## Cleanup (v0.5.0) - Delete 102+ orphaned MCP session temp files - Remove build artifacts (htmlcov, dist, __pycache__) - Archive superseded plan docs (RALPH_LOOP V2/V3, CANVAS V3, etc.) - Move debug/analysis scripts from tests/ to tools/analysis/ - Archive redundant NX journals to archive/nx_journals/ - Archive monolithic PROTOCOL.md to docs/archive/ - Update .gitignore with missing patterns - Clean old study files (optimization_log_old.txt, run_optimization_old.py) ## Canvas UX (Phases 7-9) - Phase 7: Resizable panels with localStorage persistence - Left sidebar: 200-400px, Right panel: 280-600px - New useResizablePanel hook and ResizeHandle component - Phase 8: Enable all palette items - All 8 node types now draggable - Singleton logic for model/solver/algorithm/surrogate - Phase 9: Solver configuration - Add SolverEngine type (nxnastran, mscnastran, python, etc.) - Add NastranSolutionType (SOL101-SOL200) - Engine/solution dropdowns in config panel - Python script path support ## Documentation - Update CHANGELOG.md with recent versions - Update docs/00_INDEX.md - Create examples/README.md - Add docs/plans/CANVAS_UX_IMPROVEMENTS.md
Atomizer Examples
This directory contains example configurations and scripts demonstrating Atomizer capabilities.
Configuration Examples
| File | Description |
|---|---|
optimization_config_neural.json |
Neural surrogate-accelerated optimization |
optimization_config_protocol10.json |
IMSO (Intelligent Multi-Stage Optimization) example |
optimization_config_protocol12.json |
Custom extractor with Zernike analysis |
optimization_config_zernike_mirror.json |
Telescope mirror WFE optimization |
Scripts
| File | Description |
|---|---|
llm_mode_simple_example.py |
Basic LLM-driven optimization setup |
interactive_research_session.py |
Interactive research mode with visualization |
Models
The Models/ directory contains sample FEA models for testing:
- Bracket geometries
- Beam structures
- Mirror assemblies
Zernike Reference
The Zernike_old_reference/ directory contains legacy Zernike extraction code for reference purposes.
Usage
- Copy a configuration file to your study directory
- Modify paths and parameters for your model
- Run optimization with:
cd studies/your_study
python run_optimization.py
Or use the Canvas Builder in the dashboard (http://localhost:3003).