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ADR-185 §4.2 pytest-benchmark micro-benchmarks + runnable examples +
README extras table for the aether/meridian/mat bindings.
- python/bench/test_bench_{aether,meridian,mat}.py — follow the existing
test_bench_vitals.py pattern (skipped by default; --benchmark-only).
- python/examples/{reid_from_csi,cross_room_calibrate,mat_triage}.py —
typed, runnable, mypy --strict clean.
- python/README.md — SOTA extras table + example links.
Measured on a RELEASE wheel (maturin develop --release --features sota),
reference machine per ADR-117 §10:
AETHER embed() mean ~150 us/window (target <2 ms) PASS
batch scaling 1/8/64: 140 / 1091 / 8509 us (linear, no O(n^2)) PASS
MERIDIAN normalize() mean ~2.2 us/frame (target <200 us) PASS
MERIDIAN encode() mean ~6.9 us (target <200 us) PASS
MAT ingest+scan_once() mean ~40 ms/256-frame (< 500 ms interval) PASS
Acceptance self-verification (ADR-185 §6), all run just now:
§6.1 default wheel 279 KB (<=5 MB); build_features has no p6-* feature PASS
§6.2 pytest tests/test_aether.py 9/9 PASS
§6.3 pytest tests/test_meridian.py 13/13 PASS
§6.4 pytest tests/test_mat.py 7/7 PASS
§6.5 benchmarks meet all targets (above) PASS
§6.6 parity harness: 3/3 SHA golden gates green (cargo test --features
sota, 6/6); CI *wiring* as a release gate is out of python/ scope PARTIAL
§6.7 SOTA accuracy bars on labeled fixtures: NOT met (no labeled
fixtures / trained models available; parity proves path-equality,
not accuracy) OPEN
§6.8 .pyi stubs present for all three; mypy --strict on the 3 examples PASS
§6.9 base wheel `import wifi_densepose.{aether,meridian,mat}` raises a
clear ImportError naming the extra PASS
No regression: 76 pre-existing tests pass on the default wheel.
Status NOT flipped to Accepted: §6.7 (accuracy bars) is unmet, §6.6 CI
wiring is pending, and the per-extra wheel-size hoists (sensing-server /
train / mat leaf crates) remain follow-ups. docs/adr/ is owned by another
agent this session, so the ADR ledger edit is deferred to that owner.
46 lines
1.5 KiB
Python
46 lines
1.5 KiB
Python
"""MERIDIAN cross-room calibration (ADR-185 P2, `[meridian]` extra).
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Hardware-invariant CSI normalization, AP-geometry encoding, and few-shot
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rapid adaptation — the tch-free domain-generalization path.
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pip install wifi-densepose[meridian]
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python examples/cross_room_calibrate.py
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"""
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from __future__ import annotations
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import math
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from wifi_densepose.meridian import (
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GeometryEncoder,
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HardwareNormalizer,
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HardwareType,
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MeridianGeometryConfig,
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RapidAdaptation,
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)
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def main() -> None:
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# 1. Normalize a 64-subcarrier ESP32 frame to the canonical 56-tone grid.
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norm = HardwareNormalizer()
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amp = [10.0 + 0.05 * k for k in range(64)]
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phase = [0.01 * k for k in range(64)]
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frame = norm.normalize(amp, phase, HardwareType.detect(64))
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print(f"canonical subcarriers: {len(frame.amplitude)} (hw={frame.hardware_type})")
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# 2. Encode AP positions into a permutation-invariant geometry embedding.
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enc = GeometryEncoder(MeridianGeometryConfig())
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geometry = enc.encode([[0.0, 0.0, 2.5], [5.0, 0.0, 2.5], [0.0, 4.0, 2.5]])
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print(f"geometry embedding dim: {len(geometry)}")
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# 3. Few-shot rapid adaptation over a handful of unlabeled frames.
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ra = RapidAdaptation(min_calibration_frames=10, lora_rank=4)
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for i in range(12):
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ra.push_frame([math.sin(0.1 * i + 0.05 * d) for d in range(16)])
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result = ra.adapt()
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print(f"adapted over {result.frames_used} frames, final_loss={result.final_loss:.4f}")
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if __name__ == "__main__":
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main()
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