Python Physics-simuation Resources

Viewer for MuJoCo in Python Interactive renderer to use with the official Python bindings for MuJoCo. Starting with version 2.1.2, MuJoCo comes with n

Finite basis physics-informed neural networks (FBPINNs) This repository reproduces the results of the paper Finite Basis Physics-Informed Neural Netwo

PWF 2021 Física Sin Fronteras es un proyecto del Centro Internacional de Física Teórica (ICTP) en Trieste Italia. El ICTP es un centro dedicado a fome

CPDeform Code and data for paper Contact Points Discovery for Soft-Body Manipulations with Differentiable Physics at ICLR 2022 (Spotlight). @InProceed

solarSystemOrbitalSimulation graphical orbitational simulation of solar system planets with real values and physics implemented so you get a nice elli

PINN(s): Physics-Informed Neural Network(s) for von Karman vortex street This is

A 2-dimensional physics engine written in Cairo

Combinatorial model of ligand-receptor binding The binding of ligands to receptors is the starting point for many import signal pathways within a cell

Simple_Physics_Engine An ongoing process to make a physics engine using python. I am using this goal as a way to learn python in and out. I am trying

pythonPhysics Basic Python physics library. Must have pygame installed. How to: Sketon program is included. for p in env.particles: pygame.draw.circle

Welcome to MadAnalysis 5 Outline What is MadAnalysis 5? Requirements Downloading

This repository contains the code for the paper Localization and multifractal properties of the long-range Kitaev chain in the presence of an Aubry-André-Harper modulation.

ELD The implementation of CVPR 2020 (Oral) paper "A Physics-based Noise Formation Model for Extreme Low-light Raw Denoising" and its journal (TPAMI) v

What is it? Program for scientific research, which allows to simulate the phenomenon of self-focusing of different laser beams (including Gaussian, ri

PySDM PySDM is a package for simulating the dynamics of population of particles. It is intended to serve as a building block for simulation systems mo

The best way to use this material is by forking it by click the Fork button at the top, right corner. Then you will get your own copy to play with! Th

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

PlasmaPy PlasmaPy is an open source, community-developed Python 3.7+ package for plasma science. PlasmaPy intends to be for plasma science what Astrop

PyCharge PyCharge is an open-source computational electrodynamics Python simulator that can calculate the electromagnetic fields and potentials genera

AI2-THOR Rearrangement Challenge Welcome to the 2021 AI2-THOR Rearrangement Challenge hosted at the CVPR'21 Embodied-AI Workshop. The goal of this cha

tight-binder Introduction General purpose tight-binding code for electronic structure calculations based on the Slater-Koster approximation. The code

Characterizing possible failure modes in physics-informed neural networks This repository contains the PyTorch source code for the experiments in the

Package Continuous Integration Documentation About AbiPy is a python library to analyze the results produced by Abinit, an open-source program for the

NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and

ComBind ComBind integrates data-driven modeling and physics-based docking for improved binding pose prediction and binding affinity prediction. Given

PyTASER PyTASER is a Python (3.9+) library and set of command-line tools for classifying spectral features in bulk materials, post-DFT. The goal of th

Computational Methods for Physics & Astronomy Book version at: https://restrepo.github.io/ComputationalMethods by: Sebastian Bustamante 2014/2015 Dieg

About The ROOT system provides a set of OO frameworks with all the functionality needed to handle and analyze large amounts of data in a very efficien

SciANN: Neural Networks for Scientific Computations SciANN is a Keras wrapper for scientific computations and physics-informed deep learning. New to S

Notice: Support for Python 3.6 will be dropped in v.0.2.1, please plan accordingly! Efficient and Scalable Physics-Informed Deep Learning Collocation-

NeuralPDE NeuralPDE.jl is a solver package which consists of neural network solvers for partial differential equations using scientific machine learni

Sparse Physics-based and Interpretable Neural Networks for PDEs This repository contains the code and manuscript for research done on Sparse Physics-b

Gala is a Python package for Galactic and gravitational dynamics. Documentation The documentation for Gala is hosted on Read the docs. Installation an

GebPy is a Python-based, open source tool for the generation of geological data of minerals, rocks and complete lithological sequences. The data can be generated randomly or with respect to user-defined constraints, for example a specific element concentration within minerals and rocks or the order of units within a complete lithological profile.

Larch: Data Analysis Tools for X-ray Spectroscopy and More Documentation: http://xraypy.github.io/xraylarch Code: http://github.com/xraypy/xraylarch L

We tried to recreate this classic game using python physics libraries. The result is certainly hilarious but enjoyable. One of my very first physics application.

Quaternions in numpy This Python module adds a quaternion dtype to NumPy. The code was originally based on code by Martin Ling (which he wrote with he

Fast implementation of the MuyGPs Gaussian process hyperparameter estimation algorithm MuyGPs is a GP estimation method that affords fast hyperparamet

Deep Latent Force Models This repository contains a PyTorch implementation of the deep latent force model (DLFM), presented in the paper, Compositiona

A simple script written using symbolic python that takes as input a desired metric and automatically calculates and outputs the Christoffel Pseudo-Tensor, Riemann Curvature Tensor, Ricci Tensor, Scalar Curvature and the Kretschmann Scalar

VGPL-Visual-Prior PyTorch implementation for the visual prior component (i.e. perception module) of the Visually Grounded Physics Learner (VGPL). Give

FInite volume Neural Network (FINN) This repository contains the PyTorch code for models, training, and testing, and Python code for data generation t

pybullet-planning (previously ss-pybullet) A repository of PyBullet utility functions for robotic motion planning, manipulation planning, and task and

Front-end View Backend View Table of Contents Description Prerequisites Running Basic Information Measurements User Interface Feedback and usage Descr

Ohm-s-Law-Visualizer It's an application to calculate I from v and r using Ohm's Law. It can also plot a graph between V vs I. Story I'm doing my Unde

CaloGAN Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks. This repository c

Location-Aware Generative Adversarial Networks (LAGAN) for Physics Synthesis This repository contains all the code used in L. de Oliveira (@lukedeo),

3D-printable hexagonal mirror array capable of reflecting sunlight into arbitrary patterns

freud Overview The freud Python library provides a simple, flexible, powerful set of tools for analyzing trajectories obtained from molecular dynamics

PINO Physics-informed Neural Operator for Learning Partial Differential Equation Abstract: Machine learning methods have recently shown promise in sol

DiffuseAnimals: Reaction-Diffusion Models for the Generation of Biological Patterns Introduction Reaction-diffusion equations can be utilized in order

Code for sound field predictions in domains with impedance boundaries. Used for generating results from the paper

Test symmetries with sklearn decision tree models Setup Begin from an environment with a recent version of python 3. source setup.sh Leave the enviro

VRDP (NeurIPS 2021) Dynamic Visual Reasoning by Learning Differentiable Physics Models from Video and Language Mingyu Ding, Zhenfang Chen, Tao Du, Pin

ElectriPy ⚡ Visualize the electric field of a point charges network. 🔌 Installation Install ElectriPy package: $ pip install electripy You are all d

DQC: Differentiable Quantum Chemistry Differentiable quantum chemistry package. Currently only support differentiable density functional theory (DFT)

Physion: Evaluating Physical Prediction from Vision in Humans and Machines This repo contains code and data to reproduce the results in our paper, Phy

solar-system-pygame Controls UP/DOWN for Emulation Speed Control ESC for Pause/Unpause q to Quit c or ESC again to Continue LEFT CLICK to Add an orbit

dm_control: DeepMind Infrastructure for Physics-Based Simulation. DeepMind's software stack for physics-based simulation and Reinforcement Learning en

Multi-Objective Loss Balancing for Physics-Informed Deep Learning Code for ReLoBRaLo. Abstract Physics Informed Neural Networks (PINN) are algorithms

MuJoCo Physics MuJoCo stands for Multi-Joint dynamics with Contact. It is a general purpose physics engine that aims to facilitate research and develo

Links to works on deep learning algorithms for physics problems, TUM-I15 and beyond

pySPEDAS pySPEDAS is an implementation of the SPEDAS framework for Python. The Space Physics Environment Data Analysis Software (SPEDAS) framework is

Python-Orbit-Sim A 2D physics sim for orbits. Made using pygame and tkinter. High degree of intractability, allowing you to create celestial bodies of

PhyCRNet Physics-informed convolutional-recurrent neural networks for solving spatiotemporal PDEs Paper link: [ArXiv] By: Pu Ren, Chengping Rao, Yang

PiSL A python implementation of Physics-informed Spline Learning for nonlinear dynamics discovery. Sun, F., Liu, Y. and Sun, H., 2021. Physics-informe

💻 Physics2Calculator A simple and powerful calculator for Physics 2 🔌 Predefined constants pi = 3.14159... k = 8988000000 (coulomb constant) e0 = 8.

PINNpapers Contributed by IDRL lab. Introduction Physics-Informed Neural Network (PINN) has achieved great success in scientific computing since 2017.

Zero-Shot Domain Adaptation with a Physics Prior [arXiv] [sup. material] - ICCV 2021 Oral paper, by Attila Lengyel, Sourav Garg, Michael Milford and J

zoofs is a Python library for performing feature selection using a variety of nature-inspired wrapper algorithms. The algorithms range from swarm-intelligence to physics-based to Evolutionary. It's easy to use , flexible and powerful tool to reduce your feature size.

Interaction-Network-Pytorch Pytorch Implementraion of Interaction Networks for Learning about Objects, Relations and Physics. Interaction Network is a

Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch

IDRLnet IDRLnet is a machine learning library on top of PyTorch. Use IDRLnet if you need a machine learning library that solves both forward and inver

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

Physics-aware Difference Graph Networks for Sparsely-Observed Dynamics This repository is the official PyTorch implementation of "Physics-aware Differ

PyMedPhys is an open-source Medical Physics python library built by an open community that values and prioritises code sharing, review, improvement, and learning from each other. I

Brax is a differentiable physics engine that simulates environments made up of rigid bodies, joints, and actuators. It's also a suite of learning algorithms to train agents to operate in these environments (PPO, SAC, evolutionary strategy, and direct trajectory optimization are implemented).

PhySG: Inverse Rendering with Spherical Gaussians for Physics-based Relighting and Material Editing CVPR 2021. Project page: https://kai-46.github.io/

A toy project using OpenCV, PyMunk and Mediapipe the source code for my LindkedIn post It's just a toy project and I didn't write a documentation yet,

Physics-Aware Training (PAT) is a method to train real physical systems with backpropagation. It was introduced in Wright, Logan G. & Onodera, Tatsuhiro et al. (2021)1 to train Physical Neural Networks (PNNs) - neural networks whose building blocks are physical systems.

PyDy, short for Python Dynamics, is a tool kit written in the Python programming language that utilizes an array of scientific programs to enable the study of multibody dynamics. The goal is to have a modular framework and eventually a physics abstraction layer which utilizes a variety of backends that can provide the user with their desired workflow

Table of contents What is PEM? Overview Installation Usage Executable Library Telegram Bot Try OPEM in Your Browser! MATLAB Issues & Bug Reports Contr

Diffraction Simulations - Angular Spectrum Method Implementation of the Angular Spectrum method in Python to simulate Diffraction Patterns with arbitr