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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.
50 lines
1.6 KiB
Python
50 lines
1.6 KiB
Python
"""MAT disaster-survivor triage from CSI (ADR-185 P3, `[mat]` extra).
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Ingest a CSI stream, run one detection cycle, and list detected survivors
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by START triage class.
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pip install wifi-densepose[mat]
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python examples/mat_triage.py
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Note: the stream here is synthetic (breathing-modulated) — it demonstrates
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the API and pipeline, not validated detection accuracy on real rubble.
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"""
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from __future__ import annotations
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import math
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from collections.abc import Iterator
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from wifi_densepose.mat import DisasterConfig, DisasterResponse, DisasterType, ScanZone
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def breathing_stream(
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frames: int = 256, subc: int = 56, fs: float = 20.0
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) -> Iterator[tuple[list[float], list[float]]]:
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for t in range(frames):
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tt = t / fs
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breath = 2.0 * math.sin(2 * math.pi * 0.3 * tt)
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amp = [10.0 + 0.05 * k + breath for k in range(subc)]
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phase = [0.01 * k + 0.1 * math.sin(2 * math.pi * 0.3 * tt) for k in range(subc)]
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yield amp, phase
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def main() -> None:
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cfg = DisasterConfig(DisasterType.Earthquake, sensitivity=0.9, confidence_threshold=0.1)
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resp = DisasterResponse(cfg)
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resp.initialize_event(0.0, 0.0, "Collapsed Building A")
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resp.add_zone(ScanZone.rectangle("North Wing", 0.0, 0.0, 50.0, 30.0))
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for amp, phase in breathing_stream():
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resp.push_csi_data(amp, phase)
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resp.scan_once()
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survivors = resp.survivors()
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print(f"detected {len(survivors)} survivor(s)")
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for s in survivors:
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print(f" {s.id[:8]} triage={s.triage_status} confidence={s.confidence:.3f}")
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if __name__ == "__main__":
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main()
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