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Description
Task 3: Hands-On Laboratory Infrastructure
Problem
No standardized interactive environment for experimentation.
Implementation Plan
Create 5 laboratory notebooks with shared infrastructure for hands-on RFH3 experimentation:
Base Infrastructure:
class RFH3_Lab:
"""Base class for all laboratory notebooks"""
def __init__(self):
self.rfh3 = RFH3() # Main factorizer instance
self.visualizer = ResonanceVisualizer()
self.benchmark_suite = BenchmarkSuite()
self.data_collector = ExperimentDataCollector()
self.export_manager = ResultExporter()
def setup_experiment(self, name: str, parameters: dict)
def run_experiment(self, test_cases: list)
def visualize_results(self, results: dict)
def export_findings(self, format: str = 'json')Laboratory Notebooks:
1. 06_laboratories/01_resonance_field_visualizer.ipynb
- Interactive 3D resonance field exploration
- Real-time field computation and visualization
- Parameter sliders for scale adjustments
- Factor highlighting and path tracing
- Export high-quality plots for publications
2. 06_laboratories/02_factorization_race_arena.ipynb
- Algorithm comparison and racing
- Side-by-side algorithm execution
- Real-time performance monitoring
- Statistical analysis of results
- Custom algorithm implementation
3. 06_laboratories/03_parameter_tuning_playground.ipynb
- Interactive parameter optimization
- Grid search and random search
- Bayesian optimization
- Multi-objective optimization
- Sensitivity analysis
4. 06_laboratories/04_algorithm_development_sandbox.ipynb
- Custom algorithm development
- Template-based algorithm creation
- Component testing framework
- Performance profiling tools
- Integration with main RFH3 system
5. 06_laboratories/05_benchmark_reproduction_lab.ipynb
- Reproduce published benchmarks
- Historical RSA challenge recreations
- Academic paper result reproduction
- Performance comparison analysis
- Verification of claimed improvements
Key Features
- Real-time Computation: Interactive widgets with live updates
- Export Capabilities: Results exportable in multiple formats (JSON, CSV, PNG, PDF)
- Reproducible Results: Seed management and parameter tracking
- Performance Monitoring: Resource usage tracking and optimization
- Integration: Direct integration with RFH3 codebase
Interactive Elements
- 3D plotly visualizations with zoom/rotate/slice controls
- Parameter sliders with real-time field updates
- Algorithm race leaderboards with live timing
- Optimization progress visualizations
- Custom algorithm code editors with syntax highlighting
Acceptance Criteria
- Consistent UI/UX across all laboratory notebooks
- Real-time computation and visualization
- Export capabilities for all experiments
- Reproducible results with seed management
- Integration with actual RFH3 codebase
- Performance monitoring and profiling
- Mobile-friendly responsive design
Dependencies
- Visualization infrastructure (Task 5)
- Interactive widgets framework
- Performance profiling tools
- Export utilities
Files to Create
notebooks/
├── 06_laboratories/
│ ├── shared_infrastructure/
│ │ ├── lab_framework.py
│ │ ├── experiment_data_collector.py
│ │ ├── result_exporter.py
│ │ └── benchmark_suite.py
│ ├── 01_resonance_field_visualizer.ipynb
│ ├── 02_factorization_race_arena.ipynb
│ ├── 03_parameter_tuning_playground.ipynb
│ ├── 04_algorithm_development_sandbox.ipynb
│ └── 05_benchmark_reproduction_lab.ipynb
└── shared/
└── laboratory/
├── widgets/
├── profiling/
└── export/
Implementation Notes
- Use Plotly for interactive 3D visualizations
- Implement ipywidgets for parameter controls
- Include performance profiling with memory/CPU monitoring
- Support multiple export formats for research publication
- Ensure compatibility with Google Colab and local Jupyter