Files
rUv 0bffe27288 feat(adr-117): pip wifi-densepose modernization (PIP-PHOENIX) + ruview sibling release (#786)
* docs(adr-117): seed branch — ADR-117 pip-modernization spec + soul-signature research bundle

Two artifacts landing together on this new branch as the prerequisite
documentation for the v2.0.0 Python wheel modernization work:

1. **docs/adr/ADR-117-pip-wifi-densepose-modernization.md** (644 lines)
   — Plan to bring the 2025-published `wifi-densepose` PyPI package
   (last release v1.1.0, 2025-06-07, 11.5 months out of sync) up to
   the current Rust v2/ workspace SOTA. Recommends PyO3 + maturin
   with abi3-py310 (one binary covers Python 3.10–3.13 per OS/arch),
   first-wheel scope = core + vitals + signal crates (~5 MB), v1.99.0
   tombstone + 90-day un-yank window for v1.1.0, v2.0.0 hard break.
   Open questions catalogued; phases P1–P6+ laid out with concrete
   acceptance criteria.

2. **docs/research/soul/** (5 files, ~1,450 lines) — Soul Signature
   research spec: 7-channel electromagnetic biometric fingerprint
   (AETHER 128-dim + cardiac HR/HRV + cardiac waveform morphology +
   respiratory pattern + gait timing + skeletal proportions +
   subcarrier reflection profile), fused into one RVF graph file.
   Includes 60s scanning protocol, 5-layer security model,
   threat-model + mitigations, references to existing ADRs (014,
   021, 024, 027, 030, 039, 079, 106, 108, 109, 110, 115). Marked
   "Research Specification (Pre-Implementation)". Explicit "what
   this is NOT" disclaimers preempt pseudoscience drift; every
   discriminative-power claim either cites a measurement or is
   marked "open research; baseline TBD".

Branch off main at HEAD; ready for /loop 10m implementation
iterations.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(adr-117/p1): scaffold python/ workspace — PyO3 + maturin + smoke tests (refs #785)

ADR-117 P1 — the python/ directory is now a working maturin-buildable
crate that produces the v2.x replacement for the legacy pure-Python
wifi-densepose==1.1.0 PyPI wheel.

## What lands

- `python/Cargo.toml` — PyO3 0.22 with `extension-module` + `abi3-py310`
  (one binary covers Python 3.10–3.13 per OS/arch — keeps the
  cibuildwheel matrix to 5 wheels per release, not 20). Depends on
  `wifi-densepose-core` from the existing v2/ workspace via relative
  path.

- `python/pyproject.toml` — maturin>=1.7 build backend with
  `python-source = "python"` and `module-name = "wifi_densepose._native"`
  so the compiled module loads as an internal underscore-private
  submodule of the user-facing `wifi_densepose` package. PEP 621
  metadata + classifiers + project URLs. Optional-deps:
  `wifi-densepose[client]` for the P4 WS/MQTT pure-Python layer,
  `wifi-densepose[dev]` for the test toolchain (pytest, ruff, mypy).

- `python/src/lib.rs` — minimal `#[pymodule] wifi_densepose_native`
  exporting `__rust_version__`, `__rust_build_tag__`,
  `__build_features__`, and a `hello()` smoke function. P2 will land
  the core type bindings here.

- `python/wifi_densepose/__init__.py` — pure-Python facade re-exporting
  the compiled module's symbols under their stable user-facing names.
  Docstring teaches the v1→v2 migration story up-front.

- `python/wifi_densepose/py.typed` — PEP 561 marker so `mypy --strict`
  in user code treats the wheel as fully typed (real stubs land in P2).

- `python/tests/test_smoke.py` — 6 P1 acceptance tests:
  1. package imports without error
  2. version string is PEP 440-compliant
  3. `__rust_version__` is reachable from Python (the diagnostic
     surface ADR-117 §5.2 promised)
  4. `__build_features__` lists `p1-scaffold` marker
  5. `wifi_densepose.hello()` returns "ok" (FFI round-trip)
  6. `wifi_densepose._native` is reachable but the leading underscore
     conveys "private; users should import the parent package"

- `python/README.md` — phase ledger, local build instructions
  (`maturin develop`), layout diagram.

## What's deferred to P2+

- Core type bindings (`CsiFrame`, `Keypoint`, `PoseEstimate`) — P2
- Vitals + signal DSP bindings + witness v2 — P3
- Pure-Python WS/MQTT client layer (`wifi_densepose[client]`) — P4
- cibuildwheel + PyPI publish — P5
- v1.99.0 tombstone — concurrent with P5

The new `python/` crate is intentionally OUTSIDE the v2/ Cargo
workspace — it has its own Cargo.toml with `[package]` not
`[workspace.package]` inheritance — to keep maturin's `python-source`
+ `module-name` config self-contained and to avoid forcing every
`cargo test --workspace` invocation in v2/ to compile pyo3.

Refs ADR-117 §5 (Detailed design) and §6 (Phased migration).
Refs #785 (tracking issue).

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(adr-117/p1): standalone Cargo.toml + python-source=. + #[pyo3(name=_native)] (P1 GREEN)

Three fixes to make maturin develop actually work locally:

1. `python/Cargo.toml` removed `*.workspace = true` inheritance —
   the python/ crate is intentionally outside the v2/ workspace
   (ADR-117 §5.2) so it needs every `[package]` field local.

2. `python/pyproject.toml` `python-source = "python"` was wrong
   because pyproject.toml lives at python/ — maturin was looking for
   python/python/. Changed to `python-source = "."` so the
   `wifi_densepose/` package directory sibling-to-pyproject is found.

3. `python/src/lib.rs` `#[pymodule] fn wifi_densepose_native` →
   `#[pymodule] #[pyo3(name = "_native")] fn wifi_densepose_native`.
   PyO3 generates `PyInit__native` from the pyo3-name attribute, which
   must match the `module-name` in pyproject.toml's [tool.maturin]
   block ("wifi_densepose._native"). Without this attribute the wheel
   builds but `import wifi_densepose._native` fails with
   ModuleNotFoundError.

## Local validation (P1 acceptance gate)

```
$ python -m venv .venv && .venv/Scripts/python -m pip install maturin pytest
$ VIRTUAL_ENV=… maturin develop --release
…
    Finished `release` profile [optimized] target(s)
📦 Built wheel for abi3 Python ≥ 3.10
🛠 Installed wifi-densepose-2.0.0a1

$ .venv/Scripts/python -c 'import wifi_densepose; print(wifi_densepose.__version__, wifi_densepose.__rust_version__, wifi_densepose.hello())'
2.0.0a1 2.0.0-alpha.1 ok

$ .venv/Scripts/python -m pytest tests/ -v
tests/test_smoke.py::test_package_imports PASSED
tests/test_smoke.py::test_version_string_well_formed PASSED
tests/test_smoke.py::test_rust_version_surfaced PASSED
tests/test_smoke.py::test_build_features_listed PASSED
tests/test_smoke.py::test_hello_returns_ok PASSED
tests/test_smoke.py::test_native_module_private PASSED
======================== 6 passed in 0.05s =========================
```

P1 closed. Moving to P2 (core type bindings).

Refs #785, ADR-117 §6.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(adr-117/p2): Keypoint + KeypointType bindings — 23 new tests (29/29 GREEN)

Lands the first chunk of P2: PyO3 bindings for `Keypoint` and
`KeypointType` from `wifi_densepose_core`. Bound types surface to
Python as `wifi_densepose.Keypoint` / `wifi_densepose.KeypointType`.

## Design choices that affect the API surface

1. **`Confidence` is NOT bound as a separate class.** Users hate
   wrapping a float in a constructor. Python-side, confidence is just
   a `float in [0.0, 1.0]`; the binding validates on construction
   (`ValueError` for out-of-range, matching the Rust core error).

2. **`KeypointType` is a `#[pyclass(eq, eq_int, hash, frozen)]` enum**
   — hashable so users can drop it into dicts/sets (the most common
   pattern in pose-analysis notebooks: `keypoints_by_type[k.type] = k`).

3. **`Keypoint.__init__` keyword-only `z`** so 2D users don't have to
   write `None` and 3D users get a clear named arg:
   `Keypoint(KeypointType.LeftWrist, 0.2, 0.4, 0.8, z=0.1)`.

4. **`Keypoint` is `#[pyclass(frozen)]`** — no in-place mutation. The
   Rust core type is immutable through Copy + Hash + Eq, and exposing
   setters from Python would create a copy-vs-reference inconsistency
   between languages.

## Files

- `python/src/bindings/keypoint.rs` — 220 lines of `#[pymethods]`
  wrappers + Rust↔Python enum round-trip
- `python/src/lib.rs` — `mod bindings { pub mod keypoint; }` +
  `bindings::keypoint::register(m)?` call from `#[pymodule]`
- `python/wifi_densepose/__init__.py` — re-exports `Keypoint` and
  `KeypointType` at the package root
- `python/tests/test_keypoint.py` — 23 tests covering:
  - 17-element COCO ordering of `KeypointType.all()`
  - index→type mapping for every variant
  - snake_name matches COCO spec
  - `is_face()` / `is_upper_body()` predicates
  - hashability (the bug I caught when I added the set-based face
    test — fixed by adding `hash` to the `#[pyclass]` attribute)
  - 2D + 3D constructor variants
  - position_2d / position_3d tuples
  - is_visible threshold
  - confidence validation (Err on out-of-range)
  - distance_to (2D Euclidean, 3D Euclidean, fallback when one is 2D
    and the other is 3D)
  - __repr__ + __eq__
  - the new `p2-keypoint-bindings` feature marker landed

## Local validation

\`\`\`
$ cd python && .venv/Scripts/python -m pytest tests/ -v
tests/test_smoke.py::test_package_imports PASSED
tests/test_smoke.py::test_version_string_well_formed PASSED
tests/test_smoke.py::test_rust_version_surfaced PASSED
tests/test_smoke.py::test_build_features_listed PASSED
tests/test_smoke.py::test_hello_returns_ok PASSED
tests/test_smoke.py::test_native_module_private PASSED
tests/test_keypoint.py::test_keypoint_type_all_returns_17 PASSED
…
======================== 29 passed in 0.06s =========================
\`\`\`

Wheel size after both bindings: still well under the 5 MB ADR §5.4
budget (release build with --strip on Windows: ~340 KB).

Also adds `python/.gitignore` to prevent the `.venv/` + `target/` +
`_native.abi3.pyd` artifacts from getting committed.

## What's left in P2

CsiFrame + PoseEstimate bindings land in the next iteration. They're
larger (CsiFrame has the subcarrier buffer; PoseEstimate has
17×Keypoint + BoundingBox + track_id + score). Pattern is now proven
so they go faster.

Refs #785, ADR-117 §6.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(adr-117/p2): BoundingBox + PersonPose + PoseEstimate — P2 COMPLETE (57/57 tests GREEN)

Lands the second + third chunks of P2: PyO3 bindings for `BoundingBox`,
`PersonPose`, `PoseEstimate` from `wifi_densepose_core`. Combined with
the prior Keypoint + KeypointType bindings (fd0568caa), this closes
ADR-117 §6 P2.

## Coverage

| Type | Bound | Tests | Mutability |
|---|---|---|---|
| Confidence | exposed as `float` with validation | (covered in keypoint tests) | n/a |
| KeypointType | `#[pyclass(eq, eq_int, hash, frozen)]` | 7 tests | immutable |
| Keypoint | `#[pyclass(frozen)]` | 16 tests | immutable |
| BoundingBox | `#[pyclass(frozen)]` | 8 tests | immutable |
| PersonPose | `#[pyclass]` (mutable, builder-style) | 12 tests | mutable |
| PoseEstimate | `#[pyclass(frozen)]` | 8 tests | immutable |

Smoke (P1) + new tests: **57/57 PASS** locally on Windows.

## What's deferred to P3

CsiFrame intentionally NOT bound in P2 because it uses
`Array2<Complex64>` (ndarray) — the natural Python surface is via the
`numpy` pyo3 bridge, which lands in P3 alongside the vitals + signal
DSP bindings. Binding CsiFrame without numpy interop would force
users to materialise lists of tuples which is a worse API than
`csi_frame.amplitude_array()` returning an ndarray.

## Design choices that affect the API surface

1. **PersonPose.keypoints() returns a dict keyed by KeypointType**
   instead of a fixed-length list with None slots. Pythonistas don't
   want to know the underlying storage is `[Option<Keypoint>; 17]`.

2. **PoseEstimate.id and .timestamp exposed as strings** (UUID + ISO)
   rather than as bound `FrameId` / `Timestamp` types. Users in
   notebooks rarely compare UUIDs structurally; strings are good
   enough for diagnostics and don't bloat the bindings.

3. **PersonPose is MUTABLE** (`#[pyclass]` without `frozen`) so users
   can build poses incrementally with `set_keypoint`/`set_bbox`/
   `set_id`. PoseEstimate is `frozen` because once constructed it
   represents a snapshot.

## Three PyO3 0.22 gotchas surfaced this iteration

1. `#[pymethods]` getters are NOT accessible from other Rust modules
   — need a separate `impl PyKeypoint { pub(crate) fn inner(&self)
   -> &Keypoint { ... } }` block for cross-module use.

2. `PyDict::new(py)` was removed in PyO3 0.21 → 0.22 in favour of
   `PyDict::new_bound(py)`. (Confusing because `Bound<'py, PyDict>`
   is the return type either way.)

3. `dict.set_item(K, V)` requires both K and V to impl
   `ToPyObject`. `#[pyclass]` types impl `IntoPy<PyObject>` but NOT
   `ToPyObject` — workaround: convert via `.into_py(py)` first, then
   `set_item(py_object_k, py_object_v)`.

Saved as PyO3 0.22 binding patterns memory at the horizon-tracker
level so future loop workers don't re-learn them.

## Local validation

\`\`\`
$ cd python && .venv/Scripts/python -m pytest tests/ -v
…
======================== 57 passed in 0.24s =========================
\`\`\`

Wheel size: still ~340 KB on Windows release build.

Refs #785, ADR-117 §6 (P2 done — ready for P3 vitals + signal DSP +
numpy bridge + witness v2).

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr-117): add BFLD support (§5.7a + P3.5 phase + §11.11/12 open questions)

Per maintainer feedback during P3 implementation, expand ADR-117 to
include Beamforming Feedback Loop Data (BFLD) as a first-class binding
target alongside CSI. BFLD is the transmitter-side, AP-station-loop
view of the WiFi channel (802.11ac/ax/be compressed beamforming feedback
frames) — complementary to receiver-side CSI, with three properties
that make it strategically important for the pip wheel:

1. **Up to 996 subcarriers per HE160 frame** (vs 242 for HE-LTF CSI on
   ESP32-C6, vs 52 for HT-LTF on ESP32-S3) — much denser per-subcarrier
   reflection profile
2. **Works on stock 802.11ac+ hardware** — no Nexmon patch, no ESP32
   monitor mode, no firmware drift. Captured via tcpdump/Wireshark +
   BFR dissector, or via `mac80211` debugfs on Linux 6.10+
3. **Direct input for the soul-signature spec** (`docs/research/soul/`)
   — the seven-channel biometric needs dense subcarrier reflection;
   BFLD provides it without specialized hardware

## Three additions to ADR-117

### §5.7a — New binding-target subsection
Comparison table CSI vs BFLD; binding strategy with forward-compat
stub Rust impl pending the future `wifi-densepose-bfld` crate; the
three Python types that ship in P3.5:

- `BfldFrame` (frozen) — one compressed feedback matrix snapshot
- `BfldReport` (frozen) — aggregator over a 60-s scan window
- `BfldKind` enum — `CompressedHE20/40/80/160`, `UncompressedHT20/40`

### §6 P3.5 — Concurrent-with-P3 phase
Checkbox plan for the bindings module + stub Rust storage + numpy
bridge for `feedback_matrix` (Complex64 ndarray, same approach as
`CsiFrame.amplitude` from P3). Lands in the same wheel as P3, no
schedule cushion needed.

### §11.11/12 — Two new open questions
- **§11.11** — Should the future BFR ingestion Rust crate be a new
  `wifi-densepose-bfld` workspace member, or extend `-signal`?
  *Tentative: new dedicated crate. Wireshark BFR dissector is ~2k
  lines and would bloat `-signal`; ingestion is optional for many
  deployments; keep `-signal` lean.*
- **§11.12** — Per-vendor BFR variant compatibility (Broadcom vs
  Intel vs Qualcomm vs MediaTek differ in psi/phi quantization +
  matrix entry ordering). How much normalisation in the Python
  binding vs. the future Rust crate? *Tentative: Python binding is
  dumb (numpy ndarray in/out); future Rust crate owns per-vendor
  normalisation via a `Vendor` enum on the constructor.*

### §12 — BFLD reference list
- Hernandez & Bulut, ACM TOSN 2024 (first systematic survey of
  BFR-as-sensing)
- Yousefi et al., MobiSys 2023 (practical breath + HR extraction)
- IEEE 802.11ax-2021 §27.3.10 (frame format)
- Wireshark `packet-ieee80211.c` dissector
- AX210 Linux mac80211 debugfs path (kernel 6.10+)

ADR line count: 644 → 807 (+163). Refs #785 (tracking issue).

The implementation work for P3.5 lands in the next /loop iteration
alongside P3 vitals + signal DSP bindings.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(adr-117/p3+p3.5): vitals + BFLD bindings

P3 — Vital sign extraction bindings (wifi-densepose-vitals):
- VitalStatus enum (eq, eq_int, hash, frozen) — Valid/Degraded/Unreliable/Unavailable
- VitalEstimate (frozen) — value_bpm + confidence + status
- VitalReading (frozen) — HR + BR + signal quality composite
- BreathingExtractor — 0.1–0.5 Hz bandpass + zero-crossing
- HeartRateExtractor — 0.8–2.0 Hz bandpass + autocorrelation
- py.allow_threads on extract() hot loops (Q5 audit confirmed
  core/vitals/signal are pure-sync — zero tokio deps, safe to release
  GIL with no embedded runtime needed)
- 17 tests covering construction, getters, frozen immutability,
  esp32_default + explicit ctors, synthetic-signal end-to-end

P3.5 — BFLD bindings (forward-compat surface, stub Rust):
- BfldKind enum — CompressedHE20/40/80/160 + UncompressedHT20/40
  with n_subcarriers, bandwidth_mhz, is_he metadata getters
- BfldFrame (frozen) — from_compressed_feedback() accepts numpy
  Complex64 ndarray [Nr x Nc x Nsc], validates dims against kind,
  feedback_matrix() returns lossless roundtrip ndarray
- BfldReport — aggregates frames, rejects mismatched kinds,
  computes inverse-CV coherence score
- 19 tests covering all 6 PHY variants + numpy roundtrip +
  dim-mismatch error + aggregation
- Real Rust ingestion (wifi-densepose-bfld crate) lands post-v2.0
  per ADR-117 §11.11/12 — Python API will not change

Total Python test count: 93 (was 57, +36 P3+P3.5). All passing.

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md
Refs: #785

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(adr-117/p4): pure-Python WS/MQTT client layer

New sub-package `wifi_densepose.client` (no PyO3, no Rust deps):

- ws.SensingClient — asyncio websockets>=12 wrapper for the Rust
  sensing-server /ws/sensing endpoint. Yields typed dataclasses
  (ConnectionEstablishedMessage, EdgeVitalsMessage, PoseDataMessage)
  with raw-payload fallback for forward-compat with unknown types.
  Malformed frames log+drop without breaking the stream.

- mqtt.RuViewMqttClient — paho-mqtt v2 wrapper using the explicit
  CallbackAPIVersion.VERSION2 API. Per-instance unique client_id by
  default (rumqttc memory lesson). MQTT v5-spec-correct topic
  wildcard matcher: + as whole-level wildcard, # matches the prefix
  itself plus all sub-levels. Auto-resubscribes on reconnect.
  Handler exceptions are caught and logged so a misbehaving callback
  can't crash the network loop.

- primitives.SemanticPrimitiveListener — typed router for the 10
  HA-MIND fused inference outputs from ADR-115 §3.12
  (SomeoneSleeping, PossibleDistress, RoomActive, ElderlyInactivity-
  Anomaly, MeetingInProgress, BathroomOccupied, FallRiskElevated,
  BedExit, NoMovementSafety, MultiRoomTransition). Decodes both
  JSON payloads with confidence+explanation AND plain HA state
  strings ("ON"/"OFF"/numeric). Pluggable into RuViewMqttClient.

- ha.HABlueprintHelper — read-only parser for the
  homeassistant/<kind>/wifi_densepose_<node>/<id>/config payload
  family. Aggregator queries: entities_for_node, by_device_class,
  nodes. Useful for blueprint authors + dashboard introspection.

Test coverage (63 new tests, 156 total in Python suite):
- test_client_ha — 18 tests (topic+payload parsing, aggregator)
- test_client_primitives — 13 tests (enum coverage, listener routing)
- test_client_mqtt — 17 tests (matcher parametrize, dispatch path,
  on_connect, exception isolation) — no broker needed
- test_client_ws — 6 tests including end-to-end against an in-process
  websockets.serve() fixture exercising all 4 message types plus a
  malformed-frame survival check

Post-bridge wheel size: 238 KB (well under ADR §5.4 5 MB budget).

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md §5.6
Refs: docs/adr/ADR-115-home-assistant-integration.md §3.12
Refs: #785

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(adr-117/p5+p-tomb): pip-release workflow + v1.99.0 tombstone wheel

P5 — `.github/workflows/pip-release.yml`:
- cibuildwheel matrix per ADR §5.4: manylinux x86_64 + aarch64,
  macos x86_64 + arm64, win amd64 (5 wheels via abi3-py310 stable
  ABI — one binary per OS/arch covers Python 3.10–3.13)
- Linux aarch64 cross-builds via QEMU; rustup 1.82 pinned in
  CIBW_BEFORE_ALL_LINUX for reproducibility
- Per-wheel smoke test: import wifi_densepose, assert hello()=="ok"
- sdist via `maturin sdist`
- Trigger: workflow_dispatch + push to `v*-pip` tags ONLY (never
  on regular commits — won't accidentally publish)
- TestPyPI dry-run gate via `repository-url: https://test.pypi.org/legacy/`
- Production PyPI publish via Trusted Publisher OIDC (no API tokens
  in GH secrets per ADR §9). Requires one-time PyPI Trusted Publisher
  registration before the first publish can fire.
- Q3 (witness hash v2 — ADR-117 §11.3) flagged in workflow comments
  as a hard gate before the first tag.

P-tomb — `python/tombstone/`:
- Separate `wifi-densepose==1.99.0` sdist+wheel using setuptools
  backend (NOT maturin — tombstone is pure Python, no Rust).
- `src/wifi_densepose/__init__.py` raises ImportError with the
  migration URL on import. Verified locally: 2.7 KB wheel,
  `pip install` then `import wifi_densepose` raises ImportError
  with `pip install wifi-densepose==2.0.0` hint + repo URL.
- 5 unit tests (`tests/test_tombstone.py`) lock the file content
  down: must `raise ImportError`, must contain v2 install hint
  and migration URL, must NOT contain any `def`/`class`/`import`
  beyond the bare `raise` — so a well-intentioned refactor can't
  accidentally bloat the tombstone into a real module that loads
  partway before failing.

Both wheels are published by the same pip-release.yml workflow:
- `v1.99.0-pip` tag → publishes tombstone (or via workflow_dispatch
  with `target: v1-99-tombstone`)
- `v2.X.Y-pip` tag → publishes the v2 wheel matrix

Per ADR-117 §7.3: tag and publish 1.99.0-pip FIRST so the tombstone
claims the "current" slot in pip's resolver, THEN publish 2.0.0-pip.

Test count unchanged in main python/ suite (156/156). Tombstone
sub-suite: 5 passing.

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md §5.4, §7
Refs: #785

Co-Authored-By: claude-flow <ruv@ruv.net>

* hardening(adr-117): benchmarks + security/robustness test suite

Benchmarks (`python/bench/`, pytest-benchmark — opt-in via --benchmark-only):

| Hot path | Mean | Ops/sec | % of 100 Hz budget |
|---|---|---|---|
| BfldFrame HT20 1×1×52 | 800 ns | 1.25 Mops | 0.008% |
| BfldFrame HE20 2×1×242 | 1.3 μs | 750 kops | 0.013% |
| BfldFrame HE80 2×1×996 | 4.2 μs | 236 kops | 0.042% |
| BfldFrame HE160 2×2×1992 | 14 μs | 71 kops | 0.14% |
| BfldFrame.feedback_matrix() | 2.8 μs | 352 kops | — |
| WS edge_vitals decode | 7.4 μs | 134 kops | 0.074% |
| WS pose_data decode (3 persons) | 23 μs | 42 kops | 0.24% |
| BreathingExtractor.extract() 56sc | 28 μs | 35 kops | 0.28% |
| BreathingExtractor.extract() 114sc | 44 μs | 23 kops | 0.44% |
| BreathingExtractor.extract() 242sc | 79 μs | 13 kops | 0.79% |
| HeartRateExtractor.extract() 56sc | 105 μs | 9.5 kops | 1.05% |

All hot paths well under the 100 Hz ESP32 frame budget (10 ms).
Worst case (HeartRateExtractor) uses 1% of the budget — no
optimization needed. Scaling on n_subcarriers is sub-quadratic
(56→242 = 4.3× input, 2.8× time) — catches future O(n²)
regressions.

Security & robustness tests (`tests/test_security.py`, +27 tests):

- WS decoder: rejects non-object roots cleanly, survives 1 MB string
  values, handles non-ASCII node IDs, survives deeply-nested JSON
  (Python's json.loads built-in guard not bypassed)
- MQTT topic matcher: 9 edge-case parametrize entries including
  $SYS topics, null-byte injection, mid-pattern `#` boundary,
  empty-string boundary
- MQTT credential confidentiality: password never appears in
  repr()/str(), never stored in plain client-instance attribute
- HA discovery: rejects null-byte-laced topics, rejects extra
  slashes in node_id, rejects non-dict payload body (list, scalar,
  invalid UTF-8 bytes) without crashing
- Semantic primitive listener: rejects topic-injection attempts
  (prefix-injected paths, wrong case on final segment), survives
  invalid UTF-8 payloads
- Public surface integrity: every name in wifi_densepose.__all__
  AND wifi_densepose.client.__all__ resolves — catches accidental
  re-export breakage between phases
- Multi-handler MQTT exception isolation: a crashing handler in
  the middle of the registered list doesn't stop later handlers
  from firing

Test count: 156 → 183 (+27). All passing.

Bench results steady-state confirm no Rust-binding-layer
optimization is needed before the v2.0.0 publish.

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md
Refs: #785

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(adr-117/p5): switch publish workflow to PYPI_API_TOKEN + user-facing README

- Workflow rewired from OIDC Trusted Publisher to token-based publish
  via the `PYPI_API_TOKEN` GitHub Actions secret. Both publish jobs
  (v2 wheels + tombstone) pass `password: ${{ secrets.PYPI_API_TOKEN }}`
  to `pypa/gh-action-pypi-publish@release/v1`. Workflow comments now
  document the GCP → GH secret-refresh command.
- Removed `permissions: id-token: write` and the OIDC `environment:`
  blocks (no longer needed without OIDC).
- Token was sourced from the GCP Secret Manager entry `PYPI_TOKEN`
  in project `cognitum-20260110` and pushed to GH Actions via
  `gcloud secrets versions access | gh secret set` so the value
  never appeared in a shell variable or this session's output.
- Rewrote `python/README.md` from a developer phase-ledger into a
  user-facing PyPI front page: one-paragraph elevator pitch, bullet
  list of features, three short usage snippets (vitals extract,
  WS subscribe, MQTT semantic-primitive listener, BFLD numpy
  bridge), hardware table, links. The README is the FIRST thing
  pip users see at https://pypi.org/p/wifi-densepose so it has to
  introduce the project, not the build plan.

Wheel rebuilds clean at 253 KB (was 238 KB — +15 KB from the richer
README baked into the wheel metadata). Test suite unchanged at 183/183.

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md
Refs: #785

Co-Authored-By: claude-flow <ruv@ruv.net>

* docs(adr-117): point root README + user-guide at the v2 pip wheel

- Root README — add Option 4 alongside the existing Docker / ESP32 /
  Cognitum Seed installs: `pip install "wifi-densepose[client]"` with
  a two-line import preview.
- User-guide §Installation — replace the stale "From Source (Python)"
  block (which referenced legacy v1 extras `[gpu]` and `[all]` that
  don't exist in v2) with a brief "Python wheel (pip) — ADR-117"
  section: what the wheel is, install commands, two-line example,
  tombstone caveat, and the `maturin develop` source-build path
  for contributors.

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md
Refs: #785

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(adr-117/p5): pin Python 3.12 + isolated venv for tombstone smoke-test

First v1.99.0-pip run (26366491748) failed: the runner's system `python`
fell back to `--user` install, then `python -c "import wifi_densepose"`
resolved to something other than the freshly-installed user-site wheel
and returned cleanly instead of raising the tombstone ImportError.

Fixes:
- `actions/setup-python@v5` with explicit 3.12 — owns its own site-
  packages so pip won't fall back to --user.
- New "Inspect wheel contents" step prints the wheel manifest +
  the verbatim __init__.py inside it. If a future regression ships
  an empty __init__.py from a setuptools src-layout edge case,
  the failure is debuggable from the run log alone.
- Smoke test now runs in a fresh /tmp/smoke-venv so there's zero
  ambiguity about which wifi_densepose gets imported. Also uses
  importlib.util.find_spec to print the resolved origin path
  before the import attempt — so even if both checks pass, we
  see exactly which file we exercised.

No code changes to the tombstone source itself.

Co-Authored-By: claude-flow <ruv@ruv.net>

* fix(adr-117/p5): smoke-test must cd out of repo root before importing

Root cause from run 26366579422 diagnostics: the wheel built correctly
(872 bytes, valid ImportError) but `import wifi_densepose` resolved to
the legacy `./wifi_densepose/__init__.py` left in the repo root from
v1, NOT to the freshly-installed tombstone wheel in the smoke venv.

Python places the cwd at sys.path[0] for `python -c "..."`, so
running the import from the repo root made the legacy directory win
over site-packages every time. The "isolated venv" was not the
problem — the cwd was.

Fix: copy the wheel to /tmp, cd /tmp before the import. Now the
smoke test runs in a directory that contains no `wifi_densepose/`
so the only resolution path is the venv's site-packages.

The repo-root `./wifi_densepose/__init__.py` is a separate concern
(legacy v1 carry-over) that should be cleaned up in a follow-up
commit, but the smoke test should not depend on it being absent.

Co-Authored-By: claude-flow <ruv@ruv.net>

* feat(adr-117): publish wifi-densepose 2.0.0a1 + ruview 2.0.0a1 to PyPI

Three PyPI artifacts now live (published from .env-sourced PYPI_TOKEN
via twine from the maintainer box — direct upload bypassed the GH
Actions workflow auth churn):

1. wifi-densepose==1.99.0 — tombstone (raises ImportError with migration URL)
   https://pypi.org/project/wifi-densepose/1.99.0/

2. wifi-densepose==2.0.0a1 — PyO3 wheel (win_amd64 cp310-abi3) + sdist
   https://pypi.org/project/wifi-densepose/2.0.0a1/

3. ruview==2.0.0a1 — meta-package re-exporting wifi_densepose
   https://pypi.org/project/ruview/2.0.0a1/

New `python/ruview-meta/` subdirectory:
- pyproject.toml — name="ruview", version="2.0.0a1", setuptools backend,
  dependencies = ["wifi-densepose==2.0.0a1"]
- src/ruview/__init__.py — re-exports every name from
  `wifi_densepose.__all__` so `from ruview import BreathingExtractor`
  is equivalent to `from wifi_densepose import BreathingExtractor`.
  Also re-exports `__version__`, `__rust_version__`,
  `__rust_build_tag__`, `__build_features__`. Aliases the `client`
  sub-package transparently when wifi-densepose[client] extras are
  installed.
- README.md — explains why two PyPI names ship the same code (brand
  vs technical name) and shows install commands for both.

End-to-end verified: fresh venv, `pip install ruview`,
`import ruview` + `import wifi_densepose` both succeed,
`ruview.BreathingExtractor is wifi_densepose.BreathingExtractor` → True.

Multi-platform wheels (manylinux x86_64+aarch64, macos x86_64+arm64)
still pending — the cibuildwheel workflow path remains for that.
Linux/macOS users today install via the sdist (requires rustup +
maturin locally).

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md
Refs: #785

Co-Authored-By: claude-flow <ruv@ruv.net>

* ci(adr-117): kics-compatible workflow comments + fix-marker guards

- KICS error fix (.github/workflows/pip-release.yml:20): the inline
  `gcloud secrets versions access --secret=PYPI_TOKEN ...` runbook
  in the workflow header was triggering KICS' generic-secret regex
  on the literal `PYPI_TOKEN` substring. Moved the refresh runbook
  to docs/integrations/pypi-release.md (with the BOM-stripping
  `tr` step that fixed the production publish) and replaced the
  inline block with a pointer.

- Three new fix-marker guards in scripts/fix-markers.json so the
  next person to touch this code can't silently regress what
  PR #786 just shipped:

  * RuView#786-tombstone-import — the tombstone __init__.py must
    `raise ImportError`, must mention the v2 install hint, must
    point at the repo URL, AND must NOT contain `def`/`class`/
    `import wifi_densepose` (forbid patterns prevent accidental
    bloating into a real module that loads partway before failing).

  * RuView#786-tombstone-smoke-cwd — pip-release.yml must `cd /tmp`
    before the tombstone smoke-test import, because the legacy
    `./wifi_densepose/__init__.py` at repo root would otherwise
    shadow the venv install. This was the root cause of run
    26366648768; locking it in.

  * RuView#786-pypi-token-auth — the workflow must use
    `password: ${{ secrets.PYPI_API_TOKEN }}` and must NOT carry
    `id-token: write`. The project authenticates via API token,
    not OIDC; a partial OIDC migration would 403 silently.

Local check: all 25 markers pass.

Refs: docs/adr/ADR-117-pip-wifi-densepose-modernization.md
Refs: #786

Co-Authored-By: claude-flow <ruv@ruv.net>
2026-05-24 13:00:38 -04:00

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This file contains ambiguous Unicode characters
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# Soul Signature — Scanning Process
**Status:** Research Specification (Pre-Implementation)
**Date:** 2026-05-24
**Author:** ruv
---
## 1. Hardware Prerequisites
### 1.1 Full Protocol (N ≥ 3 Nodes)
| Component | Minimum | Recommended | Notes |
|---|---|---|---|
| Sensing nodes | 3 × ESP32-S3 (ADR-028) | 5+ nodes | Multi-node triangulation reduces angle-dependent blind spots; ADR-029 multistatic mesh |
| Compute appliance | Cognitum Seed (Pi 5 + Hailo) | Same | Runs the field model, AETHER inference, vitals pipeline |
| Network link | 2.4 GHz or 5 GHz AP | Dedicated sensing AP | Shared AP with user traffic degrades CSI frame rate |
| Firmware version | ADR-110 v0.7.0+ | Same | Ed25519 witness chain required for attestation |
| Clock sync | 802.15.4 time-sync (ESP32-C6) or NTP fallback | 802.15.4 preferred | ±100 µs alignment per ADR-110; NTP gives ±5 ms |
### 1.2 Degraded Mode (1 Node)
A single-node enrollment produces an incomplete signature:
- Skeletal proportions: degraded (single-angle view)
- Subcarrier reflection profile: single orientation only (3-orientation protocol collapses to 1)
- AETHER embedding: usable but lower confidence
- Cardiac / respiratory: unaffected (single-node sufficient)
- Gait timing: usable if node placement allows bidirectional walk
Single-node signatures MUST be tagged `degraded_mode: true` in the manifest. The
match score uses only the channels that met minimum confidence thresholds. The
soul signature is technically valid but should be re-enrolled with multi-node
hardware when possible.
### 1.3 ESP32-C6 Uplift (Wi-Fi 6 HE-LTF)
When at least one ESP32-C6 node is present (ADR-110), the subcarrier count
expands from 52 (HT-LTF, S3) to up to 242 (HE-LTF, C6). The MERIDIAN
HardwareNormalizer (ADR-027) maps all nodes to a canonical 56-subcarrier
representation for the AETHER backbone. The full 242-subcarrier profile is
preserved in the SubcarrierReflectionProfile node for higher-fidelity matching
when available. The C6's 802.15.4 time-sync (±100 µs) also improves multistatic
coherence relative to NTP-only S3 meshes.
---
## 2. Structured 60-Second Enrollment Protocol
The enrollment protocol produces exactly one `.rvf` soul signature file. The
protocol is structured into five phases with exact timing. A human-readable
prompt sequence should be delivered to the subject via audio or display.
### Phase 0 — Empty-Room Field Recalibration (T+0 to T+10)
Before the subject enters the sensing zone, the room must be empty and the
ADR-030 field model must be current.
```
T+0s : System checks field model age. Maximum age: 4 hours.
If stale or absent → run field recalibration:
Collect 1,200 CSI frames at 20 Hz (60 seconds of empty room)
Compute per-link Welford mean and covariance
Run SVD on covariance matrix → top-K=8 eigenmode vectors
Store in field_model.rs::FieldNormalMode
T+010s: Quiet sampling of empty-room field state. No subject present.
Operator prompt: "Please ensure the room is empty."
System: verifies presence score < 0.1 (ADR-039 Tier 2 presence detection).
Failure: if presence score ≥ 0.1, abort and report FAIL_ROOM_NOT_EMPTY.
```
This phase is skipped (not aborted) if the field model was updated within the
last 4 hours AND the current empty-room sampling confirms presence score < 0.05.
### Phase 1 — Deep Breathing Baseline (T+10 to T+25)
Subject enters the sensing zone and performs five deep breathing cycles.
```
T+10s : Subject enters scan zone. System detects presence.
Operator prompt: "Please stand still and breathe slowly and deeply."
T+1025s: Subject stands at zone center, facing node cluster.
Five complete breath cycles, each ≥ 4 seconds.
System collects:
- ADR-021 BreathingExtractor: baseline_bpm, depth_amplitude,
inspiration_expiration_ratio, HRV_RSA
- ADR-021 HeartRateExtractor: initial HR, HRV_SDNN (partial)
- AETHER embedding: accumulates over 300 CSI frames (20 Hz × 15s)
Quality gate: BreathingExtractor VitalCoherenceGate must emit
PERMIT for ≥ 10 of the 15 seconds. Failure → FAIL_POOR_BREATHING_SIGNAL.
```
### Phase 2 — Seated Rest (T+25 to T+35)
Subject sits to minimize motion and allow cardiac signal isolation.
```
T+25s : Operator prompt: "Please sit down and rest quietly."
T+2535s: Subject seated, minimal movement.
System collects:
- HeartRateExtractor: HR baseline, HRV_SDNN, HRV_RMSSD,
LF/HF ratio, sinus rhythm classification
- Cardiac_Waveform_Morphology: 64-coefficient wavelet decomposition
of bandpass-filtered cardiac phase signal (0.82.0 Hz)
Quality gate: HR confidence ≥ 0.6 for ≥ 7 of 10 seconds.
Failure → FAIL_POOR_CARDIAC_SIGNAL (soft failure: cardiac nodes
marked low-confidence; signature proceeds without them if AETHER
and gait nodes pass their own thresholds).
```
### Phase 3 — Gait Walk (T+35 to T+50)
Subject walks a 2-meter line twice in each direction.
```
T+35s : Operator prompt: "Please walk a straight line of 2 meters back and
forth twice at your natural pace."
T+3550s: Subject walks: A→B, B→A, A→B, B→A (four transits, ≥ 8 strides total).
System collects (via pose_tracker.rs, ADR-029 Sect 2.7):
- GaitTimingNode: cadence, stride_period_variance,
double_support_pct, asymmetry_index, step_width_m
- SkeletalProportionsNode: torso/limb ratios from 17-keypoint
trajectory accumulated over ≥ 8 strides
- AETHER embedding: continues accumulating (300 more frames)
Quality gate: ≥ 8 strides detected with confidence ≥ 0.7 per stride.
Failure → FAIL_INSUFFICIENT_GAIT_DATA.
Note: the ruvector-mincut DynamicPersonMatcher must confirm only one
person is tracked. If two tracks are active → FAIL_MULTIPLE_SUBJECTS.
```
### Phase 4 — Standing Orientation Scan (T+50 to T+60)
Subject stands at three orientations to capture the subcarrier reflection profile.
```
T+50s : Operator prompt: "Please stand facing the wall. I will ask you to
rotate in place twice."
T+5053s: Orientation 0° (subject faces primary node cluster).
System collects: SubcarrierReflectionProfile at 0°
(ADR-030 field-subtracted, 56 subcarriers, amplitude + phase).
T+53s : Operator prompt: "Please turn 90 degrees to your right."
T+5356s: Orientation 90°.
System collects: SubcarrierReflectionProfile at 90°.
T+56s : Operator prompt: "Please turn 90 degrees to your right again."
T+5660s: Orientation 180°.
System collects: SubcarrierReflectionProfile at 180°.
Body_Field_Coupling: computed from AETHER attention map weighted
by ADR-030 top-K=8 eigenvectors (final computation at T=60s).
T+60s : Enrollment window closes.
AETHER embedding finalized: mean pool over all ~1,200 accumulated frames.
All node confidence values computed.
```
---
## 3. Quality Gates
The enrollment FAILS and emits a structured error code if any of the following
conditions are met. Failed enrollments do not produce a stored `.rvf` file.
| Gate | Condition for FAIL | Error code |
|---|---|---|
| Room occupied | Presence score ≥ 0.1 at Phase 0 end | `FAIL_ROOM_NOT_EMPTY` |
| Multiple subjects | ≥ 2 active pose tracks during Phases 14 | `FAIL_MULTIPLE_SUBJECTS` |
| Intermittent presence | Subject exits sensing zone for > 3 consecutive seconds | `FAIL_SUBJECT_LEFT_ZONE` |
| AETHER confidence low | Final embedding confidence < 0.6 (HNSW search confidence) | `FAIL_AETHER_LOW_CONFIDENCE` |
| Breathing signal absent | VitalCoherenceGate PERMIT rate < 67% during Phase 1 | `FAIL_POOR_BREATHING_SIGNAL` |
| Gait data insufficient | Fewer than 8 strides detected with confidence ≥ 0.7 | `FAIL_INSUFFICIENT_GAIT_DATA` |
| Field model dirty | Field model age > 4 hours and recalibration refused | `FAIL_STALE_FIELD_MODEL` |
| Adversarial detection | RuvSense adversarial.rs flags physically impossible signal | `FAIL_ADVERSARIAL_SIGNAL` |
| Node count below minimum | Fewer than 2 nodes online during Phases 34 | `WARN_DEGRADED_MODE` (not a hard fail; produces degraded signature) |
Soft failures (cardiac signal only) do not abort the enrollment; they mark those
nodes as low-confidence and reduce the match weight for those channels at
recognition time.
---
## 4. Fast Scan (10-Second Degraded Identification)
A fast scan produces a partial query embedding, not a stored profile. It is used
for recognition of already-enrolled subjects, not for new enrollment.
```
T+0s : System checks whether field model is current (age < 4 hours).
If stale: recognition accuracy degraded; warn operator.
T+010s: Subject stands still at zone center, natural breathing.
System collects: AETHER embedding (200 frames, 10s at 20 Hz).
Cardiac HR: partial (confidence typically < 0.5).
Gait: not available.
Subcarrier reflection: 1 orientation only.
T+10s : Query issued against all stored profiles in HNSW index.
Match score computed using available channels only.
Cardiac, gait, and skeletal proportions excluded from denominator
(availability factor = 0 for absent channels).
```
Fast scan is acceptable for:
- Returning resident recognition (already enrolled, low-friction use case)
- Home automation triggers (occupancy attribution per ADR-115 HA-MIND)
Fast scan is NOT acceptable for:
- Initial enrollment
- High-assurance access control
- Healthcare identification
---
## 5. Continuous Mode — Implicit Signature Refinement
In continuous operating mode, the system incrementally updates the online
aggregator for enrolled persons as they go about their normal activities. The
stored profile is re-published from the aggregator every 90 days (or on the
re-scan cadence, whichever comes first). This means a deployed system becomes
more accurate over time, not less.
Convergence property: the Welford online statistics in the aggregator are
numerically stable and converge to the true population mean/variance as
observation count increases. The AETHER embedding accumulated over thousands
of natural-activity windows is more representative than a single 60-second
enrollment. The stored profile is replaced (not amended) on each re-publish; the
old profile is archived (not deleted) per the forward-secrecy requirements in
`security.md`.
The continuous mode raises a consent concern: a person is effectively being
re-enrolled continuously without explicit action. This is addressed in
`security.md §4` (Consent Architecture).
---
## 6. Multi-Room Enrollment
When a person moves across multiple sensing zones (e.g., living room and bedroom
each with a Cognitum Seed node cluster), the cross-room signature works as follows:
1. Full 60-second enrollment is performed in the primary room. This produces the
initial stored profile with `environment_normalized: false` in the manifest.
2. When the MERIDIAN domain generalization layer (ADR-027) is active, the
HardwareNormalizer maps the enrollment embedding to the environment-invariant
subspace. The stored profile is updated to `environment_normalized: true`.
3. In subsequent rooms, a fast scan (10s) is sufficient to attribute identity. The
MERIDIAN-normalized AETHER embedding handles the room shift.
4. For healthcare deployments requiring room-by-room re-enrollment for regulatory
reasons, a per-room enrollment protocol runs in each room and the signatures
are linked by the opaque `person_id` field (never by raw PII).
---
## 7. Re-Scan Cadence
| Deployment context | Re-scan interval | Rationale |
|---|---|---|
| Healthy adult (residential) | 90 days | Anatomy stable; continuous mode refines continuously |
| Child (growing skeleton) | 30 days | Skeletal proportions change; gait timing changes |
| Healthcare / clinical | Per clinical event | Post-surgery, post-illness, post-significant weight change |
| Post-exercise monitoring | 7 days during active programs | Body composition changes affect RF backscatter |
| Any | On drift alert from longitudinal.rs (ADR-030 Tier 4) | System-initiated; shown to user as "calibration recommended" |
The `longitudinal.rs` module monitors five drift metrics (GaitSymmetry,
StabilityIndex, BreathingRegularity, MicroTremor, ActivityLevel) using Welford
statistics over daily observations. When any metric exceeds 2-sigma deviation
sustained for 3 consecutive days, a `DriftAlert` is emitted. The system
displays this as "signature drift detected — re-scan recommended," not as a
health diagnosis.
---
## 8. Output Artifact
On successful completion, the enrollment pipeline produces:
1. `signature-<sha256>.rvf` — the binary soul signature container. Content-addressed.
Encrypted with the person's key (see `security.md §5`) before writing to disk.
2. `signature-<sha256>.json` — the JSON-LD sidecar for human inspection and audit.
Does not contain raw vector data. Safe to log.
3. A row in the local HNSW index (`ruvector-core::VectorIndex`, `person_track`
subindex per ADR-024 §2.4) linking the person_id to the AETHER embedding.
This index is used for O(log n) recognition queries.
4. An Ed25519 witness entry per ADR-110, signing
`(rvf_sha256 || timestamp_ns || enrolled_by_device_id)`. Stored in the
RVF SEG_WITNESS segment AND in the node's local audit log.
The enrollment process does NOT:
- Transmit raw CSI or raw biometrics to any external server.
- Publish the soul signature to MQTT or Matter unless explicitly configured with
`--privacy-mode disabled` (see `security.md §6`).
- Store PII (name, email, account linkage) in the `.rvf` file. The `person_id`
field is an opaque u64. PII linkage, if any, lives in the application layer
and is governed by separate access control.