Merge branch 'master' into myb/strong_alias

Author: YingboMa

.github/workflows/Documentation.yml

@@ -21,4 +21,8 @@ jobs:
         env:
           GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }} # For authentication with GitHub Actions token
           DOCUMENTER_KEY: ${{ secrets.DOCUMENTER_KEY }} # For authentication with SSH deploy key
-        run: julia --project=docs/ docs/make.jl
+        run: julia --project=docs/ --code-coverage=user docs/make.jl
+      - uses: julia-actions/julia-processcoverage@v1
+      - uses: codecov/codecov-action@v1
+        with:
+          file: lcov.info

.github/workflows/FormatCheck.yml

@@ -32,7 +32,7 @@ jobs:
       - name: Format check
         run: |
           julia -e '
-          out = Cmd(`git diff --name-only`) |> read |> String
+          out = Cmd(`git diff`) |> read |> String
           if out == ""
               exit(0)
           else

.github/workflows/Invalidations.yml

@@ -0,0 +1,40 @@
+name: Invalidations
+
+on:
+  pull_request:
+
+concurrency:
+  # Skip intermediate builds: always.
+  # Cancel intermediate builds: always.
+  group: ${{ github.workflow }}-${{ github.ref }}
+  cancel-in-progress: true
+
+jobs:
+  evaluate:
+    # Only run on PRs to the default branch.
+    # In the PR trigger above branches can be specified only explicitly whereas this check should work for master, main, or any other default branch
+    if: github.base_ref == github.event.repository.default_branch
+    runs-on: ubuntu-latest
+    steps:
+    - uses: julia-actions/setup-julia@v1
+      with:
+        version: '1'
+    - uses: actions/checkout@v3
+    - uses: julia-actions/julia-buildpkg@v1
+    - uses: julia-actions/julia-invalidations@v1
+      id: invs_pr
+
+    - uses: actions/checkout@v3
+      with:
+        ref: ${{ github.event.repository.default_branch }}
+    - uses: julia-actions/julia-buildpkg@v1
+    - uses: julia-actions/julia-invalidations@v1
+      id: invs_default
+    
+    - name: Report invalidation counts
+      run: |
+        echo "Invalidations on default branch: ${{ steps.invs_default.outputs.total }} (${{ steps.invs_default.outputs.deps }} via deps)" >> $GITHUB_STEP_SUMMARY
+        echo "This branch: ${{ steps.invs_pr.outputs.total }} (${{ steps.invs_pr.outputs.deps }} via deps)" >> $GITHUB_STEP_SUMMARY
+    - name: Check if the PR does increase number of invalidations
+      if: steps.invs_pr.outputs.total > steps.invs_default.outputs.total
+      run: exit 1

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 = "8.20.0"
+version = "8.21.0"
 
 [deps]
 AbstractTrees = "1520ce14-60c1-5f80-bbc7-55ef81b5835c"
@@ -50,7 +50,7 @@ ArrayInterfaceCore = "0.1.1"
 Combinatorics = "1"
 ConstructionBase = "1"
 DataStructures = "0.17, 0.18"
-DiffEqBase = "6.83.0"
+DiffEqBase = "6.103.0"
 DiffEqCallbacks = "2.16"
 DiffRules = "0.1, 1.0"
 Distributions = "0.23, 0.24, 0.25"
@@ -70,7 +70,7 @@ NonlinearSolve = "0.3.8"
 RecursiveArrayTools = "2.3"
 Reexport = "0.2, 1"
 RuntimeGeneratedFunctions = "0.4.3, 0.5"
-SciMLBase = "1.49"
+SciMLBase = "1.54"
 Setfield = "0.7, 0.8, 1"
 SpecialFunctions = "0.7, 0.8, 0.9, 0.10, 1.0, 2"
 StaticArrays = "0.10, 0.11, 0.12, 1.0"

README.md

@@ -1,10 +1,16 @@
 # ModelingToolkit.jl
 
-[![Github Action CI](https://github.com/SciML/ModelingToolkit.jl/workflows/CI/badge.svg)](https://github.com/SciML/ModelingToolkit.jl/actions)
-[![Coverage Status](https://coveralls.io/repos/github/SciML/ModelingToolkit.jl/badge.svg?branch=master)](https://coveralls.io/github/SciML/ModelingToolkit.jl?branch=master)
+
+[![Join the chat at https://julialang.zulipchat.com #sciml-bridged](https://img.shields.io/static/v1?label=Zulip&message=chat&color=9558b2&labelColor=389826)](https://julialang.zulipchat.com/#narrow/stream/279055-sciml-bridged)
 [![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](http://mtk.sciml.ai/stable/)
-[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](http://mtk.sciml.ai/dev/)
+[![Global Docs](https://img.shields.io/badge/docs-SciML-blue.svg)](https://docs.sciml.ai/dev/modules/ModelingToolkit/)
+
+[![codecov](https://codecov.io/gh/SciML/ModelingToolkit.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/SciML/ModelingToolkit.jl)
+[![Coverage Status](https://coveralls.io/repos/github/SciML/ModelingToolkit.jl/badge.svg?branch=master)](https://coveralls.io/github/SciML/ModelingToolkit.jl?branch=master)
+[![Build Status](https://github.com/SciML/ModelingToolkit.jl/workflows/CI/badge.svg)](https://github.com/SciML/ModelingToolkit.jl/actions?query=workflow%3ACI)
+
 [![ColPrac: Contributor's Guide on Collaborative Practices for Community Packages](https://img.shields.io/badge/ColPrac-Contributor's%20Guide-blueviolet)](https://github.com/SciML/ColPrac)
+[![SciML Code Style](https://img.shields.io/static/v1?label=code%20style&message=SciML&color=9558b2&labelColor=389826)](https://github.com/SciML/SciMLStyle)
 
 ModelingToolkit.jl is a modeling framework for high-performance symbolic-numeric computation
 in scientific computing  and scientific machine learning.
@@ -32,32 +38,33 @@ lower it to a first order system, symbolically generate the Jacobian function
 for the numerical integrator, and solve it.
 
 ```julia
-using ModelingToolkit, OrdinaryDiffEq
+using DifferentialEquations, ModelingToolkit
 
 @parameters t σ ρ β
 @variables x(t) y(t) z(t)
 D = Differential(t)
 
-eqs = [D(D(x)) ~ σ*(y-x),
-       D(y) ~ x*(ρ-z)-y,
-       D(z) ~ x*y - β*z]
+eqs = [D(D(x)) ~ σ * (y - x),
+    D(y) ~ x * (ρ - z) - y,
+    D(z) ~ x * y - β * z]
 
 @named sys = ODESystem(eqs)
-sys = ode_order_lowering(sys)
+sys = structural_simplify(sys)
 
 u0 = [D(x) => 2.0,
-      x => 1.0,
-      y => 0.0,
-      z => 0.0]
-
-p  = [σ => 28.0,
-      ρ => 10.0,
-      β => 8/3]
-
-tspan = (0.0,100.0)
-prob = ODEProblem(sys,u0,tspan,p,jac=true)
-sol = solve(prob,Tsit5())
-using Plots; plot(sol,vars=(x,y))
+    x => 1.0,
+    y => 0.0,
+    z => 0.0]
+
+p = [σ => 28.0,
+    ρ => 10.0,
+    β => 8 / 3]
+
+tspan = (0.0, 100.0)
+prob = ODEProblem(sys, u0, tspan, p, jac = true)
+sol = solve(prob)
+using Plots
+plot(sol, idxs = (x, y))
 ```
 
 ![Lorenz2](https://user-images.githubusercontent.com/1814174/79118645-744eb580-7d5c-11ea-9c37-13c4efd585ca.png)
@@ -69,48 +76,50 @@ interacting Lorenz equations and simulate the resulting Differential-Algebraic
 Equation (DAE):
 
 ```julia
-using ModelingToolkit, OrdinaryDiffEq
+using DifferentialEquations, ModelingToolkit
 
 @parameters t σ ρ β
 @variables x(t) y(t) z(t)
 D = Differential(t)
 
-eqs = [D(x) ~ σ*(y-x),
-       D(y) ~ x*(ρ-z)-y,
-       D(z) ~ x*y - β*z]
+eqs = [D(x) ~ σ * (y - x),
+    D(y) ~ x * (ρ - z) - y,
+    D(z) ~ x * y - β * z]
 
 @named lorenz1 = ODESystem(eqs)
 @named lorenz2 = ODESystem(eqs)
 
 @variables a(t)
 @parameters γ
-connections = [0 ~ lorenz1.x + lorenz2.y + a*γ]
-@named connected = ODESystem(connections,t,[a],[γ],systems=[lorenz1,lorenz2])
+connections = [0 ~ lorenz1.x + lorenz2.y + a * γ]
+@named connected = ODESystem(connections, t, [a], [γ], systems = [lorenz1, lorenz2])
+sys = structural_simplify(connected)
 
 u0 = [lorenz1.x => 1.0,
-      lorenz1.y => 0.0,
-      lorenz1.z => 0.0,
-      lorenz2.x => 0.0,
-      lorenz2.y => 1.0,
-      lorenz2.z => 0.0,
-      a => 2.0]
-
-p  = [lorenz1.σ => 10.0,
-      lorenz1.ρ => 28.0,
-      lorenz1.β => 8/3,
-      lorenz2.σ => 10.0,
-      lorenz2.ρ => 28.0,
-      lorenz2.β => 8/3,
-      γ => 2.0]
-
-tspan = (0.0,100.0)
-prob = ODEProblem(connected,u0,tspan,p)
-sol = solve(prob,Rodas4())
-
-using Plots; plot(sol,vars=(a,lorenz1.x,lorenz2.z))
+    lorenz1.y => 0.0,
+    lorenz1.z => 0.0,
+    lorenz2.x => 0.0,
+    lorenz2.y => 1.0,
+    lorenz2.z => 0.0,
+    a => 2.0]
+
+p = [lorenz1.σ => 10.0,
+    lorenz1.ρ => 28.0,
+    lorenz1.β => 8 / 3,
+    lorenz2.σ => 10.0,
+    lorenz2.ρ => 28.0,
+    lorenz2.β => 8 / 3,
+    γ => 2.0]
+
+tspan = (0.0, 100.0)
+prob = ODEProblem(sys, u0, tspan, p)
+sol = solve(prob)
+
+using Plots
+plot(sol, idxs = (a, lorenz1.x, lorenz2.z))
 ```
 
-![](https://user-images.githubusercontent.com/1814174/110242538-87461780-7f24-11eb-983c-4b2c93cfc909.png)
+![](https://user-images.githubusercontent.com/17304743/187790221-528046c3-dbdb-4853-b977-799596c147f3.png)
 
 # Citation
 If you use ModelingToolkit.jl in your research, please cite [this paper](https://arxiv.org/abs/2103.05244):

docs/make.jl

@@ -2,6 +2,16 @@ using Documenter, ModelingToolkit
 
 include("pages.jl")
 
+mathengine = MathJax3(Dict(:loader => Dict("load" => ["[tex]/require", "[tex]/mathtools"]),
+                           :tex => Dict("inlineMath" => [["\$", "\$"], ["\\(", "\\)"]],
+                                        "packages" => [
+                                            "base",
+                                            "ams",
+                                            "autoload",
+                                            "mathtools",
+                                            "require",
+                                        ])))
+
 makedocs(sitename = "ModelingToolkit.jl",
          authors = "Chris Rackauckas",
          modules = [ModelingToolkit],
@@ -16,6 +26,7 @@ makedocs(sitename = "ModelingToolkit.jl",
          ],
          format = Documenter.HTML(; analytics = "UA-90474609-3",
                                   assets = ["assets/favicon.ico"],
+                                  mathengine,
                                   canonical = "https://mtk.sciml.ai/stable/",
                                   prettyurls = (get(ENV, "CI", nothing) == "true")),
          pages = pages)

docs/src/basics/AbstractSystem.md

@@ -60,6 +60,7 @@ Optionally, a system could have:
 - `get_defaults(sys)`: A `Dict` that maps variables into their default values.
 - `independent_variables(sys)`: The independent variables of a system.
 - `get_noiseeqs(sys)`: Noise equations of the current-level system.
+- `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 
 unique independent variable directly, rather than using `independent_variables(sys)[1]`, which is clunky and may cause problems if `sys` is an `AbstractMultivariateSystem` because there may be more than one independent variable. `AbstractTimeIndependentSystem`s do not have a method `get_iv`, and `independent_variables(sys)` will return a size-zero result for such. For an `AbstractMultivariateSystem`, `get_ivs` is equivalent.

docs/src/basics/Validation.md

@@ -20,10 +20,10 @@ w(t), [unit = "Hz"]
 end)
 
 # Simultaneously set default value (use plain numbers, not quantities)
-@variable x=10 [unit = u"m"]
+@variables x=10 [unit = u"m"]
 
 # Symbolic array: unit applies to all elements
-@variable x[1:3] [unit = u"m"]
+@variables x[1:3] [unit = u"m"]
 ```
 
 Do not use `quantities` such as  `1u"s"`, `1/u"s"` or `u"1/s"` as these will result in errors; instead use `u"s"`, `u"s^-1"`, or `u"s"^-1`. 

docs/src/mtkitize_tutorials/sparse_jacobians.md

@@ -50,7 +50,8 @@ prob = ODEProblem(brusselator_2d_loop,u0,(0.,11.5),p)
 Now let's use `modelingtoolkitize` to generate the symbolic version:
 
 ```@example sparsejac
-sys = modelingtoolkitize(prob)
+sys = modelingtoolkitize(prob);
+nothing # hide
 ```
 
 Now we regenerate the problem using `jac=true` for the analytical Jacobian

src/ModelingToolkit.jl

@@ -167,7 +167,7 @@ export JumpSystem
 export ODEProblem, SDEProblem
 export NonlinearFunction, NonlinearFunctionExpr
 export NonlinearProblem, BlockNonlinearProblem, NonlinearProblemExpr
-export OptimizationProblem, OptimizationProblemExpr
+export OptimizationProblem, OptimizationProblemExpr, constraints
 export AutoModelingToolkit
 export SteadyStateProblem, SteadyStateProblemExpr
 export JumpProblem, DiscreteProblem