Anto01
f13563d7ab
Documentation: - Add docs/06_PHYSICS/ with Zernike fundamentals and OPD method docs - Add docs/guides/CMA-ES_EXPLAINED.md optimization guide - Update CLAUDE.md and ATOMIZER_CONTEXT.md with current architecture - Update OP_01_CREATE_STUDY protocol Planning: - Add DYNAMIC_RESPONSE plans for random vibration/PSD support - Add OPTIMIZATION_ENGINE_MIGRATION_PLAN for code reorganization Insights System: - Update design_space, modal_analysis, stress_field, thermal_field insights - Improve error handling and data validation NX Journals: - Add analyze_wfe_zernike.py for Zernike WFE analysis - Add capture_study_images.py for automated screenshots - Add extract_expressions.py and introspect_part.py utilities - Add user_generated_journals/journal_top_view_image_taking.py Tests & Tools: - Add comprehensive Zernike OPD test suite - Add audit_v10 tests for WFE validation - Add tools for Pareto graphs and mirror data extraction - Add migrate_studies_to_topics.py utility Knowledge Base: - Initialize LAC (Learning Atomizer Core) with failure/success patterns Dashboard: - Update Setup.tsx and launch_dashboard.py - Add restart-dev.bat helper script 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
51 lines
1.9 KiB
Python
51 lines
1.9 KiB
Python
"""Debug insights availability for a study."""
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import sys
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sys.path.insert(0, ".")
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from pathlib import Path
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# Test study path resolution
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study_id = 'm1_mirror_cost_reduction_V9'
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STUDIES_DIR = Path('studies')
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# Check nested path
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for topic_dir in STUDIES_DIR.iterdir():
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if topic_dir.is_dir():
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study_dir = topic_dir / study_id
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if study_dir.exists():
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print(f"Found study at: {study_dir}")
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print(f"Has 1_setup: {(study_dir / '1_setup').exists()}")
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print(f"Has 2_results: {(study_dir / '2_results').exists()}")
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# Check what insights are available
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from optimization_engine.insights import list_available_insights, get_configured_insights, recommend_insights_for_study
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print("\n--- Available insights (can_generate=True) ---")
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available = list_available_insights(study_dir)
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print(f"Count: {len(available)}")
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for a in available:
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print(f" - {a}")
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print("\n--- Configured insights ---")
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configured = get_configured_insights(study_dir)
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print(f"Count: {len(configured)}")
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for c in configured:
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print(f" - {c.type}: {c.name}")
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print("\n--- Recommendations ---")
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recs = recommend_insights_for_study(study_dir)
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print(f"Count: {len(recs)}")
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for r in recs:
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print(f" - {r['type']}: {r['name']}")
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# Test individual insight can_generate
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print("\n--- Testing each insight's can_generate ---")
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from optimization_engine.insights import get_insight, list_insights
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for info in list_insights():
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insight = get_insight(info['type'], study_dir)
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if insight:
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can = insight.can_generate()
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print(f" {info['type']:20} can_generate={can}")
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break
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