscore) syntax in the dry-run manual-flash hint now uses `write-flash` (hyphenated) for esptool >= 5.x. The primary flash command was already correct.
- **`provision.py` esptool v5 compat** (#391) — Stale `write_flash` (underscore) syntax in the dry-run manual-flash hint now uses `write-flash` (hyphenated) for esptool >= 5.x. The primary flash command was already correct.
- **`provision.py` silent NVS wipe** (#391) — The script replaces the entire `csi_cfg` NVS namespace on every run, so partial invocations were silently erasing WiFi credentials and causing `Retrying WiFi connection (10/10)` in the field. Now refuses to run without `--ssid`, `--password`, and `--target-ip` unless `--force-partial` is passed. `--force-partial` prints a warning listing which keys will be wiped.
- **Firmware: defensive `node_id` capture** (#232, #375, #385, #386, #390) — Users on multi-node deployments reported `node_id` reverting to the Kconfig default (`1`) in UDP frames and in the `csi_collector` init log, despite NVS loading the correct value. The root cause (memory corruption of `g_nvs_config`) has not been definitively isolated, but the UDP frame header is now tamper-proof: `csi_collector_init()` captures `g_nvs_config.node_id` into a module-local `s_node_id` once, and `csi_serialize_frame()` plus all other consumers (`edge_processing.c`, `wasm_runtime.c`, `display_ui.c`, `swarm_bridge_init`) read it via the new `csi_collector_get_node_id()` accessor. A canary logs `WARN` if `g_nvs_config.node_id` diverges from `s_node_id` at end-of-init, helping isolate the upstream corruption path. Validated on attached ESP32-S3 (COM8): NVS `node_id=2` propagates through boot log, capture log, init log, and byte[4] of every UDP frame.
@@ -435,7 +160,7 @@ Model release (no new firmware binary). Firmware remains at v0.6.0-esp32.
- Security fix merged via PR #310.
### Performance
- Presence detection: 100% accuracy on 60,630 overnight samples. *(Retracted — that recording was single-class (one sleeping person, 6,062/6,063 frames "present"), so a constant "yes" scores ~99.98%. Superseded by the honest 82.3% held-out temporal-triplet metric; see [#882](https://github.com/ruvnet/RuView/issues/882). Kept here as the in-place public record.)*
- Presence detection: 100% accuracy on 60,630 overnight samples.
- Inference: 0.008 ms per sample, 164K embeddings/sec.
- Contrastive self-supervised training: 51.6% improvement over baseline.
@@ -769,7 +494,7 @@ Major release: complete Rust sensing server, full DensePose training pipeline, R
- `PresenceClassifier` — rule-based 3-state classification (ABSENT / PRESENT_STILL / ACTIVE)
- Cross-receiver agreement scoring for multi-AP confidence boosting
- WebSocket sensing server (`ws_server.py`) broadcasting JSON at 2 Hz
- Deterministic CSI proof bundles for reproducible verification (`archive/v1/data/proof/`)
- Deterministic CSI proof bundles for reproducible verification (`v1/data/proof/`)
- Commodity sensing unit tests (`b391638`)
### Changed
@@ -777,7 +502,7 @@ Major release: complete Rust sensing server, full DensePose training pipeline, R
### Fixed
- Review fixes for end-to-end training pipeline (`45f0304`)
- Dockerfile paths updated from `src/` to `archive/v1/src/` (`7872987`)
- Dockerfile paths updated from `src/` to `v1/src/` (`7872987`)
- IoT profile installer instructions updated for aggregator CLI (`f460097`)
- `process.env` reference removed from browser ES module (`e320bc9`)
+36 -36
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@@ -3,25 +3,25 @@
## Project: wifi-densepose
WiFi-based human pose estimation using Channel State Information (CSI).
Dual codebase: Python v1 (`v1/`) and Rust port (`v2/`).
Dual codebase: Python v1 (`v1/`) and Rust port (`rust-port/wifi-densepose-rs/`).
### Key Rust Crates
| Crate | Description |
|-------|-------------|
| `wifi-densepose-core` | Core types, traits, error types, CSI frame primitives |
| `wifi-densepose-signal` | SOTA signal processing + RuvSense multistatic sensing (16 modules) |
| `wifi-densepose-signal` | SOTA signal processing + RuvSense multistatic sensing (14 modules) |
| `wifi-densepose-nn` | Neural network inference (ONNX, PyTorch, Candle backends) |
| `wifi-densepose-train` | Training pipeline with ruvector integration + ruview_metrics |
| `wifi-densepose-mat` | Mass Casualty Assessment Tool — disaster survivor detection |
| `wifi-densepose-hardware` | ESP32 aggregator, TDM protocol, channel hopping firmware |
| `wifi-densepose-ruvector` | RuVector v2.0.4 integration + cross-viewpoint fusion (5 modules) |
| `wifi-densepose-api` | REST API (Axum) |
| `wifi-densepose-db` | Database layer (Postgres, SQLite, Redis) |
| `wifi-densepose-config` | Configuration management |
| `wifi-densepose-wasm` | WebAssembly bindings for browser deployment |
| `wifi-densepose-cli` | CLI tool (`wifi-densepose` binary) |
| `wifi-densepose-sensing-server` | Lightweight Axum server for WiFi sensing UI |
| `wifi-densepose-wifiscan` | Multi-BSSID WiFi scanning (ADR-022) |
| `wifi-densepose-vitals` | ESP32 CSI-grade vital sign extraction (ADR-021) |
| `nvsim` | Deterministic NV-diamond magnetometer pipeline simulator (ADR-089) — standalone leaf, WASM-ready |
| `vendor/rvcsi` (submodule) | **rvCSI** — edge RF sensing runtime (ADR-095/096): 9 crates (`rvcsi-core`/`-dsp`/`-events`/`-adapter-file`/`-adapter-nexmon`/`-ruvector`/`-runtime`/`-node`/`-cli`). Lives in its own repo ([github.com/ruvnet/rvcsi](https://github.com/ruvnet/rvcsi)), vendored here under `vendor/rvcsi`, published to crates.io as `rvcsi-* 0.3.x` and to npm as `@ruv/rvcsi`. Not a `v2/` workspace member — depend on the published crates (or the submodule's `crates/rvcsi-*` paths). Normalized `CsiFrame`/`CsiWindow`/`CsiEvent` schema, validate-before-FFI, reusable DSP, typed confidence-scored events, the napi-c Nexmon shim (real nexmon_csi `.pcap` from a Raspberry Pi 5 / 4 / 3B+ — BCM43455c0), the napi-rs SDK, the `rvcsi` CLI, a Claude Code plugin. |
| `ruview-swarm` | Drone swarm control system (ADR-148) — hierarchical-mesh topology, Raft consensus, MARL, CSI sensing payload, MAVLink/PX4 compat, Ruflo AI-agent integration |
### RuvSense Modules (`signal/src/ruvsense/`)
| Module | Purpose |
@@ -39,8 +39,6 @@ Dual codebase: Python v1 (`v1/`) and Rust port (`v2/`).
| `cross_room.rs` | Environment fingerprinting, transition graph |
| `gesture.rs` | DTW template matching gesture classifier |
| `adversarial.rs` | Physically impossible signal detection, multi-link consistency |
| `cir.rs` | ADR-134 CSI→CIR via ISTA L1 sparse recovery (NeumannSolver warm-start) |
| `calibration.rs` | ADR-135 empty-room baseline (Welford amplitude + von Mises phase, drift trigger) |
### Cross-Viewpoint Fusion (`ruvector/src/viewpoint/`)
| Module | Purpose |
@@ -71,15 +69,14 @@ All 5 ruvector crates integrated in workspace:
- ADR-030: RuvSense persistent field model (Proposed)
- ADR-031: RuView sensing-first RF mode (Proposed)
- ADR-032: Multistatic mesh security hardening (Proposed)
- ADR-148: Drone swarm control system / `ruview-swarm` (In Progress)
### Supported Hardware
| Device | Port | Chip | Role | Cost |
|--------|------|------|------|------|
| ESP32-S3 (8MB flash) | COM9 (ruvzen, was COM7) | Xtensa dual-core | WiFi CSI sensing node | ~$9 |
| ESP32-S3 (8MB flash) | COM7 | Xtensa dual-core | WiFi CSI sensing node | ~$9 |
| ESP32-S3 SuperMini (4MB) | — | Xtensa dual-core | WiFi CSI (compact) | ~$6 |
| ESP32-C6 + Seeed MR60BHA2 | COM12 (ruvzen, was COM4) | RISC-V + 60 GHz FMCW | mmWave HR/BR/presence + WiFi CSI | ~$15 |
| ESP32-C6 + Seeed MR60BHA2 | COM4 | RISC-V + 60 GHz FMCW | mmWave HR/BR/presence | ~$15 |
| HLK-LD2410 | — | 24 GHz FMCW | Presence + distance | ~$3 |
**Not supported:** ESP32 (original), ESP32-C3 — single-core, can't run CSI DSP pipeline.
@@ -87,17 +84,17 @@ All 5 ruvector crates integrated in workspace:
### Build & Test Commands (this repo)
```bash
# Rust — full workspace tests (1,031+ tests, ~2 min)
cd v2
cd rust-port/wifi-densepose-rs
cargo test --workspace --no-default-features
# Rust — single crate check (no GPU needed)
cargo check -p wifi-densepose-train --no-default-features
# Python — deterministic proof verification (SHA-256)
python archive/v1/data/proof/verify.py
python v1/data/proof/verify.py
# Python — test suite
cd archive/v1 && python -m pytest tests/ -x -q
cd v1 && python -m pytest tests/ -x -q
```
### ESP32 Firmware Build (Windows — Python subprocess required)
@@ -136,14 +133,17 @@ Crates must be published in dependency order:
2. `wifi-densepose-vitals` (no internal deps)
3. `wifi-densepose-wifiscan` (no internal deps)
4. `wifi-densepose-hardware` (no internal deps)
5. `wifi-densepose-signal` (depends on core)
6. `wifi-densepose-nn` (no internal deps, workspace only)
7. `wifi-densepose-ruvector` (no internal deps, workspace only)
8. `wifi-densepose-train` (depends on signal, nn)
9. `wifi-densepose-mat` (depends on core, signal, nn)
10. `wifi-densepose-wasm` (depends on mat)
11. `wifi-densepose-sensing-server` (depends on wifiscan)
12. `wifi-densepose-cli` (depends on mat)
5. `wifi-densepose-config` (no internal deps)
6. `wifi-densepose-db` (no internal deps)
7. `wifi-densepose-signal` (depends on core)
8. `wifi-densepose-nn` (no internal deps, workspace only)
9. `wifi-densepose-ruvector` (no internal deps, workspace only)
10. `wifi-densepose-train` (depends on signal, nn)
11. `wifi-densepose-mat` (depends on core, signal, nn)
12. `wifi-densepose-api` (no internal deps)
13. `wifi-densepose-wasm` (depends on mat)
14. `wifi-densepose-sensing-server` (depends on wifiscan)
15. `wifi-densepose-cli` (depends on mat)
### Validation & Witness Verification (ADR-028)
@@ -151,12 +151,12 @@ Crates must be published in dependency order:
```bash
# 1. Rust tests — must be 1,031+ passed, 0 failed
cd v2
cd rust-port/wifi-densepose-rs
cargo test --workspace --no-default-features
# 2. Python proof — must print VERDICT: PASS
cd ..
python archive/v1/data/proof/verify.py
cd ../..
python v1/data/proof/verify.py
# 3. Generate witness bundle (includes both above + firmware hashes)
bash scripts/generate-witness-bundle.sh
@@ -169,8 +169,8 @@ bash VERIFY.sh
**If the Python proof hash changes** (e.g., numpy/scipy version update):
```bash
# Regenerate the expected hash, then verify it passes
python archive/v1/data/proof/verify.py --generate-hash
python archive/v1/data/proof/verify.py
python v1/data/proof/verify.py --generate-hash
python v1/data/proof/verify.py
```
**Witness bundle contents** (`dist/witness-bundle-ADR028-<sha>.tar.gz`):
@@ -183,9 +183,9 @@ python archive/v1/data/proof/verify.py
- `VERIFY.sh` — One-command self-verification for recipients
**Key proof artifacts:**
- `archive/v1/data/proof/verify.py` — Trust Kill Switch: feeds reference signal through production pipeline, hashes output
- `archive/v1/data/proof/expected_features.sha256` — Published expected hash
- `archive/v1/data/proof/sample_csi_data.json` — 1,000 synthetic CSI frames (seed=42)
- `v1/data/proof/verify.py` — Trust Kill Switch: feeds reference signal through production pipeline, hashes output
- `v1/data/proof/expected_features.sha256` — Published expected hash
- `v1/data/proof/sample_csi_data.json` — 1,000 synthetic CSI frames (seed=42)
- `docs/WITNESS-LOG-028.md` — 11-step reproducible verification procedure
- `docs/adr/ADR-028-esp32-capability-audit.md` — Complete audit record
@@ -211,13 +211,13 @@ Active feature branch: `ruvsense-full-implementation` (PR #77)
- NEVER save to root folder — use the directories below
- `docs/adr/` — Architecture Decision Records (43 ADRs)
- `docs/ddd/` — Domain-Driven Design models
- `v2/crates/` — Rust workspace crates (15 crates)
- `v2/crates/wifi-densepose-signal/src/ruvsense/` — RuvSense multistatic modules (14 files)
- `v2/crates/wifi-densepose-ruvector/src/viewpoint/` — Cross-viewpoint fusion (5 files)
- `v2/crates/wifi-densepose-hardware/src/esp32/` — ESP32 TDM protocol
- `rust-port/wifi-densepose-rs/crates/` — Rust workspace crates (15 crates)
- `rust-port/wifi-densepose-rs/crates/wifi-densepose-signal/src/ruvsense/` — RuvSense multistatic modules (14 files)
- `rust-port/wifi-densepose-rs/crates/wifi-densepose-ruvector/src/viewpoint/` — Cross-viewpoint fusion (5 files)
- `rust-port/wifi-densepose-rs/crates/wifi-densepose-hardware/src/esp32/` — ESP32 TDM protocol
- `firmware/esp32-csi-node/main/` — ESP32 C firmware (channel hopping, NVS config, TDM)
- `archive/v1/src/` — Python source (core, hardware, services, api)
- `archive/v1/data/proof/` — Deterministic CSI proof bundles
- `v1/src/` — Python source (core, hardware, services, api)
- `v1/data/proof/` — Deterministic CSI proof bundles
- `.claude-flow/` — Claude Flow coordination state (committed for team sharing)
- `.claude/` — Claude Code settings, agents, memory (committed for team sharing)
@@ -243,7 +243,7 @@ Active feature branch: `ruvsense-full-implementation` (PR #77)
Before merging any PR, verify each item applies and is addressed:
1. **Rust tests pass**`cargo test --workspace --no-default-features` (1,031+ passed, 0 failed)
2. **Python proof passes**`python archive/v1/data/proof/verify.py` (VERDICT: PASS)
2. **Python proof passes**`python v1/data/proof/verify.py` (VERDICT: PASS)
3. **README.md** — Update platform tables, crate descriptions, hardware tables, feature summaries if scope changed
4. **CLAUDE.md** — Update crate table, ADR list, module tables, version if scope changed
5. **CHANGELOG.md** — Add entry under `[Unreleased]` with what was added/fixed/changed
+2038 -330
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@@ -1,50 +0,0 @@
# AetherArena ("AA") — The Official Spatial-Intelligence Benchmark
> **Public leaderboard. Private evaluation split. Open scorer. Signed results.**
AetherArena is a **standalone, project-agnostic benchmark** for camera-free **spatial intelligence** — pose, presence, occupancy, tracking, and vitals from RF/WiFi (and, over time, mmWave / UWB / radar / lidar / multimodal). It is **not** a single-vendor leaderboard: any team, framework, or sensing modality can enter, and every entrant — including the RuView baseline that donated the seed scorer — is scored by the identical, open, pinned harness.
Specified in [ADR-149](../docs/adr/ADR-149-public-community-leaderboard-huggingface.md) (Accepted).
Canonical home: **`ruvnet/aether-arena`** + a Hugging Face Space (deploy pending — see `STATUS`).
---
## Why
WiFi/RF spatial sensing has no shared yardstick — papers self-report against inconsistent splits and metrics, with **no accounting for latency, reproducibility, or privacy leakage**. AA fixes the *measurement*, not just the models: a single deterministic scorer, a private held-out split nobody can train on, and a signed result ledger that can't be silently edited.
## What gets measured (v0)
| Category | Metric | Status |
|----------|--------|--------|
| **Pose** | PCK@0.2 (all / torso), OKS | Ranked |
| **Presence** | accuracy, FP/FN | Ranked |
| **Edge latency** | p50 / p95 / p99 ms | Ranked |
| **Determinism** | proof-hash pass/fail | Ranked (gate) |
| Tracking (MOTA) | — | activates when multi-person clips land |
| Vitals (BPM err) | — | activates when paired vitals ground truth lands |
| **Privacy leakage** | membership-inference ∈ [0,1] | **gated — not ranked** until the attacker ships |
| Cross-room | degradation ratio | coming soon |
The headline rank is the **category metric**; an optional `arena_score = quality × latency_factor × privacy_factor × determinism_gate` is exposed alongside (never instead) so accuracy can't win at any cost. See ADR-149 §2.5.
## How scoring works
The scorer is RuView's **already-published** `wifi-densepose-train` acceptance harness (`ruview_metrics` + ADR-145 `ablation`), run in a pinned sandbox. **You submit a model, not predictions** — predictions on data you hold prove nothing. Your model is scored against a **private** MM-Fi held-out split (CC BY-NC 4.0; Wi-Pose excluded for redistribution reasons), and one **signed, append-only** row is written to the results ledger with a determinism proof hash.
Submission lifecycle: `submitted → validated → quarantined → smoke_scored → full_scored → published` (or `rejected` with a reason). The model only ever runs inside a no-network, read-only-FS sandbox.
## Submit (when the Space is live)
1. Write a manifest: [`schema/aa-submission.toml`](schema/aa-submission.toml).
2. Push your model artifact (`.safetensors` / `.rvf` / LoRA adapter) + manifest to the Space.
3. Watch it move through the lifecycle; your signed row appears on the board.
## Verify it's fair (you don't have to trust us)
See [`VERIFY.md`](VERIFY.md) — run the **open scorer** locally on the **public smoke split**, reproduce the determinism hash, and confirm RuView's own entries were scored by the identical path. That five-step check is the launch gate (ADR-149 §7).
## Neutrality
AA is a neutral commons. The scorer is open and versioned; any metric change is a public `harness_version` bump that **re-scores all entries**. RuView donated the seed harness and enters as one baseline — it gets no special treatment (ADR-149 §2.8).
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@@ -1,30 +0,0 @@
# AetherArena — Build Status
Tracks ADR-149 implementation milestones. "Complete" = benchmark **infrastructure** done,
tested, CI-gated, deploy-ready, RuView baseline entered, §7 acceptance test passing.
Model **SOTA** (e.g. MM-Fi PCK@20 ~72%) is a separate long-running ML effort, blocked on
ADR-079 camera-ground-truth collection — *not* an infra-completion blocker.
| # | Milestone | Status |
|---|-----------|--------|
| M1 | ADR-149 Accepted + committed | ✅ done |
| M2 | Scorer runner (`aa_score_runner`) — **real model scoring** + witness (proof+inputs hash) + **repeatability analysis** | ✅ done — builds `--no-default-features`, determinism gate PASS, repeatable 16/16 |
| M3 | CI harness-gate workflow (PR runs scorer + repeatability + real-scoring smoke + ledger verify) | ✅ done — `.github/workflows/aether-arena-harness.yml` |
| M4 | Scaffold: README + submission schema + VERIFY (acceptance test) | ✅ done |
| M5 | Public smoke split (committed) + private MM-Fi held-out split prep | 🟡 smoke split done (`fixtures/smoke_*.json`); private MM-Fi prep pending |
| M6 | HF Space (Gradio) — leaderboard + ledger integrity + submit/verify/about | ✅ deployed → https://huggingface.co/spaces/ruvnet/aether-arena (sandboxed scorer container = later hardening) |
| M7 | **Witness ledger chain** — append-only, hash-chained, tamper-evident | ✅ done — `ledger/ledger_tools.py` (seed/append/verify); tamper test fails as designed |
| M8 | Public launch | ✅ Space **LIVE** (gradio 5.9.1, serving 200) — **board empty, awaiting first real harness score** (benchmark-first: no seeded numbers) |
## v0 infrastructure: COMPLETE
Implement ✅ · Test ✅ · Deploy to HF ✅ (https://huggingface.co/spaces/ruvnet/aether-arena) · Instructions+Verification ✅ · PR runs the harness ✅ (PR #874, AA harness gate **passed**).
Remaining = data + hardening, not infra: private MM-Fi held-out split (M5), sandboxed scorer container (M6), privacy-leakage attacker (gated category), and **model SOTA** (separate ML effort, blocked on ADR-079 — explicitly not an infra exit).
## Benchmark-first posture (per user direction)
- **No placeholder numbers on the board.** The ledger seeds to genesis only; every result is a real scoring-pipeline witness. RuView gets no seeded baseline.
- **Witness chain** = `inputs_sha256` (binds witness to exact inputs) + `proof_sha256` (cross-platform-stable score hash) + the append-only hash-chained ledger. Repeatability analysis (`--repeat N`) proves the proof hash is identical across runs.
## Blockers / decisions needed
- **HF deploy (M6)** — token is in GCP Secret Manager (`HUGGINGFACE_API_KEY`); creating the public `ruvnet/aether-arena` Space still wants explicit go.
- **MM-Fi is CC BY-NC** → AA must stay non-commercial / legally distinct from the commercial RuView product.
- **Private MM-Fi split (M5)** — needs the dataset pulled + a held-out split assembled before real public scoring replaces the smoke fixture.
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@@ -1,78 +0,0 @@
# Verifying AetherArena (you don't have to trust us)
AA's credibility rests on a stranger being able to reproduce a score and see that the rules are fair. This is the **launch gate** (ADR-149 §7): v0 does not ship until all five checks below pass for someone with no insider access.
> **Wider context:** this page covers the *leaderboard scorer*. For the whole-platform answer to
> "is this real / does it actually work?" — including the deterministic pipeline proof, the
> published models + public-benchmark numbers, and the built-in-public development trail — see
> [`docs/proof-of-capabilities.md`](../docs/proof-of-capabilities.md).
## The open scorer
The scoring engine is a pure-Rust, GPU-free binary: `aa_score_runner` in `wifi-densepose-train`. It runs the real `ruview_metrics` pose-acceptance harness on a fixed fixture and emits a cross-platform-stable SHA-256 **determinism proof**.
### Reproduce the determinism hash locally
```bash
cd v2
# Verify the committed expected hash still matches (this is the CI gate):
cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features
# → prints the witness (inputs_sha256 + proof_sha256) and "VERDICT: PASS"
# See the witness row as JSON:
cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --json
```
### Witness chain — proof + repeatability analysis
Every score is a **witness**: `inputs_sha256` (binds it to the exact inputs scored)
+ `proof_sha256` (cross-platform-stable hash of the quantised score) + `harness_version`.
Witnesses are recorded in an **append-only, hash-chained ledger** (each row references
the previous row's hash), so a silent edit to any past row breaks the chain.
```bash
# Repeatability: run the scorer K times, confirm ONE identical proof hash:
cd v2
cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --repeat 16
# → {"repeatability":{"runs":16,"unique_proof_hashes":1,"repeatable":true,...}}
# Real model scoring (score predictions against an eval split):
cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- \
--split ../aether-arena/fixtures/smoke_split.json \
--pred ../aether-arena/fixtures/smoke_pred.json --json
# Verify the witness ledger chain is intact (tamper-evident):
cd ../aether-arena/ledger && python3 ledger_tools.py verify
# → "OK: N rows, chain intact" (edit any row and it reports the broken link)
```
The expected hash is committed at [`fixtures/expected_score.sha256`](fixtures/expected_score.sha256). Same harness version + same fixture → same hash on glibc / MSVC / Apple. If your local run prints `VERDICT: PASS`, you have reproduced the scorer.
### What happens if the scoring maths changes
Any edit to `ruview_metrics.rs`, `ablation.rs`, or `aa_score_runner.rs` moves the hash and **fails the CI gate** (`.github/workflows/aether-arena-harness.yml`) until the maintainer regenerates and reviews:
```bash
cargo run -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --generate-hash \
> aether-arena/fixtures/expected_score.sha256
```
So a scorer change is always a reviewed, public diff — never silent. That's `harness_version` pinning + `determinism_gate` in action (ADR-149 §2.4–§2.5).
## The five-step acceptance test (v0 launch gate)
A stranger must be able to:
1. **Submit** a model (artifact + `schema/aa-submission.toml`) with no insider help.
2. **Get a deterministic score** — same model + same `harness_version` → same numbers.
3. **See the signed row** appended to the public results ledger.
4. **Rerun the scorer locally** on the public smoke split and reproduce the logic (the command above).
5. **Understand why the rank is fair** — private split, open scorer, pinned version, proof hash — from these docs alone.
If any step fails, v0 is not ready.
## Current status
- ✅ Step 4 (rerun the open scorer locally, reproduce the hash) — **works today** via `aa_score_runner`.
- ✅ CI harness gate runs the scorer on every PR.
- ⏳ Steps 13, 5 (HF Space submission flow + signed ledger) — in progress; require the HF Space deploy (needs an HF token / maintainer authorization).
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# RuView Calibration Service (reference implementation)
Turn a **shared WiFi-CSI pose base model** into a room-specific one with a **30-second labeled
calibration** and a **~11 KB per-room LoRA adapter**. This is the deployable resolution of the
cross-subject / cross-environment generalization problem (full study: [ADR-150 §3.33.6](../../docs/adr/ADR-150-rf-foundation-encoder.md)).
## Why
Zero-shot WiFi pose generalizes poorly to a **new room or new person** — an unseen room can drop a
strong model to near-random. But that gap is **not** algorithmically closeable (CORAL, DANN,
instance-norm, contrastive foundation-pretraining all failed) and **not** closeable by collecting
more subjects (saturates ~64%). It **is** closeable, cheaply, at deployment time: a handful of
labeled frames from the actual room pin down its multipath instantly.
| Deployment case | Zero-shot | + in-room calibration |
|-----------------|----------:|----------------------:|
| Same room, new person (cross-subject) | 64% | **76%** (200 samples) |
| **New room + new person (cross-environment)** | **~10%** | **60% @ 5 samples → 73% @ 200** |
**Verified demo (this code, source-only base on an unseen MM-Fi room E04):**
`zero-shot 3.09% → after 200-sample calibration 74.29%` (+71 pts).
## How it works
A frozen shared **base** (transformer + temporal attention pool + skeleton-graph head, the published
[`ruvnet/wifi-densepose-mmfi-pose`](https://huggingface.co/ruvnet/wifi-densepose-mmfi-pose)) plus a
tiny **LoRA adapter** (rank 8 on the input projection + pose head — **11,200 params ≈ 11 KB int8 /
22 KB fp16**) fitted per room. Thousands of room-adapters hang off one base.
## Usage
```bash
# 1) Capture a short labeled clip in the deployment room -> calib.npz {X:[N,3,114,10], Y:[N,17,2]}
# (~100200 samples recommended; below ~20 the adapter can underperform zero-shot)
# 2) Fit the per-room adapter (~11 KB):
python calibrate.py --base pose_mmfi_best.pt --data calib.npz --out room.adapter.npz
# 3) Run calibrated inference (base + room adapter):
python infer.py --base pose_mmfi_best.pt --adapter room.adapter.npz --data frames.npz --out kp.npy
# omit --adapter to run the uncalibrated (zero-shot) base
```
`X` is CSI amplitude `[N, 3 antennas, 114 subcarriers, 10 frames]` (per-sample standardization is
applied internally). `Y` is `[N,17,2]` COCO keypoints in `[0,1]`.
## Calibration budget (measured, rank-8 LoRA, 3 seeds — ADR-150 §3.5)
| Labeled samples/room | cross-subject | cross-environment |
|---------------------:|--------------:|------------------:|
| 0 (zero-shot) | 64% | ~10% |
| 5 | — | 60% |
| 20 | 66% | 66% |
| 50 | 70% | 70% |
| 200 | 72% | 73% |
Knee at ~50 samples (~70%); **below ~20 samples the adapter can hurt** (too few to fit reliably).
## Two models, two producers (not interchangeable)
Adapters are **model-specific**. There are two calibration producers here:
| Producer | Target model | Input | Adapter format | Consumer |
|----------|--------------|-------|----------------|----------|
| `calibrate.py` | MM-Fi **transformer** (`pose_mmfi_best.pt`, 3×114×10) | `[N,3,114,10]` | `.npz` (`proj`/`head` LoRA) | this Python `infer.py` |
| `cog_calibrate.py` | cog **conv+MLP** (`pose_v1.safetensors`, 56×20) | `[N,56,20]` | `.safetensors` (`fc1.a`/`fc1.b`/`fc2.a`/`fc2.b`) | Rust `cog-pose-estimation run --adapter` |
```bash
# Produce a cog-format per-room adapter for the deployed Rust pose engine:
python cog_calibrate.py --base pose_v1.safetensors --data calib.npz --out room.safetensors
# then in the cog runtime:
cog-pose-estimation run --config <cfg> --adapter room.safetensors
```
Same LoRA *mechanism* (ADR-150 §3.5), different architecture and key layout — an adapter from one
producer will not load into the other model.
## Notes
- **Calibration only helps when the base hasn't already seen the room.** The published flagship was
trained on MM-Fi `random_split`, so calibrating it on an MM-Fi subject is a near-no-op (it already
saw them); for a genuinely new real-world room it is zero-shot and calibration applies. To
*reproduce the demo* on a held-out MM-Fi room, train a source-only base (exclude the target
environment) — see `ADR-150 §3.6` and the few-shot harness in `aether-arena/staging/`.
- Adapter is saved fp16 (~22 KB); quantize to int8 for the ~11 KB on-device form.
- Inference is real-time on CPU (the 75 K-param `micro` variant runs in 0.135 ms single-thread x86;
see [`docs/benchmarks/wifi-pose-efficiency-frontier.md`](../../docs/benchmarks/wifi-pose-efficiency-frontier.md)).
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"""RuView per-room calibration — fit a ~11 KB LoRA adapter from a short labeled in-room capture.
python calibrate.py --base pose_mmfi_best.pt --data room_calib.npz --out room_A.adapter.npz
`room_calib.npz` must contain `X` [N,3,114,10] CSI amplitude and `Y` [N,17,2] (or [N,34]) keypoints
in [0,1] — the labeled calibration samples from the deployment room (~100200 recommended; ≥20).
Outputs a tiny adapter (.npz, ~11 KB) that, loaded over the shared base at inference, recovers
SOTA-level pose for that room/person (ADR-150 §3.53.6).
"""
import argparse
import numpy as np
import torch
import torch.nn as nn
from model import PoseNet, standardize
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--base", required=True, help="base checkpoint (pose_mmfi_best.pt)")
ap.add_argument("--data", required=True, help="labeled calibration .npz with X and Y")
ap.add_argument("--out", required=True, help="output adapter .npz")
ap.add_argument("--rank", type=int, default=8)
ap.add_argument("--iters", type=int, default=600)
ap.add_argument("--lr", type=float, default=8e-4)
ap.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu")
a = ap.parse_args()
z = np.load(a.data)
X = torch.tensor(z["X"].astype(np.float32))
Y = torch.tensor(z["Y"].reshape(len(z["Y"]), 34).astype(np.float32))
n = len(X)
if n < 20:
print(f"WARNING: only {n} calibration samples — below ~20 the adapter may underperform "
f"zero-shot (ADR-150 §3.5). Recommend ~100200.")
dev = a.device
net = PoseNet().to(dev)
net.load_state_dict(torch.load(a.base, map_location=dev), strict=False)
net.add_lora(r=a.rank).to(dev)
for k, p in net.named_parameters():
p.requires_grad = k.endswith(".A") or k.endswith(".B")
trainable = [p for p in net.parameters() if p.requires_grad]
n_tr = sum(p.numel() for p in trainable)
Xs = standardize(X.to(dev))
Yt = Y.to(dev)
opt = torch.optim.AdamW(trainable, lr=a.lr, weight_decay=0.0)
lossf = nn.SmoothL1Loss(beta=0.1)
bs = min(128, n)
net.train()
for it in range(a.iters):
bi = torch.randint(0, n, (bs,), device=dev)
xb = Xs[bi]
# light augmentation (subcarrier dropout + noise) — matches training-time regularization
m = (torch.rand(xb.shape[0], xb.shape[1], 1, 1, device=dev) > 0.15).float()
xb = xb * m + 0.03 * torch.randn_like(xb) * torch.rand(xb.shape[0], 1, 1, 1, device=dev)
opt.zero_grad()
lossf(net(xb), Yt[bi]).backward()
opt.step()
adapter = net.lora_state()
nbytes = sum(v.astype(np.float16).nbytes for v in adapter.values())
np.savez(a.out, **{k: v.astype(np.float16) for k, v in adapter.items()},
_meta=np.array([a.rank, n, n_tr], dtype=np.int64))
print(f"saved {a.out} | rank {a.rank} | {n_tr:,} params | ~{nbytes/1024:.1f} KB fp16 | "
f"from {n} labeled samples")
if __name__ == "__main__":
main()
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"""Per-room calibration producer for the cog-pose-estimation **conv+MLP** model
(`pose_v1.safetensors`, 56 subcarriers x 20 frames). Companion to `calibrate.py`
(which targets the MM-Fi *transformer* model) — different model, different adapter
key layout, NOT interchangeable (ADR-150 §3.5).
Fits a rank-r LoRA on the pose head (fc1, fc2) from a short labeled in-room capture and
writes a **safetensors** adapter with keys `fc1.a`/`fc1.b`/`fc2.a`/`fc2.b` (scale baked
into `b`) — exactly what `cog-pose-estimation run --adapter <file>` consumes.
python cog_calibrate.py --base pose_v1.safetensors --data calib.npz --out room.safetensors
`calib.npz`: `X` [N,56,20] CSI window + `Y` [N,17,2] (or [N,34]) keypoints in [0,1].
"""
import argparse
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
class CogPose(nn.Module):
"""Mirrors cog-pose-estimation's PoseNet (Candle) exactly — same safetensors keys."""
def __init__(self):
super().__init__()
self.enc = nn.ModuleDict({
"c1": nn.Conv1d(56, 64, 3, padding=1, dilation=1),
"c2": nn.Conv1d(64, 128, 3, padding=2, dilation=2),
"c3": nn.Conv1d(128, 128, 3, padding=4, dilation=4),
})
self.head = nn.ModuleDict({"fc1": nn.Linear(128, 256), "fc2": nn.Linear(256, 34)})
self.fc1_lora = None
self.fc2_lora = None
def _lora(self, slot, x, y):
if slot is None:
return y
a, b = slot
return y + (x @ a) @ b
def forward(self, x): # x: [B, 56, 20]
h = F.relu(self.enc["c1"](x))
h = F.relu(self.enc["c2"](h))
h = F.relu(self.enc["c3"](h))
h = h.mean(2) # [B, 128]
z1 = self.head["fc1"](h)
z1 = self._lora(self.fc1_lora, h, z1)
h1 = F.relu(z1)
z2 = self.head["fc2"](h1)
z2 = self._lora(self.fc2_lora, h1, z2)
return torch.sigmoid(z2) # [B, 34]
def add_lora(self, r=4):
self.fc1_lora = (nn.Parameter(torch.randn(128, r) * 0.02), nn.Parameter(torch.zeros(r, 256)))
self.fc2_lora = (nn.Parameter(torch.randn(256, r) * 0.02), nn.Parameter(torch.zeros(r, 34)))
for p in (*self.fc1_lora, *self.fc2_lora):
self.register_parameter(f"lora_{id(p)}", p)
return self
def load_base(net: CogPose, path: str):
from safetensors.torch import load_file
sd = load_file(path)
# remap "enc.c1.weight" -> module dict keys
mapped = {}
for k, v in sd.items():
mapped[k.replace("enc.", "enc.").replace("head.", "head.")] = v
net.load_state_dict(mapped, strict=False)
return net
def fit(base: str, data: str, out: str, rank: int = 4, iters: int = 400, lr: float = 1e-3):
z = np.load(data)
X = torch.tensor(z["X"].astype(np.float32)) # [N,56,20]
Y = torch.tensor(z["Y"].reshape(len(z["Y"]), 34).astype(np.float32))
n = len(X)
net = CogPose()
load_base(net, base)
net.add_lora(rank)
for p in net.parameters():
p.requires_grad = False
lora = [*net.fc1_lora, *net.fc2_lora]
for p in lora:
p.requires_grad = True
opt = torch.optim.AdamW(lora, lr=lr, weight_decay=0.0)
lossf = nn.SmoothL1Loss(beta=0.1)
bs = min(64, n)
net.train()
for _ in range(iters):
bi = torch.randint(0, n, (bs,))
opt.zero_grad()
lossf(net(X[bi]), Y[bi]).backward()
opt.step()
alpha = 16.0
scale = alpha / rank
a1, b1 = net.fc1_lora
a2, b2 = net.fc2_lora
tensors = {
"fc1.a": a1.detach().contiguous(),
"fc1.b": (b1.detach() * scale).contiguous(), # bake scale into b
"fc2.a": a2.detach().contiguous(),
"fc2.b": (b2.detach() * scale).contiguous(),
}
from safetensors.torch import save_file
save_file(tensors, out)
return out, sum(p.numel() for p in lora), n
if __name__ == "__main__":
ap = argparse.ArgumentParser()
ap.add_argument("--base", required=True)
ap.add_argument("--data", required=True)
ap.add_argument("--out", required=True)
ap.add_argument("--rank", type=int, default=4)
ap.add_argument("--iters", type=int, default=400)
a = ap.parse_args()
out, np_, n = fit(a.base, a.data, a.out, a.rank, a.iters)
print(f"saved {out} | {np_} LoRA params from {n} samples "
f"(keys fc1.a/fc1.b/fc2.a/fc2.b — load with cog-pose-estimation run --adapter)")
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"""Run calibrated WiFi-CSI pose inference: shared base + a per-room LoRA adapter.
python infer.py --base pose_mmfi_best.pt --adapter room_A.adapter.npz --data frames.npz
`frames.npz` contains `X` [N,3,114,10] CSI amplitude. Prints/saves [N,17,2] keypoints in [0,1].
Omit --adapter to run the uncalibrated (zero-shot) base. With a room adapter, expect SOTA-level
accuracy in that room/person; without one, zero-shot degrades in unseen rooms (ADR-150 §3.6).
"""
import argparse
import numpy as np
import torch
from model import PoseNet, standardize
def main():
ap = argparse.ArgumentParser()
ap.add_argument("--base", required=True)
ap.add_argument("--adapter", default=None, help="per-room .adapter.npz (omit for zero-shot)")
ap.add_argument("--data", required=True, help=".npz with X [N,3,114,10]")
ap.add_argument("--out", default=None, help="optional .npy to save [N,17,2] keypoints")
ap.add_argument("--rank", type=int, default=8)
ap.add_argument("--device", default="cuda" if torch.cuda.is_available() else "cpu")
a = ap.parse_args()
dev = a.device
net = PoseNet().to(dev)
net.load_state_dict(torch.load(a.base, map_location=dev), strict=False)
if a.adapter:
net.add_lora(r=a.rank).to(dev)
z = np.load(a.adapter)
net.load_lora({k: z[k].astype(np.float32) for k in z.files if k.endswith(".A") or k.endswith(".B")})
net.eval()
X = torch.tensor(np.load(a.data)["X"].astype(np.float32)).to(dev)
Xs = standardize(X)
out = []
with torch.no_grad():
for i in range(0, len(Xs), 4096):
out.append(net(Xs[i:i + 4096]).cpu().numpy())
kp = np.concatenate(out).reshape(-1, 17, 2)
print(f"inferred {len(kp)} frames | adapter={'yes' if a.adapter else 'NONE (zero-shot)'}")
if a.out:
np.save(a.out, kp)
print(f"saved keypoints -> {a.out}")
if __name__ == "__main__":
main()
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"""WiFi-CSI pose model + LoRA adapter for the RuView calibration service.
Architecture matches the published flagship checkpoint
[`ruvnet/wifi-densepose-mmfi-pose`](https://huggingface.co/ruvnet/wifi-densepose-mmfi-pose)
(`pose_mmfi_best.pt`): transformer encoder + temporal attention pooling + skeleton-graph head.
The calibration service freezes this base and fits a tiny per-room **LoRA adapter** (rank 8 on the
input projection + pose head ≈ 11 KB) from ~100200 labeled in-room samples. Empirically that lifts
cross-subject 64→72% and cross-environment 11→73% (ADR-150 §3.33.6).
"""
import numpy as np
import torch
import torch.nn as nn
# COCO-17 skeleton edges for the graph-refinement head.
EDGES = [(0, 1), (0, 2), (1, 3), (2, 4), (5, 6), (5, 7), (7, 9), (6, 8), (8, 10),
(5, 11), (6, 12), (11, 12), (11, 13), (13, 15), (12, 14), (14, 16)]
_A = np.eye(17, dtype=np.float32)
for _i, _j in EDGES:
_A[_i, _j] = _A[_j, _i] = 1.0
_A = _A / _A.sum(1, keepdims=True)
class LoRA(nn.Module):
"""Low-rank adapter wrapping a frozen Linear: y = W·x + (x·A·B)·(alpha/r)."""
def __init__(self, base: nn.Linear, r: int = 8, alpha: int = 16):
super().__init__()
self.base = base
for p in self.base.parameters():
p.requires_grad = False
self.A = nn.Parameter(torch.zeros(base.in_features, r))
self.B = nn.Parameter(torch.zeros(r, base.out_features))
nn.init.normal_(self.A, std=0.02)
self.scale = alpha / r
def forward(self, x):
return self.base(x) + (x @ self.A @ self.B) * self.scale
class GR(nn.Module):
"""Skeleton-graph refinement: nudges joints toward anatomically consistent positions."""
def __init__(self, d=256, h=96):
super().__init__()
self.je = nn.Parameter(torch.randn(17, 32) * 0.02)
self.inp = nn.Linear(d + 34, h)
self.g1 = nn.Linear(h, h)
self.g2 = nn.Linear(h, h)
self.out = nn.Linear(h, 2)
self.register_buffer("A", torch.tensor(_A))
def forward(self, z, kp0):
B = z.shape[0]
f = torch.relu(self.inp(torch.cat(
[z.unsqueeze(1).expand(-1, 17, -1), self.je.unsqueeze(0).expand(B, -1, -1), kp0], -1)))
f = torch.relu(self.g1(torch.einsum('ij,bjh->bih', self.A, f)))
f = torch.relu(self.g2(torch.einsum('ij,bjh->bih', self.A, f)))
return kp0 + 0.3 * torch.tanh(self.out(f))
class PoseNet(nn.Module):
"""Flagship pose model. Input [B,3,114,10] CSI amplitude (per-sample standardized) -> [B,34]."""
def __init__(self, na=3, nsc=114, nt=10, d=256, L=4, H=8):
super().__init__()
self.proj = nn.Linear(na * nsc, d)
self.pos = nn.Parameter(torch.randn(1, nt, d) * 0.02)
enc = nn.TransformerEncoderLayer(d, H, d * 2, dropout=0.2, batch_first=True, activation='gelu')
self.tf = nn.TransformerEncoder(enc, L)
self.att = nn.Linear(d, 1)
self.head = nn.Sequential(nn.Linear(d, 256), nn.GELU(), nn.Dropout(0.3), nn.Linear(256, 34))
self.gr = GR(d)
self.na, self.nsc, self.nt = na, nsc, nt
def forward(self, x):
B = x.shape[0]
t = x.permute(0, 3, 1, 2).reshape(B, self.nt, self.na * self.nsc)
h = self.tf(self.proj(t) + self.pos)
w = torch.softmax(self.att(h), 1)
z = (h * w).sum(1)
kp0 = torch.sigmoid(self.head(z)).reshape(B, 17, 2)
return self.gr(z, kp0).reshape(B, 34)
def add_lora(self, r=8, alpha=16):
"""Wrap the input projection + pose head with LoRA adapters (the ~11 KB calibration set)."""
self.proj = LoRA(self.proj, r, alpha)
self.head[0] = LoRA(self.head[0], r, alpha)
self.head[3] = LoRA(self.head[3], r, alpha)
return self
def lora_state(self) -> dict:
"""Extract just the LoRA A/B tensors (the per-room adapter to save)."""
return {k: v.detach().cpu().numpy() for k, v in self.state_dict().items()
if k.endswith(".A") or k.endswith(".B")}
def load_lora(self, adapter: dict):
sd = self.state_dict()
for k, v in adapter.items():
sd[k] = torch.tensor(v)
self.load_state_dict(sd)
return self
def standardize(x: torch.Tensor) -> torch.Tensor:
"""Per-sample standardization used in training/inference."""
return (x - x.mean((1, 2, 3), keepdim=True)) / (x.std((1, 2, 3), keepdim=True) + 1e-6)
@@ -1,103 +0,0 @@
"""Self-contained regression test for the RuView calibration service.
Exercises the committed CLI end-to-end on synthetic data (CPU, no GPU, no real checkpoint):
build a base -> calibrate.py fits an adapter -> infer.py runs base+adapter -> assert the
adapter is small, inference is shape-correct and finite, and the adapter actually changes output.
Run: python test_calibration.py (or via pytest)
"""
import json
import subprocess
import sys
import tempfile
from pathlib import Path
import numpy as np
import torch
HERE = Path(__file__).parent
sys.path.insert(0, str(HERE))
from model import PoseNet, standardize # noqa: E402
def _make_base(path: Path):
torch.manual_seed(0)
net = PoseNet()
# Save without the deterministic gr.A buffer (mirrors the published checkpoint;
# calibrate.py/infer.py load with strict=False).
sd = {k: v for k, v in net.state_dict().items() if k != "gr.A"}
torch.save(sd, path)
def _make_data(path: Path, n: int, seed: int):
rng = np.random.default_rng(seed)
X = rng.standard_normal((n, 3, 114, 10)).astype(np.float32)
Y = rng.random((n, 17, 2)).astype(np.float32) # keypoints in [0,1]
np.savez(path, X=X, Y=Y)
def _run(*args):
r = subprocess.run(
[sys.executable, str(HERE / args[0]), *map(str, args[1:])],
capture_output=True, text=True,
)
assert r.returncode == 0, f"{args[0]} failed:\n{r.stdout}\n{r.stderr}"
return r.stdout
def test_calibration_end_to_end():
with tempfile.TemporaryDirectory() as d:
d = Path(d)
base = d / "base.pt"
calib = d / "calib.npz"
frames = d / "frames.npz"
adapter = d / "room.adapter.npz"
kp = d / "kp.npy"
_make_base(base)
_make_data(calib, n=40, seed=1) # ≥20 → no underfit warning
_make_data(frames, n=16, seed=2)
# 1) calibrate -> adapter
out = _run("calibrate.py", "--base", base, "--data", calib, "--out", adapter,
"--iters", "50", "--device", "cpu")
assert adapter.exists(), "adapter not written"
assert "saved" in out.lower()
sz = adapter.stat().st_size
assert sz < 200_000, f"adapter unexpectedly large ({sz} bytes)"
# adapter contains the expected LoRA tensors (materialize + close so the
# Windows tempdir can be cleaned up — np.load keeps a lazy file handle).
with np.load(adapter) as z:
keys = [k for k in z.files if k.endswith(".A") or k.endswith(".B")]
assert keys, f"adapter has no LoRA tensors: {z.files}"
lora = {k: z[k].astype(np.float32) for k in keys}
# 2) infer with adapter -> keypoints
_run("infer.py", "--base", base, "--adapter", adapter, "--data", frames,
"--out", kp, "--device", "cpu")
out_kp = np.load(kp)
assert out_kp.shape == (16, 17, 2), f"bad keypoint shape {out_kp.shape}"
assert np.isfinite(out_kp).all(), "non-finite keypoints"
assert (out_kp >= 0).all() and (out_kp <= 1).all(), "keypoints out of [0,1]"
# 3) adapter must actually change the output vs the zero-shot base
with np.load(frames) as fz:
frames_x = fz["X"][:]
net = PoseNet()
net.load_state_dict(torch.load(base, map_location="cpu"), strict=False)
net.eval()
x = standardize(torch.tensor(frames_x))
with torch.no_grad():
base_kp = net(x).reshape(16, 17, 2).numpy()
net.add_lora()
net.load_lora(lora)
net.eval()
with torch.no_grad():
cal_kp = net(x).reshape(16, 17, 2).numpy()
assert np.abs(base_kp - cal_kp).sum() > 1e-4, "adapter did not change output"
if __name__ == "__main__":
test_calibration_end_to_end()
print("PASS: calibration service end-to-end (calibrate -> adapter -> infer)")
@@ -1,75 +0,0 @@
"""Regression test for the cog-pose adapter producer (cog_calibrate.py).
Uses the in-repo `pose_v1.safetensors` (skips if absent). Verifies the produced adapter:
- has the exact keys/shapes the Rust `cog-pose-estimation --adapter` loader expects,
- reduces calibration fit error,
- actually changes inference output,
- is tiny.
Run: python test_cog_calibration.py (or via pytest)
"""
import os
import sys
import tempfile
from pathlib import Path
import numpy as np
import torch
import torch.nn.functional as F
HERE = Path(__file__).parent
sys.path.insert(0, str(HERE))
import cog_calibrate as C # noqa: E402
BASE = HERE / "../../v2/crates/cog-pose-estimation/cog/artifacts/pose_v1.safetensors"
def test_cog_adapter_producer():
if not BASE.exists():
print(f"(skip — {BASE} not present)")
return
from safetensors.torch import load_file
rng = np.random.default_rng(0)
n = 120
X = rng.standard_normal((n, 56, 20)).astype("float32")
Y = (0.5 + 0.1 * X[:, :34, 0].reshape(n, 34)).clip(0, 1).astype("float32")
with tempfile.TemporaryDirectory() as d:
calib = os.path.join(d, "calib.npz")
adapter = os.path.join(d, "room.safetensors")
np.savez(calib, X=X, Y=Y)
net0 = C.CogPose()
C.load_base(net0, str(BASE))
net0.eval()
with torch.no_grad():
base_err = F.smooth_l1_loss(net0(torch.tensor(X)), torch.tensor(Y)).item()
_, nparam, _ = C.fit(str(BASE), calib, adapter, rank=4, iters=400)
t = load_file(adapter)
# exact Rust loader contract: a:[in,r], b:[r,out]
assert tuple(t["fc1.a"].shape) == (128, 4)
assert tuple(t["fc1.b"].shape) == (4, 256)
assert tuple(t["fc2.a"].shape) == (256, 4)
assert tuple(t["fc2.b"].shape) == (4, 34)
net = C.CogPose()
C.load_base(net, str(BASE))
net.add_lora(4)
with torch.no_grad():
net.fc1_lora[0].copy_(t["fc1.a"]); net.fc1_lora[1].copy_(t["fc1.b"] / (16 / 4))
net.fc2_lora[0].copy_(t["fc2.a"]); net.fc2_lora[1].copy_(t["fc2.b"] / (16 / 4))
net.eval()
with torch.no_grad():
cal_err = F.smooth_l1_loss(net(torch.tensor(X)), torch.tensor(Y)).item()
changed = (net0(torch.tensor(X[:8])) - net(torch.tensor(X[:8]))).abs().sum().item()
assert cal_err < base_err, f"calibration did not reduce error ({base_err} -> {cal_err})"
assert changed > 1e-3, "adapter inert"
assert nparam < 5000, f"adapter unexpectedly large ({nparam} params)"
if __name__ == "__main__":
test_cog_adapter_producer()
print("PASS: cog adapter producer (Rust-loadable format, reduces error, active)")
@@ -1 +0,0 @@
9c35e541d51f00998691b98948887ebca09b907d8eb29a113f97e792340456ba
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@@ -1 +0,0 @@
{"frames": [{"pred": [[0.4003, 0.2734], [0.5038, 0.4197], [0.2053, 0.4438], [0.4397, 0.685], [0.5796, 0.7645], [0.8001, 0.2195], [0.2789, 0.2833], [0.314, 0.5439], [0.511, 0.2259], [0.6008, 0.46], [0.4837, 0.3879], [0.3475, 0.5597], [0.6569, 0.3575], [0.437, 0.6539], [0.2341, 0.6038], [0.7331, 0.392], [0.5615, 0.4915]]}, {"pred": [[0.4669, 0.6066], [0.6012, 0.7873], [0.4124, 0.5997], [0.2832, 0.281], [0.2732, 0.3635], [0.2503, 0.4848], [0.6827, 0.715], [0.4336, 0.7165], [0.295, 0.3386], [0.5337, 0.3544], [0.4397, 0.5474], [0.5163, 0.5528], [0.7547, 0.6799], [0.4195, 0.4448], [0.2257, 0.2269], [0.384, 0.2176], [0.2419, 0.4332]]}, {"pred": [[0.5585, 0.283], [0.4325, 0.2934], [0.463, 0.4744], [0.4188, 0.3454], [0.215, 0.7565], [0.527, 0.2353], [0.7084, 0.6124], [0.3015, 0.6744], [0.4103, 0.3532], [0.7243, 0.6932], [0.3302, 0.4918], [0.2072, 0.3754], [0.7914, 0.4878], [0.7618, 0.4079], [0.323, 0.3386], [0.7104, 0.4997], [0.2673, 0.6077]]}, {"pred": [[0.6372, 0.4984], [0.4184, 0.6763], [0.4498, 0.7549], [0.2924, 0.303], [0.3069, 0.7022], [0.3954, 0.5098], [0.7836, 0.6071], [0.4733, 0.7114], [0.3407, 0.3793], [0.3408, 0.4678], [0.4156, 0.4911], [0.4525, 0.7519], [0.5117, 0.1985], [0.1893, 0.6784], [0.6281, 0.5346], [0.5175, 0.673], [0.36, 0.3665]]}, {"pred": [[0.5535, 0.6537], [0.568, 0.511], [0.4705, 0.5377], [0.6372, 0.7163], [0.5493, 0.7515], [0.2559, 0.4549], [0.2553, 0.6176], [0.2991, 0.6154], [0.7185, 0.7986], [0.4586, 0.5057], [0.2975, 0.4525], [0.3263, 0.3719], [0.5131, 0.4576], [0.557, 0.5268], [0.6572, 0.7736], [0.2146, 0.6526], [0.4662, 0.7371]]}, {"pred": [[0.2924, 0.7595], [0.2612, 0.2315], [0.2488, 0.7751], [0.2329, 0.7282], [0.4744, 0.4206], [0.3618, 0.267], [0.2477, 0.285], [0.3976, 0.3746], [0.494, 0.2874], [0.3596, 0.2112], [0.3311, 0.4692], [0.6912, 0.4727], [0.4434, 0.5233], [0.4139, 0.7048], [0.425, 0.3937], [0.2326, 0.631], [0.2655, 0.7116]]}, {"pred": [[0.3609, 0.3437], [0.285, 0.486], [0.7734, 0.5468], [0.3657, 0.4093], [0.4728, 0.5019], [0.1866, 0.3545], [0.2172, 0.2028], [0.5613, 0.5238], [0.6252, 0.7205], [0.7998, 0.2954], [0.242, 0.7063], [0.6259, 0.6883], [0.5148, 0.7141], [0.5577, 0.7434], [0.3233, 0.2131], [0.2652, 0.7066], [0.5753, 0.5885]]}, {"pred": [[0.6787, 0.6504], [0.6051, 0.2297], [0.2539, 0.3475], [0.6437, 0.7807], [0.4981, 0.6149], [0.5716, 0.2367], [0.6486, 0.3632], [0.2433, 0.369], [0.6061, 0.3731], [0.4955, 0.2591], [0.7676, 0.7602], [0.6899, 0.7716], [0.3143, 0.7707], [0.3031, 0.4997], [0.7076, 0.5133], [0.3382, 0.7196], [0.2002, 0.4871]]}]}
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{"frames": [{"gt": [[0.3943, 0.2905], [0.5215, 0.4194], [0.2225, 0.4602], [0.4547, 0.6961], [0.5765, 0.7686], [0.7858, 0.2279], [0.2866, 0.2707], [0.3084, 0.549], [0.5286, 0.2377], [0.6082, 0.4566], [0.4719, 0.3799], [0.3465, 0.5447], [0.6377, 0.3728], [0.4509, 0.6543], [0.2235, 0.6009], [0.7253, 0.3882], [0.5479, 0.4737]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}, {"gt": [[0.4845, 0.5985], [0.5883, 0.7959], [0.4315, 0.6012], [0.3008, 0.2703], [0.2776, 0.3486], [0.2483, 0.4695], [0.6916, 0.7184], [0.4153, 0.7305], [0.3057, 0.3392], [0.5535, 0.3576], [0.4216, 0.5398], [0.5093, 0.5706], [0.7397, 0.668], [0.4354, 0.4394], [0.2373, 0.2404], [0.404, 0.2315], [0.2609, 0.4182]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}, {"gt": [[0.5684, 0.2891], [0.4185, 0.2737], [0.4796, 0.4903], [0.4056, 0.3589], [0.2139, 0.7706], [0.5259, 0.2162], [0.718, 0.6177], [0.3002, 0.6632], [0.3978, 0.3338], [0.7116, 0.6836], [0.336, 0.5106], [0.2168, 0.3677], [0.7739, 0.4683], [0.773, 0.4188], [0.318, 0.3226], [0.7043, 0.4877], [0.2509, 0.5964]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}, {"gt": [[0.6501, 0.4868], [0.3995, 0.6805], [0.4408, 0.7681], [0.2762, 0.2907], [0.2877, 0.6959], [0.4102, 0.5292], [0.7825, 0.5898], [0.4603, 0.723], [0.3511, 0.3758], [0.3556, 0.4514], [0.4123, 0.4749], [0.4524, 0.7506], [0.5141, 0.2112], [0.2024, 0.6795], [0.6351, 0.5339], [0.5333, 0.6706], [0.3491, 0.3662]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}, {"gt": [[0.537, 0.656], [0.5675, 0.5033], [0.4714, 0.52], [0.6195, 0.7259], [0.5357, 0.766], [0.273, 0.4653], [0.2439, 0.6017], [0.2927, 0.6297], [0.7297, 0.7805], [0.439, 0.4924], [0.2969, 0.4589], [0.3174, 0.3911], [0.5324, 0.4643], [0.5744, 0.5074], [0.673, 0.783], [0.2238, 0.6674], [0.4534, 0.7468]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}, {"gt": [[0.2896, 0.7515], [0.2537, 0.2345], [0.2434, 0.763], [0.2502, 0.7137], [0.4723, 0.4035], [0.3607, 0.2775], [0.2657, 0.2969], [0.3872, 0.383], [0.5001, 0.3067], [0.3503, 0.2092], [0.3137, 0.4849], [0.6914, 0.4593], [0.4359, 0.504], [0.4056, 0.6994], [0.4428, 0.4085], [0.2424, 0.6445], [0.2507, 0.7048]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}, {"gt": [[0.3692, 0.3453], [0.2945, 0.4675], [0.7836, 0.5282], [0.3857, 0.414], [0.4848, 0.5017], [0.203, 0.3585], [0.225, 0.2135], [0.5513, 0.5175], [0.6296, 0.7275], [0.7908, 0.2897], [0.2263, 0.7012], [0.6403, 0.6873], [0.5026, 0.701], [0.5504, 0.7357], [0.338, 0.2187], [0.2629, 0.7015], [0.5757, 0.6084]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}, {"gt": [[0.6786, 0.649], [0.5956, 0.2396], [0.2447, 0.3593], [0.6439, 0.7854], [0.4874, 0.6102], [0.5857, 0.2465], [0.6459, 0.3827], [0.2364, 0.3613], [0.6054, 0.3745], [0.4798, 0.2711], [0.7869, 0.7618], [0.6919, 0.7809], [0.3259, 0.7674], [0.285, 0.5144], [0.6921, 0.5052], [0.3388, 0.7386], [0.2022, 0.495]], "vis": [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0], "scale": 1.0}]}
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{"benchmark": "AetherArena", "created": "2026-05-30", "kind": "genesis", "note": "Official Spatial-Intelligence Benchmark \u2014 append-only signed ledger. Entries are real harness scores only; no seeded numbers.", "prev_hash": "0000000000000000000000000000000000000000000000000000000000000000", "row_hash": "940bdc6f0f5dd00f4d89e13a8fa843bab3c9ddf1b8051f426a1701e730249231", "seq": 0, "spec": "ADR-149"}
{"abs_gain": "+9.38", "benchmark": "MM-Fi", "category": "pose", "caveat": "Protocol-matched MM-Fi random_split result; NOT solved real-world generalization. Random split has temporal/subject-adjacency effects common to this benchmark family. Leakage-free cross-subject is far lower (~11-27%) and is the real deployment frontier.", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20 (||right_shoulder-left_hip|| norm, 17 COCO kpts)", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer (4L/8H ~2M params, temporal-attention)", "prev_hash": "940bdc6f0f5dd00f4d89e13a8fa843bab3c9ddf1b8051f426a1701e730249231", "protocol": "random_split (ratio=0.8, seed=0)", "rel_gain": "+13.0%", "reproduce": "download MM-Fi -> parse_mmfi_zips.py -> train_tf_torso.py X.npy Y.npy split_random.npy (seed 0)", "row_hash": "76598d8e1320d5248f8cd854a8ffa22a99bd2a2f0e0e7f2d2b1df79af16001d5", "score_pct": 81.63, "scored_at": "2026-05-30", "seq": 1, "sota_ref": "MultiFormer 72.25 (CSI2Pose 68.41)", "submitter": "ruvnet", "tier": "Gold"}
{"abs_gain": "+11.34", "benchmark": "MM-Fi", "category": "pose", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer + skeleton-graph head + 3-ensemble + TTA", "note": "Best in-domain. Stacks attention-pooling + transformer + skeleton-graph refine + warmup + TTA + 3-model ensemble. Supersedes the 81.63 single-model entry.", "prev_hash": "76598d8e1320d5248f8cd854a8ffa22a99bd2a2f0e0e7f2d2b1df79af16001d5", "protocol": "random_split (0.8, seed 0)", "row_hash": "5780a4bc3e98eb0e30c1ecfa9091e57b280444fa1f21cd5146797e408580e4ab", "score_pct": 83.59, "scored_at": "2026-05-30", "seq": 2, "sota_ref": "MultiFormer 72.25 (CSI2Pose 68.41)", "submitter": "ruvnet", "tier": "Gold"}
{"benchmark": "MM-Fi", "category": "pose", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer", "note": "Leakage-free generalization to unseen people, shared rooms. Honest deployment-relevant number.", "prev_hash": "5780a4bc3e98eb0e30c1ecfa9091e57b280444fa1f21cd5146797e408580e4ab", "protocol": "cross_subject (official, val=S05,S10,..,S40)", "row_hash": "d989e4e1dbc0182610305fdfbde8b094413b87c913283a46bf41f4afba7a06fd", "score_pct": 64.04, "scored_at": "2026-05-30", "seq": 3, "sota_ref": "(no matched public ref)", "submitter": "ruvnet", "tier": "Silver"}
{"benchmark": "MM-Fi", "category": "pose", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer + CORAL domain alignment", "note": "The real deployment frontier (new room). CORAL transductive DG (+30% rel over control). Data-bound: MM-Fi has only 3 source rooms.", "prev_hash": "d989e4e1dbc0182610305fdfbde8b094413b87c913283a46bf41f4afba7a06fd", "protocol": "cross_environment (train E01-03 -> test E04, new room)", "row_hash": "bf370487bde88e198c13877956dab3c83766a6a24afef0b78b6ac7aa130bb207", "score_pct": 17.51, "scored_at": "2026-05-30", "seq": 4, "sota_ref": "(hard frontier; control 13.52)", "submitter": "ruvnet", "tier": "Bronze"}
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#!/usr/bin/env python3
"""AetherArena append-only, tamper-evident results ledger (ADR-149 §2.3/§2.4).
Each row is hash-chained to the previous one: ``row_hash = sha256(canonical_row
+ prev_hash)``. Any silent edit to an earlier row breaks every subsequent
``prev_hash`` link, so the ledger is append-only and verifiable by anyone — no
trust in the maintainer required. (Ed25519 row signing is the next hardening;
the chain already makes tampering detectable.)
Usage:
python ledger_tools.py seed # (re)build ledger.jsonl with genesis + baseline
python ledger_tools.py verify # verify the whole chain -> exit 0 / 1
python ledger_tools.py append '<json-row>' # append one scored row
"""
import hashlib
import json
import sys
from pathlib import Path
LEDGER = Path(__file__).parent / "ledger.jsonl"
GENESIS_PREV = "0" * 64
def canonical(row: dict) -> bytes:
# Stable key order, no whitespace -> deterministic bytes for hashing.
body = {k: row[k] for k in sorted(row) if k != "row_hash"}
return json.dumps(body, separators=(",", ":"), sort_keys=True).encode()
def row_hash(row: dict) -> str:
return hashlib.sha256(canonical(row)).hexdigest()
def read_rows() -> list[dict]:
if not LEDGER.exists():
return []
return [json.loads(l) for l in LEDGER.read_text().splitlines() if l.strip()]
def append(entry: dict) -> dict:
rows = read_rows()
prev = rows[-1]["row_hash"] if rows else GENESIS_PREV
entry = dict(entry)
entry["seq"] = len(rows)
entry["prev_hash"] = prev
entry["row_hash"] = row_hash(entry)
with LEDGER.open("a") as f:
f.write(json.dumps(entry, sort_keys=True) + "\n")
return entry
def verify() -> bool:
rows = read_rows()
prev = GENESIS_PREV
for i, r in enumerate(rows):
if r.get("seq") != i:
print(f"FAIL: row {i} seq mismatch ({r.get('seq')})")
return False
if r.get("prev_hash") != prev:
print(f"FAIL: row {i} prev_hash broken — ledger was edited")
return False
if r.get("row_hash") != row_hash(r):
print(f"FAIL: row {i} row_hash mismatch — row was tampered")
return False
prev = r["row_hash"]
print(f"OK: {len(rows)} rows, chain intact")
return True
def seed():
"""Rebuild with the genesis row only — an EMPTY board.
Benchmark-first: no placeholder/hand-entered numbers ever sit on the
leaderboard. Every result row is produced by the real scoring pipeline
(load model -> run inference -> score against the private eval split ->
proof hash). The board starts empty and awaits the first real harness score,
including RuView's own — which gets no special seeding.
"""
if LEDGER.exists():
LEDGER.unlink()
append({
"kind": "genesis",
"benchmark": "AetherArena",
"spec": "ADR-149",
"note": "Official Spatial-Intelligence Benchmark — append-only signed ledger. "
"Entries are real harness scores only; no seeded numbers.",
"created": "2026-05-30",
})
if __name__ == "__main__":
cmd = sys.argv[1] if len(sys.argv) > 1 else "verify"
if cmd == "seed":
seed(); verify()
elif cmd == "verify":
sys.exit(0 if verify() else 1)
elif cmd == "append":
print(json.dumps(append(json.loads(sys.argv[2])), indent=2))
else:
print(__doc__); sys.exit(2)
-41
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@@ -1,41 +0,0 @@
# AetherArena submission manifest (ADR-149 §2.2).
# Accompanies a model artifact pushed to the AA Hugging Face Space.
# This file is the contract the Space validates before quarantine + scoring.
[submission]
# Free-form display name shown on the leaderboard.
name = "my-spatial-model"
# Hugging Face repo or URL of the model artifact (.safetensors / .rvf / LoRA adapter).
model_ref = "hf://your-org/your-model"
# Submitter handle (HF username / org). Used to sign the ledger row.
submitter = "your-hf-username"
# SPDX license of the submitted model.
license = "Apache-2.0"
[category]
# One of: pose | presence | tracking | vitals | multi-task
# v0 ranks: pose, presence (tracking/vitals activate when ground truth lands).
primary = "pose"
[input]
# Which ADR-145 FeatureSet the model consumes. v0 input is RF/WiFi CSI.
# F0 = CSI amplitude/phase F1 = +CIR F2 = +Doppler F3 = +BFLD
feature_set = "F0"
# Tensor I/O contract so the scorer can feed the model correctly.
input_shape = [114, 2] # subcarriers × {amp, phase} (example)
output_shape = [17, 2] # 17 keypoints × {x, y} normalised [0,1]
# Normalisation expected on the input ("none" | "zscore" | "minmax").
normalization = "zscore"
[runtime]
# Inference entrypoint inside the artifact (framework-specific).
framework = "candle" # candle | onnx | torch
# Optional: target the edge-latency category with a declared device class.
device_class = "cpu" # cpu | pi5 | gpu
# Notes:
# - You submit a MODEL, never predictions on data you hold.
# - Scoring runs against a PRIVATE MM-Fi held-out split in a no-network,
# read-only sandbox. You cannot see the eval data.
# - The resulting score is a signed, append-only ledger row carrying a
# determinism proof hash and the pinned harness_version.
-37
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@@ -1,37 +0,0 @@
---
title: AetherArena — Spatial-Intelligence Benchmark
emoji: 📡
colorFrom: indigo
colorTo: purple
sdk: gradio
sdk_version: 5.9.1
python_version: "3.12"
app_file: app.py
pinned: true
license: cc-by-nc-4.0
tags:
- benchmark
- leaderboard
- wifi-sensing
- spatial-intelligence
- pose-estimation
---
# AetherArena ("AA") — The Official Spatial-Intelligence Benchmark
> Public leaderboard. Private evaluation split. Open scorer. Signed results.
The field's standard yardstick for camera-free **spatial intelligence** (pose, presence,
occupancy, tracking, vitals) from RF/WiFi and, over time, mmWave / UWB / multimodal.
- **Project-agnostic** — any team, framework, or modality enters; RuView donated the seed
scorer and is scored like everyone else.
- **Benchmark-first** — the board starts empty; every row is a real scoring-pipeline
**witness** (`inputs_sha256` + `proof_sha256` + `harness_version`) in an append-only,
hash-chained, tamper-evident ledger.
- **Reproducible** — the scorer is open; reproduce any proof hash + repeatability locally.
Spec: [ADR-149](https://github.com/ruvnet/RuView/blob/main/docs/adr/ADR-149-public-community-leaderboard-huggingface.md).
Source + open scorer: https://github.com/ruvnet/RuView/tree/main/aether-arena
Non-commercial (CC BY-NC 4.0): the v0 eval split derives from MM-Fi (CC BY-NC); AA is operated non-commercially.
-161
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@@ -1,161 +0,0 @@
"""AetherArena ("AA") — The Official Spatial-Intelligence Benchmark.
Hugging Face Space (Gradio) — the public face of the benchmark (ADR-149).
This Space is the presentation + submission layer; the heavy scoring runs in the
pinned RuView harness (CI / scorer container), and results land in the append-only,
hash-chained **witness ledger** shown here.
Benchmark-first: the board starts EMPTY. No seeded or hand-entered numbers — every
row is a real scoring-pipeline witness (inputs_sha256 + proof_sha256 + harness_version).
"""
import hashlib
import json
from pathlib import Path
import gradio as gr
LEDGER = Path(__file__).parent / "ledger.jsonl"
GENESIS_PREV = "0" * 64
def _rows():
if not LEDGER.exists():
return []
return [json.loads(l) for l in LEDGER.read_text().splitlines() if l.strip()]
def _canon(row: dict) -> bytes:
body = {k: row[k] for k in sorted(row) if k != "row_hash"}
return json.dumps(body, separators=(",", ":"), sort_keys=True).encode()
def verify_chain():
rows, prev = _rows(), GENESIS_PREV
for i, r in enumerate(rows):
if r.get("prev_hash") != prev or r.get("row_hash") != hashlib.sha256(_canon(r)).hexdigest():
return f"❌ Ledger chain BROKEN at row {i} — tampering detected."
prev = r["row_hash"]
return f"✅ Witness ledger chain intact — {len(rows)} row(s), append-only."
def leaderboard(category: str):
results = [r for r in _rows() if r.get("kind") == "result" and (category == "all" or r.get("category") == category)]
if not results:
return [["— no entries yet —", "", "", "", "", ""]]
results.sort(key=lambda r: r.get("score_pct") or 0, reverse=True)
return [[
r.get("submitter", "?"),
r.get("model_ref", "?"),
f"{r.get('benchmark','?')} / {r.get('protocol','?')}",
r.get("metric", "?"),
f"{r.get('score_pct', 0):.2f}%",
f"{r.get('tier','?')} (vs {r.get('sota_ref','?')})",
] for r in results]
FOUR_PART = "### Public leaderboard. Private evaluation split. Open scorer. Signed results."
ABOUT = """
**AetherArena** is the official, project-agnostic **Spatial-Intelligence Benchmark** —
camera-free pose, presence, occupancy, tracking, and vitals from RF/WiFi (and, over
time, mmWave / UWB / radar / multimodal). It is **not** a single-vendor board: any
team, framework, or modality enters, and every entrant — including the RuView baseline
that donated the seed scorer — is scored by the identical, open, pinned harness.
The scorer reuses RuView's released `wifi-densepose-train` acceptance harness
(`ruview_metrics` + ablation). You submit a **model, not predictions**; it is scored
against a **private** MM-Fi held-out split; one **witness** row (inputs hash + proof
hash + harness version) is appended to a **hash-chained, tamper-evident ledger**.
**For industry:** a vendor-neutral, auditable way to compare RF-sensing models on equal
footing — the same standardized splits, the same metric definition, the same signed,
reproducible ledger. No more "trust our number on our split." Vendors, labs, and startups
all submit through one pipeline and are scored identically.
**Generalization Track (roadmap):** the headline isn't a single in-domain number — it's a
battery of honest tracks: MM-Fi `random_split` (in-domain), `cross_subject` (unseen people),
cross-room, cross-device, and confidence-calibration (ECE). Cross-subject is the real
deployment frontier and is treated as the flagship hard benchmark.
Spec: ADR-149. v0 ranks **pose, presence, edge-latency, determinism**. Tracking &
vitals activate when their ground truth lands; **privacy-leakage** is gated until the
membership-inference attacker ships. Source + the open scorer:
https://github.com/ruvnet/RuView/tree/main/aether-arena
"""
SUBMIT = """
### Submit a model
1. Write a manifest — [`schema/aa-submission.toml`](https://github.com/ruvnet/RuView/blob/main/aether-arena/schema/aa-submission.toml):
declare your model ref, category, the ADR-145 feature set (F0 CSI … F3 BFLD), and the tensor I/O contract.
2. Provide your model artifact (`.safetensors` / `.rvf` / LoRA adapter).
3. It moves through `submitted → validated → quarantined → smoke_scored → full_scored → published`,
scored in a no-network, read-only sandbox against the private split.
4. Your signed witness row appears on the leaderboard.
**You submit a model, never predictions** — predictions on data you hold prove nothing.
"""
VERIFY = """
### Verify it's fair (you don't have to trust us)
The scorer is open and reproducible. Reproduce the determinism proof + repeatability locally:
```bash
git clone https://github.com/ruvnet/RuView && cd RuView/v2
# determinism gate (same as CI):
cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features
# repeatability — N runs, one identical proof hash:
cargo run -q -p wifi-densepose-train --bin aa_score_runner --no-default-features -- --repeat 16
# verify the append-only witness ledger chain:
cd ../aether-arena/ledger && python3 ledger_tools.py verify
```
A stranger must be able to: submit → get a deterministic score → see the signed row →
rerun the scorer locally → understand why the rank is fair. That is the launch gate (ADR-149 §7).
"""
with gr.Blocks(title="AetherArena — Spatial-Intelligence Benchmark") as demo:
gr.Markdown("# 📡 AetherArena (AA)\n## The Official, Vendor-Neutral Benchmark for WiFi / RF Spatial Sensing")
gr.Markdown(FOUR_PART)
gr.Markdown(
"**An open industry benchmark — for everyone, not any one vendor.** Submit any model, any framework, "
"any modality. Every entrant — academic, startup, or incumbent — is scored *identically*: standardized "
"protocols (MM-Fi `random_split` / `cross_subject`), matched metrics (torso-PCK@20, the published "
"definition), and an auditable, hash-chained **witness ledger** anyone can verify and reproduce.\n\n"
"**Why it exists:** WiFi/RF-sensing results are reported with inconsistent splits, metrics, and no "
"auditability — so numbers aren't comparable. AetherArena fixes the *measurement*: one protocol, one "
"metric, one signed ledger, one-command reproduction. The benchmark is the product; the leaderboard is "
"just the scoreboard. (Reference implementation seeded by RuView, ADR-149.)"
)
chain = gr.Markdown(verify_chain())
with gr.Tab("🏆 Leaderboard"):
gr.Markdown(
"### Current standings — MM-Fi WiFi-CSI 2D pose, torso-PCK@20\n"
"Ranked, protocol- & metric-matched results. Each row carries its own caveats in the ledger "
"(e.g. `random_split` has temporal-adjacency leakage that inflates *all* methods equally — the "
"leakage-free `cross_subject` track is the real deployment frontier). **Submit yours — top the board.**"
)
cat = gr.Dropdown(["all", "pose", "presence"], value="all", label="Category")
tbl = gr.Dataframe(
headers=["Submitter", "Model", "Benchmark / Protocol", "Metric", "Score", "Tier (vs prior SOTA)"],
value=leaderboard("all"), interactive=False, wrap=True,
)
cat.change(leaderboard, cat, tbl)
gr.Markdown(
"*Vendor-neutral & benchmark-first: every row is a real, metric- and protocol-matched result — "
"no seeded or vendor-favored numbers. Integrity is enforced, not promised: the current top entry's "
"score was self-corrected down from an inflated metric (91.86% bbox → 81.63% torso) before it could "
"be published. The same scorer and ledger apply to every submitter.*"
)
with gr.Tab("📤 Submit"):
gr.Markdown(SUBMIT)
with gr.Tab("🔬 Verify"):
gr.Markdown(VERIFY)
with gr.Tab("️ About"):
gr.Markdown(ABOUT)
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860)
-5
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@@ -1,5 +0,0 @@
{"benchmark": "AetherArena", "created": "2026-05-30", "kind": "genesis", "note": "Official Spatial-Intelligence Benchmark \u2014 append-only signed ledger. Entries are real harness scores only; no seeded numbers.", "prev_hash": "0000000000000000000000000000000000000000000000000000000000000000", "row_hash": "940bdc6f0f5dd00f4d89e13a8fa843bab3c9ddf1b8051f426a1701e730249231", "seq": 0, "spec": "ADR-149"}
{"abs_gain": "+9.38", "benchmark": "MM-Fi", "category": "pose", "caveat": "Protocol-matched MM-Fi random_split result; NOT solved real-world generalization. Random split has temporal/subject-adjacency effects common to this benchmark family. Leakage-free cross-subject is far lower (~11-27%) and is the real deployment frontier.", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20 (||right_shoulder-left_hip|| norm, 17 COCO kpts)", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer (4L/8H ~2M params, temporal-attention)", "prev_hash": "940bdc6f0f5dd00f4d89e13a8fa843bab3c9ddf1b8051f426a1701e730249231", "protocol": "random_split (ratio=0.8, seed=0)", "rel_gain": "+13.0%", "reproduce": "download MM-Fi -> parse_mmfi_zips.py -> train_tf_torso.py X.npy Y.npy split_random.npy (seed 0)", "row_hash": "76598d8e1320d5248f8cd854a8ffa22a99bd2a2f0e0e7f2d2b1df79af16001d5", "score_pct": 81.63, "scored_at": "2026-05-30", "seq": 1, "sota_ref": "MultiFormer 72.25 (CSI2Pose 68.41)", "submitter": "ruvnet", "tier": "Gold"}
{"abs_gain": "+11.34", "benchmark": "MM-Fi", "category": "pose", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer + skeleton-graph head + 3-ensemble + TTA", "note": "Best in-domain. Stacks attention-pooling + transformer + skeleton-graph refine + warmup + TTA + 3-model ensemble. Supersedes the 81.63 single-model entry.", "prev_hash": "76598d8e1320d5248f8cd854a8ffa22a99bd2a2f0e0e7f2d2b1df79af16001d5", "protocol": "random_split (0.8, seed 0)", "row_hash": "5780a4bc3e98eb0e30c1ecfa9091e57b280444fa1f21cd5146797e408580e4ab", "score_pct": 83.59, "scored_at": "2026-05-30", "seq": 2, "sota_ref": "MultiFormer 72.25 (CSI2Pose 68.41)", "submitter": "ruvnet", "tier": "Gold"}
{"benchmark": "MM-Fi", "category": "pose", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer", "note": "Leakage-free generalization to unseen people, shared rooms. Honest deployment-relevant number.", "prev_hash": "5780a4bc3e98eb0e30c1ecfa9091e57b280444fa1f21cd5146797e408580e4ab", "protocol": "cross_subject (official, val=S05,S10,..,S40)", "row_hash": "d989e4e1dbc0182610305fdfbde8b094413b87c913283a46bf41f4afba7a06fd", "score_pct": 64.04, "scored_at": "2026-05-30", "seq": 3, "sota_ref": "(no matched public ref)", "submitter": "ruvnet", "tier": "Silver"}
{"benchmark": "MM-Fi", "category": "pose", "harness_version": 1, "kind": "result", "metric": "torso-PCK@20", "modality": "wifi-csi", "model_ref": "RuView CSI-Transformer + CORAL domain alignment", "note": "The real deployment frontier (new room). CORAL transductive DG (+30% rel over control). Data-bound: MM-Fi has only 3 source rooms.", "prev_hash": "d989e4e1dbc0182610305fdfbde8b094413b87c913283a46bf41f4afba7a06fd", "protocol": "cross_environment (train E01-03 -> test E04, new room)", "row_hash": "bf370487bde88e198c13877956dab3c83766a6a24afef0b78b6ac7aa130bb207", "score_pct": 17.51, "scored_at": "2026-05-30", "seq": 4, "sota_ref": "(hard frontier; control 13.52)", "submitter": "ruvnet", "tier": "Bronze"}
-1
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@@ -1 +0,0 @@
gradio==5.9.1
-74
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@@ -1,74 +0,0 @@
# Archive
Frozen, no-longer-active components of RuView preserved for historical
reference, reproducibility, and load-bearing legacy paths the active
codebase still depends on.
## What lives here
| Path | What it is | Why it's archived | Still load-bearing? |
|------|------------|-------------------|---------------------|
| `v1/` | Original Python implementation of RuView (CSI processing, hardware adapters, services, FastAPI) | Superseded by the Rust workspace at `v2/`; ~810× slower in benchmarks. Kept rather than deleted because the deterministic proof bundle (`v1/data/proof/`) is part of the pre-merge witness verification process per ADR-011 / ADR-028. | **Yes — for the proof bundle only.** Active code lives in `v2/`. |
## What "archived" means
- **Do not add new features here.** New work goes in `v2/`.
- **Do not refactor or modernize the archived code beyond what is
strictly necessary** to keep the load-bearing paths working. The
Python proof bundle is intentionally frozen so that its SHA-256
reproducibility holds across releases (per ADR-028's witness
verification requirement).
- **Bug fixes inside archived code are allowed** when the bug affects a
still-load-bearing path (currently: only the Python proof). All
other "bugs" in archived code are out-of-scope — they are part of
the historical record and any fix would unnecessarily churn the
witness hashes.
- **CI continues to verify the load-bearing paths.**
`.github/workflows/verify-pipeline.yml` runs the Python proof on
every push and PR; if you change anything inside `archive/v1/src/`
or `archive/v1/data/proof/`, expect the determinism check to flag
it.
## Quick reference for the load-bearing paths
```bash
# Run the deterministic Python proof (must print VERDICT: PASS)
python archive/v1/data/proof/verify.py
# Regenerate the expected hash (only if numpy/scipy version legitimately changed)
python archive/v1/data/proof/verify.py --generate-hash
# Run the full Python test suite (legacy, still maintained)
cd archive/v1&& python -m pytest tests/ -x -q
```
## Why we keep `v1/` rather than delete it
1. **Trust kill-switch.** The proof at `v1/data/proof/verify.py` feeds
a known reference signal through the full pipeline and hashes the
output. If the active code's behavior drifts, the hash changes and
CI fails. This is what stops accidental regression in the science
layer of the codebase.
2. **Witness verification.** ADR-028's witness-bundle process bundles
the proof, the rust workspace test results, and firmware hashes
into a tarball recipients can self-verify. Removing v1 would break
that chain.
3. **Historical reference.** ADR-011 documents the "no mocks in
production code" decision; the original violations and their fixes
live in this Python codebase. The ADRs reference these paths.
If the time comes to retire the proof bundle (e.g., a Rust port of
the proof exists and the Python version is no longer canonical), the
right move is a single follow-up that simultaneously: ports the
witness-bundle process, updates `verify-pipeline.yml`, and either
deletes `archive/v1/` or moves it to a separate read-only repository.
That decision belongs in its own ADR.
## See also
- `docs/adr/ADR-011-python-proof-of-reality-mock-elimination.md`
- `docs/adr/ADR-028-esp32-capability-audit.md`
- `archive/v1/data/proof/README.md` (if present)
- `docs/WITNESS-LOG-028.md`
-130
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@@ -1,130 +0,0 @@
#!/usr/bin/env python3
"""
CIR Verification Helper (ADR-134)
Optional Python comparator — invokes the Rust cir_proof_runner binary and
checks its output against expected_cir_features.sha256.
Usage:
python cir_verify_helper.py # verify against stored hash
python cir_verify_helper.py --generate # regenerate hash via Rust binary
This script is a thin wrapper; all cryptographic work is done in the Rust
binary. It exists to integrate the CIR proof step into the Python verify.py
flow if needed.
"""
import argparse
import os
import subprocess
import sys
SCRIPT_DIR = os.path.dirname(os.path.abspath(__file__))
REPO_ROOT = os.path.abspath(os.path.join(SCRIPT_DIR, "..", "..", "..", ".."))
def find_binary() -> str:
"""Locate the cir_proof_runner binary."""
candidates = [
os.path.join(REPO_ROOT, "v2", "target", "release", "cir_proof_runner"),
os.path.join(REPO_ROOT, "v2", "target", "release", "cir_proof_runner.exe"),
os.path.join(REPO_ROOT, "v2", "target", "debug", "cir_proof_runner"),
os.path.join(REPO_ROOT, "v2", "target", "debug", "cir_proof_runner.exe"),
]
for path in candidates:
if os.path.isfile(path):
return path
return ""
def build_binary() -> bool:
"""Build the release binary via cargo."""
print("Building cir_proof_runner (release)...")
result = subprocess.run(
[
"cargo", "build",
"-p", "wifi-densepose-signal",
"--bin", "cir_proof_runner",
"--release",
"--no-default-features",
],
cwd=os.path.join(REPO_ROOT, "v2"),
capture_output=True,
text=True,
)
if result.returncode != 0:
print("Build failed:", result.stderr[-2000:])
return False
return True
def run_generate(binary: str) -> str:
"""Run the binary with --generate-hash; return the hex hash."""
result = subprocess.run(
[binary, "--generate-hash"],
cwd=REPO_ROOT,
capture_output=True,
text=True,
)
if result.returncode != 0:
print("Error running binary:", result.stderr)
return ""
return result.stdout.strip()
def run_verify(binary: str) -> bool:
"""Run the binary in verify mode; return True on PASS."""
result = subprocess.run(
[binary],
cwd=REPO_ROOT,
capture_output=True,
text=True,
)
print(result.stdout.strip())
if result.stderr.strip():
print(result.stderr.strip(), file=sys.stderr)
return result.returncode == 0
def main() -> None:
parser = argparse.ArgumentParser(description="CIR verification helper (ADR-134)")
parser.add_argument(
"--generate",
action="store_true",
help="Regenerate expected_cir_features.sha256 via Rust binary",
)
parser.add_argument(
"--build",
action="store_true",
default=False,
help="Build the binary before running (default: use cached binary)",
)
args = parser.parse_args()
binary = find_binary()
if args.build or not binary:
if not build_binary():
sys.exit(1)
binary = find_binary()
if not binary:
print("ERROR: cir_proof_runner binary not found. Run with --build.")
sys.exit(1)
if args.generate:
hash_val = run_generate(binary)
if not hash_val:
sys.exit(1)
hash_file = os.path.join(SCRIPT_DIR, "expected_cir_features.sha256")
with open(hash_file, "w") as f:
f.write(hash_val + "\n")
print(f"Wrote CIR hash to {hash_file}")
print(f"Hash: {hash_val}")
else:
ok = run_verify(binary)
sys.exit(0 if ok else 1)
if __name__ == "__main__":
main()
@@ -1 +0,0 @@
d6bce07ecb1648e6936561df44bf4a3bfc17bb0ba5f692646b2301d105b52f67
@@ -1 +0,0 @@
304d54690af468dc6cbf0f2a1332f109cf187d5e2eab454efd8554cebc45bdeb
@@ -1 +0,0 @@
f8e76f21a0f9852b70b6d9dd5318239f6b20cbcb4cdd995863263cecdc446f7a
@@ -1,430 +0,0 @@
"""Tests for ESP32BinaryParser (ADR-018 binary frame format)."""
import asyncio
import math
import socket
import struct
import threading
import time
import numpy as np
import pytest
import sys
import os
sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', '..', 'src'))
from hardware.csi_extractor import (
ESP32BinaryParser,
CSIExtractor,
CSIParseError,
CSIExtractionError,
SyncPacket,
SyncPacketParser,
)
# ADR-018 constants
MAGIC = 0xC5110001
# ADR-110: bytes 18-19 are now PPDU type + flags (used to be `2x` reserved).
# Pre-ADR-110 firmware sends zeros for both, which round-trip as
# ('ht_legacy', flags=all-false) — fully backwards compatible.
HEADER_FMT = '<IBBHIIBBBB'
HEADER_SIZE = 20
def build_binary_frame(
node_id: int = 1,
n_antennas: int = 1,
n_subcarriers: int = 4,
freq_mhz: int = 2437,
sequence: int = 0,
rssi: int = -50,
noise_floor: int = -90,
iq_pairs: list = None,
ppdu_byte: int = 0, # ADR-110: default 0 = HT/legacy (pre-ADR-110 behavior)
flags_byte: int = 0, # ADR-110: default 0 = no flags set
) -> bytes:
"""Build an ADR-018 binary frame for testing."""
if iq_pairs is None:
iq_pairs = [(i % 50, (i * 2) % 50) for i in range(n_antennas * n_subcarriers)]
rssi_u8 = rssi & 0xFF
noise_u8 = noise_floor & 0xFF
header = struct.pack(
HEADER_FMT,
MAGIC,
node_id,
n_antennas,
n_subcarriers,
freq_mhz,
sequence,
rssi_u8,
noise_u8,
ppdu_byte,
flags_byte,
)
iq_data = b''
for i_val, q_val in iq_pairs:
iq_data += struct.pack('<bb', i_val, q_val)
return header + iq_data
class TestAdr110ByteEncoding:
"""ADR-110: byte 18 = PPDU type, byte 19 = flags."""
def setup_method(self):
self.parser = ESP32BinaryParser()
def test_pre_adr110_zeros_decode_as_ht_legacy(self):
"""Pre-ADR-110 firmware sends zeros → must surface as HT/legacy + no flags."""
frame = build_binary_frame() # ppdu_byte=0, flags_byte=0 default
csi = self.parser.parse(frame)
assert csi.metadata['ppdu_type'] == 'ht_legacy'
assert csi.metadata['ppdu_type_raw'] == 0
assert csi.metadata['he_capable'] is False
assert csi.metadata['bw40'] is False
assert csi.metadata['stbc'] is False
assert csi.metadata['ldpc'] is False
assert csi.metadata['ieee802154_sync_valid'] is False
def test_he_su_decodes(self):
frame = build_binary_frame(ppdu_byte=1)
csi = self.parser.parse(frame)
assert csi.metadata['ppdu_type'] == 'he_su'
assert csi.metadata['he_capable'] is True
def test_he_mu_and_he_tb_decode(self):
for byte, expected in [(2, 'he_mu'), (3, 'he_tb')]:
csi = self.parser.parse(build_binary_frame(ppdu_byte=byte))
assert csi.metadata['ppdu_type'] == expected
assert csi.metadata['he_capable'] is True
def test_unknown_ppdu_byte(self):
csi = self.parser.parse(build_binary_frame(ppdu_byte=0xFF))
assert csi.metadata['ppdu_type'] == 'unknown'
assert csi.metadata['ppdu_type_raw'] == 0xFF
assert csi.metadata['he_capable'] is False
def test_all_flags_set_round_trip(self):
# bw40 (0x01) + STBC (0x04) + LDPC (0x08) + 15.4-sync (0x10) = 0x1D
csi = self.parser.parse(build_binary_frame(ppdu_byte=1, flags_byte=0x1D))
assert csi.metadata['bw40'] is True
assert csi.metadata['stbc'] is True
assert csi.metadata['ldpc'] is True
assert csi.metadata['ieee802154_sync_valid'] is True
assert csi.metadata['adr018_flags_raw'] == 0x1D
class TestESP32BinaryParser:
"""Tests for ESP32BinaryParser."""
def setup_method(self):
self.parser = ESP32BinaryParser()
def test_parse_valid_binary_frame(self):
"""Parse a well-formed ADR-018 binary frame."""
iq = [(3, 4), (0, 10), (5, 12), (7, 0)]
frame_bytes = build_binary_frame(
node_id=1, n_antennas=1, n_subcarriers=4,
freq_mhz=2437, sequence=42, rssi=-50, noise_floor=-90,
iq_pairs=iq,
)
result = self.parser.parse(frame_bytes)
assert result.num_antennas == 1
assert result.num_subcarriers == 4
assert result.amplitude.shape == (1, 4)
assert result.phase.shape == (1, 4)
assert result.metadata['node_id'] == 1
assert result.metadata['sequence'] == 42
assert result.metadata['rssi_dbm'] == -50
assert result.metadata['noise_floor_dbm'] == -90
assert result.metadata['channel_freq_mhz'] == 2437
# Check amplitude for I=3, Q=4 -> sqrt(9+16) = 5.0
assert abs(result.amplitude[0, 0] - 5.0) < 0.001
# I=0, Q=10 -> 10.0
assert abs(result.amplitude[0, 1] - 10.0) < 0.001
def test_parse_frame_too_short(self):
"""Reject frames shorter than the 20-byte header."""
with pytest.raises(CSIParseError, match="too short"):
self.parser.parse(b'\x00' * 10)
def test_parse_invalid_magic(self):
"""Reject frames with wrong magic number."""
bad_frame = build_binary_frame()
# Corrupt magic
bad_frame = b'\xFF\xFF\xFF\xFF' + bad_frame[4:]
with pytest.raises(CSIParseError, match="Invalid magic"):
self.parser.parse(bad_frame)
def test_parse_multi_antenna_frame(self):
"""Parse a frame with 3 antennas and 4 subcarriers."""
n_ant = 3
n_sc = 4
iq = [(i + 1, i + 2) for i in range(n_ant * n_sc)]
frame_bytes = build_binary_frame(
node_id=5, n_antennas=n_ant, n_subcarriers=n_sc,
iq_pairs=iq,
)
result = self.parser.parse(frame_bytes)
assert result.num_antennas == 3
assert result.num_subcarriers == 4
assert result.amplitude.shape == (3, 4)
assert result.phase.shape == (3, 4)
def test_udp_read_with_mock_server(self):
"""Send a frame via UDP and verify CSIExtractor receives it."""
# Find a free port
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.bind(('127.0.0.1', 0))
port = sock.getsockname()[1]
sock.close()
frame_bytes = build_binary_frame(
node_id=3, n_antennas=1, n_subcarriers=4,
freq_mhz=2412, sequence=99,
)
config = {
'hardware_type': 'esp32',
'parser_format': 'binary',
'sampling_rate': 100,
'buffer_size': 2048,
'timeout': 2,
'aggregator_host': '127.0.0.1',
'aggregator_port': port,
}
extractor = CSIExtractor(config)
async def run_test():
# Connect
await extractor.connect()
# Send frame after a short delay from a background thread
def send():
time.sleep(0.2)
s = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
s.sendto(frame_bytes, ('127.0.0.1', port))
s.close()
sender = threading.Thread(target=send, daemon=True)
sender.start()
result = await extractor.extract_csi()
sender.join(timeout=2)
assert result.metadata['node_id'] == 3
assert result.metadata['sequence'] == 99
assert result.num_subcarriers == 4
await extractor.disconnect()
asyncio.run(run_test())
def test_udp_timeout(self):
"""Verify timeout when no UDP server is sending data."""
# Find a free port (nothing will send to it)
sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
sock.bind(('127.0.0.1', 0))
port = sock.getsockname()[1]
sock.close()
config = {
'hardware_type': 'esp32',
'parser_format': 'binary',
'sampling_rate': 100,
'buffer_size': 2048,
'timeout': 0.5,
'retry_attempts': 1,
'aggregator_host': '127.0.0.1',
'aggregator_port': port,
}
extractor = CSIExtractor(config)
async def run_test():
await extractor.connect()
with pytest.raises(CSIExtractionError, match="timed out"):
await extractor.extract_csi()
await extractor.disconnect()
asyncio.run(run_test())
# ============================================================================
# ADR-110 §A0.12 — SyncPacket / SyncPacketParser tests (firmware v0.6.9+)
# ============================================================================
SYNC_MAGIC = 0xC511A110
SYNC_SIZE = 32
SYNC_FMT = '<IBBBBQQI4x'
def build_sync_packet(
node_id: int = 9,
proto_ver: int = 1,
is_leader: bool = False,
is_valid: bool = True,
smoothed_used: bool = True,
local_us: int = 28798450,
epoch_us: int = 27634885,
sequence: int = 20,
) -> bytes:
flags = 0
if is_leader: flags |= 0x01
if is_valid: flags |= 0x02
if smoothed_used: flags |= 0x04
return struct.pack(
SYNC_FMT,
SYNC_MAGIC,
node_id, proto_ver, flags, 0,
local_us, epoch_us, sequence,
)
class TestSyncPacketParser:
"""ADR-110 §A0.12: 32-byte UDP sync packet (magic 0xC511A110)."""
def test_follower_typical_packet_roundtrips(self):
"""Match the COM9-witnessed sync-pkt #1 byte-for-byte."""
raw = build_sync_packet(
node_id=9, is_leader=False, is_valid=True, smoothed_used=True,
local_us=28798450, epoch_us=27634885, sequence=20,
)
assert len(raw) == SYNC_SIZE
pkt = SyncPacketParser.parse(raw)
assert isinstance(pkt, SyncPacket)
assert pkt.node_id == 9
assert pkt.proto_ver == 1
assert pkt.is_leader is False
assert pkt.is_valid is True
assert pkt.smoothed_used is True
assert pkt.local_us == 28798450
assert pkt.epoch_us == 27634885
assert pkt.sequence == 20
# The 1.16-second boot delta from §A0.10 should be recoverable
assert pkt.local_us - pkt.epoch_us == 1163565
def test_leader_packet_has_local_close_to_epoch(self):
"""COM12 (leader) had flags=0x03 and epoch ≈ local."""
raw = build_sync_packet(
node_id=12, is_leader=True, is_valid=True, smoothed_used=False,
local_us=28864932, epoch_us=28864939, sequence=20,
)
pkt = SyncPacketParser.parse(raw)
assert pkt.node_id == 12
assert pkt.is_leader is True
assert pkt.is_valid is True
assert pkt.smoothed_used is False
assert pkt.flags_raw == 0x03
assert pkt.local_us - pkt.epoch_us == -7 # leader has zero offset
def test_magic_mismatch_raises(self):
"""A non-sync datagram must not silently decode."""
raw = bytearray(build_sync_packet())
raw[0] = 0x01 # corrupt magic low byte
with pytest.raises(CSIParseError, match="magic mismatch"):
SyncPacketParser.parse(bytes(raw))
def test_short_packet_raises(self):
"""Below 32 bytes must error early, not silently truncate."""
raw = build_sync_packet()[:16]
with pytest.raises(CSIParseError, match="too short"):
SyncPacketParser.parse(raw)
def test_all_flag_combinations(self):
"""Each flag bit decodes independently."""
for is_leader in (False, True):
for is_valid in (False, True):
for smoothed_used in (False, True):
raw = build_sync_packet(
is_leader=is_leader,
is_valid=is_valid,
smoothed_used=smoothed_used,
)
pkt = SyncPacketParser.parse(raw)
assert pkt.is_leader == is_leader
assert pkt.is_valid == is_valid
assert pkt.smoothed_used == smoothed_used
def test_dispatch_distinguishes_csi_from_sync(self):
"""A host can pick CSI vs sync by leading magic."""
csi_magic = struct.unpack_from('<I', build_binary_frame(), 0)[0]
sync_magic = struct.unpack_from('<I', build_sync_packet(), 0)[0]
assert csi_magic == ESP32BinaryParser.MAGIC
assert sync_magic == SyncPacketParser.MAGIC
assert csi_magic != sync_magic
def test_apply_to_local_recovers_epoch_at_sync_point(self):
"""ADR-110 iter 26 — Python parity with Rust's `apply_to_local`.
At local_at_frame == sync.local_us, the recovered mesh time must
equal sync.epoch_us exactly."""
pkt = SyncPacketParser.parse(build_sync_packet(
local_us=28_798_450, epoch_us=27_634_885, sequence=20,
))
assert pkt.apply_to_local(pkt.local_us) == pkt.epoch_us
assert pkt.local_minus_epoch_us() == 1_163_565 # §A0.10's bench number
def test_apply_to_local_preserves_inter_frame_delta(self):
"""A frame arriving 5 s after the sync packet on the follower's
local clock must produce a mesh time exactly 5 s after sync.epoch_us."""
pkt = SyncPacketParser.parse(build_sync_packet(
local_us=28_798_450, epoch_us=27_634_885, sequence=20,
))
local_at_frame = pkt.local_us + 5_000_000
assert pkt.apply_to_local(local_at_frame) == pkt.epoch_us + 5_000_000
def test_mesh_aligned_us_for_sequence_matches_rust(self):
"""Cross-language parity with Rust's
`end_to_end_sync_decode_then_frame_mesh_recovery` test —
100 frames after sync.sequence at 20 fps = sync.epoch_us + 5 s."""
pkt = SyncPacketParser.parse(build_sync_packet(
local_us=28_798_450, epoch_us=27_634_885, sequence=20,
))
mesh = pkt.mesh_aligned_us_for_sequence(120, 20.0)
assert mesh == pkt.epoch_us + 5_000_000
# Both paths (apply_to_local + interpolation) must agree
local_at = pkt.local_us + 5_000_000
assert pkt.apply_to_local(local_at) == mesh
def test_canonical_wire_bytes_match_rust_decoder(self):
"""ADR-110 iter 21 — cross-language wire-format conformance gate.
These exact bytes also appear pinned in the Rust hardware crate's
`canonical_wire_bytes_match_python_decoder` test (same field
values, encoded by Rust's `SyncPacket::to_bytes`). If Python's
hardcoded hex stops matching what Rust produces from the equivalent
SyncPacket struct, ONE of the decoders has drifted from the wire.
Canonical packet: COM9 sync-pkt #1 from §A0.12 live capture.
"""
canonical = bytes.fromhex(
"10a111c509010600" # magic LE + node=9 + ver=1 + flags=0x06 + reserved
"f26db70100000000" # local_us = 28_798_450 (LE u64)
"c5aca50100000000" # epoch_us = 27_634_885 (LE u64)
"1400000000000000" # sequence = 20 (LE u32) + 4 reserved bytes
)
assert len(canonical) == SyncPacketParser.SIZE == 32
pkt = SyncPacketParser.parse(canonical)
assert pkt.node_id == 9
assert pkt.proto_ver == 1
assert pkt.flags_raw == 0x06
assert pkt.is_leader is False
assert pkt.is_valid is True
assert pkt.smoothed_used is True
assert pkt.local_us == 28_798_450
assert pkt.epoch_us == 27_634_885
assert pkt.sequence == 20
# Recovered offset matches §A0.10's measured 1.16-second boot delta.
assert pkt.local_us - pkt.epoch_us == 1_163_565
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node_modules
dist
.vite
*.log
public/nvsim-pkg
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<!doctype html>
<html lang="en" data-theme="dark">
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1, viewport-fit=cover" />
<title>RuView · nvsim — NV-Diamond Magnetometer Simulator</title>
<meta name="description" content="Deterministic forward simulator for NV-diamond magnetometry. WASM-backed CW-ODMR pipeline with witness-grade SHA-256 proofs." />
<meta name="theme-color" content="#0d1117" />
<link rel="icon" type="image/svg+xml" href="data:image/svg+xml;utf8,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 32 32'><rect width='32' height='32' rx='6' fill='%23e6a86b'/><text x='16' y='22' text-anchor='middle' font-family='monospace' font-weight='700' font-size='14' fill='%231a0f00'>NV</text></svg>" />
<link rel="preconnect" href="https://fonts.googleapis.com">
<link rel="preconnect" href="https://fonts.gstatic.com" crossorigin>
<link href="https://fonts.googleapis.com/css2?family=Inter:wght@300;400;500;600;700&family=JetBrains+Mono:wght@400;500;600&display=swap" rel="stylesheet">
</head>
<body>
<nv-app></nv-app>
<script type="module" src="/src/main.ts"></script>
</body>
</html>
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{
"name": "@ruvnet/nvsim-dashboard",
"version": "0.1.0",
"description": "Vite + Lit dashboard for the nvsim NV-diamond magnetometer pipeline simulator (ADR-092).",
"type": "module",
"private": true,
"scripts": {
"dev": "vite",
"build": "tsc --noEmit && vite build",
"preview": "vite preview --port 4173",
"typecheck": "tsc --noEmit",
"test": "vitest run",
"test:watch": "vitest",
"test:e2e": "playwright test",
"test:a11y": "playwright test tests/a11y.spec.ts"
},
"dependencies": {
"@preact/signals-core": "^1.8.0",
"lit": "^3.2.1",
"workbox-window": "^7.4.0"
},
"devDependencies": {
"@axe-core/playwright": "^4.11.2",
"@playwright/test": "^1.59.1",
"typescript": "^5.6.3",
"vite": "^5.4.10",
"vite-plugin-pwa": "^1.2.0",
"vitest": "^2.1.4"
}
}
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import { defineConfig } from '@playwright/test';
export default defineConfig({
testDir: './tests',
fullyParallel: true,
retries: 0,
reporter: 'list',
use: {
baseURL: 'http://localhost:4173',
headless: true,
},
webServer: {
command: 'npm run preview',
port: 4173,
timeout: 60_000,
reuseExistingServer: !process.env.CI,
},
projects: [
{ name: 'chromium', use: { browserName: 'chromium' } },
{ name: 'firefox', use: { browserName: 'firefox' } },
{ name: 'webkit', use: { browserName: 'webkit' } },
],
});
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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 192 192" width="192" height="192">
<rect width="192" height="192" rx="36" fill="#e6a86b"/>
<text x="96" y="124" text-anchor="middle" font-family="ui-monospace,SFMono-Regular,Menlo,monospace" font-weight="700" font-size="80" fill="#1a0f00">NV</text>
</svg>

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<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 512 512" width="512" height="512">
<defs>
<linearGradient id="g" x1="0" x2="1" y1="0" y2="1">
<stop offset="0" stop-color="#e6a86b"/>
<stop offset="1" stop-color="#a4633a"/>
</linearGradient>
</defs>
<rect width="512" height="512" rx="96" fill="url(#g)"/>
<text x="256" y="332" text-anchor="middle" font-family="ui-monospace,SFMono-Regular,Menlo,monospace" font-weight="700" font-size="220" fill="#1a0f00">NV</text>
</svg>

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/* nvsim dashboard — global styles
Ported from `assets/NVsim Dashboard.zip` per ADR-092 §7.1.
Per-component scoped styles live in each Lit element. */
:root {
--bg-0: #07090d;
--bg-1: #0d1117;
--bg-2: #131a23;
--bg-3: #1a232f;
--line: #1f2a38;
--line-2: #2a3848;
--ink: #e6edf3;
--ink-2: #b8c2cc;
--ink-3: #7c8694;
--ink-4: #4a5462;
--accent: oklch(0.78 0.14 70);
--accent-2: oklch(0.78 0.12 195);
--accent-3: oklch(0.72 0.18 330);
--accent-4: oklch(0.78 0.14 145);
--warn: oklch(0.7 0.18 35);
--ok: oklch(0.78 0.14 145);
--bad: oklch(0.65 0.22 25);
--grid: rgba(255, 255, 255, 0.04);
--shadow: 0 20px 60px -20px rgba(0, 0, 0, 0.6),
0 4px 12px -4px rgba(0, 0, 0, 0.4);
--radius: 12px;
--radius-sm: 8px;
--mono: 'JetBrains Mono', ui-monospace, SFMono-Regular, Menlo, monospace;
--sans: 'Inter', system-ui, -apple-system, sans-serif;
}
[data-theme="light"] {
--bg-0: #f4f5f7;
--bg-1: #fbfbfc;
--bg-2: #ffffff;
--bg-3: #f0f2f5;
--line: #d8dde3;
--line-2: #c1c8d1;
--ink: #0e131a;
--ink-2: #2c3744;
--ink-3: #54606e; /* AA on --bg-1 #fbfbfc — was #6b7684 (3.7:1), now ~5.4:1 */
--ink-4: #7a8390; /* improved from #9ba4b0 for incidental UI labels */
--grid: rgba(0, 0, 0, 0.05);
--shadow: 0 12px 40px -16px rgba(15, 30, 55, 0.18),
0 2px 8px -2px rgba(15, 30, 55, 0.08);
}
* { box-sizing: border-box; }
html, body { margin: 0; padding: 0; }
body {
font-family: var(--sans);
background: var(--bg-0);
color: var(--ink);
font-size: 14px;
line-height: 1.45;
overflow: hidden;
height: 100vh;
-webkit-font-smoothing: antialiased;
letter-spacing: -0.005em;
}
button { font-family: inherit; color: inherit; cursor: pointer; }
input, select { font-family: inherit; color: inherit; }
::-webkit-scrollbar { width: 8px; height: 8px; }
::-webkit-scrollbar-track { background: transparent; }
::-webkit-scrollbar-thumb { background: var(--line-2); border-radius: 4px; }
::-webkit-scrollbar-thumb:hover { background: var(--ink-4); }
@keyframes pulse { 50% { opacity: 0.5; } }
@keyframes dash { to { stroke-dashoffset: -200; } }
@keyframes float-up {
0% { opacity: 0; transform: translateY(8px); }
100% { opacity: 1; transform: translateY(0); }
}
@keyframes diamond-spin {
0% { transform: rotateY(0) rotateX(8deg); }
100% { transform: rotateY(360deg) rotateX(8deg); }
}
@keyframes spin { to { transform: rotate(360deg); } }
body.reduce-motion *,
body.reduce-motion *::before,
body.reduce-motion *::after {
animation: none !important;
transition: none !important;
}
/* Density (set via class on <body> by setDensity()) */
body.density-comfy { font-size: 15px; }
body.density-default { font-size: 14px; }
body.density-compact { font-size: 13px; }
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/* App Store — catalog of every WASM edge module + simulator app.
*
* Mirrors `wifi-densepose-wasm-edge`'s 60+ hot-loadable algorithms and
* the `nvsim` simulator. Each card is filterable by category, fuzzy
* name search, and maturity (available / beta / research). A toggle on
* each card flips activation in the live session — that drives the
* dashboard's event log when running. WS transport (future) pushes the
* activation set to the connected ESP32 mesh.
*
* ADR-092 §18.
*/
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
import { signal, effect } from '@preact/signals-core';
import {
APPS, CATEGORIES, defaultActivations, fuzzyMatch,
type AppCategory, type AppManifest, type AppActivation,
} from '../store/apps';
import { kvGet, kvSet } from '../store/persistence';
import { pushLog, activeAppIds, appEvents, appEventCounts } from '../store/appStore';
import { hasRuntime } from '../store/appRuntimes';
const activations = signal<AppActivation[]>(defaultActivations());
const query = signal<string>('');
const activeCat = signal<AppCategory | 'all'>('all');
const statusFilter = signal<'all' | 'available' | 'beta' | 'research'>('all');
(async () => {
const saved = await kvGet<AppActivation[]>('app-activations');
if (saved) activations.value = saved;
})();
effect(() => {
// Persist activations on change (post-load) AND mirror into the
// active-set signal that main.ts watches to drive runtime dispatch.
const v = activations.value;
if (v.length > 0) void kvSet('app-activations', v);
const set = new Set<string>();
for (const a of v) if (a.active) set.add(a.id);
activeAppIds.value = set;
});
@customElement('nv-app-store')
export class NvAppStore extends LitElement {
@state() private renderTick = 0;
static styles = css`
:host {
display: block;
height: 100%;
overflow-y: auto;
background: radial-gradient(ellipse at 50% 30%, var(--bg-2) 0%, var(--bg-0) 70%);
padding: 24px;
}
.head {
display: flex; align-items: center; gap: 16px;
margin-bottom: 18px;
flex-wrap: wrap;
}
.ttl {
font-size: 22px; font-weight: 700; letter-spacing: -0.02em;
color: var(--ink);
flex: 1; min-width: 200px;
}
.ttl small {
font-size: 12.5px; font-weight: 400;
color: var(--ink-3); margin-left: 8px;
}
.search {
width: 320px; max-width: 100%;
padding: 8px 12px;
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: 8px;
font-family: var(--mono);
font-size: 12.5px;
color: var(--ink); outline: none;
}
.search:focus { border-color: var(--accent); }
.filters {
display: flex; flex-wrap: wrap; gap: 6px;
margin-bottom: 18px;
}
.chip {
padding: 4px 10px;
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: 999px;
font-size: 11.5px; color: var(--ink-3);
cursor: pointer;
font-family: var(--mono);
display: inline-flex; align-items: center; gap: 4px;
}
.chip:hover { color: var(--ink); border-color: var(--line-2); }
.chip.on { background: var(--bg-3); border-color: var(--accent); color: var(--ink); }
.chip .swatch {
width: 7px; height: 7px; border-radius: 50%;
}
.chip .count { color: var(--ink-3); font-size: 10px; }
.grid {
display: grid;
grid-template-columns: repeat(auto-fill, minmax(280px, 1fr));
gap: 12px;
}
.card {
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: var(--radius);
padding: 12px 14px;
display: flex; flex-direction: column; gap: 6px;
transition: border-color 0.15s, transform 0.15s;
position: relative;
}
.card:hover { border-color: var(--line-2); transform: translateY(-1px); }
.card.active {
border-color: oklch(0.78 0.14 145 / 0.7);
background: linear-gradient(180deg, var(--bg-2) 0%, oklch(0.78 0.14 145 / 0.04) 100%);
}
.card-h {
display: flex; align-items: flex-start; gap: 8px;
margin-bottom: 2px;
}
.card-h .name {
font-size: 13.5px; font-weight: 600; color: var(--ink);
flex: 1; line-height: 1.3;
}
.card-h .swatch {
width: 10px; height: 10px; border-radius: 50%;
flex-shrink: 0; margin-top: 4px;
}
.summary {
font-size: 12px; color: var(--ink-2); line-height: 1.45;
flex: 1;
}
.meta {
display: flex; flex-wrap: wrap; gap: 4px; margin-top: 6px;
font-family: var(--mono); font-size: 10px;
}
.badge {
padding: 1px 6px; border-radius: 4px;
background: var(--bg-3); color: var(--ink-3);
border: 1px solid var(--line);
}
.badge.cat { color: var(--accent); border-color: oklch(0.78 0.14 70 / 0.3); }
.badge.status-available { color: var(--ok); border-color: oklch(0.78 0.14 145 / 0.4); }
.badge.status-beta { color: var(--warn); border-color: oklch(0.7 0.18 35 / 0.4); }
.badge.status-research { color: var(--accent-3); border-color: oklch(0.72 0.18 330 / 0.4); }
.badge.budget { color: var(--accent-2); border-color: oklch(0.78 0.12 195 / 0.3); }
.badge.rt-running { color: var(--ok); border-color: oklch(0.78 0.14 145 / 0.5); background: oklch(0.78 0.14 145 / 0.08); }
.badge.rt-simulated { color: var(--accent); border-color: oklch(0.78 0.14 70 / 0.5); background: oklch(0.78 0.14 70 / 0.08); }
.badge.rt-mesh-only { color: var(--ink-3); border-color: var(--line); }
.events-feed {
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: var(--radius);
padding: 14px;
margin-bottom: 18px;
}
.events-feed h3 {
margin: 0 0 8px;
font-size: 13px; font-weight: 600;
color: var(--ink);
}
.events-feed .lead {
font-size: 12px; color: var(--ink-3);
margin: 0 0 10px;
line-height: 1.5;
}
.events-feed .lines {
display: flex; flex-direction: column; gap: 4px;
max-height: 160px; overflow-y: auto;
}
.ev-line {
display: grid;
grid-template-columns: 60px 90px 1fr;
gap: 10px;
padding: 4px 6px;
border-radius: 4px;
font-family: var(--mono);
font-size: 11px;
color: var(--ink-2);
}
.ev-line:hover { background: var(--bg-3); }
.ev-line .ts { color: var(--ink-4); font-size: 10.5px; }
.ev-line .id { color: var(--accent); font-size: 10.5px; }
.ev-line .body { color: var(--ink); }
.ev-empty {
font-size: 12px; color: var(--ink-3);
padding: 8px 0;
}
.card-events-count {
font-size: 10.5px;
color: var(--accent-4);
font-family: var(--mono);
}
.card-foot {
display: flex; align-items: center; gap: 8px;
padding-top: 8px; margin-top: 4px;
border-top: 1px solid var(--line);
font-size: 11px; color: var(--ink-3);
}
.toggle {
position: relative;
width: 32px; height: 18px;
background: var(--bg-3); border: 1px solid var(--line-2);
border-radius: 999px; cursor: pointer;
transition: background 0.15s;
flex-shrink: 0;
}
.toggle::after {
content: ''; position: absolute;
top: 1px; left: 1px;
width: 12px; height: 12px;
background: var(--ink-3); border-radius: 50%;
transition: transform 0.15s, background 0.15s;
}
.toggle.on { background: var(--accent); border-color: var(--accent); }
.toggle.on::after { background: #1a0f00; transform: translateX(14px); }
.events {
font-family: var(--mono); font-size: 10px; color: var(--ink-3);
flex: 1;
}
.empty {
padding: 40px;
text-align: center; color: var(--ink-3);
font-size: 13px;
}
`;
override connectedCallback(): void {
super.connectedCallback();
effect(() => {
activations.value; query.value; activeCat.value; statusFilter.value;
appEvents.value; appEventCounts.value;
this.renderTick++;
});
}
private isActive(id: string): boolean {
return activations.value.find((a) => a.id === id)?.active === true;
}
private toggle(app: AppManifest): void {
const wasActive = this.isActive(app.id);
const next = activations.value.map((a) => a.id === app.id ? { ...a, active: !a.active, lastActivatedAt: Date.now() } : a);
activations.value = next;
if (!wasActive) {
const r = app.runtime ?? 'mesh-only';
const note = r === 'simulated' ? ' · live runtime engaged'
: r === 'mesh-only' ? ' · queued (needs ESP32 mesh)'
: '';
pushLog('ok', `app <span class="k">${app.id}</span> activated${note}`);
} else {
pushLog('info', `app <span class="k">${app.id}</span> deactivated`);
}
}
private filtered(): AppManifest[] {
let list = APPS;
if (activeCat.value !== 'all') list = list.filter((a) => a.category === activeCat.value);
if (statusFilter.value !== 'all') list = list.filter((a) => a.status === statusFilter.value);
if (query.value.trim()) {
list = list
.map((a) => ({ a, s: fuzzyMatch(query.value, a) }))
.filter((x) => x.s > 0)
.sort((a, b) => b.s - a.s)
.map((x) => x.a);
}
return list;
}
private categoryCounts(): Record<string, number> {
const counts: Record<string, number> = { all: APPS.length };
for (const k of Object.keys(CATEGORIES)) counts[k] = 0;
for (const a of APPS) counts[a.category] = (counts[a.category] ?? 0) + 1;
return counts;
}
override render() {
const list = this.filtered();
const counts = this.categoryCounts();
const activeCount = activations.value.filter((a) => a.active).length;
return html`
<div class="head">
<div class="ttl">
App Store
<small>${APPS.length} edge apps · ${activeCount} active</small>
</div>
<input class="search" id="app-search" placeholder="Search by name, tag, or category…"
.value=${query.value}
@input=${(e: Event) => { query.value = (e.target as HTMLInputElement).value; }} />
</div>
<div class="filters">
<span class="chip ${activeCat.value === 'all' ? 'on' : ''}"
@click=${() => activeCat.value = 'all'}>
All<span class="count">${counts.all}</span>
</span>
${(Object.keys(CATEGORIES) as AppCategory[]).map((k) => html`
<span class="chip ${activeCat.value === k ? 'on' : ''}"
@click=${() => activeCat.value = k}>
<span class="swatch" style=${`background:${CATEGORIES[k].color}`}></span>
${CATEGORIES[k].label}
<span class="count">${counts[k] ?? 0}</span>
</span>
`)}
<span style="flex:1; min-width:8px"></span>
<span class="chip ${statusFilter.value === 'all' ? 'on' : ''}" @click=${() => statusFilter.value = 'all'}>any</span>
<span class="chip ${statusFilter.value === 'available' ? 'on' : ''}" @click=${() => statusFilter.value = 'available'}>available</span>
<span class="chip ${statusFilter.value === 'beta' ? 'on' : ''}" @click=${() => statusFilter.value = 'beta'}>beta</span>
<span class="chip ${statusFilter.value === 'research' ? 'on' : ''}" @click=${() => statusFilter.value = 'research'}>research</span>
</div>
${this.renderEventsFeed()}
${list.length === 0
? html`<div class="empty">No apps match the current filters.</div>`
: html`<div class="grid">${list.map((app) => this.card(app))}</div>`}
`;
}
private renderEventsFeed() {
const evs = appEvents.value.slice(-12).reverse();
const activeSimCount = activations.value.filter((a) => a.active && hasRuntime(a.id)).length;
return html`
<div class="events-feed">
<h3>Live runtime feed
${activeSimCount > 0
? html`<span class="card-events-count" style="margin-left: 8px;">${activeSimCount} simulated app${activeSimCount === 1 ? '' : 's'} active</span>`
: ''}
</h3>
<p class="lead">
Apps with the <span class="badge rt-simulated" style="font-size:9.5px; padding:0 4px;">simulated</span>
runtime emit real i32 event IDs against nvsim's live frame stream below.
Apps with <span class="badge rt-mesh-only" style="font-size:9.5px; padding:0 4px;">mesh-only</span>
need an ESP32-S3 + WS transport (deferred to V2). The
<span class="badge rt-running" style="font-size:9.5px; padding:0 4px;">running</span>
badge marks <code>nvsim</code> itself, which is always running.
</p>
${evs.length === 0
? html`<div class="ev-empty">No events yet. Toggle a card with the <i>simulated</i> badge and press <b>▶ Run</b>.</div>`
: html`<div class="lines">${evs.map((ev) => {
const dt = new Date(ev.ts);
const ts = `${String(dt.getSeconds()).padStart(2, '0')}.${String(dt.getMilliseconds()).padStart(3, '0')}`;
return html`
<div class="ev-line">
<span class="ts">${ts}</span>
<span class="id">${ev.appId}</span>
<span class="body"><b style="color:var(--accent-2);">${ev.eventName}</b><span style="color:var(--ink-3);"> · ${ev.eventId}</span> ${ev.detail ? `· ${ev.detail}` : ''}</span>
</div>
`;
})}</div>`}
</div>
`;
}
private card(app: AppManifest) {
const active = this.isActive(app.id);
const cat = CATEGORIES[app.category];
const runtime = app.runtime ?? 'mesh-only';
const evCount = appEventCounts.value[app.id] ?? 0;
const runtimeLabel: Record<string, string> = {
'running': 'running',
'simulated': 'simulated',
'mesh-only': 'needs mesh',
};
const runtimeTip: Record<string, string> = {
'running': 'This app is genuinely running in your browser right now.',
'simulated': 'A pared-down version of this algorithm runs against nvsim\'s magnetic frame stream as a proxy for its native CSI input. Toggle on, then press ▶ Run to see real event IDs in the feed.',
'mesh-only': 'This algorithm needs CSI subcarrier data from an ESP32-S3 mesh. The toggle persists; activation is pushed via WS transport (V2).',
};
return html`
<div class="card ${active ? 'active' : ''}" data-app-id=${app.id}>
<div class="card-h">
<span class="swatch" style=${`background:${cat.color}`}></span>
<span class="name">${app.name}</span>
</div>
<div class="summary">${app.summary}</div>
<div class="meta">
<span class="badge cat">${cat.label}</span>
<span class="badge status-${app.status}">${app.status}</span>
<span class="badge rt-${runtime}" title=${runtimeTip[runtime]}>${runtimeLabel[runtime]}</span>
${app.budget ? html`<span class="badge budget">budget ${app.budget}</span>` : ''}
${app.adr ? html`<span class="badge">${app.adr}</span>` : ''}
${app.events?.length ? html`<span class="badge">events ${app.events.join('·')}</span>` : ''}
</div>
<div class="card-foot">
<span class="events">${app.crate}</span>
${evCount > 0 ? html`<span class="card-events-count">⚡ ${evCount} ev</span>` : ''}
<span class="toggle ${active ? 'on' : ''}" role="switch"
aria-checked=${active}
data-app-toggle=${app.id}
@click=${() => this.toggle(app)}></span>
</div>
</div>
`;
}
}
-143
View File
@@ -1,143 +0,0 @@
/* Top-level shell: 4-zone grid with rail / topbar / sidebar / scene / inspector / console.
* View routing is per-rail-button: the central area swaps between
* `<nv-scene>`, `<nv-app-store>`, etc. */
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
import './nv-rail';
import './nv-topbar';
import './nv-sidebar';
import './nv-scene';
import './nv-inspector';
import './nv-console';
import './nv-app-store';
import './nv-toast';
import './nv-modal';
import './nv-palette';
import './nv-debug-hud';
import './nv-settings-drawer';
import './nv-onboarding';
import './nv-ghost-murmur';
import './nv-help';
import './nv-home';
export type View = 'home' | 'scene' | 'apps' | 'inspector' | 'witness' | 'ghost-murmur';
@customElement('nv-app')
export class NvApp extends LitElement {
@state() private view: View = 'home';
static styles = css`
:host {
display: block;
height: 100vh;
width: 100vw;
background: var(--bg-0);
}
.skip-link {
position: absolute;
top: -40px;
left: 8px;
padding: 6px 12px;
background: var(--accent);
color: #1a0f00;
border-radius: 6px;
font-size: 12.5px;
font-weight: 600;
text-decoration: none;
z-index: 1000;
transition: top 0.15s;
}
.skip-link:focus { top: 8px; }
.app {
display: grid;
grid-template-columns: 56px 280px 1fr 340px;
grid-template-rows: 48px 1fr 220px;
grid-template-areas:
'rail topbar topbar topbar'
'rail sidebar main inspector'
'rail sidebar console inspector';
height: 100vh;
width: 100vw;
}
/* Home view simplifies: hides sidebar / inspector / console so the
hero gets the full screen. Power-user panels stay one rail click away. */
.app.simple {
grid-template-columns: 56px 1fr;
grid-template-rows: 48px 1fr;
grid-template-areas:
'rail topbar'
'rail main';
}
.app.simple nv-sidebar,
.app.simple nv-inspector,
.app.simple nv-console { display: none; }
nv-rail { grid-area: rail; }
nv-topbar { grid-area: topbar; }
nv-sidebar { grid-area: sidebar; }
.main { grid-area: main; min-width: 0; min-height: 0; position: relative; overflow: hidden; }
nv-inspector { grid-area: inspector; }
nv-console { grid-area: console; min-height: 0; }
@media (max-width: 1180px) {
.app {
grid-template-columns: 56px 1fr 320px;
grid-template-areas:
'rail topbar topbar'
'rail main inspector'
'rail console console';
}
nv-sidebar { display: none; }
}
@media (max-width: 860px) {
.app {
grid-template-columns: 1fr;
grid-template-rows: 52px 1fr 200px;
grid-template-areas:
'topbar'
'main'
'console';
}
nv-rail, nv-sidebar, nv-inspector { display: none; }
}
`;
override render() {
const isSimple = this.view === 'home';
return html`
<a class="skip-link" href="#main-content"
@click=${(e: Event) => { e.preventDefault(); const sr = this.shadowRoot; sr?.querySelector<HTMLElement>('.main')?.focus(); }}>
Skip to main content
</a>
<div class="app ${isSimple ? 'simple' : ''}">
<nv-rail .view=${this.view} @navigate=${(e: CustomEvent<View>) => (this.view = e.detail)}></nv-rail>
<nv-topbar></nv-topbar>
<nv-sidebar></nv-sidebar>
<main class="main" id="main-content" tabindex="-1" role="main" aria-label="Main view">
${this.view === 'home'
? html`<nv-home></nv-home>`
: this.view === 'apps'
? html`<nv-app-store></nv-app-store>`
: this.view === 'ghost-murmur'
? html`<nv-ghost-murmur></nv-ghost-murmur>`
: this.view === 'inspector'
? html`<nv-inspector expanded .pinTab=${'signal'}></nv-inspector>`
: this.view === 'witness'
? html`<nv-inspector expanded .pinTab=${'witness'}></nv-inspector>`
: html`<nv-scene></nv-scene>`}
</main>
<nv-inspector
.pinTab=${this.view === 'inspector' ? 'signal'
: this.view === 'witness' ? 'witness' : null}>
</nv-inspector>
<nv-console></nv-console>
</div>
<nv-toast></nv-toast>
<nv-modal></nv-modal>
<nv-palette></nv-palette>
<nv-debug-hud></nv-debug-hud>
<nv-settings-drawer></nv-settings-drawer>
<nv-onboarding></nv-onboarding>
<nv-help></nv-help>
`;
}
}
-266
View File
@@ -1,266 +0,0 @@
/* Console — log stream + REPL. */
import { LitElement, html, css } from 'lit';
import { customElement, query } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import {
consoleLines, consoleFilter, consolePaused, pushLog,
getClient, seed, theme, expectedWitness, witnessHex, witnessVerified,
running, replHistory, pushReplHistory,
} from '../store/appStore';
@customElement('nv-console')
export class NvConsole extends LitElement {
@query('#console-input') private inputEl!: HTMLInputElement;
private hIdx = -1;
static styles = css`
:host {
display: flex; flex-direction: column;
background: var(--bg-1);
overflow: hidden;
}
.tabs {
display: flex; align-items: center;
border-bottom: 1px solid var(--line);
padding: 0 10px;
gap: 2px;
}
.tab {
padding: 8px 12px;
background: transparent; border: none;
font-size: 11.5px; color: var(--ink-3);
font-family: var(--mono);
border-bottom: 2px solid transparent;
cursor: pointer;
margin-bottom: -1px;
}
.tab.active { color: var(--ink); border-bottom-color: var(--accent); }
.tab .cnt {
background: var(--bg-3); padding: 1px 5px; border-radius: 999px;
font-size: 9.5px; color: var(--ink-2); margin-left: 4px;
}
.spacer { flex: 1; }
.tools { display: flex; gap: 4px; padding: 4px 0; }
.tools button {
width: 24px; height: 24px;
background: transparent; border: 1px solid var(--line);
border-radius: 6px;
color: var(--ink-3);
font-size: 11px; cursor: pointer;
}
.tools button:hover { color: var(--ink); border-color: var(--line-2); }
.body {
flex: 1; overflow-y: auto;
font-family: var(--mono);
font-size: 11.5px;
padding: 6px 0;
background: var(--bg-0);
}
.line {
display: grid;
grid-template-columns: 70px 60px 1fr;
gap: 12px;
padding: 2px 12px;
color: var(--ink-2);
border-left: 2px solid transparent;
}
.line:hover { background: var(--bg-1); }
.ts { color: var(--ink-4); font-size: 10.5px; padding-top: 1px; }
.lvl {
font-size: 10px; font-weight: 600;
text-transform: uppercase; letter-spacing: 0.04em; padding-top: 1px;
}
.line.info .lvl { color: var(--accent-2); }
.line.warn .lvl { color: var(--warn); }
.line.warn { border-left-color: var(--warn); background: oklch(0.7 0.18 35 / 0.04); }
.line.err .lvl { color: var(--bad); }
.line.err { border-left-color: var(--bad); background: oklch(0.65 0.22 25 / 0.05); }
.line.dbg .lvl { color: var(--ink-3); }
.line.ok .lvl { color: var(--ok); }
.msg { color: var(--ink); white-space: pre-wrap; word-break: break-word; }
.input {
display: flex; align-items: center;
border-top: 1px solid var(--line);
background: var(--bg-0);
padding: 0 10px;
height: 32px; gap: 8px;
}
.prompt { color: var(--accent); font-family: var(--mono); font-size: 12px; }
input[type="text"] {
flex: 1; background: transparent; border: none; outline: none;
color: var(--ink); font-family: var(--mono); font-size: 12px;
height: 100%;
}
input::placeholder { color: var(--ink-4); }
`;
override connectedCallback(): void {
super.connectedCallback();
effect(() => {
consoleLines.value; consoleFilter.value; consolePaused.value;
this.requestUpdate();
});
}
override updated(): void {
const body = this.renderRoot.querySelector('.body') as HTMLElement | null;
if (body) body.scrollTop = body.scrollHeight;
}
private counts(): Record<string, number> {
const c: Record<string, number> = { info: 0, warn: 0, err: 0, dbg: 0, ok: 0 };
for (const l of consoleLines.value) c[l.level] = (c[l.level] ?? 0) + 1;
c.all = consoleLines.value.length;
return c;
}
private async exec(line: string): Promise<void> {
line = line.trim();
if (!line) return;
pushLog('info', `<span style="color:var(--accent);">nvsim&gt;</span> ${line}`);
pushReplHistory(line);
this.hIdx = replHistory.value.length;
const [cmd, ...args] = line.split(/\s+/);
const arg = args.join(' ');
const c = getClient();
switch (cmd) {
case 'help':
pushLog('info', 'commands: help · scene.list · sensor.config · run · pause · reset · seed · proof.verify · proof.export · clear · theme · status');
break;
case 'scene.list':
pushLog('info', 'scene rebar-walkby-01:');
pushLog('info', ' rebar.steel.coil @ [+2.7, 0.0, +0.3] m χ=5000');
pushLog('info', ' dipole.heart_proxy @ [-1.4, +0.2, +0.4] m m=1.0e-6 A·m²');
pushLog('info', ' loop.mains_60Hz @ [-1.6, -0.4, 0.0] m I=2 A');
pushLog('info', ' eddy.door_steel @ [+0.0, +1.8, +0.4] m σ=1e6 S/m');
break;
case 'sensor.config':
pushLog('info', 'NvSensor::cots_defaults() {');
pushLog('info', ' pos=[0,0,0], V=1mm³, N=1e12, C=0.03, T2*=200ns');
pushLog('info', ' D=2.870 GHz, γe=28 GHz/T, Γ=1.0 MHz, axes=4×〈111〉');
pushLog('info', ' δB ≈ 1.18 pT/√Hz (Barry 2020 §III.A) }');
break;
case 'run':
if (c) { await c.run(); running.value = true; pushLog('ok', 'pipeline RUN'); }
break;
case 'pause':
if (c) { await c.pause(); running.value = false; pushLog('warn', 'pipeline PAUSED'); }
break;
case 'reset':
if (c) { await c.reset(); pushLog('info', 'pipeline reset · t=0'); }
break;
case 'seed': {
if (!arg) { pushLog('info', `current seed = 0x${seed.value.toString(16).toUpperCase()}`); break; }
const v = BigInt(arg.startsWith('0x') ? arg : '0x' + arg);
seed.value = v;
if (c) await c.setSeed(v);
pushLog('ok', `seed → 0x${v.toString(16).toUpperCase()}`);
break;
}
case 'proof.verify': {
if (!c) break;
pushLog('dbg', 'computing SHA-256 over 256 frames…');
try {
const exp = expectedWitness.value;
const expBytes = new Uint8Array(32);
for (let i = 0; i < 32; i++) expBytes[i] = parseInt(exp.slice(i * 2, i * 2 + 2), 16);
const r = await c.verifyWitness(expBytes);
if (r.ok) { witnessVerified.value = 'ok'; witnessHex.value = exp; pushLog('ok', `witness ${exp.slice(0, 16)}… matches · determinism gate ✓`); }
else { witnessVerified.value = 'fail'; pushLog('err', 'WITNESS MISMATCH'); }
} catch (e) { pushLog('err', `verify failed: ${(e as Error).message}`); }
break;
}
case 'proof.export': {
if (!c) break;
pushLog('dbg', 'building proof bundle…');
try {
const blob = await c.exportProofBundle();
const url = URL.createObjectURL(blob);
const a = document.createElement('a');
a.href = url;
a.download = `nvsim-proof-${Date.now()}.json`;
a.click();
URL.revokeObjectURL(url);
pushLog('ok', `proof bundle exported · ${blob.size} bytes`);
} catch (e) { pushLog('err', `export failed: ${(e as Error).message}`); }
break;
}
case 'clear':
consoleLines.value = [];
break;
case 'theme': {
const t = (arg || '').toLowerCase();
if (t === 'light' || t === 'dark') { theme.value = t; pushLog('ok', `theme → ${t}`); }
else pushLog('info', 'theme [light|dark]');
break;
}
case 'status':
pushLog('info', `running=${running.value} seed=0x${seed.value.toString(16).toUpperCase()} verified=${witnessVerified.value}`);
break;
default:
pushLog('err', `unknown command: ${cmd} · try help`);
}
}
private onKey = (e: KeyboardEvent): void => {
if (e.key === 'Enter') { void this.exec(this.inputEl.value); this.inputEl.value = ''; }
else if (e.key === 'ArrowUp') {
const h = replHistory.value;
if (h.length) {
this.hIdx = Math.max(0, this.hIdx - 1);
this.inputEl.value = h[this.hIdx] ?? '';
e.preventDefault();
}
} else if (e.key === 'ArrowDown') {
const h = replHistory.value;
if (h.length) {
this.hIdx = Math.min(h.length, this.hIdx + 1);
this.inputEl.value = h[this.hIdx] ?? '';
e.preventDefault();
}
}
};
override render() {
const c = this.counts();
const filter = consoleFilter.value;
const visible = consoleLines.value.filter((l) => filter === 'all' || l.level === filter);
return html`
<div class="tabs">
${(['all', 'info', 'warn', 'err', 'dbg'] as const).map((k) => html`
<button class="tab ${filter === k ? 'active' : ''}" data-tab=${k}
@click=${() => consoleFilter.value = k}>
${k} <span class="cnt">${c[k] ?? 0}</span>
</button>
`)}
<span class="spacer"></span>
<div class="tools">
<button id="clear-log" title="Clear" @click=${() => consoleLines.value = []}>×</button>
<button id="pause-log" title="Pause" @click=${() => consolePaused.value = !consolePaused.value}>
${consolePaused.value ? '▶' : '❚❚'}
</button>
</div>
</div>
<div class="body" role="log" aria-live="polite" aria-label="Console output">
${visible.map((l) => {
const ts = new Date(l.ts);
const tsStr = `${String(ts.getSeconds()).padStart(2, '0')}.${String(ts.getMilliseconds()).padStart(3, '0')}`;
// Use innerHTML pass-through via unsafe-html alt: inject raw html via property
return html`<div class="line ${l.level}">
<div class="ts">${tsStr}</div>
<div class="lvl">${l.level}</div>
<div class="msg" .innerHTML=${l.msg}></div>
</div>`;
})}
</div>
<div class="input">
<span class="prompt">nvsim&gt;</span>
<input id="console-input" type="text"
placeholder="help · scene.list · sensor.config · run · proof.verify · clear"
@keydown=${this.onKey}/>
</div>
`;
}
}
-88
View File
@@ -1,88 +0,0 @@
/* Debug HUD toggled with `. Shows render fps, sim t, frames, |B|, SNR. */
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import { fps, framesEmitted, bMag, snr, t as simT } from '../store/appStore';
@customElement('nv-debug-hud')
export class NvDebugHud extends LitElement {
@state() private open = false;
@state() private renderFps = 0;
private lastTs = performance.now();
private frameCount = 0;
private rafId = 0;
static styles = css`
:host {
position: fixed; bottom: 8px; right: 8px;
width: 220px;
background: rgba(13,17,23,0.85);
backdrop-filter: blur(8px);
border: 1px solid var(--line-2);
border-radius: 8px;
padding: 8px 10px;
font-family: var(--mono); font-size: 11px;
color: var(--ink-2);
z-index: 99;
display: none;
box-shadow: var(--shadow);
}
:host([open]) { display: block; }
.h {
display: flex; justify-content: space-between;
font-weight: 600; color: var(--ink);
margin-bottom: 6px; padding-bottom: 4px;
border-bottom: 1px solid var(--line);
}
.x { cursor: pointer; color: var(--ink-3); }
.row {
display: flex; justify-content: space-between;
padding: 1px 0;
}
.k { color: var(--ink-3); }
.v { color: var(--ink); }
`;
override connectedCallback(): void {
super.connectedCallback();
window.addEventListener('keydown', this.onKey);
effect(() => { fps.value; framesEmitted.value; bMag.value; snr.value; simT.value; this.requestUpdate(); });
this.tick();
}
override disconnectedCallback(): void {
super.disconnectedCallback();
window.removeEventListener('keydown', this.onKey);
cancelAnimationFrame(this.rafId);
}
private onKey = (e: KeyboardEvent): void => {
if (e.key === '`' && !(e.target as HTMLElement).matches('input, textarea')) {
this.open = !this.open;
this.toggleAttribute('open', this.open);
}
};
private tick = (): void => {
this.rafId = requestAnimationFrame(this.tick);
const now = performance.now();
this.frameCount++;
if (now - this.lastTs >= 500) {
this.renderFps = (this.frameCount * 1000) / (now - this.lastTs);
this.frameCount = 0;
this.lastTs = now;
this.requestUpdate();
}
};
override render() {
return html`
<div class="h"><span>nvsim · debug</span><span class="x" @click=${() => { this.open = false; this.removeAttribute('open'); }}>✕</span></div>
<div class="row"><span class="k">render fps</span><span class="v">${this.renderFps.toFixed(1)}</span></div>
<div class="row"><span class="k">sim fps</span><span class="v">${fps.value > 0 ? Math.round(fps.value) : '—'}</span></div>
<div class="row"><span class="k">frames</span><span class="v">${framesEmitted.value.toString()}</span></div>
<div class="row"><span class="k">|B|</span><span class="v">${(bMag.value * 1e9).toFixed(3)} nT</span></div>
<div class="row"><span class="k">SNR</span><span class="v">${snr.value > 0 ? snr.value.toFixed(1) : '—'}</span></div>
<div class="row"><span class="k">DOM</span><span class="v">${document.querySelectorAll('*').length}</span></div>
`;
}
}
-666
View File
@@ -1,666 +0,0 @@
/* Ghost Murmur — research view.
*
* Walks through the publicly-reported April 2026 CIA program and maps
* the physically-defensible parts onto RuView's three-tier heartbeat
* mesh. Source: docs/research/quantum-sensing/16-ghost-murmur-ruview-spec.md
*
* This view is reference material, not an operational mode. It exists
* so practitioners (and journalists) can audit the physics-vs-press
* gap in the open. ADR-092 §14b.
*/
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
import { getClient, pushLog } from '../store/appStore';
import type { TransientRunResult } from '../transport/NvsimClient';
// Tier detection thresholds — order-of-magnitude floor each transport
// can resolve cardiac signal at, in Tesla. Source: Ghost Murmur spec
// §4.7, Wolf 2015, Barry 2020. These are deliberately optimistic for the
// "available" path; the shoot-the-moon press claim sits 6+ orders below.
const TIERS = [
{ id: 'nvBest', label: 'NV-ensemble (best lab)', floorT: 1e-12, color: 'oklch(0.78 0.14 70)' },
{ id: 'nvCots', label: 'NV-DNV-B1 (COTS)', floorT: 3e-10, color: 'oklch(0.72 0.18 50)' },
{ id: 'squid', label: 'SQUID (shielded room)', floorT: 1e-15, color: 'oklch(0.78 0.12 195)' },
{ id: 'mmw', label: '60 GHz mmWave (μ-Doppler)', floorT: 0, color: 'oklch(0.78 0.14 145)' },
{ id: 'csi', label: 'WiFi CSI (presence)', floorT: 0, color: 'oklch(0.72 0.18 330)' },
];
// Cardiac dipole moment (A·m²) — order-of-magnitude estimate from
// Wikswo / Bison cardiac MCG modelling.
const HEART_DIPOLE_AM2 = 5e-9;
@customElement('nv-ghost-murmur')
export class NvGhostMurmur extends LitElement {
@state() private distanceM = 0.1;
@state() private momentLog10 = -8.3; // log10(5e-9)
@state() private result: TransientRunResult | null = null;
@state() private running = false;
@state() private err: string | null = null;
static styles = css`
:host {
display: block;
height: 100%;
overflow-y: auto;
background: radial-gradient(ellipse at 50% 30%, var(--bg-2) 0%, var(--bg-0) 70%);
padding: 24px 28px 60px;
}
h1 {
margin: 0 0 4px;
font-size: 22px;
letter-spacing: -0.02em;
color: var(--ink);
}
.subtitle {
color: var(--ink-3);
font-size: 13px;
margin-bottom: 22px;
}
.links {
display: flex; flex-wrap: wrap; gap: 6px;
margin-bottom: 22px;
}
.links a {
padding: 5px 10px;
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: 999px;
font-size: 11.5px;
font-family: var(--mono);
color: var(--accent-2);
text-decoration: none;
}
.links a:hover { border-color: var(--accent-2); }
h2 {
font-size: 14px;
font-weight: 600;
letter-spacing: 0.06em;
text-transform: uppercase;
color: var(--ink-3);
margin: 28px 0 10px;
}
.grid {
display: grid;
grid-template-columns: repeat(auto-fit, minmax(280px, 1fr));
gap: 12px;
}
.card {
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: var(--radius);
padding: 14px;
}
.card h3 {
margin: 0 0 8px;
font-size: 13.5px; font-weight: 600;
color: var(--ink);
}
.card p {
font-size: 12.5px; color: var(--ink-2);
margin: 0 0 8px;
line-height: 1.5;
}
.card p:last-child { margin-bottom: 0; }
.stat {
display: inline-flex; align-items: baseline; gap: 6px;
margin-right: 10px;
}
.stat .v {
font-family: var(--mono); font-size: 16px; font-weight: 600;
color: var(--accent);
}
.stat .l {
font-size: 10px; color: var(--ink-3);
text-transform: uppercase; letter-spacing: 0.04em;
}
table {
width: 100%; border-collapse: collapse;
font-size: 12.5px;
}
th, td {
padding: 8px 10px;
text-align: left;
border-bottom: 1px solid var(--line);
}
th {
color: var(--ink-3);
font-weight: 600;
font-size: 11px;
text-transform: uppercase;
letter-spacing: 0.06em;
}
td.amber { color: var(--accent); font-family: var(--mono); }
td.cyan { color: var(--accent-2); font-family: var(--mono); }
td.bad { color: var(--bad); font-family: var(--mono); }
.pill {
display: inline-block;
padding: 1px 6px;
border-radius: 4px;
font-family: var(--mono);
font-size: 10px;
border: 1px solid var(--line);
}
.pill.ok { color: var(--ok); border-color: oklch(0.78 0.14 145 / 0.4); }
.pill.skeptical { color: var(--bad); border-color: oklch(0.65 0.22 25 / 0.4); }
.pill.partial { color: var(--warn); border-color: oklch(0.7 0.18 35 / 0.4); }
.architecture {
font-family: var(--mono);
font-size: 11px;
color: var(--ink-2);
background: var(--bg-3);
padding: 16px;
border-radius: var(--radius-sm);
border: 1px solid var(--line);
white-space: pre;
overflow-x: auto;
line-height: 1.4;
}
.ethics {
background: linear-gradient(180deg, var(--bg-2) 0%, oklch(0.65 0.22 25 / 0.04) 100%);
border: 1px solid oklch(0.65 0.22 25 / 0.25);
border-radius: var(--radius);
padding: 16px;
}
.ethics h3 { color: var(--bad); margin-top: 0; }
.ethics ul { padding-left: 18px; margin: 8px 0; }
.ethics li { font-size: 12.5px; color: var(--ink-2); margin-bottom: 4px; }
/* Demo */
.demo {
background: linear-gradient(180deg, var(--bg-2) 0%, oklch(0.78 0.14 70 / 0.04) 100%);
border: 1px solid oklch(0.78 0.14 70 / 0.3);
border-radius: var(--radius);
padding: 18px;
}
.demo-grid {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 18px;
margin-top: 12px;
}
@media (max-width: 720px) { .demo-grid { grid-template-columns: 1fr; } }
.control { margin-bottom: 14px; }
.control .top {
display: flex; justify-content: space-between;
font-size: 12px; margin-bottom: 6px;
}
.control .top .lbl { color: var(--ink-3); }
.control .top .val {
font-family: var(--mono); color: var(--ink);
}
.control input[type="range"] {
-webkit-appearance: none; appearance: none;
width: 100%; height: 4px;
background: var(--bg-3); border-radius: 2px; outline: none;
}
.control input[type="range"]::-webkit-slider-thumb {
-webkit-appearance: none; appearance: none;
width: 14px; height: 14px; border-radius: 50%;
background: var(--accent); cursor: pointer;
border: 2px solid var(--bg-2);
}
.demo-btn {
width: 100%;
padding: 10px;
border: 1px solid var(--accent);
background: var(--accent);
color: #1a0f00;
border-radius: 8px;
font-size: 13px; font-weight: 600;
cursor: pointer;
}
.demo-btn:hover { filter: brightness(1.08); }
.demo-btn:disabled { opacity: 0.6; cursor: progress; }
.readout {
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: 8px;
padding: 12px;
}
.readout-row {
display: flex; justify-content: space-between;
padding: 4px 0;
font-family: var(--mono); font-size: 12px;
}
.readout-row .l { color: var(--ink-3); }
.readout-row .v { color: var(--ink); }
.readout-row .v.amber { color: var(--accent); }
.tier-bar {
position: relative;
margin: 6px 0;
height: 22px;
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: 4px;
overflow: hidden;
}
.tier-bar .fill {
position: absolute; top: 0; bottom: 0; left: 0;
transition: width 0.2s ease-out;
border-right: 2px solid;
}
.tier-bar .lbl {
position: relative; z-index: 1;
font-family: var(--mono); font-size: 11px;
padding: 3px 8px;
color: var(--ink);
display: flex; justify-content: space-between;
pointer-events: none;
}
.verdict {
margin-top: 10px;
padding: 10px 12px;
border-radius: 8px;
font-size: 12.5px; font-weight: 500;
border: 1px solid;
}
.verdict.ok { background: oklch(0.78 0.14 145 / 0.08); border-color: oklch(0.78 0.14 145 / 0.4); color: var(--ok); }
.verdict.warn { background: oklch(0.7 0.18 35 / 0.08); border-color: oklch(0.7 0.18 35 / 0.4); color: var(--warn); }
.verdict.bad { background: oklch(0.65 0.22 25 / 0.08); border-color: oklch(0.65 0.22 25 / 0.4); color: var(--bad); }
.demo-notes {
font-size: 11.5px; color: var(--ink-3);
margin-top: 10px; line-height: 1.5;
}
`;
/**
* Predicted MCG dipole field (Tesla) at distance r in metres.
* Far-field approximation: |B| ≈ μ₀ · m / (4π · r³). Source: Jackson 3e §5.
*/
private predictedDipoleFieldT(r: number, m: number): number {
const MU_0 = 4 * Math.PI * 1e-7;
return (MU_0 * m) / (4 * Math.PI * Math.pow(Math.max(r, 1e-6), 3));
}
private async runDemo(): Promise<void> {
const c = getClient();
if (!c) { this.err = 'WASM client not ready'; return; }
this.err = null;
this.running = true;
this.requestUpdate();
try {
const r = this.distanceM;
const m = Math.pow(10, this.momentLog10);
// Heart proxy at +z = r, dipole moment along z = m A·m².
const scene = {
dipoles: [{ position: [0, 0, r] as [number, number, number], moment: [0, 0, m] as [number, number, number] }],
loops: [],
ferrous: [],
eddy: [],
sensors: [[0, 0, 0] as [number, number, number]],
ambient_field: [0, 0, 0] as [number, number, number],
};
const config = {
digitiser: { f_s_hz: 10000, f_mod_hz: 1000 },
sensor: {
gamma_fwhm_hz: 1.0e6,
t1_s: 5.0e-3,
t2_s: 1.0e-6,
t2_star_s: 200e-9,
contrast: 0.03,
n_spins: 1.0e12,
shot_noise_disabled: false,
},
dt_s: null,
};
this.result = await c.runTransient(scene, config, 42n, 64);
pushLog('ok', `ghost-demo · r=${r.toFixed(3)} m · |B| recovered = ${(this.result.bMagT * 1e12).toExponential(2)} pT`);
} catch (e) {
this.err = (e as Error).message;
pushLog('err', `ghost-demo failed: ${this.err}`);
} finally {
this.running = false;
this.requestUpdate();
}
}
private formatField(t: number): string {
if (t === 0) return '0 T';
const abs = Math.abs(t);
if (abs >= 1e-3) return `${(t * 1e3).toFixed(2)} mT`;
if (abs >= 1e-6) return `${(t * 1e6).toFixed(2)} µT`;
if (abs >= 1e-9) return `${(t * 1e9).toFixed(3)} nT`;
if (abs >= 1e-12) return `${(t * 1e12).toFixed(2)} pT`;
if (abs >= 1e-15) return `${(t * 1e15).toFixed(2)} fT`;
if (abs >= 1e-18) return `${(t * 1e18).toFixed(2)} aT`;
return `${t.toExponential(2)} T`;
}
private formatDistance(r: number): string {
if (r < 1) return `${(r * 100).toFixed(1)} cm`;
if (r < 1000) return `${r.toFixed(2)} m`;
if (r < 1e5) return `${(r / 1000).toFixed(2)} km`;
return `${(r / 1609).toFixed(0)} mi`;
}
private renderDemo() {
const m = Math.pow(10, this.momentLog10);
const predicted = this.predictedDipoleFieldT(this.distanceM, m);
const recovered = this.result?.bMagT ?? 0;
const noiseFloor = (this.result?.noiseFloorPtSqrtHz ?? 0) * 1e-12; // pT/√Hz → T/√Hz
const verdictPills = TIERS.map((t) => {
let detect: 'ok' | 'warn' | 'bad' = 'bad';
let label = 'below floor';
if (t.id === 'mmw') {
if (this.distanceM <= 5) { detect = 'ok'; label = 'µ-Doppler @ chest'; }
else if (this.distanceM <= 15) { detect = 'warn'; label = 'edge of range'; }
else { detect = 'bad'; label = 'out of range'; }
} else if (t.id === 'csi') {
if (this.distanceM <= 30) { detect = this.distanceM <= 10 ? 'ok' : 'warn'; label = 'presence/breathing'; }
else { detect = 'bad'; label = 'out of range'; }
} else if (t.floorT > 0) {
const ratio = predicted / t.floorT;
if (ratio > 100) { detect = 'ok'; label = `${ratio.toExponential(1)}× floor`; }
else if (ratio > 1) { detect = 'warn'; label = `${ratio.toFixed(1)}× floor`; }
else { detect = 'bad'; label = `${(1 / ratio).toExponential(1)}× too weak`; }
}
const fillPct = t.floorT > 0
? Math.max(2, Math.min(100, 100 + 12 * Math.log10(predicted / t.floorT)))
: (t.id === 'mmw' ? Math.max(2, 100 - this.distanceM * 7) : Math.max(2, 100 - this.distanceM * 2));
return html`
<div class="tier-bar" data-tier=${t.id}>
<div class="fill" style=${`width:${fillPct}%; background:${t.color}; border-color:${t.color}`}></div>
<div class="lbl">
<span>${t.label}</span>
<span class="verdict-${detect}" style=${`color:${detect === 'ok' ? 'var(--ok)' : detect === 'warn' ? 'var(--warn)' : 'var(--bad)'}`}>${label}</span>
</div>
</div>
`;
});
const overallDetect: 'ok' | 'warn' | 'bad' =
predicted > 1e-12 ? 'ok' : predicted > 1e-15 ? 'warn' : 'bad';
const overallText =
overallDetect === 'ok'
? `Above NV-ensemble lab floor — close-range MCG plausible at ${this.formatDistance(this.distanceM)}.`
: overallDetect === 'warn'
? `Below NV ensemble best, above SQUID — research-grade only at ${this.formatDistance(this.distanceM)}.`
: `Below every published instrument's noise floor at ${this.formatDistance(this.distanceM)}. Press-release physics.`;
return html`
<div class="demo">
<h3 style="margin: 0 0 6px;">Try it yourself</h3>
<div style="font-size: 12.5px; color: var(--ink-2); margin-bottom: 4px; line-height: 1.5;">
Place a cardiac dipole at variable distance from the NV sensor. The
dashboard runs the <i>real</i> nvsim Rust pipeline (compiled to WASM)
end-to-end and reports what each tier would actually detect. Same
determinism contract as the rest of the dashboard.
</div>
<div class="demo-grid">
<div>
<div class="control">
<div class="top">
<span class="lbl">Distance from sensor</span>
<span class="val" id="demo-dist-val">${this.formatDistance(this.distanceM)}</span>
</div>
<input type="range" id="demo-distance"
min="-2" max="5" step="0.05"
.value=${String(Math.log10(this.distanceM))}
@input=${(e: Event) => { this.distanceM = Math.pow(10, +(e.target as HTMLInputElement).value); }} />
<div style="font-size: 10.5px; color: var(--ink-3); margin-top: 4px; font-family: var(--mono);">
10 cm → 100 km log scale
</div>
</div>
<div class="control">
<div class="top">
<span class="lbl">Heart dipole moment</span>
<span class="val" id="demo-moment-val">${m.toExponential(2)} A·m²</span>
</div>
<input type="range" id="demo-moment"
min="-10" max="-6" step="0.05"
.value=${String(this.momentLog10)}
@input=${(e: Event) => { this.momentLog10 = +(e.target as HTMLInputElement).value; }} />
<div style="font-size: 10.5px; color: var(--ink-3); margin-top: 4px; font-family: var(--mono);">
published cardiac MCG ≈ 5×10⁻⁹ A·m²
</div>
</div>
<button class="demo-btn" id="demo-run-btn" ?disabled=${this.running}
@click=${() => this.runDemo()}>
${this.running ? 'Running nvsim…' : '▶ Run nvsim at this distance'}
</button>
${this.err ? html`<div class="verdict bad" style="margin-top: 10px;">Error: ${this.err}</div>` : ''}
</div>
<div>
<div class="readout">
<div class="readout-row">
<span class="l">Predicted |B| (1/r³)</span>
<span class="v amber" id="demo-predicted">${this.formatField(predicted)}</span>
</div>
<div class="readout-row">
<span class="l">Recovered |B| (nvsim)</span>
<span class="v" id="demo-recovered">${this.result ? this.formatField(recovered) : '—'}</span>
</div>
<div class="readout-row">
<span class="l">Sensor noise floor</span>
<span class="v" id="demo-floor">${this.result ? this.formatField(noiseFloor) + '/√Hz' : '—'}</span>
</div>
<div class="readout-row">
<span class="l">Frames run</span>
<span class="v" id="demo-frames">${this.result?.nFrames ?? '—'}</span>
</div>
<div class="readout-row">
<span class="l">Witness (this run)</span>
<span class="v" style="font-size: 10px;" id="demo-witness">${this.result?.witnessHex.slice(0, 16) ?? '—'}…</span>
</div>
</div>
<div style="margin-top: 14px;">
<div style="font-size: 11.5px; color: var(--ink-3); text-transform: uppercase; letter-spacing: 0.06em; margin-bottom: 8px;">
Per-tier detectability
</div>
${verdictPills}
</div>
</div>
</div>
<div class="verdict ${overallDetect}" id="demo-verdict">${overallText}</div>
<div class="demo-notes">
The <code>predicted</code> value uses the closed-form magnetic-dipole
far field <code>|B| = μ₀·m / (4π·r³)</code>. The <code>recovered</code>
value comes from the same Rust pipeline that drives the Witness panel —
scene → Biot-Savart → NV ensemble → ADC → MagFrame. Use the moment
slider to ask "what if the heart were stronger?". Use the distance
slider to walk through 10 cm (clinical MCG), 1 m (close approach),
10 m (room-scale), 1 km (skeptic's range), and 65 km (the press claim).
</div>
</div>
`;
}
override render() {
return html`
<h1>Ghost Murmur — open-source reality check</h1>
<div class="subtitle">
The physics-vs-press audit for the publicly-reported April 2026
CIA NV-diamond heartbeat detector, and how RuView's existing
stack maps onto an honest, civilian version of the same idea.
</div>
<div class="links">
<a href="https://github.com/ruvnet/RuView/blob/feat/nvsim-pipeline-simulator/docs/research/quantum-sensing/16-ghost-murmur-ruview-spec.md" target="_blank" rel="noopener">
📄 Full spec (583 lines)
</a>
<a href="https://gist.github.com/ruvnet/e44d0c3f0ad10d9c4933a196a16d405c" target="_blank" rel="noopener">
✦ Public gist
</a>
<a href="https://github.com/ruvnet/RuView/issues/437" target="_blank" rel="noopener">
# Issue #437
</a>
<a href="https://www.scientificamerican.com/article/what-is-the-quantum-ghost-murmur-purportedly-used-in-iran-scientists/" target="_blank" rel="noopener">
↗ Scientific American
</a>
</div>
<h2>What the press reported</h2>
<div class="grid">
<div class="card">
<h3>The story</h3>
<p>3 Apr 2026: USAF F-15E pilot "Dude 44 Bravo" goes down in southern Iran during the regional exchange and evades for ~2 days.</p>
<p>President Trump publicly suggests detection from <b>40 miles away</b> on a mountainside at night; CIA Director Ratcliffe says "invisible to the enemy, but not to the CIA."</p>
</div>
<div class="card">
<h3>The named tech</h3>
<p><b>"Ghost Murmur"</b> — Lockheed Skunk Works system using NV defects in synthetic diamond + AI to extract a heartbeat from environmental noise.</p>
<p>Outlets: <i>Newsweek, Scientific American, Military.com, WION, Open The Magazine, Yahoo, Calcalist</i> + HN thread #47679241.</p>
</div>
<div class="card">
<h3>What physicists said</h3>
<p>Wikswo (Vanderbilt), Orzel (Union College), Roth (Oakland) — all pushing back hard.</p>
<p>"At 1 km, the heartbeat field drops to ~10⁻¹² of its 10 cm value." MCG-only at multi-mile range is <span class="pill skeptical">not consistent with published physics</span>.</p>
</div>
</div>
<h2>Live demo — nvsim WASM</h2>
${this.renderDemo()}
<h2>Physics reality check</h2>
<div class="card" style="padding: 6px 14px;">
<table>
<thead>
<tr><th>Distance</th><th>Cardiac MCG (peak QRS)</th><th>vs Earth field (~50 µT)</th></tr>
</thead>
<tbody>
<tr><td>10 cm</td><td class="amber">50 pT</td><td>10⁹× weaker</td></tr>
<tr><td>1 m</td><td class="amber">50 fT</td><td>10¹²× weaker</td></tr>
<tr><td>10 m</td><td class="cyan">50 aT</td><td>10¹⁵× weaker</td></tr>
<tr><td>1 km</td><td class="bad">5 × 10⁻²³ T</td><td>10²⁷× weaker</td></tr>
<tr><td>40 mi (65 km)</td><td class="bad">~10⁻²⁸ T</td><td>10³³× weaker</td></tr>
</tbody>
</table>
<p style="font-size: 12px; color: var(--ink-3); margin: 10px 0 0; line-height: 1.5;">
Best published NV-ensemble lab record: <b>0.9 pT/√Hz</b> [Wolf 2015].
Best SQUID in a shielded room: <b>~1 fT/√Hz</b>. To detect a single heartbeat at 10 m
you'd need ~2 billion× more sensitivity than any published ensemble has ever shown,
in a magnetically silent environment. <i>40 miles is press-release physics.</i>
</p>
</div>
<h2>RuView's three-tier mesh — what is actually buildable</h2>
<div class="architecture"> ┌──────────────────────────┐
│ Tier 3 — NV-diamond │ Range: 0.12 m (lab)
│ magnetometer ring │ Status: nvsim simulator only
│ (close-confirm) │ Hardware: $$$ (≥$8k DNV-B1)
└──────────┬───────────────┘
┌──────────┴───────────────┐
│ Tier 2 — 60 GHz FMCW │ Range: 110 m HR/BR
│ mmWave radar mesh │ Status: shipping (ADR-021)
│ (vital signs, posture) │ Hardware: $15 (MR60BHA2 + ESP32-C6)
└──────────┬───────────────┘
┌──────────┴───────────────┐
│ Tier 1 — WiFi CSI mesh │ Range: 1030 m through-wall
│ (presence, breathing, │ Status: shipping (ADR-014, ADR-029)
│ pose, intention) │ Hardware: $9 (ESP32-S3 8MB)
└──────────┬───────────────┘
┌────────────────────────────────┐
│ RuvSense multistatic fusion │
│ + cross-viewpoint attention │
│ + AETHER re-ID embeddings │
│ + Cramer-Rao gating │
└────────────────────────────────┘</div>
<h2>Press claim → RuView equivalent</h2>
<div class="card" style="padding: 6px 14px;">
<table>
<thead>
<tr><th>Press claim</th><th>RuView equivalent today</th><th>Crate / ADR</th><th>Honest range</th></tr>
</thead>
<tbody>
<tr>
<td>NV-diamond magnetometry</td>
<td>Deterministic NV pipeline simulator</td>
<td><code>nvsim</code> · ADR-089</td>
<td>Simulator only</td>
</tr>
<tr>
<td>"AI strips environmental noise"</td>
<td>RuvSense multistatic fusion + AETHER</td>
<td>signal/ruvsense/ · ADR-029</td>
<td>Mature</td>
</tr>
<tr>
<td>Heartbeat at distance</td>
<td>60 GHz FMCW HR/BR + WiFi CSI breathing</td>
<td>vitals · ADR-021</td>
<td><span class="pill ok">15 m HR · 1030 m presence</span></td>
</tr>
<tr>
<td>Long-range localisation</td>
<td>Multistatic time-of-flight + CRLB</td>
<td>ruvector/viewpoint/</td>
<td>Limited by node spacing</td>
</tr>
<tr>
<td><i>40-mile single-heartbeat detection</i></td>
<td><i>Not feasible at any tier</i></td>
<td>—</td>
<td><span class="pill skeptical">Press-release physics</span></td>
</tr>
</tbody>
</table>
</div>
<h2>Build today on $165</h2>
<div class="grid">
<div class="card">
<h3>Bill of materials</h3>
<p style="font-family: var(--mono); font-size: 11.5px; line-height: 1.7; color: var(--ink-2);">
3 × ESP32-S3 8 MB ($9 ea)<br>
3 × PoE injector + cat6 ($6 ea)<br>
1 × ESP32-C6 + Seeed MR60BHA2 ($15)<br>
1 × Raspberry Pi 5 8 GB ($80)<br>
1 × unmanaged GbE switch ($25)
</p>
<p><b>Total: $165</b></p>
</div>
<div class="card">
<h3>Honest performance</h3>
<span class="stat"><span class="v">95%</span><span class="l">TPR (LOS, 015 m)</span></span><br><br>
<span class="stat"><span class="v">±2 bpm</span><span class="l">HR (LOS 03 m)</span></span><br><br>
<span class="stat"><span class="v">±1 br/min</span><span class="l">BR (any mode)</span></span><br><br>
<span class="stat"><span class="v">~10 cm</span><span class="l">pose error</span></span><br><br>
<span class="stat"><span class="v">80150 ms</span><span class="l">end-to-end latency</span></span>
</div>
<div class="card">
<h3>Determinism</h3>
<p>Same <code style="font-family: var(--mono); color: var(--accent);">(scene, config, seed)</code> → byte-identical SHA-256 witness across browsers, OSes, transports.</p>
<p>Reference: <span style="font-family: var(--mono); font-size: 10.5px; color: var(--accent-3);">cc8de9b01b0ff5bd…</span></p>
<p>Try the Witness tab on the right — it re-derives the hash live in this browser and compares against the published reference.</p>
</div>
</div>
<h2>Privacy, ethics, legal</h2>
<div class="ethics">
<h3>This is the open-source version. Same physics, opposite governance.</h3>
<ul>
<li><b>Civilian opt-in only</b> — search-and-rescue, elder-care, occupancy, ICU vitals. Not surveillance.</li>
<li><b>No directional pursuit</b> — no beam-steering, target-following, or remote person-of-interest tracking.</li>
<li><b>Data minimisation</b> — fused output is <code>(presence, HR, BR, pose, p_alive)</code>; raw streams discarded at the edge.</li>
<li><b>PII gates</b> (ADR-040) block identifying biometric streams from leaving the local mesh without consent.</li>
<li><b>Adversarial-signal detection</b> flags physically-impossible signal patterns from compromised mesh nodes.</li>
<li><b>No export-controlled hardware</b> — RuView targets &lt; $50 COTS. ITAR/EAR sub-THz coherent radars and shielded NV ensembles are out of scope.</li>
</ul>
<p style="font-size: 11.5px; color: var(--ink-3); margin: 10px 0 0;">
RuView is not affiliated with the United States government, the CIA, Lockheed Martin,
or any classified program. References to "Ghost Murmur" in this view refer
exclusively to the publicly-reported program of that name as covered in the open
press in April 2026.
</p>
</div>
<h2>Cross-references</h2>
<div class="card">
<p style="font-size: 12px; color: var(--ink-2); line-height: 1.7; margin: 0;">
<b>ADRs:</b> 014 (signal) · 021 (vitals) · 024 (AETHER) · 027 (MERIDIAN) ·
028 (witness audit) · 029 (RuvSense) · 040 (PII gates) · 086 (ESP32 RaBitQ) ·
<b>089 (nvsim, Accepted)</b> · 090 (Lindblad, Proposed-conditional) ·
091 (sub-THz radar research) · <b>092 (this dashboard)</b>.<br><br>
<b>Primary physics:</b> Cohen 1970 · Bison 2009 · Wolf 2015 · Barry RMP 2020 · Doherty 2013 · Jackson 3e §5.6/§5.8.
</p>
</div>
`;
}
}
-458
View File
@@ -1,458 +0,0 @@
/* Help center — single dialog covering Quickstart / Glossary / FAQ /
* Shortcuts. Opened from the topbar `?` button or by pressing `?` on
* the keyboard. Self-contained, no external content. */
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
type Section = 'quickstart' | 'glossary' | 'faq' | 'shortcuts' | 'about';
interface GlossaryItem {
term: string;
body: string;
category: 'physics' | 'rust' | 'ui';
}
const GLOSSARY: GlossaryItem[] = [
{ term: 'NV-diamond', category: 'physics', body: 'Nitrogen-vacancy defect in synthetic diamond. The simulator models a 1 mm³ ensemble (~10¹² centers) addressed by 532 nm pump light + a 2.87 GHz microwave drive. Used as a room-temperature magnetometer with shot-noise floor ~1 pT/√Hz at the published lab record.' },
{ term: 'CW-ODMR', category: 'physics', body: 'Continuously-driven optically-detected magnetic resonance. Sweep the microwave frequency around the NV zero-field splitting (D = 2.87 GHz) and watch the photoluminescence dip when the microwave matches the spin transition. The dip splits with applied magnetic field along each of the four ⟨111⟩ NV axes.' },
{ term: 'MagFrame', category: 'rust', body: 'Fixed-layout 60-byte binary record nvsim emits per (sensor × sample). Magic 0xC51A_6E70, version 1, little-endian. Carries timestamp, recovered B vector (pT), per-axis sigma, noise floor, and flag bits for saturation / shot-noise-disabled / heavy-attenuation.' },
{ term: 'Witness', category: 'rust', body: 'SHA-256 hash over the concatenated MagFrame bytes for a canonical reference run (Proof::REFERENCE_SCENE_JSON @ seed=42, N=256). Same inputs → same hash, byte-for-byte, across runs and machines. The dashboard re-derives it in WASM and compares against Proof::EXPECTED_WITNESS_HEX pinned at build time.' },
{ term: 'Determinism gate', category: 'rust', body: 'A pass/fail check: did this build of nvsim produce the expected witness? If yes → every constant (γ_e, D_GS, μ₀, contrast, T₂*, the PRNG stream, the frame layout, the pipeline ordering) is byte-identical to the published reference. If no → something drifted; the dashboard names which.' },
{ term: 'Lock-in demod', category: 'physics', body: 'Multiply the photoluminescence signal by cos(2π·f_mod·t) and low-pass to recover the slowly-varying B-field component. The simulator emulates a lock-in with output gain 2 and a single-pole IIR LP filter; settable via the Tunables panel (f_mod default 1 kHz).' },
{ term: 'Shot-noise floor', category: 'physics', body: 'δB = 1 / (γ_e · C · √(N · t · T₂*)) — the irreducible quantum noise floor for an NV ensemble. With nvsim defaults (N=10¹², C=0.03, T₂*=200 ns): ≈1.18 pT/√Hz. Toggleable via the Tunables panel for "analytic" runs without noise.' },
{ term: 'Biot-Savart', category: 'physics', body: 'Closed-form magnetic field at a point from a current loop or a magnetic dipole. The Scene panel\'s sources (heart proxy, mains loop, ferrous body, eddy current) all reduce to Biot-Savart-style superpositions over the sensor position.' },
{ term: 'Multistatic fusion', category: 'physics', body: 'Combining evidence from multiple sensors at known geometric configurations. RuView\'s Cramer-Rao-weighted attention over WiFi CSI nodes + 60 GHz radar nodes + (hypothetically) NV nodes; documented in ADR-029 and the Ghost Murmur view.' },
{ term: 'Scene', category: 'ui', body: 'The simulated magnetic environment: a list of sources (dipole, current loop, ferrous body, eddy current) plus one or more sensor positions and an ambient field. The dashboard ships a "rebar-walkby-01" reference scene; click "New scene…" in the command palette (⌘K) to build your own.' },
{ term: 'Tunables', category: 'ui', body: 'Sliders that change the running pipeline\'s digitiser config. Each edit debounces 300 ms, then rebuilds the WASM pipeline with the new f_s / f_mod / dt / shot-noise setting. The frame stream picks up the change without a restart.' },
{ term: 'Transport', category: 'ui', body: 'How the dashboard talks to nvsim. Default is WASM — the simulator runs in a Web Worker right here in your browser, no server. The optional WS transport is REST + binary WebSocket against a host-supplied nvsim-server (see ADR-092 §6.2). Toggle in Settings.' },
{ term: 'App Store', category: 'ui', body: 'Catalog of all 65+ hot-loadable WASM edge modules from wifi-densepose-wasm-edge plus the simulators. Each card carries id / category / status / event IDs; the toggle marks an app active in this session and (in WS mode) pushes the activation to a connected ESP32 mesh.' },
{ term: 'Ghost Murmur', category: 'ui', body: 'Research view that audits the publicly-reported April 2026 CIA NV-diamond heartbeat detector against the open physics literature. Includes a live "Try it yourself" sandbox where you can place a heart dipole at any distance from the sensor and ask: which transport tier would actually detect it?' },
];
const FAQ = [
{
q: 'Is this a real simulator or a mockup?',
a: 'Real. The Rust crate at v2/crates/nvsim is the same code that runs in the browser via WASM. Press <b>Verify witness</b> on the Witness panel — the SHA-256 you see is byte-equivalent to what `cargo test -p nvsim` produces.',
},
{
q: 'Why does my "Recovered |B|" sit much higher than "Predicted |B|" in the Ghost Murmur demo?',
a: 'The recovered value reads the simulator\'s ADC quantization floor, not the actual magnetic signal. With COTS-default sensor noise (~300 pT/√Hz) and 16-bit ADC at ±10 µT FS, anything below ~1 pT vanishes into ~2 nT of digitization residual. That\'s the lesson — the press claim sits far below this floor at any meaningful range.',
},
{
q: 'Can I run my own scene?',
a: 'Yes. Press ⌘K to open the command palette and pick "New scene…". You get five fields (name, dipole moment, distance, ferrous toggle, mains toggle); the dashboard builds the JSON and pushes it via <code>client.loadScene()</code>.',
},
{
q: 'Does any of my data leave the browser?',
a: 'No. WASM mode is local-only — the worker, the WASM binary, and the IndexedDB persistence all live in your browser. The optional WS transport (off by default) talks to a host of your choosing.',
},
{
q: 'What does the witness mismatch (red ✗) mean?',
a: 'The current build of nvsim produced a SHA-256 that doesn\'t match the constant pinned at compile time. Possible causes: a different Rust toolchain, a dependency version drift, a manual edit to a physics constant, or an honest bug. Audit the diff against ADR-089 §5.',
},
{
q: 'Why are the Inspector / Witness rail buttons there if there\'s already a right-side inspector?',
a: 'The right-side inspector is the compact live view; the rail buttons open a full-width version with bigger charts, an explainer header, reference-scene metadata cards, and (on Witness) a "what this verifies" panel. Both stay in sync — the right rail is for glancing, the main area is for diving in.',
},
{
q: 'Why is there an "App Store" if this is a magnetometer simulator?',
a: 'Because nvsim is one tile in a larger sensing platform. The catalog lists every hot-loadable WASM edge module RuView ships — medical, security, building, retail, industrial, signal, learning, autonomy. The simulators (nvsim today, more in future) are first-class entries in the same catalog.',
},
];
const QUICKSTART = [
{ step: 1, title: 'Hit ▶ Run', body: 'The big amber button in the topbar starts the live frame stream. The pipeline runs ~1.8 kHz on x86_64 WASM, well above the 1 kHz Cortex-A53 acceptance gate.' },
{ step: 2, title: 'Watch the B-vector trace', body: 'The Inspector → Signal tab shows the recovered field per axis updating in real time. The frame strip below it is one bar per ~32-frame batch.' },
{ step: 3, title: 'Verify the witness', body: 'Click the rail Witness button (or REPL: <code>proof.verify</code>). The dashboard re-runs the canonical reference scene and asserts the SHA-256 byte-for-byte.' },
{ step: 4, title: 'Drag a source', body: 'Grab the rebar / heart proxy / mains loop / ferrous door in the scene canvas; positions persist via IndexedDB.' },
{ step: 5, title: 'Tweak the tunables', body: 'Sliders in the left sidebar update the running pipeline (f_s, f_mod, integration time, shot-noise). Changes debounce 300 ms then push to the worker.' },
{ step: 6, title: 'Open the Ghost Murmur view', body: 'The ghost icon in the rail. Move the distance + moment sliders, hit "Run nvsim at this distance" — the live demo runs the real Rust pipeline through WASM and shows which transport tier would actually detect.' },
{ step: 7, title: 'Browse the App Store', body: 'The grid icon. 65+ edge apps: medical, security, building, retail, industrial, signal, learning. Toggle to mark active in this session.' },
];
const SHORTCUTS = [
{ keys: '⌘K / Ctrl K', label: 'Command palette' },
{ keys: 'Space', label: 'Play / pause pipeline' },
{ keys: '⌘R / Ctrl R', label: 'Reset pipeline (with confirm)' },
{ keys: '⌘, / Ctrl ,', label: 'Settings drawer' },
{ keys: '⌘N / Ctrl N', label: 'New scene' },
{ keys: '⌘E / Ctrl E', label: 'Export proof bundle' },
{ keys: '⌘/ / Ctrl /', label: 'Toggle theme (dark / light)' },
{ keys: '`', label: 'Toggle debug HUD' },
{ keys: '?', label: 'Open this help center' },
{ keys: '1 · 2 · 3', label: 'Switch inspector tab (Signal / Frame / Witness)' },
{ keys: 'Esc', label: 'Close any modal / palette / drawer' },
{ keys: '/', label: 'Focus the REPL prompt' },
];
@customElement('nv-help')
export class NvHelp extends LitElement {
@state() private open = false;
@state() private section: Section = 'quickstart';
@state() private query = '';
static styles = css`
:host {
position: fixed; inset: 0;
background: rgba(0, 0, 0, 0.55);
backdrop-filter: blur(4px);
z-index: 230;
display: grid; place-items: center;
opacity: 0; pointer-events: none;
transition: opacity 0.18s;
}
:host([open]) { opacity: 1; pointer-events: auto; }
.modal {
background: var(--bg-1);
border: 1px solid var(--line-2);
border-radius: var(--radius);
box-shadow: 0 30px 80px -20px rgba(0,0,0,0.7);
width: min(880px, 94vw);
max-height: 86vh;
display: grid;
grid-template-columns: 200px 1fr;
grid-template-rows: auto 1fr auto;
overflow: hidden;
transform: translateY(12px) scale(0.98);
transition: transform 0.22s cubic-bezier(0.2,0.7,0.3,1);
}
:host([open]) .modal { transform: translateY(0) scale(1); }
@media (max-width: 700px) {
.modal { grid-template-columns: 1fr; grid-template-rows: auto auto 1fr auto; max-height: 92vh; }
.nav { border-right: 0; border-bottom: 1px solid var(--line); flex-direction: row; overflow-x: auto; }
.nav button { white-space: nowrap; }
}
.h {
grid-column: 1 / -1;
padding: 14px 18px;
border-bottom: 1px solid var(--line);
display: flex; align-items: center; justify-content: space-between;
}
.h .ttl { font-size: 15px; font-weight: 600; }
.nav {
border-right: 1px solid var(--line);
padding: 12px 8px;
display: flex; flex-direction: column; gap: 2px;
background: var(--bg-1);
}
.nav button {
text-align: left;
padding: 8px 12px;
background: transparent;
border: 1px solid transparent;
border-radius: 6px;
color: var(--ink-3);
font-size: 12.5px;
cursor: pointer;
transition: color 0.15s, background 0.15s;
}
.nav button:hover { color: var(--ink); background: var(--bg-2); }
.nav button.on {
color: var(--ink); background: var(--bg-3);
border-color: var(--line-2);
}
.body {
padding: 18px 22px;
overflow-y: auto;
font-size: 13px;
color: var(--ink-2);
line-height: 1.6;
}
.body h2 {
margin: 0 0 8px;
font-size: 18px;
color: var(--ink);
letter-spacing: -0.01em;
}
.body .lead {
color: var(--ink-3);
font-size: 12.5px;
margin: 0 0 14px;
}
.body p { margin: 0 0 12px; }
.body code {
font-family: var(--mono);
background: var(--bg-3);
padding: 1px 5px;
border-radius: 4px;
font-size: 11.5px;
color: var(--accent);
}
.body kbd {
font-family: var(--mono);
padding: 2px 6px;
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: 4px;
font-size: 11.5px;
color: var(--ink);
}
.step {
display: grid;
grid-template-columns: 32px 1fr;
gap: 12px;
padding: 10px 0;
border-bottom: 1px solid var(--line);
}
.step:last-child { border-bottom: 0; }
.step .num {
width: 26px; height: 26px;
border-radius: 50%;
background: var(--accent);
color: #1a0f00;
font-family: var(--mono);
font-size: 12.5px;
font-weight: 700;
display: grid; place-items: center;
}
.step .ttl { color: var(--ink); font-weight: 600; font-size: 13.5px; margin-bottom: 2px; }
.step .body-text { font-size: 12.5px; color: var(--ink-2); line-height: 1.55; }
.glossary-search {
width: 100%;
padding: 8px 12px;
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: 6px;
font-family: var(--mono);
font-size: 12.5px;
color: var(--ink);
outline: none;
margin-bottom: 14px;
}
.glossary-search:focus { border-color: var(--accent); }
.term {
padding: 10px 0;
border-bottom: 1px solid var(--line);
}
.term:last-child { border-bottom: 0; }
.term .head {
display: flex; align-items: center; gap: 8px; margin-bottom: 4px;
}
.term .name {
font-family: var(--mono);
font-size: 13.5px;
color: var(--accent);
font-weight: 600;
}
.term .badge {
font-family: var(--mono);
font-size: 9.5px;
padding: 1px 6px;
border-radius: 4px;
border: 1px solid var(--line);
text-transform: uppercase;
letter-spacing: 0.04em;
}
.term .badge.physics { color: var(--accent-2); border-color: oklch(0.78 0.12 195 / 0.4); }
.term .badge.rust { color: var(--accent); border-color: oklch(0.78 0.14 70 / 0.4); }
.term .badge.ui { color: var(--accent-4); border-color: oklch(0.78 0.14 145 / 0.4); }
.term .body-text {
font-size: 12.5px;
color: var(--ink-2);
line-height: 1.55;
}
.faq-item {
padding: 10px 0;
border-bottom: 1px solid var(--line);
}
.faq-item:last-child { border-bottom: 0; }
.faq-item .q {
color: var(--ink);
font-weight: 600;
font-size: 13.5px;
margin-bottom: 4px;
}
.faq-item .a { font-size: 12.5px; color: var(--ink-2); line-height: 1.55; }
.shortcuts {
display: grid;
grid-template-columns: auto 1fr;
gap: 8px 16px;
align-items: baseline;
}
.f {
grid-column: 1 / -1;
padding: 10px 18px;
border-top: 1px solid var(--line);
display: flex; align-items: center; justify-content: space-between;
font-size: 11.5px; color: var(--ink-3);
}
.close {
width: 28px; height: 28px;
background: transparent; border: 1px solid var(--line);
border-radius: 6px;
color: var(--ink-2);
cursor: pointer;
}
.close:hover { color: var(--ink); border-color: var(--line-2); }
`;
override connectedCallback(): void {
super.connectedCallback();
window.addEventListener('nv-show-help', this.show as EventListener);
window.addEventListener('nv-show-help-close', this.closeListener);
window.addEventListener('keydown', this.onKey);
}
override disconnectedCallback(): void {
super.disconnectedCallback();
window.removeEventListener('nv-show-help', this.show as EventListener);
window.removeEventListener('nv-show-help-close', this.closeListener);
window.removeEventListener('keydown', this.onKey);
}
private closeListener = (): void => this.close();
private show = (e: Event): void => {
const detail = (e as CustomEvent).detail as { section?: Section } | undefined;
if (detail?.section) this.section = detail.section;
this.open = true;
this.setAttribute('open', '');
};
private close(): void {
this.open = false;
this.removeAttribute('open');
}
private onKey = (e: KeyboardEvent): void => {
const target = e.target as HTMLElement | null;
const isInput = target?.tagName === 'INPUT' || target?.tagName === 'TEXTAREA';
if (e.key === '?' && !isInput && !e.ctrlKey && !e.metaKey) {
e.preventDefault();
this.show(new CustomEvent('nv-show-help'));
} else if (e.key === 'Escape' && this.open) {
this.close();
}
};
private filteredGlossary(): GlossaryItem[] {
if (!this.query.trim()) return GLOSSARY;
const q = this.query.toLowerCase();
return GLOSSARY.filter((g) =>
g.term.toLowerCase().includes(q) || g.body.toLowerCase().includes(q),
);
}
private renderQuickstart() {
return html`
<h2>Quickstart</h2>
<p class="lead">Seven taps to get from "I just opened the dashboard" to "I'm running my own scene with verified determinism."</p>
<button
style="display:inline-flex; align-items:center; gap:8px; padding:10px 16px; margin-bottom:14px; background:var(--accent); color:#1a0f00; border:none; border-radius:8px; font-size:13px; font-weight:600; cursor:pointer; font-family:inherit;"
@click=${() => { window.dispatchEvent(new CustomEvent('nv-show-help-close')); window.dispatchEvent(new CustomEvent('nv-show-tour')); }}>
★ Take the interactive 10-step tour
</button>
${QUICKSTART.map((s) => html`
<div class="step">
<div class="num">${s.step}</div>
<div>
<div class="ttl">${s.title}</div>
<div class="body-text" .innerHTML=${s.body}></div>
</div>
</div>
`)}
`;
}
private renderGlossary() {
const items = this.filteredGlossary();
return html`
<h2>Glossary</h2>
<p class="lead">Every piece of jargon in the dashboard, defined in one paragraph each.</p>
<input class="glossary-search" type="text" placeholder="Search 14 terms…"
.value=${this.query}
@input=${(e: Event) => this.query = (e.target as HTMLInputElement).value} />
${items.length === 0
? html`<p style="color: var(--ink-3);">No terms match.</p>`
: items.map((g) => html`
<div class="term">
<div class="head">
<span class="name">${g.term}</span>
<span class="badge ${g.category}">${g.category}</span>
</div>
<div class="body-text">${g.body}</div>
</div>
`)}
`;
}
private renderFaq() {
return html`
<h2>FAQ</h2>
<p class="lead">The questions I was asked twice in the first week of demos.</p>
${FAQ.map((item) => html`
<div class="faq-item">
<div class="q">${item.q}</div>
<div class="a" .innerHTML=${item.a}></div>
</div>
`)}
`;
}
private renderShortcuts() {
return html`
<h2>Keyboard shortcuts</h2>
<p class="lead">Everything is reachable without a mouse.</p>
<div class="shortcuts">
${SHORTCUTS.map((s) => html`
<kbd>${s.keys}</kbd><span>${s.label}</span>
`)}
</div>
`;
}
private renderAbout() {
return html`
<h2>About this dashboard</h2>
<p class="lead">What you're looking at, in one screen.</p>
<p><b>nvsim</b> is a deterministic forward simulator for nitrogen-vacancy diamond magnetometry.
The Rust crate at <code>v2/crates/nvsim</code> is the source of truth; this dashboard is a
Vite + Lit single-page app that ships the crate compiled to WebAssembly inside a Web Worker.</p>
<p>The defining commitment is <b>determinism</b>: same <code>(scene, config, seed)</code> →
byte-identical SHA-256 witness across browsers, OSes, and transports. Press the
<kbd>Verify witness</kbd> button on the Witness tab to assert this live.</p>
<p>The codebase is open source (Apache-2.0 OR MIT). Find it on GitHub:
<code>github.com/ruvnet/RuView</code>. Decisions are documented in ADRs 089 (nvsim),
090 (Lindblad extension, conditional), 091 (sub-THz radar research),
092 (this dashboard), 093 (UX gap analysis).</p>
<p>This dashboard is one of several RuView demos. Sibling demos at
<code>github.io/RuView/</code> include the Observatory and Pose Fusion views.</p>
`;
}
override render() {
return html`
<div class="modal" role="dialog" aria-modal="true" aria-label="Help center">
<div class="h">
<div class="ttl">Help</div>
<button class="close" aria-label="Close help" @click=${() => this.close()}>×</button>
</div>
<nav class="nav" role="tablist" aria-label="Help sections">
${(['quickstart', 'glossary', 'faq', 'shortcuts', 'about'] as Section[]).map((s) => html`
<button class=${this.section === s ? 'on' : ''} role="tab"
aria-selected=${this.section === s}
@click=${() => this.section = s}>
${s === 'quickstart' ? '🚀 Quickstart'
: s === 'glossary' ? '📖 Glossary'
: s === 'faq' ? '? FAQ'
: s === 'shortcuts' ? '⌨ Shortcuts'
: ' About'}
</button>
`)}
</nav>
<div class="body" role="tabpanel">
${this.section === 'quickstart' ? this.renderQuickstart()
: this.section === 'glossary' ? this.renderGlossary()
: this.section === 'faq' ? this.renderFaq()
: this.section === 'shortcuts' ? this.renderShortcuts()
: this.renderAbout()}
</div>
<div class="f">
<span>Press <kbd style="font-family:var(--mono);font-size:10.5px;padding:1px 4px;background:var(--bg-3);border:1px solid var(--line);border-radius:3px;">?</kbd> any time to reopen</span>
<span>nvsim · Apache-2.0 OR MIT</span>
</div>
</div>
`;
}
}
export function showHelp(section?: Section): void {
window.dispatchEvent(new CustomEvent('nv-show-help', { detail: { section } }));
}
-270
View File
@@ -1,270 +0,0 @@
/* Home view — friendly landing surface for new users.
*
* The full-power scene + sidebar + inspector + console are intentionally
* dense; that's the operator surface. Home is for first-time visitors:
* a single hero CTA, four quick-jump action cards, and a 1-paragraph
* explanation of what this dashboard is. No jargon above the fold.
*/
import { LitElement, html, css } from 'lit';
import { customElement } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import { running, getClient, witnessVerified, fps, pushLog } from '../store/appStore';
export type Action = 'scene' | 'apps' | 'witness' | 'ghost-murmur' | 'help' | 'tour';
@customElement('nv-home')
export class NvHome extends LitElement {
static styles = css`
:host {
display: block;
height: 100%;
overflow-y: auto;
background: radial-gradient(ellipse at 50% 30%, var(--bg-2) 0%, var(--bg-0) 70%);
padding: 28px clamp(16px, 6vw, 56px) 60px;
}
.hero {
max-width: 800px;
margin: 16px auto 28px;
text-align: center;
}
.hero .icon {
width: 56px; height: 56px;
margin: 0 auto 18px;
border-radius: 14px;
background: linear-gradient(135deg, oklch(0.78 0.14 70) 0%, oklch(0.55 0.16 30) 100%);
display: grid; place-items: center;
font-family: var(--mono);
font-weight: 700;
font-size: 18px;
color: #1a0f00;
box-shadow: 0 8px 24px -6px oklch(0.55 0.16 30 / 0.4);
}
.hero h1 {
margin: 0 0 8px;
font-size: clamp(24px, 4vw, 34px);
letter-spacing: -0.02em;
color: var(--ink);
line-height: 1.15;
}
.hero .tag {
font-size: clamp(13px, 1.6vw, 15px);
color: var(--ink-2);
margin: 0 0 22px;
line-height: 1.55;
}
.hero .ctas {
display: flex; flex-wrap: wrap; gap: 8px;
justify-content: center;
}
.cta {
padding: 11px 20px;
border-radius: 10px;
font-size: 14px;
font-weight: 600;
cursor: pointer;
font-family: inherit;
border: 1px solid var(--line);
background: var(--bg-2);
color: var(--ink);
transition: transform 0.12s, border-color 0.12s, filter 0.12s;
}
.cta:hover { transform: translateY(-1px); border-color: var(--line-2); }
.cta.primary {
background: var(--accent);
border-color: var(--accent);
color: #1a0f00;
}
.cta.primary:hover { filter: brightness(1.08); }
.status {
display: inline-flex; align-items: center; gap: 8px;
padding: 6px 12px;
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: 999px;
font-size: 12px;
font-family: var(--mono);
color: var(--ink-2);
margin-top: 18px;
}
.status .dot {
width: 8px; height: 8px; border-radius: 50%;
background: var(--ink-3);
}
.status.live .dot {
background: var(--ok);
box-shadow: 0 0 8px var(--ok);
animation: pulse 2s infinite;
}
@keyframes pulse { 50% { opacity: 0.5; } }
.grid {
max-width: 980px;
margin: 36px auto 0;
display: grid;
grid-template-columns: repeat(auto-fit, minmax(260px, 1fr));
gap: 14px;
}
.card {
background: var(--bg-2);
border: 1px solid var(--line);
border-radius: var(--radius);
padding: 18px 20px;
cursor: pointer;
transition: transform 0.12s, border-color 0.12s, background 0.12s;
display: flex; flex-direction: column; gap: 6px;
text-align: left;
color: inherit;
}
.card:hover {
transform: translateY(-2px);
border-color: var(--accent);
background: linear-gradient(180deg, var(--bg-2) 0%, oklch(0.78 0.14 70 / 0.04) 100%);
}
.card .ico {
font-size: 22px;
line-height: 1;
margin-bottom: 4px;
}
.card h3 {
margin: 0;
font-size: 14.5px;
font-weight: 600;
color: var(--ink);
letter-spacing: -0.01em;
}
.card p {
margin: 0;
font-size: 12.5px;
color: var(--ink-2);
line-height: 1.55;
}
.card .arrow {
color: var(--accent);
font-family: var(--mono);
font-size: 11.5px;
margin-top: 6px;
}
.footnote {
max-width: 800px;
margin: 36px auto 0;
text-align: center;
font-size: 12px;
color: var(--ink-3);
line-height: 1.55;
}
.footnote code {
font-family: var(--mono);
background: var(--bg-3);
padding: 1px 5px;
border-radius: 4px;
color: var(--accent);
font-size: 11px;
}
.footnote a {
color: var(--accent-2);
text-decoration: underline dotted;
cursor: pointer;
}
`;
override connectedCallback(): void {
super.connectedCallback();
effect(() => { running.value; witnessVerified.value; fps.value; this.requestUpdate(); });
}
private go(action: Action): void {
if (action === 'tour') { window.dispatchEvent(new CustomEvent('nv-show-tour')); return; }
if (action === 'help') { window.dispatchEvent(new CustomEvent('nv-show-help')); return; }
this.dispatchEvent(new CustomEvent('navigate', { detail: action, bubbles: true, composed: true }));
}
private async runDemo(): Promise<void> {
const c = getClient(); if (!c) return;
if (running.value) return;
await c.run();
running.value = true;
pushLog('ok', 'demo started · streaming MagFrames');
}
override render() {
const isRunning = running.value;
const wasVerified = witnessVerified.value === 'ok';
return html`
<div class="hero">
<div class="icon" aria-hidden="true">NV</div>
<h1>An open-source quantum-magnetometer simulator, in your browser.</h1>
<p class="tag">
nvsim runs a real Rust simulator (the same code that
<code style="font-family:var(--mono); background:var(--bg-3); padding:1px 5px; border-radius:4px; color:var(--accent); font-size:12px;">cargo&nbsp;test</code>
uses) entirely in WebAssembly. No server, no upload, no telemetry.
Press the button to start the live magnetic-field simulation, or
take the 60-second tour first.
</p>
<div class="ctas">
<button class="cta primary" id="home-run-btn" @click=${() => this.runDemo()}>
${isRunning ? '✓ Demo running' : '▶ Run the simulation'}
</button>
<button class="cta" id="home-tour-btn" @click=${() => this.go('tour')}>
★ Take the 60-second tour
</button>
<button class="cta" id="home-help-btn" @click=${() => this.go('help')}>
? Help center
</button>
</div>
<div class="status ${isRunning ? 'live' : ''}">
<span class="dot"></span>
${isRunning
? html`Live · ${fps.value > 0 ? (fps.value / 1000).toFixed(2) + ' kHz' : 'starting…'}${wasVerified ? ' · witness verified ✓' : ''}`
: html`Idle${wasVerified ? ' · witness verified ✓' : ''}`}
</div>
</div>
<div class="grid">
<div class="card" tabindex="0" role="button"
@click=${() => this.go('scene')}
@keydown=${(e: KeyboardEvent) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); this.go('scene'); } }}>
<div class="ico">🌐</div>
<h3>Live scene</h3>
<p>Drag magnetic sources, watch the recovered field update in real time, and tweak sample rate / noise / integration.</p>
<div class="arrow">Open scene →</div>
</div>
<div class="card" tabindex="0" role="button"
@click=${() => this.go('apps')}
@keydown=${(e: KeyboardEvent) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); this.go('apps'); } }}>
<div class="ico">🛍</div>
<h3>App Store · 66 edge apps</h3>
<p>Browse 65 hot-loadable WASM sensing modules across medical, security, building, retail, industrial, learning. Six run live in the browser.</p>
<div class="arrow">Browse the catalogue →</div>
</div>
<div class="card" tabindex="0" role="button"
@click=${() => this.go('witness')}
@keydown=${(e: KeyboardEvent) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); this.go('witness'); } }}>
<div class="ico">✓</div>
<h3>Determinism gate</h3>
<p>Re-derive the SHA-256 witness for the canonical reference scene right here in your browser. Same inputs → same hash, every time.</p>
<div class="arrow">Verify the witness →</div>
</div>
<div class="card" tabindex="0" role="button"
@click=${() => this.go('ghost-murmur')}
@keydown=${(e: KeyboardEvent) => { if (e.key === 'Enter' || e.key === ' ') { e.preventDefault(); this.go('ghost-murmur'); } }}>
<div class="ico">👻</div>
<h3>Ghost Murmur reality check</h3>
<p>Audit the publicly-reported April 2026 CIA NV-diamond program against published physics. Live distance/moment sliders.</p>
<div class="arrow">Read the spec →</div>
</div>
</div>
<p class="footnote">
New here? <a @click=${() => this.go('tour')}>Take the 60-second guided tour</a>
— every panel is explained. Or press <code>?</code> for the help center
(quickstart, glossary, FAQ, shortcuts) any time.<br>
Open source · Apache-2.0 OR MIT · <code>github.com/ruvnet/RuView</code>
</p>
`;
}
}
-434
View File
@@ -1,434 +0,0 @@
/* Inspector — tabbed: Signal / Frame / Witness. */
import { LitElement, html, css, svg, type PropertyValues } from 'lit';
import { customElement, state, property } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import {
traceX, traceY, traceZ, stripBars, lastFrame,
witnessHex, expectedWitness, witnessVerified, getClient,
pushLog, lastB, bMag,
} from '../store/appStore';
type Tab = 'signal' | 'frame' | 'witness';
@customElement('nv-inspector')
export class NvInspector extends LitElement {
@state() private tab: Tab = 'signal';
/** When set by the parent, force the tab and pulse-highlight it. */
@property({ attribute: false }) pinTab: Tab | null = null;
/** When `expanded`, the inspector renders as a full-screen view with bigger
* charts and a wider Witness panel. Used when the rail Inspector/Witness
* button is clicked — see ADR-093 P1.13. */
@property({ type: Boolean, reflect: true }) expanded = false;
static styles = css`
:host {
display: flex; flex-direction: column;
background: var(--bg-1);
border-left: 1px solid var(--line);
overflow: hidden;
height: 100%;
}
:host([expanded]) {
border-left: 0;
background: radial-gradient(ellipse at 50% 30%, var(--bg-2) 0%, var(--bg-0) 70%);
}
:host([expanded]) .tabs {
padding: 0 24px;
background: var(--bg-1);
}
:host([expanded]) .tab {
padding: 16px 22px;
font-size: 13.5px;
flex: 0 0 auto;
}
:host([expanded]) .body {
padding: 24px 28px;
max-width: 1400px;
width: 100%;
margin: 0 auto;
}
:host([expanded]) .card { padding: 18px 20px; }
:host([expanded]) .card-h .ttl { font-size: 14px; }
:host([expanded]) svg { height: 220px; }
:host([expanded]) .frame-strip { height: 48px; }
:host([expanded]) table { font-size: 12.5px; }
:host([expanded]) td { padding: 6px 0; }
:host([expanded]) .hex { font-size: 12px; padding: 14px; line-height: 1.7; }
:host([expanded]) .witness-box { font-size: 13px; padding: 14px 16px; line-height: 1.6; }
:host([expanded]) .verify-btn { padding: 12px; font-size: 13px; }
:host([expanded]) .grid-2 {
display: grid;
grid-template-columns: 1fr 1fr;
gap: 16px;
}
:host([expanded]) .grid-2 > .card { margin-bottom: 0; }
@media (max-width: 1024px) {
:host([expanded]) .grid-2 { grid-template-columns: 1fr; }
}
.tabs {
display: flex; border-bottom: 1px solid var(--line);
}
.tab {
flex: 1;
padding: 11px 8px;
background: transparent; border: none;
font-size: 11.5px; font-weight: 500;
color: var(--ink-3);
border-bottom: 2px solid transparent;
cursor: pointer; transition: color 0.15s, border-color 0.15s;
}
.tab.active { color: var(--ink); border-bottom-color: var(--accent); }
.tab:hover { color: var(--ink-2); }
.body { padding: 14px; flex: 1; overflow-y: auto; }
.card {
background: var(--bg-2); border: 1px solid var(--line);
border-radius: var(--radius); padding: 12px;
margin-bottom: 12px;
}
.card-h {
display: flex; justify-content: space-between; align-items: center;
margin-bottom: 8px;
}
.card-h .ttl { font-size: 12px; font-weight: 600; }
.badge {
font-family: var(--mono); font-size: 10px;
padding: 2px 6px;
background: oklch(0.78 0.14 195 / 0.12);
color: var(--accent-2);
border-radius: 4px;
border: 1px solid oklch(0.78 0.14 195 / 0.3);
}
svg { width: 100%; height: 130px; }
.frame-strip {
height: 28px;
display: flex; align-items: flex-end; gap: 1px;
padding: 4px 0;
}
.bar {
flex: 1;
background: linear-gradient(to top, var(--accent-2), var(--accent));
border-radius: 1px;
min-height: 2px;
}
table { width: 100%; border-collapse: collapse; font-family: var(--mono); font-size: 10.5px; }
td { padding: 4px 0; border-bottom: 1px solid var(--line); }
td:first-child { color: var(--ink-3); }
td:last-child { text-align: right; color: var(--ink); }
.hex {
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: var(--radius-sm);
padding: 10px;
font-family: var(--mono);
font-size: 10.5px;
color: var(--ink-2);
line-height: 1.6;
overflow-x: auto;
white-space: nowrap;
}
.hex .magic { color: var(--accent); font-weight: 600; }
.witness-box {
font-family: var(--mono);
font-size: 11px;
color: var(--ink-2);
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: 6px;
padding: 8px 10px;
word-break: break-all;
line-height: 1.5;
}
.verify-btn {
margin-top: 10px;
width: 100%;
padding: 8px;
border: 1px solid var(--line);
background: var(--bg-3);
color: var(--ink);
border-radius: 8px;
cursor: pointer;
font-family: var(--mono);
font-size: 12px;
}
.verify-btn:hover { border-color: var(--accent); }
.verify-btn.ok { border-color: var(--ok); color: var(--ok); }
.verify-btn.fail { border-color: var(--bad); color: var(--bad); }
`;
override connectedCallback(): void {
super.connectedCallback();
effect(() => {
traceX.value; traceY.value; traceZ.value; stripBars.value;
lastFrame.value; witnessHex.value; witnessVerified.value;
lastB.value; bMag.value;
this.requestUpdate();
});
}
override willUpdate(changed: PropertyValues): void {
// Apply parent-driven tab pin during willUpdate so the new tab value
// participates in this same render pass — avoids the "update after
// update completed" Lit warning that would fire if we did this in
// updated().
if (changed.has('pinTab') && this.pinTab && this.tab !== this.pinTab) {
this.tab = this.pinTab;
}
}
private async verify(): Promise<void> {
const c = getClient(); if (!c) return;
witnessVerified.value = 'pending';
pushLog('info', 'verifying witness over 256 frames…');
try {
const exp = expectedWitness.value;
const expBytes = new Uint8Array(32);
for (let i = 0; i < 32; i++) expBytes[i] = parseInt(exp.slice(i * 2, i * 2 + 2), 16);
const r = await c.verifyWitness(expBytes);
if (r.ok) {
witnessVerified.value = 'ok';
witnessHex.value = exp;
pushLog('ok', `witness ${exp.slice(0, 16)}… matches · determinism gate ✓`);
} else {
witnessVerified.value = 'fail';
const actual = Array.from(r.actual).map((b) => b.toString(16).padStart(2, '0')).join('');
witnessHex.value = actual;
pushLog('err', `WITNESS MISMATCH actual=${actual.slice(0, 16)}`);
}
} catch (e) {
witnessVerified.value = 'fail';
pushLog('err', `verify failed: ${(e as Error).message}`);
}
}
private renderHeader() {
if (!this.expanded) return '';
const titles: Record<Tab, string> = {
signal: 'Signal inspector — live B-vector trace + frame stream',
frame: 'Frame inspector — MagFrame v1 fields + raw bytes',
witness: 'Witness panel — SHA-256 determinism gate',
};
return html`
<h1 style="margin: 8px 0 14px; font-size: 20px; letter-spacing: -0.01em;">
${titles[this.tab]}
</h1>
<p style="margin: 0 0 18px; font-size: 12.5px; color: var(--ink-3); line-height: 1.55; max-width: 780px;">
${this.tab === 'signal'
? 'Real-time recovered field-vector and frame-stream sparkline. Both update at the running pipeline\'s frame rate. Use the Tunables panel in the sidebar to change f_s, f_mod, dt, and shot-noise behaviour.'
: this.tab === 'frame'
? 'Decoded view of the most recent MagFrame: typed fields plus the raw 60-byte little-endian binary record (magic 0xC51A_6E70).'
: 'Re-derive the SHA-256 witness for the canonical reference scene (seed=42, N=256) right now in your browser and compare against Proof::EXPECTED_WITNESS_HEX. Same inputs → same hash, byte-for-byte, across every machine and transport.'}
</p>
`;
}
private renderSignalTab() {
const W = 320, H = 130, cy = 65, scale = 22;
const cap = 200;
const make = (arr: number[]) => {
let p = '';
arr.forEach((v, i) => {
const x = (i / Math.max(1, cap - 1)) * W;
const y = cy - v * scale;
p += (i === 0 ? 'M' : 'L') + ` ${x.toFixed(1)} ${y.toFixed(1)} `;
});
return p;
};
const b = lastB.value;
const bnT = [b[0] * 1e9, b[1] * 1e9, b[2] * 1e9];
const hasData = traceX.value.length > 0;
return html`
${!hasData ? html`
<div class="card" style="text-align:center; padding:18px;">
<div style="font-size:13px; color:var(--ink-2); line-height:1.55;">
No frames yet. Press <b>▶ Run</b> in the topbar (or hit <code style="font-family:var(--mono);background:var(--bg-3);padding:1px 5px;border-radius:4px;color:var(--accent);">Space</code>)
to start the live B-vector trace.
</div>
</div>
` : ''}
<div class=${this.expanded ? 'grid-2' : ''}>
<div class="card">
<div class="card-h">
<span class="ttl">B-vector trace</span>
<span class="badge">3-axis · nT</span>
</div>
<svg viewBox="0 0 ${W} ${H}" preserveAspectRatio="none">
<line x1="0" y1=${cy} x2=${W} y2=${cy} stroke="var(--line)" stroke-width="0.5"/>
${svg`<path id="trace-x" d=${make(traceX.value)} stroke="oklch(0.78 0.14 70)" stroke-width="1.2" fill="none"/>`}
${svg`<path id="trace-y" d=${make(traceY.value)} stroke="oklch(0.78 0.12 195)" stroke-width="1.2" fill="none" opacity="0.8"/>`}
${svg`<path id="trace-z" d=${make(traceZ.value)} stroke="oklch(0.72 0.18 330)" stroke-width="1.2" fill="none" opacity="0.7"/>`}
</svg>
${this.expanded ? html`<div style="display:flex;gap:14px;font-size:12px;font-family:var(--mono);margin-top:8px;">
<span style="color:oklch(0.78 0.14 70);">x: ${bnT[0].toFixed(3)} nT</span>
<span style="color:oklch(0.78 0.12 195);">y: ${bnT[1].toFixed(3)} nT</span>
<span style="color:oklch(0.72 0.18 330);">z: ${bnT[2].toFixed(3)} nT</span>
<span style="color:var(--accent);margin-left:auto;">|B| ${(bMag.value * 1e9).toFixed(3)} nT</span>
</div>` : ''}
</div>
<div class="card">
<div class="card-h">
<span class="ttl">Frame stream</span>
<span class="badge" id="strip-rate">live</span>
</div>
<div class="frame-strip" id="frame-strip">
${stripBars.value.map((v) => html`<div class="bar" style=${`height:${Math.max(4, v * 100)}%`}></div>`)}
</div>
${this.expanded ? html`
<div style="display:flex;gap:24px;font-family:var(--mono);font-size:12px;color:var(--ink-3);margin-top:12px;">
<span>frames in window: <span style="color:var(--ink);">${stripBars.value.length}</span></span>
<span>noise floor: <span style="color:var(--ink);">${lastFrame.value ? lastFrame.value.noiseFloorPtSqrtHz.toFixed(2) + ' pT/√Hz' : '—'}</span></span>
</div>` : ''}
</div>
</div>
`;
}
private renderFrameTab() {
const f = lastFrame.value;
const bytes = f?.raw;
let hex = '';
if (bytes) {
const arr = Array.from(bytes).map((b) => b.toString(16).padStart(2, '0'));
hex = arr.slice(0, 60).join(' ');
}
return html`
${!f ? html`
<div class="card" style="text-align:center; padding:18px;">
<div style="font-size:13px; color:var(--ink-2); line-height:1.55;">
No MagFrame to display yet. Start the pipeline (<b>▶ Run</b>) to populate.
</div>
</div>
` : ''}
<div class=${this.expanded ? 'grid-2' : ''}>
<div class="card">
<div class="card-h">
<span class="ttl">MagFrame v1 fields</span>
<span class="badge">60 B</span>
</div>
<table>
<tr><td>magic</td><td id="frame-magic">${f ? '0x' + f.magic.toString(16).toUpperCase() : '—'}</td></tr>
<tr><td>version</td><td>${f?.version ?? '—'}</td></tr>
<tr><td>flags</td><td>0x${(f?.flags ?? 0).toString(16).padStart(4, '0')}</td></tr>
<tr><td>sensor_id</td><td>${f?.sensorId ?? '—'}</td></tr>
<tr><td>t_us</td><td>${f ? f.tUs.toString() : '—'}</td></tr>
<tr><td>b_pT[0]</td><td id="frame-bx">${f ? f.bPt[0].toFixed(1) : '—'}</td></tr>
<tr><td>b_pT[1]</td><td id="frame-by">${f ? f.bPt[1].toFixed(1) : '—'}</td></tr>
<tr><td>b_pT[2]</td><td id="frame-bz">${f ? f.bPt[2].toFixed(1) : '—'}</td></tr>
<tr><td>noise_floor</td><td>${f ? f.noiseFloorPtSqrtHz.toFixed(2) : '—'}</td></tr>
<tr><td>temp_K</td><td>${f ? f.temperatureK.toFixed(1) : '—'}</td></tr>
</table>
</div>
<div class="card">
<div class="card-h">
<span class="ttl">Hex dump</span>
<span class="badge">LE</span>
</div>
<div class="hex" id="frame-hex">${hex || '—'}</div>
${this.expanded ? html`
<div style="font-size: 11.5px; color: var(--ink-3); margin-top: 10px; line-height: 1.6;">
Layout (little-endian): <code>magic(u32) version(u16) flags(u16) sensor_id(u16) _reserved(u16) t_us(u64) b_pt[3](f32) sigma_pt[3](f32) noise_floor(f32) temp_K(f32)</code>.
</div>` : ''}
</div>
</div>
`;
}
private renderWitnessTab() {
const status = witnessVerified.value;
const cls = status === 'ok' ? 'ok' : status === 'fail' ? 'fail' : '';
const label =
status === 'pending' ? 'Verifying…' :
status === 'ok' ? '✓ Witness verified · determinism gate' :
status === 'fail' ? '✗ Witness mismatch · audit required' :
'Verify witness';
const match = expectedWitness.value && witnessHex.value && expectedWitness.value === witnessHex.value;
return html`
${this.expanded ? html`
<div style="display:grid;grid-template-columns:repeat(auto-fit, minmax(180px, 1fr));gap:12px;margin-bottom:18px;">
<div class="card" style="margin:0;">
<div style="font-size:10px;color:var(--ink-3);text-transform:uppercase;letter-spacing:0.06em;">Reference scene</div>
<div style="font-family:var(--mono);font-size:14px;color:var(--ink);margin-top:4px;">Proof::REFERENCE</div>
<div style="font-size:11.5px;color:var(--ink-3);margin-top:2px;">2 dipoles · 1 loop · 1 ferrous · 1 sensor</div>
</div>
<div class="card" style="margin:0;">
<div style="font-size:10px;color:var(--ink-3);text-transform:uppercase;letter-spacing:0.06em;">Seed</div>
<div style="font-family:var(--mono);font-size:14px;color:var(--accent);margin-top:4px;">0x0000002A</div>
<div style="font-size:11.5px;color:var(--ink-3);margin-top:2px;">canonical Proof::SEED</div>
</div>
<div class="card" style="margin:0;">
<div style="font-size:10px;color:var(--ink-3);text-transform:uppercase;letter-spacing:0.06em;">Sample count</div>
<div style="font-family:var(--mono);font-size:14px;color:var(--ink);margin-top:4px;">256</div>
<div style="font-size:11.5px;color:var(--ink-3);margin-top:2px;">Proof::N_SAMPLES</div>
</div>
<div class="card" style="margin:0;">
<div style="font-size:10px;color:var(--ink-3);text-transform:uppercase;letter-spacing:0.06em;">Status</div>
<div style="font-family:var(--mono);font-size:14px;margin-top:4px;color:${status === 'ok' ? 'var(--ok)' : status === 'fail' ? 'var(--bad)' : 'var(--ink-3)'};">
${status === 'ok' ? '✓ matches' : status === 'fail' ? '✗ drift' : status === 'pending' ? '… running' : '— idle'}
</div>
<div style="font-size:11.5px;color:var(--ink-3);margin-top:2px;">${match ? 'byte-equivalent' : 'not yet verified'}</div>
</div>
</div>
` : ''}
<div class="card">
<div class="card-h">
<span class="ttl">Expected (Proof::EXPECTED_WITNESS_HEX)</span>
<span class="badge">SHA-256</span>
</div>
<div class="witness-box" id="expected-witness">${expectedWitness.value || '(loading…)'}</div>
</div>
<div class="card">
<div class="card-h">
<span class="ttl">Actual (last verify)</span>
<span class="badge">SHA-256</span>
</div>
<div class="witness-box" id="actual-witness">${witnessHex.value || '(not verified yet)'}</div>
<button class="verify-btn ${cls}" id="verify-btn" @click=${this.verify}>${label}</button>
</div>
${this.expanded ? html`
<div class="card">
<div class="card-h">
<span class="ttl">What this verifies</span>
<span class="badge">ADR-089 §5</span>
</div>
<div style="font-size: 12.5px; color: var(--ink-2); line-height: 1.6;">
<p style="margin: 0 0 10px;">Pressing <b>Verify</b> runs the canonical reference pipeline
(<code>Proof::generate</code>) end-to-end inside this browser's WASM Worker:
scene → Biot-Savart synthesis → material attenuation → NV ensemble → ADC + lock-in →
concatenated <code>MagFrame</code> bytes → SHA-256.</p>
<p style="margin: 0 0 10px;">If the resulting hash matches the constant pinned at build time
(<code>cc8de9b01b0ff5bd…</code>), every constant — γ_e, D_GS, μ₀, T₂*, contrast, the PRNG
stream, the frame layout, the pipeline ordering — is byte-identical to the published
reference. If it doesn't match, <i>something</i> drifted; the dashboard names which.</p>
<p style="margin: 0;">This is the same regression test that runs in
<code>cargo test -p nvsim</code> — running in your browser, against your own WASM build.</p>
</div>
</div>
` : ''}
`;
}
override render() {
return html`
<div class="tabs" role="tablist">
<button class="tab ${this.tab === 'signal' ? 'active' : ''}" data-pane="signal"
role="tab" aria-selected=${this.tab === 'signal'}
@click=${() => this.tab = 'signal'}>Signal</button>
<button class="tab ${this.tab === 'frame' ? 'active' : ''}" data-pane="frame"
role="tab" aria-selected=${this.tab === 'frame'}
@click=${() => this.tab = 'frame'}>Frame</button>
<button class="tab ${this.tab === 'witness' ? 'active' : ''}" data-pane="witness"
role="tab" aria-selected=${this.tab === 'witness'}
@click=${() => this.tab = 'witness'}>Witness</button>
</div>
<div class="body" role="tabpanel">
${this.renderHeader()}
${this.tab === 'signal' ? this.renderSignalTab()
: this.tab === 'frame' ? this.renderFrameTab()
: this.renderWitnessTab()}
</div>
`;
}
}
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@@ -1,153 +0,0 @@
/* Modal dialog — opened via window.dispatchEvent('nv-modal', { title, body, buttons }). */
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
interface ModalButton {
label: string;
variant?: 'ghost' | 'primary' | 'danger';
onClick?: () => void;
}
interface ModalReq {
title: string;
body: string;
buttons?: ModalButton[];
}
@customElement('nv-modal')
export class NvModal extends LitElement {
@state() private open = false;
@state() private mTitle = '';
@state() private mBody = '';
@state() private buttons: ModalButton[] = [];
static styles = css`
:host {
position: fixed; inset: 0;
background: rgba(0,0,0,0.55);
backdrop-filter: blur(4px);
z-index: 200;
display: grid; place-items: center;
opacity: 0; pointer-events: none;
transition: opacity 0.18s;
}
:host([open]) { opacity: 1; pointer-events: auto; }
.modal {
background: var(--bg-1);
border: 1px solid var(--line-2);
border-radius: var(--radius);
box-shadow: 0 30px 80px -20px rgba(0,0,0,0.7);
width: min(520px, 92vw);
max-height: 86vh;
display: flex; flex-direction: column;
transform: translateY(12px) scale(0.98);
transition: transform 0.22s cubic-bezier(0.2,0.7,0.3,1);
}
:host([open]) .modal { transform: translateY(0) scale(1); }
.h {
padding: 14px 16px;
border-bottom: 1px solid var(--line);
display: flex; align-items: center; justify-content: space-between;
}
.h .ttl { font-size: 14px; font-weight: 600; }
.body { padding: 16px; overflow-y: auto; font-size: 13px; color: var(--ink-2); line-height: 1.55; }
.f {
padding: 12px 16px;
border-top: 1px solid var(--line);
display: flex; gap: 8px; justify-content: flex-end;
}
button {
padding: 6px 12px;
border-radius: 8px;
font-size: 12.5px;
cursor: pointer;
font-family: inherit;
border: 1px solid var(--line);
background: var(--bg-2); color: var(--ink);
}
button.ghost { background: transparent; }
button.primary { background: var(--accent); border-color: var(--accent); color: #1a0f00; }
button.danger { background: var(--bad); border-color: var(--bad); color: #fff; }
.close {
width: 28px; height: 28px;
background: transparent; border: 1px solid var(--line);
border-radius: 6px;
color: var(--ink-2);
}
`;
override connectedCallback(): void {
super.connectedCallback();
window.addEventListener('nv-modal', this.onModal as EventListener);
window.addEventListener('keydown', this.onKey);
}
override disconnectedCallback(): void {
super.disconnectedCallback();
window.removeEventListener('nv-modal', this.onModal as EventListener);
window.removeEventListener('keydown', this.onKey);
}
private onModal = (e: Event): void => {
const r = (e as CustomEvent).detail as ModalReq;
this.mTitle = r.title; this.mBody = r.body;
this.buttons = r.buttons ?? [{ label: 'Close', variant: 'primary' }];
this.open = true; this.setAttribute('open', '');
// a11y: focus the first interactive element inside the modal so keyboard
// users land in the dialog rather than behind it. Light focus trap via
// the keydown handler below catches Tab cycling.
requestAnimationFrame(() => {
const root = this.shadowRoot;
if (!root) return;
const first = root.querySelector<HTMLElement>('input, select, textarea, button:not(.close)');
first?.focus();
});
};
override updated(): void {
if (!this.open) return;
const root = this.shadowRoot;
if (!root) return;
// Trap Tab inside the modal while open.
const trap = (e: KeyboardEvent): void => {
if (e.key !== 'Tab') return;
const focusables = Array.from(
root.querySelectorAll<HTMLElement>('input, select, textarea, button, [href]'),
).filter((el) => !el.hasAttribute('disabled'));
if (focusables.length === 0) return;
const first = focusables[0];
const last = focusables[focusables.length - 1];
const active = (root.activeElement as HTMLElement | null) ?? null;
if (e.shiftKey && active === first) { e.preventDefault(); last.focus(); }
else if (!e.shiftKey && active === last) { e.preventDefault(); first.focus(); }
};
root.removeEventListener('keydown', trap as EventListener);
root.addEventListener('keydown', trap as EventListener);
}
private onKey = (e: KeyboardEvent): void => {
if (e.key === 'Escape' && this.open) this.close();
};
private close(): void { this.open = false; this.removeAttribute('open'); }
private clickBtn(b: ModalButton): void { b.onClick?.(); this.close(); }
override render() {
return html`
<div class="modal" role="dialog" aria-modal="true">
<div class="h">
<div class="ttl">${this.mTitle}</div>
<button class="close" @click=${() => this.close()}>×</button>
</div>
<div class="body" .innerHTML=${this.mBody}></div>
<div class="f">
${this.buttons.map((b) => html`
<button class=${b.variant ?? ''} @click=${() => this.clickBtn(b)}>${b.label}</button>
`)}
</div>
</div>
`;
}
}
export function openModal(req: ModalReq): void {
window.dispatchEvent(new CustomEvent('nv-modal', { detail: req }));
}
-397
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@@ -1,397 +0,0 @@
/* Welcome modal + step-by-step introduction tour.
*
* 10 steps walking the user through every panel of the dashboard with
* concrete CTAs ("Try it now") that fire real navigation against the
* live UI. First-run only by default; replayable via Settings → Help.
*/
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
import { kvGet, kvSet } from '../store/persistence';
interface TourStep {
/** Optional icon shown at the top of the step. */
icon: string;
title: string;
/** Markdown-ish HTML body (rendered via .innerHTML). */
body: string;
/** Optional CTA: clicking runs the action then advances. */
cta?: { label: string; run?: () => void };
/** Optional "do this yourself" hint. */
hint?: string;
}
const STEPS: TourStep[] = [
{
icon: '👋',
title: 'Welcome to nvsim',
body: `<p style="font-size:14px; line-height:1.6;">
<b>nvsim</b> is an open-source, deterministic forward simulator for
<b>nitrogen-vacancy diamond magnetometry</b> — a real Rust crate compiled
to WebAssembly and running in your browser, right now.</p>
<p style="font-size:13px; color:var(--ink-2); line-height:1.55;">
This 60-second tour walks you through the four panels, the App Store,
the Ghost Murmur research view, and the determinism contract that
makes nvsim distinctive.</p>
<p style="font-size:11.5px; color:var(--ink-3); line-height:1.5; margin-top:14px;">
Press <kbd>Esc</kbd> any time to skip. You can replay this tour from
<b>Settings → Help</b>.</p>`,
cta: { label: 'Start the tour →' },
},
{
icon: '🌐',
title: 'The Scene canvas',
body: `<p>The middle panel shows your <b>magnetic scene</b> — a small simulated
environment with four sources and one NV-diamond sensor at the centre.</p>
<p>The four amber/cyan/magenta blobs are draggable: <b>rebar coil</b>
(steel χ=5000), <b>heart proxy</b> dipole, <b>60 Hz mains</b> current loop,
and a <b>steel door</b> (eddy current). Field lines connect each source
to the sensor and animate while the pipeline runs.</p>
<p style="font-size:12.5px; color:var(--ink-3);">
Top-left toolbar: zoom in/out, fit-to-view, layer toggles. Bottom-right:
sim controls (step / play / step / speed cycle). Drag positions persist
across reloads.</p>`,
hint: 'Try dragging the heart_proxy after the tour ends.',
},
{
icon: '▶',
title: 'Run the pipeline',
body: `<p>Press <b>▶ Run</b> in the topbar (or hit <kbd>Space</kbd>) to start
the live frame stream. nvsim runs at ~1.8 kHz on x86_64 WASM —
well above the 1 kHz Cortex-A53 acceptance gate.</p>
<p>The FPS pill in the topbar updates with the throughput. The B-vector
trace and frame-stream sparkline in the right inspector update in real
time.</p>
<p style="font-size:12.5px; color:var(--ink-3);">
<kbd>Space</kbd> toggles run/pause from anywhere. Reset (<kbd>⌘R</kbd>)
rewinds <code>t</code> to 0 without changing the seed.</p>`,
},
{
icon: '🔍',
title: 'Inspector — three tabs, three depths',
body: `<p>The right rail shows the live inspector: <b>Signal</b> (B-vector
trace + frame-stream sparkline), <b>Frame</b> (decoded MagFrame fields +
raw 60-byte hex dump), <b>Witness</b> (SHA-256 determinism gate).</p>
<p>Click the <b>magnifier</b> icon in the left rail to expand the
inspector to the full main area, with bigger charts and an explainer
header. Click the <b>shield</b> icon to do the same focused on Witness.</p>
<p style="font-size:12.5px; color:var(--ink-3);">
Number keys <kbd>1</kbd> <kbd>2</kbd> <kbd>3</kbd> jump between the
three inspector tabs from anywhere.</p>`,
},
{
icon: '✓',
title: 'The witness — what makes nvsim distinctive',
body: `<p>nvsim's defining commitment: same <code>(scene, config, seed)</code> →
byte-identical SHA-256 across runs, machines, and transports.</p>
<p>Click the <b>Witness</b> tab and press <b>Verify witness</b>. The
dashboard re-derives the hash for the canonical reference scene
(<code>seed=42, N=256</code>) and asserts it matches the constant
pinned at compile time
(<code style="font-size:10.5px;">cc8de9b01b0ff5bd…</code>).</p>
<p>A green check means every constant — γ_e, D_GS, μ₀, T₂*, contrast,
the PRNG stream, the frame layout — is byte-identical to the published
reference. A red ✗ means something drifted; the dashboard names which.</p>`,
},
{
icon: '🎚',
title: 'Tunables — change the simulation live',
body: `<p>The left sidebar's <b>Tunables</b> panel has four sliders:</p>
<ul style="margin:0 0 12px; padding-left:18px; font-size:13px; color:var(--ink-2); line-height:1.6;">
<li><b>Sample rate</b> (1100 kHz) — digitiser frame rate</li>
<li><b>Lock-in f_mod</b> (0.15 kHz) — microwave modulation freq</li>
<li><b>Integration t</b> (0.110 ms) — per-sample integration time</li>
<li><b>Shot noise</b> (on/off) — toggle quantum noise</li>
</ul>
<p>Edits debounce 300 ms then rebuild the WASM pipeline without restarting
the frame stream. Watch the noise floor and B-vector spread change
in the Signal trace.</p>`,
},
{
icon: '👻',
title: 'Ghost Murmur — research view',
body: `<p>Click the ghost icon in the left rail. This view audits the
publicly-reported <b>April 2026 CIA Ghost Murmur</b> NV-diamond
heartbeat-detection program against the open physics literature.</p>
<p>Includes a <b>"Try it yourself"</b> sandbox: place a cardiac dipole at
any distance from the sensor, hit Run, and see what the real nvsim
pipeline recovers. Per-tier detectability bars compare the predicted
signal vs each transport's noise floor (NV-ensemble lab, COTS DNV-B1,
SQUID, 60 GHz mmWave, WiFi CSI).</p>
<p style="font-size:12.5px; color:var(--ink-3);">
Spoiler: at 1 km the cardiac MCG is ~10⁻¹² of its 10 cm value.
Press claims of 40-mile detection sit far below any published instrument's
floor.</p>`,
},
{
icon: '🛍',
title: 'App Store — 65 edge apps',
body: `<p>Click the grid icon. The <b>App Store</b> catalogues every
hot-loadable WASM edge module RuView ships, organised by category:
medical, security, smart-building, retail, industrial, signal,
learning, autonomy, exotic.</p>
<p>Each card carries id / category / status / event IDs / compute budget /
ADR back-reference. The toggle marks an app active in this session;
the WS transport (when configured) pushes the activation set to a
connected ESP32 mesh.</p>
<p style="font-size:12.5px; color:var(--ink-3);">
Try searching for "ghost", "heart", or "occupancy" to fuzzy-filter
the catalogue.</p>`,
},
{
icon: '⌨',
title: 'Console + REPL',
body: `<p>The bottom panel is a structured event log with five filter tabs
(<b>all / info / warn / err / dbg</b>) plus a REPL prompt.</p>
<p>REPL commands include
<code>help</code>, <code>scene.list</code>, <code>sensor.config</code>,
<code>run</code>, <code>pause</code>, <code>seed [hex]</code>,
<code>proof.verify</code>, <code>proof.export</code>,
<code>theme [light|dark]</code>, <code>status</code>, <code>clear</code>.</p>
<p style="font-size:12.5px; color:var(--ink-3);">
Press <kbd>/</kbd> to focus the REPL from anywhere. Arrow ↑/↓ recall
history (persisted across reloads). <kbd>⌘K</kbd> opens the command
palette with every action discoverable.</p>`,
},
{
icon: '🚀',
title: 'You are ready',
body: `<p style="font-size:14px;">That's the whole tour. A few last pointers:</p>
<ul style="margin:0 0 14px; padding-left:18px; font-size:13px; color:var(--ink-2); line-height:1.7;">
<li>Press <kbd>?</kbd> any time to open the help center
(Quickstart / Glossary / FAQ / Shortcuts / About).</li>
<li>Press <kbd>⌘K</kbd> for the command palette.</li>
<li>Press <kbd>\`</kbd> to toggle the debug HUD.</li>
<li>Settings (<kbd>⌘,</kbd>) lets you switch theme, density, motion,
transport, and replay this tour.</li>
</ul>
<p style="font-size:12.5px; color:var(--ink-3); line-height:1.55;">
Source: <code>github.com/ruvnet/RuView</code> · Apache-2.0 OR MIT ·
ADRs 089/090/091/092/093.</p>`,
cta: { label: 'Get started →' },
},
];
@customElement('nv-onboarding')
export class NvOnboarding extends LitElement {
@state() private open = false;
@state() private step = 0;
static styles = css`
:host {
position: fixed; inset: 0;
background: rgba(0, 0, 0, 0.55);
backdrop-filter: blur(4px);
z-index: 240;
display: grid; place-items: center;
opacity: 0; pointer-events: none;
transition: opacity 0.18s;
}
:host([open]) { opacity: 1; pointer-events: auto; }
.card {
background: var(--bg-1);
border: 1px solid var(--line-2);
border-radius: var(--radius);
box-shadow: 0 30px 80px -20px rgba(0,0,0,0.7);
width: min(640px, 94vw);
max-height: 86vh;
display: flex; flex-direction: column;
transform: translateY(12px) scale(0.98);
transition: transform 0.22s cubic-bezier(0.2,0.7,0.3,1);
overflow: hidden;
}
:host([open]) .card { transform: translateY(0) scale(1); }
.h {
padding: 22px 26px 12px;
display: flex; align-items: flex-start; gap: 14px;
}
.h .icon {
width: 44px; height: 44px;
border-radius: 12px;
background: linear-gradient(135deg, oklch(0.78 0.14 70) 0%, oklch(0.55 0.16 30) 100%);
display: grid; place-items: center;
font-size: 22px;
flex-shrink: 0;
box-shadow: 0 4px 12px -2px oklch(0.55 0.16 30 / 0.35);
}
.h .title-wrap { flex: 1; min-width: 0; }
.h h2 {
margin: 0;
font-size: 18px;
letter-spacing: -0.01em;
color: var(--ink);
}
.h .step-label {
font-family: var(--mono);
font-size: 10.5px;
color: var(--ink-3);
margin-top: 4px;
text-transform: uppercase;
letter-spacing: 0.06em;
}
.h .skip {
width: 28px; height: 28px;
background: transparent;
border: 1px solid var(--line);
border-radius: 6px;
color: var(--ink-2);
cursor: pointer;
flex-shrink: 0;
}
.h .skip:hover { color: var(--ink); border-color: var(--line-2); }
.body {
padding: 0 26px 16px;
font-size: 13px;
color: var(--ink-2);
line-height: 1.6;
overflow-y: auto;
flex: 1;
}
.body p { margin: 0 0 12px; }
.body p:last-child { margin-bottom: 0; }
.body code, .body kbd {
font-family: var(--mono);
font-size: 11.5px;
padding: 1px 5px;
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: 4px;
}
.body code { color: var(--accent); }
.body kbd { color: var(--ink); }
.hint {
margin: 14px 0 0;
padding: 10px 12px;
background: oklch(0.78 0.12 195 / 0.06);
border: 1px solid oklch(0.78 0.12 195 / 0.25);
border-radius: 8px;
font-size: 12px;
color: var(--accent-2);
display: flex; gap: 8px; align-items: flex-start;
}
.hint::before {
content: '💡';
flex-shrink: 0;
}
.footer {
display: flex; align-items: center; gap: 14px;
padding: 14px 22px;
border-top: 1px solid var(--line);
background: var(--bg-1);
}
.progress { flex: 1; }
.dots { display: flex; gap: 5px; margin-bottom: 4px; }
.dot {
width: 6px; height: 6px; border-radius: 50%;
background: var(--bg-3);
border: 1px solid var(--line-2);
transition: background 0.15s, border-color 0.15s, transform 0.15s;
}
.dot.active {
background: var(--accent);
border-color: var(--accent);
transform: scale(1.2);
}
.dot.done {
background: var(--accent-4);
border-color: var(--accent-4);
}
.progress-label {
font-family: var(--mono);
font-size: 10px;
color: var(--ink-3);
}
button.primary, button.ghost {
padding: 9px 16px;
border-radius: 8px;
font-size: 13px;
font-weight: 500;
cursor: pointer;
font-family: inherit;
border: 1px solid var(--line);
background: var(--bg-2);
color: var(--ink);
}
button.ghost:hover { border-color: var(--line-2); }
button.primary {
background: var(--accent);
border-color: var(--accent);
color: #1a0f00;
}
button.primary:hover { filter: brightness(1.08); }
`;
override async connectedCallback(): Promise<void> {
super.connectedCallback();
window.addEventListener('nv-show-tour', this.show as EventListener);
const seen = await kvGet<boolean>('onboarding-seen');
if (!seen) {
this.open = true;
this.setAttribute('open', '');
}
}
override disconnectedCallback(): void {
super.disconnectedCallback();
window.removeEventListener('nv-show-tour', this.show as EventListener);
}
private show = (): void => {
this.step = 0;
this.open = true;
this.setAttribute('open', '');
};
private async dismiss(): Promise<void> {
this.open = false;
this.removeAttribute('open');
await kvSet('onboarding-seen', true);
}
private next(): void {
const s = STEPS[this.step];
s.cta?.run?.();
if (this.step < STEPS.length - 1) this.step++;
else void this.dismiss();
}
private prev(): void {
if (this.step > 0) this.step--;
}
override render() {
const s = STEPS[this.step];
const isLast = this.step === STEPS.length - 1;
return html`
<div class="card" role="dialog" aria-modal="true" aria-label="Welcome tour">
<div class="h">
<div class="icon" aria-hidden="true">${s.icon}</div>
<div class="title-wrap">
<h2>${s.title}</h2>
<div class="step-label">Step ${this.step + 1} of ${STEPS.length}</div>
</div>
<button class="skip" @click=${() => this.dismiss()} aria-label="Skip tour" title="Skip tour">×</button>
</div>
<div class="body">
<div .innerHTML=${s.body}></div>
${s.hint ? html`<div class="hint">${s.hint}</div>` : ''}
</div>
<div class="footer">
<div class="progress">
<div class="dots">
${STEPS.map((_, i) => html`
<div class="dot ${i === this.step ? 'active' : i < this.step ? 'done' : ''}"></div>
`)}
</div>
<div class="progress-label">${this.step + 1} / ${STEPS.length}</div>
</div>
${this.step > 0
? html`<button class="ghost" @click=${() => this.prev()}>← Back</button>`
: html`<button class="ghost" @click=${() => this.dismiss()}>Skip</button>`}
<button class="primary" @click=${() => this.next()}>
${s.cta?.label ?? (isLast ? 'Done' : 'Next →')}
</button>
</div>
</div>
`;
}
}
-244
View File
@@ -1,244 +0,0 @@
/* Command palette ⌘K. */
import { LitElement, html, css } from 'lit';
import { customElement, state, query } from 'lit/decorators.js';
import { toast } from './nv-toast';
import { openModal } from './nv-modal';
import {
getClient, theme, expectedWitness, witnessHex, witnessVerified, pushLog, running,
} from '../store/appStore';
interface Cmd { ico: string; label: string; kbd?: string; run: () => void; }
@customElement('nv-palette')
export class NvPalette extends LitElement {
@state() private open = false;
@state() private filter = '';
@state() private idx = 0;
@query('#palette-input') private inputEl!: HTMLInputElement;
static styles = css`
:host {
position: fixed; inset: 0; z-index: 220;
background: rgba(0,0,0,0.5);
opacity: 0; pointer-events: none;
transition: opacity 0.15s;
display: flex; justify-content: center; padding-top: 12vh;
backdrop-filter: blur(4px);
}
:host([open]) { opacity: 1; pointer-events: auto; }
.palette {
width: min(560px, 92vw);
background: var(--bg-1);
border: 1px solid var(--line-2);
border-radius: var(--radius);
box-shadow: 0 30px 80px -20px rgba(0,0,0,0.7);
overflow: hidden;
display: flex; flex-direction: column;
max-height: 60vh;
}
.input {
padding: 14px 16px;
border-bottom: 1px solid var(--line);
}
input {
width: 100%;
background: transparent; border: none; outline: none;
color: var(--ink); font-size: 14px;
font-family: inherit;
}
.list { flex: 1; overflow-y: auto; padding: 4px; }
.item {
display: flex; align-items: center; gap: 10px;
padding: 8px 12px;
border-radius: 6px;
cursor: pointer;
font-size: 12.5px;
}
.item.active { background: var(--bg-3); }
.item .ico { width: 20px; text-align: center; color: var(--accent); }
.item .lbl { flex: 1; }
.item .kbd {
font-family: var(--mono); font-size: 10.5px;
color: var(--ink-3);
padding: 1px 5px; background: var(--bg-3); border-radius: 4px;
}
`;
private cmds: Cmd[] = [
{ ico: '▶', label: 'Run pipeline', kbd: 'Space', run: async () => { await getClient()?.run(); running.value = true; toast('Pipeline running', '▶'); } },
{ ico: '❚', label: 'Pause pipeline', run: async () => { await getClient()?.pause(); running.value = false; toast('Paused', '❚❚'); } },
{ ico: '+', label: 'New scene…', kbd: '⌘N', run: () => openModal({
title: 'New scene',
body: `<p>Build a fresh magnetic scene. The dashboard generates the JSON
and pushes it to the running pipeline (or you can copy the JSON
for offline use).</p>
<label>Name</label>
<input type="text" id="ns-name" value="custom-scene-${Date.now().toString(36)}" />
<label>Heart-proxy dipole moment (A·m²)</label>
<input type="text" id="ns-moment" value="1.0e-6" />
<label>Distance heart → sensor (m)</label>
<input type="text" id="ns-distance" value="0.5" />
<label>Add ferrous distractor at +x = 1 m?</label>
<select id="ns-ferrous">
<option value="0">No</option>
<option value="1" selected>Yes (steel coil, χ=5000)</option>
</select>
<label>Add 60 Hz mains-current loop?</label>
<select id="ns-mains">
<option value="0">No</option>
<option value="1" selected>Yes (2 A loop, 5 cm radius, +y = 1 m)</option>
</select>`,
buttons: [
{ label: 'Cancel', variant: 'ghost' },
{ label: 'Create', variant: 'primary', onClick: async () => {
const root = document.querySelector('nv-app')?.shadowRoot?.querySelector('nv-modal')?.shadowRoot;
if (!root) return;
const name = (root.querySelector<HTMLInputElement>('#ns-name')?.value ?? 'custom').trim();
const m = parseFloat(root.querySelector<HTMLInputElement>('#ns-moment')?.value ?? '1e-6');
const d = parseFloat(root.querySelector<HTMLInputElement>('#ns-distance')?.value ?? '0.5');
const ferr = root.querySelector<HTMLSelectElement>('#ns-ferrous')?.value === '1';
const mains = root.querySelector<HTMLSelectElement>('#ns-mains')?.value === '1';
const scene = {
dipoles: [{ position: [0, 0, d] as [number, number, number], moment: [0, 0, m] as [number, number, number] }],
loops: mains ? [{
centre: [0, 1, 0] as [number, number, number],
normal: [0, 1, 0] as [number, number, number],
radius: 0.05, current: 2.0, n_segments: 64,
}] : [],
ferrous: ferr ? [{ position: [1, 0, 0] as [number, number, number], volume: 1e-4, susceptibility: 5000 }] : [],
eddy: [],
sensors: [[0, 0, 0] as [number, number, number]],
ambient_field: [1e-6, 0, 0] as [number, number, number],
};
await getClient()?.loadScene(scene);
pushLog('ok', `scene <span class="s">${name}</span> loaded · 1 dipole · ${mains ? '1 loop · ' : ''}${ferr ? '1 ferrous · ' : ''}1 sensor`);
toast(`Scene "${name}" loaded`, '+');
} },
],
}) },
{ ico: '📦', label: 'Export proof bundle…', kbd: '⌘E', run: async () => {
const c = getClient(); if (!c) return;
pushLog('dbg', 'building proof bundle…');
try {
const blob = await c.exportProofBundle();
const url = URL.createObjectURL(blob);
const a = document.createElement('a');
a.href = url;
a.download = `nvsim-proof-${Date.now()}.json`;
a.click();
URL.revokeObjectURL(url);
pushLog('ok', `proof bundle exported · ${blob.size} bytes`);
toast(`Proof bundle saved (${blob.size} B)`, '📦');
} catch (e) { pushLog('err', `export failed: ${(e as Error).message}`); }
} },
{ ico: '⟳', label: 'Reset pipeline', kbd: '⌘R', run: () => openModal({
title: 'Reset pipeline?',
body: '<p>Clears the frame stream and rewinds <code>t</code> to 0.</p>',
buttons: [
{ label: 'Cancel', variant: 'ghost' },
{ label: 'Reset', variant: 'danger', onClick: async () => { await getClient()?.reset(); pushLog('warn', 'pipeline reset · t=0'); toast('Pipeline reset', '⟳'); } },
],
}) },
{ ico: '✓', label: 'Verify witness', run: async () => {
const c = getClient(); if (!c) return;
witnessVerified.value = 'pending';
const exp = expectedWitness.value;
const eb = new Uint8Array(32);
for (let i = 0; i < 32; i++) eb[i] = parseInt(exp.slice(i * 2, i * 2 + 2), 16);
const r = await c.verifyWitness(eb);
if (r.ok) { witnessVerified.value = 'ok'; witnessHex.value = exp; toast('Witness verified', '✓'); }
else { witnessVerified.value = 'fail'; toast('Witness mismatch!', '✗'); }
} },
{ ico: '☼', label: 'Toggle theme', kbd: '⌘/', run: () => { theme.value = theme.value === 'dark' ? 'light' : 'dark'; } },
{ ico: '⚙', label: 'Open settings', kbd: '⌘,', run: () => window.dispatchEvent(new CustomEvent('open-settings')) },
{ ico: '?', label: 'Keyboard shortcuts…', run: () => openModal({
title: 'Keyboard shortcuts',
body: `<div style="display:grid;grid-template-columns:auto 1fr;gap:6px 16px;font-size:13px;">
<div><code>⌘K / Ctrl K</code></div><div>Command palette</div>
<div><code>Space</code></div><div>Play / pause</div>
<div><code>⌘R</code></div><div>Reset</div>
<div><code>⌘,</code></div><div>Settings</div>
<div><code>⌘/</code></div><div>Toggle theme</div>
<div><code>\`</code></div><div>Debug HUD</div>
<div><code>1 · 2 · 3</code></div><div>Inspector tabs</div>
<div><code>Esc</code></div><div>Close modal/palette</div>
<div><code>/</code></div><div>Focus REPL</div>
</div>`,
buttons: [{ label: 'Close', variant: 'primary' }],
}) },
{ ico: 'i', label: 'About nvsim…', run: () => openModal({
title: 'About nvsim',
body: `<p><b>nvsim</b> is a deterministic, byte-reproducible forward simulator for nitrogen-vacancy diamond magnetometry.</p>
<p>This dashboard runs nvsim as WASM in a Web Worker. Same <code>(scene, config, seed)</code> → byte-identical SHA-256 witness across runs and machines.</p>
<p>License: MIT OR Apache-2.0 · See ADR-089, ADR-092.</p>`,
buttons: [{ label: 'Close', variant: 'primary' }],
}) },
];
override connectedCallback(): void {
super.connectedCallback();
window.addEventListener('keydown', this.onKey);
window.addEventListener('nv-palette', this.onOpen as EventListener);
}
override disconnectedCallback(): void {
super.disconnectedCallback();
window.removeEventListener('keydown', this.onKey);
window.removeEventListener('nv-palette', this.onOpen as EventListener);
}
private onKey = (e: KeyboardEvent): void => {
if ((e.metaKey || e.ctrlKey) && e.key.toLowerCase() === 'k') {
e.preventDefault();
this.openPal();
} else if (e.key === 'Escape' && this.open) {
this.closePal();
} else if (this.open) {
if (e.key === 'ArrowDown') { this.idx = Math.min(this.cmds.length - 1, this.idx + 1); e.preventDefault(); }
else if (e.key === 'ArrowUp') { this.idx = Math.max(0, this.idx - 1); e.preventDefault(); }
else if (e.key === 'Enter') { this.runIdx(); e.preventDefault(); }
}
};
private onOpen = (): void => this.openPal();
private openPal(): void {
this.open = true; this.setAttribute('open', '');
this.filter = ''; this.idx = 0;
setTimeout(() => this.inputEl?.focus(), 0);
}
private closePal(): void { this.open = false; this.removeAttribute('open'); }
private filtered(): Cmd[] {
if (!this.filter.trim()) return this.cmds;
const q = this.filter.toLowerCase();
return this.cmds.filter((c) => c.label.toLowerCase().includes(q));
}
private runIdx(): void {
const f = this.filtered();
const c = f[this.idx];
if (c) { c.run(); this.closePal(); }
}
override render() {
const items = this.filtered();
return html`
<div class="palette" data-id="palette">
<div class="input">
<input id="palette-input" type="text" placeholder="Type a command…"
.value=${this.filter}
@input=${(e: Event) => { this.filter = (e.target as HTMLInputElement).value; this.idx = 0; }} />
</div>
<div class="list">
${items.map((c, i) => html`
<div class="item ${i === this.idx ? 'active' : ''}" @click=${() => { this.idx = i; this.runIdx(); }}>
<span class="ico">${c.ico}</span>
<span class="lbl">${c.label}</span>
${c.kbd ? html`<span class="kbd">${c.kbd}</span>` : ''}
</div>
`)}
</div>
</div>
`;
}
}
-116
View File
@@ -1,116 +0,0 @@
/* Left rail navigation. Emits `navigate` events for view switching. */
import { LitElement, html, css } from 'lit';
import { customElement, property } from 'lit/decorators.js';
import type { View } from './nv-app';
@customElement('nv-rail')
export class NvRail extends LitElement {
@property() view: View = 'scene';
static styles = css`
:host {
display: flex;
flex-direction: column;
align-items: center;
padding: 10px 0;
gap: 4px;
background: var(--bg-1);
border-right: 1px solid var(--line);
}
.logo {
width: 36px; height: 36px;
border-radius: 10px;
background: linear-gradient(135deg, oklch(0.78 0.14 70) 0%, oklch(0.55 0.16 30) 100%);
display: grid; place-items: center;
color: #1a0f00;
font-weight: 700;
font-family: var(--mono);
font-size: 11px;
margin-bottom: 14px;
box-shadow: 0 4px 12px -2px oklch(0.55 0.16 30 / 0.35);
}
.btn {
width: 36px; height: 36px;
border-radius: 8px;
background: transparent;
border: 1px solid transparent;
color: var(--ink-3);
display: grid; place-items: center;
transition: all 0.15s;
position: relative;
cursor: pointer;
}
.btn:hover { color: var(--ink); background: var(--bg-2); }
.btn.active {
color: var(--ink);
background: var(--bg-3);
border-color: var(--line-2);
}
.btn.active::before {
content: ''; position: absolute; left: -10px; top: 8px; bottom: 8px;
width: 2px; background: var(--accent); border-radius: 2px;
}
.btn.ghost.active::before { background: var(--accent-3); }
.spacer { flex: 1; }
svg { width: 18px; height: 18px; fill: none; stroke: currentColor; stroke-width: 1.8; }
`;
private navigate(v: View): void {
this.dispatchEvent(new CustomEvent('navigate', { detail: v }));
}
override render() {
return html`
<div class="logo" aria-hidden="true">NV</div>
<nav role="navigation" aria-label="Primary"
style="display:flex; flex-direction:column; align-items:center; gap:4px; flex:1;">
<button class="btn ${this.view === 'home' ? 'active' : ''}"
data-id="home-btn" title="Home" aria-label="Home"
aria-current=${this.view === 'home' ? 'page' : 'false'}
@click=${() => this.navigate('home')}>
<svg viewBox="0 0 24 24" aria-hidden="true"><path d="M3 12L12 4l9 8M5 10v10h14V10"/></svg>
</button>
<button class="btn ${this.view === 'scene' ? 'active' : ''}"
data-id="scene-btn" title="Scene" aria-label="Scene"
aria-current=${this.view === 'scene' ? 'page' : 'false'}
@click=${() => this.navigate('scene')}>
<svg viewBox="0 0 24 24" aria-hidden="true"><path d="M12 2L3 7l9 5 9-5-9-5zm0 13l-9-5v6l9 5 9-5v-6l-9 5z"/></svg>
</button>
<button class="btn ${this.view === 'apps' ? 'active' : ''}"
data-id="apps-btn" title="App Store" aria-label="App Store"
aria-current=${this.view === 'apps' ? 'page' : 'false'}
@click=${() => this.navigate('apps')}>
<svg viewBox="0 0 24 24" aria-hidden="true"><rect x="3" y="3" width="7" height="7" rx="1"/><rect x="14" y="3" width="7" height="7" rx="1"/><rect x="3" y="14" width="7" height="7" rx="1"/><rect x="14" y="14" width="7" height="7" rx="1"/></svg>
</button>
<button class="btn ${this.view === 'inspector' ? 'active' : ''}"
data-id="inspector-btn" title="Inspector" aria-label="Inspector"
aria-current=${this.view === 'inspector' ? 'page' : 'false'}
@click=${() => this.navigate('inspector')}>
<svg viewBox="0 0 24 24" aria-hidden="true"><circle cx="11" cy="11" r="7"/><line x1="21" y1="21" x2="16.6" y2="16.6"/></svg>
</button>
<button class="btn ${this.view === 'witness' ? 'active' : ''}"
data-id="witness-btn" title="Witness" aria-label="Witness"
aria-current=${this.view === 'witness' ? 'page' : 'false'}
@click=${() => this.navigate('witness')}>
<svg viewBox="0 0 24 24" aria-hidden="true"><path d="M9 12l2 2 4-4M21 12c0 4.97-4.03 9-9 9s-9-4.03-9-9 4.03-9 9-9 9 4.03 9 9z"/></svg>
</button>
<button class="btn ghost ${this.view === 'ghost-murmur' ? 'active' : ''}"
data-id="ghost-murmur-btn" title="Ghost Murmur — research spec"
aria-label="Ghost Murmur research"
aria-current=${this.view === 'ghost-murmur' ? 'page' : 'false'}
@click=${() => this.navigate('ghost-murmur')}>
<svg viewBox="0 0 24 24" aria-hidden="true">
<path d="M9 2C5.7 2 3 4.7 3 8v12l3-2 3 2 3-2 3 2 3-2 3 2V8c0-3.3-2.7-6-6-6H9z"/>
<circle cx="9" cy="10" r="1.2" fill="currentColor"/>
<circle cx="15" cy="10" r="1.2" fill="currentColor"/>
</svg>
</button>
</nav>
<div class="spacer"></div>
<button class="btn" data-id="settings-btn" title="Settings" aria-label="Settings"
@click=${() => this.dispatchEvent(new CustomEvent('open-settings', { bubbles: true, composed: true }))}>
<svg viewBox="0 0 24 24" aria-hidden="true"><circle cx="12" cy="12" r="3"/><path d="M19.4 15a1.65 1.65 0 00.33 1.82l.06.06a2 2 0 010 2.83 2 2 0 01-2.83 0l-.06-.06A1.65 1.65 0 0015 19.4a1.65 1.65 0 00-1 1.51V21a2 2 0 01-4 0v-.09A1.65 1.65 0 009 19.4a1.65 1.65 0 00-1.82.33l-.06.06a2 2 0 01-2.83 0 2 2 0 010-2.83l.06-.06A1.65 1.65 0 004.6 15a1.65 1.65 0 00-1.51-1H3a2 2 0 010-4h.09A1.65 1.65 0 004.6 9a1.65 1.65 0 00-.33-1.82l-.06-.06a2 2 0 010-2.83 2 2 0 012.83 0l.06.06A1.65 1.65 0 009 4.6a1.65 1.65 0 001-1.51V3a2 2 0 014 0v.09A1.65 1.65 0 0015 4.6a1.65 1.65 0 001.82-.33l.06.06a2 2 0 012.83 0 2 2 0 010 2.83l-.06.06A1.65 1.65 0 0019.4 9a1.65 1.65 0 001.51 1H21a2 2 0 010 4h-.09a1.65 1.65 0 00-1.51 1z"/></svg>
</button>
`;
}
}
-374
View File
@@ -1,374 +0,0 @@
/* Scene canvas — SVG with draggable sources, NV crystal sensor, field lines, mini ODMR. */
import { LitElement, html, css, svg } from 'lit';
import { customElement, state } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import { lastB, bMag, fps, snr, motionReduced, running, getClient, speed, pushLog, lastFrame, scenePositions } from '../store/appStore';
interface SceneItem { id: string; x: number; y: number; color: string; name: string; }
@customElement('nv-scene')
export class NvScene extends LitElement {
@state() private zoom = 1.0;
@state() private layerVisible = { source: true, field: true, label: true };
@state() private items: SceneItem[] = [
{ id: 'rebar', x: 740, y: 240, color: 'oklch(0.72 0.18 330)', name: 'rebar.steel' },
{ id: 'heart', x: 220, y: 180, color: 'oklch(0.78 0.14 195)', name: 'heart_proxy' },
{ id: 'mains', x: 180, y: 380, color: 'oklch(0.72 0.18 330)', name: 'mains_60Hz' },
{ id: 'door', x: 800, y: 470, color: 'oklch(0.78 0.14 145)', name: 'door.steel' },
];
@state() private dragging: string | null = null;
@state() private selected: string | null = null;
private dragOffset = { dx: 0, dy: 0 };
static styles = css`
:host {
display: block; height: 100%; width: 100%;
background: radial-gradient(ellipse at 50% 30%, var(--bg-2) 0%, var(--bg-0) 70%);
position: relative; overflow: hidden;
border-bottom: 1px solid var(--line);
}
.grid {
position: absolute; inset: 0;
background-image:
linear-gradient(var(--grid) 1px, transparent 1px),
linear-gradient(90deg, var(--grid) 1px, transparent 1px);
background-size: 32px 32px;
pointer-events: none;
mask-image: radial-gradient(ellipse at center, black 40%, transparent 100%);
}
svg { position: absolute; inset: 0; width: 100%; height: 100%; }
.stat-card {
background: rgba(13,17,23,0.7);
backdrop-filter: blur(8px);
border: 1px solid var(--line);
border-radius: var(--radius-sm);
padding: 8px 12px;
font-size: 11px;
min-width: 96px;
}
[data-theme="light"] .stat-card { background: rgba(255,255,255,0.85); }
.stat-card .lbl {
color: var(--ink-3);
text-transform: uppercase; font-weight: 600; letter-spacing: 0.06em; font-size: 9.5px;
}
.stat-card .val { font-family: var(--mono); font-size: 16px; font-weight: 600; margin-top: 2px; }
.stat-card .val.amber { color: var(--accent); }
.stat-card .val.cyan { color: var(--accent-2); }
.stat-card .val.mint { color: var(--accent-4); }
.scene-readout {
position: absolute; top: 14px; right: 14px;
display: flex; gap: 8px; z-index: 5;
}
.draggable { cursor: grab; transition: filter 0.15s; }
.draggable:hover { filter: brightness(1.15) drop-shadow(0 0 6px currentColor); }
.draggable.dragging { cursor: grabbing; filter: brightness(1.25) drop-shadow(0 0 10px currentColor); }
.field-line { stroke-dasharray: 4 6; }
@keyframes dash { to { stroke-dashoffset: -200; } }
.field-line.anim { animation: dash 4s linear infinite; }
@keyframes spin {
0% { transform: rotateY(0) rotateX(8deg); }
100% { transform: rotateY(360deg) rotateX(8deg); }
}
.crystal { transform-origin: center; transform-box: fill-box; }
.crystal.anim { animation: spin 12s linear infinite; }
.label {
font-family: var(--mono); font-size: 11px; fill: var(--ink-2);
pointer-events: none;
}
.scene-toolbar {
position: absolute; top: 14px; left: 14px;
display: flex; gap: 6px; z-index: 5;
background: rgba(13,17,23,0.85);
backdrop-filter: blur(8px);
border: 1px solid var(--line);
border-radius: 8px;
padding: 4px;
}
[data-theme="light"] .scene-toolbar { background: rgba(255,255,255,0.85); }
.scene-toolbar button {
width: 28px; height: 28px;
background: transparent;
border: 1px solid transparent;
border-radius: 6px;
color: var(--ink-2);
cursor: pointer;
display: grid; place-items: center;
font-size: 13px;
}
.scene-toolbar button:hover { color: var(--ink); background: var(--bg-2); }
.scene-toolbar button.on { background: var(--bg-3); color: var(--accent); border-color: var(--line-2); }
.sim-controls {
position: absolute; bottom: 14px; right: 14px;
display: flex; gap: 6px; align-items: center;
background: rgba(13,17,23,0.85);
backdrop-filter: blur(12px);
border: 1px solid var(--line-2);
border-radius: 999px;
padding: 6px 10px;
z-index: 5;
}
[data-theme="light"] .sim-controls { background: rgba(255,255,255,0.92); }
.sim-controls .play {
width: 32px; height: 32px;
background: var(--accent);
border: none;
border-radius: 50%;
color: #1a0f00;
cursor: pointer;
display: grid; place-items: center;
font-size: 13px;
}
.sim-controls .play:hover { filter: brightness(1.08); }
.sim-controls .step {
width: 26px; height: 26px;
border-radius: 6px;
background: transparent;
color: var(--ink-2);
border: 1px solid var(--line);
cursor: pointer;
font-size: 11px;
}
.sim-controls .step:hover { color: var(--ink); border-color: var(--line-2); }
.sim-controls .speed {
font-family: var(--mono); font-size: 11px;
color: var(--ink-2);
padding: 0 6px;
min-width: 36px;
text-align: center;
cursor: pointer;
}
`;
override connectedCallback(): void {
super.connectedCallback();
// Restore drag positions if any are persisted.
if (scenePositions.value.length > 0) {
this.items = this.items.map((it) => {
const saved = scenePositions.value.find((p) => p.id === it.id);
return saved ? { ...it, x: saved.x, y: saved.y } : it;
});
}
effect(() => {
lastB.value; bMag.value; fps.value; snr.value; motionReduced.value;
running.value; speed.value; lastFrame.value;
this.requestUpdate();
});
// Compute SNR from the last frame: |B_pT| / max(σ_pT[k]) per ADR-093 P1.4.
effect(() => {
const f = lastFrame.value;
if (!f) return;
const bmag = Math.sqrt(f.bPt[0] ** 2 + f.bPt[1] ** 2 + f.bPt[2] ** 2);
const sigmaMax = Math.max(Math.abs(f.sigmaPt[0]), Math.abs(f.sigmaPt[1]), Math.abs(f.sigmaPt[2]), 0.001);
const snrVal = bmag / sigmaMax;
if (Number.isFinite(snrVal)) snr.value = snrVal;
});
window.addEventListener('pointermove', this.onPointerMove);
window.addEventListener('pointerup', this.onPointerUp);
window.addEventListener('keydown', this.onKey);
}
/** Tab cycles selection; arrow keys nudge by 8 px (32 px with Shift);
* Esc deselects. ADR-093 P2.6. */
private onKey = (e: KeyboardEvent): void => {
const target = e.target as HTMLElement | null;
if (target && (target.tagName === 'INPUT' || target.tagName === 'TEXTAREA')) return;
if (!this.selected) {
if (e.key === 'Tab' && document.activeElement === document.body) {
e.preventDefault();
this.selected = this.items[0]?.id ?? null;
}
return;
}
if (e.key === 'ArrowLeft' || e.key === 'ArrowRight' || e.key === 'ArrowUp' || e.key === 'ArrowDown') {
e.preventDefault();
const step = e.shiftKey ? 32 : 8;
const dx = e.key === 'ArrowLeft' ? -step : e.key === 'ArrowRight' ? step : 0;
const dy = e.key === 'ArrowUp' ? -step : e.key === 'ArrowDown' ? step : 0;
this.items = this.items.map((it) =>
it.id === this.selected
? { ...it, x: Math.max(20, Math.min(980, it.x + dx)), y: Math.max(20, Math.min(580, it.y + dy)) }
: it,
);
scenePositions.value = this.items.map(({ id, x, y }) => ({ id, x, y }));
} else if (e.key === 'Tab') {
e.preventDefault();
const idx = this.items.findIndex((it) => it.id === this.selected);
const next = (idx + (e.shiftKey ? -1 : 1) + this.items.length) % this.items.length;
this.selected = this.items[next].id;
} else if (e.key === 'Escape') {
this.selected = null;
}
};
private async toggleRun(): Promise<void> {
const c = getClient(); if (!c) return;
if (running.value) { await c.pause(); running.value = false; }
else { await c.run(); running.value = true; }
}
private async stepFwd(): Promise<void> {
const c = getClient(); if (!c) return;
await c.step('fwd', 10);
pushLog('dbg', 'sim step → +1 frame');
}
private async stepBack(): Promise<void> {
const c = getClient(); if (!c) return;
await c.step('back', 10);
pushLog('dbg', 'sim step ← -1 frame');
}
private cycleSpeed(): void {
const speeds = [0.25, 0.5, 1.0, 2.0, 4.0];
const idx = speeds.indexOf(speed.value);
speed.value = speeds[(idx + 1) % speeds.length];
}
private zoomIn(): void { this.zoom = Math.min(2.5, this.zoom * 1.2); }
private zoomOut(): void { this.zoom = Math.max(0.5, this.zoom / 1.2); }
private fitView(): void { this.zoom = 1.0; }
private toggleLayer(k: 'source' | 'field' | 'label'): void {
this.layerVisible = { ...this.layerVisible, [k]: !this.layerVisible[k] };
}
override disconnectedCallback(): void {
super.disconnectedCallback();
window.removeEventListener('pointermove', this.onPointerMove);
window.removeEventListener('pointerup', this.onPointerUp);
window.removeEventListener('keydown', this.onKey);
}
private onDown = (id: string, e: PointerEvent): void => {
e.preventDefault();
this.dragging = id;
this.selected = id;
const item = this.items.find((i) => i.id === id);
if (!item) return;
const svgEl = this.renderRoot.querySelector('svg') as SVGSVGElement | null;
if (!svgEl) return;
const pt = this.toSvg(e, svgEl);
this.dragOffset = { dx: pt.x - item.x, dy: pt.y - item.y };
};
private onPointerMove = (e: PointerEvent): void => {
if (!this.dragging) return;
const svgEl = this.renderRoot.querySelector('svg') as SVGSVGElement | null;
if (!svgEl) return;
const pt = this.toSvg(e, svgEl);
this.items = this.items.map((it) =>
it.id === this.dragging
? { ...it, x: pt.x - this.dragOffset.dx, y: pt.y - this.dragOffset.dy }
: it,
);
};
private onPointerUp = (): void => {
if (this.dragging) {
// Persist all positions on drop.
scenePositions.value = this.items.map(({ id, x, y }) => ({ id, x, y }));
}
this.dragging = null;
};
private toSvg(e: PointerEvent, svgEl: SVGSVGElement): { x: number; y: number } {
const r = svgEl.getBoundingClientRect();
const vbX = ((e.clientX - r.left) / r.width) * 1000;
const vbY = ((e.clientY - r.top) / r.height) * 600;
return { x: vbX, y: vbY };
}
override render() {
const b = lastB.value;
const bnT = [b[0] * 1e9, b[1] * 1e9, b[2] * 1e9];
const bMagNT = bMag.value * 1e9;
const animClass = motionReduced.value ? '' : 'anim';
const vbW = 1000 / this.zoom;
const vbH = 600 / this.zoom;
const vbX = (1000 - vbW) / 2;
const vbY = (600 - vbH) / 2;
return html`
<div class="grid"></div>
<svg viewBox="${vbX.toFixed(1)} ${vbY.toFixed(1)} ${vbW.toFixed(1)} ${vbH.toFixed(1)}"
preserveAspectRatio="xMidYMid meet" id="scene-svg">
<defs>
<radialGradient id="g-sensor" cx="50%" cy="50%" r="50%">
<stop offset="0" stop-color="oklch(0.78 0.14 70)" stop-opacity="0.4"/>
<stop offset="1" stop-color="oklch(0.78 0.14 70)" stop-opacity="0"/>
</radialGradient>
<filter id="glow"><feGaussianBlur stdDeviation="3" result="b"/><feMerge><feMergeNode in="b"/><feMergeNode in="SourceGraphic"/></feMerge></filter>
</defs>
<!-- Field lines from each source to sensor -->
${this.layerVisible.field ? this.items.map((it) => svg`
<line class="field-line ${animClass}" x1=${it.x} y1=${it.y}
x2="500" y2="320"
stroke=${it.color} stroke-width="1" stroke-opacity="0.5"/>
`) : ''}
<!-- Source primitives -->
${this.layerVisible.source ? this.items.map((it) => svg`
<g class=${`draggable ${this.dragging === it.id ? 'dragging' : ''} ${this.selected === it.id ? 'selected' : ''}`}
data-id=${it.id} data-source-id=${it.id}
transform=${`translate(${it.x.toFixed(0)},${it.y.toFixed(0)})`}
@pointerdown=${(e: PointerEvent) => this.onDown(it.id, e)}>
<ellipse cx="0" cy="0" rx="32" ry="22" fill=${it.color} fill-opacity="0.18"
stroke=${it.color} stroke-width="1.2"/>
<circle cx="0" cy="0" r="4" fill=${it.color}/>
${this.layerVisible.label ? svg`<text class="label" x="0" y="40" text-anchor="middle">${it.name}</text>` : ''}
</g>
`) : ''}
<!-- Sensor (NV diamond) at center -->
<g id="sensor-g" class="draggable" data-id="sensor" transform="translate(500, 320)">
<circle cx="0" cy="0" r="46" fill="url(#g-sensor)"/>
<g class=${`crystal ${animClass}`} stroke="oklch(0.78 0.14 70)" stroke-width="2"
fill="oklch(0.78 0.14 70 / 0.08)" filter="url(#glow)">
<polygon points="0,-22 19,-7 12,18 -12,18 -19,-7"/>
</g>
<circle cx="0" cy="0" r="3" fill="var(--accent)"/>
<text class="label" x="0" y="56" text-anchor="middle">
sensor · 〈111〉 NV
</text>
<text class="label" x="0" y="72" text-anchor="middle">
B_in: <tspan fill="var(--accent)" id="b-in-svg">[${bnT[0].toFixed(2)}, ${bnT[1].toFixed(2)}, ${bnT[2].toFixed(2)}] nT</tspan>
</text>
</g>
</svg>
<div class="scene-toolbar" id="scene-toolbar">
<button id="zoom-in-btn" title="Zoom in" @click=${this.zoomIn}>+</button>
<button id="zoom-out-btn" title="Zoom out" @click=${this.zoomOut}></button>
<button id="fit-btn" title="Fit to view" @click=${this.fitView}>⊡</button>
<button id="layer-source-btn" class=${this.layerVisible.source ? 'on' : ''}
title="Sources" @click=${() => this.toggleLayer('source')}>●</button>
<button id="layer-field-btn" class=${this.layerVisible.field ? 'on' : ''}
title="Field lines" @click=${() => this.toggleLayer('field')}>≈</button>
<button id="layer-label-btn" class=${this.layerVisible.label ? 'on' : ''}
title="Labels" @click=${() => this.toggleLayer('label')}>T</button>
</div>
<div class="sim-controls" id="sim-controls">
<button class="step" id="step-back-btn" title="Step back" @click=${this.stepBack}>⏮</button>
<button class="play" id="play-btn" title="Play / pause" @click=${this.toggleRun}>
${running.value ? '❚❚' : '▶'}
</button>
<button class="step" id="step-fwd-btn" title="Step forward" @click=${this.stepFwd}>⏭</button>
<span class="speed" id="speed-val" title="Cycle speed" @click=${this.cycleSpeed}>${speed.value}×</span>
</div>
<div class="scene-readout">
<div class="stat-card">
<div class="lbl">|B|</div>
<div class="val amber" id="bmag-readout">${bMagNT.toFixed(3)} nT</div>
</div>
<div class="stat-card">
<div class="lbl">FPS</div>
<div class="val cyan" id="fps-readout">${fps.value > 0 ? Math.round(fps.value) : '—'}</div>
</div>
<div class="stat-card">
<div class="lbl">SNR</div>
<div class="val mint" id="snr-readout">${snr.value > 0 ? snr.value.toFixed(1) : '—'}</div>
</div>
</div>
`;
}
}
@@ -1,272 +0,0 @@
/* Settings drawer — theme / density / motion / auto-update. */
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import { theme, density, motionReduced, autoUpdate, transport, wsUrl } from '../store/appStore';
@customElement('nv-settings-drawer')
export class NvSettingsDrawer extends LitElement {
@state() private open = false;
static styles = css`
/* The host covers the viewport without transforming itself. Only the
* inner .panel is transformed; otherwise the host's transform would
* create a containing block for the fixed-position scrim, clipping
* it to the panel's 420 px width and breaking outside-to-dismiss. */
:host {
position: fixed; inset: 0;
z-index: 51;
pointer-events: none;
opacity: 0;
transition: opacity 0.2s;
}
:host([open]) { pointer-events: auto; opacity: 1; }
.scrim {
position: absolute; inset: 0;
background: rgba(0, 0, 0, 0.5);
backdrop-filter: blur(2px);
}
.panel {
position: absolute;
top: 0; right: 0; bottom: 0;
width: 420px; max-width: 100vw;
background: var(--bg-1);
border-left: 1px solid var(--line);
transform: translateX(100%);
transition: transform 0.25s cubic-bezier(0.4, 0, 0.2, 1);
display: flex; flex-direction: column;
box-shadow: -20px 0 60px -20px rgba(0, 0, 0, 0.5);
}
:host([open]) .panel { transform: translateX(0); }
.h {
padding: 14px 16px;
border-bottom: 1px solid var(--line);
display: flex; align-items: center; justify-content: space-between;
}
.h .ttl { font-size: 14px; font-weight: 600; }
.body { flex: 1; overflow-y: auto; padding: 16px; }
.group { margin-bottom: 22px; }
.group h4 {
margin: 0 0 10px;
font-size: 11px; font-weight: 600;
text-transform: uppercase; letter-spacing: 0.08em;
color: var(--ink-3);
}
.row {
display: flex; justify-content: space-between; align-items: center;
padding: 10px 0;
border-bottom: 1px solid var(--line);
}
.row:last-child { border-bottom: 0; }
.row .lbl { font-size: 13px; }
.row .desc { font-size: 11.5px; color: var(--ink-3); margin-top: 2px; }
.row > div:first-child { flex: 1; padding-right: 12px; }
.seg {
display: inline-flex;
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: var(--radius-sm);
padding: 2px;
}
.seg button {
padding: 4px 10px;
background: transparent; border: none;
border-radius: 6px;
font-size: 11.5px; color: var(--ink-3);
font-family: var(--mono);
cursor: pointer;
}
.seg button.on { background: var(--bg-1); color: var(--ink); }
.toggle {
position: relative;
width: 36px; height: 20px;
background: var(--bg-3);
border: 1px solid var(--line-2);
border-radius: 999px;
cursor: pointer;
flex-shrink: 0;
}
.toggle::after {
content: ''; position: absolute;
top: 2px; left: 2px;
width: 14px; height: 14px;
background: var(--ink-3);
border-radius: 50%;
transition: transform 0.15s, background 0.15s;
}
.toggle.on { background: var(--accent); border-color: var(--accent); }
.toggle.on::after { background: #1a0f00; transform: translateX(16px); }
.close {
width: 28px; height: 28px;
background: transparent; border: 1px solid var(--line);
border-radius: 6px;
color: var(--ink-2);
}
input[type="text"] {
background: var(--bg-3);
border: 1px solid var(--line);
border-radius: 6px;
padding: 6px 10px;
color: var(--ink); font-family: var(--mono); font-size: 12px;
outline: none;
}
`;
override connectedCallback(): void {
super.connectedCallback();
effect(() => { theme.value; density.value; motionReduced.value; autoUpdate.value; transport.value; wsUrl.value; this.requestUpdate(); });
window.addEventListener('open-settings', () => { this.open = true; this.setAttribute('open', ''); });
}
private close(): void { this.open = false; this.removeAttribute('open'); }
private async resetPrefs(): Promise<void> {
if (!confirm('Reset all preferences and IndexedDB state? Reloads the page.')) return;
try {
const dbs = await indexedDB.databases?.();
if (dbs) for (const d of dbs) if (d.name) indexedDB.deleteDatabase(d.name);
} catch { /* noop */ }
location.reload();
}
override render() {
return html`
<div class="scrim" @click=${() => this.close()}></div>
<div class="panel" role="dialog" aria-modal="true" aria-label="Settings">
<div class="h">
<div class="ttl">Settings</div>
<button class="close" @click=${() => this.close()}>×</button>
</div>
<div class="body">
<div class="group">
<h4>Appearance</h4>
<div class="row">
<div>
<div class="lbl">Theme</div>
<div class="desc">Dark is the default; light has higher contrast for daylight work.</div>
</div>
<div class="seg">
<button class=${theme.value === 'dark' ? 'on' : ''}
@click=${() => theme.value = 'dark'}>dark</button>
<button class=${theme.value === 'light' ? 'on' : ''}
@click=${() => theme.value = 'light'}>light</button>
</div>
</div>
<div class="row">
<div>
<div class="lbl">Density</div>
<div class="desc">Affects panel padding and font scale (15 / 14 / 13 px). Choose what your eyes prefer.</div>
</div>
<div class="seg">
<button class=${density.value === 'comfy' ? 'on' : ''}
@click=${() => density.value = 'comfy'}>comfy</button>
<button class=${density.value === 'default' ? 'on' : ''}
@click=${() => density.value = 'default'}>default</button>
<button class=${density.value === 'compact' ? 'on' : ''}
@click=${() => density.value = 'compact'}>compact</button>
</div>
</div>
<div class="row">
<div>
<div class="lbl">Reduce motion</div>
<div class="desc">Stops the rotating diamond, animated field lines, and chart easing. Auto-on if your system has the prefers-reduced-motion preference set.</div>
</div>
<span class="toggle ${motionReduced.value ? 'on' : ''}"
role="switch" aria-checked=${motionReduced.value}
@click=${() => motionReduced.value = !motionReduced.value}></span>
</div>
</div>
<div class="group">
<h4>Pipeline</h4>
<div class="row">
<div>
<div class="lbl">Auto-rerun on edit</div>
<div class="desc">When you change a Tunables slider or load a new scene, push the change to the worker without a manual restart.</div>
</div>
<span class="toggle ${autoUpdate.value ? 'on' : ''}"
role="switch" aria-checked=${autoUpdate.value}
@click=${() => autoUpdate.value = !autoUpdate.value}></span>
</div>
</div>
<div class="group">
<h4>Transport</h4>
<div class="row">
<div>
<div class="lbl">Mode</div>
<div class="desc">WASM runs nvsim in your browser (default, no server). WS connects to a host-supplied nvsim-server (REST + binary WebSocket); see ADR-092 §6.2.</div>
</div>
<div class="seg">
<button class=${transport.value === 'wasm' ? 'on' : ''}
@click=${() => transport.value = 'wasm'}>WASM</button>
<button class=${transport.value === 'ws' ? 'on' : ''}
@click=${() => transport.value = 'ws'}>WS</button>
</div>
</div>
${transport.value === 'ws' ? html`
<div class="row">
<div>
<div class="lbl">WS URL</div>
<div class="desc">Where your nvsim-server is listening. The server defaults to 127.0.0.1:7878.</div>
</div>
<input type="text" placeholder="ws://localhost:7878" .value=${wsUrl.value}
@input=${(e: Event) => wsUrl.value = (e.target as HTMLInputElement).value} />
</div>` : ''}
</div>
<div class="group">
<h4>Help</h4>
<div class="row">
<div>
<div class="lbl">Open help center</div>
<div class="desc">Quickstart, glossary, FAQ, and shortcuts. Press <kbd style="font-family:var(--mono);font-size:10.5px;padding:1px 4px;background:var(--bg-3);border:1px solid var(--line);border-radius:3px;">?</kbd> any time.</div>
</div>
<button class="seg"
@click=${() => { this.close(); window.dispatchEvent(new CustomEvent('nv-show-help')); }}
style="padding:6px 12px;cursor:pointer;background:var(--bg-3);border:1px solid var(--line);border-radius:6px;color:var(--ink);">
Open
</button>
</div>
<div class="row">
<div>
<div class="lbl">Replay welcome tour</div>
<div class="desc">Re-show the 6-step first-run walkthrough.</div>
</div>
<button class="seg"
@click=${() => { this.close(); window.dispatchEvent(new CustomEvent('nv-show-tour')); }}
style="padding:6px 12px;cursor:pointer;background:var(--bg-3);border:1px solid var(--line);border-radius:6px;color:var(--ink);">
Replay
</button>
</div>
<div class="row">
<div>
<div class="lbl">Reset all preferences</div>
<div class="desc">Wipe theme, density, motion, scene drag positions, REPL history, and the onboarding-seen flag.</div>
</div>
<button class="seg"
@click=${() => this.resetPrefs()}
style="padding:6px 12px;cursor:pointer;background:var(--bg-3);border:1px solid oklch(0.65 0.22 25 / 0.4);border-radius:6px;color:var(--bad);">
Reset
</button>
</div>
</div>
<div class="group">
<h4>About</h4>
<div class="row" style="border-bottom:0;">
<div>
<div class="lbl">nvsim · v0.3.0</div>
<div class="desc">Open-source NV-diamond simulator. Apache-2.0 OR MIT.<br>
<a style="color:var(--accent-2); text-decoration:underline dotted; cursor:pointer;"
@click=${() => { this.close(); window.dispatchEvent(new CustomEvent('nv-show-help', { detail: { section: 'about' } })); }}>
More info →
</a></div>
</div>
</div>
</div>
</div>
</div>
`;
}
}
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/* Sidebar — Scene panel, NV sensor panel, Tunables, Pipeline diagram. */
import { LitElement, html, css } from 'lit';
import { customElement } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import { fs, fmod, dtMs, noiseEnabled, running, getClient, pushLog } from '../store/appStore';
let configPushTimer: number | null = null;
function pushConfigDebounced(): void {
if (configPushTimer !== null) window.clearTimeout(configPushTimer);
configPushTimer = window.setTimeout(async () => {
const c = getClient();
if (!c) return;
try {
await c.setConfig({
digitiser: { f_s_hz: fs.value, f_mod_hz: fmod.value },
sensor: {
gamma_fwhm_hz: 1.0e6,
t1_s: 5.0e-3,
t2_s: 1.0e-6,
t2_star_s: 200e-9,
contrast: 0.03,
n_spins: 1.0e12,
shot_noise_disabled: !noiseEnabled.value,
},
dt_s: dtMs.value * 1e-3,
});
pushLog('dbg', `config pushed · fs=${fs.value} f_mod=${fmod.value} dt=${dtMs.value.toFixed(1)}ms noise=${noiseEnabled.value ? 'on' : 'off'}`);
} catch (e) {
pushLog('warn', `config push failed: ${(e as Error).message}`);
}
}, 300);
}
@customElement('nv-sidebar')
export class NvSidebar extends LitElement {
static styles = css`
:host {
display: flex; flex-direction: column; gap: 14px;
padding: 14px; overflow-y: auto;
background: var(--bg-1); border-right: 1px solid var(--line);
}
.panel {
background: var(--bg-2); border: 1px solid var(--line);
border-radius: var(--radius); padding: 12px;
}
.panel-h {
display: flex; align-items: center; justify-content: space-between;
font-size: 11px; font-weight: 600; color: var(--ink-3);
text-transform: uppercase; letter-spacing: 0.08em;
margin-bottom: 6px;
}
.panel-help {
font-size: 11.5px; color: var(--ink-3);
margin: 0 0 10px;
line-height: 1.5;
}
.help-link {
color: var(--accent-2);
cursor: pointer;
text-decoration: underline dotted;
}
.help-link:hover { color: var(--accent); }
.count {
background: var(--bg-3); color: var(--ink-2);
padding: 1px 6px; border-radius: 999px;
font-family: var(--mono); font-size: 10px;
text-transform: none; letter-spacing: 0;
}
.scene-item {
display: flex; align-items: center; gap: 10px;
padding: 8px 10px;
border-radius: var(--radius-sm);
cursor: pointer;
transition: background 0.15s;
border: 1px solid transparent;
}
.scene-item:hover { background: var(--bg-3); }
.scene-item .swatch { width: 8px; height: 8px; border-radius: 50%; flex-shrink: 0; }
.scene-item .name { font-size: 13px; flex: 1; }
.scene-item .meta { font-family: var(--mono); font-size: 10.5px; color: var(--ink-3); }
.field-row {
display: flex; align-items: center; justify-content: space-between;
padding: 6px 0; font-size: 12.5px;
border-bottom: 1px solid var(--line);
}
.field-row:last-child { border-bottom: 0; }
.field-row .lbl { color: var(--ink-3); }
.field-row .val { font-family: var(--mono); color: var(--ink); font-size: 12px; }
.slider-row { padding: 8px 0; border-bottom: 1px solid var(--line); }
.slider-row:last-child { border-bottom: 0; padding-bottom: 0; }
.slider-row .top { display: flex; justify-content: space-between; margin-bottom: 6px; font-size: 12px; }
.slider-row .top .lbl { color: var(--ink-3); }
.slider-row .top .val { font-family: var(--mono); color: var(--ink); }
input[type="range"] {
-webkit-appearance: none; appearance: none;
width: 100%; height: 4px;
background: var(--bg-3); border-radius: 2px; outline: none;
}
input[type="range"]::-webkit-slider-thumb {
-webkit-appearance: none; appearance: none;
width: 14px; height: 14px; border-radius: 50%;
background: var(--accent); cursor: pointer;
border: 2px solid var(--bg-2);
box-shadow: 0 0 0 1px var(--line-2);
}
.pipeline { display: flex; gap: 4px; align-items: center; flex-wrap: wrap; margin-top: 6px; }
.stage {
flex: 1; min-width: 50px;
padding: 4px 6px;
background: var(--bg-3); border: 1px solid var(--line);
border-radius: 6px; font-size: 9.5px; text-align: center;
color: var(--ink-2); font-family: var(--mono);
}
.stage.live { border-color: var(--accent-2); color: var(--accent-2); }
.stage-arrow { color: var(--ink-4); font-size: 10px; }
`;
override connectedCallback(): void {
super.connectedCallback();
effect(() => { fs.value; fmod.value; dtMs.value; noiseEnabled.value; running.value; this.requestUpdate(); });
}
override render() {
return html`
<div class="panel">
<div class="panel-h">Scene <span class="count">4 sources</span></div>
<div class="panel-help">
Magnetic primitives in the simulated environment. Drag any in the
canvas to reposition; positions persist across reloads.
</div>
<div class="scene-item">
<span class="swatch" style="background:oklch(0.72 0.18 330)"></span>
<span class="name">rebar.steel.coil</span>
<span class="meta">χ=5000</span>
</div>
<div class="scene-item">
<span class="swatch" style="background:oklch(0.78 0.14 195)"></span>
<span class="name">heart_proxy</span>
<span class="meta">1e-6 A·m²</span>
</div>
<div class="scene-item">
<span class="swatch" style="background:oklch(0.72 0.18 330)"></span>
<span class="name">mains_60Hz</span>
<span class="meta">2 A · 60 Hz</span>
</div>
<div class="scene-item">
<span class="swatch" style="background:oklch(0.78 0.14 145)"></span>
<span class="name">door.steel</span>
<span class="meta">eddy</span>
</div>
</div>
<div class="panel">
<div class="panel-h">NV sensor <span class="count">COTS</span></div>
<div class="panel-help">
Element Six DNV-B1 reference: 1 mm³ diamond, ~10¹² NV centers.
Floor δB ≈ 1.18 pT/√Hz per Barry 2020 §III.A.
<span class="help-link" title="Open glossary"
@click=${() => window.dispatchEvent(new CustomEvent('nv-show-help', { detail: { section: 'glossary' } }))}>What's NV?</span>
</div>
<div class="field-row" title="Sensing volume (cubic millimetres)"><span class="lbl">V</span><span class="val">1 mm³</span></div>
<div class="field-row" title="Number of NV centers contributing to readout"><span class="lbl">N</span><span class="val">1e12 NV</span></div>
<div class="field-row" title="ODMR contrast — fractional dip at resonance"><span class="lbl">C</span><span class="val">0.030</span></div>
<div class="field-row" title="Inhomogeneous dephasing time T₂*"><span class="lbl">T₂*</span><span class="val">200 ns</span></div>
<div class="field-row" title="Shot-noise-limited field sensitivity"><span class="lbl">δB</span><span class="val">1.18 pT/√Hz</span></div>
</div>
<div class="panel">
<div class="panel-h">Tunables</div>
<div class="panel-help">
Live pipeline parameters. Edits debounce 300 ms then rebuild the
WASM pipeline without restarting the frame stream.
</div>
<div class="slider-row" title="Digitiser sample rate — frames per second emitted by the pipeline">
<div class="top"><span class="lbl">Sample rate</span><span class="val">${(fs.value / 1000).toFixed(1)} kHz</span></div>
<input type="range" min="1000" max="100000" .value=${String(fs.value)}
aria-label="Sample rate in Hz"
@input=${(e: Event) => { fs.value = +(e.target as HTMLInputElement).value; pushConfigDebounced(); }} />
</div>
<div class="slider-row" title="Microwave modulation frequency for lock-in demodulation">
<div class="top"><span class="lbl">Lockin f_mod</span><span class="val">${(fmod.value / 1000).toFixed(3)} kHz</span></div>
<input type="range" min="100" max="5000" .value=${String(fmod.value)}
aria-label="Lock-in modulation frequency in Hz"
@input=${(e: Event) => { fmod.value = +(e.target as HTMLInputElement).value; pushConfigDebounced(); }} />
</div>
<div class="slider-row" title="Per-sample integration time">
<div class="top"><span class="lbl">Integration t</span><span class="val">${dtMs.value.toFixed(1)} ms</span></div>
<input type="range" min="0.1" max="10" step="0.1" .value=${String(dtMs.value)}
aria-label="Integration time in milliseconds"
@input=${(e: Event) => { dtMs.value = +(e.target as HTMLInputElement).value; pushConfigDebounced(); }} />
</div>
<div class="slider-row" title="Toggle shot-noise sampling. OFF = analytic noise-free output (debug only)">
<div class="top"><span class="lbl">Shot noise</span><span class="val">${noiseEnabled.value ? 'ON' : 'OFF'}</span></div>
<input type="range" min="0" max="1" .value=${noiseEnabled.value ? '1' : '0'}
aria-label="Shot-noise sampling enabled"
@input=${(e: Event) => { noiseEnabled.value = (e.target as HTMLInputElement).value === '1'; pushConfigDebounced(); }} />
</div>
</div>
<div class="panel">
<div class="panel-h">Pipeline</div>
<div class="panel-help">
Forward simulator stages, left to right. Stages glow cyan while
the pipeline is running.
</div>
<div class="pipeline">
<span class="stage ${running.value ? 'live' : ''}">scene</span>
<span class="stage-arrow">→</span>
<span class="stage ${running.value ? 'live' : ''}">B-S</span>
<span class="stage-arrow">→</span>
<span class="stage ${running.value ? 'live' : ''}">prop</span>
<span class="stage-arrow">→</span>
<span class="stage ${running.value ? 'live' : ''}">NV</span>
<span class="stage-arrow">→</span>
<span class="stage ${running.value ? 'live' : ''}">ADC</span>
<span class="stage-arrow">→</span>
<span class="stage ${running.value ? 'live' : ''}">frame</span>
</div>
</div>
`;
}
}
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/* Toast notification — shown briefly via window.dispatchEvent('nv-toast', detail). */
import { LitElement, html, css } from 'lit';
import { customElement, state } from 'lit/decorators.js';
@customElement('nv-toast')
export class NvToast extends LitElement {
@state() private visible = false;
@state() private msg = '';
@state() private icon = '✓';
private timer: number | null = null;
static styles = css`
:host {
position: fixed; bottom: 24px; left: 50%;
transform: translateX(-50%) translateY(80px);
background: var(--bg-2);
border: 1px solid var(--line-2);
border-radius: var(--radius);
padding: 10px 14px;
font-size: 12.5px;
box-shadow: var(--shadow);
z-index: 100;
opacity: 0; pointer-events: none;
transition: opacity 0.2s, transform 0.2s;
display: flex; align-items: center; gap: 8px;
}
:host([visible]) {
opacity: 1;
transform: translateX(-50%) translateY(0);
pointer-events: auto;
}
.icon { color: var(--accent); }
`;
override connectedCallback(): void {
super.connectedCallback();
window.addEventListener('nv-toast', this.onToast as EventListener);
}
override disconnectedCallback(): void {
super.disconnectedCallback();
window.removeEventListener('nv-toast', this.onToast as EventListener);
}
private onToast = (e: Event): void => {
const detail = (e as CustomEvent).detail as { msg?: string; icon?: string };
this.msg = detail.msg ?? 'Done';
this.icon = detail.icon ?? '✓';
this.visible = true;
this.setAttribute('visible', '');
if (this.timer !== null) window.clearTimeout(this.timer);
this.timer = window.setTimeout(() => {
this.visible = false;
this.removeAttribute('visible');
}, 1800);
};
override render() {
return html`<span class="icon">${this.icon}</span><span>${this.msg}</span>`;
}
}
export function toast(msg: string, icon = '✓'): void {
window.dispatchEvent(new CustomEvent('nv-toast', { detail: { msg, icon } }));
}
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/* Topbar — breadcrumbs, transport pill, FPS pill, seed pill, controls. */
import { LitElement, html, css } from 'lit';
import { customElement } from 'lit/decorators.js';
import { effect } from '@preact/signals-core';
import {
fps, transportLabel, seed, theme, sceneName,
running, getClient, pushLog,
} from '../store/appStore';
import { openModal } from './nv-modal';
import { toast } from './nv-toast';
@customElement('nv-topbar')
export class NvTopbar extends LitElement {
static styles = css`
:host {
display: flex; align-items: center;
padding: 0 16px; gap: 12px;
background: var(--bg-1);
border-bottom: 1px solid var(--line);
z-index: 10;
}
.crumbs { display: flex; align-items: center; gap: 8px; font-size: 12.5px; color: var(--ink-3); }
.crumbs .sep { color: var(--ink-4); }
.crumbs .cur { color: var(--ink); font-weight: 500; }
.spacer { flex: 1; }
.pill {
display: inline-flex; align-items: center; gap: 6px;
padding: 5px 10px;
background: var(--bg-2); border: 1px solid var(--line);
border-radius: 999px;
font-size: 12px; color: var(--ink-2);
font-family: var(--mono); font-weight: 500;
}
.pill .dot { width: 6px; height: 6px; border-radius: 50%; background: var(--ok); box-shadow: 0 0 6px var(--ok); animation: pulse 2s infinite; }
.pill.wasm .dot { background: var(--accent-2); box-shadow: 0 0 6px var(--accent-2); }
.pill.seed { color: var(--ink-3); cursor: pointer; }
.pill.seed:hover { border-color: var(--line-2); }
.pill.seed b { color: var(--accent); font-weight: 600; }
.pill.wasm { cursor: pointer; }
.pill.wasm:hover { border-color: var(--line-2); }
button {
display: inline-flex; align-items: center; gap: 6px;
padding: 6px 12px;
background: var(--bg-2); border: 1px solid var(--line);
border-radius: 8px;
font-size: 12.5px; font-weight: 500; color: var(--ink);
cursor: pointer;
transition: all 0.15s;
}
button:hover { border-color: var(--line-2); background: var(--bg-3); }
button.primary { background: var(--accent); border-color: var(--accent); color: #1a0f00; }
button.primary:hover { filter: brightness(1.08); }
button.ghost { background: transparent; }
`;
override connectedCallback(): void {
super.connectedCallback();
effect(() => { fps.value; transportLabel.value; seed.value; theme.value; sceneName.value; running.value; this.requestUpdate(); });
}
private async toggleRun(): Promise<void> {
const c = getClient(); if (!c) return;
if (running.value) { await c.pause(); running.value = false; }
else { await c.run(); running.value = true; }
}
private async reset(): Promise<void> {
const c = getClient(); if (!c) return;
await c.reset();
}
private toggleTheme(): void {
theme.value = theme.value === 'dark' ? 'light' : 'dark';
}
private async openSeedModal(): Promise<void> {
const cur = `0x${seed.value.toString(16).toUpperCase().padStart(8, '0')}`;
openModal({
title: 'Set seed',
body: `<p>Set the 32-bit hex seed for the shot-noise PRNG. Same <code>(scene, config, seed)</code> → byte-identical witness.</p>
<label>Hex seed</label>
<input type="text" id="seed-input" value="${cur}" autofocus />`,
buttons: [
{ label: 'Cancel', variant: 'ghost' },
{ label: 'Apply', variant: 'primary', onClick: async () => {
const inp = document.querySelector('nv-modal')?.shadowRoot?.querySelector<HTMLInputElement>('#seed-input');
if (!inp) return;
const raw = inp.value.trim().replace(/^0x/i, '');
const v = BigInt('0x' + raw);
seed.value = v;
await getClient()?.setSeed(v);
pushLog('ok', `seed → 0x${v.toString(16).toUpperCase()}`);
toast(`Seed → 0x${v.toString(16).toUpperCase().slice(0, 8)}`, '⟳');
} },
],
});
}
private openTransportSettings(): void {
window.dispatchEvent(new CustomEvent('open-settings'));
}
override render() {
const seedHex = seed.value.toString(16).toUpperCase().padStart(8, '0');
return html`
<div class="crumbs">
<span class="home">RuView</span><span class="sep">/</span>
<span>nvsim</span><span class="sep">/</span>
<span class="cur" id="scene-name">${sceneName.value}</span>
</div>
<div class="spacer"></div>
<span class="pill" id="fps-pill">
<span class="dot"></span>
<span id="fps-val">${fps.value > 0 ? (fps.value / 1000).toFixed(2) + ' kHz' : 'idle'}</span>
</span>
<span class="pill wasm" id="transport-pill" title="Transport settings"
@click=${this.openTransportSettings}>
<span class="dot"></span>${transportLabel.value}
</span>
<span class="pill seed" id="seed-pill" title="Set seed"
@click=${this.openSeedModal}>
seed: <b>0x${seedHex}</b>
</span>
<button class="ghost" id="tour-btn" title="Replay the 10-step welcome tour"
aria-label="Replay welcome tour"
@click=${() => window.dispatchEvent(new CustomEvent('nv-show-tour'))}>
Tour
</button>
<button class="ghost" id="help-btn" title="Help (press ? any time)" aria-label="Open help"
@click=${() => window.dispatchEvent(new CustomEvent('nv-show-help'))}>
?
</button>
<button class="ghost" id="theme-btn" title="Toggle theme" aria-label="Toggle theme"
@click=${this.toggleTheme}>
${theme.value === 'dark' ? '☼' : '☾'}
</button>
<button id="reset-btn" @click=${this.reset}> Reset</button>
<button class="primary" id="run-btn" @click=${this.toggleRun}>
${running.value ? '❚❚ Pause' : '▶ Run'}
</button>
`;
}
}
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/* nvsim dashboard entry — boots the WasmClient, mounts <nv-app>. */
import './app.css';
import './components/nv-app';
import { effect } from '@preact/signals-core';
import { WasmClient } from './transport/WasmClient';
import { WsClient } from './transport/WsClient';
import type { NvsimClient, MagFrameBatch } from './transport/NvsimClient';
import {
setClient, transport, wsUrl, connected, transportError,
theme, density, motionReduced,
pushLog, expectedWitness, framesEmitted, fps, lastB, bMag,
pushTrace, pushStripBar, lastFrame, sceneJson, witnessHex,
replHistory, scenePositions, type SceneItemPos,
activeAppIds, pushAppEvent,
} from './store/appStore';
import { APP_RUNTIMES, type AppRuntimeContext } from './store/appRuntimes';
import { kvGet, kvSet } from './store/persistence';
function applyTheme(t: string): void {
document.documentElement.setAttribute('data-theme', t);
}
function applyDensity(d: string): void {
document.body.classList.remove('density-comfy', 'density-default', 'density-compact');
document.body.classList.add(`density-${d}`);
}
function applyMotion(reduced: boolean): void {
document.body.classList.toggle('reduce-motion', reduced);
}
(async () => {
// Restore persisted prefs
const t = (await kvGet<'dark' | 'light'>('theme')) ?? 'dark';
const d = (await kvGet<'comfy' | 'default' | 'compact'>('density')) ?? 'default';
const sysMotion = window.matchMedia?.('(prefers-reduced-motion: reduce)').matches ?? false;
const m = (await kvGet<boolean>('motionReduced')) ?? sysMotion;
theme.value = t; applyTheme(t);
density.value = d; applyDensity(d);
motionReduced.value = m; applyMotion(m);
// React to changes → persist
effect(() => { applyTheme(theme.value); kvSet('theme', theme.value); });
effect(() => { applyDensity(density.value); kvSet('density', density.value); });
effect(() => { applyMotion(motionReduced.value); kvSet('motionReduced', motionReduced.value); });
// REPL history + scene drag positions persistence (P0.10, P1.7)
const histSaved = await kvGet<string[]>('repl-history');
if (histSaved && Array.isArray(histSaved)) replHistory.value = histSaved;
effect(() => { void kvSet('repl-history', replHistory.value); });
const positionsSaved = await kvGet<SceneItemPos[]>('scene-positions');
if (positionsSaved && Array.isArray(positionsSaved)) scenePositions.value = positionsSaved;
effect(() => { void kvSet('scene-positions', scenePositions.value); });
// Restore WS URL preference + transport mode
const savedWsUrl = (await kvGet<string>('wsUrl')) ?? '';
if (savedWsUrl) wsUrl.value = savedWsUrl;
const savedTransport = (await kvGet<'wasm' | 'ws'>('transport')) ?? 'wasm';
transport.value = savedTransport;
effect(() => { void kvSet('wsUrl', wsUrl.value); });
effect(() => { void kvSet('transport', transport.value); });
// Per-app runtime scratch state + history buffer (defined first so the
// onFrames callback can close over them).
const appState: Record<string, Record<string, number>> = {};
const bMagHistory: number[] = [];
const runtimeStartTs = performance.now();
const onFrames = (batch: MagFrameBatch): void => {
if (batch.frames.length === 0) return;
const last = batch.frames[batch.frames.length - 1];
lastFrame.value = last;
const bx = last.bPt[0] * 1e-12;
const by = last.bPt[1] * 1e-12;
const bz = last.bPt[2] * 1e-12;
lastB.value = [bx, by, bz];
const bmagT = Math.sqrt(bx * bx + by * by + bz * bz);
bMag.value = bmagT;
pushTrace([bx * 1e9, by * 1e9, bz * 1e9]);
pushStripBar(Math.min(1, Math.abs(bz * 1e9) / 5 + 0.3));
bMagHistory.push(bmagT);
while (bMagHistory.length > 256) bMagHistory.shift();
const activeIds = activeAppIds.value;
if (activeIds.size === 0) return;
const elapsedS = (performance.now() - runtimeStartTs) / 1000;
for (const id of activeIds) {
const fn = APP_RUNTIMES[id];
if (!fn) continue;
if (!appState[id]) appState[id] = {};
const ctx: AppRuntimeContext = {
frame: last,
bMagT: bmagT,
bRecoveredT: [bx, by, bz],
bHistory: bMagHistory,
elapsedS,
state: appState[id],
};
try {
const result = fn(ctx);
if (!result) continue;
const evs = Array.isArray(result) ? result : [result];
for (const ev of evs) {
pushAppEvent(ev);
pushLog('info',
`<span class="k">[${ev.appId}]</span> <span class="s">${ev.eventName}</span> <span class="n">(${ev.eventId})</span>${ev.detail ? ' · ' + ev.detail : ''}`);
}
} catch (e) {
pushLog('warn', `[${id}] runtime error: ${(e as Error).message}`);
}
}
};
// Boot transport (WASM by default, WS if user previously selected it)
let activeClient: NvsimClient | null = null;
async function bootTransport(): Promise<void> {
try {
if (activeClient) await activeClient.close();
const want = transport.value;
if (want === 'ws' && wsUrl.value.trim()) {
const c = new WsClient(wsUrl.value.trim());
const info = await c.boot();
activeClient = c;
connected.value = true;
transportError.value = null;
expectedWitness.value = info.expectedWitnessHex;
wireClient(c);
pushLog('ok', `transport WS · ${wsUrl.value} · nvsim@${info.buildVersion}`);
} else {
if (want === 'ws') {
pushLog('warn', 'WS transport selected but no URL set — falling back to WASM');
}
const c = new WasmClient();
const info = await c.boot();
activeClient = c;
connected.value = true;
transportError.value = null;
expectedWitness.value = info.expectedWitnessHex;
wireClient(c);
pushLog('ok', `transport WASM · nvsim@${info.buildVersion} · magic=0x${info.frameMagic.toString(16).toUpperCase()}`);
}
setClient(activeClient);
} catch (e) {
const msg = (e as Error).message;
transportError.value = msg;
connected.value = false;
pushLog('err', `transport boot failed: ${msg}`);
}
}
function wireClient(c: NvsimClient): void {
c.onEvent((ev) => {
if (ev.type === 'log') pushLog(ev.level, ev.msg);
if (ev.type === 'fps') fps.value = ev.value;
if (ev.type === 'state') framesEmitted.value = BigInt(ev.framesEmitted);
});
c.onFrames(onFrames);
}
// React to transport-mode flips: tear down + re-boot.
let bootInProgress = false;
effect(() => {
transport.value; wsUrl.value;
if (bootInProgress) return;
bootInProgress = true;
void bootTransport().finally(() => { bootInProgress = false; });
});
pushLog('info', 'nvsim — booting transport');
// Initial boot — handled by the effect() above.
// Auto-verify witness whenever a fresh transport boot completes.
let verifiedFor: string | null = null;
effect(() => {
const exp = expectedWitness.value;
const isConn = connected.value;
if (!exp || !isConn) return;
if (verifiedFor === exp) return;
verifiedFor = exp;
void (async () => {
const c = activeClient;
if (!c) return;
try {
const expBytes = new Uint8Array(32);
for (let i = 0; i < 32; i++) expBytes[i] = parseInt(exp.slice(i * 2, i * 2 + 2), 16);
const r = await c.verifyWitness(expBytes);
if (r.ok) {
witnessHex.value = exp;
pushLog('ok', `witness verified · determinism gate ✓ · transport=${transport.value}`);
} else {
const actual = Array.from(r.actual).map((b) => b.toString(16).padStart(2, '0')).join('');
witnessHex.value = actual;
pushLog('err', `WITNESS MISMATCH · expected ${exp.slice(0, 16)}… got ${actual.slice(0, 16)}`);
}
} catch (e) {
pushLog('warn', `witness verify skipped: ${(e as Error).message}`);
}
})();
});
sceneJson.value = '(reference scene)';
})();
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/* In-browser simulated runtimes for App Store apps.
*
* Each runtime takes the most recent nvsim MagFrame + a short rolling
* history and decides whether to emit one or more app events. Outputs are
* illustrative: nvsim produces magnetic-field samples, the wasm-edge
* algorithms expect WiFi CSI subcarriers different physical modalities.
* The simulated runtime preserves *event-emission semantics* (the same
* i32 event IDs, the same trigger logic shape) so users can see the
* cards working without an ESP32 mesh.
*
* For engineering-grade output, deploy the real `wifi-densepose-wasm-edge`
* crate to ESP32 firmware over the WS transport see ADR-040 / ADR-092 §6.2.
*/
import type { MagFrameRecord } from '../transport/NvsimClient';
export interface AppEvent {
/** Wall-clock timestamp (ms). */
ts: number;
/** App id that emitted. */
appId: string;
/** i32 event id from `event_types` mod in wifi-densepose-wasm-edge. */
eventId: number;
/** Human-readable event name (matches the constant name). */
eventName: string;
/** Numeric value the app reports (units app-specific). */
value: number;
/** Optional extra context for the console line. */
detail?: string;
}
export interface AppRuntimeContext {
frame: MagFrameRecord;
bMagT: number;
bRecoveredT: [number, number, number];
/** Rolling history of |B| in T. Most recent last. */
bHistory: number[];
/** Time since the runtime was activated (s). */
elapsedS: number;
/** Per-app scratch state — runtimes can persist counters here. */
state: Record<string, number>;
}
export type AppRuntimeFn = (ctx: AppRuntimeContext) => AppEvent | AppEvent[] | null;
/** Welford-style running-stat helper. */
function rollingMean(arr: number[]): number {
if (arr.length === 0) return 0;
let s = 0;
for (const v of arr) s += v;
return s / arr.length;
}
function rollingStd(arr: number[]): number {
if (arr.length < 2) return 0;
const m = rollingMean(arr);
let s = 0;
for (const v of arr) s += (v - m) * (v - m);
return Math.sqrt(s / (arr.length - 1));
}
/** vital_trend — periodic 1-Hz HR/BR estimate from the B_z oscillation. */
const vitalTrend: AppRuntimeFn = (ctx) => {
if (ctx.bHistory.length < 64) return null;
const last = ctx.state['lastEmitS'] ?? 0;
if (ctx.elapsedS - last < 1.0) return null;
ctx.state['lastEmitS'] = ctx.elapsedS;
// Crude HR estimate: count zero-crossings of detrended B_z over the last
// 64 samples; treat each crossing pair as one cardiac cycle.
const tail = ctx.bHistory.slice(-64);
const m = rollingMean(tail);
let crossings = 0;
for (let i = 1; i < tail.length; i++) {
if ((tail[i] - m) * (tail[i - 1] - m) < 0) crossings++;
}
// 64 samples ≈ 0.65 s at the worker's 32-frame batches × 16 ms tick.
const cycles = crossings / 2;
const hr = Math.max(40, Math.min(180, Math.round((cycles / 0.65) * 60)));
const br = Math.max(8, Math.min(30, Math.round(hr / 4))); // crude proxy
const evs: AppEvent[] = [
{ ts: Date.now(), appId: 'vital_trend', eventId: 100, eventName: 'VITAL_TREND', value: hr, detail: `HR≈${hr} BPM, BR≈${br} br/min` },
];
if (hr < 60) evs.push({ ts: Date.now(), appId: 'vital_trend', eventId: 103, eventName: 'BRADYCARDIA', value: hr, detail: `HR=${hr} BPM` });
else if (hr > 100) evs.push({ ts: Date.now(), appId: 'vital_trend', eventId: 104, eventName: 'TACHYCARDIA', value: hr, detail: `HR=${hr} BPM` });
if (br < 12) evs.push({ ts: Date.now(), appId: 'vital_trend', eventId: 101, eventName: 'BRADYPNEA', value: br, detail: `BR=${br} br/min` });
else if (br > 24) evs.push({ ts: Date.now(), appId: 'vital_trend', eventId: 102, eventName: 'TACHYPNEA', value: br, detail: `BR=${br} br/min` });
return evs;
};
/** occupancy — variance threshold on |B| over a 5-second window. */
const occupancy: AppRuntimeFn = (ctx) => {
if (ctx.bHistory.length < 32) return null;
const last = ctx.state['lastEmitS'] ?? 0;
if (ctx.elapsedS - last < 2.0) return null;
const std = rollingStd(ctx.bHistory.slice(-128)) * 1e9; // T → nT
const occupied = std > 0.01; // empirical threshold for the demo
const wasOccupied = (ctx.state['occ'] ?? 0) > 0.5;
if (occupied !== wasOccupied) {
ctx.state['occ'] = occupied ? 1 : 0;
ctx.state['lastEmitS'] = ctx.elapsedS;
return {
ts: Date.now(),
appId: 'occupancy',
eventId: occupied ? 300 : 302,
eventName: occupied ? 'ZONE_OCCUPIED' : 'ZONE_TRANSITION',
value: std,
detail: occupied ? `σ(|B|)=${std.toFixed(3)} nT — entered` : `σ(|B|)=${std.toFixed(3)} nT — left`,
};
}
return null;
};
/** intrusion — |B| above ambient + dwell timer. */
const intrusion: AppRuntimeFn = (ctx) => {
const ambient = ctx.state['ambient'] ?? ctx.bMagT;
ctx.state['ambient'] = 0.95 * ambient + 0.05 * ctx.bMagT;
const exceeds = ctx.bMagT > ambient * 1.5 && ctx.bMagT > 1e-12;
const dwellStart = ctx.state['dwellStart'] ?? 0;
if (exceeds && dwellStart === 0) {
ctx.state['dwellStart'] = ctx.elapsedS;
} else if (!exceeds) {
ctx.state['dwellStart'] = 0;
}
if (exceeds && dwellStart > 0 && ctx.elapsedS - dwellStart > 0.5 && (ctx.state['lastEmitS'] ?? 0) < dwellStart) {
ctx.state['lastEmitS'] = ctx.elapsedS;
return {
ts: Date.now(),
appId: 'intrusion',
eventId: 200,
eventName: 'INTRUSION_ALERT',
value: ctx.bMagT * 1e9,
detail: `|B|=${(ctx.bMagT * 1e9).toFixed(2)} nT > 1.5× ambient (${(ambient * 1e9).toFixed(2)} nT) for ${(ctx.elapsedS - dwellStart).toFixed(1)} s`,
};
}
return null;
};
/** coherence — z-score of recent |B| against a longer baseline. */
const coherence: AppRuntimeFn = (ctx) => {
if (ctx.bHistory.length < 64) return null;
const last = ctx.state['lastEmitS'] ?? 0;
if (ctx.elapsedS - last < 0.5) return null;
ctx.state['lastEmitS'] = ctx.elapsedS;
const recent = ctx.bHistory.slice(-32);
const baseline = ctx.bHistory.slice(-128, -32);
if (baseline.length < 32) return null;
const mu = rollingMean(baseline);
const sd = rollingStd(baseline);
if (sd === 0) return null;
const recentMean = rollingMean(recent);
const z = Math.abs(recentMean - mu) / sd;
return {
ts: Date.now(),
appId: 'coherence',
eventId: 2,
eventName: 'COHERENCE_SCORE',
value: z,
detail: `z=${z.toFixed(2)} σ ${z > 3 ? '· DRIFT' : z > 1.5 ? '· marginal' : '· stable'}`,
};
};
/** adversarial — detect physically-impossible 1/r³ violation. */
const adversarial: AppRuntimeFn = (ctx) => {
if (ctx.bHistory.length < 32) return null;
const last = ctx.state['lastEmitS'] ?? 0;
if (ctx.elapsedS - last < 3.0) return null;
// Fake "multi-link consistency": compare instantaneous |B| with the
// smoothed |B|. A sharp factor-of-N step violates dipole physics
// (real 1/r³ source moves continuously).
const tail = ctx.bHistory.slice(-32);
let maxJump = 0;
for (let i = 1; i < tail.length; i++) {
const j = Math.abs(Math.log(Math.max(tail[i], 1e-15)) - Math.log(Math.max(tail[i - 1], 1e-15)));
if (j > maxJump) maxJump = j;
}
if (maxJump > 5) {
ctx.state['lastEmitS'] = ctx.elapsedS;
return {
ts: Date.now(),
appId: 'adversarial',
eventId: 3,
eventName: 'ANOMALY_DETECTED',
value: maxJump,
detail: `log-jump ${maxJump.toFixed(1)} — physically implausible step in |B|`,
};
}
return null;
};
/** exo_ghost_hunter empty-room CSI anomaly detector adapted to the
* magnetic noise floor: flag impulsive / periodic / drift / random
* patterns and a hidden-presence sub-detector at 0.15-0.5 Hz. */
const exoGhostHunter: AppRuntimeFn = (ctx) => {
if (ctx.bHistory.length < 128) return null;
const last = ctx.state['lastEmitS'] ?? 0;
if (ctx.elapsedS - last < 4.0) return null;
ctx.state['lastEmitS'] = ctx.elapsedS;
const tail = ctx.bHistory.slice(-128);
const std = rollingStd(tail) * 1e9;
// Detect impulsive: max - mean > 4σ
const m = rollingMean(tail);
let maxDev = 0;
for (const v of tail) {
const d = Math.abs(v - m);
if (d > maxDev) maxDev = d;
}
const cls: 1 | 3 | 4 = maxDev > 4 * (std * 1e-9) ? 1 // impulsive
: ctx.elapsedS > 10 ? 3 // drift bias as a default after warmup
: 4; // random
const clsName = cls === 1 ? 'impulsive' : cls === 3 ? 'drift' : 'random';
return {
ts: Date.now(),
appId: 'exo_ghost_hunter',
eventId: 651,
eventName: 'ANOMALY_CLASS',
value: cls,
detail: `class=${clsName} · σ=${std.toFixed(3)} nT`,
};
};
export const APP_RUNTIMES: Record<string, AppRuntimeFn> = {
vital_trend: vitalTrend,
occupancy,
intrusion,
coherence,
adversarial,
exo_ghost_hunter: exoGhostHunter,
};
export function hasRuntime(appId: string): boolean {
return appId in APP_RUNTIMES;
}
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/* Application-wide reactive state.
*
* One signal per logical observable; components subscribe to only the
* signals they read. Keeps re-renders surgical even at 1 kHz frame rates.
* Persistence lives in `persistence.ts`; this module is pure state.
*/
import { signal, computed } from '@preact/signals-core';
import type { NvsimClient, MagFrameRecord, NvsimEvent } from '../transport/NvsimClient';
export type Theme = 'dark' | 'light';
export type Density = 'comfy' | 'default' | 'compact';
export type TransportMode = 'wasm' | 'ws';
export const transport = signal<TransportMode>('wasm');
export const wsUrl = signal<string>('');
export const connected = signal<boolean>(false);
export const transportError = signal<string | null>(null);
export const running = signal<boolean>(false);
export const paused = signal<boolean>(true);
export const speed = signal<number>(1.0);
export const t = signal<number>(0); // sim time (s)
export const framesEmitted = signal<bigint>(0n);
export const seed = signal<bigint>(0xCAFEBABEn);
export const fs = signal<number>(10000); // sample rate Hz
export const fmod = signal<number>(1000); // lockin Hz
export const dtMs = signal<number>(1.0);
export const noiseEnabled = signal<boolean>(true);
export const theme = signal<Theme>('dark');
export const density = signal<Density>('default');
export const motionReduced = signal<boolean>(false);
export const autoUpdate = signal<boolean>(true);
export const lastB = signal<[number, number, number]>([0, 0, 0]); // T
export const bMag = signal<number>(0);
export const snr = signal<number>(0);
export const fps = signal<number>(0);
export const witnessHex = signal<string>('');
export const witnessVerified = signal<'pending' | 'ok' | 'fail' | 'idle'>('idle');
export const expectedWitness = signal<string>('');
export const lastFrame = signal<MagFrameRecord | null>(null);
export const traceX = signal<number[]>([]);
export const traceY = signal<number[]>([]);
export const traceZ = signal<number[]>([]);
export const stripBars = signal<number[]>([]);
export const sceneName = signal<string>('rebar-walkby-01');
export const sceneJson = signal<string>('');
export const consolePaused = signal<boolean>(false);
export const consoleFilter = signal<'all' | 'info' | 'warn' | 'err' | 'dbg' | 'ok'>('all');
/** REPL command history, persisted via persistence.ts (kvSet 'repl-history'). */
export const replHistory = signal<string[]>([]);
export function pushReplHistory(cmd: string): void {
const next = replHistory.value.slice();
next.push(cmd);
while (next.length > 200) next.shift();
replHistory.value = next;
}
/** Scene drag positions, persisted via persistence.ts (kvSet 'scene-positions'). */
export interface SceneItemPos { id: string; x: number; y: number }
export const scenePositions = signal<SceneItemPos[]>([]);
/** App-runtime emitted events. See appRuntimes.ts. */
import type { AppEvent } from './appRuntimes';
export const appEvents = signal<AppEvent[]>([]);
export const appEventCounts = signal<Record<string, number>>({});
export function pushAppEvent(ev: AppEvent): void {
const next = appEvents.value.slice();
next.push(ev);
while (next.length > 200) next.shift();
appEvents.value = next;
const c = { ...appEventCounts.value };
c[ev.appId] = (c[ev.appId] ?? 0) + 1;
appEventCounts.value = c;
}
/** Active app activations driven by the App Store toggles. Mirrored
* from `apps.ts` but exposed as a signal here so `main.ts` can dispatch
* frames to active runtimes without importing the App Store component. */
export const activeAppIds = signal<Set<string>>(new Set());
export const transportLabel = computed<string>(() =>
transport.value === 'wasm' ? 'wasm' : 'ws',
);
let _client: NvsimClient | null = null;
export function setClient(c: NvsimClient): void { _client = c; }
export function getClient(): NvsimClient | null { return _client; }
export interface ConsoleLine {
ts: number;
level: 'info' | 'warn' | 'err' | 'dbg' | 'ok';
msg: string;
}
export const consoleLines = signal<ConsoleLine[]>([]);
const MAX_LINES = 200;
export function pushLog(level: ConsoleLine['level'], msg: string): void {
if (consolePaused.value) return;
const next = consoleLines.value.slice();
next.push({ ts: Date.now(), level, msg });
while (next.length > MAX_LINES) next.shift();
consoleLines.value = next;
}
export function pushTrace(b: [number, number, number]): void {
const cap = 200;
const x = traceX.value.slice(); x.push(b[0]); if (x.length > cap) x.shift();
const y = traceY.value.slice(); y.push(b[1]); if (y.length > cap) y.shift();
const z = traceZ.value.slice(); z.push(b[2]); if (z.length > cap) z.shift();
traceX.value = x;
traceY.value = y;
traceZ.value = z;
}
export function pushStripBar(amp: number): void {
const cap = 48;
const next = stripBars.value.slice();
next.push(Math.max(0, Math.min(1, amp)));
while (next.length > cap) next.shift();
stripBars.value = next;
}
export function recordEvent(_ev: NvsimEvent): void {
// future: route NvsimEvent into store updates per type. For V1 the
// worker pushes B-vector / frame data directly via the data plane.
}
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/* RuView Edge App Store registry.
*
* Catalog of every WASM edge module shipping in the workspace plus the
* `nvsim` simulator itself. Each entry maps to a hot-loadable algorithm
* the dashboard can run in-browser (WASM transport) or push to a real
* ESP32-S3 mesh (WS transport, deployed via WASM3 ADR-040 Tier 3).
*
* Categories (ADR-041 event-ID ranges):
* med 100199 Medical & health
* sec 200299 Security & safety
* bld 300399 Smart building
* ret 400499 Retail & hospitality
* ind 500599 Industrial
* sig 600619 Signal-processing primitives
* lrn 620639 Online learning
* spt 640659 Spatial / graph
* tmp 640660 Temporal logic / planning
* ais 700719 AI safety
* qnt 720739 Quantum-flavoured signal
* aut 740759 Autonomy / mesh
* exo 650699 Exotic / research
* sim Pipeline simulators (nvsim)
*
* The `crate` field names the Cargo crate that owns the implementation.
* `wasmEdge` apps are compiled out of `wifi-densepose-wasm-edge`;
* `nvsim` apps come from `nvsim`. Future apps may target other crates.
*/
export type AppCategory =
| 'sim'
| 'med'
| 'sec'
| 'bld'
| 'ret'
| 'ind'
| 'sig'
| 'lrn'
| 'spt'
| 'tmp'
| 'ais'
| 'qnt'
| 'aut'
| 'exo';
/** What actually happens when a card's toggle is on.
* - `running` the algorithm is genuinely running in the browser right now
* (e.g. `nvsim` itself, which is the simulator the dashboard fronts).
* - `simulated` a pared-down version of the algorithm runs against nvsim's
* live magnetic frame stream as a *proxy* for its native CSI input.
* Emits real i32 event IDs into the console feed; output is illustrative,
* not engineering-grade. Listed apps' Rust source is real, builds for
* wasm32-unknown-unknown, and passes its native unit tests.
* - `mesh-only` algorithm needs CSI subcarrier data from a real ESP32-S3
* mesh (or a future CSI simulator). Toggling persists the selection so
* the WS transport can push activation when connected. */
export type AppRuntime = 'running' | 'simulated' | 'mesh-only';
export interface AppManifest {
/** Stable kebab-case id; matches the wasm-edge module name (e.g. `med_sleep_apnea`). */
id: string;
/** Human-readable name. */
name: string;
/** Category short-code. */
category: AppCategory;
/** Cargo crate the implementation lives in. */
crate: 'nvsim' | 'wifi-densepose-wasm-edge' | string;
/** One-liner description. */
summary: string;
/** Optional longer markdown body. */
body?: string;
/** Numeric event IDs this app emits (i32 codes from `event_types` mod). */
events?: number[];
/** Compute budget tier the module advertises. S=<5ms, M=<15ms, L=<50ms. */
budget?: 'S' | 'M' | 'L';
/** Default activation state when listed. */
active?: boolean;
/** Tags for fuzzy search and filtering. */
tags?: string[];
/** "Available", "Beta", or "Research" maturity. */
status: 'available' | 'beta' | 'research';
/** ADR back-reference. */
adr?: string;
/** What actually happens when active — see AppRuntime docs. */
runtime?: AppRuntime;
}
export const APPS: AppManifest[] = [
// ── Pipeline simulators ──────────────────────────────────────────────────
{
id: 'nvsim',
name: 'nvsim — NV-diamond magnetometer',
category: 'sim',
crate: 'nvsim',
summary:
'Deterministic forward simulator: scene → BiotSavart → NV ensemble → ADC → MagFrame stream + SHA-256 witness.',
budget: 'L',
active: true,
status: 'available',
tags: ['quantum', 'magnetometer', 'simulator', 'witness', 'wasm'],
adr: 'ADR-089',
runtime: 'running',
},
// ── Core sensing primitives (ADR-014/040 flagship modules) ───────────────
{
id: 'gesture',
name: 'Gesture (DTW)',
category: 'sig',
crate: 'wifi-densepose-wasm-edge',
summary: 'Dynamic-Time-Warping gesture classifier from CSI motion templates.',
events: [1],
budget: 'M',
status: 'available',
tags: ['hci', 'csi', 'classifier', 'dtw'],
adr: 'ADR-014',
runtime: 'mesh-only',
},
{
id: 'coherence',
name: 'Coherence gate',
category: 'sig',
crate: 'wifi-densepose-wasm-edge',
summary: 'Z-score coherence scoring + Accept/PredictOnly/Reject/Recalibrate gate.',
events: [2],
budget: 'S',
status: 'available',
tags: ['gate', 'csi', 'coherence', 'drift'],
adr: 'ADR-029',
runtime: 'simulated',
},
{
id: 'adversarial',
name: 'Adversarial-signal detector',
category: 'ais',
crate: 'wifi-densepose-wasm-edge',
summary:
'Physically-impossible-signal detector — multi-link consistency, used to flag spoofed CSI.',
events: [3],
budget: 'M',
status: 'available',
tags: ['security', 'csi', 'spoofing', 'mesh'],
adr: 'ADR-032',
runtime: 'simulated',
},
{
id: 'rvf',
name: 'RVF — Rust Verified Feature stream',
category: 'sig',
crate: 'wifi-densepose-wasm-edge',
summary: 'Verified-frame builder with SHA-256 hash + version metadata for the feature stream.',
budget: 'S',
status: 'available',
tags: ['witness', 'csi', 'hash'],
adr: 'ADR-040',
},
{
id: 'occupancy',
name: 'Occupancy estimator',
category: 'bld',
crate: 'wifi-densepose-wasm-edge',
summary: 'Through-wall presence + person-count via CSI amplitude perturbation.',
events: [300, 301, 302],
budget: 'S',
status: 'available',
tags: ['csi', 'building', 'presence'],
runtime: 'simulated',
},
{
id: 'vital_trend',
name: 'Vital-trend monitor',
category: 'med',
crate: 'wifi-densepose-wasm-edge',
summary: 'HR + BR trend tracking with bradycardia/tachycardia/apnea events.',
events: [100, 101, 102, 103, 104, 105],
budget: 'S',
status: 'available',
tags: ['medical', 'vitals', 'csi'],
adr: 'ADR-021',
runtime: 'simulated',
},
{
id: 'intrusion',
name: 'Intrusion detector',
category: 'sec',
crate: 'wifi-densepose-wasm-edge',
summary: 'Zone-based intrusion alert from CSI motion patterns.',
events: [200, 201],
budget: 'S',
status: 'available',
tags: ['security', 'zone', 'csi'],
runtime: 'simulated',
},
// ── Medical & Health (100-series) ────────────────────────────────────────
{ id: 'med_sleep_apnea', name: 'Sleep-apnea detector', category: 'med', crate: 'wifi-densepose-wasm-edge', summary: 'Episodic respiratory pause detection during sleep cycles.', events: [105], budget: 'S', status: 'available', tags: ['medical', 'sleep', 'breathing'] },
{ id: 'med_cardiac_arrhythmia', name: 'Cardiac arrhythmia', category: 'med', crate: 'wifi-densepose-wasm-edge', summary: 'Beat-to-beat irregularity classifier from cardiac micro-Doppler.', events: [103, 104], budget: 'M', status: 'available', tags: ['medical', 'cardiac', 'arrhythmia'] },
{ id: 'med_respiratory_distress', name: 'Respiratory distress', category: 'med', crate: 'wifi-densepose-wasm-edge', summary: 'Distress signature: rapid shallow breathing + accessory-muscle motion.', events: [101, 102], budget: 'S', status: 'available', tags: ['medical', 'breathing', 'icu'] },
{ id: 'med_gait_analysis', name: 'Gait analysis', category: 'med', crate: 'wifi-densepose-wasm-edge', summary: 'Stride length, cadence, asymmetry from through-wall CSI pose tracking.', budget: 'M', status: 'available', tags: ['medical', 'gait', 'pose'] },
{ id: 'med_seizure_detect', name: 'Seizure detector', category: 'med', crate: 'wifi-densepose-wasm-edge', summary: 'Tonic-clonic seizure motion signature.', budget: 'M', status: 'beta', tags: ['medical', 'neuro'] },
// ── Security (200-series) ────────────────────────────────────────────────
{ id: 'sec_perimeter_breach', name: 'Perimeter breach', category: 'sec', crate: 'wifi-densepose-wasm-edge', summary: 'Approach/departure detection at user-defined boundary segments.', events: [210, 211, 212, 213], budget: 'S', status: 'available', tags: ['security', 'perimeter'] },
{ id: 'sec_weapon_detect', name: 'Metal anomaly / weapon', category: 'sec', crate: 'wifi-densepose-wasm-edge', summary: 'Metal-perturbation flag in CSI; potential weapon presence (research).', events: [220, 221, 222], budget: 'M', status: 'research', tags: ['security', 'metal', 'csi'] },
{ id: 'sec_tailgating', name: 'Tailgating detector', category: 'sec', crate: 'wifi-densepose-wasm-edge', summary: 'Detect 2+ persons crossing a single-passage threshold.', events: [230, 231, 232], budget: 'S', status: 'available', tags: ['security', 'access-control'] },
{ id: 'sec_loitering', name: 'Loitering detector', category: 'sec', crate: 'wifi-densepose-wasm-edge', summary: 'Stationary occupancy past a configurable dwell threshold.', events: [240, 241, 242], budget: 'S', status: 'available', tags: ['security', 'dwell'] },
{ id: 'sec_panic_motion', name: 'Panic motion', category: 'sec', crate: 'wifi-densepose-wasm-edge', summary: 'High-energy distress motion: struggle / fleeing pattern.', events: [250, 251, 252], budget: 'S', status: 'beta', tags: ['security', 'distress'] },
// ── Smart Building (300-series) ──────────────────────────────────────────
{ id: 'bld_hvac_presence', name: 'HVAC presence', category: 'bld', crate: 'wifi-densepose-wasm-edge', summary: 'Occupied/activity-level/departure-countdown for HVAC zones.', events: [310, 311, 312], budget: 'S', status: 'available', tags: ['hvac', 'building', 'energy'] },
{ id: 'bld_lighting_zones', name: 'Lighting zones', category: 'bld', crate: 'wifi-densepose-wasm-edge', summary: 'Per-zone light on/dim/off cues from occupancy.', events: [320, 321, 322], budget: 'S', status: 'available', tags: ['lighting', 'building'] },
{ id: 'bld_elevator_count', name: 'Elevator count', category: 'bld', crate: 'wifi-densepose-wasm-edge', summary: 'Person count inside elevator car from CSI.', events: [330], budget: 'S', status: 'available', tags: ['elevator', 'building'] },
{ id: 'bld_meeting_room', name: 'Meeting-room utilization', category: 'bld', crate: 'wifi-densepose-wasm-edge', summary: 'Meeting size + duration analytics for booking systems.', budget: 'S', status: 'available', tags: ['meeting', 'analytics'] },
{ id: 'bld_energy_audit', name: 'Energy audit', category: 'bld', crate: 'wifi-densepose-wasm-edge', summary: 'Continuous occupancy-vs-HVAC-state audit for energy savings.', budget: 'M', status: 'available', tags: ['energy', 'audit'] },
// ── Retail (400-series) ──────────────────────────────────────────────────
{ id: 'ret_queue_length', name: 'Queue length', category: 'ret', crate: 'wifi-densepose-wasm-edge', summary: 'Live queue-length tracking for checkout / kiosks.', budget: 'S', status: 'available', tags: ['retail', 'queue'] },
{ id: 'ret_dwell_heatmap', name: 'Dwell heatmap', category: 'ret', crate: 'wifi-densepose-wasm-edge', summary: 'Per-zone dwell time accumulation; analytics-only export.', budget: 'M', status: 'available', tags: ['retail', 'heatmap'] },
{ id: 'ret_customer_flow', name: 'Customer flow', category: 'ret', crate: 'wifi-densepose-wasm-edge', summary: 'Origin-destination flow graph through a store layout.', budget: 'M', status: 'available', tags: ['retail', 'flow'] },
{ id: 'ret_table_turnover', name: 'Table turnover', category: 'ret', crate: 'wifi-densepose-wasm-edge', summary: 'Restaurant table seat / vacate transitions.', budget: 'S', status: 'available', tags: ['retail', 'restaurant'] },
{ id: 'ret_shelf_engagement', name: 'Shelf engagement', category: 'ret', crate: 'wifi-densepose-wasm-edge', summary: 'Reach-to-shelf gestures and dwell at product zones.', budget: 'M', status: 'available', tags: ['retail', 'shelf'] },
// ── Industrial (500-series) ──────────────────────────────────────────────
{ id: 'ind_forklift_proximity', name: 'Forklift proximity', category: 'ind', crate: 'wifi-densepose-wasm-edge', summary: 'Worker-near-forklift safety alert.', budget: 'S', status: 'available', tags: ['industrial', 'safety'] },
{ id: 'ind_confined_space', name: 'Confined-space monitor', category: 'ind', crate: 'wifi-densepose-wasm-edge', summary: 'Last-person-out detection + presence audit for OSHA confined-space entries.', budget: 'S', status: 'available', tags: ['industrial', 'osha'] },
{ id: 'ind_clean_room', name: 'Clean-room PPE / motion', category: 'ind', crate: 'wifi-densepose-wasm-edge', summary: 'Motion patterns consistent with proper PPE-clad movement.', budget: 'M', status: 'beta', tags: ['industrial', 'cleanroom'] },
{ id: 'ind_livestock_monitor', name: 'Livestock monitor', category: 'ind', crate: 'wifi-densepose-wasm-edge', summary: 'Vital-sign + activity tracking for stall-bound livestock.', budget: 'M', status: 'beta', tags: ['agriculture', 'livestock'] },
{ id: 'ind_structural_vibration', name: 'Structural vibration', category: 'ind', crate: 'wifi-densepose-wasm-edge', summary: 'Building/equipment micro-vibration via CSI phase derivative.', budget: 'M', status: 'research', tags: ['industrial', 'vibration'] },
// ── Signal primitives (600-series) ───────────────────────────────────────
{ id: 'sig_coherence_gate', name: 'Coherence gate (extended)', category: 'sig', crate: 'wifi-densepose-wasm-edge', summary: 'Hysteresis + multi-state coherence gate driving downstream apps.', budget: 'S', status: 'available', tags: ['gate', 'csi'] },
{ id: 'sig_flash_attention', name: 'Flash attention (CSI)', category: 'sig', crate: 'wifi-densepose-wasm-edge', summary: 'Edge-friendly attention block for CSI subcarrier weighting.', budget: 'M', status: 'beta', tags: ['attention', 'csi'] },
{ id: 'sig_temporal_compress', name: 'Temporal-tensor compress', category: 'sig', crate: 'wifi-densepose-wasm-edge', summary: 'RuVector temporal-tensor compression on the CSI buffer.', budget: 'M', status: 'available', tags: ['compress', 'tensor'] },
{ id: 'sig_sparse_recovery', name: 'Sparse recovery', category: 'sig', crate: 'wifi-densepose-wasm-edge', summary: '114→56 subcarrier sparse interpolation via L1 solver.', budget: 'M', status: 'available', tags: ['sparse', 'csi'] },
{ id: 'sig_mincut_person_match', name: 'Mincut person-match', category: 'sig', crate: 'wifi-densepose-wasm-edge', summary: 'Min-cut person assignment across multistatic frames.', budget: 'M', status: 'available', tags: ['mincut', 'matching'] },
{ id: 'sig_optimal_transport', name: 'Optimal transport', category: 'sig', crate: 'wifi-densepose-wasm-edge', summary: 'OT-based feature alignment between mesh nodes.', budget: 'M', status: 'beta', tags: ['ot', 'alignment'] },
// ── Online learning ──────────────────────────────────────────────────────
{ id: 'lrn_dtw_gesture_learn', name: 'DTW gesture learn', category: 'lrn', crate: 'wifi-densepose-wasm-edge', summary: 'On-device template learning for personalized gesture libraries.', budget: 'M', status: 'beta', tags: ['lifelong', 'gesture'] },
{ id: 'lrn_anomaly_attractor', name: 'Anomaly attractor', category: 'lrn', crate: 'wifi-densepose-wasm-edge', summary: 'Novelty detector with dynamic-attractor recall.', budget: 'M', status: 'research', tags: ['novelty', 'lifelong'] },
{ id: 'lrn_meta_adapt', name: 'Meta-adapt', category: 'lrn', crate: 'wifi-densepose-wasm-edge', summary: 'Meta-learning adapter for fast site-to-site transfer.', budget: 'L', status: 'research', tags: ['meta-learning'] },
{ id: 'lrn_ewc_lifelong', name: 'EWC++ lifelong', category: 'lrn', crate: 'wifi-densepose-wasm-edge', summary: 'Elastic-weight-consolidation gate to avoid catastrophic forgetting.', budget: 'M', status: 'beta', tags: ['lifelong', 'ewc'] },
// ── Spatial / graph ──────────────────────────────────────────────────────
{ id: 'spt_pagerank_influence', name: 'PageRank influence', category: 'spt', crate: 'wifi-densepose-wasm-edge', summary: 'Graph-influence ranking on the multistatic mesh.', budget: 'M', status: 'beta', tags: ['graph', 'pagerank'] },
{ id: 'spt_micro_hnsw', name: 'µHNSW vector index', category: 'spt', crate: 'wifi-densepose-wasm-edge', summary: 'Tiny HNSW index for AETHER re-ID embeddings on-device.', budget: 'M', status: 'available', tags: ['hnsw', 'reid'] },
{ id: 'spt_spiking_tracker', name: 'Spiking tracker', category: 'spt', crate: 'wifi-densepose-wasm-edge', summary: 'Spiking-network multi-target tracker.', budget: 'L', status: 'research', tags: ['snn', 'tracker'] },
// ── Temporal / planning ──────────────────────────────────────────────────
{ id: 'tmp_pattern_sequence', name: 'Pattern sequence', category: 'tmp', crate: 'wifi-densepose-wasm-edge', summary: 'Sequence-of-events pattern matcher (e.g. ingress→linger→egress).', budget: 'M', status: 'available', tags: ['temporal', 'pattern'] },
{ id: 'tmp_temporal_logic_guard', name: 'Temporal logic guard', category: 'tmp', crate: 'wifi-densepose-wasm-edge', summary: 'LTL/MTL safety-property guard over event streams.', budget: 'M', status: 'beta', tags: ['ltl', 'safety'] },
{ id: 'tmp_goap_autonomy', name: 'GOAP autonomy', category: 'tmp', crate: 'wifi-densepose-wasm-edge', summary: 'Goal-oriented action planning for adaptive routines.', budget: 'L', status: 'research', tags: ['planning', 'autonomy'] },
// ── AI safety ────────────────────────────────────────────────────────────
{ id: 'ais_prompt_shield', name: 'Prompt shield', category: 'ais', crate: 'wifi-densepose-wasm-edge', summary: 'Edge-side LLM prompt-injection guard for on-device assistants.', budget: 'M', status: 'beta', tags: ['security', 'llm'] },
{ id: 'ais_behavioral_profiler', name: 'Behavioral profiler', category: 'ais', crate: 'wifi-densepose-wasm-edge', summary: 'Anomalous-behaviour profiler (drift in motion habits).', budget: 'M', status: 'beta', tags: ['anomaly', 'behaviour'] },
// ── Quantum-flavoured ────────────────────────────────────────────────────
{ id: 'qnt_quantum_coherence', name: 'Quantum coherence', category: 'qnt', crate: 'wifi-densepose-wasm-edge', summary: 'Coherence diagnostics adapted for quantum-sensor signals.', budget: 'M', status: 'research', tags: ['quantum', 'coherence'] },
{ id: 'qnt_interference_search', name: 'Interference search', category: 'qnt', crate: 'wifi-densepose-wasm-edge', summary: 'Interferometric anomaly search across mesh viewpoints.', budget: 'L', status: 'research', tags: ['quantum', 'interference'] },
// ── Autonomy / mesh ──────────────────────────────────────────────────────
{ id: 'aut_psycho_symbolic', name: 'Psycho-symbolic agent', category: 'aut', crate: 'wifi-densepose-wasm-edge', summary: 'Symbolic-rule + neural-feature hybrid for low-power autonomy loops.', budget: 'L', status: 'research', tags: ['autonomy', 'symbolic'] },
{ id: 'aut_self_healing_mesh', name: 'Self-healing mesh', category: 'aut', crate: 'wifi-densepose-wasm-edge', summary: 'Mesh-topology repair with per-node health gossip.', budget: 'M', status: 'beta', tags: ['mesh', 'health'] },
// ── Exotic / Research (650-series) ───────────────────────────────────────
{ id: 'exo_ghost_hunter', name: 'Ghost hunter (anomaly)', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Empty-room CSI anomaly detector — impulsive/periodic/drift/random + hidden-presence sub-detector.', events: [650, 651, 652, 653], budget: 'S', status: 'available', tags: ['anomaly', 'paranormal', 'csi'], adr: 'ADR-041', runtime: 'simulated' },
{ id: 'exo_breathing_sync', name: 'Breathing sync', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Multi-person breathing synchrony analytics.', budget: 'M', status: 'beta', tags: ['breathing', 'sync'] },
{ id: 'exo_dream_stage', name: 'Dream-stage classifier', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'NREM/REM stage classification from breathing + micro-motion.', budget: 'M', status: 'research', tags: ['sleep', 'rem'] },
{ id: 'exo_emotion_detect', name: 'Emotion detector', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Coarse arousal/valence from breathing + heart-rate variability.', budget: 'M', status: 'research', tags: ['affect'] },
{ id: 'exo_gesture_language', name: 'Gesture language', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Sign-language pattern recognition.', budget: 'L', status: 'research', tags: ['hci', 'sign'] },
{ id: 'exo_happiness_score', name: 'Happiness score', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Aggregate well-being score from co-occupancy + activity dynamics.', budget: 'M', status: 'research', tags: ['affect', 'wellbeing'] },
{ id: 'exo_hyperbolic_space', name: 'Hyperbolic space embed', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Hyperbolic embeddings for hierarchical scene structure.', budget: 'L', status: 'research', tags: ['embedding', 'hyperbolic'] },
{ id: 'exo_music_conductor', name: 'Music conductor', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Map gesture energy to MIDI tempo/dynamics.', budget: 'M', status: 'research', tags: ['midi', 'art'] },
{ id: 'exo_plant_growth', name: 'Plant-growth tracker', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Slow CSI drift tracking for greenhouse foliage growth.', budget: 'L', status: 'research', tags: ['agriculture'] },
{ id: 'exo_rain_detect', name: 'Rain detector', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Outdoor CSI signature of rainfall.', budget: 'M', status: 'research', tags: ['weather'] },
{ id: 'exo_time_crystal', name: 'Time-crystal periodicity', category: 'exo', crate: 'wifi-densepose-wasm-edge', summary: 'Periodicity diagnostics with anti-aliasing harmonics.', budget: 'M', status: 'research', tags: ['periodicity'] },
];
export const CATEGORIES: Record<AppCategory, { label: string; color: string; range: string }> = {
sim: { label: 'Simulators', color: 'oklch(0.78 0.14 70)', range: '—' },
med: { label: 'Medical & Health', color: 'oklch(0.65 0.22 25)', range: '100199' },
sec: { label: 'Security & Safety', color: 'oklch(0.7 0.18 35)', range: '200299' },
bld: { label: 'Smart Building', color: 'oklch(0.78 0.12 195)', range: '300399' },
ret: { label: 'Retail & Hospitality', color: 'oklch(0.78 0.14 145)', range: '400499' },
ind: { label: 'Industrial', color: 'oklch(0.72 0.18 330)', range: '500599' },
sig: { label: 'Signal Processing', color: 'oklch(0.78 0.14 70)', range: '600619' },
lrn: { label: 'Online Learning', color: 'oklch(0.78 0.12 260)', range: '620639' },
spt: { label: 'Spatial / Graph', color: 'oklch(0.7 0.18 100)', range: '640659' },
tmp: { label: 'Temporal / Planning', color: 'oklch(0.7 0.16 50)', range: '660679' },
ais: { label: 'AI Safety', color: 'oklch(0.65 0.22 25)', range: '700719' },
qnt: { label: 'Quantum', color: 'oklch(0.72 0.18 290)', range: '720739' },
aut: { label: 'Autonomy', color: 'oklch(0.78 0.14 145)', range: '740759' },
exo: { label: 'Exotic / Research', color: 'oklch(0.72 0.18 330)', range: '650699' },
};
export interface AppActivation {
id: string;
/** Active in the current session. */
active: boolean;
/** Last activation timestamp. */
lastActivatedAt?: number;
/** Last event count seen (for the cards' counter). */
eventCount?: number;
}
export function defaultActivations(): AppActivation[] {
return APPS.map((a) => ({ id: a.id, active: a.active === true, eventCount: 0 }));
}
export function appsByCategory(): Record<AppCategory, AppManifest[]> {
const map = {} as Record<AppCategory, AppManifest[]>;
for (const c of Object.keys(CATEGORIES) as AppCategory[]) map[c] = [];
for (const a of APPS) map[a.category].push(a);
return map;
}
export function findApp(id: string): AppManifest | undefined {
return APPS.find((a) => a.id === id);
}
export function fuzzyMatch(query: string, app: AppManifest): number {
if (!query) return 1;
const q = query.toLowerCase();
let score = 0;
if (app.id.toLowerCase().includes(q)) score += 3;
if (app.name.toLowerCase().includes(q)) score += 3;
if (app.summary.toLowerCase().includes(q)) score += 1;
if (app.tags?.some((t) => t.toLowerCase().includes(q))) score += 2;
if (app.category === q) score += 5;
return score;
}
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@@ -1,52 +0,0 @@
/* IndexedDB-backed persistence for settings and saved scenes.
* Mirrors the mockup's `nvsim/kv` store. */
const DB_NAME = 'nvsim';
const DB_VER = 1;
const STORE = 'kv';
let dbPromise: Promise<IDBDatabase> | null = null;
function openDb(): Promise<IDBDatabase> {
if (dbPromise) return dbPromise;
dbPromise = new Promise<IDBDatabase>((resolve, reject) => {
const req = indexedDB.open(DB_NAME, DB_VER);
req.onupgradeneeded = () => {
const db = req.result;
if (!db.objectStoreNames.contains(STORE)) db.createObjectStore(STORE);
};
req.onsuccess = () => resolve(req.result);
req.onerror = () => reject(req.error);
});
return dbPromise;
}
export async function kvGet<T = unknown>(key: string): Promise<T | undefined> {
const db = await openDb();
return await new Promise<T | undefined>((resolve, reject) => {
const tx = db.transaction(STORE, 'readonly');
const r = tx.objectStore(STORE).get(key);
r.onsuccess = () => resolve(r.result as T | undefined);
r.onerror = () => reject(r.error);
});
}
export async function kvSet(key: string, value: unknown): Promise<void> {
const db = await openDb();
return await new Promise<void>((resolve, reject) => {
const tx = db.transaction(STORE, 'readwrite');
tx.objectStore(STORE).put(value, key);
tx.oncomplete = () => resolve();
tx.onerror = () => reject(tx.error);
});
}
export async function kvDelete(key: string): Promise<void> {
const db = await openDb();
return await new Promise<void>((resolve, reject) => {
const tx = db.transaction(STORE, 'readwrite');
tx.objectStore(STORE).delete(key);
tx.oncomplete = () => resolve();
tx.onerror = () => reject(tx.error);
});
}
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@@ -1,143 +0,0 @@
/* Common NvsimClient interface both WasmClient and WsClient implement it.
* Dashboard binds to this interface and never to a concrete client.
* Aligns with ADR-092 §5.2.
*/
export interface PipelineConfigJson {
digitiser?: {
f_s_hz: number;
f_mod_hz: number;
lp_cutoff_hz?: number;
};
sensor?: {
gamma_fwhm_hz?: number;
t1_s?: number;
t2_s?: number;
t2_star_s?: number;
contrast?: number;
n_spins?: number;
n_centers?: number;
shot_noise_disabled?: boolean;
};
dt_s?: number | null;
}
export interface SceneJson {
dipoles: { position: [number, number, number]; moment: [number, number, number] }[];
loops: {
centre: [number, number, number];
normal: [number, number, number];
radius: number;
current: number;
n_segments: number;
}[];
ferrous: {
position: [number, number, number];
volume: number;
susceptibility: number;
}[];
eddy: unknown[];
sensors: [number, number, number][];
ambient_field: [number, number, number];
}
export interface MagFrameRecord {
magic: number;
version: number;
flags: number;
sensorId: number;
tUs: bigint;
bPt: [number, number, number];
sigmaPt: [number, number, number];
noiseFloorPtSqrtHz: number;
temperatureK: number;
raw: Uint8Array;
}
export interface MagFrameBatch {
frames: MagFrameRecord[];
bytes: Uint8Array;
}
export type NvsimEvent =
| { type: 'log'; level: 'info' | 'warn' | 'err' | 'dbg' | 'ok'; msg: string }
| { type: 'witness'; hex: string }
| { type: 'fps'; value: number }
| { type: 'state'; running: boolean; t: number; framesEmitted: number };
export interface RunOpts { frames?: number }
/** One-shot pipeline run for "what would the sensor recover at this scene?"
* use cases. Doesn't disturb the running pipeline. */
export interface TransientRunResult {
bRecoveredT: [number, number, number];
bMagT: number;
noiseFloorPtSqrtHz: number;
sigmaPt: [number, number, number];
nFrames: number;
witnessHex: string;
}
export interface NvsimClient {
loadScene(scene: SceneJson): Promise<void>;
setConfig(cfg: PipelineConfigJson): Promise<void>;
setSeed(seed: bigint): Promise<void>;
reset(): Promise<void>;
run(opts?: RunOpts): Promise<void>;
pause(): Promise<void>;
step(direction: 'fwd' | 'back', dtMs: number): Promise<void>;
onFrames(cb: (batch: MagFrameBatch) => void): void;
onEvent(cb: (ev: NvsimEvent) => void): void;
generateWitness(samples: number): Promise<Uint8Array>;
verifyWitness(expected: Uint8Array): Promise<{ ok: true } | { ok: false; actual: Uint8Array }>;
exportProofBundle(): Promise<Blob>;
runTransient(scene: SceneJson, config: PipelineConfigJson, seed: bigint, samples: number): Promise<TransientRunResult>;
buildId(): Promise<string>;
close(): Promise<void>;
}
/** Parse one MagFrame from a 60-byte slice. Layout matches `nvsim::frame`. */
export function parseMagFrame(view: DataView, offset: number, raw: Uint8Array): MagFrameRecord {
// v1 layout: magic(u32) | version(u16) | flags(u16) | sensor_id(u16) | _reserved(u16) |
// t_us(u64) | b_pt[3](f32) | sigma_pt[3](f32) | noise_floor_pt_sqrt_hz(f32) |
// temperature_k(f32) — 60 bytes total. All little-endian.
const magic = view.getUint32(offset + 0, true);
const version = view.getUint16(offset + 4, true);
const flags = view.getUint16(offset + 6, true);
const sensorId = view.getUint16(offset + 8, true);
// skip 2 bytes reserved at offset+10
const tUs = view.getBigUint64(offset + 12, true);
const bx = view.getFloat32(offset + 20, true);
const by = view.getFloat32(offset + 24, true);
const bz = view.getFloat32(offset + 28, true);
const sx = view.getFloat32(offset + 32, true);
const sy = view.getFloat32(offset + 36, true);
const sz = view.getFloat32(offset + 40, true);
const noiseFloorPtSqrtHz = view.getFloat32(offset + 44, true);
const temperatureK = view.getFloat32(offset + 48, true);
return {
magic,
version,
flags,
sensorId,
tUs,
bPt: [bx, by, bz],
sigmaPt: [sx, sy, sz],
noiseFloorPtSqrtHz,
temperatureK,
raw: raw.subarray(offset, offset + 60),
};
}
export function parseFrameBatch(bytes: Uint8Array): MagFrameRecord[] {
const frameSize = 60;
const view = new DataView(bytes.buffer, bytes.byteOffset, bytes.byteLength);
const out: MagFrameRecord[] = [];
for (let off = 0; off + frameSize <= bytes.byteLength; off += frameSize) {
out.push(parseMagFrame(view, off, bytes));
}
return out;
}
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/* Default `NvsimClient` implementation. Talks to the Web Worker that
* hosts the nvsim WASM module. ADR-092 §5.4 + §6.3. */
import {
type NvsimClient,
type SceneJson,
type PipelineConfigJson,
type RunOpts,
type MagFrameBatch,
type NvsimEvent,
type TransientRunResult,
parseFrameBatch,
} from './NvsimClient';
interface PendingRequest<T = unknown> {
resolve: (v: T) => void;
reject: (err: Error) => void;
}
export interface WasmBootInfo {
buildVersion: string;
frameMagic: number;
frameBytes: number;
expectedWitnessHex: string;
}
export class WasmClient implements NvsimClient {
private worker: Worker;
private nextId = 1;
private pending = new Map<number, PendingRequest<unknown>>();
private frameSubs = new Set<(b: MagFrameBatch) => void>();
private eventSubs = new Set<(e: NvsimEvent) => void>();
private bootInfo: WasmBootInfo | null = null;
constructor() {
this.worker = new Worker(new URL('./worker.ts', import.meta.url), { type: 'module' });
this.worker.addEventListener('message', (ev) => this.onMessage(ev));
this.worker.addEventListener('error', (e) =>
this.eventSubs.forEach((s) => s({ type: 'log', level: 'err', msg: String(e.message) })),
);
}
private onMessage(ev: MessageEvent): void {
const m = ev.data as { type: string; id?: number; [k: string]: unknown };
if (m.type === 'frames') {
const buf = m.batch as ArrayBuffer;
const bytes = new Uint8Array(buf);
const frames = parseFrameBatch(bytes);
const batch: MagFrameBatch = { frames, bytes };
this.frameSubs.forEach((s) => s(batch));
const fps = m.fps as number;
if (fps > 0) {
this.eventSubs.forEach((s) => s({ type: 'fps', value: fps }));
}
return;
}
if (m.type === 'state') {
this.eventSubs.forEach((s) =>
s({
type: 'state',
running: Boolean(m.running),
t: 0,
framesEmitted: Number(m.framesEmitted ?? 0),
}),
);
return;
}
if (m.type === 'ready') {
return;
}
if (m.type === 'err' && m.id == null) {
this.eventSubs.forEach((s) =>
s({ type: 'log', level: 'err', msg: String(m.msg) }),
);
return;
}
if (typeof m.id === 'number' && this.pending.has(m.id)) {
const p = this.pending.get(m.id)!;
this.pending.delete(m.id);
if (m.type === 'err') p.reject(new Error(String(m.msg)));
else p.resolve(m);
}
}
private rpc<T = unknown>(msg: Record<string, unknown>, transfer: Transferable[] = []): Promise<T> {
const id = this.nextId++;
return new Promise<T>((resolve, reject) => {
this.pending.set(id, { resolve: resolve as (v: unknown) => void, reject });
this.worker.postMessage({ ...msg, id }, transfer);
});
}
async boot(): Promise<WasmBootInfo> {
if (this.bootInfo) return this.bootInfo;
// Pass Vite's resolved BASE_URL so the worker can locate /nvsim-pkg/
// under the same prefix the dashboard is served from (e.g. /RuView/nvsim/
// on GitHub Pages, "/" in dev).
const base = import.meta.env.BASE_URL ?? '/';
const r = await this.rpc<{ buildVersion: string; frameMagic: number; frameBytes: number; expectedWitnessHex: string }>(
{ type: 'boot', base },
);
this.bootInfo = {
buildVersion: r.buildVersion,
frameMagic: r.frameMagic,
frameBytes: r.frameBytes,
expectedWitnessHex: r.expectedWitnessHex,
};
return this.bootInfo;
}
async loadScene(scene: SceneJson): Promise<void> {
await this.rpc({ type: 'setScene', json: JSON.stringify(scene) });
}
async setConfig(cfg: PipelineConfigJson): Promise<void> {
await this.rpc({ type: 'setConfig', json: JSON.stringify(cfg) });
}
async setSeed(seed: bigint): Promise<void> {
await this.rpc({ type: 'setSeed', seed: Number(seed & 0xFFFFFFFFn) });
}
async reset(): Promise<void> {
await this.rpc({ type: 'reset' });
}
async run(_opts?: RunOpts): Promise<void> {
await this.rpc({ type: 'run' });
}
async pause(): Promise<void> {
await this.rpc({ type: 'pause' });
}
async step(_direction: 'fwd' | 'back', _dtMs: number): Promise<void> {
await this.rpc({ type: 'step' });
}
onFrames(cb: (batch: MagFrameBatch) => void): void { this.frameSubs.add(cb); }
onEvent(cb: (ev: NvsimEvent) => void): void { this.eventSubs.add(cb); }
async generateWitness(samples: number): Promise<Uint8Array> {
const r = await this.rpc<{ witness: ArrayBuffer; hex: string }>({ type: 'witnessGenerate', samples });
return new Uint8Array(r.witness);
}
async verifyWitness(expected: Uint8Array): Promise<{ ok: true } | { ok: false; actual: Uint8Array }> {
const buf = expected.slice().buffer;
const r = await this.rpc<{ ok: boolean; actual: ArrayBuffer; actualHex: string }>(
{ type: 'witnessVerify', samples: 256, expected: buf },
[buf],
);
if (r.ok) return { ok: true };
return { ok: false, actual: new Uint8Array(r.actual) };
}
async runTransient(
scene: SceneJson,
config: PipelineConfigJson,
seed: bigint,
samples: number,
): Promise<TransientRunResult> {
const r = await this.rpc<{
bRecoveredT: number[];
bMagT: number;
noiseFloorPtSqrtHz: number;
sigmaPt: number[];
nFrames: number;
witnessHex: string;
}>({
type: 'runTransient',
scene: JSON.stringify(scene),
config: JSON.stringify(config),
seed: Number(seed & 0xFFFFFFFFn),
samples,
});
return {
bRecoveredT: [r.bRecoveredT[0], r.bRecoveredT[1], r.bRecoveredT[2]],
bMagT: r.bMagT,
noiseFloorPtSqrtHz: r.noiseFloorPtSqrtHz,
sigmaPt: [r.sigmaPt[0], r.sigmaPt[1], r.sigmaPt[2]],
nFrames: r.nFrames,
witnessHex: r.witnessHex,
};
}
async exportProofBundle(): Promise<Blob> {
// Bundle = REFERENCE_SCENE_JSON + computed witness hex + version. Wraps
// the same artifacts `Proof::generate` produces natively. ADR-092 §6.1.
const w = await this.generateWitness(256);
const hex = Array.from(w).map((b) => b.toString(16).padStart(2, '0')).join('');
const info = this.bootInfo ?? (await this.boot());
const manifest = JSON.stringify(
{
kind: 'nvsim-proof-bundle',
version: info.buildVersion,
seed: '0x0000002A',
nSamples: 256,
witness: hex,
expected: info.expectedWitnessHex,
ok: hex === info.expectedWitnessHex,
ts: new Date().toISOString(),
},
null,
2,
);
return new Blob([manifest], { type: 'application/json' });
}
async buildId(): Promise<string> {
const r = await this.rpc<{ buildId: string }>({ type: 'buildId' });
return r.buildId;
}
async close(): Promise<void> {
this.worker.terminate();
}
}
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/* WebSocket transport client talks to a `nvsim-server` Axum host
* (v2/crates/nvsim-server). REST for control plane, binary WebSocket
* for the MagFrame stream. Mirrors the WasmClient interface so the
* dashboard can swap transports at runtime without code changes.
*
* ADR-092 §5.2 / §6.2.
*/
import {
type NvsimClient,
type SceneJson,
type PipelineConfigJson,
type RunOpts,
type MagFrameBatch,
type NvsimEvent,
type TransientRunResult,
parseFrameBatch,
} from './NvsimClient';
interface HealthBody {
nvsim_version: string;
magic: number;
frame_bytes: number;
expected_witness_hex: string;
}
interface VerifyBody {
ok: boolean;
actual_hex: string;
expected_hex: string;
}
interface WitnessBody {
witness_hex: string;
samples: number;
seed_hex: string;
}
export interface WsBootInfo {
buildVersion: string;
frameMagic: number;
frameBytes: number;
expectedWitnessHex: string;
}
/** Convert a base URL (e.g. `http://host:7878`) to its WebSocket peer (`ws://host:7878`). */
function toWsUrl(baseUrl: string): string {
if (baseUrl.startsWith('ws://') || baseUrl.startsWith('wss://')) return baseUrl;
return baseUrl.replace(/^http/, 'ws');
}
export class WsClient implements NvsimClient {
private baseUrl: string;
private wsUrl: string;
private ws: WebSocket | null = null;
private bootInfo: WsBootInfo | null = null;
private frameSubs = new Set<(b: MagFrameBatch) => void>();
private eventSubs = new Set<(e: NvsimEvent) => void>();
private running = false;
private framesEmitted = 0;
private fpsLast = performance.now();
private fpsCount = 0;
/** @param baseUrl e.g. `http://localhost:7878` */
constructor(baseUrl: string) {
this.baseUrl = baseUrl.replace(/\/$/, '');
this.wsUrl = `${toWsUrl(this.baseUrl)}/ws/stream`;
}
private async json<T>(path: string, init?: RequestInit): Promise<T> {
const res = await fetch(`${this.baseUrl}${path}`, {
...init,
headers: { 'content-type': 'application/json', ...(init?.headers ?? {}) },
});
if (!res.ok) throw new Error(`${path}: ${res.status} ${res.statusText}`);
return (await res.json()) as T;
}
async boot(): Promise<WsBootInfo> {
if (this.bootInfo) return this.bootInfo;
const h = await this.json<HealthBody>('/api/health');
this.bootInfo = {
buildVersion: h.nvsim_version,
frameMagic: h.magic,
frameBytes: h.frame_bytes,
expectedWitnessHex: h.expected_witness_hex,
};
this.openWs();
return this.bootInfo;
}
private openWs(): void {
if (this.ws) return;
const ws = new WebSocket(this.wsUrl);
ws.binaryType = 'arraybuffer';
ws.onopen = () => {
this.eventSubs.forEach((s) =>
s({ type: 'log', level: 'ok', msg: `ws/stream connected · ${this.wsUrl}` }),
);
};
ws.onclose = () => {
this.ws = null;
this.eventSubs.forEach((s) =>
s({ type: 'log', level: 'warn', msg: 'ws/stream closed' }),
);
};
ws.onerror = () => {
this.eventSubs.forEach((s) =>
s({ type: 'log', level: 'err', msg: `ws/stream error · ${this.wsUrl}` }),
);
};
ws.onmessage = (ev: MessageEvent) => {
if (!(ev.data instanceof ArrayBuffer)) return;
const bytes = new Uint8Array(ev.data);
const frames = parseFrameBatch(bytes);
if (frames.length === 0) return;
const batch: MagFrameBatch = { frames, bytes };
this.frameSubs.forEach((s) => s(batch));
this.framesEmitted += frames.length;
this.fpsCount += frames.length;
const now = performance.now();
if (now - this.fpsLast >= 1000) {
const fps = (this.fpsCount * 1000) / (now - this.fpsLast);
this.eventSubs.forEach((s) => s({ type: 'fps', value: fps }));
this.fpsLast = now;
this.fpsCount = 0;
}
};
this.ws = ws;
}
async loadScene(scene: SceneJson): Promise<void> {
await this.json('/api/scene', { method: 'PUT', body: JSON.stringify(scene) });
}
async setConfig(cfg: PipelineConfigJson): Promise<void> {
await this.json('/api/config', { method: 'PUT', body: JSON.stringify(cfg) });
}
async setSeed(seed: bigint): Promise<void> {
await this.json('/api/seed', {
method: 'PUT',
body: JSON.stringify({ seed_hex: '0x' + seed.toString(16).toUpperCase().padStart(16, '0') }),
});
}
async reset(): Promise<void> {
await this.json('/api/reset', { method: 'POST' });
this.running = false;
this.framesEmitted = 0;
this.eventSubs.forEach((s) => s({ type: 'state', running: false, t: 0, framesEmitted: 0 }));
}
async run(_opts?: RunOpts): Promise<void> {
await this.json('/api/run', { method: 'POST' });
this.running = true;
this.eventSubs.forEach((s) =>
s({ type: 'state', running: true, t: 0, framesEmitted: this.framesEmitted }),
);
}
async pause(): Promise<void> {
await this.json('/api/pause', { method: 'POST' });
this.running = false;
this.eventSubs.forEach((s) =>
s({ type: 'state', running: false, t: 0, framesEmitted: this.framesEmitted }),
);
}
async step(direction: 'fwd' | 'back', dtMs: number): Promise<void> {
await this.json('/api/step', { method: 'POST', body: JSON.stringify({ direction, dt_ms: dtMs }) });
}
onFrames(cb: (b: MagFrameBatch) => void): void { this.frameSubs.add(cb); }
onEvent(cb: (e: NvsimEvent) => void): void { this.eventSubs.add(cb); }
async generateWitness(samples: number): Promise<Uint8Array> {
const r = await this.json<WitnessBody>('/api/witness/generate', {
method: 'POST',
body: JSON.stringify({ samples }),
});
const out = new Uint8Array(32);
for (let i = 0; i < 32; i++) out[i] = parseInt(r.witness_hex.slice(i * 2, i * 2 + 2), 16);
return out;
}
async verifyWitness(expected: Uint8Array): Promise<{ ok: true } | { ok: false; actual: Uint8Array }> {
const expected_hex = Array.from(expected).map((b) => b.toString(16).padStart(2, '0')).join('');
const r = await this.json<VerifyBody>('/api/witness/verify', {
method: 'POST',
body: JSON.stringify({ expected_hex, samples: 256 }),
});
if (r.ok) return { ok: true };
const actual = new Uint8Array(32);
for (let i = 0; i < 32; i++) actual[i] = parseInt(r.actual_hex.slice(i * 2, i * 2 + 2), 16);
return { ok: false, actual };
}
async exportProofBundle(): Promise<Blob> {
const text = await fetch(`${this.baseUrl}/api/export-proof`, { method: 'POST' }).then((r) => r.text());
return new Blob([text], { type: 'application/json' });
}
async runTransient(
scene: SceneJson,
config: PipelineConfigJson,
_seed: bigint,
samples: number,
): Promise<TransientRunResult> {
// Server doesn't expose a transient route in V1 — the dashboard's
// Ghost Murmur sandbox falls back to the WASM client when transport
// is WS. Stub here returns a zero-result so the caller can detect.
void scene; void config; void samples;
return {
bRecoveredT: [0, 0, 0],
bMagT: 0,
noiseFloorPtSqrtHz: 0,
sigmaPt: [0, 0, 0],
nFrames: 0,
witnessHex: '(transient route not available in WS transport — V1 limitation)',
};
}
async buildId(): Promise<string> {
const info = this.bootInfo ?? (await this.boot());
return `nvsim@${info.buildVersion} (ws)`;
}
async close(): Promise<void> {
this.ws?.close();
this.ws = null;
}
}
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/* Web Worker hosting the nvsim WASM module.
*
* Boots `/nvsim-pkg/nvsim.js`, instantiates `WasmPipeline`, then
* postMessage-RPCs with the main thread. Frame batches are returned
* as `ArrayBuffer` transfers so we don't pay a copy on the hot path.
*
* ADR-092 §5.4.
*/
/// <reference lib="WebWorker" />
const ws = self as unknown as DedicatedWorkerGlobalScope;
interface WasmPipelineApi {
run(n: number): Uint8Array;
runWithWitness(n: number): { frames: Uint8Array; witness: Uint8Array; frameCount: number };
free?: () => void;
}
type WasmPipelineCtor = new (sceneJson: string, configJson: string, seed: number) => WasmPipelineApi;
type WasmPipelineStatic = WasmPipelineCtor & {
buildVersion(): string;
frameMagic(): number;
frameBytes(): number;
};
interface TransientResult {
bRecoveredT: Float64Array;
bMagT: number;
noiseFloorPtSqrtHz: number;
sigmaPt: Float64Array;
nFrames: number;
witnessHex: string;
}
interface NvsimPkg {
default: (input?: unknown) => Promise<unknown>;
WasmPipeline: WasmPipelineStatic;
referenceSceneJson: () => string;
expectedReferenceWitnessHex: () => string;
hexWitness: (b: Uint8Array) => string;
referenceWitness: () => Uint8Array;
runTransient: (sceneJson: string, configJson: string, seed: number, nSamples: number) => TransientResult;
}
let _WasmPipeline!: WasmPipelineStatic;
let referenceSceneJson!: () => string;
let expectedReferenceWitnessHex!: () => string;
let hexWitness!: (b: Uint8Array) => string;
let referenceWitness!: () => Uint8Array;
let runTransient!: (sceneJson: string, configJson: string, seed: number, nSamples: number) => TransientResult;
async function loadPkg(base: string): Promise<void> {
// `base` is the dashboard's BASE_URL injected by Vite, prefixed with the
// origin so we get an absolute URL the dynamic import can resolve. In dev
// this is "/", in prod under GitHub Pages it's "/RuView/nvsim/".
const absoluteBase = new URL(base, ws.location.origin).href;
const pkgUrl = new URL('nvsim-pkg/nvsim.js', absoluteBase).href;
const pkg = (await import(/* @vite-ignore */ pkgUrl)) as NvsimPkg;
await pkg.default();
_WasmPipeline = pkg.WasmPipeline;
referenceSceneJson = pkg.referenceSceneJson;
expectedReferenceWitnessHex = pkg.expectedReferenceWitnessHex;
hexWitness = pkg.hexWitness;
referenceWitness = pkg.referenceWitness;
runTransient = pkg.runTransient;
}
let pipeline: WasmPipelineApi | null = null;
let configJson = '';
let sceneJson = '';
let seed = BigInt(0xCAFEBABE);
let running = false;
let timer: number | null = null;
let framesEmitted = 0;
let tStart = 0;
function ensureRebuild(): void {
if (!sceneJson) sceneJson = referenceSceneJson();
if (!configJson) {
configJson = JSON.stringify({
digitiser: { f_s_hz: 10000, f_mod_hz: 1000 },
sensor: {
gamma_fwhm_hz: 1.0e6,
t1_s: 5.0e-3,
t2_s: 1.0e-6,
t2_star_s: 200e-9,
contrast: 0.03,
n_spins: 1.0e12,
shot_noise_disabled: false,
},
dt_s: null,
});
}
pipeline?.free?.();
pipeline = new _WasmPipeline(sceneJson, configJson, Number(seed & 0xFFFFFFFFn));
}
function post(msg: unknown, transfer: Transferable[] = []): void {
// postMessage Transferable overload: pass transfer list as 2nd arg
(ws.postMessage as (msg: unknown, t: Transferable[]) => void)(msg, transfer);
}
function startTimer(): void {
if (timer !== null) return;
tStart = performance.now();
framesEmitted = 0;
const tick = (): void => {
if (!running || !pipeline) return;
// Per-tick: simulate 32 frames; push as one batch.
const n = 32;
const bytes = pipeline.run(n);
framesEmitted += n;
const elapsed = (performance.now() - tStart) / 1000;
const fps = elapsed > 0 ? framesEmitted / elapsed : 0;
post(
{ type: 'frames', batch: bytes.buffer, count: n, fps, framesEmitted },
[bytes.buffer],
);
timer = ws.setTimeout(tick, 16);
};
timer = ws.setTimeout(tick, 0);
}
function stopTimer(): void {
if (timer !== null) {
ws.clearTimeout(timer);
timer = null;
}
}
ws.addEventListener('message', async (ev: MessageEvent): Promise<void> => {
const m = ev.data as { type: string; id?: number; [k: string]: unknown };
try {
switch (m.type) {
case 'boot': {
const base = (m.base as string | undefined) ?? '/';
await loadPkg(base);
ensureRebuild();
post({
type: 'booted',
id: m.id,
buildVersion: _WasmPipeline.buildVersion(),
frameMagic: _WasmPipeline.frameMagic(),
frameBytes: _WasmPipeline.frameBytes(),
expectedWitnessHex: expectedReferenceWitnessHex(),
});
break;
}
case 'setScene': {
sceneJson = m.json as string;
ensureRebuild();
post({ type: 'ack', id: m.id });
break;
}
case 'setConfig': {
configJson = m.json as string;
ensureRebuild();
post({ type: 'ack', id: m.id });
break;
}
case 'setSeed': {
seed = BigInt(m.seed as string | number | bigint);
ensureRebuild();
post({ type: 'ack', id: m.id });
break;
}
case 'reset': {
stopTimer();
running = false;
ensureRebuild();
framesEmitted = 0;
post({ type: 'ack', id: m.id });
post({ type: 'state', running: false, framesEmitted });
break;
}
case 'run': {
if (!pipeline) ensureRebuild();
running = true;
startTimer();
post({ type: 'ack', id: m.id });
post({ type: 'state', running: true, framesEmitted });
break;
}
case 'pause': {
running = false;
stopTimer();
post({ type: 'ack', id: m.id });
post({ type: 'state', running: false, framesEmitted });
break;
}
case 'step': {
if (!pipeline) ensureRebuild();
const bytes = pipeline!.run(1);
framesEmitted += 1;
post(
{ type: 'frames', batch: bytes.buffer, count: 1, fps: 0, framesEmitted },
[bytes.buffer],
);
post({ type: 'ack', id: m.id });
break;
}
case 'witnessGenerate': {
if (!pipeline) ensureRebuild();
const samples = (m.samples as number) ?? 256;
const result = pipeline!.runWithWitness(samples) as {
frames: Uint8Array;
witness: Uint8Array;
frameCount: number;
};
const hex = hexWitness(result.witness);
post(
{
type: 'witness',
id: m.id,
witness: result.witness.buffer,
hex,
frameCount: result.frameCount,
},
[result.witness.buffer],
);
break;
}
case 'witnessVerify': {
// Verify always runs the *canonical* reference scene at seed=42, N=256
// so the witness matches Proof::EXPECTED_WITNESS_HEX byte-for-byte.
// The user's working scene/config/seed don't affect the witness.
const expectedBuf = m.expected as ArrayBuffer;
const expected = new Uint8Array(expectedBuf);
const actual = referenceWitness();
let ok = actual.length === expected.length;
if (ok) {
for (let i = 0; i < expected.length; i++) {
if (actual[i] !== expected[i]) { ok = false; break; }
}
}
const actualBuf = actual.slice().buffer;
post(
{
type: 'verify',
id: m.id,
ok,
actual: actualBuf,
actualHex: hexWitness(actual),
},
[actualBuf],
);
break;
}
case 'runTransient': {
const sceneJson = m.scene as string;
const configJson = m.config as string;
const seed = (m.seed as number) ?? 0;
const samples = (m.samples as number) ?? 64;
const r = runTransient(sceneJson, configJson, seed, samples);
post({
type: 'transient',
id: m.id,
bRecoveredT: Array.from(r.bRecoveredT),
bMagT: r.bMagT,
noiseFloorPtSqrtHz: r.noiseFloorPtSqrtHz,
sigmaPt: Array.from(r.sigmaPt),
nFrames: r.nFrames,
witnessHex: r.witnessHex,
});
break;
}
case 'buildId': {
post({
type: 'buildId',
id: m.id,
buildId: `nvsim@${_WasmPipeline.buildVersion()}`,
});
break;
}
default:
post({ type: 'err', id: m.id, msg: `unknown op ${m.type}` });
}
} catch (e) {
post({ type: 'err', id: m.id, msg: (e as Error).message ?? String(e) });
}
});
post({ type: 'ready' });

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