Frank14f
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1835f517e9
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chore: SR pipeline restructuring + DRL training infrastructure
SR_analysis restructured:
- Stage 1/2/3/4 unified pipeline with per-stage docs
- Old scripts/sindy/validate moved to old/archive
- Results reorganized: formulas/validations/figures with scene_registry.json
- Added diagnostic plots and PIPELINE.md
drl_pinball/train:
- New illusion training pipeline: env_illusion.py, train_illusion.py
- Cross-Re transfer: crossre_transfer.sh, extend_transfer.sh
- Calibration data: 0.75L/1L/1.5L/2L + re60/re100/re200/re400
- Launch scripts for multi-GPU training
Cleaned 100+ intermediate/dead files from SR_analysis.
Co-authored-by: Cursor <cursoragent@cursor.com>
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2026-07-05 17:36:29 +08:00 |
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Frank14f
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5f061bec06
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feat(train): cross-Re transfer pipeline — re60/re200/re400 calibrations + script
- Add crossre_transfer.sh: calibrate → transfer-train for re60→re200→re400
- Add re60 config (ν=0.006667, SI=800, uniform+free-slip, very weak shedding)
- Calibrate re60, re200, re400: FORCE_SCALE, SENS_SCALE, dtw_norm_scale, SIM_BP
- Fix all paths: use DynamisLab submodule CelerisLab, remove external ~/CelerisLab
- Remove _clean_cache() from envs/calibrate — CelerisLab handles internally
- Move V4 backups to old/: env_karman_2000x600, train_karman_2000x600, etc.
- train_karman.py: save model + vecnormalize every episode (non-optional)
- Update TRAIN_KNOWLEDGE.md: file structure, calibration table, cross-re guide
- All 3 Re verified: 5-episode transfer test passed (re60: 0.64, re200: 0.43, re400: 0.49)
Co-authored-by: Cursor <cursoragent@cursor.com>
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2026-07-03 00:21:49 +08:00 |
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Frank14f
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b3ee72e144
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feat(train): V5 parameterized training pipeline — Karman + Illusion verified
Calibration-driven, no_bias only, 2000x600 grid. All cases share unified
env/train/calibrate pattern. Multi-GPU server deployment ready.
Core additions:
- calibrate.py: Phase 0 calibration (karman/illusion), produces
calibration.json with rounded FORCE_SCALE, SENS_SCALE, SIM_BP/VAL
- env_karman.py: parameterized Karman cloak env (calibration + config_path)
- env_illusion.py: illusion env with FFT harmonics target (S_DIM=14)
- env_vortex.py: vortex cloaking env (lamb/taylor, MAX_STEPS=150)
- train_karman.py, train_illusion.py: parameterized training scripts
- launch_multi.sh: sequential multi-GPU launcher (7-min staggered)
- SERVER_DEPLOY.md: complete server setup, calibration, training guide
- calibrations/re100/ & calibrations/illusion_1L/: pre-run calibrations
Fixes:
- SIM_VAL[-1] 0.95 -> 1.0 (r_sim maps to full [0,1] range)
- Cross-Re configs: re50/200/400 (viscosity-only variants)
Verified end-to-end on GPU0+GPU1:
- Karman V5 20-ep: best reward 0.459 at Ep16 (monotonic rise)
- Illusion 20-ep: best reward 0.224 at Ep19 (harmonics, DTW learning)
Co-authored-by: Cursor <cursoragent@cursor.com>
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2026-07-01 20:10:27 +08:00 |
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Frank14f
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2ae248421d
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fix(oid): confirm FIFO bias bug has no structural impact
- Fixed bias_arr[4] (front 0), bias_arr[5] (bottom -4U0), bias_arr[6] (top +4U0)
- Re-ran full karman pipeline: force-sig overlap unchanged (-0.034)
- Force-OID still beats POD (0.295 vs 0.068, was 0.750 vs 0.418)
- Absolute R2 shifted because corrected FIFO changed PPO trajectory start
- Structural conclusion (force-sig near-orthogonal) is robust
Co-authored-by: Cursor <cursoragent@cursor.com>
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2026-06-30 16:26:54 +08:00 |
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