From 58414feb1ac273ad9a03cd5715ff61d1c19ca450 Mon Sep 17 00:00:00 2001 From: Jammy2211 Date: Thu, 15 Oct 2026 16:48:29 +0100 Subject: [PATCH] =?UTF-8?q?projects.yaml:=20analytic=5Fgaussian,=20ep=5Fto?= =?UTF-8?q?y=5Fgaussian=20=E2=86=92=20Science/active=20and=20RAL=20active/?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit They are Cortex science projects, not inference benchmarks; inference/ and profiling/ keep only the autolens/autofit benchmark repos (mirrors Pulse/Insight). Co-Authored-By: Claude Opus 5.5 --- dashboard.html | 10 +++++----- dashboard.md | 8 ++++---- projects.yaml | 8 ++++---- state.json | 2 +- 4 files changed, 14 insertions(+), 14 deletions(-) diff --git a/dashboard.html b/dashboard.html index 293dd4e..d4b303d 100644 --- a/dashboard.html +++ b/dashboard.html @@ -331,7 +331,7 @@ - Open slope_hierarchy_scale: https://github.com/PyAutoLabs/slope_hierarchy_scale - Open ic50_workspace: https://github.com/Jammy2211/ic50_workspace - Open autolens_inference: https://github.com/PyAutoLabs/autolens_inference -- Open autofit_inference: https://github.com/PyAutoLabs/autofit_inference
Last updated 2026-10-15 13:25:33 UTC
↻ Update

+- Open autofit_inference: https://github.com/PyAutoLabs/autofit_inference
Last updated 2026-10-15 15:48:28 UTC
↻ Update

@@ -451,7 +451,7 @@

euclid_dr1 — Does the sep1 DR1 delivery reproduce the ten prelim lenses by

analytic_gaussian — Graphical and EP against a closed-form Gaussian posterior, at ensemble scale

-

active · ral · PyAutoCortex#34 · projects/analytic_gaussian.md · local /mnt/c/Users/Jammy/Science/inference/analytic_gaussian · RAL /mnt/ral/jnightin/analytic_gaussian

+

active · ral · PyAutoCortex#34 · projects/analytic_gaussian.md · local /mnt/c/Users/Jammy/Science/active/analytic_gaussian · RAL /mnt/ral/jnightin/active/analytic_gaussian

Now

Wave 1 (342413, 200 seeds at N=5) is accepted as the baseline: autofit EP is exact on the Gaussian leg, leg B sigma misses as pre-registered (78/200), collapse rate 0/200. On criterion 2, astra and an independent Opus review both favour an under-calibrated mu threshold (calibrated on five unrepresentative seeds) and found no defect in the minimal-EP control; both flag the per-site sigma>0 clip (analytic_ep_minimal.py:333) as the one audit target, and astra will not clear the control without an independent reconstruction of the EP fixed point. Next: run the planned diagnostic (archive/tasks/analytic_gaussian/minimal_ep_legb_mu_threshold.md) on a passing, an edge and the worst mu seed; the N=25 rung stays written but unsubmitted until it lands.

Runs

@@ -465,11 +465,11 @@

analytic_gaussian — Graphical and EP against a closed-form Gaussian poster
  • 2026-09-10 — note — question: Is criterion 2's mu threshold or the minimal-EP control wrong — planned, never run [archive/tasks/analytic_gaussian/minimal_ep_legb_mu_threshold.md]

    • full log

    -

    resume analytic_gaussian

    +

    resume analytic_gaussian

    ep_toy_gaussian — NUTS versus three EP fits on the #1405 collapse toy at N=50

    -

    active · ral · ep_toy_gaussian#1 · projects/ep_toy_gaussian.md · local /mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian · RAL /mnt/ral/jnightin/ep_toy_gaussian

    +

    active · ral · ep_toy_gaussian#1 · projects/ep_toy_gaussian.md · local /mnt/c/Users/Jammy/Science/active/ep_toy_gaussian · RAL /mnt/ral/jnightin/active/ep_toy_gaussian

    Now

    Wave 1 (n50_seed42: 342639 + 342640_[0-2]) failed on infrastructure — EP x3 on EMFILE (fixed by PyAutoFit#1632/#1634, both in the RAL mirror at 404b3e5f7), NUTS on OOM at the 8 GB cap while XLA compiled the 50-factor window-adaptation scan, which grows with N (≥5.4 GB at N=20 locally). Wave 2 is prepared but not submitted: sample n50_seed42_w2 (free locally and on RAL; still needs its toy.SAMPLES entry), submit_nuts raised to 64 GB, submit_ep unchanged at 8 GB (peak ~590 MB). The collapse question at N=50 is unanswered; only n5_smoke speaks (EP RECOVER 3/3, NUTS 49.89/11.14). Next: human go, add the sample entry, push and submit NUTS then EP with SAMPLE=n50_seed42_w2 exported.

    Runs

    @@ -483,7 +483,7 @@

    ep_toy_gaussian — NUTS versus three EP fits on the #1405 collapse toy at N
  • 2026-09-24 — note — per-search overhead profile on this toy (2026-09-24, laptop, N=5, max_steps=3): 2.45 s per Dynesty factor search, ~1.47 s dynesty run_nested + ~0.98 s autofit wrapper (plots, a redundant second run_nested pass, samples writes); inside run_…

    • full log

    -

    resume ep_toy_gaussian

    +

    resume ep_toy_gaussian

    slope_hierarchy_scale — Hierarchical slope recovery with graphical and EP at N=25 to 50

    diff --git a/dashboard.md b/dashboard.md index 65858df..be9a580 100644 --- a/dashboard.md +++ b/dashboard.md @@ -177,7 +177,7 @@ Use the cortex skill. — resume euclid_dr1: read PyAutoCortex projects/euclid_d ### analytic_gaussian — Graphical and EP against a closed-form Gaussian posterior, at ensemble scale -active · ral · [PyAutoCortex#34](https://github.com/PyAutoLabs/PyAutoCortex/issues/34) · [projects/analytic_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/analytic_gaussian.md) · local `/mnt/c/Users/Jammy/Science/inference/analytic_gaussian` · RAL `/mnt/ral/jnightin/analytic_gaussian` +active · ral · [PyAutoCortex#34](https://github.com/PyAutoLabs/PyAutoCortex/issues/34) · [projects/analytic_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/analytic_gaussian.md) · local `/mnt/c/Users/Jammy/Science/active/analytic_gaussian` · RAL `/mnt/ral/jnightin/active/analytic_gaussian` **Now** @@ -200,14 +200,14 @@ Wave 1 (342413, 200 seeds at N=5) is accepted as the baseline: autofit EP is exa
    📋 resume analytic_gaussian ``` -Use the cortex skill. — resume analytic_gaussian: read PyAutoCortex projects/analytic_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/inference/analytic_gaussian/wiki/project/state.md and the assistant autofit_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say. +Use the cortex skill. — resume analytic_gaussian: read PyAutoCortex projects/analytic_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/analytic_gaussian/wiki/project/state.md and the assistant autofit_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say. ```
    ### ep_toy_gaussian — NUTS versus three EP fits on the #1405 collapse toy at N=50 -active · ral · [ep_toy_gaussian#1](https://github.com/PyAutoLabs/ep_toy_gaussian/issues/1) · [projects/ep_toy_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ep_toy_gaussian.md) · local `/mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian` · RAL `/mnt/ral/jnightin/ep_toy_gaussian` +active · ral · [ep_toy_gaussian#1](https://github.com/PyAutoLabs/ep_toy_gaussian/issues/1) · [projects/ep_toy_gaussian.md](https://github.com/PyAutoLabs/PyAutoCortex/blob/main/projects/ep_toy_gaussian.md) · local `/mnt/c/Users/Jammy/Science/active/ep_toy_gaussian` · RAL `/mnt/ral/jnightin/active/ep_toy_gaussian` **Now** @@ -230,7 +230,7 @@ Wave 1 (n50_seed42: 342639 + 342640_[0-2]) failed on infrastructure — EP x3 on
    📋 resume ep_toy_gaussian ``` -Use the cortex skill. — resume ep_toy_gaussian: read PyAutoCortex projects/ep_toy_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian/wiki/project/state.md and the assistant autofit_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say. +Use the cortex skill. — resume ep_toy_gaussian: read PyAutoCortex projects/ep_toy_gaussian.md (Now, Runs, Log) and then /mnt/c/Users/Jammy/Science/active/ep_toy_gaussian/wiki/project/state.md and the assistant autofit_assistant's AGENTS.md; tell me where I left off and what I said I would do next. Submit nothing and log nothing until I say. ```
    diff --git a/projects.yaml b/projects.yaml index 9b88bf7..a3799f0 100644 --- a/projects.yaml +++ b/projects.yaml @@ -117,8 +117,8 @@ euclid_dr1: analytic_gaussian: remote: none - local_path: /mnt/c/Users/Jammy/Science/inference/analytic_gaussian - ral_root: /mnt/ral/jnightin/analytic_gaussian + local_path: /mnt/c/Users/Jammy/Science/active/analytic_gaussian + ral_root: /mnt/ral/jnightin/active/analytic_gaussian mirror: none sync_cli: hpc/sync sync_verbs: [push, pull, logs, sync, status, submit, push-submit, jobs, sacct, cancel, tail, du, check] @@ -131,8 +131,8 @@ analytic_gaussian: ep_toy_gaussian: remote: PyAutoLabs/ep_toy_gaussian - local_path: /mnt/c/Users/Jammy/Science/inference/ep_toy_gaussian - ral_root: /mnt/ral/jnightin/ep_toy_gaussian + local_path: /mnt/c/Users/Jammy/Science/active/ep_toy_gaussian + ral_root: /mnt/ral/jnightin/active/ep_toy_gaussian mirror: none sync_cli: hpc/sync sync_verbs: [push, pull, logs, sync, status, submit, push-submit, jobs, sacct, cancel, tail, du, check] diff --git a/state.json b/state.json index 02afcd9..f772002 100644 --- a/state.json +++ b/state.json @@ -4,7 +4,7 @@ "repo": "PyAutoCortex", "status": "yellow", "headline": "YELLOW \u2014 8 active \u00b7 25 running", - "updated": "2026-10-15T13:25:33Z", + "updated": "2026-10-15T15:48:29Z", "pages_url": "https://pyautolabs.github.io/PyAutoCortex/", "items": [ {