ivp

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A library of numerical methods for solving initial value problems (IVPs)
for Rust and Python.

This library provides a pure Rust implementation of SciPy's solve_ivp function with slight modifications to the API to better fit Rust's design patterns. It is also available as a Python package with a SciPy-compatible API.

Features

Currently implemented solvers:

• DOP853: An 8th order Dormand-Prince method with step-size control and dense output.
• DOPRI5: A 5th order Dormand-Prince method with step-size control and dense output.
• RK4: The classic 4th order Runge-Kutta method with fixed step-size and cubic Hermite interpolation for dense output.
• RK23: A 3rd order Runge-Kutta method with 2nd order error estimate for step-size control.
• Radau: A 5th order implicit Runge-Kutta method of Radau IIA type with step-size control and dense output.
• BDF: A variable-order (1 to 5) Backward Differentiation Formula method for stiff ODEs with adaptive step-size control and dense output.

Installation

Rust

cargo add ivp

Python

pip install ivp-rs

Example Usage (Python)

from ivp import solve_ivp
import numpy as np

def exponential_decay(t, y):
    return -0.5 * y

# Solve the ODE
sol = solve_ivp(exponential_decay, (0, 10), [1.0], method='RK45', rtol=1e-6, atol=1e-9)

print(f"Final time: {sol.t[-1]}")
print(f"Final state: {sol.y[:, -1]}")