feat(progress): stage-aware freq estimator + silent-phase detail (M-PROGRESS C6/D3) - #100
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…ROGRESS C6/D3) C6: _estimate_frequency_cost learns Hessian and IR multipliers from tagged frequency perf_log stages when >=2 source=app records exist; falls back to the fixed SP-anchored model otherwise. D3: surface per-phase progress in the live status label for NMR GIAO (per-atom shielding), analytical Hessian build (per-atom contractions at verbose=6), CCSD cycles, and MP2 integral/kernel milestones — mirroring the existing TD-DFT per-root pattern (D2). Co-authored-by: NCCU Schultz Lab <nccu-schultz-lab@users.noreply.github.com> Co-authored-by: Cursor <cursoragent@cursor.com>
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Summary
Closes the last open items on M-PROGRESS roadmap Phase C (C6) and Phase D (D3).
PROG.C6 — Stage-aware frequency cost model
When ≥2 tagged
source="app"frequency records carry C4stagesbreakdowns,_estimate_frequency_costlearns median Hessian and IR ratios from history instead of the fixed SP-anchored multipliers. Falls back to the existing model when stage data is insufficient.PROG.D3 — Per-phase live status (mirrors D2 TD-DFT)
Surfaces specific progress in the live status label during long silent kernels:
nmr_obj.verbose=4)hess_obj.verbose=6)ccsd.verbose=4)mp2.verbose=5)D1 generic heartbeat still covers phases without a specific signal (e.g. CCSD(T) triples).
Tests
tests/test_progress_phase_c.py— C6 stage-ratio learning + bucketingtests/test_app.py— D3 regex/status label updatespytest -m "not network"greenpre-commit run --all-filesgreenLocal follow-up
Voilà pass on a long NMR / frequency / MP2 run to confirm status lines read well during silent phases (not closable from cloud).