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Add docstring references to solver documentation for problem constructors
This adds comprehensive docstrings to all major problem constructors in ModelingToolkit.jl that reference the appropriate solver documentation for extended keyword arguments: - ODEProblem, SDEProblem, DAEProblem, BVProblem, DDEProblem, JumpProblem → DifferentialEquations.jl docs - NonlinearProblem → NonlinearSolve.jl docs - OptimizationProblem → Optimization.jl docs - LinearProblem → LinearSolve.jl docs Each docstring now clearly indicates that additional keyword arguments are supported beyond those listed, with links to the relevant solver documentation for complete details on available options. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <[email protected]>
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‎src/problems/bvproblem.jl

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"""
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BVProblem(sys::System, op, tspan; kwargs...)
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Construct a `BVProblem` from a ModelingToolkit `System` for boundary value problems.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the DifferentialEquations.jl `solve` function. For a complete list
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and detailed descriptions, see the [DifferentialEquations.jl solve documentation](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (with boundary conditions)
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- `op`: Operating point/initial conditions
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- `tspan`: Time span for the problem
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## Keywords
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- `check_compatibility=true`: Whether to check system compatibility
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- `cse=true`: Whether to perform common subexpression elimination
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- `checkbounds=false`: Whether to enable bounds checking
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- `eval_expression=false`: Whether to evaluate expressions
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- `eval_module=@__MODULE__`: Module for expression evaluation
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- `expression=Val{false}`: Expression evaluation mode
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- `guesses=Dict()`: Initial guesses for boundary value problem
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- `callback=nothing`: Callback functions (note: BVP solvers do not support callbacks)
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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@fallback_iip_specialize function SciMLBase.BVProblem{iip, spec}(
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sys::System, op, tspan;
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check_compatibility = true, cse = true,

‎src/problems/daeproblem.jl

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return maybe_codegen_scimlfn(expression, DAEFunction{iip, spec}, args; kwargs...)
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end
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"""
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DAEProblem(sys::System, op, tspan; kwargs...)
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Construct a `DAEProblem` from a ModelingToolkit `System` for differential-algebraic equations.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the DifferentialEquations.jl `solve` function. For a complete list
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and detailed descriptions, see the [DifferentialEquations.jl solve documentation](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (differential-algebraic system)
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- `op`: Operating point/initial conditions
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- `tspan`: Time span for the problem
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## Keywords
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- `callback=nothing`: Callback functions for the solver
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- `check_length=true`: Whether to check length compatibility
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- `eval_expression=false`: Whether to evaluate expressions
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- `eval_module=@__MODULE__`: Module for expression evaluation
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- `check_compatibility=true`: Whether to check system compatibility
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- `expression=Val{false}`: Expression evaluation mode
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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@fallback_iip_specialize function SciMLBase.DAEProblem{iip, spec}(
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sys::System, op, tspan;
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callback = nothing, check_length = true, eval_expression = false,

‎src/problems/ddeproblem.jl

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return maybe_codegen_scimlfn(expression, DDEFunction{iip, spec}, args; kwargs...)
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end
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"""
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DDEProblem(sys::System, op, tspan; kwargs...)
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Construct a `DDEProblem` from a ModelingToolkit `System` for delay differential equations.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the DifferentialEquations.jl `solve` function. For a complete list
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and detailed descriptions, see the [DifferentialEquations.jl solve documentation](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (must contain delay equations)
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- `op`: Operating point/initial conditions
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- `tspan`: Time span for the problem
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## Keywords
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- `callback=nothing`: Callback functions for the solver
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- `check_length=true`: Whether to check length compatibility
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- `cse=true`: Whether to perform common subexpression elimination
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- `checkbounds=false`: Whether to enable bounds checking
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- `eval_expression=false`: Whether to evaluate expressions
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- `eval_module=@__MODULE__`: Module for expression evaluation
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- `check_compatibility=true`: Whether to check system compatibility
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- `u0_constructor=identity`: Constructor for initial conditions
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- `expression=Val{false}`: Expression evaluation mode
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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@fallback_iip_specialize function SciMLBase.DDEProblem{iip, spec}(
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sys::System, op, tspan;
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callback = nothing, check_length = true, cse = true, checkbounds = false,

‎src/problems/jumpproblem.jl

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"""
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JumpProblem(sys::System, op, tspan; kwargs...)
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Construct a `JumpProblem` from a ModelingToolkit `System` for jump processes.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the DifferentialEquations.jl `solve` function. For a complete list
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and detailed descriptions, see the [DifferentialEquations.jl solve documentation](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (must contain jump processes)
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- `op`: Operating point/initial conditions
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- `tspan`: Time span for the problem (can be a tuple or nothing)
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## Keywords
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- `check_compatibility=true`: Whether to check system compatibility
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- `eval_expression=false`: Whether to evaluate expressions
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- `eval_module=@__MODULE__`: Module for expression evaluation
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- `checkbounds=false`: Whether to enable bounds checking
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- `cse=true`: Whether to perform common subexpression elimination
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- `aggregator=JumpProcesses.NullAggregator()`: Aggregator for jump processes
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- `callback=nothing`: Callback functions for the solver
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- `rng=nothing`: Random number generator
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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@fallback_iip_specialize function JumpProcesses.JumpProblem{iip, spec}(
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sys::System, op, tspan::Union{Tuple, Nothing};
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check_compatibility = true, eval_expression = false, eval_module = @__MODULE__,

‎src/problems/linearproblem.jl

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SciMLBase.LinearProblem{false}(sys, op; kwargs...)
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end
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"""
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LinearProblem(sys::System, op; kwargs...)
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Construct a `LinearProblem` from a ModelingToolkit `System` for linear systems.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the LinearSolve.jl `solve` function. For a complete list
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and detailed descriptions, see the [LinearSolve.jl documentation](https://docs.sciml.ai/LinearSolve/stable/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (linear system)
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- `op`: Operating point/initial conditions
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## Keywords
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- `check_length=true`: Whether to check length compatibility
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- `expression=Val{false}`: Expression evaluation mode
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- `check_compatibility=true`: Whether to check system compatibility
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- `sparse=false`: Whether to use sparse arrays
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- `eval_expression=false`: Whether to evaluate expressions
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- `eval_module=@__MODULE__`: Module for expression evaluation
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- `checkbounds=false`: Whether to enable bounds checking
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- `cse=true`: Whether to perform common subexpression elimination
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- `u0_constructor=identity`: Constructor for initial conditions
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- `u0_eltype=nothing`: Element type for initial conditions
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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function SciMLBase.LinearProblem{iip}(
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sys::System, op; check_length = true, expression = Val{false},
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check_compatibility = true, sparse = false, eval_expression = false,

‎src/problems/nonlinearproblem.jl

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return maybe_codegen_scimlfn(expression, NonlinearFunction{iip, spec}, args; kwargs...)
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end
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"""
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NonlinearProblem(sys::System, op; kwargs...)
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Construct a `NonlinearProblem` from a ModelingToolkit `System` for nonlinear equations.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the NonlinearSolve.jl `solve` function. For a complete list
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and detailed descriptions, see the [NonlinearSolve.jl documentation](https://docs.sciml.ai/NonlinearSolve/stable/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (nonlinear system)
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- `op`: Operating point/initial guess
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## Keywords
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- `expression=Val{false}`: Expression evaluation mode
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- `check_length=true`: Whether to check length compatibility
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- `check_compatibility=true`: Whether to check system compatibility
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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@fallback_iip_specialize function SciMLBase.NonlinearProblem{iip, spec}(
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sys::System, op; expression = Val{false},
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check_length = true, check_compatibility = true, kwargs...) where {iip, spec}

‎src/problems/odeproblem.jl

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maybe_codegen_scimlfn(expression, ODEFunction{iip, spec}, args; kwargs...)
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end
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"""
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ODEProblem(sys::System, op, tspan; kwargs...)
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Construct an `ODEProblem` from a ModelingToolkit `System`.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the DifferentialEquations.jl `solve` function. For a complete list
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and detailed descriptions, see the [DifferentialEquations.jl solve documentation](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert
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- `op`: Operating point/initial conditions
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- `tspan`: Time span for the problem
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## Keywords
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- `callback=nothing`: Callback functions for the solver
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- `check_length=true`: Whether to check length compatibility
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- `eval_expression=false`: Whether to evaluate expressions
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- `expression=Val{false}`: Expression evaluation mode
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- `eval_module=@__MODULE__`: Module for expression evaluation
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- `check_compatibility=true`: Whether to check system compatibility
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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@fallback_iip_specialize function SciMLBase.ODEProblem{iip, spec}(
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sys::System, op, tspan;
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callback = nothing, check_length = true, eval_expression = false,

‎src/problems/optimizationproblem.jl

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return OptimizationProblem{true}(sys, args...; kwargs...)
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end
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"""
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OptimizationProblem(sys::System, op; kwargs...)
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Construct an `OptimizationProblem` from a ModelingToolkit `System` for optimization.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the Optimization.jl `solve` function. For a complete list
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and detailed descriptions, see the [Optimization.jl documentation](https://docs.sciml.ai/Optimization/stable/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (optimization system with cost and constraints)
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- `op`: Operating point/initial guess
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## Keywords
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- `lb=nothing`: Lower bounds for optimization variables
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- `ub=nothing`: Upper bounds for optimization variables
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- `check_compatibility=true`: Whether to check system compatibility
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- `expression=Val{false}`: Expression evaluation mode
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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function SciMLBase.OptimizationProblem{iip}(
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sys::System, op; lb = nothing,
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ub = nothing, check_compatibility = true, expression = Val{false},

‎src/problems/sdeproblem.jl

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return maybe_codegen_scimlfn(expression, SDEFunction{iip, spec}, args; kwargs...)
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end
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"""
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SDEProblem(sys::System, op, tspan; kwargs...)
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Construct an `SDEProblem` from a ModelingToolkit `System` with noise.
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## Additional Keyword Arguments
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Beyond the arguments listed below, this constructor accepts all keyword arguments
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supported by the DifferentialEquations.jl `solve` function. For a complete list
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and detailed descriptions, see the [DifferentialEquations.jl solve documentation](https://docs.sciml.ai/DiffEqDocs/stable/basics/common_solver_opts/).
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## Arguments
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- `sys::System`: The ModelingToolkit system to convert (must contain noise equations)
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- `op`: Operating point/initial conditions
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- `tspan`: Time span for the problem
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## Keywords
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- `callback=nothing`: Callback functions for the solver
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- `check_length=true`: Whether to check length compatibility
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- `eval_expression=false`: Whether to evaluate expressions
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- `eval_module=@__MODULE__`: Module for expression evaluation
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- `check_compatibility=true`: Whether to check system compatibility
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- `sparse=false`: Whether to use sparse arrays
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- `sparsenoise=sparse`: Whether to use sparse noise representation
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- `expression=Val{false}`: Expression evaluation mode
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- `kwargs...`: Additional keyword arguments passed to the solver
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"""
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@fallback_iip_specialize function SciMLBase.SDEProblem{iip, spec}(
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sys::System, op, tspan;
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callback = nothing, check_length = true, eval_expression = false,

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