Easy, standardised parameter get/set for heterogeneous or nested immutable models.
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Updated Last
1 Year Ago
Started In
October 2020


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ModelParameters simplifies the process of writing and using complex, high performance models, decoupling technical decisions about model structure and composition from usability concerns.

It provides linear indexing of parameters, a Tables.jl interface, and controllable Interact.jl Interfaces (via InteractModels.jl) -- for any object, of any complexity. Parameters of immutable objects can be updated from a vector, tuple or table using a single command, rebuilding the object with the new values.

Use case

ModelParameters.jl is designed to help writing physics/environmental/ecological models with heterogeneous structure and multiple formulation options.

Once these models grow beyond a certain complexity it becomes preferable to organise them in modular way, and to reuse components in variants in other models. This pattern is seen in climate models and land models related to CLIMA project, and in ecological modelling tools like DynamicGrids.jl and GrowthMaps.jl that this package was built for.

Models may be structured as a composed nested hierarchy of structs, Tuple chains of objects, NameTuples, or some combination of the above. For performance, or running on GPUs, immutability is often necessary.

The problem comes when trying to use these models in Optim.jl, or run sensitivity analysis on them with DiffEqSensitivity.jl, or pass priors to a Bayesian modelling package. These packages often need parameter values, bounds and priors as Vectors. They may also need to update the model with new parameters as required. Writing out these conversions for every model combination is error prone and inefficient - especially with nested immutable models, that need to be rebuilt to change the parameters.

ModelParameters.jl can convert any arbitrarily complex model built with structs, Tuples and NamedTuples into vectors of values, bounds, priors, and anything else you need to attach, and easily reconstruct the whole model when they are updated. This is facilitated by wrapping your parameters, wherever they are in the model, in a Param:

using ModelParameters

Base.@kwdef struct Submodel1{A,B}
    α::A = Param(0.8, bounds=(0.2, 0.9))
    β::B = Param(0.5, bounds=(0.7, 0.4))

Base.@kwdef struct Submodel2{Γ}
    γ::Γ = Param(1e-3, bounds=(1e-4, 1e-2))

Base.@kwdef struct SubModel3{Λ,X}
    λ::Λ = Param(0.8, bounds=(0.2, 0.9))
    x::X = Submodel2()

julia> model = Model((Submodel1(), SubModel3()))
Model with parent object of type: 

Tuple{Submodel1{Param{Float64,NamedTuple{(:val, :bounds),Tuple{Float64,Tuple{Float64,Float64}}}},Param{Float64,NamedTuple{(:val, :bounds),Tuple{Float64,Tuple{Float64,Float64}}}}},SubModel3{Param{Float64,NamedTuple{(:val, :bounds),Tuple{Float64,Tuple{Float64,Float64}}}},Submodel2{Param{Float64,NamedTuple{(:val, :bounds)

And parameters:
│ component │ field │   val │         bounds │
│ Submodel1 │     α │   0.8 │     (0.2, 0.9) │
│ Submodel1 │     β │   0.5 │     (0.7, 0.4) │
│ SubModel3 │     λ │   0.8 │     (0.2, 0.9) │
│ Submodel2 │     γ │ 0.001 │ (0.0001, 0.01) │

julia> model[:val]
(0.8, 0.5, 0.8, 0.001)

To get the model values as a vector for Optim.jl, simply:


What are Params?

Param is a wrapper for your parameter value and any metadata you need to track about it. Param has flexible fields, but expects to always have a :val field -- which is the default if you don't used a keyword argument:

par = Param(99.0)
@assert par.val == 99.0

Internally Param uses a NamedTuple to be flexible for scripting. You can just add any fields you need. When parameters are built into a Model, they are standardised so that they all have the same fields, filling the gaps with nothing.

There are a few other "privileged" fields that have specific behaviour, if you use them. A units field will be combined other fields using withunits, and this is done by default for val when you run stripparams on the models - if there is actually a units field. The InteractModel in the sub-package InteractModels.jl may also combine range or bounds fields with units and use them to construct sliders.

Param is also a Number, and should work as-is in a lot of models for convenience. But it can easily be stripped from objects using stripparams.

What is a Model?

A model is another wrapper type, this time for a whole model - whatever it may be. Its a mutable and untyped containers for you typed, immutable models, so they can be updated in a user interface or by using setproperties!. Letting you keep a handle to the updated version. Model gives you a Tables.jl interface, provides a table of parameters in the REPL, and give you some powerful tools for making changes to your model.

There is a more limited StaticModel variant where you need maximum performance and don't need a handle to the model object.

An InteractModel from the InteractModels.jl subpackage is identical to Model, with the addition of an Interact.jl interface. It accepts a function that generates anything that can go into a web page (like a plot) in response to model parameter changes you make with the generated sliders.

Setting model values

Setting new values

You can also add new columns to all model parameters directly from the model:

model[:bounds] = ((1.0, 4.0), (0.0, 1.0), (0.0, 0.1), (0.0, 100.0))

Swapping number types

ModelParameters makes it very easy to make modifications to your model parameters. To update all model values to be Float32, you can simply do:

model[:val] = map(Float32, model[:val])

Tables.jl interface

You can also save and import your model parameters to/from CSV or any other kind of Table or DataFrame using the Tables.jl interface:

update!(model, table)

Live Interact.jl models

InteractModels.jl is a subpackage of ModelParameters.jl, but needs to be installed separately. This avoids loading the heavy web-stack dependencies of Interact.jl when you don't need them.

Using InteractModels, any model can have an Interact.jl web interface defined for it automatically, by providing a function that plots or displays your model in some way that can show in a web page. The interface, slider controllers and model updates are all taken care of.

Potential Problems

If you define structs with type parameters that are not connected to fields, ModelParameters.jl will not be able to reconstruct them with new Param values, or use stripparams to remove the Param wrappers.

Defining ConstructionBase.constructorof from ConstructionBase.jl is the solution to this, and will also mean your objects can be used with other packages for immutable manipulation like Flatten.jl, Setfield.jl, Accessors.jl and BangBang.jl.

ConstructionBaseExtras.jl also exists to add support to common packages, such as StaticArrays.jl arrays. Import it if you need StaticArrays support, or open an issue to add support to additional packages.

Note: Breaking change in 0.4.0 With the introduction of weak extensions in Julia 1.9, ConstructionBase.jl and ConstructionBaseExtras.jl should not be loaded at the same time (see this issue). ModelParameters.jl has dropped the direct dependency on ConstructionBase.jl in version 0.4.0. Users that employ Julia versions <1.9 are advised to load ConstructionBaseExtras.jl themselves if StaticArrays.jl support is needed.

Required Packages

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