- WORK IN PROGRESS
Monte Carlo method based on a walk-on-spheres implementation for solving a 2D Poisson PDE written in Python.
Based on the excellent video by Keenan Crane from Carnegie Mellon University and a code snippet he provided here.
The version presented here utilizes recursion.
Associated literature and video from the original author: "Grid-Free Monte Carlo for PDEs with Spatially Varying Coefficients" by Sawhney, Seyb, Jarosz, Crane.
Print help on usage:
python Random_walks_Poisson_solver.py -h
Do a single walk and plot it.
python Random_walks_Poisson_solver.py -d -v
Run the solver using dedicated settings for number of walks, accuracy, and maximum number of steps per walk.
python Random_walks_Poisson_solver.py -w 100 -e 0.01 -s 30
- Python 3.9+ (due to the version of argparse which is used)
- Numpy
- Matplotlib
2022 Andreas Ennemoser – andreas.ennemoser@aon.at
Distributed under the MIT license. See LICENSE for more information.