Changelog 0.6

Public release notes for nimbus-bci 0.6.0 (2026-09-13). The package ships a full CHANGELOG.md in the PyPI sdist; this page is the docs mirror for the product surface. Upgrading from 0.5? Start with Migration to 0.6. Also new in docs: Paradigms & profiles · Transforms · Research / PEFT.

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Highlights

• Cheap online adaptation: head partial_fit ~8–10× vs sklearn batch refit; ~22–131× vs trunk retrain at matched n
• Factories: for_deployment, for_research, for_features, for_riemann, for_p300, for_balora
• Portable profiles + MI / P300 session bundles
• Embedding transforms + opt-in [train] PEFT / BaLoRA

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Added

• fit_calibrated(...) — fit + pin decision-gate accept rate
• adapt(...) / adapt_async(...) — adaptation gateway; BrainStateBatch
• export_profile / from_profile / UserProfile
• Transforms: standardize / whiten / coral / affine / rpa / euclidean_alignment
• P300 / Riemann / MI recipes — see Paradigms & profiles
• Session-bundle trust: trusted=True + sidecar_sha256
• calibration_status / suggest_calibration_trials
• BaLoRA + trunk PEFT behind [train] — see Research / PEFT
• Metrics: cohen_kappa, roc_auc_score, brier_score, temperature_scale_logits
• Optional forgetting λ\<1 and prior_fraction= on LDA/QDA
• adapt_errp, adapt_pseudo, fit_tent, T3A, fit_population (research)

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Changed (breaking)

• Presets: research → strict, consumer → permissive
• Middleware imports regrouped under policies/ / alignment/ / techniques/ (no shims)
• scikit-learn >= 1.6; Python >=3.11,<3.14; [train] torch >=2.14
• sfreq never-declared warning when encoder has training_sfreq

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Evidence integrity

Update cost is the robust claim (held even where accuracy gates failed). Cite wall-time ratios — details on Evidence.

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