https://github.com/sciml/symbolicanalysis.jl

Symbolics-based function property propagation for optimization
https://github.com/sciml/symbolicanalysis.jl

Last synced: 7 months ago
JSON representation

Symbolics-based function property propagation for optimization

• Host: GitHub
• URL: https://github.com/sciml/symbolicanalysis.jl
• Owner: SciML
• License: mit
• Created: 2023-08-10T02:56:17.000Z (almost 3 years ago)
• Default Branch: main
• Last Pushed: 2025-08-25T03:28:56.000Z (12 months ago)
• Last Synced: 2025-08-29T10:23:27.581Z (11 months ago)
• Language: Julia
• Homepage:
• Size: 1.89 MB
• Stars: 20
• Watchers: 4
• Forks: 1
• Open Issues: 7
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# SymbolicAnalysis.jl



Symbolics.jl based function property propagation for optimization

SymbolicAnalysis is a package for implementing the Disciplined Programming approach to optimization,

As demonstrated by the [DCP framework](https://dcp.stanford.edu/), and further followups to it for further classes of

functions https://www.cvxpy.org/tutorial/index.html such as DGP, DQP etc, symbolic representation of problems can be leveraged

to identify and facilitate building Convex (or similar function properties) expressions.

This package aims to utilize expression graph rewriting and metadata propagation supported by Symbolics.jl, to support

propagation of several of these properties - limited right now to Euclidean Convexity and Geodesic Convexity on the Symmetric

Positive Definite manifold. This package provides an easier to expand implementation of functional properties than the previous

implementations [CVXPY](https://www.cvxpy.org/index.html) and [Convex.jl](https://github.com/jump-dev/Convex.jl) as well as a

more performant implementation of the function property propagation.