Symbolics

Symbolic programming for the next generation of numerical software

https://github.com/juliasymbolics/symbolics.jl

Science Score: 77.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
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codemeta.json file
Found codemeta.json file
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.zenodo.json file
Found .zenodo.json file
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DOI references
Found 5 DOI reference(s) in README
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Academic publication links
Links to: arxiv.org, acm.org
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Committers with academic emails
12 of 102 committers (11.8%) from academic institutions
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (13.1%) to scientific vocabulary

Keywords

cas computer-algebra-system high-performance mathematics parallel-computing symbolic-computing

Keywords from Contributors

ode sciml differential-equations sde pde dde dae ordinary-differential-equations stochastic-differential-equations delay-differential-equations

Last synced: 6 months ago · JSON representation ·

Repository

Symbolic programming for the next generation of numerical software

Basic Info

Host: GitHub
Owner: JuliaSymbolics
License: other
Language: Julia
Default Branch: master
Homepage: https://docs.sciml.ai/Symbolics/stable/
Size: 37.5 MB

Statistics

Stars: 1,443
Watchers: 23
Forks: 172
Open Issues: 482
Releases: 224

Topics

cas computer-algebra-system high-performance mathematics parallel-computing symbolic-computing

Created about 5 years ago · Last pushed 6 months ago

Metadata Files

Readme Changelog License Citation

Symbolics.jl

Symbolics.jl is a fast and modern Computer Algebra System (CAS) for a fast and modern programming language (Julia). The goal is to have a high-performance and parallelized symbolic algebra system that is directly extendable in the same language as that of the users.

Installation

To install Symbolics.jl, use the Julia package manager:

julia julia> using Pkg julia> Pkg.add("Symbolics")

Documentation

For information on using the package, see the stable documentation. Use the in-development documentation for the version of the documentation which contains the unreleased features.

Relationship to Other Packages

SymbolicUtils.jl: This is a rule-rewriting system that is the core of Symbolics.jl. Symbolics.jl builds off of SymbolicUtils.jl to extend it to a whole symbolic algebra system, complete with support for differentiation, solving symbolic systems of equations, etc. If you're looking for the barebones to build a new CAS for specific algebras, SymbolicUtils.jl is that foundation. Otherwise, Symbolics.jl is for you.
ModelingToolkit.jl: This is a symbolic-numeric modeling system for the SciML ecosystem. It heavily uses Symbolics.jl for its representation of symbolic equations along with tools like differentiation, and adds the representation of common modeling systems like ODEs, SDEs, and more.

Example

```julia julia> using Symbolics

julia> @variables t x y julia> D = Differential(t)

julia> z = t + t^2 julia> D(z) # symbolic representation of derivative(t + t^2, t) Differential(t)(t + t^2)

julia> expand_derivatives(D(z)) 1 + 2t

julia> Symbolics.jacobian([x + x*y, x^2 + y],[x, y]) 2×2 Matrix{Num}: 1 + y x 2x 1

julia> B = simplify.([t^2 + t + t^2 2t + 4t x + y + y + 2t x^2 - x^2 + y^2]) 2×2 Matrix{Num}: t + 2(t^2) 6t x + 2t + 2y y^2

julia> simplify.(substitute.(B, (Dict(x => y^2),))) 2×2 Matrix{Num}: t + 2(t^2) 6t 2t + y^2 + 2y y^2

julia> substitute.(B, (Dict(x => 2.0, y => 3.0, t => 4.0),)) 2×2 Matrix{Num}: 36.0 24.0 16.0 9.0 ```

Citation

If you use Symbolics.jl, please cite this paper (or see the free arxiv version)

bib @article{10.1145/3511528.3511535, author = {Gowda, Shashi and Ma, Yingbo and Cheli, Alessandro and Gw\'{o}\'{z}zd\'{z}, Maja and Shah, Viral B. and Edelman, Alan and Rackauckas, Christopher}, title = {High-Performance Symbolic-Numerics via Multiple Dispatch}, year = {2022}, issue_date = {September 2021}, publisher = {Association for Computing Machinery}, address = {New York, NY, USA}, volume = {55}, number = {3}, issn = {1932-2240}, url = {https://doi.org/10.1145/3511528.3511535}, doi = {10.1145/3511528.3511535}, abstract = {As mathematical computing becomes more democratized in high-level languages, high-performance symbolic-numeric systems are necessary for domain scientists and engineers to get the best performance out of their machine without deep knowledge of code optimization. Naturally, users need different term types either to have different algebraic properties for them, or to use efficient data structures. To this end, we developed Symbolics.jl, an extendable symbolic system which uses dynamic multiple dispatch to change behavior depending on the domain needs. In this work we detail an underlying abstract term interface which allows for speed without sacrificing generality. We show that by formalizing a generic API on actions independent of implementation, we can retroactively add optimized data structures to our system without changing the pre-existing term rewriters. We showcase how this can be used to optimize term construction and give a 113x acceleration on general symbolic transformations. Further, we show that such a generic API allows for complementary term-rewriting implementations. Exploiting this feature, we demonstrate the ability to swap between classical term-rewriting simplifiers and e-graph-based term-rewriting simplifiers. We illustrate how this symbolic system improves numerical computing tasks by showcasing an e-graph ruleset which minimizes the number of CPU cycles during expression evaluation, and demonstrate how it simplifies a real-world reaction-network simulation to halve the runtime. Additionally, we show a reaction-diffusion partial differential equation solver which is able to be automatically converted into symbolic expressions via multiple dispatch tracing, which is subsequently accelerated and parallelized to give a 157x simulation speedup. Together, this presents Symbolics.jl as a next-generation symbolic-numeric computing environment geared towards modeling and simulation.}, journal = {ACM Commun. Comput. Algebra}, month = {jan}, pages = {92–96}, numpages = {5} }

Owner

Name: JuliaSymbolics
Login: JuliaSymbolics
Kind: organization

Website: JuliaSymbolics.org
Repositories: 8
Profile: https://github.com/JuliaSymbolics

A fast and modern CAS for a fast and modern language

Citation (CITATION.bib)

## Citation

If you use Symbolics.jl, please [cite this paper](https://arxiv.org/abs/2105.03949)

@article{10.1145/3511528.3511535,
author = {Gowda, Shashi and Ma, Yingbo and Cheli, Alessandro and Gw\'{o}\'{z}zd\'{z}, Maja and Shah, Viral B. and Edelman, Alan and Rackauckas, Christopher},
title = {High-Performance Symbolic-Numerics via Multiple Dispatch},
year = {2022},
issue_date = {September 2021},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {55},
number = {3},
issn = {1932-2240},
url = {https://doi.org/10.1145/3511528.3511535},
doi = {10.1145/3511528.3511535},
abstract = {As mathematical computing becomes more democratized in high-level languages, high-performance symbolic-numeric systems are necessary for domain scientists and engineers to get the best performance out of their machine without deep knowledge of code optimization. Naturally, users need different term types either to have different algebraic properties for them, or to use efficient data structures. To this end, we developed Symbolics.jl, an extendable symbolic system which uses dynamic multiple dispatch to change behavior depending on the domain needs. In this work we detail an underlying abstract term interface which allows for speed without sacrificing generality. We show that by formalizing a generic API on actions independent of implementation, we can retroactively add optimized data structures to our system without changing the pre-existing term rewriters. We showcase how this can be used to optimize term construction and give a 113x acceleration on general symbolic transformations. Further, we show that such a generic API allows for complementary term-rewriting implementations. Exploiting this feature, we demonstrate the ability to swap between classical term-rewriting simplifiers and e-graph-based term-rewriting simplifiers. We illustrate how this symbolic system improves numerical computing tasks by showcasing an e-graph ruleset which minimizes the number of CPU cycles during expression evaluation, and demonstrate how it simplifies a real-world reaction-network simulation to halve the runtime. Additionally, we show a reaction-diffusion partial differential equation solver which is able to be automatically converted into symbolic expressions via multiple dispatch tracing, which is subsequently accelerated and parallelized to give a 157x simulation speedup. Together, this presents Symbolics.jl as a next-generation symbolic-numeric computing environment geared towards modeling and simulation.},
journal = {ACM Commun. Comput. Algebra},
month = {jan},
pages = {92–96},
numpages = {5}
}

GitHub Events

Total

Create event: 137
Issues event: 149
Release event: 45
Watch event: 93
Delete event: 89
Issue comment event: 687
Push event: 475
Pull request review event: 120
Pull request review comment event: 76
Pull request event: 394
Fork event: 21

Last Year

Create event: 137
Issues event: 149
Release event: 45
Watch event: 93
Delete event: 89
Issue comment event: 687
Push event: 475
Pull request review event: 120
Pull request review comment event: 76
Pull request event: 394
Fork event: 21

Committers

Last synced: about 2 years ago

All Time

Total Commits: 1,204
Total Committers: 102
Avg Commits per committer: 11.804
Development Distribution Score (DDS): 0.667

Past Year

Commits: 173
Committers: 37
Avg Commits per committer: 4.676
Development Distribution Score (DDS): 0.763

Top Committers

Name	Email	Commits
Shashi Gowda	g**a@m**u	401
Yingbo Ma	m**5@g**m	239
Christopher Rackauckas	a**s@c**m	163
Bowen S. Zhu	b**u@f**u	58
Kamil Ziemian	k**t@g**m	21
xtalax	a**y@g**m	18
ArnoStrouwen	a**n@t**e	16
github-actions[bot]	4****]	13
Fredrik Bagge Carlson	c**b@u**g	13
CompatHelper Julia	c**y@j**g	12
Joe Carpinelli	j**p@u**u	12
Jimmy Envall	j**l@g**m	10
Luke Adams	l**e@l**m	10
Shashi Gowda	s**1@g**m	10
benjamin currie	s**a@g**m	10
Valentin Kaisermayer	v**r@b**u	9
Pepijn de Vos	p**s@g**m	8
sumiya11	a**2@m**u	8
dependabot[bot]	4****]	7
Philip Bittihn	p**p@b**e	6
Sam Isaacson	i****s	5
Chris Elrod	e**c@g**m	5
Fredrik Bagge Carlson	b**n@g**m	5
Mason Protter	m**r@i**m	5
anand jain	a**j@u**u	5
Aayush Sabharwal	a**l@j**m	4
David Gustavsson	d**n@g**m	4
Grigorii Starkov	g**i@t**e	4
Raphael Chinchilla	r**a@u**u	4
ashutosh-b-b	a**3@g**m	4
and 72 more...

Committer Domains (Top 20 + Academic)

gmx.de: 2 mit.edu: 2 chrisrackauckas.com: 1 fas.harvard.edu: 1 telenet.be: 1 ulund.org: 1 julialang.org: 1 umd.edu: 1 lukeclydeadams.com: 1 best-research.eu: 1 mail.ru: 1 bittihn.de: 1 uchicago.edu: 1 juliahub.com: 1 tp4.rub.de: 1 ucsb.edu: 1 fastmail.com: 1 polymtl.ca: 1 juliacomputing.com: 1 gmx.com: 1 edu.hse.ru: 1 mail.uni-paderborn.de: 1 mpi-inf.mpg.de: 1 uq.edu.au: 1 vt.edu: 1 dartmouth.edu: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time

Total issues: 343
Total pull requests: 761
Average time to close issues: 8 months
Average time to close pull requests: about 1 month
Total issue authors: 190
Total pull request authors: 78
Average comments per issue: 2.99
Average comments per pull request: 1.28
Merged pull requests: 571
Bot issues: 0
Bot pull requests: 137

Past Year

Issues: 109
Pull requests: 418
Average time to close issues: 10 days
Average time to close pull requests: 3 days
Issue authors: 65
Pull request authors: 30
Average comments per issue: 0.96
Average comments per pull request: 1.17
Merged pull requests: 324
Bot issues: 0
Bot pull requests: 72

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Top Authors

Issue Authors

baggepinnen (16)
AayushSabharwal (11)
TorkelE (9)
n0rbed (9)
ChrisRackauckas (8)
bowenszhu (7)
nsajko (6)
B-LIE (6)
thorek1 (5)
LilithHafner (5)
dpsanders (5)
isaacsas (5)
lassepe (5)
hersle (5)
Audrius-St (4)

Pull Request Authors

ChrisRackauckas (147)
AayushSabharwal (142)
github-actions[bot] (90)
dependabot[bot] (47)
YingboMa (27)
hersle (25)
n0rbed (24)
shashi (23)
baggepinnen (17)
devmotion (13)
bowenszhu (13)
sumiya11 (12)
ArnoStrouwen (11)
TorkelE (8)
karlwessel (7)

Top Labels

Issue Labels

array variables (12) good first issue (5) code-generation (2) register (1) julia-compiler (1) enhancement (1) error-reporting (1) array library (1)

Pull Request Labels

dependencies (47) github_actions (9)

Packages

Total packages: 3
Total downloads:
- julia 4,370 total

Total dependent packages: 101
(may contain duplicates)
Total dependent repositories: 0
(may contain duplicates)
Total versions: 675

juliahub.com: Symbolics

Symbolic programming for the next generation of numerical software

Homepage: https://docs.sciml.ai/Symbolics/stable/
Documentation: https://docs.juliahub.com/General/Symbolics/stable/
License: MIT
Latest release: 6.52.0
published 7 months ago

Versions: 225
Dependent Packages: 101
Dependent Repositories: 0
Downloads: 4,370 Total

Rankings

Stargazers count: 0.2%

Forks count: 0.7%

Dependent packages count: 0.9%

Average: 2.9%

Dependent repos count: 9.9%

Last synced: 6 months ago

proxy.golang.org: github.com/juliasymbolics/symbolics.jl

Documentation: https://pkg.go.dev/github.com/juliasymbolics/symbolics.jl#section-documentation
License: other
Latest release: v6.52.0+incompatible
published 6 months ago

Versions: 225
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.5%

Average: 5.7%

Dependent repos count: 5.9%

Last synced: 6 months ago

proxy.golang.org: github.com/JuliaSymbolics/Symbolics.jl

Documentation: https://pkg.go.dev/github.com/JuliaSymbolics/Symbolics.jl#section-documentation
License: other
Latest release: v6.52.0+incompatible
published 6 months ago

Versions: 225
Dependent Packages: 0
Dependent Repositories: 0

Rankings

Dependent packages count: 5.5%

Average: 5.7%

Dependent repos count: 5.9%

Last synced: 6 months ago

Dependencies

.github/workflows/Documentation.yml actions

actions/checkout v2 composite
julia-actions/setup-julia latest composite

.github/workflows/Downstream.yml actions

actions/checkout v2 composite
julia-actions/julia-buildpkg latest composite
julia-actions/setup-julia v1 composite

.github/workflows/TagBot.yml actions

JuliaRegistries/TagBot v1 composite

.github/workflows/ci.yml actions

actions/cache v1 composite
actions/checkout v2 composite
codecov/codecov-action v1 composite
julia-actions/julia-buildpkg v1 composite
julia-actions/julia-processcoverage v1 composite
julia-actions/julia-runtest v1 composite
julia-actions/setup-julia v1 composite

Symbolics

Science Score: 77.0%

Keywords

Keywords from Contributors

Repository

Basic Info

Statistics

Topics

Metadata Files

README.md

Symbolics.jl

Installation

Documentation

Relationship to Other Packages

Example

Citation

Owner

Citation (CITATION.bib)

GitHub Events

Total

Last Year

Committers

All Time

Past Year

Top Committers

Committer Domains (Top 20 + Academic)

Issues and Pull Requests

All Time

Past Year

Top Authors

Issue Authors

Pull Request Authors

Top Labels

Issue Labels

Pull Request Labels

Packages

juliahub.com: Symbolics

Rankings

proxy.golang.org: github.com/juliasymbolics/symbolics.jl

Rankings

proxy.golang.org: github.com/JuliaSymbolics/Symbolics.jl

Rankings

Dependencies