diffeqpy
DiffEqBase.jl
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| diffeqpy | DiffEqBase.jl | |
|---|---|---|
| 4 | 1 | |
| 491 | 295 | |
| 3.3% | 3.1% | |
| 7.7 | 9.3 | |
| about 1 month ago | 10 days ago | |
| Python | Julia | |
| MIT License | GNU General Public License v3.0 or later |
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diffeqpy
- ‘Machine Scientists’ Distill the Laws of Physics from Raw Data
- Is it possible to create a Python package with Julia and publish it on PyPi?
-
Julia vs R/Python
10-100x speed increase was not an exaggeration for me. With julia I was able to run things quickly on my own machine which I had been running on a compute cluster. I agree that numba could be just as fast as julia. I also just saw that you can run that DE library from julia that I like so much from python using this package. https://github.com/SciML/diffeqpy
DiffEqBase.jl
What are some alternatives?
DifferentialEquations.jl - Multi-language suite for high-performance solvers of differential equations and scientific machine learning (SciML) components. Ordinary differential equations (ODEs), stochastic differential equations (SDEs), delay differential equations (DDEs), differential-algebraic equations (DAEs), and more in Julia.
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
DiffEqSensitivity.jl - A component of the DiffEq ecosystem for enabling sensitivity analysis for scientific machine learning (SciML). Optimize-then-discretize, discretize-then-optimize, and more for ODEs, SDEs, DDEs, DAEs, etc. [Moved to: https://github.com/SciML/SciMLSensitivity.jl]
ComponentArrays.jl - Arrays with arbitrarily nested named components.
csvzip - A standalone CLI tool to reduce CSVs size by converting categorical columns in a list of unique integers.
OrdinaryDiffEq.jl - High performance ordinary differential equation (ODE) and differential-algebraic equation (DAE) solvers, including neural ordinary differential equations (neural ODEs) and scientific machine learning (SciML)
PySR - High-Performance Symbolic Regression in Python and Julia
ModelingToolkitStandardLibrary.jl - A standard library of components to model the world and beyond
SciMLTutorials.jl - Tutorials for doing scientific machine learning (SciML) and high-performance differential equation solving with open source software.
python-bigsimr
FunctionalModels.jl - Equation-based modeling and simulations in Julia