NonlinearSystem

struct NonlinearSystem <: AbstractTimeIndependentSystem

A nonlinear system of equations.

Fields

• tag: A tag for the system. If two systems have the same tag, then they are structurally identical.

• eqs: Vector of equations defining the system.

• states: Unknown variables.

• ps: Parameters.

• var_to_name: Array variables.

• observed: Observed states.

• jac: Jacobian matrix. Note: this field will not be defined until calculate_jacobian is called on the system.

• name: The name of the system.

• systems: The internal systems. These are required to have unique names.

• defaults: The default values to use when initial conditions and/or parameters are not supplied in ODEProblem.

• connector_type: Type of the system.

• metadata: Metadata for the system, to be used by downstream packages.

• gui_metadata: Metadata for MTK GUI.

• tearing_state: Cache for intermediate tearing state.

• substitutions: Substitutions generated by tearing.

• complete: If a model sys is complete, then sys.x no longer performs namespacing.

• parent: The hierarchical parent system before simplification.

Examples

@variables x y z
@parameters σ ρ β

eqs = [0 ~ σ*(y-x),
       0 ~ x*(ρ-z)-y,
       0 ~ x*y - β*z]
@named ns = NonlinearSystem(eqs, [x,y,z],[σ,ρ,β])

structural_simplify(sys; ...)
structural_simplify(sys, io; simplify, kwargs...)

Structurally simplify algebraic equations in a system and compute the topological sort of the observed equations. When simplify=true, the simplify function will be applied during the tearing process. It also takes kwargs allow_symbolic=false and allow_parameter=true which limits the coefficient types during tearing.

The optional argument io may take a tuple (inputs, outputs). This will convert all inputs to parameters and allow them to be unconnected, i.e., simplification will allow models where n_states = n_equations - n_inputs.

tearing(sys; simplify=false)

Tear the nonlinear equations in system. When simplify=true, we simplify the new residual equations after tearing. End users are encouraged to call structural_simplify instead, which calls this function internally.

calculate_jacobian(sys::AbstractSystem)

Calculate the Jacobian matrix of a system.

Returns a matrix of Num instances. The result from the first call will be cached in the system object.

generate_jacobian(sys::AbstractSystem, dvs = states(sys), ps = parameters(sys),
                  expression = Val{true}; sparse = false, kwargs...)

Generates a function for the Jacobian matrix of a system. Extra arguments control the arguments to the internal build_function call.

SciMLBase.NonlinearFunction{iip}(sys::NonlinearSystem, dvs = states(sys),
                                 ps = parameters(sys);
                                 version = nothing,
                                 jac = false,
                                 sparse = false,
                                 kwargs...) where {iip}

Create an NonlinearFunction from the NonlinearSystem. The arguments dvs and ps are used to set the order of the dependent variable and parameter vectors, respectively.

DiffEqBase.NonlinearProblem{iip}(sys::NonlinearSystem, u0map,
                                 parammap = DiffEqBase.NullParameters();
                                 jac = false, sparse = false,
                                 checkbounds = false,
                                 linenumbers = true, parallel = SerialForm(),
                                 kwargs...) where {iip}

Generates an NonlinearProblem from a NonlinearSystem and allows for automatically symbolically calculating numerical enhancements.

SciMLBase.NonlinearFunctionExpr{iip}(sys::NonlinearSystem, dvs = states(sys),
                                     ps = parameters(sys);
                                     version = nothing,
                                     jac = false,
                                     sparse = false,
                                     kwargs...) where {iip}

Create a Julia expression for an ODEFunction from the ODESystem. The arguments dvs and ps are used to set the order of the dependent variable and parameter vectors, respectively.

DiffEqBase.NonlinearProblemExpr{iip}(sys::NonlinearSystem, u0map,
                                     parammap = DiffEqBase.NullParameters();
                                     jac = false, sparse = false,
                                     checkbounds = false,
                                     linenumbers = true, parallel = SerialForm(),
                                     kwargs...) where {iip}

Generates a Julia expression for a NonlinearProblem from a NonlinearSystem and allows for automatically symbolically calculating numerical enhancements.