Add posturography, physiological-signal, and mocap-I/O utilities#352
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Ports the still standing study's posturography stack into pure numpy/scipy: CoP sway metrics, confidence-ellipse and convex-hull area, Collins-De Luca stabilogram diffusion, DFA, sample entropy, spectral edges, sway texture, sway orientation, axial Rayleigh, spatial extent, and principal-axis projection. From-scratch SDA/DFA/SampEn are validated against known-answer synthetic signals. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0147io2kMk8M6jcNFNt1G96m
Ports the still standing study's physiology features: windowed respiration rate (band-pass + Welch peak per window) and caller-supplied spectral band fractions (the cardiorespiratory spectral-composition diagnostic, with bands supplied by the caller so there is no sensor dependency). Registers the _posture and _physio exports in the package namespace. Validated against a 0.25 Hz breathing sinusoid (~15 br/min) and a two-tone band split. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0147io2kMk8M6jcNFNt1G96m
Consolidates the several near-duplicate QTM/TSV loaders into one robust read_qtm_tsv (MARKER_NAMES header, autodetected data start, zeros->NaN, encoding fallback, returns marker names / [T,M,3] array / fs). Adds compare_modality_envelopes (per-second resample + Pearson r, decoupled from QoM computation) and a Welch-based dominant_frequency (not re-exported at package level to avoid colliding with _analysis.dominant_frequency). Validated with an in-test QTM TSV fixture and known-lag envelopes. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0147io2kMk8M6jcNFNt1G96m
…tes) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_0147io2kMk8M6jcNFNt1G96m
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Second batch of study-derived methods (independent of #351):
_posture.py— a full posturography battery: CoP sway metrics (path length/rate, 95% confidence-ellipse area, ML/AP stats, mean sway frequency), convex-hull area, stabilogram diffusion (Collins–De Luca), DFA, sample entropy, spectral edge frequencies, sway texture (frozen-fraction/burst-rate), PCA sway orientation + anisotropy, axial Rayleigh statistics (with correct angle doubling), and spatial-extent / drift-decomposition metrics._physio.py— respiration-rate estimation (band-pass + Welch peak per window) and spectral band-fraction diagnostics for QoM signals (how much of a near-still signal is cardiorespiratory)._mocap.py— a robust QTM/TSV reader (consolidating several ad hoc loaders), video-vs-mocap envelope validation, and a band-limited dominant-frequency helper (module-level only; not re-exported to avoid shadowing the existing_analysis.dominant_frequency).38 new tests with known-answer synthetics (white-noise DFA α≈0.5, random-walk SDA H≈0.5, sine-vs-shuffled sample entropy, synthetic breathing at 15 br/min, in-test QTM fixtures). No new suite failures. Sources: stillstanding project and Westney comparisons (self-port).
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