sdepack 0.1.2

Runge-Kutta Numerical Integration Stochastic Differential Equations for Python

sdepack

Runge-Kutta Numerical Integration of Stochastic Differential Equations for Python

sdepack is a high-performance Python library for numerically solving scalar stochastic differential equations (SDEs) using stochastic Runge-Kutta methods. It offers deterministic, seed-controlled integration of Itô SDEs of the form:

$$dX(t) = F(X, t),dt + Q,G(X, t),dW(t)$$

Solvers range from the first-order Euler-Maruyama scheme to fourth-order stochastic Runge-Kutta methods using Kasdin coefficients.

Quick example

import numpy as np
import sdepack

x = np.zeros(101, dtype=np.float64)
sdepack.rk4_ti_solve(
    lambda x: -0.5 * x,     # drift
    lambda x: 1.0,           # diffusion
    x, 0.0, 10.0, 1.0, 100, 0.1, 42
)

Installation

pip install sdepack

Requires Python 3.10+ and NumPy. See the full installation guide for conda, poetry, and source builds.

Documentation

• Theory — mathematical background, Itô SDEs, convergence
• Quickstart — runnable examples
• API Reference — solver signatures and parameters
• References — literature citations

License

MIT — see LICENSE.