DifferentialEquations.jl
mujoco
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DifferentialEquations.jl | mujoco | |
---|---|---|
6 | 20 | |
2,754 | 7,159 | |
1.5% | 4.0% | |
7.3 | 9.8 | |
17 days ago | 2 days ago | |
Julia | C++ | |
GNU General Public License v3.0 or later | Apache License 2.0 |
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DifferentialEquations.jl
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Startups are building with the Julia Programming Language
This lists some of its unique abilities:
https://docs.sciml.ai/DiffEqDocs/stable/
The routines are sufficiently generic, with regard to Julia’s type system, to allow the solvers to automatically compose with other packages and to seamlessly use types other than Numbers. For example, instead of handling just functions Number→Number, you can define your ODE in terms of quantities with physical dimensions, uncertainties, quaternions, etc., and it will just work (for example, propagating uncertainties correctly to the solution¹). Recent developments involve research into the automated selection of solution routines based on the properties of the ODE, something that seems really next-level to me.
[1] https://lwn.net/Articles/834571/
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From Common Lisp to Julia
https://github.com/SciML/DifferentialEquations.jl/issues/786. As you could see from the tweet, it's now at 0.1 seconds. That has been within one year.
Also, if you take a look at a tutorial, say the tutorial video from 2018,
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When is julia getting proper precompilation?
It's not faith, and it's not all from Julia itself. https://github.com/SciML/DifferentialEquations.jl/issues/785 should reduce compile times of what OP mentioned for example.
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Julia 1.7 has been released
Let's even put raw numbers to it. DifferentialEquations.jl usage has seen compile times drop from 22 seconds to 3 seconds over the last few months.
https://github.com/SciML/DifferentialEquations.jl/issues/786
- Suggest me a Good library for scientific computing in Julia with good support for multi-core CPUs and GPUs.
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DifferentialEquations compilation issue in Julia 1.6
https://github.com/SciML/DifferentialEquations.jl/issues/737 double posted, with the answer here. Please don't do that.
mujoco
- MuJoCo 3
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Mujoco Question
I have installed mujoco-2.3.5-window-x86_64.zip and Source Code (zip) in https://github.com/deepmind/mujoco/releases. From download file, I extracted file and clicked simulate (mujoco-2.3.5-window-x86_6 -> bin); however it shows black screen. I am not sure what I am doing wrong.
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Python Tutorials
Best place for technical MuJoCo questions is our GitHub repo (https://github.com/deepmind/mujoco) -- our entire team is notified for each issue posted there.
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Mujoco + Unity => setting transform
Could you please post this question on https://github.com/deepmind/mujoco also? You'd me more likely to get an answer there since most of our team don't track Reddit questions.
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Hi, i guys i have been working on bouncing ball experiment in Mujoco and i have had a fairly realistic effect of a ball bouncing, however i want it to be bouncing forward like tossing ball and it bounces forward? how can i achieve this? my XML is below
Could you please post this as an issue on https://github.com/deepmind/mujoco ?
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MuJoCo Soft Surface Problem
Try posting in https://github.com/deepmind/mujoco/discussions ?
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Deep RL with Mujoco environments using Docker on Apple Silicon
Not really. You can use conda or pip to install prebuilt mujoco packages that also include glfw. Check out https://github.com/deepmind/mujoco/blob/main/python/README.md
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DeepMind's open-source version of MuJoCo available on GitHub
MuJoCo Github link
- MuJoCo Physics
- DeepMind open-sources MuJoCo Physics
What are some alternatives?
ModelingToolkit.jl - An acausal modeling framework for automatically parallelized scientific machine learning (SciML) in Julia. A computer algebra system for integrated symbolics for physics-informed machine learning and automated transformations of differential equations
gazebo-classic - Gazebo classic. For the latest version, see https://github.com/gazebosim/gz-sim
diffeqpy - Solving differential equations in Python using DifferentialEquations.jl and the SciML Scientific Machine Learning organization
Bullet - Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc.
Gridap.jl - Grid-based approximation of partial differential equations in Julia
brax - Massively parallel rigidbody physics simulation on accelerator hardware.
ApproxFun.jl - Julia package for function approximation
CHRONO - High-performance C++ library for multiphysics and multibody dynamics simulations
DiffEqBase.jl - The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
sofa - Real-time multi-physics simulation with an emphasis on medical simulation.
FFTW.jl - Julia bindings to the FFTW library for fast Fourier transforms
LiquidFun - 2D physics engine for games