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

Deep learning library for solving differential equations and more

DeepXDE Voting on whether we should have a Slack channel for discussion. DeepXDE is a library for scientific machine learning. Use DeepXDE if you need

1.4k Dec 29, 2022

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

Score-Based Generative Modeling through Stochastic Differential Equations This repo contains a PyTorch implementation for the paper Score-Based Genera

757 Jan 4, 2023

Python framework for Stochastic Differential Equations modeling

SDElearn: a Python package for SDE modeling This package implements functionalities for working with Stochastic Differential Equations models (SDEs fo

4 May 10, 2022

Visualizations of some specific solutions of different differential equations.

Diff_sims Visualizations of some specific solutions of different differential equations. Heat Equation in 1 Dimension (A very beautiful and elegant ex

2 Jan 13, 2022

Combines power of torch, numerical methods to conquer and solve ALL {O,P}DEs

torch_DE_solver Combines power of torch, numerical methods and math overall to conquer and solve ALL {O,P}DEs There are three examples to provide a li

28 Dec 12, 2022

Numerical Methods with Python, Numpy and Matplotlib

Numerical Bric-a-Brac Collections of numerical techniques with Python and standard computational packages (Numpy, SciPy, Numba, Matplotlib ...). Diffe

10 Dec 20, 2021

FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization

FuseDream This repo contains code for our paper (paper link): FuseDream: Training-Free Text-to-Image Generation with Improved CLIP+GAN Space Optimizat

191 Dec 31, 2022

Using NumPy to solve the equations of fluid mechanics together with Finite Differences, explicit time stepping and Chorin's Projection methods

Computational Fluid Dynamics in Python Using NumPy to solve the equations of fluid mechanics 🌊 🌊 🌊 together with Finite Differences, explicit time

4 Nov 12, 2022

An okayish python script to generate a random Euler circuit with given number of vertices and edges.

Euler-Circuit-Test-Case-Generator An okayish python script to generate a random Euler circuit with given number of vertices and edges. Executing the S

1 Nov 13, 2021

Simple program to easily view Euler parameters in 3D.

5 Aug 20, 2021

Simple Linear 2nd ODE Solver GUI - A 2nd constant coefficient linear ODE solver with simple GUI using euler's method

Simple_Linear_2nd_ODE_Solver_GUI Description It is a 2nd constant coefficient li

4 Feb 5, 2022

Double pendulum simulator using a symplectic Euler's method and Hamiltonian mechanics

Symplectic Double Pendulum Simulator Double pendulum simulator using a symplectic Euler's method. The program calculates the momentum and position of

1 Jan 12, 2022

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

Bayesian Methods for Hackers Using Python and PyMC The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chap

25.1k Jan 2, 2023

A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.

Knodle (Knowledge-supervised Deep Learning Framework) - a new framework for weak supervision with neural networks. It provides a modularization for se

93 Nov 6, 2022

Here, I have discuss the three methods of list reversion. The three methods are built-in method, slicing method and position changing method.

Three-different-method-for-list-reversion Here, I have discuss the three methods of list reversion. The three methods are built-in method, slicing met

4 Sep 24, 2021

Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

5 Sep 16, 2022

A package with multiple bias correction methods for climatic variables, including the QM, DQM, QDM, UQM, and SDM methods

9 Nov 18, 2022

Analog clock that shows the weather instead of the actual numerical hour it points to.

Eli's weatherClock An digital analog clock but instead of showing the hours, the clock shows the weather at that hour of the day. So instead of showin

154 Dec 1, 2022

The FinQA dataset from paper: FinQA: A Dataset of Numerical Reasoning over Financial Data

Data and code for EMNLP 2021 paper "FinQA: A Dataset of Numerical Reasoning over Financial Data"

114 Dec 29, 2022

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/

The windML framework provides an easy-to-use access to wind data sources within the Python world, building upon numpy, scipy, sklearn, and matplotlib. Renewable Wind Energy, Forecasting, Prediction

windml Build status : The importance of wind in smart grids with a large number of renewable energy resources is increasing. With the growing infrastr

125 Dec 24, 2022

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

You might also like...

Deep learning library for solving differential equations and more

PyTorch implementation for Score-Based Generative Modeling through Stochastic Differential Equations (ICLR 2021, Oral)

Python framework for Stochastic Differential Equations modeling

Visualizations of some specific solutions of different differential equations.

Combines power of torch, numerical methods to conquer and solve ALL {O,P}DEs

Numerical Methods with Python, Numpy and Matplotlib

FuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space OptimizationFuseDream: Training-Free Text-to-Image Generationwith Improved CLIP+GAN Space Optimization

Using NumPy to solve the equations of fluid mechanics together with Finite Differences, explicit time stepping and Chorin's Projection methods

An okayish python script to generate a random Euler circuit with given number of vertices and edges.

Simple program to easily view Euler parameters in 3D.

Simple Linear 2nd ODE Solver GUI - A 2nd constant coefficient linear ODE solver with simple GUI using euler's method

Double pendulum simulator using a symplectic Euler's method and Hamiltonian mechanics

aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

A PyTorch-based open-source framework that provides methods for improving the weakly annotated data and allows researchers to efficiently develop and compare their own methods.

Here, I have discuss the three methods of list reversion. The three methods are built-in method, slicing method and position changing method.

Implementation of temporal pooling methods studied in [ICIP'20] A Comparative Evaluation Of Temporal Pooling Methods For Blind Video Quality Assessment

A package with multiple bias correction methods for climatic variables, including the QM, DQM, QDM, UQM, and SDM methods

Analog clock that shows the weather instead of the actual numerical hour it points to.

The FinQA dataset from paper: FinQA: A Dataset of Numerical Reasoning over Financial Data

Releases(v1.0.0)

v1.0.0(Oct 25, 2021)

Owner

Aleksey Korshuk

Application for viewing pokemon regional variants.

This is a learning tool and exploration app made using the Dash interactive Python framework developed by Plotly

a python function to plot a geopandas dataframe

A little word cloud generator in Python

LinkedIn connections analyzer

A Python package for caclulations and visualizations in geological sciences.

Using SQLite within Python to create database and analyze Starcraft 2 units data (Pandas also used)

The visual framework is designed on the idea of module and implemented by mixin method

Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:

Implement the Perspective open source code in preparation for data visualization

Apache Superset is a Data Visualization and Data Exploration Platform

nptsne is a numpy compatible python binary package that offers a number of APIs for fast tSNE calculation.

erdantic is a simple tool for drawing entity relationship diagrams (ERDs) for Python data model classes

demir.ai Dataset Operations

A python script and steps to display locations of peers connected to qbittorrent

daily report of @arkinvest ETF activity + data collection

Make sankey, alluvial and sankey bump plots in ggplot

Automatic data visualization in atom with the nteract data-explorer

A simple python tool for explore your object detection dataset

The windML framework provides an easy-to-use access to wind data sources within the Python world, building upon numpy, scipy, sklearn, and matplotlib. Renewable Wind Energy, Forecasting, Prediction