SimPhy
Physion
Algodoo
Akinator
Crayon Physics Deluxe
Minecraft
myPhysicsLab
PhET Interactive Simulations
Matplotlib
Pandas
NumPy
Seaborn
D3.js
Plotly
GnuPlot
Jupyter
You can create different types of bodies inside its physics world with different parameters like restitution, friction, velocity etc. attach them with different types of Joints like spring, rope, chain, pulley etc. Due to its native Physics engine the accuracy in solving is great.
One can visualize the motion with the numerous built in tools like tracers of points on body or Body ghosting, Graphs between different parameters( like KE, speed, velocity, momentum, etc), FBD of grouped and ungrouped objects, Camera tool ( to set frame of reference) etc.
It supports gravitational , electric, magnetic and buoyancy fields. One can even set variable fields ( time dependent ) and can easily change the fields as well using sliders.
One can create their own GUI elements in it like buttons , sliders , checkboxes , List , dialog etc. and even can write scriptable codes in them for different events in its in-built powerful scripting editing tool.
SimPhy MatplotlibNice interface and you can even add extra fields and script on buttons and sliders as well.
Based on our record, Matplotlib seems to be more popular. It has been mentiond 114 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
Numbers are useful, but sometimes itโs easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 7 months ago
NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 8 months ago
The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโฆ. - Source: dev.to / 10 months ago
Physion - Physics Simulation Sandbox
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
Algodoo - Algodoo is a 2D simulator freeware product designed as a physics learning tool. It was originally created by Emil Emerfeldt as part of his masterโs thesis in 2008. Read more about Algodoo.
NumPy - NumPy is the fundamental package for scientific computing with Python
Akinator - Akinator is an entertainment app that acts like a digital genie that can read your mind. The game will ask you a few questions about the character you have chosen, and it will attempt to guess the character from your provided answers.
Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.
