Close remaining CI review items; automate table generation

Addresses the second-round CI review findings:

- P1 false-pass (remaining): removed five phase-local try/except blocks
  that swallowed sub-step exceptions (HonestDiD M-grids in brand-awareness
  and BRFSS, dCDH HonestDiD and heterogeneity refit, dose-response
  dataframe extraction). Exceptions now escape, the phase is marked
  ok=false, and run_scenario's atexit handler exits nonzero. The fix
  caught a real API-usage bug on its first rerun: dose_response extract
  phase tried to pull event_study level on a result fit with
  aggregate="dose"; the event_study fit lives in a dedicated phase, so
  that level is removed from the extraction loop.
- P2 scenario-spec drift: BRFSS scenario text now says pweight TSL
  stage-2 (matching the aggregate_survey-returned design), not "Full
  replicate-weight path"; dCDH reversible scenario text now says
  heterogeneity="group" (matching the script), not "cohort".
- P3 path leakage: tracemalloc output now scrubs $HOME, repo root, and
  site-packages before writing the committed txt.

Drift-prevention layer:

- gen_findings_tables.py reads every JSON baseline and rewrites the
  numerical tables in performance-plan.md between
  <!-- TABLE:start <id> --> / <!-- TABLE:end <id> --> markers. Tables
  now re-derive from data on every rerun, eliminating the hand-edit
  drift the prior review flagged. Narrative prose stays hand-written
  by design, forcing a human re-read of findings when numbers shift.

Findings refresh (the numbers moved slightly; three narrative claims
needed updating):

- "Rust marginally slower than Python on JK1 at large scale" -> removed;
  fresh data has Rust and Python within noise on brand awareness at
  large (JK1 phase 0.577s Py / 0.562s Rust, totals 1.03 / 1.04).
- "ImputationDiD consistently dominant phase at all scales" -> narrowed
  to "dominant under Python; tied with SunAbraham under Rust at large".
- "Nine-figures of MB" in memory finding #3 was a phrasing error
  (literally 100+ TB); corrected to "mid-100s of MB".

Priority of optimization opportunities refreshed against new data:

- #1 aggregate_survey precompute stratum scaffolding: High (unchanged,
  now strongly supported - 24.75s Python / 25.41s Rust at 1M rows, 100%
  of chain runtime, growth only +31 MB).
- #2 Staggered CS working-memory audit: Low with explicit bump-trigger
  (Rust large crosses 512 MB Lambda line).
- #5 Rust-port JK1 replicate fit loop: demoted from Medium to Low -
  the "Rust regression to fix" leg of the rationale is gone because
  Rust is no longer slower.

Net: one clear priority (aggregate_survey fix), four optional follow-ups.
Still measurement only. No changes under diff_diff/ or rust/.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

Author: igerber

benchmarks/speed_review/baselines/brand_awareness_survey_large_python.json

@@ -2,47 +2,47 @@
   "scenario": "brand_awareness_survey_large",
   "backend": "python",
   "has_rust_backend": false,
-  "total_seconds": 0.9061127080000002,
+  "total_seconds": 1.026685333,
   "memory": {
     "available": true,
-    "start_mb": 189.33,
-    "peak_mb": 335.59,
-    "growth_mb": 146.27,
+    "start_mb": 195.45,
+    "peak_mb": 335.25,
+    "growth_mb": 139.8,
     "sampler_interval_s": 0.01
   },
   "phases": {
     "1_naive_fit_no_survey_design": {
-      "seconds": 0.013970540999999947,
+      "seconds": 0.01289908400000006,
       "ok": true,
       "error": null
     },
     "2_tsl_strata_psu_fpc": {
-      "seconds": 0.03233287500000004,
+      "seconds": 0.030157082999999973,
       "ok": true,
       "error": null
     },
     "3_replicate_weights_jk1": {
-      "seconds": 0.44611704099999994,
+      "seconds": 0.5706585830000002,
       "ok": true,
       "error": null
     },
     "4_multi_outcome_loop_3_metrics": {
-      "seconds": 0.21938504199999986,
+      "seconds": 0.21575479099999972,
       "ok": true,
       "error": null
     },
     "5_check_parallel_trends": {
-      "seconds": 0.04051395800000002,
+      "seconds": 0.039158959000000326,
       "ok": true,
       "error": null
     },
     "6_placebo_refit_pre_period": {
-      "seconds": 0.016386375000000175,
+      "seconds": 0.02081145899999992,
       "ok": true,
       "error": null
     },
     "7_event_study_plus_honest_did": {
-      "seconds": 0.13737600000000016,
+      "seconds": 0.13721408299999993,
       "ok": true,
       "error": null
     }

benchmarks/speed_review/baselines/brand_awareness_survey_large_rust.json

@@ -2,47 +2,47 @@
   "scenario": "brand_awareness_survey_large",
   "backend": "rust",
   "has_rust_backend": true,
-  "total_seconds": 0.8791467499999999,
+  "total_seconds": 1.03563075,
   "memory": {
     "available": true,
-    "start_mb": 187.97,
-    "peak_mb": 315.2,
-    "growth_mb": 127.23,
+    "start_mb": 194.5,
+    "peak_mb": 338.94,
+    "growth_mb": 144.44,
     "sampler_interval_s": 0.01
   },
   "phases": {
     "1_naive_fit_no_survey_design": {
-      "seconds": 0.013859375000000007,
+      "seconds": 0.01294266700000013,
       "ok": true,
       "error": null
     },
     "2_tsl_strata_psu_fpc": {
-      "seconds": 0.02124400000000004,
+      "seconds": 0.031624374999999816,
       "ok": true,
       "error": null
     },
     "3_replicate_weights_jk1": {
-      "seconds": 0.42970375000000005,
+      "seconds": 0.5619407919999999,
       "ok": true,
       "error": null
     },
     "4_multi_outcome_loop_3_metrics": {
-      "seconds": 0.2112943330000001,
+      "seconds": 0.263706,
       "ok": true,
       "error": null
     },
     "5_check_parallel_trends": {
-      "seconds": 0.038379208000000276,
+      "seconds": 0.009824249999999868,
       "ok": true,
       "error": null
     },
     "6_placebo_refit_pre_period": {
-      "seconds": 0.025571082999999994,
+      "seconds": 0.012082083000000132,
       "ok": true,
       "error": null
     },
     "7_event_study_plus_honest_did": {
-      "seconds": 0.1390828329999998,
+      "seconds": 0.1435007500000003,
       "ok": true,
       "error": null
     }

benchmarks/speed_review/baselines/brand_awareness_survey_medium_python.json

@@ -2,47 +2,47 @@
   "scenario": "brand_awareness_survey_medium",
   "backend": "python",
   "has_rust_backend": false,
-  "total_seconds": 0.560188,
+  "total_seconds": 0.763684958,
   "memory": {
     "available": true,
-    "start_mb": 131.69,
-    "peak_mb": 187.8,
-    "growth_mb": 56.11,
+    "start_mb": 135.03,
+    "peak_mb": 193.52,
+    "growth_mb": 58.48,
     "sampler_interval_s": 0.01
   },
   "phases": {
     "1_naive_fit_no_survey_design": {
-      "seconds": 0.011834042000000045,
+      "seconds": 0.01204445799999998,
       "ok": true,
       "error": null
     },
     "2_tsl_strata_psu_fpc": {
-      "seconds": 0.03354012500000003,
+      "seconds": 0.03723474999999998,
       "ok": true,
       "error": null
     },
     "3_replicate_weights_jk1": {
-      "seconds": 0.21381758399999995,
+      "seconds": 0.377466875,
       "ok": true,
       "error": null
     },
     "4_multi_outcome_loop_3_metrics": {
-      "seconds": 0.13717983300000003,
+      "seconds": 0.14207241700000006,
       "ok": true,
       "error": null
     },
     "5_check_parallel_trends": {
-      "seconds": 0.018324165999999975,
+      "seconds": 0.014263458000000062,
       "ok": true,
       "error": null
     },
     "6_placebo_refit_pre_period": {
-      "seconds": 0.058137000000000105,
+      "seconds": 0.06729445800000011,
       "ok": true,
       "error": null
     },
     "7_event_study_plus_honest_did": {
-      "seconds": 0.08734375000000005,
+      "seconds": 0.11328508300000006,
       "ok": true,
       "error": null
     }

benchmarks/speed_review/baselines/brand_awareness_survey_medium_rust.json

@@ -2,47 +2,47 @@
   "scenario": "brand_awareness_survey_medium",
   "backend": "rust",
   "has_rust_backend": true,
-  "total_seconds": 0.5398647089999999,
+  "total_seconds": 0.5770147080000001,
   "memory": {
     "available": true,
-    "start_mb": 133.16,
-    "peak_mb": 185.38,
-    "growth_mb": 52.22,
+    "start_mb": 135.83,
+    "peak_mb": 189.91,
+    "growth_mb": 54.08,
     "sampler_interval_s": 0.01
   },
   "phases": {
     "1_naive_fit_no_survey_design": {
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+      "seconds": 0.014149625000000055,
       "ok": true,
       "error": null
     },
     "2_tsl_strata_psu_fpc": {
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+      "seconds": 0.03726633299999993,
       "ok": true,
       "error": null
     },
     "3_replicate_weights_jk1": {
-      "seconds": 0.191542875,
+      "seconds": 0.20208641699999985,
       "ok": true,
       "error": null
     },
     "4_multi_outcome_loop_3_metrics": {
-      "seconds": 0.105974083,
+      "seconds": 0.14449316599999995,
       "ok": true,
       "error": null
     },
     "5_check_parallel_trends": {
-      "seconds": 0.02876208299999994,
+      "seconds": 0.022887250000000137,
       "ok": true,
       "error": null
     },
     "6_placebo_refit_pre_period": {
-      "seconds": 0.06280441700000017,
+      "seconds": 0.07035533400000005,
       "ok": true,
       "error": null
     },
     "7_event_study_plus_honest_did": {
-      "seconds": 0.10540583399999992,
+      "seconds": 0.085751833,
       "ok": true,
       "error": null
     }

benchmarks/speed_review/baselines/brand_awareness_survey_small_python.json

@@ -2,47 +2,47 @@
   "scenario": "brand_awareness_survey_small",
   "backend": "python",
   "has_rust_backend": false,
-  "total_seconds": 0.15974079200000002,
+  "total_seconds": 0.21190179099999995,
   "memory": {
     "available": true,
-    "start_mb": 115.44,
-    "peak_mb": 125.66,
-    "growth_mb": 10.22,
+    "start_mb": 115.28,
+    "peak_mb": 131.0,
+    "growth_mb": 15.72,
     "sampler_interval_s": 0.01
   },
   "phases": {
     "1_naive_fit_no_survey_design": {
-      "seconds": 0.0016714159999999811,
+      "seconds": 0.0019152919999999574,
       "ok": true,
       "error": null
     },
     "2_tsl_strata_psu_fpc": {
-      "seconds": 0.0061952499999999855,
+      "seconds": 0.007577749999999939,
       "ok": true,
       "error": null
     },
     "3_replicate_weights_jk1": {
-      "seconds": 0.018200666000000032,
+      "seconds": 0.02303670899999999,
       "ok": true,
       "error": null
     },
     "4_multi_outcome_loop_3_metrics": {
-      "seconds": 0.02470079199999997,
+      "seconds": 0.052659917000000056,
       "ok": true,
       "error": null
     },
     "5_check_parallel_trends": {
-      "seconds": 0.008862999999999954,
+      "seconds": 0.009975750000000061,
       "ok": true,
       "error": null
     },
     "6_placebo_refit_pre_period": {
-      "seconds": 0.024017708000000026,
+      "seconds": 0.027377666999999994,
       "ok": true,
       "error": null
     },
     "7_event_study_plus_honest_did": {
-      "seconds": 0.07607645800000007,
+      "seconds": 0.08933650000000004,
       "ok": true,
       "error": null
     }

benchmarks/speed_review/baselines/brand_awareness_survey_small_rust.json

@@ -2,47 +2,47 @@
   "scenario": "brand_awareness_survey_small",
   "backend": "rust",
   "has_rust_backend": true,
-  "total_seconds": 0.19896133300000007,
+  "total_seconds": 0.19699320799999998,
   "memory": {
     "available": true,
-    "start_mb": 116.34,
-    "peak_mb": 129.73,
-    "growth_mb": 13.39,
+    "start_mb": 115.36,
+    "peak_mb": 130.86,
+    "growth_mb": 15.5,
     "sampler_interval_s": 0.01
   },
   "phases": {
     "1_naive_fit_no_survey_design": {
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+      "seconds": 0.0021563339999999265,
       "ok": true,
       "error": null
     },
     "2_tsl_strata_psu_fpc": {
-      "seconds": 0.005711999999999939,
+      "seconds": 0.006268332999999959,
       "ok": true,
       "error": null
     },
     "3_replicate_weights_jk1": {
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+      "seconds": 0.020846708999999963,
       "ok": true,
       "error": null
     },
     "4_multi_outcome_loop_3_metrics": {
-      "seconds": 0.06204845800000003,
+      "seconds": 0.027288292000000047,
       "ok": true,
       "error": null
     },
     "5_check_parallel_trends": {
-      "seconds": 0.00982324999999995,
+      "seconds": 0.01103129199999997,
       "ok": true,
       "error": null
     },
     "6_placebo_refit_pre_period": {
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+      "seconds": 0.02803533300000005,
       "ok": true,
       "error": null
     },
     "7_event_study_plus_honest_did": {
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       "ok": true,
       "error": null
     }