ComponentArrays.jl
ScottishTaxBenefitModel.jl
ComponentArrays.jl | ScottishTaxBenefitModel.jl | |
---|---|---|
1 | 1 | |
277 | 8 | |
- | - | |
7.0 | 9.6 | |
3 days ago | 7 days ago | |
Julia | Julia | |
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
ComponentArrays.jl
-
Recursion absolutely necessary for distributed computing?
But for these to be as fast as say an Array when being used as the object in a differential equation solve or as the underlying construct of a nonlinear optimization, you would need the compiler to elide the struct construction which it doesn't always do. This is why the tools evolved to be around things like https://github.com/jonniedie/ComponentArrays.jl instead, where it's an Array-backed object with a higher level. Such immutable objects are used in these array-like contexts when the problems are small enough (FieldVectors or SLVector LabelledArrays.jl in DiffEq), and such applications work well in Haskell as well, but I haven't seen a compiler do well with say a 1,000 ODE model written in this style. And it's not quite an extreme case if it's what people are doing daily.
ScottishTaxBenefitModel.jl
-
An Online Simulation of a UBI
Source code;
What are some alternatives?
DiffEqBase.jl - The lightweight Base library for shared types and functionality for defining differential equation and scientific machine learning (SciML) problems
RegressionTables.jl - Journal-style regression tables
JuMP.jl - Modeling language for Mathematical Optimization (linear, mixed-integer, conic, semidefinite, nonlinear)
openfisca-france - French tax and benefit system for OpenFisca
RayTracer.jl - Differentiable RayTracing in Julia
Causal.jl - Causal.jl - A modeling and simulation framework adopting causal modeling approach.
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
policyengine-us - The PolicyEngine US Python package contains a rules engine of the US tax-benefit system, and microdata generation for microsimulation analysis.
ControlSystems.jl - A Control Systems Toolbox for Julia
DSGE.jl - Solve and estimate Dynamic Stochastic General Equilibrium models (including the New York Fed DSGE)
roadtofreeme - See when lockdown restrictions are easing in the UK. Built with Next.JS & Sanity.io.