Notebook Improvements:
- Fixed 05_performance_benchmarks.ipynb: Reduced observation count from 50k to 10k max
- Fixed mean_field_games_tutorial.ipynb: Improved numerical stability
- Reduced grid size (100x100 -> 50x50) for Python implementation
- Added CFL condition checking and auto-adjustment
- Implemented semi-implicit schemes for better stability
- Added sub-stepping for Fokker-Planck solver
- Enhanced error handling with NaN/Inf detection
- Added graceful convergence handling
Marketing Materials:
- Created LINKEDIN_POST.md for v1.0.0 announcement
- Compelling narrative with real benchmarks
- Clear call-to-action for stars and contributions
- Links to documentation and installation
Status:
- All 8 notebooks now functional (100% success rate)
- Ready for crates.io and PyPI publication
- Professional presentation for open source community
- Add python_bindings.rs with MFGConfigPy and solve_mfg_1d_rust
- Update notebook to compare Rust vs Python implementations
- Add performance benchmarking and accuracy validation
- Include convergence plots and 3D visualizations
- Update __init__.py to expose MFG functions
Note: Python bindings need maturin build due to macOS linker issues with cargo
- Add complete mean_field module with 6 submodules
- Implement HJB and Fokker-Planck PDE solvers with rayon parallelization
- Add forward-backward fixed-point iteration algorithm
- Include Nash equilibrium and optimal transport utilities
- Add comprehensive Jupyter notebook tutorial with:
* Mathematical formulation (HJB and FP equations)
* Finite difference methods explanation
* Complete congestion game example
* 3D visualizations and convergence plots
* Citations to Jiang, Chewi, Pooladian (2023) paper
- All tests passing (5 tests in mean_field module)
- Based on 'Numerical Methods for Mean Field Games' PDF algorithms
ThotDjehuty