A Tutorial for the Odespy Interface to ODE Solvers

Contents:

• A Tutorial for the Odespy Interface to ODE Solvers
  • Motivation
    • Traditional Approach
    • Odespy’s Unified Interface
    • Methods and Implementations Offered by Odespy
  • Installation
  • Basic Usage
    • Overview
    • First Example: Logistic Growth
    • Parameters in the Right-Hand Side Function
    • Continuing a Previous Simulation
    • Termination Criterion for the Simulation
    • A Class-Based Implementation
    • Using Other Symbols
    • Example: Solving an ODE System
    • The Euler-Cromer Method
    • Testing Several Methods
  • More Advanced Implementations
    • Make a Subclass of Class Problem
    • Example: Solving a Complex ODE Problem
    • Avoiding Callbacks to Python
    • Example: Solving a Stochastic Differential Equation
  • Adaptive Methods
    • The Test Problem
    • Running Simple Methods
    • Running the Runge-Kutta-Fehlberg Method
    • Testing More Adaptive Solvers
    • Extensive Testing
  • Solving Partial Differential Equations
    • Discretization in Space
    • Implementation
    • Experiments
  • Inner Workings of the Package
    • Solver Parameters
    • Solver Classes
    • A Very Simple Subclass
    • A Subclass with More Code
    • A Simple Example of an Implicit Method
  • Troubleshooting
    • Constructor takes exactly two arguments, 5 given

Indices and tables

• Index
• Module Index
• Search Page