Files
Atomizer/atomizer-field/TESTING_CHECKLIST.md
Antoine d5ffba099e feat: Merge Atomizer-Field neural network module into main repository
Permanently integrates the Atomizer-Field GNN surrogate system:
- neural_models/: Graph Neural Network for FEA field prediction
- batch_parser.py: Parse training data from FEA exports
- train.py: Neural network training pipeline
- predict.py: Inference engine for fast predictions

This enables 600x-2200x speedup over traditional FEA by replacing
expensive simulations with millisecond neural network predictions.

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <noreply@anthropic.com>
2025-11-26 15:31:33 -05:00

278 lines
5.9 KiB
Markdown
Raw Blame History

This file contains ambiguous Unicode characters
This file contains Unicode characters that might be confused with other characters. If you think that this is intentional, you can safely ignore this warning. Use the Escape button to reveal them.
# AtomizerField Testing Checklist
Quick reference for testing status and next steps.
---
## ✅ Completed Tests
### Environment Setup
- [x] Conda environment created (`atomizer_field`)
- [x] All dependencies installed
- [x] NumPy MINGW-W64 issue resolved
- [x] No segmentation faults
### Smoke Tests (5/5)
- [x] Model creation (128,589 parameters)
- [x] Forward pass
- [x] Loss functions (4 types)
- [x] Batch processing
- [x] Gradient flow
### Simple Beam Test (7/7)
- [x] File existence (BDF + OP2)
- [x] Directory setup
- [x] Module imports
- [x] BDF/OP2 parsing (5,179 nodes, 4,866 elements)
- [x] Data validation
- [x] Graph conversion
- [x] Neural prediction (95.94 ms)
### Visualization
- [x] 3D mesh rendering
- [x] Displacement field (original + deformed)
- [x] Stress field (von Mises)
- [x] Report generation (markdown + images)
### Unit Validation
- [x] UNITSYS detection (MN-MM)
- [x] Material properties (E = 200 GPa)
- [x] Stress values (117 MPa reasonable)
- [x] Force values (2.73 MN validated)
- [x] Direction vectors preserved
---
## ❌ Not Yet Tested (Requires Trained Model)
### Physics Tests (0/4)
- [ ] Cantilever beam (analytical comparison)
- [ ] Equilibrium check (∇·σ + f = 0)
- [ ] Constitutive law (σ = C:ε)
- [ ] Energy conservation
### Learning Tests (0/4)
- [ ] Memorization (single case < 1% error)
- [ ] Interpolation (between cases < 10% error)
- [ ] Extrapolation (unseen loads < 20% error)
- [ ] Pattern recognition (physics transfer)
### Integration Tests (0/5)
- [ ] Batch prediction
- [ ] Gradient computation
- [ ] Optimization loop
- [ ] Uncertainty quantification
- [ ] Online learning
### Performance Tests (0/3)
- [ ] Accuracy benchmark (< 10% error)
- [ ] Speed benchmark (< 50 ms)
- [ ] Scalability (10K+ nodes)
---
## 🔧 Known Issues to Fix
### Minor (Non-blocking)
- [ ] Unit labels: "MPa" should be "kPa" (or convert values)
- [ ] Missing SPCs warning (investigate BDF)
- [ ] Unicode encoding (mostly fixed, minor cleanup remains)
### Documentation
- [ ] Unit conversion guide
- [ ] Training data generation guide
- [ ] User manual
---
## 🚀 Testing Roadmap
### Phase 1: Pre-Training Validation
**Status:** ✅ COMPLETE
- [x] Core pipeline working
- [x] Test case validated
- [x] Units understood
- [x] Visualization working
### Phase 2: Training Preparation
**Status:** 🔜 NEXT
- [ ] Fix unit labels (30 min)
- [ ] Document unit system (1 hour)
- [ ] Create training data generation script
- [ ] Generate 50 test cases (1-2 weeks)
### Phase 3: Initial Training
**Status:** ⏸️ WAITING
- [ ] Train on 50 cases (2-4 hours)
- [ ] Validate on 10 held-out cases
- [ ] Check loss convergence
- [ ] Run memorization test
### Phase 4: Physics Validation
**Status:** ⏸️ WAITING
- [ ] Cantilever beam test
- [ ] Equilibrium check
- [ ] Energy conservation
- [ ] Compare vs analytical solutions
### Phase 5: Full Validation
**Status:** ⏸️ WAITING
- [ ] Run full test suite (18 tests)
- [ ] Accuracy benchmarks
- [ ] Speed benchmarks
- [ ] Scalability tests
### Phase 6: Production Deployment
**Status:** ⏸️ WAITING
- [ ] Integration with Atomizer
- [ ] End-to-end optimization test
- [ ] Performance profiling
- [ ] User acceptance testing
---
## 📊 Test Commands Quick Reference
### Run Tests
```bash
# Activate environment
conda activate atomizer_field
# Quick smoke tests (30 seconds)
python test_suite.py --quick
# Simple Beam end-to-end (1 minute)
python test_simple_beam.py
# Physics tests (15 minutes) - REQUIRES TRAINED MODEL
python test_suite.py --physics
# Full test suite (1 hour) - REQUIRES TRAINED MODEL
python test_suite.py --full
```
### Visualization
```bash
# Mesh only
python visualize_results.py test_case_beam --mesh
# Displacement
python visualize_results.py test_case_beam --displacement
# Stress
python visualize_results.py test_case_beam --stress
# Full report
python visualize_results.py test_case_beam --report
```
### Unit Validation
```bash
# Check parsed data units
python check_units.py
# Check OP2 raw data
python check_op2_units.py
# Check actual values
python check_actual_values.py
```
### Training (When Ready)
```bash
# Generate training data
python batch_parser.py --input Models/ --output training_data/
# Train model
python train.py \
--data_dirs training_data/* \
--epochs 100 \
--batch_size 16 \
--loss physics
# Monitor training
tensorboard --logdir runs/
```
---
## 📈 Success Criteria
### Phase 1: Core System ✅
- [x] All smoke tests passing
- [x] End-to-end test passing
- [x] Real FEA data processed
- [x] Visualization working
### Phase 2: Training Ready 🔜
- [ ] Unit labels correct
- [ ] 50+ training cases generated
- [ ] Training script validated
- [ ] Monitoring setup (TensorBoard)
### Phase 3: Model Trained ⏸️
- [ ] Training loss < 0.01
- [ ] Validation loss < 0.05
- [ ] No overfitting (train ≈ val loss)
- [ ] Predictions physically reasonable
### Phase 4: Physics Validated ⏸️
- [ ] Equilibrium error < 1%
- [ ] Constitutive error < 5%
- [ ] Energy conservation < 5%
- [ ] Analytical test < 5% error
### Phase 5: Production Ready ⏸️
- [ ] Prediction error < 10%
- [ ] Inference time < 50 ms
- [ ] All 18 tests passing
- [ ] Integration with Atomizer working
---
## 🎯 Current Focus
**Status:** ✅ Core validation complete, ready for training phase
**Next immediate steps:**
1. Fix unit labels (optional, 30 min)
2. Generate training data (critical, 1-2 weeks)
3. Train model (critical, 2-4 hours)
**Blockers:** None - system ready!
---
## 📞 Quick Status Check
Run this to verify system health:
```bash
conda activate atomizer_field
python test_simple_beam.py
```
Expected output:
```
TEST 1: Files exist ✓
TEST 2: Directory setup ✓
TEST 3: Modules import ✓
TEST 4: BDF/OP2 parsed ✓
TEST 5: Data validated ✓
TEST 6: Graph created ✓
TEST 7: Prediction made ✓
[SUCCESS] All 7 tests passed!
```
---
*Testing Checklist v1.0*
*Last updated: November 24, 2025*
*Status: Phase 1 complete, Phase 2 ready to start*