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Warm up the small-grid perf budget test to absorb cold-start noise - #86
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The small-grid variant measured the cold first call to simulate_manual_action, while its large-grid sibling already ran a warmup iteration before timing. On a loaded CI machine the first call can spike past the 150ms budget because of module import resolution, MagicMock attribute caching and cold BLAS/pandas paths, even though the steady-state logic runs in roughly 3-10ms. Mirror the large-grid test's warmup pattern, then rebuild the env.get_obs side_effect iterator so the timed call still has a fresh pair of observations to consume.
marota
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Apr 30, 2026
Reconciliation of section 2 (0.5.0): - Drop misattributed PRs that were actually pre-rebrand: save/reload (#49/#52), MW Start (#62), interaction-logging (#64), SLD highlights (#63), load shedding initial integration (#61). All now properly cited in section 1.5–1.6. - Disambiguate App.tsx refactor history: PR #56 (hooks, 2100 → 800, pre-rebrand) vs PR #74 (components, 1000 → 650, 0.5.0) vs PR #75 (memoization Phase 2, same LoC). - Add accurate 0.5.0 PRs: #66 (vectorization w/ benchmark table), #69/#70/#71 (UI polish), #72 (curtailment), #73 (loads_p/gens_p format + configurable MW), #74/#75 (App.tsx decomposition), #78 (PST tap re-simulation), #84/#86/#87/#90 (detachable tabs). - Add a recap table summarizing what's truly new in 0.5.0. Diagrams added (Mermaid, GitHub-rendered): - Gantt timeline of all 4 phases (top of doc). - High-level architecture (frontend / backend / data). - Two-step analysis sequence diagram (section 1.6). - App.tsx LoC evolution flow (section 2.4). - Backend mixin decomposition before/after PR #104/#106 (section 3). - PyPSA-EUR pipeline flowchart (section 4). https://claude.ai/code/session_01Pg7fuCUG2edfm5PyHS6SbN
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The small-grid variant measured the cold first call to simulate_manual_action, while its large-grid sibling already ran a warmup iteration before timing. On a loaded CI machine the first call can spike past the 150ms budget because of module import resolution, MagicMock attribute caching and cold BLAS/pandas paths, even though the steady-state logic runs in roughly 3-10ms.
Mirror the large-grid test's warmup pattern, then rebuild the env.get_obs side_effect iterator so the timed call still has a fresh pair of observations to consume.