Merge branch 'master' into recompile

Author: ChrisRackauckas

.github/workflows/Documentation.yml

@@ -11,7 +11,7 @@ jobs:
   build:
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@latest
         with:
           version: '1'

.github/workflows/Downstream.yml

@@ -31,14 +31,14 @@ jobs:
           - {user: SciML, repo: MethodOfLines.jl, group: DAE}
           - {user: ai4energy, repo: Ai4EComponentLib.jl, group: Downstream}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v1
         with:
           version: ${{ matrix.julia-version }}
           arch: x64
       - uses: julia-actions/julia-buildpkg@latest
       - name: Clone Downstream
-        uses: actions/checkout@v3
+        uses: actions/checkout@v4
         with:
           repository: ${{ matrix.package.user }}/${{ matrix.package.repo }}
           path: downstream

.github/workflows/FormatCheck.yml

@@ -21,7 +21,7 @@ jobs:
         with:
           version: ${{ matrix.julia-version }}
 
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - name: Install JuliaFormatter and format
         # This will use the latest version by default but you can set the version like so:
         #

.github/workflows/Invalidations.yml

@@ -19,12 +19,12 @@ jobs:
     - uses: julia-actions/setup-julia@v1
       with:
         version: '1'
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
     - uses: julia-actions/julia-buildpkg@v1
     - uses: julia-actions/julia-invalidations@v1
       id: invs_pr
 
-    - uses: actions/checkout@v3
+    - uses: actions/checkout@v4
       with:
         ref: ${{ github.event.repository.default_branch }}
     - uses: julia-actions/julia-buildpkg@v1

.github/workflows/ci.yml

@@ -17,7 +17,7 @@ jobs:
           - '1'
           - '1.6'
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@v1
         with:
           version: ${{ matrix.version }}

CONTRIBUTING.md

@@ -1,3 +1,3 @@
   - This repository follows the [SciMLStyle](https://github.com/SciML/SciMLStyle) and the SciML [ColPrac](https://github.com/SciML/ColPrac).
-  - Please run `using JuliaFormatter, ModelingToolkit; format(joinpath(dirname(pathof(ModelingToolkit)), ".."))` before commiting.
+  - Please run `using JuliaFormatter, ModelingToolkit; format(joinpath(dirname(pathof(ModelingToolkit)), ".."))` before committing.
   - Add tests for any new features.

Project.toml

@@ -1,7 +1,7 @@
 name = "ModelingToolkit"
 uuid = "961ee093-0014-501f-94e3-6117800e7a78"
 authors = ["Yingbo Ma <[email protected]>", "Chris Rackauckas <[email protected]> and contributors"]
-version = "8.64.0"
+version = "8.68.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -32,6 +32,7 @@ MLStyle = "d8e11817-5142-5d16-987a-aa16d5891078"
 MacroTools = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
 NaNMath = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
 PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
+OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
 Reexport = "189a3867-3050-52da-a836-e630ba90ab69"
 RuntimeGeneratedFunctions = "7e49a35a-f44a-4d26-94aa-eba1b4ca6b47"
@@ -79,6 +80,7 @@ Latexify = "0.11, 0.12, 0.13, 0.14, 0.15, 0.16"
 MLStyle = "0.4.17"
 MacroTools = "0.5"
 NaNMath = "0.3, 1"
+OrdinaryDiffEq = "6"
 RecursiveArrayTools = "2.3"
 Reexport = "0.2, 1"
 RuntimeGeneratedFunctions = "0.5.9"
@@ -108,7 +110,6 @@ NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
 Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationMOI = "fd9f6733-72f4-499f-8506-86b2bdd0dea1"
 OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
-OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReferenceTests = "324d217c-45ce-50fc-942e-d289b448e8cf"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
@@ -121,4 +122,4 @@ Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["AmplNLWriter", "BenchmarkTools", "ControlSystemsMTK", "NonlinearSolve", "ForwardDiff", "Ipopt", "Ipopt_jll", "ModelingToolkitStandardLibrary", "Optimization", "OptimizationOptimJL", "OptimizationMOI", "OrdinaryDiffEq", "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"]

docs/src/basics/FAQ.md

@@ -120,7 +120,7 @@ We can solve this problem by using the `missing_variable_defaults()` function
 prob = ODEProblem(sys, ModelingToolkit.missing_variable_defaults(sys), (0,1))
 ```
 
-This function provides 0 for the default values, which is a safe assumption for dummy derivatives of most models.  However, the 2nd arument allows for a different default value or values to be used if needed.
+This function provides 0 for the default values, which is a safe assumption for dummy derivatives of most models.  However, the 2nd argument allows for a different default value or values to be used if needed.
 
 ```
 julia> ModelingToolkit.missing_variable_defaults(sys, [1,2,3])

src/ModelingToolkit.jl

@@ -110,7 +110,7 @@ abstract type AbstractOptimizationSystem <: AbstractTimeIndependentSystem end
 
 function independent_variable end
 
-# this has to be included early to deal with depency issues
+# this has to be included early to deal with dependency issues
 include("structural_transformation/bareiss.jl")
 function complete end
 function var_derivative! end

src/bipartite_graph.jl

@@ -618,7 +618,7 @@ Essentially the graph adapter performs two largely orthogonal functions
  1. It pairs an undirected bipartite graph with a matching of the destination vertex.
 
     This matching is used to induce an orientation on the otherwise undirected graph:
-    Matched edges pass from destination to source [source to desination], all other edges
+    Matched edges pass from destination to source [source to destination], all other edges
     pass in the opposite direction.
 
  2. It exposes the graph view obtained by contracting the destination [source] vertices
@@ -632,7 +632,7 @@ graph is acyclic.
 # Hypergraph interpretation
 
 Consider the bipartite graph `B` as the incidence graph of some hypergraph `H`.
-Note that a maching `M` on `B` in the above sense is equivalent to determining
+Note that a matching `M` on `B` in the above sense is equivalent to determining
 an (1,n)-orientation on the hypergraph (i.e. each directed hyperedge has exactly
 one head, but any arbitrary number of tails). In this setting, this is simply
 the graph formed by expanding each directed hyperedge into `n` ordinary edges
@@ -685,7 +685,7 @@ function Base.iterate(c::CMONeighbors{false}, (l, state...))
         r === nothing && return nothing
         # If this is a matched edge, skip it, it's reversed in the induced
         # directed graph. Otherwise, if there is no matching for this destination
-        # edge, also skip it, since it got delted in the contraction.
+        # edge, also skip it, since it got deleted in the contraction.
         vsrc = c.g.matching[r[1]]
         if vsrc === c.v || !isa(vsrc, Int)
             state = (r[2],)