Merge branch 'master' into compathelper/new_version/2024-09-21-00-22-18-420-00730187477

Author: ChrisRackauckas

.github/workflows/Documentation.yml

@@ -20,7 +20,7 @@ jobs:
       - uses: actions/checkout@v4
       - uses: julia-actions/setup-julia@latest
         with:
-          version: '1'
+          version: 'lts'
       - run: sudo apt-get update && sudo apt-get install -y xorg-dev mesa-utils xvfb libgl1 freeglut3-dev libxrandr-dev libxinerama-dev libxcursor-dev libxi-dev libxext-dev
       - name: Install dependencies
         run: DISPLAY=:0 xvfb-run -s '-screen 0 1024x768x24' julia --project=docs/ -e 'using Pkg; Pkg.develop(PackageSpec(path=pwd())); Pkg.instantiate()'

.github/workflows/Tests.yml

@@ -25,6 +25,10 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
+        version:
+          - "1"
+          - "lts"
+          - "pre"
         group:
           - InterfaceI
           - InterfaceII
@@ -35,5 +39,6 @@ jobs:
           - RegressionI
     uses: "SciML/.github/.github/workflows/tests.yml@v1"
     with:
+      julia-version: "${{ matrix.version }}"
       group: "${{ matrix.group }}"
     secrets: "inherit"

Project.toml

@@ -1,13 +1,14 @@
 name = "ModelingToolkit"
 uuid = "961ee093-0014-501f-94e3-6117800e7a78"
 authors = ["Yingbo Ma <mayingbo5@gmail.com>", "Chris Rackauckas <accounts@chrisrackauckas.com> and contributors"]
-version = "9.40.0"
+version = "9.50.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
 ArrayInterface = "4fba245c-0d91-5ea0-9b3e-6abc04ee57a9"
 BlockArrays = "8e7c35d0-a365-5155-bbbb-fb81a777f24e"
 Combinatorics = "861a8166-3701-5b0c-9a16-15d98fcdc6aa"
+CommonSolve = "38540f10-b2f7-11e9-35d8-d573e4eb0ff2"
 Compat = "34da2185-b29b-5c13-b0c7-acf172513d20"
 ConstructionBase = "187b0558-2788-49d3-abe0-74a17ed4e7c9"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
@@ -20,10 +21,12 @@ Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 DocStringExtensions = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
 DomainSets = "5b8099bc-c8ec-5219-889f-1d9e522a28bf"
 DynamicQuantities = "06fc5a27-2a28-4c7c-a15d-362465fb6821"
+EnumX = "4e289a0a-7415-4d19-859d-a7e5c4648b56"
 ExprTools = "e2ba6199-217a-4e67-a87a-7c52f15ade04"
 Expronicon = "6b7a57c9-7cc1-4fdf-b7f5-e857abae3636"
 FindFirstFunctions = "64ca27bc-2ba2-4a57-88aa-44e436879224"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
+FunctionWrappers = "069b7b12-0de2-55c6-9aab-29f3d0a68a2e"
 FunctionWrappersWrappers = "77dc65aa-8811-40c2-897b-53d922fa7daf"
 Graphs = "86223c79-3864-5bf0-83f7-82e725a168b6"
 InteractiveUtils = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
@@ -35,6 +38,7 @@ LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MLStyle = "d8e11817-5142-5d16-987a-aa16d5891078"
 NaNMath = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
 NonlinearSolve = "8913a72c-1f9b-4ce2-8d82-65094dcecaec"
+OffsetArrays = "6fe1bfb0-de20-5000-8ca7-80f57d26f881"
 OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
 PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
 RecursiveArrayTools = "731186ca-8d62-57ce-b412-fbd966d074cd"
@@ -59,40 +63,47 @@ Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DeepDiffs = "ab62b9b5-e342-54a8-a765-a90f495de1a6"
+HomotopyContinuation = "f213a82b-91d6-5c5d-acf7-10f1c761b327"
 LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 
 [extensions]
 MTKBifurcationKitExt = "BifurcationKit"
 MTKChainRulesCoreExt = "ChainRulesCore"
 MTKDeepDiffsExt = "DeepDiffs"
+MTKHomotopyContinuationExt = "HomotopyContinuation"
 MTKLabelledArraysExt = "LabelledArrays"
 
 [compat]
 AbstractTrees = "0.3, 0.4"
 ArrayInterface = "6, 7"
-BifurcationKit = "0.3"
+BifurcationKit = "0.4"
 BlockArrays = "1.1"
 ChainRulesCore = "1"
 Combinatorics = "1"
+CommonSolve = "0.2.4"
 Compat = "3.42, 4"
 ConstructionBase = "1"
+DataInterpolations = "6.4"
 DataStructures = "0.17, 0.18"
 DeepDiffs = "1"
-DiffEqBase = "6.103.0"
-DiffEqCallbacks = "2.16, 3"
+DiffEqBase = "6.157"
+DiffEqCallbacks = "2.16, 3, 4"
 DiffEqNoiseProcess = "5"
 DiffRules = "0.1, 1.0"
 Distributed = "1"
 Distributions = "0.23, 0.24, 0.25"
 DocStringExtensions = "0.7, 0.8, 0.9"
 DomainSets = "0.6, 0.7"
 DynamicQuantities = "^0.11.2, 0.12, 0.13, 1"
+EnumX = "1.0.4"
 ExprTools = "0.1.10"
 Expronicon = "0.8"
 FindFirstFunctions = "1"
 ForwardDiff = "0.10.3"
+FunctionWrappers = "1.1"
 FunctionWrappersWrappers = "0.1"
 Graphs = "1.5.2"
+HomotopyContinuation = "2.11"
 InteractiveUtils = "1"
 JuliaFormatter = "1.0.47"
 JumpProcesses = "9.13.1"
@@ -102,24 +113,27 @@ Libdl = "1"
 LinearAlgebra = "1"
 MLStyle = "0.4.17"
 NaNMath = "0.3, 1"
-NonlinearSolve = "3.14"
+NonlinearSolve = "3.14, 4"
+OffsetArrays = "1"
 OrderedCollections = "1"
 OrdinaryDiffEq = "6.82.0"
+OrdinaryDiffEqCore = "1.7.0"
 PrecompileTools = "1"
+REPL = "1"
 RecursiveArrayTools = "3.26"
 Reexport = "0.2, 1"
 RuntimeGeneratedFunctions = "0.5.9"
-SciMLBase = "2.52.1"
+SciMLBase = "2.57.1"
 SciMLStructures = "1.0"
 Serialization = "1"
 Setfield = "0.7, 0.8, 1"
-SimpleNonlinearSolve = "0.1.0, 1"
+SimpleNonlinearSolve = "0.1.0, 1, 2"
 SparseArrays = "1"
 SpecialFunctions = "0.7, 0.8, 0.9, 0.10, 1.0, 2"
 StaticArrays = "0.10, 0.11, 0.12, 1.0"
-SymbolicIndexingInterface = "0.3.29"
-SymbolicUtils = "3.2"
-Symbolics = "6.3"
+SymbolicIndexingInterface = "0.3.35"
+SymbolicUtils = "3.7"
+Symbolics = "6.15.4"
 URIs = "1"
 UnPack = "0.1, 1.0"
 Unitful = "1.1"
@@ -129,6 +143,7 @@ julia = "1.9"
 AmplNLWriter = "7c4d4715-977e-5154-bfe0-e096adeac482"
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 ControlSystemsBase = "aaaaaaaa-a6ca-5380-bf3e-84a91bcd477e"
+DataInterpolations = "82cc6244-b520-54b8-b5a6-8a565e85f1d0"
 DeepDiffs = "ab62b9b5-e342-54a8-a765-a90f495de1a6"
 DelayDiffEq = "bcd4f6db-9728-5f36-b5f7-82caef46ccdb"
 ForwardDiff = "f6369f11-7733-5829-9624-2563aa707210"
@@ -141,7 +156,9 @@ Optimization = "7f7a1694-90dd-40f0-9382-eb1efda571ba"
 OptimizationMOI = "fd9f6733-72f4-499f-8506-86b2bdd0dea1"
 OptimizationOptimJL = "36348300-93cb-4f02-beb5-3c3902f8871e"
 OrdinaryDiffEq = "1dea7af3-3e70-54e6-95c3-0bf5283fa5ed"
+OrdinaryDiffEqCore = "bbf590c4-e513-4bbe-9b18-05decba2e5d8"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+REPL = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 ReferenceTests = "324d217c-45ce-50fc-942e-d289b448e8cf"
 SafeTestsets = "1bc83da4-3b8d-516f-aca4-4fe02f6d838f"
@@ -154,4 +171,4 @@ Sundials = "c3572dad-4567-51f8-b174-8c6c989267f4"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 
 [targets]
-test = ["AmplNLWriter", "BenchmarkTools", "ControlSystemsBase", "DelayDiffEq", "NonlinearSolve", "ForwardDiff", "Ipopt", "Ipopt_jll", "ModelingToolkitStandardLibrary", "Optimization", "OptimizationOptimJL", "OptimizationMOI", "OrdinaryDiffEq", "Random", "ReferenceTests", "SafeTestsets", "StableRNGs", "Statistics", "SteadyStateDiffEq", "Test", "StochasticDiffEq", "Sundials", "StochasticDelayDiffEq", "Pkg", "JET"]
+test = ["AmplNLWriter", "BenchmarkTools", "ControlSystemsBase", "DataInterpolations", "DelayDiffEq", "NonlinearSolve", "ForwardDiff", "Ipopt", "Ipopt_jll", "ModelingToolkitStandardLibrary", "Optimization", "OptimizationOptimJL", "OptimizationMOI", "OrdinaryDiffEq", "OrdinaryDiffEqCore", "REPL", "Random", "ReferenceTests", "SafeTestsets", "StableRNGs", "Statistics", "SteadyStateDiffEq", "Test", "StochasticDiffEq", "Sundials", "StochasticDelayDiffEq", "Pkg", "JET"]

docs/Project.toml

@@ -1,6 +1,7 @@
 [deps]
 BenchmarkTools = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
 BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
+DataInterpolations = "82cc6244-b520-54b8-b5a6-8a565e85f1d0"
 DifferentialEquations = "0c46a032-eb83-5123-abaf-570d42b7fbaa"
 Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
@@ -22,15 +23,16 @@ Unitful = "1986cc42-f94f-5a68-af5c-568840ba703d"
 
 [compat]
 BenchmarkTools = "1.3"
-BifurcationKit = "0.3"
+BifurcationKit = "0.4"
+DataInterpolations = "6.5"
 DifferentialEquations = "7.6"
 Distributions = "0.25"
 Documenter = "1"
 DynamicQuantities = "^0.11.2, 0.12, 1"
 ModelingToolkit = "8.33, 9"
-NonlinearSolve = "3"
+NonlinearSolve = "3, 4"
 Optim = "1.7"
-Optimization = "3.9"
+Optimization = "3.9, 4"
 OptimizationOptimJL = "0.1, 0.4"
 OrdinaryDiffEq = "6.31"
 Plots = "1.36"

docs/pages.jl

@@ -12,12 +12,12 @@ pages = [
         "tutorials/parameter_identifiability.md",
         "tutorials/bifurcation_diagram_computation.md",
         "tutorials/SampledData.md",
-        "tutorials/domain_connections.md"],
+        "tutorials/domain_connections.md",
+        "tutorials/callable_params.md"],
     "Examples" => Any[
         "Basic Examples" => Any["examples/higher_order.md",
             "examples/spring_mass.md",
             "examples/modelingtoolkitize_index_reduction.md",
-            "examples/parsing.md",
             "examples/remake.md"],
         "Advanced Examples" => Any["examples/tearing_parallelism.md",
             "examples/sparse_jacobians.md",

docs/src/basics/AbstractSystem.md

@@ -63,6 +63,7 @@ Optionally, a system could have:
   - `get_defaults(sys)`: A `Dict` that maps variables into their default values
     for the current-level system.
   - `get_noiseeqs(sys)`: Noise equations of the current-level system.
+  - `get_description(sys)`: A string that describes what a system represents.
   - `get_metadata(sys)`: Any metadata about the system or its origin to be used by downstream packages.
 
 Note that if you know a system is an `AbstractTimeDependentSystem` you could use `get_iv` to get the

docs/src/basics/FAQ.md

@@ -244,3 +244,62 @@ D = Differential(x)
 @variables y(x)
 @named sys = ODESystem([D(y) ~ x], x)
 ```
+
+## Ordering of tunable parameters
+
+Tunable parameters are floating point parameters, not used in callbacks and not marked with `tunable = false` in their metadata. These are expected to be used with AD
+and optimization libraries. As such, they are stored together in one `Vector{T}`. To obtain the ordering of tunable parameters in this buffer, use:
+
+```@docs
+tunable_parameters
+```
+
+If you have an array in which a particular dimension is in the order of tunable parameters (e.g. the jacobian with respect to tunables) then that dimension of the
+array can be reordered into the required permutation using the symbolic variables:
+
+```@docs
+reorder_dimension_by_tunables!
+reorder_dimension_by_tunables
+```
+
+For example:
+
+```@example reorder
+using ModelingToolkit
+
+@parameters p q[1:3] r[1:2, 1:2]
+
+@named sys = ODESystem(Equation[], ModelingToolkit.t_nounits, [], [p, q, r])
+sys = complete(sys)
+```
+
+The canonicalized tunables portion of `MTKParameters` will be in the order of tunables:
+
+```@example reorder
+using SciMLStructures: canonicalize, Tunable
+
+ps = MTKParameters(sys, [p => 1.0, q => [2.0, 3.0, 4.0], r => [5.0 6.0; 7.0 8.0]])
+arr = canonicalize(Tunable(), ps)[1]
+```
+
+We can reorder this to contain the value for `p`, then all values for `q`, then for `r` using:
+
+```@example reorder
+reorder_dimension_by_tunables(sys, arr, [p, q, r])
+```
+
+This also works with interleaved subarrays of symbolics:
+
+```@example reorder
+reorder_dimension_by_tunables(sys, arr, [q[1], r[1, :], q[2], r[2, :], q[3], p])
+```
+
+And arbitrary dimensions of higher dimensional arrays:
+
+```@example reorder
+highdimarr = stack([i * arr for i in 1:5]; dims = 1)
+```
+
+```@example reorder
+reorder_dimension_by_tunables(sys, highdimarr, [q[1:2], r[1, :], q[3], r[2, :], p]; dim = 2)
+```

docs/src/basics/InputOutput.md

@@ -55,7 +55,6 @@ We can inspect the state realization chosen by MTK
 x_sym
 ```
 
-as expected, `x` is chosen as the state variable.
 as expected, `x` is chosen as the state variable.
 
 ```@example inputoutput