WHOOP HCI-capture extraction + CSV ground-truth correlation (#103)#133
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digitalerdude wants to merge 1 commit into
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WHOOP HCI-capture extraction + CSV ground-truth correlation (#103)#133digitalerdude wants to merge 1 commit into
digitalerdude wants to merge 1 commit into
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Two stdlib tools in Tools/linux-capture that turn a WHOOP data export into leverage for the un-decoded deep-record layouts tracked in ryanbr#103: - hci_extract.py: parse a phone Bluetooth HCI capture (iOS .pklg / Android btsnoop) of the official app, reassemble L2CAP/ATT, and emit the CRC-valid WHOOP frames as the project's capture.json. Only WHOOP streams reach the output. - correlate_ground_truth.py: known-plaintext field search. Cross-reference capture records against the official per-night values in a WHOOP CSV export (reusing the Swift importer's localized header aliases) to locate each biometric's byte offset + encoding. Distribution-overlap scoring (recall + precision) rejects constants and coincidences. Prints offsets only, so the output is safe to post on ryanbr#103 while health data stays local. Docs: new README sections + a ground-truth-correlation note in WHOOP5_DEEP_DATA.md. 25 new stdlib tests; full suite 129 green. Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
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Was & warum
Zwei stdlib-Tools in
Tools/linux-capture/, die einen WHOOP-Datenexport nutzbar machen, um die un-dekodierten Deep-Record-Layouts aus #103 zu knacken (type-0x2F, 5/MG-History-Typen — siehedocs/WHOOP5_DEEP_DATA.md).Der Import dieses CSV-Formats ist bereits vollständig gelöst (inkl. lokalisierter DE/ES-Header, #3). Die offene Lücke laut #103 ist das Decoding — und genau dafür ist ein eigener Export das ideale Known-Plaintext-Material.
Tools
hci_extract.py— parst ein Phone-Bluetooth-HCI-Capture der offiziellen App (iOS.pklg/ Androidbtsnoop_hci.log), reassembliert L2CAP/ATT und gibt die CRC-validen WHOOP-Frames als das projekteigenecapture.json-Format aus. Nur WHOOP-Streams landen im Output (Frames anderer Geräte fallen weg). App-Writes werden alsdir:txmitgeschnitten (die Enable-Sequenz).correlate_ground_truth.py— Known-Plaintext-Feldsuche. Kreuzt Capture-Records gegen die offiziellen Nacht-Werte eines WHOOP-CSV-Exports (HRV, Ruhe-HF, Hauttemperatur, SpO₂, Atemfrequenz) und findet pro Biometrie das Byte-Offset + Encoding + Scale. Die lokalisierten Header-Aliase sind aus dem Swift-Importer (CSVParsing.swift) gespiegelt. Distribution-Overlap-Scoring (Recall + Precision) verwirft Konstanten und Zufallstreffer.Privacy
Beide Tools laufen lokal;
correlategibt nur Offsets/Encodings aus, nie Gesundheitswerte. So können 5/MG-Besitzer eine bestätigte Feld-Zuordnung auf #103 beitragen, ohne Capture oder Datenexport zu posten.Verifikation
hci_extract(331 type-47 Frames) →correlategewinnt Ruhe-HF (Offset 10, u8) und Hauttemperatur (Offset 14, float32) exakt zurück.Mapped Offsets folgen weiterhin der Projektregel real captures, never invented offsets, bevor sie in
parseFrameWhoop5/whoop_protocol.jsonlanden.🤖 Generated with Claude Code