FEniCS
A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
Science Score: 54.0%
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Repository
A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
Basic Info
- Host: GitHub
- Owner: SciML
- License: other
- Language: Julia
- Default Branch: master
- Homepage: https://docs.sciml.ai/FEniCS/stable/
- Size: 877 KB
Statistics
- Stars: 106
- Watchers: 11
- Forks: 25
- Open Issues: 10
- Releases: 10
Topics
Metadata Files
README.md
FEniCS.jl: Finite Element PDE Solving in Julia
FEniCS.jl is a wrapper for the FEniCS library for finite element discretizations of PDEs. This wrapper includes three parts:
- Installation and direct access to FEniCS via a Conda installation. Alternatively, one may use their current FEniCS installation.
- A low-level development API and provides some functionality to make directly dealing with the library a little bit easier, but still requires knowledge of FEniCS itself. Interfaces have been provided for the main functions and their attributes, and instructions to add further ones can be found here.
- A high-level API for usage with DifferentialEquations. An example can be seen solving the heat equation with high order adaptive timestepping.
Various gists/jupyter notebooks have been created to provide a brief overview of the overall functionality, and of any differences between the Pythonic FEniCS and the Julian wrapper. DifferentialEquations.jl ecosystem. Paraview can also be used to visualize various results, just like in FEniCS (see below).
Installation Instructions
To get the wrapper on your system, providing a FEniCS installation exists, follow the below steps:
Add PyCall with the correct Python environment corresponding to FEniCS. Then simply add FEniCS.jl using Pkg.add("FEniCS")
Alternatively, one can install Docker and then run the following command
sh
docker run -ti cmhyett/julia-fenics
and once inside, Julia can be accessed by calling
sh
julia
Once inside the Julia environment, simply add FEniCS with Pkg.add("FEniCS"). All other dependencies are handled by the docker image.
This wrapper was originally started via the Google Summer of Code program along with the help of Chris Rackauckas and Bart Janssens. This was continued via GSoC '18 along with the help of Chris Rackauckas and Timo Betcke.
Tutorial
Below is a small demonstration of how a user would use our code to solve the Poisson equation with Dirichlet conditions. This directly mirrors one of the tutorials FEniCS provides
julia
using FEniCS
mesh = UnitSquareMesh(8,8)
V = FunctionSpace(mesh,"P",1)
u_D = Expression("1+x[0]*x[0]+2*x[1]*x[1]", degree=2)
u = TrialFunction(V)
bc1 = DirichletBC(V,u_D, "on_boundary")
v = TestFunction(V)
f = Constant(-6.0)
a = dot(grad(u),grad(v))*dx
L = f*v*dx
U = FeFunction(V)
lvsolve(a,L,U,bc1) #linear variational solver
errornorm(u_D, U, norm="L2")
get_array(L) #this returns an array for the stiffness matrix
get_array(U) #this returns an array for the solution values
vtkfile = File("poisson/solution.pvd")
vtkfile << U.pyobject #exports the solution to a vtkfile
We can also plot the solution (this relies on FEniCS backend for plotting) or import it from our file into Paraview:
```julia import PyPlot # plotting won't work if PyPlot is not imported FEniCS.Plot(U) FEniCS.Plot(mesh)
```
See the examples directory for more examples.
Owner
- Name: SciML Open Source Scientific Machine Learning
- Login: SciML
- Kind: organization
- Email: contact@chrisrackauckas.com
- Website: https://sciml.ai
- Twitter: SciML_Org
- Repositories: 170
- Profile: https://github.com/SciML
Open source software for scientific machine learning
Citation (CITATION.bib)
@article{DifferentialEquations.jl-2017,
author = {Rackauckas, Christopher and Nie, Qing},
doi = {10.5334/jors.151},
journal = {The Journal of Open Research Software},
keywords = {Applied Mathematics},
note = {Exported from https://app.dimensions.ai on 2019/05/05},
number = {1},
pages = {},
title = {DifferentialEquations.jl – A Performant and Feature-Rich Ecosystem for Solving Differential Equations in Julia},
url = {https://app.dimensions.ai/details/publication/pub.1085583166 and http://openresearchsoftware.metajnl.com/articles/10.5334/jors.151/galley/245/download/},
volume = {5},
year = {2017}
}
GitHub Events
Total
- Watch event: 8
- Delete event: 3
- Push event: 9
- Pull request review event: 1
- Pull request review comment event: 1
- Pull request event: 6
- Fork event: 1
- Create event: 4
Last Year
- Watch event: 8
- Delete event: 3
- Push event: 9
- Pull request review event: 1
- Pull request review comment event: 1
- Pull request event: 6
- Fork event: 1
- Create event: 4
Committers
Last synced: 8 months ago
Top Committers
| Name | Commits | |
|---|---|---|
| Yiannis Simillides | y****4@u****k | 106 |
| Christopher Rackauckas | a****s@c****m | 45 |
| Carlos Fernando Baptista | c****a@g****m | 14 |
| Steve Kelly | k****a@g****m | 11 |
| Jan Weidner | j****6@g****m | 9 |
| Arno Strouwen | a****n@t****e | 8 |
| dependabot[bot] | 4****] | 6 |
| github-actions[bot] | 4****] | 6 |
| chyett home | c****t@g****m | 5 |
| CompatHelper Julia | c****y@j****g | 2 |
| Bart Janssens | b****t@b****g | 2 |
| femtocleaner[bot] | f****] | 2 |
| tungli | 4****0@m****z | 2 |
| Alexander Prokhorchuk | 5****s | 1 |
| Anant Thazhemadam | a****m@g****m | 1 |
| Anshul Singhvi | a****7@s****u | 1 |
| Chris de Graaf | me@c****v | 1 |
| David Widmann | d****n | 1 |
| Hendrik Ranocha | m****l@r****e | 1 |
| Julia TagBot | 5****t | 1 |
| ScottPJones | s****s@a****u | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: 6 months ago
All Time
- Total issues: 28
- Total pull requests: 80
- Average time to close issues: 12 months
- Average time to close pull requests: about 2 months
- Total issue authors: 18
- Total pull request authors: 18
- Average comments per issue: 3.86
- Average comments per pull request: 1.49
- Merged pull requests: 68
- Bot issues: 0
- Bot pull requests: 20
Past Year
- Issues: 1
- Pull requests: 1
- Average time to close issues: about 2 months
- Average time to close pull requests: 2 minutes
- Issue authors: 1
- Pull request authors: 1
- Average comments per issue: 1.0
- Average comments per pull request: 0.0
- Merged pull requests: 1
- Bot issues: 0
- Bot pull requests: 1
Top Authors
Issue Authors
- ChrisRackauckas (9)
- clason (3)
- sverek (1)
- JuliaTagBot (1)
- 00krishna (1)
- francispoulin (1)
- ysimillides (1)
- barche (1)
- rodrigolece (1)
- JonasIsensee (1)
- brendanjmeade (1)
- cmey (1)
- CFBaptista (1)
- aterenin (1)
- stevengj (1)
Pull Request Authors
- ysimillides (23)
- github-actions[bot] (12)
- dependabot[bot] (10)
- CFBaptista (9)
- ArnoStrouwen (7)
- jw3126 (6)
- ChrisRackauckas (4)
- sjkelly (3)
- femtocleaner[bot] (2)
- christopher-dG (2)
- JuliaTagBot (1)
- barche (1)
- cmhyett (1)
- ranocha (1)
- tungli (1)
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Packages
- Total packages: 1
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Total downloads:
- julia 3 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 7
juliahub.com: FEniCS
A scientific machine learning (SciML) wrapper for the FEniCS Finite Element library in the Julia programming language
- Homepage: https://docs.sciml.ai/FEniCS/stable/
- Documentation: https://docs.juliahub.com/General/FEniCS/stable/
- License: MIT
-
Latest release: 0.4.2
published over 1 year ago
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