Numerical methods for ordinary differential equations: Euler, Improved Euler, Runge-Kutta.

Last update: Apr 29, 2022

Overview

Numerical methods

Numerical methods for ordinary differential equations are methods used to find numerical approximations to the solutions of ordinary differential equations (ODEs). Their use is also known as "numerical integration", although this term can also refer to the computation of integrals.

In this app we use:

Euler
Improved Euler
Runge-Kutta

Check PDF report for more details.

How to use

You can install and run from source with:

git clone https://github.com/AlekseyKorshuk/numerical-methods --recursive
cd numerical-methods
pip install -r requirements.txt
python main.py

Now visit 127.0.0.1:8050.

Sample results

Graphs

Exact and numerical solutions

Total approximation error depending on the number of grid cells

Local truncation error

Global truncation error

UML diagram

Toggle callback graph

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Releases(v1.0.0)

v1.0.0(Oct 25, 2021)

Full Changelog: https://github.com/AlekseyKorshuk/numerical-methods/commits/v1.0.0
Source code(tar.gz)
Source code(zip)

Owner

Aleksey Korshuk

Telegram: https://t.me/goodimpression

GitHub Repository https://numerical-methods-ode.herokuapp.com/

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Numerical methods for ordinary differential equations: Euler, Improved Euler, Runge-Kutta.

Related tags

Overview

Numerical methods

How to use

Sample results

Graphs

Exact and numerical solutions

Total approximation error depending on the number of grid cells

Local truncation error

Global truncation error

UML diagram

Toggle callback graph

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