Merge branch 'master' into myb/unit

Author: ChrisRackauckas

.github/dependabot.yml

@@ -5,3 +5,6 @@ updates:
     directory: "/" # Location of package manifests
     schedule:
       interval: "weekly"
+    ignore:
+      - dependency-name: "crate-ci/typos"
+        update-types: ["version-update:semver-patch"]

.github/workflows/SpellCheck.yml

@@ -0,0 +1,13 @@
+name: Spell Check
+
+on: [pull_request]
+
+jobs:
+  typos-check:
+    name: Spell Check with Typos
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout Actions Repository
+        uses: actions/checkout@v4
+      - name: Check spelling
+        uses: crate-ci/typos@v1.16.25 

.github/workflows/ci.yml

@@ -21,9 +21,12 @@ jobs:
   test:
     runs-on: ubuntu-latest
     strategy:
+      fail-fast: false
       matrix:
         group:
-          - All
+          - InterfaceI
+          - InterfaceII
+          - Extensions
         version:
           - '1'
     steps:
@@ -43,6 +46,8 @@ jobs:
             ${{ runner.os }}-
       - uses: julia-actions/julia-buildpkg@v1
       - uses: julia-actions/julia-runtest@v1
+        env:
+          GROUP: ${{ matrix.group }}
       - uses: julia-actions/julia-processcoverage@v1
       - uses: codecov/codecov-action@v3
         with:

.typos.toml

@@ -0,0 +1,6 @@
+[default.extend-words]
+nin = "nin"
+nd = "nd"
+Strat = "Strat"
+eles = "eles"
+ser = "ser"

Project.toml

@@ -1,7 +1,7 @@
 name = "ModelingToolkit"
 uuid = "961ee093-0014-501f-94e3-6117800e7a78"
 authors = ["Yingbo Ma <mayingbo5@gmail.com>", "Chris Rackauckas <accounts@chrisrackauckas.com> and contributors"]
-version = "8.72.2"
+version = "8.75.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -69,6 +69,7 @@ DataStructures = "0.17, 0.18"
 DiffEqBase = "6.103.0"
 DiffEqCallbacks = "2.16"
 DiffRules = "0.1, 1.0"
+Distributed = "1"
 Distributions = "0.23, 0.24, 0.25"
 DocStringExtensions = "0.7, 0.8, 0.9"
 DomainSets = "0.6"
@@ -77,26 +78,31 @@ ForwardDiff = "0.10.3"
 FunctionWrappersWrappers = "0.1"
 Graphs = "1.5.2"
 IfElse = "0.1"
+InteractiveUtils = "1"
 JuliaFormatter = "1"
 JumpProcesses = "9.1"
 LabelledArrays = "1.3"
 Latexify = "0.11, 0.12, 0.13, 0.14, 0.15, 0.16"
+Libdl = "1"
+LinearAlgebra = "1"
 MLStyle = "0.4.17"
 MacroTools = "0.5"
 NaNMath = "0.3, 1"
 OrdinaryDiffEq = "6"
 PrecompileTools = "1"
-RecursiveArrayTools = "2.3"
+RecursiveArrayTools = "2.3, 3"
 Reexport = "0.2, 1"
 RuntimeGeneratedFunctions = "0.5.9"
 SciMLBase = "2.0.1"
+Serialization = "1"
 Setfield = "0.7, 0.8, 1"
-SimpleNonlinearSolve = "0.1.0"
+SimpleNonlinearSolve = "0.1.0, 1"
+SparseArrays = "1"
 SpecialFunctions = "0.7, 0.8, 0.9, 0.10, 1.0, 2"
 StaticArrays = "0.10, 0.11, 0.12, 1.0"
-SymbolicIndexingInterface = "0.1, 0.2"
+SymbolicIndexingInterface = "0.3.1"
 SymbolicUtils = "1.0"
-Symbolics = "5.0"
+Symbolics = "5.7"
 URIs = "1"
 UnPack = "0.1, 1.0"
 Unitful = "1.1"
@@ -105,7 +111,6 @@ julia = "1.9"
 [extras]
 AmplNLWriter = "7c4d4715-977e-5154-bfe0-e096adeac482"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
-BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
 ControlSystemsMTK = "687d7614-c7e5-45fc-bfc3-9ee385575c88"
 DeepDiffs = "ab62b9b5-e342-54a8-a765-a90f495de1a6"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
@@ -116,6 +121,7 @@ NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationMOI = "fd9f6733-72f4-499f-8506-86b2bdd0dea1"
 OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
+Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReferenceTests = "324d217c-45ce-50fc-942e-d289b448e8cf"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
@@ -128,4 +134,4 @@ Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["AmplNLWriter", "BenchmarkTools", "BifurcationKit", "ControlSystemsMTK", "NonlinearSolve", "ForwardDiff", "Ipopt", "Ipopt_jll", "ModelingToolkitStandardLibrary", "Optimization", "OptimizationOptimJL", "OptimizationMOI", "Random", "ReferenceTests", "SafeTestsets", "StableRNGs", "Statistics", "SteadyStateDiffEq", "Test", "StochasticDiffEq", "Sundials", "StochasticDelayDiffEq"]
+test = ["AmplNLWriter", "BenchmarkTools", "ControlSystemsMTK", "NonlinearSolve", "ForwardDiff", "Ipopt", "Ipopt_jll", "ModelingToolkitStandardLibrary", "Optimization", "OptimizationOptimJL", "OptimizationMOI", "Random", "ReferenceTests", "SafeTestsets", "StableRNGs", "Statistics", "SteadyStateDiffEq", "Test", "StochasticDiffEq", "Sundials", "StochasticDelayDiffEq", "Pkg"]

docs/Project.toml

@@ -27,14 +27,14 @@ Distributions = "0.25"
 Documenter = "1"
 ModelingToolkit = "8.33"
 ModelingToolkitDesigner = "1"
-NonlinearSolve = "0.3, 1, 2"
+NonlinearSolve = "0.3, 1, 2, 3"
 Optim = "1.7"
 Optimization = "3.9"
 OptimizationOptimJL = "0.1"
 OrdinaryDiffEq = "6.31"
 Plots = "1.36"
 StochasticDiffEq = "6"
-StructuralIdentifiability = "0.4"
+StructuralIdentifiability = "0.4, 0.5"
 SymbolicUtils = "1"
 Symbolics = "5"
 Unitful = "1.12"

docs/src/basics/AbstractSystem.md

@@ -121,7 +121,7 @@ patterns via an abstract interpretation without requiring differentiation.
 
 At the end, the system types have `DEProblem` constructors, like `ODEProblem`,
 which allow for directly generating the problem types required for numerical
-methods. The first argument is always the `AbstractSystem`, and the proceding
+methods. The first argument is always the `AbstractSystem`, and the next
 arguments match the argument order of their original constructors. Whenever an
 array would normally be provided, such as `u0` the initial condition of an
 `ODEProblem`, it is instead replaced with a variable map, i.e., an array of

docs/src/basics/Linearization.md

@@ -51,7 +51,7 @@ If linearization is to be performed around multiple operating points, the simpli
 
 ## Symbolic linearization
 
-The function [`ModelingToolkit.linearize_symbolic`](@ref) works simiar to [`ModelingToolkit.linearize`](@ref) but returns symbolic rather than numeric Jacobians. Symbolic linearization have several limitations and no all systems that can be linearized numerically can be linearized symbolically.
+The function [`ModelingToolkit.linearize_symbolic`](@ref) works similar to [`ModelingToolkit.linearize`](@ref) but returns symbolic rather than numeric Jacobians. Symbolic linearization have several limitations and no all systems that can be linearized numerically can be linearized symbolically.
 
 ## Input derivatives
 

docs/src/basics/MTKModel_Connector.md

@@ -29,7 +29,7 @@ equations.
   - `@icon` : for embedding the model icon
   - `@parameters`: for specifying the symbolic parameters
   - `@structural_parameters`: for specifying non-symbolic parameters
-  - `@variables`: for specifing the states
+  - `@variables`: for specifying the states
 
 Let's explore these in more detail with the following example:
 
@@ -104,7 +104,7 @@ end
 
 #### `@structural_parameters` begin block
 
-  - This block is for non symbolic input arguements. These are for inputs that usually are not meant to be part of components; but influence how they are defined. One can list inputs like boolean flags, functions etc... here.
+  - This block is for non symbolic input arguments. These are for inputs that usually are not meant to be part of components; but influence how they are defined. One can list inputs like boolean flags, functions etc... here.
   - Whenever default values are specified, unlike parameters/variables, they are reflected in the keyword argument list.
 
 #### `@parameters` and `@variables` begin block
@@ -251,3 +251,104 @@ Dict{Symbol, Any} with 7 entries:
   :extend               => Any[[:p2, :p1], Symbol("#mtkmodel__anonymous__ModelB"), :ModelB]
   :equations            => ["model_a.k ~ f(v)"]
 ```
+
+### Using conditional statements
+
+#### Conditional elements of the system
+
+Both `@mtkmodel` and `@connector` support conditionally defining parameters,
+variables, equations, and components.
+
+The if-elseif-else statements can be used inside `@equations`, `@parameters`,
+`@variables`, `@components`.
+
+```@example branches-in-components
+using ModelingToolkit
+
+@mtkmodel C begin end
+
+@mtkmodel BranchInsideTheBlock begin
+    @structural_parameters begin
+        flag = true
+    end
+    @parameters begin
+        if flag
+            a1
+        else
+            a2
+        end
+    end
+    @components begin
+        if flag
+            sys1 = C()
+        else
+            sys2 = C()
+        end
+    end
+end
+```
+
+Alternatively, the `@equations`, `@parameters`, `@variables`, `@components` can be
+used inside the if-elseif-else statements.
+
+```@example branches-in-components
+@mtkmodel BranchOutsideTheBlock begin
+    @structural_parameters begin
+        flag = true
+    end
+    if flag
+        @parameters begin
+            a1
+        end
+        @components begin
+            sys1 = C()
+        end
+        @equations begin
+            a1 ~ 0
+        end
+    else
+        @parameters begin
+            a2
+        end
+        @equations begin
+            a2 ~ 0
+        end
+    end
+end
+```
+
+The conditional parts are reflected in the `structure`. For `BranchOutsideTheBlock`, the metadata is:
+
+```julia
+julia> BranchOutsideTheBlock.structure
+Dict{Symbol, Any} with 5 entries:
+  :components           => Any[(:if, :flag, [[:sys1, :C]], Any[])]
+  :kwargs               => Dict{Symbol, Any}(:flag=>true)
+  :independent_variable => t
+  :parameters           => Dict{Symbol, Dict{Symbol, Any}}(:a1=>Dict(:condition=>(:if, :flag, Dict{Symbol, Any}(:kwargs => Dict{Any, Any}(:a1 => nothing), :parameters => Any[Dict{Symbol, Dict{Symbol, Any}}(:a1 => Dict())]), Dict{Symbol, Any}(:kwargs => Dict{Any, Any}(:a2 => nothing), :parameters => Any[Dict{Symbol, Dict{Symbol, Any}}(:a2 => Dict())]))
+  :equations            => Any[(:if, :flag, ["a1 ~ 0"], ["a2 ~ 0"])]
+```
+
+Conditional entries are entered in the format of `(branch, condition, [case when it is true], [case when it is false])`;
+where `branch` is either `:if` or `:elseif`.<br>
+The `[case when it is false]` is either an empty vector or `nothing` when only if branch is
+present; it is a vector or dictionary whenever else branch is present; it is a conditional tuple
+whenever elseif branches are present.
+
+For the conditional components and equations these condition tuples are added
+directly, while for parameters and variables these are added as `:condition` metadata.
+
+#### Conditional initial guess of symbolic variables
+
+Using ternary operator or if-elseif-else statement, conditional initial guesses can be assigned to parameters and variables.
+
+```@example branches-in-components
+@mtkmodel DefaultValues begin
+    @structural_parameters begin
+        flag = true
+    end
+    @parameters begin
+        p = flag ? 1 : 2
+    end
+end
+```

docs/src/basics/Variable_metadata.md

@@ -83,6 +83,19 @@ hasbounds(u)
 getbounds(u)
 ```
 
+## Guess
+
+Specify an initial guess for custom initial conditions of an `ODESystem`.
+
+```@example metadata
+@variables u [guess = 1]
+hasguess(u)
+```
+
+```@example metadata
+getguess(u)
+```
+
 ## Mark input as a disturbance
 
 Indicate that an input is not available for control, i.e., it's a disturbance input.

docs/src/tutorials/bifurcation_diagram_computation.md

@@ -1,6 +1,6 @@
 # [Bifurcation Diagrams](@id bifurcation_diagrams)
 
-Bifurcation diagrams describes how, for a dynamic system, the quantity and quality of its steady states changes with a parameter's value. These can be computed through the [BifurcationKit.jl](https://github.com/bifurcationkit/BifurcationKit.jl) package. ModelingToolkit provides a simple interface for creating BifurcationKit compatible `BifurcationProblem`s from `NonlinearSystem`s and `ODESystem`s. All teh features provided by BifurcationKit can then be applied to these systems. This tutorial provides a brief introduction for these features, with BifurcationKit.jl providing [a more extensive documentation](https://bifurcationkit.github.io/BifurcationKitDocs.jl/stable/).
+Bifurcation diagrams describes how, for a dynamic system, the quantity and quality of its steady states changes with a parameter's value. These can be computed through the [BifurcationKit.jl](https://github.com/bifurcationkit/BifurcationKit.jl) package. ModelingToolkit provides a simple interface for creating BifurcationKit compatible `BifurcationProblem`s from `NonlinearSystem`s and `ODESystem`s. All the features provided by BifurcationKit can then be applied to these systems. This tutorial provides a brief introduction for these features, with BifurcationKit.jl providing [a more extensive documentation](https://bifurcationkit.github.io/BifurcationKitDocs.jl/stable/).
 
 ### Creating a `BifurcationProblem`
 

docs/src/tutorials/domain_connections.md

@@ -205,7 +205,7 @@ nothing #hide
 
 ![actsys2](https://github.com/SciML/ModelingToolkit.jl/assets/40798837/8ed50035-f6ac-48cb-a585-1ef415154a02)
 
-After running `structural_simplify()` on `actsys2`, the defaults will show that `act.port_a.ρ` points to `fluid_a₊ρ` and `act.port_b.ρ` points to `fluid_b₊ρ`.  This is a special case, in most cases a hydraulic system will have only 1 fluid, however this simple system has 2 separate domain networks.  Therefore, we can connect a single fluid to both networks.  This does not interfer with the mathmatical equations of the system, since no states are connected.
+After running `structural_simplify()` on `actsys2`, the defaults will show that `act.port_a.ρ` points to `fluid_a₊ρ` and `act.port_b.ρ` points to `fluid_b₊ρ`.  This is a special case, in most cases a hydraulic system will have only 1 fluid, however this simple system has 2 separate domain networks.  Therefore, we can connect a single fluid to both networks.  This does not interfere with the mathematical equations of the system, since no states are connected.
 
 ```@example domain
 @component function ActuatorSystem1(; name)
@@ -239,7 +239,7 @@ nothing #hide
 
 ## Special Connection Cases (`domain_connect()`)
 
-In some cases a component will be defined with 2 connectors of the same domain, but they are not connected.  For example the `Restrictor` defined here gives equations to define the behavior of how the 2 connectors `port_a` and `port_b` are physcially connected.
+In some cases a component will be defined with 2 connectors of the same domain, but they are not connected.  For example the `Restrictor` defined here gives equations to define the behavior of how the 2 connectors `port_a` and `port_b` are physically connected.
 
 ```@example domain
 @component function Restrictor(; name, p_int)

docs/src/tutorials/ode_modeling.md

@@ -327,7 +327,7 @@ plot(solve(prob))
 
 More on this topic may be found in [Composing Models and Building Reusable Components](@ref acausal).
 
-## Inital Guess
+## Initial Guess
 
 It is often a good idea to specify reasonable values for the initial state and the
 parameters of a model component. Then, these do not have to be explicitly specified when constructing the `ODEProblem`.
@@ -347,7 +347,7 @@ end
 ```
 
 While defining the model `UnitstepFOLFactory`, an initial guess of 0.0 is assigned to `x(t)` and 1.0 to `τ`.
-Additionaly, these initial guesses can be modified while creating instances of `UnitstepFOLFactory` by passing arguements.
+Additionally, these initial guesses can be modified while creating instances of `UnitstepFOLFactory` by passing arguments.
 
 ```@example ode2
 @named fol = UnitstepFOLFactory(; x = 0.1)

ext/MTKBifurcationKitExt.jl

@@ -20,7 +20,7 @@ struct ObservableRecordFromSolution{S, T}
     param_end_idxs::Int64
     # The index (in subs_vals) that contain the bifurcation parameter.
     bif_par_idx::Int64
-    # A Vector of pairs (Symbolic => value) with teh default values of all system variables and parameters.
+    # A Vector of pairs (Symbolic => value) with the default values of all system variables and parameters.
     subs_vals::T
 
     function ObservableRecordFromSolution(nsys::NonlinearSystem,
@@ -34,17 +34,17 @@ struct ObservableRecordFromSolution{S, T}
         param_end_idxs = state_end_idxs + length(parameters(nsys))
 
         bif_par_idx = state_end_idxs + bif_idx
-        # Gets the (base) substitution values for states. 
+        # Gets the (base) substitution values for states.
         subs_vals_states = Pair.(states(nsys), u0_vals)
-        # Gets the (base) substitution values for parameters. 
+        # Gets the (base) substitution values for parameters.
         subs_vals_params = Pair.(parameters(nsys), p_vals)
-        # Gets the (base) substitution values for observables. 
+        # Gets the (base) substitution values for observables.
         subs_vals_obs = [obs.lhs => substitute(obs.rhs,
             [subs_vals_states; subs_vals_params]) for obs in observed(nsys)]
-        # Sometimes observables depend on other observables, hence we make a second upate to this vector.
+        # Sometimes observables depend on other observables, hence we make a second update to this vector.
         subs_vals_obs = [obs.lhs => substitute(obs.rhs,
             [subs_vals_states; subs_vals_params; subs_vals_obs]) for obs in observed(nsys)]
-        # During the bifurcation process, teh value of some states, parameters, and observables may vary (and are calculated in each step). Those that are not are stored in this vector
+        # During the bifurcation process, the value of some states, parameters, and observables may vary (and are calculated in each step). Those that are not are stored in this vector
         subs_vals = [subs_vals_states; subs_vals_params; subs_vals_obs]
 
         param_end_idxs = state_end_idxs + length(parameters(nsys))
@@ -136,7 +136,7 @@ function BifurcationKit.BifurcationProblem(osys::ODESystem, args...; kwargs...)
     nsys = NonlinearSystem([0 ~ eq.rhs for eq in equations(osys)],
         states(osys),
         parameters(osys);
-        name = osys.name)
+        name = nameof(osys))
     return BifurcationKit.BifurcationProblem(nsys, args...; kwargs...)
 end