Merge branch 'master' into careful-event-affects

Author: BenChung

.github/workflows/Documentation.yml

@@ -31,8 +31,8 @@ jobs:
           JULIA_DEBUG: "Documenter"
         run: DISPLAY=:0 xvfb-run -s '-screen 0 1024x768x24' julia --project=docs/ --code-coverage=user docs/make.jl
       - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v4
+      - uses: codecov/codecov-action@v5
         with:
-          file: lcov.info
+          files: lcov.info
           token: ${{ secrets.CODECOV_TOKEN }}
           fail_ci_if_error: true

.github/workflows/Downstream.yml

@@ -68,8 +68,8 @@ jobs:
             exit(0)  # Exit immediately, as a success
           end
       - uses: julia-actions/julia-processcoverage@v1
-      - uses: codecov/codecov-action@v4
+      - uses: codecov/codecov-action@v5
         with:
-          file: lcov.info
+          files: lcov.info
           token: ${{ secrets.CODECOV_TOKEN }}
-          fail_ci_if_error: true
+          fail_ci_if_error: false

.github/workflows/Tests.yml

@@ -32,6 +32,7 @@ jobs:
         group:
           - InterfaceI
           - InterfaceII
+          - Initialization
           - SymbolicIndexingInterface
           - Extended
           - Extensions

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 = "9.50.0"
+version = "9.54.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -64,6 +64,7 @@ BifurcationKit = "0f109fa4-8a5d-4b75-95aa-f515264e7665"
 ChainRulesCore = "d360d2e6-b24c-11e9-a2a3-2a2ae2dbcce4"
 DeepDiffs = "ab62b9b5-e342-54a8-a765-a90f495de1a6"
 HomotopyContinuation = "f213a82b-91d6-5c5d-acf7-10f1c761b327"
+InfiniteOpt = "20393b10-9daf-11e9-18c9-8db751c92c57"
 LabelledArrays = "2ee39098-c373-598a-b85f-a56591580800"
 
 [extensions]
@@ -72,6 +73,7 @@ MTKChainRulesCoreExt = "ChainRulesCore"
 MTKDeepDiffsExt = "DeepDiffs"
 MTKHomotopyContinuationExt = "HomotopyContinuation"
 MTKLabelledArraysExt = "LabelledArrays"
+MTKInfiniteOptExt = "InfiniteOpt"
 
 [compat]
 AbstractTrees = "0.3, 0.4"
@@ -104,6 +106,7 @@ FunctionWrappers = "1.1"
 FunctionWrappersWrappers = "0.1"
 Graphs = "1.5.2"
 HomotopyContinuation = "2.11"
+InfiniteOpt = "0.5"
 InteractiveUtils = "1"
 JuliaFormatter = "1.0.47"
 JumpProcesses = "9.13.1"
@@ -123,17 +126,17 @@ REPL = "1"
 RecursiveArrayTools = "3.26"
 Reexport = "0.2, 1"
 RuntimeGeneratedFunctions = "0.5.9"
-SciMLBase = "2.57.1"
+SciMLBase = "2.64"
 SciMLStructures = "1.0"
 Serialization = "1"
 Setfield = "0.7, 0.8, 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 = "0.3.31"
+SymbolicIndexingInterface = "0.3.35"
 SymbolicUtils = "3.7"
-Symbolics = "6.15.4"
+Symbolics = "6.19"
 URIs = "1"
 UnPack = "0.1, 1.0"
 Unitful = "1.1"

docs/Project.toml

@@ -33,8 +33,8 @@ DynamicQuantities = "^0.11.2, 0.12, 1"
 ModelingToolkit = "8.33, 9"
 NonlinearSolve = "3, 4"
 Optim = "1.7"
-Optimization = "3.9"
-OptimizationOptimJL = "0.1"
+Optimization = "3.9, 4"
+OptimizationOptimJL = "0.1, 0.4"
 OrdinaryDiffEq = "6.31"
 Plots = "1.36"
 SciMLStructures = "1.1"

docs/src/basics/FAQ.md

@@ -82,6 +82,16 @@ parameter_index(sys, sym)
 Note that while the variable index will be an integer, the parameter index is a struct of
 type `ParameterIndex` whose internals should not be relied upon.
 
+## Can I index with strings?
+
+Strings are not considered symbolic variables, and thus cannot directly be used for symbolic
+indexing. However, ModelingToolkit does provide a method to parse the string representation of
+a variable, given the system in which that variable exists.
+
+```@docs
+ModelingToolkit.parse_variable
+```
+
 ## Transforming value maps to arrays
 
 ModelingToolkit.jl allows (and recommends) input maps like `[x => 2.0, y => 3.0]`

docs/src/basics/Variable_metadata.md

@@ -86,6 +86,44 @@ hasbounds(u)
 getbounds(u)
 ```
 
+Bounds can also be specified for array variables. A scalar array bound is applied to each
+element of the array. A bound may also be specified as an array, in which case the size of
+the array must match the size of the symbolic variable.
+
+```@example metadata
+@variables x[1:2, 1:2] [bounds = (-1, 1)]
+hasbounds(x)
+```
+
+```@example metadata
+getbounds(x)
+```
+
+```@example metadata
+getbounds(x[1, 1])
+```
+
+```@example metadata
+getbounds(x[1:2, 1])
+```
+
+```@example metadata
+@variables x[1:2] [bounds = (-Inf, [1.0, Inf])]
+hasbounds(x)
+```
+
+```@example metadata
+getbounds(x)
+```
+
+```@example metadata
+getbounds(x[2])
+```
+
+```@example metadata
+hasbounds(x[2])
+```
+
 ## Guess
 
 Specify an initial guess for custom initial conditions of an `ODESystem`.

docs/src/examples/higher_order.md

@@ -3,7 +3,7 @@
 ModelingToolkit has a system for transformations of mathematical
 systems. These transformations allow for symbolically changing
 the representation of the model to problems that are easier to
-numerically solve. One simple to demonstrate transformation is the
+numerically solve. One simple to demonstrate transformation, is
 `structural_simplify`, which does a lot of tricks, one being the
 transformation that turns an Nth order ODE into N
 coupled 1st order ODEs.
@@ -15,16 +15,28 @@ We utilize the derivative operator twice here to define the second order:
 using ModelingToolkit, OrdinaryDiffEq
 using ModelingToolkit: t_nounits as t, D_nounits as D
 
-@parameters σ ρ β
-@variables x(t) y(t) z(t)
-
-eqs = [D(D(x)) ~ σ * (y - x),
-    D(y) ~ x * (ρ - z) - y,
-    D(z) ~ x * y - β * z]
-
-@named sys = ODESystem(eqs, t)
+@mtkmodel SECOND_ORDER begin
+    @parameters begin
+        σ = 28.0
+        ρ = 10.0
+        β = 8 / 3
+    end
+    @variables begin
+        x(t) = 1.0
+        y(t) = 0.0
+        z(t) = 0.0
+    end
+    @equations begin
+        D(D(x)) ~ σ * (y - x)
+        D(y) ~ x * (ρ - z) - y
+        D(z) ~ x * y - β * z
+    end
+end
+@mtkbuild sys = SECOND_ORDER()
 ```
 
+The second order ODE has been automatically transformed to two first order ODEs.
+
 Note that we could've used an alternative syntax for 2nd order, i.e.
 `D = Differential(t)^2` and then `D(x)` would be the second derivative,
 and this syntax extends to `N`-th order. Also, we can use `*` or `∘` to compose
@@ -33,28 +45,17 @@ and this syntax extends to `N`-th order. Also, we can use `*` or `∘` to compos
 Now let's transform this into the `ODESystem` of first order components.
 We do this by calling `structural_simplify`:
 
-```@example orderlowering
-sys = structural_simplify(sys)
-```
-
 Now we can directly numerically solve the lowered system. Note that,
 following the original problem, the solution requires knowing the
-initial condition for `x'`, and thus we include that in our input
-specification:
+initial condition for both `x` and `D(x)`.
+The former already got assigned a default value in the `@mtkmodel`,
+but we still have to provide a value for the latter.
 
 ```@example orderlowering
-u0 = [D(x) => 2.0,
-    x => 1.0,
-    y => 0.0,
-    z => 0.0]
-
-p = [σ => 28.0,
-    ρ => 10.0,
-    β => 8 / 3]
-
+u0 = [D(sys.x) => 2.0]
 tspan = (0.0, 100.0)
-prob = ODEProblem(sys, u0, tspan, p, jac = true)
+prob = ODEProblem(sys, u0, tspan, [], jac = true)
 sol = solve(prob, Tsit5())
-using Plots;
-plot(sol, idxs = (x, y));
+using Plots
+plot(sol, idxs = (sys.x, sys.y))
 ```

docs/src/examples/perturbation.md

@@ -39,7 +39,8 @@ eqs_pert = taylor_coeff(eq_pert, ϵ, 0:2)
 !!! note
 
     The 0-th order equation can be solved analytically, but ModelingToolkit does currently not feature automatic analytical solution of ODEs, so we proceed with solving it numerically.
-    These are the ODEs we want to solve. Now construct an `ODESystem`, which automatically inserts dummy derivatives for the velocities:
+
+These are the ODEs we want to solve. Now construct an `ODESystem`, which automatically inserts dummy derivatives for the velocities:
 
 ```@example perturbation
 @mtkbuild sys = ODESystem(eqs_pert, t)

docs/src/tutorials/initialization.md

@@ -113,7 +113,7 @@ the `initialization_eqs` keyword argument, for example:
 
 ```@example init
 prob = ODEProblem(pend, [x => 1], (0.0, 1.5), [g => 1], guesses = [λ => 0, y => 1],
-    initialization_eqs = [y ~ 1])
+    initialization_eqs = [y ~ 0])
 sol = solve(prob, Rodas5P())
 plot(sol, idxs = (x, y))
 ```