ModelingToolkit.jl has a system of contextual variable types which allows for helping the system transformation machinery do complex manipulations and automatic detection. The standard variable definition in ModelingToolkit.jl is the
@variable which is defined by Symbolics.jl. For example:
@variables x y(x)
This is used for the "normal" variable of a given system, like the states of a differential equation or objective function. All of the macros below support the same syntax as
All modeling projects have some form of parameters.
@parameters marks a variable as being the parameter of some system, which allows automatic detection algorithms to ignore such variables when attempting to find the states of a system.
In many engineering systems some variables act like "flows" while others do not. For example, in circuit models you have current which flows, and the related voltage which does not. Or in thermal models you have heat flows. In these cases, the
connect statement enforces conservation of flow between all of the connected components.
For example, the following specifies that
x is a 2x2 matrix of flow variables with the unit m^3/s:
@variables x[1:2,1:2] [connect = Flow; unit = u"m^3/s"]
description keys for the metadata. One can get and set metadata by
julia> @variables x [unit = u"m^3/s"]; julia> hasmetadata(x, Symbolics.option_to_metadata_type(Val(:unit))) true julia> getmetadata(x, Symbolics.option_to_metadata_type(Val(:unit))) m³ s⁻¹ julia> x = setmetadata(x, Symbolics.option_to_metadata_type(Val(:unit)), u"m/s") x julia> getmetadata(x, Symbolics.option_to_metadata_type(Val(:unit))) m s⁻¹