Latexify.jl
Symbolics.jl
| Latexify.jl | Symbolics.jl | |
|---|---|---|
| 2 | 13 | |
| 531 | 1,294 | |
| - | 1.5% | |
| 6.9 | 9.4 | |
| 22 days ago | 3 days ago | |
| Julia | Julia | |
| MIT License | GNU General Public License v3.0 or later |
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Latexify.jl
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Converting Symbolics.jl Objects to SymPy.jl Objects
My current solution to this is to use Latexify.jl, great module name btw, to convert the objects to latex, then perform some dodgy string manipulation on the latex, specifically turning it into a form readable by the Python module latex2sympy2 which has a function latex2sympy which can properly convert it. I've written a function to_sympy() which properly converts the Num and Matrix{NUM} types:
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Don't be scared.. Math and Computing are friends..
That's funny, I just implemented that conversion for Latexify.jl: https://github.com/korsbo/Latexify.jl/pull/205
Symbolics.jl
- Symbolics.jl
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What packages would you like Julia to have?
It’s not up to parity with SymPy/Matlab by far yet - here’s the tracking issue on it https://github.com/JuliaSymbolics/Symbolics.jl/issues/59
- Converting Symbolics.jl Objects to SymPy.jl Objects
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Error With StaticArrays Module & Symbolics.jl
Hello Juila Community. This is my second day working with Julia, having come over from Sympy due to performance reasons. I am working on a project that requires calculating matrix determinants and adjugates for families of matrices with symbolics entries. I am using Symbolics.jl for the symbols and using Juilia 1.8.2.
- ModelingToolkit over Modelica
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A Mature Library For Symbolic Computation?
After spending some time reading the documentation, it turns out that JuliaSymbolics also lacks factorizations functionality (according to [Link](https://github.com/JuliaSymbolics/Symbolics.jl/issues/59))
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Looking for numerical/iterative approach for determining a value
You can also get an expression for the partial of β with respect to h using Symbolics.jl:
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In 2022, the difference between symbolic computing and compiler optimizations will be erased in #julialang. Anyone who can come up with a set of symbolic mathematical rules will automatically receive an optimized compiler pass to build better code
The example is applied to the right-hand side of a generated mass-matrix ODE (DAE) which is then solved using the adaptive time stepping methods of DifferentialEquations.jl. It's a test example that comes from the robotics / rigid body dynamics simulation groups (specifically interested in control) where they before were generating the governing equations with SymPy, and recently switched to try Symbolics.jl (and we got the example because of some performance issues that needed fixing). The comparison is with and without applying the code simplifier before solving. The table shows an average global induced error of 1e-12 when chopping off the 1e-11 * sin(x) terms and smaller. Thus there's nothing "competitive" against standard adaptive time stepping here: it's used to enhance the simulation of generated models that are simulated with the adaptive time steppers.
- From Julia to Rust
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Fractions in Julia Symbolics
Done. https://github.com/JuliaSymbolics/Symbolics.jl/issues/215
What are some alternatives?
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)
julia - The Julia Programming Language
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
Octavian.jl - Multi-threaded BLAS-like library that provides pure Julia matrix multiplication
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.
LaTeXDatax.jl - Julia plugin for the datax LaTeX package
fricas - Official repository of the FriCAS computer algebra system
Dagger.jl - A framework for out-of-core and parallel execution
egg - egg is a flexible, high-performance e-graph library
StaticArrays.jl - Statically sized arrays for Julia
JET.jl - An experimental code analyzer for Julia. No need for additional type annotations.