4 Commits

Include renames

Author	SHA1	Message	Date
mathias	308f71b566	fix(ci): Taskfile YAML syntax error + staticcheck tagged-switch (jepa-fx-risk#19) ... Taskfile.yml line 46 had an unquoted Go-template `{{.VAR}}` inside a YAML flow sequence (`cmds: [...]`) -- the literal braces broke YAML parsing outright ("did not find expected ',' or ']'"), so `task check` (and thus CI's push-triggered check job) failed before running a single command. A manual `workflow_dispatch` re-run passed because the autoresearch workflow never calls `task check` at all -- unrelated path, not an env/secret difference as first suspected. Quoted the string. Also fixed a staticcheck QF1002 in internal/eval/var.go: a boolean switch comparing the same variable (n1) in every case is a tagged switch in disguise -- converted to `switch n1 { case 0: ... case n: ... }`.	2026-07-24 15:26:01 +02:00
mathiasandClaude Sonnet 4.6	68bf8f15c5	feat(eval): VaR breach rate metric (#12) + HMM regime detector (#13) — rq-04 prep ... #12 — VaR_breach_rate_99_oos_regime_cond metric: - internal/eval/var.go: VaRBreachRate() + kupiecPOF() + LinearProbePredict() (stdlib math only) - internal/eval/var_test.go: 8 golden tests (zero/all breach, perfect calibration, boundary) - cmd/eval/main.go: -metric var flag (no-leakage probe → VaR → Kupiec P) - scripts/var_breach.py: Python equivalent with METRIC_KEY constant (13 TDD tests) - train.py LOCKED VaR EVAL BLOCK: writes VaR_breach_rate_99_oos_regime_cond + kupiec_p to metrics.json - Fixed bug: train.py used bare 'os' before import; now uses module-level '_os' consistently #13 — HMM regime detector + JEPA conditioning seam: - scripts/prepare_regime.py: GaussianHMM (diag, 3-state) on realized_vol; states sorted by mean vol (0=calm, 1=stressed, 2=crisis); deterministic (random_state=42); outputs eurusd_regime.parquet - tests/test_regime.py: 11 TDD tests (dtype, states, determinism, vol sort, daily fallback) - train.py: JEPA_ENABLE_REGIME toggle + REGIME CONDITIONING SEAM (concat baseline, agent-editable) - requirements.txt: hmmlearn>=0.3, scikit-learn>=1.4 78 Python + all Go tests green. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-06-27 10:35:10 +02:00
mathiasandClaude Sonnet 4.6	20aeecb971	fix(eval): correct probe metric to use true year-based OOS split ... - train.py build(): year-based split (train≤2021, OOS≥2022) replaces misleading 70/30 mixed-period split; true OOS val_vol_r2 now ~-0.36 vs previously reported +0.18 (artefact of cross-period data leakage) - train.py: EXPORT_EMBEDDINGS block now exports both train+OOS embeddings with dates and HV labels for Go eval harness - cmd/eval: LinearProbeTrainTest uses train stats for standardisation of both sets (no leakage); standardiseCompute/applyStandardise helpers - internal/eval: add LinearProbeTrainTest (fit-on-train, eval-on-OOS) alongside LinearProbe (same-set); 8/8 tests still green Phase-0 gate result: val_vol_r2=-0.36, silhouette=0.043, erank=58.9/64. Backbone produces high-rank embeddings (SIGReg working) but does NOT generalize across 2021→2022 regime boundary. Gate: INCONCLUSIVE/FAIL. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-06-24 22:57:14 +02:00
mathiasandClaude Sonnet 4.6	e11e7d2524	feat(eval): Go evaluation harness — LinearProbe, Silhouette, EffectiveRank (#4) ... internal/eval: three pure-Go diagnostics on frozen embeddings: LinearProbe(emb, y, λ) → val_vol_r2 (OOS R², closed-form ridge, Cholesky) Silhouette(emb, labels) → mean silhouette (Euclidean, multi-label, errors on <2 classes) EffectiveRank(emb) → Roy effective rank (Jacobi eigenvalues → entropy → exp(H)) cmd/eval/main.go: CLI driver reading embeddings.json (exported by train.py with EXPORT_EMBEDDINGS=1), standardises per-dim, dispatches to -metric flag. task eval:probe / eval:silhouette / eval:collapse wired in Taskfile. 8/8 tests pass (red-green: perfect clusters, rank-1, full-rank, noise, constant target, single-label error). Pure stdlib, no external deps. Closes #4. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>	2026-06-24 12:01:04 +02:00