All python stochastic differential equations (SDE) solver.
Built for stochastic simulations of hydrodynamically interacting brownian particles (molecular dynamics), but can do much more (such as option pricing in stochastic volitality models).
Uses jax, jax.jit and jax.grad for performace and ease of use.
import pychastic
problem = pychastic.sde_problem.SDEProblem(lambda x: 0.2*x,lambda x: 0.5*x,1.0,2.0)
solver = pychastic.sde_solver.SDESolver()
trajectory = solver.solve(problem)
import matplotlib.pyplot as plt
plt.plot(trajectory['time_values'],trajectory['solution_values'])
plt.show()This software is licensed under MIT license
Copyright (c) Radost Waszkiewicz and Maciej Bartczak (2021).
Waszkiewicz, R., Bartczak M., Kolasa K. and Lisicki M. Pychastic: Precise Brownian Dynamics using Taylor-Ito integrators in Python; SciPost Physics Codebases (2023)
@article{Waszkiewicz_2023,
title = {Pychastic: Precise Brownian dynamics using Taylor-It{\=o} integrators in Python},
author = {Waszkiewicz, Radost and Bartczak, Maciej and Kolasa, Kamil and Lisicki, Maciej},
year = 2023,
journal = {SciPost Physics Codebases},
pages = {11}
}